INVESTIGATION OF THE LEVELS OF SPERM-BINDING GENE EXPRESSION IN
FROGS FROM THE GENERA XENOPUS AND LEPIDOBATRACHUS
Kyle Steven Jones
B.S., San Diego State University, 2007
THESIS
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF SCIENCE
in
BIOLOGICAL SCIENCES
(Molecular and Cellular Biology)
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
SPRING
2011
INVESTIGATION OF THE LEVELS OF SPERM-BINDING GENE EXPRESSION IN
FROGS FROM THE GENERA XENOPUS AND LEPIDOBATRACHUS
A Thesis
by
Kyle Steven Jones
Approved by:
__________________________________, Committee Chair
Thomas R. Peavy, Ph.D.
__________________________________, Second Reader
Nicholas Ewing, Ph.D.
__________________________________, Third Reader
Enid T. Gonzalez, Ph.D.
____________________________
Date
ii
Student: Kyle Steven Jones
I certify that this student has met the requirements for format contained in the University
format manual, and that this thesis is suitable for shelving in the Library and credit is to
be awarded for the thesis.
__________________________, Graduate Coordinator
Susanne Lindgren, Ph.D.
Department of Biological Sciences
iii
___________________
Date
Abstract
of
INVESTIGATION OF THE LEVELS OF SPERM-BINDING GENE EXPRESSION IN
FROGS FROM THE GENERA XENOPUS AND LEPIDOBATRACHUS
by
Kyle Steven Jones
Pre-zygotic blocks to fertilization create scenarios where two members of an
interbreeding population are unable to conceive and produce offspring resulting in
reproductive isolation. This inability to naturally produce offspring could be a result of
the failure of sperm binding to the exterior of the female egg. The mammalian oocyte is
surrounded by an extracellular matrix termed the zona pellucida (vitelline envelope in
amphibians) that houses glycoproteins (ZPC) that function to bind sperm in a speciesspecific manner to prevent hybridization. Zebrafish have experienced numerous ZPC
gene duplications creating multiple copies within the genome, albeit non-functional with
regards to sperm-binding. On the other hand, mammals have only one ZPC gene copy
that codes for and functions as the primary sperm-binding protein. Evolutionarily
between these two groups of taxa lie amphibians in which ZPC is also a sperm-binding
protein. Multiple gene copies have been found to be expressed in three species of frogs:
iv
Xenopus laevis, Xenopus borealis, and Lepidobatrachus laevis. The discovery of multiple
ZPC genes has led to further questions as to why multiple copies are expressed and to
what degree. Since determining the function of each ZPC gene would require
considerable effort (purified proteins and sperm binding assays), the focus of these
studies is on the expression level of each gene because it is likely to be informative as to
the functional role the translated protein plays in fertilization. One possibility is a single
ZPC copy is expressed in higher amounts likely rendering it the functional sperm-binding
gene while remaining gene copies play structural roles within the vitelline envelope.
Alternatively, all ZPC genes may be able to bind sperm, and expression of these ZPCs in
the same egg would cause competition for sperm-binding. Competition may have led to
the evolution of binding affinity differences where the gene product with the greatest
affinity for sperm will have a decided advantage for binding. However, the situation
could be a combination of the first two scenarios where multiple genes expressed in high
amounts perform sperm-binding while remaining low expressing gene copies perform
alternative roles. My hypothesis is that Xenopus and Lepidobatrachus ZPC genes are
unequally expressed within their respective ovaries and that orthologous genes show a
similar pattern of expression. Levels of gene expression were determined from ovary
cDNA libraries using quantitative PCR (qPCR) which measures the expression of each
ZPC gene as compared to a reference gene. The reference gene, in this case GAPDH, is
used as a baseline to which all qPCR expression data is normalized. Using qPCR, the
ZPC gene expression profiles were determined for individuals from two closely related
species X. laevis and X. borealis as well as the distant relative L. laevis to investigate if
v
gene copies are expressed in higher amounts relative to others. Through qPCR and
ANOVA statistical hypothesis tests, ZPC genes were found to be unequally expressed in
Xenopus and Lepidobatrachus. Furthermore, phylogenetic evidence suggests X. laevis
and X. borealis ZPC orthologs have maintained a relatively similar level of expression
after their ancestral split. Genes with comparable expression levels may share a common
role with predominantly expressed genes performing as functional sperm-binding
proteins while low expressers may have lost their ability to bind sperm. While precise
functional roles of each ZPC cannot be assigned from this work, the discovery of unequal
expression provides preliminary information for future experimental design aimed at
elucidating the functions of the different ZPC genes.
_______________________, Committee Chair
Thomas R. Peavy, Ph.D.
_______________________
Date
vi
ACKNOWLEDGMENTS
Several individuals have played integral roles leading to the completion of this
work. First, I would like to expresses my sincere thanks to my thesis advisor and mentor
Dr. Tom Peavy. Since I first arrived in Sacramento, he has challenged me in both
research and within the classroom by providing instruction and guidance, but still
allowing me to earn the education I set out to attain. He has invested countless hours
educating me not only on how to navigate my way through the graduate program, but
how to be successful moving forward.
Additionally, Dr. Enid Gonzalez and Dr. Nick Ewing deserve a great deal of
thanks for their participation on my advisory committee. Membership to the committee
requires sacrifice and commitment on their end to provide me with feedback and
direction on how to achieve the best possible outcome in the lab and inside the classroom.
I would also like to thank the faculty and staff of Sacramento State including Dr. Jamie
Kneitel for lending me some of his wisdom on statistics.
This type of graduate program where completion primarily depends on the
amount of effort put forth, at times can seem like a never-ending quest. Shari has been by
my side and always given me the proper perspective and support throughout my
participation in this program and I will always appreciate her for that. Additionally, I
thank all of my life-long friends from Springtown who have maintained strong support of
me in each of educational journeys. Finally, I would like to recognize my parents for all
their hard work to provide the tools and placing me in a position to be successful in
school, work, and life. For their enduring support, I am forever grateful.
vii
TABLE OF CONTENTS
Page
Acknowledgments...................................................................................................... vii
List of Tables .............................................................................................................. ix
List of Figures ............................................................................................................... x
Chapter
1.
INTRODUCTION ..................................................................................................1
Hypothesis....................................................................................................... 19
Objectives ....................................................................................................... 19
Rational for Experimental Design .................................................................. 19
2.
METHODS .......................................................................................................... 22
3.
RESULTS ............................................................................................................ 35
Cloning and Sequencing GAPDH cDNAs ......................................................35
qPCR Primer Design ........................................................................................49
Optimization of Primer Annealing Temperatures ............................................65
Mixed Plasmid PCR Controls ..........................................................................72
Primer Efficiency .............................................................................................74
qPCR Assays to Determine Gene Expression .................................................79
ZPC Phylogenetic Analysis .............................................................................87
4.
DISCUSSION ...................................................................................................... 95
References ................................................................................................................. 105
viii
LIST OF TABLES
Page
Table 1.
Summary of primers used to clone GAPDH from L. laevis
and X. borealis .....................................................................................37
Table 2.
Pairwise comparison of ZPC cDNA sequences ...................................59
Table 3.
Summary of ZPC and GAPDH qPCR primers for L. laevis,
X. laevis, and X. borealis .....................................................................61
Table 4.
qPCR primer efficiency summary .......................................................78
Table 5.
L. laevis ZPC and GAPDH CT values..................................................82
Table 6.
X. laevis ZPC and GAPDH CT values .................................................85
Table 7.
X. borealis ZPC and GAPDH CT values..............................................88
ix
LIST OF FIGURES
Page
Figure 1.
Steps leading to fertilization ..................................................................3
Figure 2.
Structure of the ZPC gene ......................................................................6
Figure 3.
Predicted 3D model of the frog Lepidobatrachus laevis
ZP domain ..............................................................................................8
Figure 4.
MHC and ZP3/ZPC structure...............................................................11
Figure 5.
2D immunoblot of X. laevis and L. laevis vitelline
envelopes (VE).....................................................................................20
Figure 6.
Quantitative PCR master mix set-up....................................................31
Figure 7.
GAPDH protein sequence alignment and primer design .....................36
Figure 8.
Degenerate PCR of the L. laevis GAPDH cDNA ................................39
Figure 9.
Sequence alignment of the middle portion of the L. laevis
and X. laevis GAPDH cDNAs .............................................................40
Figure 10.
Cloning the 3’ end of the L. laevis GAPDH cDNA sequence .............42
Figure 11.
Cloning the 5’ end of the L. laevis GAPDH cDNA sequence .............43
Figure 12.
Degenerate PCR of the X. borealis GAPDH cDNA ............................45
Figure 13.
Sequence alignment of the middle portion of the X. borealis
and X. laevis GAPDH cDNAs .............................................................47
Figure 14.
Cloning the 3’ end of the X. borealis GAPDH cDNA
sequence ...............................................................................................48
Figure 15.
Cloning the 5’ end of the X. borealis GAPDH cDNA
sequence ...............................................................................................50
Figure 16.
Sequence alignment of the X. borealis and X. laevis
GAPDH cDNAs ...................................................................................51
Figure 17.
Sequence alignment of L. laevis ZPC cDNAs .....................................54
x
Figure 18.
Phylogenetic tree of frog ZPC cDNAs ................................................58
Figure 19.
Sequence alignment of X. laevis ZPC cDNAs .....................................63
Figure 20.
Sequence alignment of X. borealis ZPC cDNAs .................................66
Figure 21.
L. laevis ZPC and GAPDH qPCR primer optimization .......................69
Figure 22.
X. laevis ZPC and GAPDH qPCR primer optimization ......................71
Figure 23.
X. borealis ZPC and GAPDH qPCR primer optimization...................73
Figure 24.
Mixed plasmid control PCR.................................................................75
Figure 25.
Representative qPCR primer efficiency plot .......................................76
Figure 26.
L. laevis ZPC expression levels using qPCR .......................................83
Figure 27.
X. laevis ZPC expression levels using qPCR .......................................86
Figure 28.
X. borealis ZPC expression levels using qPCR ...................................89
Figure 29.
ZPC maximum likelihood phylogenetic tree .......................................92
Figure 30.
ZPC neighbor-joining phylogenetic tree ..............................................93
xi
1
Chapter 1
INTRODUCTION
Fertilization involves the fusion of haploid male and female gametes which leads
to the formation of a new diploid organism. This fundamental process of generating new
individuals is crucial to maintaining populations, preserving evolution, and avoids species
extinction. In order to regulate this interaction, mammalian eggs are surrounded by a
thick extracellular matrix called the zona pellucida, while this same structure is termed
the vitelline envelope in amphibians and the chorion in fish. Glycoproteins found in these
extracellular matrices serve as regulators of fertilization. In particular, one glycoprotein
termed ZPC serves as the initial sperm-binding molecule which binds to a
complementary receptor found on the surface of sperm. This sperm-binding interaction
resembles a “lock and key” mechanism to ensure species-specificity and prevent
hybridization with gametes from other species. Mutations that disrupt this lock and key
mechanism would generate instances where the gametes can no longer recognize and
bind to each other thus causing reproductive incompatibility between two individuals.
Infertility is a heterogeneous group of disorders that prevents otherwise healthy
individuals from conceiving and producing offspring. Some factors contributing to failed
reproductive attempts in males include germ cell arrest, sperm autoimmunity, and
reduced sperm quality [1]. The reduction in quality not only describes the sperm’s
inability to reach the egg, but also translates to sperm that are unable to bind with ZPC,
the sperm-binding receptor, present within the zona pellucida and form the lock and key
relationship that triggers subsequent steps toward the generation of a new organism.
2
There is evidence to suggest that male and female reproductive proteins are coevolving with each other such that receptors and ligands acquire mutations that maintain
their compatibility for their binding interaction and thus enable fertilization [2]. However,
mutations that occur to these reproductive proteins in individuals from other populations
of the same species that do not have an opportunity to breed with each other may lead to
instances of infertility (prezygotic block to fertilization) due to the disruption of the lock
and key interaction. As a result, this prezygotic block to fertilization due to failure of
sperm-binding may lead to speciation. Therefore, a more complete understanding of the
early stages where sperm interact with glycoproteins at the surface of the zona pellucida
should provide insight into the evolution of reproductive proteins and build upon current
ideas of infertility and speciation.
Our current understanding is that species-specific binding of sperm to the egg
leads to the triggering of a series of carefully orchestrated events resulting in the
formation of a new organism. The zona pellucida is comprised of glycoproteins ZPA,
ZPB, and ZPC, but sperm must first bind to ZPC before subsequent steps to fertilization
can transpire (Figure 1). Once a single sperm has successfully bound to ZPC present
within the exterior coating of the egg, a vesicle at the tip of the sperm releases its contents
through an exocytotic event called the acrosome reaction. This sperm receptor-ZPC
binding interaction has been shown to require enough points of contact to create a high
affinity bond before the acrosome reaction is possible [3,4]. The released acrosomal
contents, consisting of proteases and glycosidases, facilitate enzymatic hydrolysis of the
extracellular matrix thereby enabling sperm to penetrate the thick barrier and gain access
3
Figure 1. Steps leading to fertilization. The step-by-step mechanism of fertilization in the
mouse begins with (1) the sperm locating the egg; (2) then species-specific binding of the
sperm receptor to ZPC (circled); (3) followed by the triggering of the acrosome reaction;
(4) subsequent penetration through the zona pellucida; and (5) finally fusion of the sperm
with the egg plasma membrane [5].
4
to the egg's plasma membrane. Unfortunately, the identity of the sperm binding receptor
for ZPC is unclear at this point.
The role of ZPC during fertilization is not complete after one sperm penetrates
into the egg. Upon sperm fusion, the egg undergoes a series of events termed the block to
polyspermy which prevents subsequent sperm from penetrating the egg. This block
includes a temporary but fast depolarization of the membrane so as to immediately
electrically repulse additional sperm from fusing [6,7]. The second block is more
permanent but slower and entails an exocytotic release of the egg's cortical granules
(vesicles that reside just below the plasma membrane surface) which contain a
glycosidase and protease that eliminates the sperm binding activity of ZPC [8]. Thus,
prevention of subsequent sperm binding prevents polyspermic fertilization which is very
important in most species since there are deleterious consequences of having more than
one sperm fuse with the egg pronucleus such as abnormal development or embryo
termination [9,8].
The focus of my studies is to further understand the role of the ZPC glycoprotein
with respect to fertilization and speciation in vertebrates since homologues of ZPC are
found in the egg envelope from all vertebrates examined to date (e.g. amphibian vitelline
envelope). Much of our knowledge about the structure and function of the zona pellucida
genes, in particular ZPC, comes from studies in mice, but it is unclear as to how much is
translatable to other species. For example, the sperm-binding capability of ZPC was
demonstrated in mice using sperm binding assays to covalently-linked purified
preparations of zona pellucida glycoproteins [10]. Furthermore, the location of where
5
acrosome intact sperm bind on the ZPC glycoprotein was shown to be towards the Cterminus of the ZPC when portions of the glycoprotein were tested [11,12]. These studies
have been extended into humans by using baculovirus expression truncations of human
ZPC during sperm binding assays which demonstrated that the final 156 amino acids of
the C-terminal region was the key region [13]. As for non-mammalian species, it has
been shown that the ZPC glycoprotein found in the vitelline envelope of the frog Xenopus
laevis also serves as the sperm binding protein [14,15,16]. However, fish ZPC genes do
not serve a functional role in sperm binding since sperm bypass the comparable zona
pellucida-like structure, termed the chorion, by entering through a small pore called the
micropyle [17,18].
Although the sperm-binding location is of prime importance, ZPC proteins
possess other regions that are essential for the proper folding, secretion, and incorporation
of ZPC into the growing extracellular matrix during oogenesis (Figure 2). Specifically,
the N-terminus of mouse ZPC is comprised of a 22 amino acid signal peptide that targets
the protein for the secretory pathway whereas the X. laevis ZPC signal peptide is only
slightly shorter at 21 amino acids [19,14]. Before secretion into the extracellular space,
the signal peptide leads ZPC to the rough endoplasmic reticulum and golgi apparatus
where it is post-translationally modified. After passage through the golgi, glycosylated
ZPC is tethered internally to the plasma membrane vesicle by hydrophobic residues
comprising a transmembrane domain [14]. Mutations in the transmembrane domain do
not inhibit the secretion of ZPC, but rather the assembly of the zona pellucida is
completely abolished making this region critical for its incorporation into the growing
6
Signal
Peptide
5’
ZP Domain
TM
Domain
Sperm Binding
xxxxxxxxxxxxxxx
3’
Furin
Cleavage
Figure 2. Structure of the ZPC gene. The 5’ end codes for the signal peptide (white dots)
followed by the ZP domain (diagonal stripes). The putative sperm binding activity
(xxxxx) occurs after the ZP domain upstream of a furin cleavage site (checkers).
Hydrophobic amino acids are coded for towards the 3’ end that comprises the
transmembrane domain (horizontal stripes).
7
matrix [20]. Upon fusion with the plasma membrane during secretion, ZPC becomes
exposed to the egg’s exterior. The tether connecting the transmembrane domain with the
remaining portions of ZPC is cleaved upstream (extracellular space) of the
transmembrane domain at the furin-like cleavage site (mouse Lys371 – Arg372) by the
calcium-dependent serine endoprotease furin [21,14]. The cleavage from the
transmembrane domain releases ZPC from the membrane allowing for incorporation into
the fibrillar structure through subunit interactions at the ZP domain [22].
The ZP domain is approximately 260 amino acids in length and functions in the
polymerization of the growing extracellular matrix and orients ZPC in a position where it
is capable of binding sperm. Eight cysteine residues, highly conserved throughout
evolution, form four disulfide bonds within the ZP domain which are critical in
maintaining the structure and assembly of the zona pellucida (Figure 3). There are other
proteins that possess a ZP domain such as α-tectorin and uromodulin. These ZP domain
containing proteins also are found to make up extracellular matrices in other tissues (e.g.
ear membranes or kidney tubule lining, respectively) but do not play a role in
fertilization. For example, α-tectorin forms an extracellular matrix within the ear to aid in
hearing [23,24]. The presence and location of cysteine residues within the ZP domain is
exceedingly important as demonstrated by point mutations that alter the cysteines within
the α-tectorin ZP domain thereby resulting in the inability to formulate a matrix and
subsequent hearing loss. In essence, the loss of ZP domain disulfide bond structures alters
the structure leading to loss of function [24]. With respect to ZPC, mutations that alter the
three-dimensional structure of the ZP domain such as disulfide bonds are likely to inhibit
8
N-terminus
Cys106
Cys138
Cys199
Cys158
C-terminus
Figure 3. Predicted 3D model of the frog Lepidobatrachus laevis ZP domain. 102 amino
acids of the predicted N-terminal region of the ZP domain from the frog L. laevis ZPC
(Llzpc.4) modeled with Swiss-Model using the mouse ZPC crystal structure (PDB:
3D4G) as a template (resolution of 2.3 Å). Disulfide bonds are predicted to form between
Cys138 and Cys158 and between Cys106 and Cys199 in the enlarged image. Arrows
point toward the C-terminus.
9
the assembly of the zona pellucida and contribute to instances of infertility. As for our
current model of the structure of ZPC, only 102 amino acids from the N-terminal region
of the ZP domain from mouse ZPC has ever been crystallized and structurally
determined, so the exact folding pattern and spatial orientation of each ZPC residue is not
known [25].
In addition, glycosylation of ZPC during the secretion process is also critical for
its sperm-binding activity. A combination of N- and O-linked oligosaccharides are added
to the ZPC polypeptide within the golgi, and it is thought that the O-linked sugars added
near the C-terminal region are the most critical for species-specific sperm-binding
activity [26]. In particular, terminal N-acetylglucosamine and fucose residues seem to be
of the most importance since ZPC sperm-binding activity can be eliminated when these
sugars are enzymatically removed [27]. As briefly mentioned with respect to the block to
polyspermy, cortical granule glycosidases are released after a single sperm fuses with the
egg and it is the removal of these critical terminal sugars from their respective
oligosaccharides that causes this loss of sperm binding [16]. In addition, there is an
evolutionarily conserved N-linked site in all species examined (X. laevis amino acid site
113) comprised of simple mannose structures which may be important for the structure or
function of the molecule [16]. Mutations at amino acid sites that alter glycosylation
patterns would also affect sperm-binding activity.
With respect to mutations, there is evidence that mammalian ZPC sperm-binding
proteins on the surface of the female egg are experiencing amino acid substitutions at
accelerated rates especially in the C-terminal region where ZPC interacts with sperm
10
[28]. This pattern of evolution, termed positive Darwinian selection, is determined by
comparing the rate of nonsynonymous substitutions (amino acid replacing) to
synonymous substitutions (or silent sites). In most proteins, their amino acid sites do not
usually exhibit such high rates of substitutions but are rather subjected to purifying
selection (nonsynonymous rate < synonymous rate) where mutations that alter amino
acids are removed from populations due to selectional pressures that preserve the original
function of the protein. Many other sites do not experience these extremes (positive and
negative selection) but are neutral instead (nonsynonymous rate = synonymous rate).
Substitutions at these sites neither have positive or detrimental effects. However, ZPC
genes do show signs of high rates of amino acid substitutions in the sperm-binding region
(positive selection) suggesting that changes in this region are beneficial to the
reproductive success or survival of the species [28]. It is thought that interbreeding
individuals in a population will co-evolve so as to have compatible mutations for
successful fertilization, whereas different mutations are likely to be selected for in
individuals from other populations that could lead to incompatibility of the lock and key
binding interaction (infertility) between populations. This mating incompatibility
between individuals from separate populations could then lead to speciation. Speciation,
the splitting of lineages, is an event that is often thought of as beneficial due to the
preservation of mutations that may have enabled individuals to adapt to their local
environment.
In addition to ZPC, there are other mammalian proteins that have been found to
be under the influence of positive selection that are recognition proteins (i.e. receptor-
11
Figure 4. MHC and ZP3/ZPC structure. Regions of mammalian MHC and ZP3/ZPC
believed to be under positive Darwinian selection are indicated by black spheres (MHC)
and black circles (ZP3/ZPC). The 3D structure shows an antigen bound to the antigen
recognition site of MHC which is thought to be the region experiencing rapid evolution.
The primary structure diagram of ZP3/ZPC (folded structure mostly is unknown) also
indicates alleged areas of selection including the sperm-recognition site and regions of
the N-terminus [28].
12
ligand interactions). The class I major histocompatibility complex (MHC, Figure 4) genes
encode cell-surface glycoproteins present on all nucleated cells that bind non-self
antigens to induce an immune response. Positive selection has been identified at sites
within exons 2 and 3 which code for two variable α-domains of the extracellular antigen
recognition site that bind foreign proteins and present them to cytotoxic T lymphocytes.
The increase in variability resulting from rapid amino acid changes in the antigen
recognition site enhances the possibility that foreign antigens will be recognized by the
MHC molecules. Alterations of the amino acid sequence of the α-domains in the antigen
recognition site of MHC proteins can provide a greater diversity of antigens to which
they can bind and so may experience positive selection. Positive selection can be strong
since the pathogens they experience are also undergoing strong positive selection for
mutations that enable them to evade the host [29,30].
Furthermore, this phenomenon of rapidly evolving reproductive proteins has not
only been observed in mammals, but has also been detected in lower organisms.
Although ZPC is not present in invertebrates, reproductive proteins from these taxa have
been shown to be experiencing positive selection. Bindin, an acrosomal surface protein
isolated from the sea urchin Strongylyocentrotus purpuratus, enables their sperm to
penetrate through the jelly layers of the egg and bind species-specifically to proteins
embedded within the vitelline envelope [31,32]. Substantial research working with sea
urchins as a model suggests that bindin sequences are highly divergent between closely
related species and appears to be due to positive selection. During intraspecific mating,
the concentrations of sperm needed for successful fertilization varies between males
13
suggesting that bindin has variable affinities for different receptor sequences within their
population [33]. In addition to sea urchins, co-evolution between the male and female
reproductive proteins in species of abalone has also been observed to be driven by
positive selection [34,35,36].
Similar to the evolution of mammalian ZPCs, recent evidence from Dr. Peavy's
laboratory suggests that amino acid sites within the C-terminal region of frog ZPC genes
are also experiencing high rates of amino acid substitutions (positive selection). Not only
is this occurring in the model organism X. laevis, but also in the close relative X. borealis
indicating that positive selection may effect the sperm-binding region of ZPC in frogs as
well as in mammals. Moreover, work to assess the molecular evolution of ZPC genes in
amphibians yielded the discovery that multiple copies of the ZPC gene were expressed
within frog ovaries. In short, after cloning and sequencing ZPC genes from individual
ovary cDNA libraries, 5 genes were found in X. borealis, 4 in X. laevis, and 6 in
Lepidobatrachus laevis [37, Peavy unpublished]. The detection of multiple ZPC genes
expressed within the ovaries of the frog species examined has led to questions as to
whether each gene is expressed in equal amounts and whether each ZPC gene product has
sperm-binding activity.
Interestingly, multiple ZPC genes have also been found to be expressed in the
eggs of teleost fish, which include medaka, carp, and zebrafish. Since the ZPC gene has
not been found to exist in invertebrate species such as the sea urchin and abalone, ZPC
genes seem to have evolved after the split of vertebrate lineages. As for the model
organism zebrafish, evidence points to upward of five different ZPC gene copies
14
arranged in tandem repeats due to gene duplication events that are expressed specifically
in the early-growing oocyte [38,17]. Furthermore, if duplications occurred before the split
that gave rise to amphibians, fish and frogs would share common ZPC genes (orthologues
and paralogues). However, as mentioned previously, fish ZPC genes do not serve a
functional role in sperm binding since sperm bypass the chorion entirely by entering
through a small pore called the micropyle [17,18]. Thus, the same selectional forces do
not act on the ZPC gene with regards to sperm binding activity in fish [39]. Since it has
been shown that X. laevis ZPC does bind to sperm, the evolution of sperm binding
activity likely emerged after the lineage leading to amphibians split off from fish.
A shift in reproductive strategy from external to internal fertilization may have
lead to “birth-and-death” ZP gene evolution in the lineage leading to mammals. After the
divergence from birds (300 million years ago), two ZP genes (ZPAX and ZPD) were
silenced in mammals possibly due to the accumulation of mutations from a relaxation of
their functional constraints. Furthermore, gene death is seemingly observed in the mouse
where ZPB exists in the genome as a nonfunctional pseudogene copy after its split from
the rat lineage, whereas it has a different gene termed ZP1 that has seemingly taken its
place in the zona pellucida [40]. Contrasting the larger number of gene copies in fish and
frogs, mammals only express one functional ZPC gene copy that is highly homologous
within mammalian species. Ancient mammalian copies may have been deleted over
evolutionary time or possibly still exist as relics of their ancestry within genomes as
pseudogenes. The "death" of a gene by becoming a pseudogene is due to one of the
following events: mutations that cause a stop codon or reading frame shift in the coding
15
region; or by the accumulation of mutations in promoter regions causing a silencing of a
once expressed gene [40,41]. This mechanism of “gene death” has been extensity studied
in MHC genes, and evidence suggests that ZPCs have followed a pattern of progressive
gene loss in the lineage leading mammals [30,42,43,44].
If this is the case, some ZPC gene copies expressed in amphibians may have lost
the ability to bind sperm and may be heading down the path toward silencing.
Additionally, amphibians and mammals require species-specific sperm-egg binding
interactions at the initiation of fertilization creating the need for the evolution of high
affinity binding interactions which seemingly has eliminated the need for a micropyle.
Shifting to sperm-binding during the evolution from fish to amphibians would likely have
caused selectional pressure on sperm to not only be the first to reach the egg, but also the
ability to bind tightly enough with ZPC proteins to initiate the acrosome reaction [2].
In the case of sperm-binding genes, sperm competition and sexual conflict may be
forces driving positive selection, divergence, and possibly silencing of reproductive
genes. Males and females have opposing strategies when it comes to fertilization where
males allocate large numbers of sperm to increase the chances of conception while
females seek to limit the rate of fertilization to avoid deleterious effects such as
polyspermy. The success of each sperm depends on its ability to bind complementarily to
ZPC with high enough affinity to induce the acrosome reaction creating competition
between sperm for the optimal binding sequence. However, subtle alterations to the ZPC
protein structure may prove sufficient in slowing the fertilization rate forcing sperm to
compete with one another. This causes a scenario whereby the sperm receptor co-evolves
16
with mutations found in ZPC. Modes of sexual conflict where fitness in one sex is
decreased while fitness improves in the other may explain the need for constant coevolution (driven by positive selection) between the sexes [45]. By keeping sperm one
step behind in the evolutionary race to fertilization, females are able to slow the process
and minimize the deleterious effects of polyspermy.
Since it is has been shown in mice and X. laevis that ZPC does serve as the
primary sperm binding molecule, the existence of multiple ZPC gene products being
expressed in frogs leads to the question as to which ones can serve as functional spermbinding molecules [11,12,27]. One possibility is that there is only one functional copy
while remaining copies provide structural support to the vitelline envelope [46]. This
functional copy would likely be expressed in the highest amount to ensure sperm binding.
Alternatively, more than one ZPC gene may be able to bind to sperm and the expression
of multiple ZPC genes in the same egg would cause a competition for sperm binding.
Molecular evolution (positive selection) and competition may have led to binding affinity
differences where the gene with the greatest affinity for sperm will have a decided
advantage for binding. Competition among sperm would select for complementary
mutations as they co-evolve which could cause a decrease in the number of sperm that
can actually bind the egg at one time. This could be beneficial to the egg since there are
many sperm reaching the egg vitelline envelope at the same time and this rate limiting
binding step could serve to help prevent polyspermic fertilization. In this case, it is likely
that all ZPC genes would be expressed in relatively equal amounts to function as
competitors. However, the scenario may be a combination of expressing more than one
17
functional ZPC gene and the others having become non-functional and potentially
serving alternative roles such as structural. Although, it is possible that ZPC genes
serving an alternative structural role may be expressed in high amounts so as to add
strength and stability to the vitelline envelope, it seems less likely since there are plenty
of other ZP glycoproteins that comprise the matrix as mentioned previously.
Furthermore, research examining the duplicated midbrain homeobox-1 and -2 (mbx1 and
mbx2) genes in zebrafish provides evidence that the highly expressed gene (mbx1)
translates into protein which performs the original function whereas the low expresser
(mbx2) displays a diminished or alternative role [46]. In any case, one of the first steps
towards answering these functional questions is to determine the expression levels of the
various ZPC gene products found in the eggs, which is the goal of this study.
Although there is substantial research and evidence elucidating the role of ZPC in
anuran fertilization, we do not know the ZPC expression level for the different genes in
individual frogs. Xenopus is a prime organism for these studies since it is a commonly
used vertebrate model for molecular, developmental, and fertilization research. As for a
comparison, it would be best to study a frog species closely related to X. laevis (i.e. X.
borealis) and a more distantly related one (i.e. Lepidobatrachus laevis) so as to assess the
short and long term evolutionary patterns. By examining ZPC expression in close and
distantly related frog species, comparisons can be made to determine whether or not
orthologous ZPC genes show similar patterns of expression through out the evolution of
these vertebrate species.
18
X. borealis was chosen as the closely related species since it last shared a
common ancestor with X. laevis approximately 10 mya [47,48,49]. Interestingly, the
lineage leading to Xenopus frogs experienced a whole genome duplication event
approximately 30 million years ago [47,48,49]. Since X. borealis was found to have 5
ZPC genes expressed in its ovary, this means that there has to be at least one other gene
loci since a single loci can only provide 4 allelic copies (4n). Evidence suggests
duplicated genes (paralogs) are often subject to purifying selection soon after genome
duplication and gene duplicates may acquire mutations in regulatory regions which effect
expression [50,18]. Our hypothesis is that the ZPC gene that functions as the primary
sperm-binding protein in the closely related X. laevis and X. borealis should also be
expressed to a similar degree and expressed in higher amounts compared to paralogs.
As for a distant relative to Xenopus, the South American frog Lepidobatrachus
laevis from the Leptodactylidae family was chosen. Within the order Anura, frog species
are classified as advanced or primitive frogs grouped together in the suborders
Neobatrachia and Archaebatrachia. X. laevis and X. borealis are examples of a small
percentage of frogs that belong to Archaebatrachia or the more primitive classification.
The vast majority (96%) of species are members of Neobatrachia including L. laevis.
Based on molecular and fossil data, Xenopus and Lepidobatrachus last shared a common
ancestor about 110-120 million years ago, making L. laevis a distant relative of Xenopus
species [51,48].
As mentioned previously, studies from Dr. Peavy's lab have shown that a single L.
laevis female expressed 6 different ZPC genes and yet this species is only diploid. In
19
addition to the existence of multiple gene copies, data from 2D immunoblots suggests
that the amount of translated ZPC protein is variable within the L. laevis vitelline
envelope (Figure 5, Peavy unpublished results). Although the amount of protein
translation does not always correlate with levels of gene expression, this immunoblotting
data suggests that ZPC protein levels do indeed vary and are unequally expressed.
Hypothesis
This has led me to the following hypothesis statement:
Xenopus laevis, Xenopus borealis and Lepidobatrachus laevis ZPC genes are unequally
expressed within their respective ovaries, and orthologous ZPC genes have a similar
pattern of expression.
Objectives

Clone and sequence the GAPDH cDNA for use as a reference gene in qPCR

Design qPCR primers to known ZPC sequences as well as to GAPDH

Optimize conditions and parameters for qPCR

Perform qPCR and analyze results to determine gene expression patterns
Rationale for Experimental Design
To support and build upon data suggesting unequal ZPC protein translation, the
expression level of each X. laevis, X. borealis and L. laevis ZPC gene will be determined
by quantitative PCR (qPCR). Most studies aiming to quantify gene expression turn to
20
Homologous
VE antisera
ZPC
ZPC
X. laevis
ZPC antisera
ZPC
ZPC
X. laevis
L. laevis
Figure 5. 2D immunoblot of X. laevis and L. laevis vitelline envelopes (VE). Isoelectric
point is indicated on the top horizontal axis and molecular weights down the vertical axis.
(a) Immunoblot of X. laevis VE using antisera to the entire X. laevis VE glycoproteins.
(b) Immunoblot of X. laevis VE using X. laevis ZPC antisera. (c) Immunoblot of L. laevis
VEs using antisera to the entire L. laevis VE. (d) Immunoblot of L. laevis VE using X.
laevis ZPC antisera.
21
qPCR due to its sensitivity and level of accuracy. Quantitative PCR measures gene
expression by monitoring the generation of PCR products at each successive cycle. What
sets this technology apart from a traditional PCR approach is the use of fluorescent
reporters that detect the formation of products in early cycles before the reaction has a
chance to become variable with respect to the total amount of product made (end-point
assay). The point at which the fluorescent intensity raises appreciably above background
(threshold level) is termed the CT value. The CT value approximates when the reaction
enters into the exponential phase of amplification. In addition, CT values correspond to
the amount of starting material (mRNA or cDNA in this case) [52].
Expression will be determined by first comparing ZPC CT values to the CT of a
housekeeping gene. In this case, glyceraldehyde 3-phosphate dehydrogenase (GAPDH)
was chosen to normalize ZPC expressional data because it is a commonly used reference
gene and is expressed in the early growing frog oocyte [53]. Since the sequence of
GAPDH is known for X. laevis, it can be used for the design of primers to target
amplification, cloning, and sequencing of the corresponding cDNA in X. borealis and L.
laevis. Primers designed to amplify ZPC and GAPDH will then be used in qPCR
reactions to determine their respective CT values for each gene. Once obtained, the CT
values can be used to determine the expression levels of each ZPC gene relative to the
reference gene and compared to see if similar patterns of expression were found.
22
Chapter 2
METHODS
Sequencing of ZPC cDNAs from Frog Ovary cDNA Libraries.
Dr. Peavy prepared ovary cDNA libraries from single female individuals from the
frog species Lepidobatrachus laevis, Xenopus laevis, and X. borealis. Ovary tissue was
snap frozen in liquid nitrogen and subsequently processed for RNA purification (Qiagen
RNA purification kit). Ovary cDNA libraries were constructed using the Marathon cDNA
Amplification Kit (Clontech). In addition, another L. laevis ovary cDNA library was
made using the Lambda Uni-ZAP XR vector kit (Agilent Technologies, Santa Clara,
CA). Degenerate primers designed to the conserved ZP domain of the ZPC genes were
used to PCR amplify the targeted middle cDNA portion encoding the ZP domain.
Subsequently, the 5' and 3' cDNA ends were PCR amplified using specific primers
designed from the known sequence of the conserved domain in combination with the
Marathon adaptor AP1 primer [37, Peavy unpublished]. PCR products were cloned into
the pGEM-T Easy (Promega) vector, transformations performed (using competent XLIBlue E. coli cells and LB-ampicillin plates), and colonies selected for plasmid
purification (Qiagen Plasmid Mini Kit). After performing EcoRI restriction digest to
identify clones with appropriately sized inserts, the PCR product inserts were sequenced
commercially (Davis Sequencing, Davis, CA; Sequetech, Mountain View, CA). ZPC
sequence information was edited to produce full length sequences using the Lasergene
software package (DNASTAR Inc, Madison, WI). Glycerol stocks were made for all
ZPC clones and stored at -80oC for future use.
23
PCR and Sequencing of Glyceraldehyde 3-phosphate dehydrogenase
Degenerate primers were designed based on the GAPDH amino acid sequence of
an evolutionarily diverse group of organisms aligned by the web-based multiple sequence
alignment program CLUSTALW (http://www.ebi.ac.uk/Tools/msa/clustalw2/) and
reformatted using the pretty printing BOXSHADE program
(http://www.ch.embnet.org/software/BOX_form.html). The following taxa were used for
the alignment: Mouse 1 (XP_001480018.1), Mouse 2 (NP_032110.1), Human
(NP_002037), Chicken (NP_989636), Zebrafish (NP_001108586), X. laevis
(NP_001080567.1), and X. tropicalis (NP_001004949.1). Primers were designed to
evolutionarily conserved regions to increase the chances that orthologous GAPDH
sequences would be amplified from the X. borealis and L. laevis ovary cDNA libraries.
One forward and two reverse degenerate primers were designed in order to perform
nested PCR to reduce the amplification of nonspecific products. Custom-made
degenerate primers (Sigma, Woodlands, TX) were diluted to 10µM working aliquots.
PCR reactions were performed using an aliquot of the L. laevis or X. borealis
ovary cDNA library in combination with an internal degenerate primer (GAPDH.dR1)
and the appropriate vector primer (T3 or AP1). The Advantage PCR Polymerase kit
(Clontech, Mountain View, CA) was used for amplification since this enzyme mix has
proofreading capability to reduce the nucleotide incorporation error rate. PCR was
performed using a MyCycler thermocycler (Bio-Rad, Hercules, CA) based on the
following conditions: initial denature cycle at 95oC for 5 minutes; 35 cycles at 94oC for
45 seconds, 50oC for 45 seconds, and 72oC for 45 seconds; and a final hold cycle at 4oC.
24
A negative control without template DNA was also included. PCR products were
analyzed by loading ten microliters into 1.5% agarose-TAE gels, electrophoretically
separated, stained using ethidium bromide, and visualized using a AlphaImager 2200 gel
documentation system (Alpha Innotech, Santa Clara, CA). For nested PCR, the initial
PCR reaction was diluted 1/500x and served as the starting template for the subsequent
PCR amplification. In addition, a set of nested internal degenerate primers (GAPDH.dF1
and GAPDH.dR2) were used in combination with the vector primers in a PCR reaction
similar to that described above except that a gradient temperature was used for annealing
conditions (50.0oC, 52.9oC, and 56.2oC). PCR products were electrophoretically analyzed
as described. PCR products were subsequently purified using the QIAquick PCR
Purification Kit (Qiagen), ligated into pGEM T-easy, and transformed into E. coli. After
purifying plasmid DNA and analyzing restriction digests, appropriately sized PCR
products were commercially sequenced. This middle section of the putative GAPDH
sequences was then used in BLAST searches (http://blast.ncbi.nlm.nih.gov/Blast.cgi) of
the sequence databases to determine whether it was indeed the GAPDH sequence from
each frog species.
Primers were subsequently designed for amplification of the 5' and 3' ends of the
L. laevis and X. borealis GAPDH cDNAs based on the sequences obtained above using
the Primer Select software program within the Lasergene software package. Once again,
a nested PCR approach was undertaken using specific internal primers and the vector
ends. Appropriately sized PCR products were PCR purified if they were one of the only
bands observed on the gel. However, if there were multiple bands, PCR products were
25
isolated by cutting out gel slices from 1.4% low melt agarose-TAE gels (Agarose II, ISC
BioExpress) and extracting the DNA using the QIAquick Gel Extraction Kit (Qiagen).
PCR products were subsequently ligated, transformed, sequenced and edited as
described.
qPCR Primer Design
All primers used in qPCR assays were designed using the Primer Select software.
Each ZPC sequence was initially imported into the SeqBuilder software program
(Lasergene) and converted to a format compatible with the Primer Select program.
Forward and reverse primer sets were designed based on parameters determined for
optimal qPCR as defined by Logan et al. [54]. Primer sets were designed with a
theoretical melting temperature (Tm) of 60oC (+/- 2oC), %GC content to be approximately
50%, and PCR product length to be 100-150 base pairs. The length of the primers ranged
from 25-36 bases to ensure that primers will specificity target and amplify a 100-150 base
pair product of either ZPC or GAPDH from a cDNA library. Only two or three of the last
five bases in the 3’ end of each primer were designed to have a guanine or cytosine so as
to prevent artificial GC clamping and amplification of non-specific products.
CLUSTALW and BOXSHADE programs were used to visualize the alignment of the
ZPC cDNA sequences so that regions specific to each clone could be targeted for primer
design. Potential primer sets designed through Primer Select were then evaluated with
respect to their location within the CLUSTALW alignments. A total of 15 ZPC primer
26
sets were designed for qPCR assays which included 6 for L. laevis, 5 for X. borealis, and
4 for X. laevis. Additionally, a GAPDH primer set was designed for each species.
qPCR Primer Annealing Temperature Optimization
The optimal annealing temperature (TA) for each primer set was determined using
the MyCycler thermocycler which has the capability to perform gradient annealing
temperature PCR. The template DNA for each primer set was plasmid DNA that was
purified from E. coli transformants that contained the appropriate cDNA insert clone.
Each ZPC and GAPDH plasmid DNA was quantified using the PicoGreen fluorescent
assay (Invitrogen, Carlsbad, CA) and a Turner Biosystems 380 Fluorometer (Fisher
Scientific, Pittsburg, PA). Plasmid DNA was diluted to a working concentration of
2.5ng/µl which was then used to generate serial dilutions for template DNA in the PCR
reactions. The GoTaq Flexi DNA Polymerase kit (Promega) was used for PCR reactions.
PCR reactions were assembled in a PCR clean hood which included UV irradiation of all
components except primers and DNA template. A master mix was prepared using all the
components except plasmid DNA and then aliquoted to thin walled PCR tubes. In
addition, a negative control without template DNA was included ("no template") so as to
determine whether primer dimers were being formed during the reaction and if there was
template contamination. Gradient PCR was performed using the following conditions:
initial denature cycle at 95oC for 5 minutes; 25 cycles at 94oC for 45 seconds, gradient
annealing temperature for 45 seconds, and 72oC for 45 seconds; and a final hold cycle at
27
4oC. PCR products were then electrophoretically analyzed using 2% agarose-TAE gels
and a DNA size standard, ExACT Gene 100bp ladder (Fisher Scientific).
Mixed Plasmid Experiments
Mixed plasmid experiments were preformed to verify that each primer set is
specific for the template it was designed for and that the specific primers do not amplify
any of the other ZPC templates found in a particular cDNA library. Each PCR reaction
was performed as above, but instead of using a gradient of annealing temperatures, the
temperature deemed as optimal was used for annealing (i.e. amplification was robust at
this temperature, but the next higher temperature resulted in a dramatic reduction of
product). Each experiment contained a positive control which utilized one plasmid ZPC
cDNA template, its specific primer set, and the annealing temperature optimal for
amplifying its specific product. The mixed plasmid PCR reaction was then set up to
include all the other plasmid ZPC cDNA templates (without the positive control plasmid
template), the specific primer set for the control plasmid, and the same optimized
annealing temperature. A "no template" negative control was also included as described
before. PCR reactions were analyzed on 2% agarose gels as described above.
iQ5 Multicolor Real-Time Detection System Calibration
It is essential that the iQ5 Multicolor Real-Time Detection System (Bio-Rad) be
calibrated for the type of vessel, volume, and sealing methodology prior to performing
qPCR. The first calibration is the mask alignment. To align the mask, 10x External Well
28
Factor Solution (Bio-Rad) is diluted to 1x with ddH2O, and then 25µl (the chosen
volume) is pipetted into the vessel of choice, either a hard-shell 96-well plate (Bio-Rad)
or alternatively clear 0.2mL 8-tube Strips (Bio-Rad) depending on the needs of the
experiment. For the 96-well plate, all wells were loaded with 25µL of 1x external well
factor solution and sealed with Microseal ‘B’ Film (Bio-Rad). For the 0.2mL 8-tube
strips, 25µl of 1x External Well Factor Solution was pipetted into each tube and sealed
with corresponding flat cap strips (Bio-Rad). Within the iQ5 Optical System Software,
the steps were followed to align, optimize, and save the mask settings. It is also essential
that the background level of fluorescence from the vessel is accounted for (background
calibration) by using empty vessels that have been sealed in the same manner as before.
Once the mask and background has been calibrated, the persistent well factor is calibrated
to account for well-to-well fluorescence detection variation. The same vessels containing
the 25µl of 1x External Well Factor Solution was returned to the heating block and the
persistent well factors were collected. Calibrations were valid for six months according to
the manufacturer instructions. The "Pure Dye Calibration" did not need to be done since
the fluorescent DNA binding dye SYBR Green was been used for detection.
Primer Efficiency
The ability of each primer set to efficiently amplify the target was tested using the
iQ5 Multicolor Real-Time Detection System (Bio-Rad). Master mixes were prepared
using the iQ SYBR Green Supermix (Bio-Rad) which contains 2x reaction buffer,
dNTPs, iTaq DNA polymerase, MgCl2, SYBR Green I, fluorescein, and stabilizers. In
29
addition, brand new pipetteman (Gilson) were used for delivering volumes to PCR
vessels to increase accuracy and prevent contamination from previous PCR reactions.
Master mixes were prepared as described above in a clean PCR hood and primers and
template DNA were then added later. Plasmid DNA previously used for primer
optimization protocols served as the starting template for primer efficiency assays. The
2.5ng/µl working solution of plasmid DNA (containing cDNA inserts) was serially
diluted 10-fold five times creating a gradient of concentrations ranging from 2.5ng/µl to
0.000025ng/µl. Only 1µl of plasmid templates diluted in the range from 0.025ng/µl to
0.000025ng/µl were used as starting template for the primer efficiency qPCR reactions. A
"no template" negative control was also included for any particular set of reactions. Strip
tubes were then capped, centrifuged, and placed on the optical reaction block of the iQ5
Multicolor Real-Time Detection System. The following qPCR protocol was used for each
primer efficiency assay: initial denature cycle at 95oC for 5 minutes; 30 cycles at 94oC
for 15 seconds, optimal annealing temperature for 30 seconds; and lastly a melting curve
cycle from 55-95oC using 81 steps with each step being 15 seconds. The efficiency of
each primer set was calculated by the iQ5 software as determined by setting up a standard
curve for each dilution series assay. Acceptable primer efficiency has been established to
be between 90-110%. Melt curves were also analyzed to examine whether there was any
evidence of primer dimer amplification.
Gene Expression Level Assays using qPCR
30
Quantitative PCR was performed using the same iQ5 Multicolor Real-Time
Detection System as above. Master mix without primers was exposed to UV irradiation in
the PCR hood for 15 minutes as before. A single master mix is prepared for the
assessment of ZPC and GAPDH as outlined in Figure 6. The SYBR Green Super Mix
contains the following components: ddH2O, 2x reaction buffer, dNTPs, iTaq DNA
polymerase, 6mM MgCl2, SYBR Green I, fluorescein, and stabilizers. Half of the total
volume (74.75µl) is transferred to one tube where primers for the specific ZPC cDNA are
added, whereas the second half is added to a tube with the GAPDH primer set. Then,
25µl is pipetted into wells of the 96-well plate in triplicate. Separate master mixes are
prepared to serve as the "no template" negative control (simply doesn't contain ovary
cDNA). Plates were then sealed with Microseal ‘B’ Film, centrifuged, and placed on the
optical reaction block of the iQ5 Multicolor Real-Time Detection System. qPCR
protocols were set up using the iQ5 Optical System Software. The same qPCR protocol
was used for each different ZPC or GAPDH gene being assayed based on the optimal
annealing temperature utilized in the primer efficiency assays.
Data Analysis
Upon completion of each assay, the data is analyzed in the Data Analysis Module
of the iQ5 Optical System Software. The PCR Quantification (PCR Quant) tab displays
the amplification curves and is used to set the analysis conditions for each trial. The CT
value threshold was manually set at 200 relative fluorescent units (RFU) for each species
and gene being measured. Once the threshold was set, the specific CT value for each
31
Super Mix
81.25ul
ddH2O
61.75ul
Ovary cDNA 6.5ul
74.75ul
GAPDH Forward Primer 3.5ul
GAPDH Reverse Primer 3.5ul
25ul
74.75ul
ZPC Forward Primer 3.5ul
ZPC Reverse Primer 3.5ul
25ul
Figure 6. Quantitative PCR master mix set-up. To minimize technical variability between
reactions master mixes were used for each qPCR assay. Volumes of qPCR reagents are
listed next to each PCR tube. Volumes next to arrows indicate amount of reaction
material that was transferred to either a new PCR tube or the wells of a qPCR plate.
32
reaction was then recorded into a spreadsheet for further analyses of relative gene
expression. Since reactions were performed in triplicate, CT values were averaged for
each trail. Two additional trials, each with triplicate samples were also performed.
GAPDH qPCR assays were performed concurrently with each ZPC gene trial to serve as
a plate-to-plate control to make sure equal volumes of cDNA are incorporated into each
trial.
In order to determine the relative ZPC gene expression differences, average ZPC
CT values were normalized to the average GAPDH CT values. GAPDH served as the
baseline that all ZPC CT values were compared to within a particular species. CT values
were normalized to GAPDH by calculating the ΔCT where ΔCT = CT ZPC – CT GAPDH.
Once the ZPC CT values were normalized to GAPDH, each normalized ZPC gene was
compared to the others found within the particular frog species by calculating the
Δ(ΔCT) value where Δ(ΔCT) = ΔCT ZPC.n - ΔCT ZPC.lowest. In order to calculate this, the
lowest expressed gene (ΔCT ZPC.lowest) was used as the baseline to which all other ZPC
genes would be compared. Then, the relative fold difference was calculated using the
following equation: 2Δ(ΔCT). For example, one ZPC might be expressed 4 times as much
as the lowest expressed ZPC gene.
In addition, melt curve data was viewed through the Melt Curve/Peak setting
within the Data Analysis software. The RFU (relative fluorescence unit) data collected
during the melt curve cycle was plotted against temperature to create a graphical display
of the data. This melt curve was then used to derive a melt peak chart which depicts the
rate of change in fluorescence with respect to temperature (a rapid decrease in
33
fluorescence signal indicates that a specific product melted). The number of different
sized products can then be estimated by the number of individual peaks on the melt peak
chart.
Statistical Analysis
Statistical tests were conducted to determine and decipher significant levels of
expression between each measured gene. Using Microsoft Excel, the existence of
variable expression was established through ANOVA analysis using ΔCT values from
triplicate trials. Significant levels of expression for individual genes were determined by
performing t-tests comparing pairwise combinations using the Bonferroni correction. The
Bonferroni correction is established by dividing 0.05 by the total number of pairwise
comparisons to yield the alpha level. For example, L. laevis expresses six ZPC genes
making 15 total pairwise comparisons. The null hypothesis of equal expression is rejected
if p-values derived from t-tests are less than 0.0033 (0.05/15 = 0.0033).
Phylogenetic Analyses
Phylogenetic and molecular evolutionary analyses of the ZPC gene family were
conducted using MEGA software version 4 [55]. ZPC cDNA sequences from L. laevis, X.
laevis, and X. borealis were imported into the MEGA program and globally aligned by
CLUSTALW. Phylogenetic trees were constructed showing evolutionary relationships
within and across species using the maximum likelihood and neighbor-joining methods.
A bootstrap analysis was performed using 1000 replicates to resample the data and gain
34
and estimate of the level of confidence in the branching order from the resulting tree.
Bootstrap values are the percentage of tree replicates that show the same branching
pattern as the consensus tree [56].
35
Chapter 3
RESULTS
Cloning and Sequencing GAPDH cDNAs
Design of GAPDH Degenerate Primers
Degenerate primers were designed based on a GAPDH protein multiple sequence
alignment of species ranging from zebrafish to human, including the frog species X.
laevis and X. tropicalis (Figure 7). The diversity of the organisms included in the
alignment increases the likelihood that the conserved sequences observed in the
alignment will also be conserved for the two targeted frog species, L. laevis and X.
borealis. Degenerate primers were designed to evolutionarily conserved amino acid
regions indicated by the black shading in Figure 7. One forward and two reverse
degenerate primers were designed so that they could be used in combination with vector
primers based on which cDNA library kit was used for cDNA construction. The primers
GAPDH.dF1 (forward) and GAPDH.dR1 (reverse) both have a fold degeneracy of 256
giving the primers a 1 in 256 chance of base pairing 100% with the corresponding
GAPDH cDNA in the library (Table 1). The third degenerate primer was 384 fold
degenerate making the chances of perfect base pairing lower, but still within a reasonable
range. The primers were designed to be 20-24 bases in length and to have little or no
degeneracy at their 3' ends to decrease the chances of non-target amplification.
Cloning of L. laevis GAPDH
For the first round of the L. laevis nested PCR strategy, the GAPDH.dR1 primer
36
Mouse1
Mouse2
Human
Chicken
Zebrafish
X.laevis
X.tropicalis
1
1
1
1
1
1
1
--MVKVGVNGFGRIGRLVTRAAICSGKVEIVAINDPFIDLNYMVYMFQYDSTHGKFNSTV
--MVKVGVNGFGRIGRLVTRAAICSGKVEIVAINDPFIDLNYMVYMFQYDSTHGKFNGTV
MGKVKVGVNGFGRIGRLVTRAAFNSGKVDIVAINDPFIDLNYMVYMFQYDSTHGKFHGTV
--MVKVGVNGFGRIGRLVTRAAVLSGKVQVVAINDPFIDLNYMVYMFKYDSTHGHFKGTV
--MVKVGINGFGRIGRLVTRAAFLTKKVEIVAINDPFIDLDYMVYMFQYDSTHGKYKGEV
--MVKVGINGFGCIGRLVTRAAFDSGKVQVVAINDPFIDLDYMVYMFKYDSTHGRFKGTV
------------------------------------------MAYMFKYDSTHGRFKGTV
Mouse1
Mouse2
Human
Chicken
Zebrafish
X.laevis
X.tropicalis
59
59
61
59
59
59
19
Mouse1
Mouse2
Human
Chicken
Zebrafish
X.laevis
X.tropicalis
119
119
121
119
119
119
79
KAENGKLVINGKPITIFQERDPANIKWGEASAEYVVESTGVFTTMEKARAHLKGGAKRVI
KAENGKLVINGKPITIFQERDPTNIKWGEAGAEYVVESTGVFTTMEKAGAHLKGGAKRVI
KAENGKLVINGNPITIFQERDPSKIKWGDAGAEYVVESTGVFTTMEKAGAHLQGGAKRVI
KAENGKLVINGHAITIFQERDPSNIKWADAGAEYVVESTGVFTTMEKAGAHLKGGAKRVI
KAEGGKLVIDGHAITVYSERDPANIKWGDAGATYVVESTGVFTTIEKASAHIKGGAKRVI
KAENGKLIINDQVITVFQERDPSSIKWGDAGAVYVVESTGVFTTTEKASLHLKGGAKRVV
CVENGKLVINGKAVTVFQERDPSNIKWGDAGAVYVVESTGVFTTKEKAGLHLKGGAKRVI
GAPDH.dF1
-------->
ISAPSADAPMFVMGVNHEKYDNSLKIFSNASCTTNCLAPVAKVIHDNFGIVEGLMTTVHA
ISAPSADAPMFVMGVNHEKYDNSLKIVSNASCTTNCLAPLAKVIHDNFGIVEGLMTTVHA
ISAPSADAPMFVMGVNHEKYDNSLKIISNASCTTNCLAPLAKVIHDNFGIVEGLMTTVHA
ISAPSADAPMFVMGVNHEKYDKSLKIVSNASCTTNCLAPLAKVIHDNFGIVEGLMTTVHA
ISAPSADAPMFVMGVNHEKYDNSLTVVSNASCTTNCLAPLAKVINDNFVIVEGLMSTVHA
ISAPSADAPMFVVGVNHEKYENSLKVVSNASCTTNCLAPLAKVINDNFGIVEGLMTTVHA
ISAPSADAPMFVVGVNHDKYDNSLHVVSNASCTTNCLAPLAKVINDNFGILEGLMTTVHA
Mouse1
Mouse2
Human
Chicken
Zebrafish
X.laevis
X.tropicalis
179
179
181
179
179
179
139
Mouse1
Mouse2
Human
Chicken
Zebrafish
X.laevis
X.tropicalis
239
239
241
239
239
239
199
Mouse1
Mouse2
Human
Chicken
Zebrafish
X.laevis
X.tropicalis
299
299
301
299
299
299
259
ITATQKTVDGPSGKLWRDGRGAAQNIIPASTGAAKAVGKVIPELNWKLTGMAFRVPTPNV
ITATQKTVDGPSGKLWRDGRGAAQNIIPASTGAAKAVGKVIPELNGKLTGMAFRVPTPNV
ITATQKTVDGPSGKLWRDGRGALQNIIPASTGAAKAVGKVIPELNGKLTGMAFRVPTANV
ITATQKTVDGPSGKLWRDGRGAAQNIIPASTGAAKAVGKVIPELNGKLTGMAFRVPTPNV
ITATQKTVDGPSGKLWRDGRGASQNIIPASTGAAKAVGKVIPELNGKLTGMAFRVPTPNV
FTATQKTVDGPSGKLWRDGRGAGQNIIPASTGAAKAVGKVIPELNGKITGMAFRVPTPNV
FTATQKTVDGPSGKLWRDGRGAGQNIIPASTGAAKAVGKVIPELNGKLTGMAFRVPTPNV
GAPDH.dR2
<-------FVLDLTCRLEKPAKYDDIKKVVKQASEGPLKGILGYTEDQVVSCYFNSNSHSSTFDARAG
SVVDLTCRLEKPAKYDDIKKVVKQASEGPLKGILGYTEDQVVSCDFNSNSHSSTFDAGAG
SVVDLTCRLEKPAKYDDIKKVVKQASEGPLKGILGYTEHQVVSSDFNSDTHSSTFDAGAG
SVVDLTCRLEKPAKYDDIKRVVKAAADGPLKGILGYTEDQVVSCDFNGDSHSSTFDAGAG
SVVDLTVRLEKPAKYDEIKKVVKAAADGPMKGILGYTEHQVVSTDFNGDCRSSIFDAGAG
SVVDLTCRLQKPAKYDDIKAAIKTASEGPMKGILGYTQDQVVSTDFNGDTHSSIFDADAG
SVVDLTCRLSKPAKYDDIKAAIKTAAHGPMKGILEYTEDQVVSTDFNGDTHSSIFDAGAG
GAPDH.dR2
<--------IALNDNFVKLISWYDNEYGYSNRVVDLMAYMASKE
IALNDNFVKLISWYDNEYGYSNRVVDLMAYMASKE
IALNDHFVKLISWYDNEFGYSNRVVDLMAHMASKE
IALNDHFVKLVSWYDNEFGYSNRVVDLMVHMASKE
IALNDHFVKLVTWYDNEFGYSNRVCDLMAHMASKE
IALNENFVKLVSWYDNECGYSNRVVDLVCHMASKE
IALNDNFVKLVSWYDNECGYSHRVVDLMCHMASKE
Figure 7. GAPDH protein sequence alignment and primer design. GAPDH protein
sequences from taxa ranging from zebrafish to human were aligned by CLUSTALW and
imported into BOXSHADE. Black shading indicates sequence identity while grey
shading shows conservative substitutions. No shading (white) indicates sequence
differences. Degenerate primer locations are represented by arrows above the sequences.
Table 1. Summary of primers used to clone GAPDH from L. laevis and X. borealis. GAPDH degenerate primers used to
clone a middle portion of the corresponding cDNA were designed by hand to evolutionarily conserved regions. Gene
specific GAPDH PCR primers targeting the 5' and 3' cDNA ends of L. laevis and X. borealis were designed using
Primer Select software after sequencing of the middle portion, and were used in combination with their vector primers
flanking the cDNA cloning sites
37
38
was used in combination with the T3 vector primer (Figure 8a). The expected size for the
PCR product was 950 bp which was observed in the stained agarose gel in addition to
several other bands found to be approximately 175 bp and 750 bp. This initial PCR
reaction was performed at a relatively low annealing temperature or low stringency
(50oC) to ensure amplification which explains the additional PCR products. A nested
PCR strategy was then used to amplify an expected 403 bp product by utilizing the two
internal degenerate primers GAPDH.dF1 and GAPDH.dR2. A 1/500 dilution of the initial
PCR reaction containing the 950 bp amplicon served as the starting template for this
nested PCR. In addition, a gradient was used for the annealing step (50oC, 52.9oC,
56.2oC) to optimize the annealing temperature and decrease non-target amplification. The
stained gel of the nested PCR revealed lone bands at the 400 bp ladder mark for each of
the annealing temperatures (Figure 8b).
The nested PCR reactions for L. laevis GAPDH were pooled together and then
ligated into the pGEM-T Easy vector, transformed into competent E. coli cells, and plated
on LB agar plates containing ampicillin. Selected colony transformants were then used to
generate overnight cultures for spin column plasmid purification. After digestion with
EcoR1 restriction enzyme, 5 clones were identified to contain the appropriately sized 400
bp cDNA (Figure 8c). One clone was subsequently sent off for commercial sequencing
using the sp6 vector primer. After receiving the sequence information, a BLAST search
was performed which returned with the best alignment being to the X. laevis GAPDH
cDNA sequence. The sequenced 403 bp L. laevis cDNA sequence aligned to the middle
portion of the X. laevis GAPDH cDNA as intended with 83% identity (Figure 9).
39
a.
1
L
1000 bp
950 bp
2
GAPDH
3
GAPDH
100 bp
b.
1
L
2
50.0
3
52.9
4
56.2
5
TA
-
1000 bp
GAPDH
400 bp
100 bp
c.
1
L
2
a
3
b
4
c
5
d
6
e
1000 bp
400 bp
GAPDH
100 bp
Figure 8. Degenerate PCR of the L. laevis GAPDH cDNA. (a) First round PCR using the
GAPDH.dR1 primer in combination with the T3 vector primer (b) Second round nested
PCR with internal GAPDH.dF1 and GAPDH.dR2 (c) EcoR1 restriction enzyme digests
of cloned nested PCR products. L = ladder; - = negative control; TA = annealing
temperature; letters (a, b, c, etc.) = clones.
40
XlGAPDH
LlGAPDH
1 AGCAGATGCCCCCATGTTTGTAGTTGGCGTGAACCATGAGAAATATGAGAACTCTCTTAA
1 -GCTGATGCCCCGATGTTTGTTGTTGGTGTCAACCATGAAAGCTATGACAACTCACTGAA
XlGAPDH
LlGAPDH
61 AGTTGTTAGCAATGCTTCCTGCACTACAAACTGTCTGGCTCCTCTCGCAAAGGTCATCAA
60 GGTTATCAGCAATGCCTCATGCACCACCAACTGCCTTGCTCCTCTTGCAAAGGTCATCCA
XlGAPDH
LlGAPDH
121 CGACAACTTTGGCATTGTTGAGGGACTCATGACAACAGTCCATGCTTTCACTGCCACCCA
120 TGACAACTTTGGCATTGTAGAGGCCCTGATGACCACAGTCCATGCTTACACCGCTACCCA
XlGAPDH
LlGAPDH
181 GAAGACAGTGGATGGCCCATCAGGCAAGCTGTGGAGAGATGGCAGAGGTGCAGGTCAGAA
180 GAAGACCGTGGACGGACCATCTGGAAAGATGTGGCGTGATGGCAGAGGTGCAGGCCAGAA
XlGAPDH
LlGAPDH
241 CATTATTCCCGCCTCAACTGGTGCAGCAAAGGCTGTCGGAAAAGTTATCCCTGAGCTGAA
240 CATCATCCCAGCATCTACTGGTGCTGCTAAGGCTGTGGGCAAAGTCATCCCAGCCCTGAA
XlGAPDH
LlGAPDH
301 CGGAAAAATAACCGGAATGGCTTTCCGTGTCCCCACCCCAAATGTGTCCGTCGTGGATCT
300 TGGAAAGTGCACTGGTATGGCCCTCAGAGTTCCCACTCCCAATGTGTCAGTCGTTGACTT
XlGAPDH
LlGAPDH
361 GACCTGCCGCCTGCAGAAGCCGGCCAAGTACGATGACATCAAGG
360 GACTGCCCGTCTGGAGAAACCAGCCAAGTACGACGATATCAAGA
Figure 9. Sequence alignment of the middle portion of the L. laevis and X. laevis GAPDH
cDNAs. Approximately 400 bases of the cloned and sequenced L. laevis GAPDH cDNA
was aligned by CLUSTALW to the published sequence for the X. laevis GAPDH cDNA
(NM_001087098) and imported into BOXSHADE program. Black shading indicates
sequence identity while grey and no shading (white) indicates sequence differences. The
sequences aligned with 83% identity.
41
This L. laevis GAPDH sequence was then used to design additional primers for
the amplification of the corresponding 5’ and 3’ cDNA ends (Table 1). To amplify the 3’
end, LlGAPDH.F1 was used with the T7 vector primer to generate a 650 bp product
(Figure 10a). An aliquot of this initial PCR was then used in a nested PCR using the
internal LlGAPDH.F2 primer and the T7 vector primer, and a gradient was used for the
annealing step (58.8-65.0oC). In addition to the expected 600 bp product, multiple sized
products were evident in the stained gel (Figure 10b). In order to separate the 600 bp
product from the mixture for cloning purposes, an aliquot of the nested PCR was
electrophoresed on a low melt agarose gel and the agarose plug corresponding to the 600
bp region was removed. The agarose plug was melted at 50oC and subsequently ligated
into the pGEM-T Easy vector and transformed into E. coli as before. Plasmid purification
of overnight bacterial cultures was performed, and EcoR1 digested plasmids revealed the
correctly sized 600 bp products in the stained gel (Figure 10c). Several clones were sent
off for commercial sequencing. BLAST searches of the cloned sequences revealed that it
aligned to the 3' end of the X. laevis GAPDH cDNA with 78% sequence identity.
For the 5' cDNA end, the primer combination of LlGAPDH.R1 and T3 was used
to amplify an expected 800 bp GAPDH product, however multiple non-target products
were also amplified (Figure 11a). An aliquot of this initial PCR was then used as template
for a nested PCR using the internal primer LlGAPDH.R2 and the T3 vector primer. This
nested PCR resulted in an intensely staining band at the 700 bp ladder mark which
corresponded to the anticipated GAPDH size and with minor bands noted at 500 bp and
250 bp (Figure 11b). An aliquot of the nested PCR was used for ligation and
42
a.
1
L
2
3’
3
3’
1000 bp
650 bp
GAPDH
100 bp
b.
1
2
3
4
5
6
L
58.8
60.8
63.7
65.0
63.7
TA
1000 bp
600 bp
GAPDH
100 bp
c.
1
L
2
a
3
b
1000 bp
600 bp
GAPDH
100 bp
Figure 10. Cloning of the 3’ cDNA end of L. laevis GAPDH cDNA sequence. (a) Initial
PCR amplification of the 3' end using the gene specific primer LlGAPDH.F1 in
combination with the T7 vector primer (b) Nested PCR of first round PCR products using
the gene specific primer LlGAPDH.F2 in combination with T7 vector primer. Labels
below lane numbers indicate the gradient annealing temperatures used during
amplification. (c) EcoR1 restriction enzyme digest of cloned nested PCR products. L =
ladder, - = negative control, TA = annealing temperature, letters (a, b) = clones.
43
a.
1
L
2
5’
3
5’
1000 bp
800 bp
GAPDH
100 bp
b.
1
L
2
48.7
3
49.9
5
4
51.7
51.7
TA
1000 bp
750 bp
GAPDH
100 bp
c.
1
L
1000 bp
700 bp
2
a
3
b
4
c
5
d
6
e
7
f
8
g
9
h
GAPDH
100 bp
Figure 11. Cloning the 5’ end of the L. laevis GAPDH cDNA sequence. (a) Initial PCR
amplification using the gene specific LlGAPDH.R1 primer with T3 vector primer (b)
Nested PCR using first round PCR products and internal LlGAPDH.R2 primer with T3
vector primer. Annealing temperatures are listed below lanes; no template control is in
lane 5. (c) EcoR1 restriction enzyme digests of cloned nested PCR products. L = ladder;
TA = annealing temperature; letters (a, b, c, etc.) = clones.
44
transformation. Transformant plasmid DNA was purified as before and the EcoR1 digests
revealed several clones with the expected 700 bp product (Figure 11c). Several clones
were sent off for commercial sequencing. Interestingly, the BLAST searches of the
resulting sequences indicated they were from the bacterial species Bacillus pumilus.
Additional clones were subsequently sequenced, but each one aligned to the bacterial
species. Although the 5’ end of the L. laevis GAPDH sequence was not obtained, it was
deemed unnecessary to pursue for the design of qPCR primers since 2/3rds of the
sequence (66%) was determined.
Cloning of X. borealis GAPDH
For the first round of the X. borealis nested PCR strategy, the degenerate primer
GAPDH.dR1 was used in combination with the AP1 vector primer (Figure 12a). The
expected size for the PCR product was 970 bp which was observed in the stained agarose
gel in addition to several other bands found to be approximately 600 bp and 500 bp. This
initial PCR reaction was run at low stringency (50oC) to ensure amplification which
explains the additional PCR products.
A nested PCR strategy was then used to amplify an expected 600 bp product by
utilizing GAPDH.dR1 and the internal degenerate primer GAPDH.dF1. A 1/500 dilution
of the initial PCR reaction containing the 970 bp amplicon served as the starting template
for this nested PCR. In addition, a gradient was used for the annealing step (50oC, 52.9oC,
56.2oC) to optimize the annealing temperature and decrease non-target amplification. The
stained gel of the nested PCR revealed lone bands at the 600 bp ladder mark for each of
45
a.
1
L
2
GAPDH
3
-
1000 bp
970 bp
GAPDH
100 bp
b.
1
L
2
50.0
3
52.9
4
56.2
5
50.0
TA
1000 bp
600 bp
GAPDH
100 bp
c.
1
L
2
f
3
g
4
h
5
i
6
j
7
k
8
l
1000 bp
600 bp
GAPDH
100 bp
Figure 12. Degenerate PCR of the X. borealis GAPDH cDNA. (a) First round PCR using
the GAPDH.dR1 primer in combination with the AP1 vector primer. (b) Second round
nested PCR with internal GAPDH.dF1 and GAPDH.dR2 (c) EcoR1 restriction enzyme
digests of cloned nested PCR products. L = ladder; - = negative control; TA = annealing
temperature; letters (f, g, h, etc.) = clones.
46
the annealing temperatures (Figure 12b).
The nested PCR reactions for X. borealis GAPDH were pooled together, ligated,
transformed, and colony transformant plasmids purified for analysis by EcoRI digestion.
Four clones were identified to contain the appropriately sized 600 bp cDNA (Figure 12c).
One clone was subsequently sent off for commercial sequencing using the sp6 vector
primer. After receiving the sequence information, a BLAST search was performed which
returned with the best match to the X. laevis GAPDH cDNA sequence. The 586 bp X.
borealis cDNA sequence aligned to the middle portion of the X. laevis GAPDH cDNA as
intended with 89% identity (Figure 13).
This X. borealis GAPDH sequence was then used to design additional primers for
the amplification of the corresponding 5’ and 3’ cDNA ends (Table 1). To amplify the 3’
end, XbGAPDH.F1 was used with the AP1 vector primer to generate a 600 bp product
(Figure 14a). An aliquot of this initial PCR was then used in a nested PCR using the
internal XbGAPDH.F2 primer and the AP1 vector primer to generate a product 550 bp in
length (Figure 14b). A small amount of the 800bp product persisted, but the discrepancy
in the amounts was so great that the cloning vector was thought to likely preferentially
ligate the smaller GAPDH product. PCR products were subsequently ligated,
transformed, and colony transformant plasmids purified for analysis by EcoRI digestion
(Figure 14c). Several positive clones were sent off for commercial sequencing. BLAST
searches of the cloned sequences revealed that they aligned to the 3' end of the X. laevis
GAPDH cDNA with 86% sequence identity.
For the 5' cDNA end, the primer combination of XbGAPDH.R1 and AP1 was
47
XlGAPDH
XbGAPDH
1 AGCAGATGCCCCCATGTTTGTAGTTGGCGTGAACCATGAGAAATATGAGAACTCTCTTAA
1 TGCTGACGCACCAATGTTCGTTGTTGGAGTGAACCATGACAAATATGACAACTCTCTTAC
XlGAPDH
XbGAPDH
61 AGTTGTTAGCAATGCTTCCTGCACTACAAACTGTCTGGCTCCTCTCGCAAAGGTCATCAA
61 AGTTGTGAGCAATGCATCCTGCACAACAAACTGCTTGGCTCCTCTTGCAAAGGTCATAAA
XlGAPDH
XbGAPDH
121 CGACAACTTTGGCATTGTTGAGGGACTCATGACAACAGTCCATGCTTTCACTGCCACCCA
121 CGACAATTTTGGCATTGTTGAGGGACTAATGACAACTGTCCATGCTTACACTGCTACCCA
XlGAPDH
XbGAPDH
181 GAAGACAGTGGATGGCCCATCAGGCAAGCTGTGGAGAGATGGCAGAGGTGCAGGTCAGAA
181 GAAGACTGTGGATGGCCCATCAGGGAAGCTGTGGAGAGATGGAAGAGGTGCTGGTCAGAA
XlGAPDH
XbGAPDH
241 CATTATTCCCGCCTCAACTGGTGCAGCAAAGGCTGTCGGAAAAGTTATCCCTGAGCTGAA
241 CATCATCCCCGCCTCCACTGGTGCAGCAAAGGCTGTAGGAAAGGTTATCCCTGAGCTGAA
XlGAPDH
XbGAPDH
301 CGGAAAAATAACCGGAATGGCTTTCCGTGTCCCCACCCCAAATGTGTCCGTCGTGGATCT
301 TGGCAAACTCACAGGAATGGCTTTCCGTGTCCCAGTCCCTAATGTGCCCGTTGTGGATCT
XlGAPDH
XbGAPDH
361 GACCTGCCGCCTGCAGAAGCCGGCCAAGTACGATGACATCAAGGCCGCCATTAAGACTGC
361 GACCTGCCGCCTGGAGAAGCCTGCAAAGTACAGTGATATCAAGGCTGCGGTTAAGGCTGC
XlGAPDH
XbGAPDH
421 ATCAGAGGGCCCAATGAAGGGAATCCTGGGATACACACAAGACCAGGTTGTCTCCACTGA
421 GTCCGAGGGACCAATGAAGGGAATCCTGCAATACACTGAAGACCAGGTTGTCTCCACTGA
XlGAPDH
XbGAPDH
481 CTTCAATGGTGACACTCACTCCTCCATCTTTGATGCTGATGCTGGAATTGCCCTGAATGA
481 CTTCAATGGCTGCACTCATTCCTCCATCTTTGATGCTGATGCTGGAATTGCACTGAATGA
XlGAPDH
XbGAPDH
541 AAACTTTGTGAAACTGGTTTCCTGGTATGATAATGAATGCGGCTAC
541 AAACTTTGTGAAGCTGGTTTCCTGGTAGGACAACGAATGCGGGTAT
Figure 13. Sequence alignment of the middle portion of the X. borealis and X. laevis
GAPDH cDNAs. Approximately 600 bases of the cloned and sequenced X. borealis
GAPDH cDNA was aligned by CLUSTALW to the published sequence for the X.. laevis
GAPDH cDNA (NM_001087098) and imported into BOXSHADE program. Black
shading indicates sequence identity while grey and no shading (white) indicates sequence
differences. The sequences aligned with 89% sequence identity.
48
a.
1
2
L
3’
3
-
1000 bp
600 bp
GAPDH
100 bp
b.
1
L
3
-
2
3’
1000 bp
GAPDH
550 bp
100 bp
c.
1
L
2
a
3
b
4
c
1000 bp
550 bp
GAPDH
100 bp
Figure 14. Cloning the 3’ end of the X. borealis GAPDH cDNA sequence. (a) Initial PCR
amplification using the gene specific primer XbGAPDH.F1 in combination with the AP1
vector primer. (b) Nested PCR using first round PCR products and the gene specific
primer XbGAPDH.F2 in combination with AP1 vector primer. Labels below lane
numbers indicate the gradient of annealing temperatures used during amplification. (c)
EcoR1 restriction enzyme digests of cloned nested PCR products. L = ladder; - = negative
control; TA = annealing temperature; letters (a, b, c) = clones.
49
used to amplify an expected 800 bp GAPDH product, however multiple non-target
products were also amplified (Figure 15a). An aliquot of this initial PCR was then used as
template for a nested PCR using the internal primer XbGAPDH.R2 and AP1 vector
primer using a temperature gradient (54.9oC, 56.6 oC, and 57.8 oC ) to limit the generation
of non-target products. This nested PCR resulted in an intensely staining band at the 700
bp ladder mark corresponding to the anticipated GAPDH size with minor bands noted at
450 bp and 350 bp (Figure 15b). An aliquot of the nested PCR was used for ligation and
trasformation into E. coli. Plasmid DNA was purified as before and the EcoR1 digests
revealed two clones with the expected 700 bp product (Figure 15c). The clones were sent
off for commercial sequencing. BLAST searches of the cloned sequences revealed that
they aligned to the 5' end of the X. laevis GAPDH cDNA with 91% sequence identity
Thus, the full length X. borealis GAPDH cDNA sequence (1185 bases) was assembled
from the 5’, middle, and 3’ sequenced regions and aligned to X. laevis (Figure 16).
qPCR Primer Design
Each primer to be used in future qPCR assays was designed as close to optimal
parameters given sequence constraints to find unique regions for each clone. All primers
were designed with a melting temperature (Tm) of 60oC according to Primer Select
software (DNASTAR, Madison, WI). Primer lengths ranged from 20 to 36 bases so as to
be close to this Tm, and centered around regions that were divergent to other clones. Each
primer was designed with the goal of having the last base on the 3’ end of the primer
being either a cytosine or a guanine for stability to increase the chances that Taq
50
a.
1
L
3
-
2
5’
1000 bp
800 bp
GAPDH
100 bp
b.
1000 bp
1
2
3
4
5
L
54.9
56.6
57.8
57.8
700 bp
TA
GAPDH
100 bp
c.
1000 bp
700 bp
1
2
3
4
5
6
7
8
9
L
h
i
j
k
l
m
n
o
GAPDH
100 bp
Figure 15. Cloning the 5’ end of the X. borealis GAPDH cDNA sequence. (a) Initial PCR
amplification using the gene specific primer XbGAPDH.R1 in combination with the AP1
vector primer. (b) Nested PCR using first round PCR products and internal
XbGAPDH.R2 primer and AP1 vector primer. (c) EcoR1 restriction enzyme digests of
cloned nested PCR products. L = ladder; - = negative control; TA = annealing
temperature; letters (h, i, j, etc.) = clones.
51
XlGAPDH
XbGAPDH
1 -----------------------CAGACTTCAGAGG--GGTTGATAA---ACCAAATCAA
1 TCCATCCTAATACGACTCACTATAGGGCTCGAGCGGCCGCCCGGGCAGGTACCAAACCAA
XlGAPDH
XbGAPDH
33 GTGACTACAAAAATGGTGAAGGTTGGAATTAACGGATTTGGCTGTATTGGGCGCCTGGTG
61 GGGACCACAAAAATGGCAAAGGTTGGAATCAATGGATTTGGCCGCATTGGGCGCCTGGTG
XlGAPDH
XbGAPDH
93 ACCCGCGCTGCCTTTGATAGCGGCAAAGTTCAAGTCGTTGCTATCAATGACCCCTTCATC
121 ACCCGCGCTGCCTTTGATAGCGGCAAAGTTCAAGTCGTCGCCATCAATGACCCCTTCATC
XlGAPDH
XbGAPDH
153 GACTTGGACTACATGGTGTACATGTTCAAGTATGACTCCACCCACGGCCGCTTTAAGGGA
181 GACTTGGACTATATGGTTTACATGTTCAAGTATGACTCCACCCACGGCTGCTTTAAGGGA
XlGAPDH
XbGAPDH
213 ACCGTTAAGGCTGAGAATGGCAAGCTGATCATCAATGACCAAGTCATCACCGTCTTCCAG
241 ACAGTGAAGGCTGAGAATGGAAAGCTGGTCATCAATGGGCATGAAATCACCGTTTTCCAG
XlGAPDH
XbGAPDH
273 GAGCGTGACCCCTCCAGCATTAAGTGGGGAGATGCTGGTGCCGTGTATGTGGTGGAATCT
301 GAGCGTGATCCCTCAAACATTAAGTGGGGCGATGCTGGTGCCATGTATGTGGTGGAATCT
XlGAPDH
XbGAPDH
333 ACTGGAGTCTTCACAACCACAGAGAAGGCCTCTCTGCACTTGAAGGGAGGTGCCAAGCGT
361 ACTGGAGTCTTCACAACCAAAGACAAGGCCTCTATGCACTTGAAGGGAGGAGCCAAGCGT
XlGAPDH
XbGAPDH
393 GTCGTTATCTCCGCCCCCTCAGCAGATGCCCCCATGTTTGTAGTTGGCGTGAACCATGAG
421 GTCATCATCTCCGCCCCCTCAGCAGATGCCCCCATGTTTGTTGTTGGAGTGAACCATGAC
XlGAPDH
XbGAPDH
453 AAATATGAGAACTCTCTTAAAGTTGTTAGCAATGCTTCCTGCACTACAAACTGTCTGGCT
481 AAATATGACAACTCTCTTACAGTTGTGAGCAATGCATCCTGCACAACAAACTGCTTGGCT
XlGAPDH
XbGAPDH
513 CCTCTCGCAAAGGTCATCAACGACAACTTTGGCATTGTTGAGGGACTCATGACAACAGTC
541 CCTCTTGCAAAGGTCATAAACGACAATTTTGGCATTGTTGAGGGACTAATGACAACTGTC
XlGAPDH
XbGAPDH
573 CATGCTTTCACTGCCACCCAGAAGACAGTGGATGGCCCATCAGGCAAGCTGTGGAGAGAT
601 CATGCTTACACTGCTACCCAGAAGACTGTGGATGGCCCATCAGGGAAGCTGTGGAGAGAT
XlGAPDH
XbGAPDH
633 GGCAGAGGTGCAGGTCAGAACATTATTCCCGCCTCAACTGGTGCAGCAAAGGCTGTCGGA
661 GGAAGAGGTGCTGGTCAGAACATCATCCCCGCCTCCACTGGTGCACCACAGGCTGTAAGA
XlGAPDH
XbGAPDH
693 AAAGTTATCCCTGAGCTGAACGGAAAAATAACCGGAATGGCTTTCCGTGTCCCCACCCCA
721 AAGGTTATCCCTGAACTGAATGGCAAACTCACAGGAATGGCTTTCCGTGTCCCATTCCCT
XlGAPDH
XbGAPDH
753 AATGTGTCCGTCGTGGATCTGACCTGCCGCCTGCAGAAGCCGGCCAAGTACGATGACATC
781 AATGTGTCCGTTGTGGATCTGACCTGCCGCCTGGAGAATCCTGCAAAGTACAGTGATATC
XlGAPDH
XbGAPDH
813 AAGGCCGCCATTAAGACTGCATCAGAGGGCCCAATGAAGGGAATCCTGGGATACACACAA
841 AAGGCTGCGGTTAAGGCTGCGTCCGAGGGACCAATGAACGGAATCCTGCAATACACTGAA
XlGAPDH
XbGAPDH
873 GACCAGGTTGTCTCCACTGACTTCAATGGTGACACTCACTCCTCCATCTTTGATGCTGAT
901 GACCAGGTTGTCTCCACTGACTTCAATGGCTGCACTCATTCCTCCATCTTTGATGCTGAT
XlGAPDH
XbGAPDH
933 GCTGGAATTGCCCTGAATGAAAACTTTGTGAAACTGGTTTCCTGGTATGATAATGAATGC
961 GCTGGAATTGCACTGAATGAAAACTTTGTGAAGCTGGTTTCCTGGTATGATAACGAATGC
XlGAPDH 993 GGCTACAGCAACCGTGTTGTGGATCTTGTGTGTCACATGGCATCTAAGGAATAAGCACTT
XbGAPDH 1021 GGCTACAGCCACCGTGTTGTGGATCTTATGTGTCACATGGCATCTCAGGAATAAACACCT
XlGAPDH 1053 GTCACCT-GTCAACCCCTCTTCT--CACTGAAGGGGTCCAGAGTCGCCCATCCTGCTAGT
XbGAPDH 1081 GTCA----ATCAACCCCTCTTCT--CTCTGAAGGA--CCATAGTCAACCCATCTACTACT
52
XlGAPDH 1110 CTGTC------ACTGTTTCTGTGTTCCTAAATAAAACCATGATGAAACATTXbGAPDH 1133 CTGTCTGTGTCGCTGTTTCTGTGTTACTAAATAAAACAATGATGAAACAGCA
Figure 16. Sequence alignment of the X. borealis and X. laevis GAPDH cDNAs. The full
length X. borealis GAPDH cDNA was aligned with X. laevis GAPDH cDNA
(NM_001087098) by CLUSTALW and imported into BOXSHADE. Sequences aligned
with 91% sequence identity.
53
polymerase will amplify the specific product. However, care was taken to limit the last
five bases at the primer’s 3’ end to have only two or three cytosine or guanine bases to
ensure there is no non-specific GC clamping that could lead to amplification of nontarget products. The optimal amplicon size (PCR product) for each of the designed primer
pairs was in the range of 100-150 bases. In addition, the amplicon was to contain
approximately 50% GC content since melting curves will be performed at the end of
qPCR runs. All designed qPCR primer pairs were then tested using conventional PCR
(endpoint assay) to assess their performance in the next phase of experimentation.
Lepidobatrachus laevis qPCR primers
In order to design specific qPCR primers for targeted genes, it was essential to
find regions that were unique to particular cDNAs. For the L. laevis ZPC genes, the six
full length ZPC cDNAs that were previously sequenced were globally aligned using the
CLUSTALW software program and then imported into the shading program
BOXSHADE to reveal sequence differences (Figure 17). The aligned order (Llzpc.3,
Llzpc.6, Llzpc.1, Llzpc.2, Llzpc.5, and Llzpc.4) demonstrates visually which sequences
are more related to each other since sequences listed first in the alignment have the
highest level of similarity to each other followed by the more divergent sequences. To
further assess the relationships of these ZPC cDNAs, a distance-based gene tree was
generated (Figure 18a), and a comparison of their pairwise nucleotide identities was
performed (Table 2a). These analyses revealed that the highest level of identity exists
between Llzpc.3 and Llzpc.6 at 90% whereas the lowest level of identity found was for
54
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1
1
1
1
1
1
AGCACGAGGACACTGACATGGACTGAAGGAGTAGAAATTGTGTGACTTTTCCTGTAGTCA
---------------------------------------GTGTGACTTTTCCTGTAGTCA
-----------------------------------------GTGACTTCTCCTGCGGTCA
---------------------------------------GTGTGACTTCTCCTGCAGTCA
---------------------------------------GTGTGACTTCTCCTGTAGTCA
--------------------------------------AGTGCTATTCTGAATAGAGTCA
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
61
22
20
22
22
23
GGATGGAGCTGTGGA------TCAGGTGGAGTTGTCTATTAGTGGTCCTGATCTATGGAG
GGATGGAGCTGTGGA------TCAGGTGGAGTTGTCTATTAGTGGTTCTGATCTATGGAG
GGATGGAGCTGTGGA------TCAGGTGGAGTTGTTTATTAGTGGTTCTGATCTATGGAG
GGATGGAGCTGTGGA------TCAGGTGGAGTTGTCTATTAGTGGTTCTGATCTATGGAG
GGATGGAGCTGTGGA------TCAGGTGGAGTTGCCTATTAGTGGTCCTGATCTATGGAG
GAATGGGTTTTTGGAGATTATCCTGGTGGCCTTTGATGGTAGGAGTGATCTTCTGCAGCT
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
115
76
74
76
76
83
CAGGCTTTAGCAGAGCTTTGGTTAGACCTCGGCGCCAGTCAGAC--ACT-TGGTGGAGGA
CAGGCTTTAGCAGAGCCTTGGTTAGACCTCGGCGCCAGTCAGAC--ACT-TGGTGGAGGA
CAGGCTTTAGCAGTGCTTTGGTTAGACCCCGGCGCCAGTCAGAC--ACT-TGGTGGAGGA
CAGGCTTTTGCAGAGCTTTGGTTAGACCCCGGCGCCAGTCAGAC--ACT-TGGTGGAGGA
CAGGCTTTAGCAGAGCCTTGGTTAGACCTCGGCGCCAGTCAGAC--ACT-TGGTGGAGGA
TGTGCCTTGAGGTTTGTAGATCTAATGTCCTGAGTAGACCACGCCGACAACAGTGGAGTA
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
172
133
131
133
133
143
GTTATCAGCCTGGATGGGGATCTCCTAGAGGACTTGGACAACCTGCATCTGGAGTGGGGT
GTTATCAGCCTGGATGGGGATCTCCTAGAGGACTTGGACAACCTGTATCTGGAGTGGGCT
GTTATCAGCCTGGATGGGGATCTCCTAGAGGACATGGACAACCTGTATCTGGAGTGGGCT
GTTATCAGCCTGGATGGGGATCTCCTAGAGGACTTGGTCAACCTGCATCTGGAGTGGGGT
GTTATCAACCTGGATGGGGATCTCCTAGAGGACTTGGACAACCTGTATCTGGAGTAGGCT
ACCAGCAACCTGGTTGGGGATCTCC---AAGATCT------TCTGCA--TGGAATGCACA
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
232
193
191
193
193
192
CTCCTAGAGGAAGCTCTTGGTATCCGGCTCAGTCAGTGTCTGGTTTTGGGGCTTTAAGAG
CTCCTAGAGGAAGCTCTTGGTATCCGGCTCAGTCAGTGTCTGGTTTTGGGGCTTTAAGAG
CTCCTAGAGGAAGCTCTTGGTATCCGGCTCAGTCAGTGTCTGGTTTTGGGGCTTTAAGAG
CTCCTAGAGGAAGCTCTTGGTATCCAGCTC---------------------------GAG
CTCCTAGAGGAAGCTCTTGGTATCCAGCTC---------------------------GAG
GTCC-AGGAGATATGGATGGGGTTCTGTTC------------------------------
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
292
253
251
226
226
221
GTGCTCAACCTGTGTCCGGATGGGGCT-CCAGGTTTCCCGGAAGAGA---TGATCAGACC
GTGCTCAGCCTGTATCTGGATGGGGCT-CCAGGTTTCCCGGAAGAGA---TGATCAGACC
GTGCTCAGCCTGTGTCCGGATGGGGCT-CCAGGTTTCCCGGAAGAGA---TGATCAGACC
GTGCTCAGCCTGTGTCCGGATGGGGCT-CCAGGTTTCCTGGAAGAGA---TGATCAGACC
GTGCTCAGCCTGTGTCCGGATGGGGCT-CCAGGTTTCCTGGAAGAGACGATGATCGGTCC
AATCTCTGTCAG-GCTGGGACAACGCTGCTAGATATTCCAGTGGGGC---CGCTAATCTC
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
348
309
307
282
285
277
CGACAGCTTCCTCCATT------CTCTCCTATCAATGTGCAGTGTGGTGAGGACAGGATG
CGACAGCTTCCTCCATTTCCATCCTCTCCTATCAGTGTGCAGTGTGGTGAGGACAGGATG
CGACAGCTTCCTCCATT------CTCTCCTATCAGTGTGCAGTGTGGTGAGGACAGGATG
CGACAGCTTCCTCCATCTCCATCCTCTCCTATCAGTGTGCAGTGTGGTGAGGACAGGATG
CGACAGCTTCCTCCATCTCCATCCTCTCCTATCAGTGTGCAGTGTGGTGAGGACAGGATG
CGACAGATGCCACCCCA---GTGGTCACCAGTCACTGTGCAGTGCAATGAAGACAACATG
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
402
369
361
342
345
334
GTGGTGATGGTGAAGAGAGACTTCTATGGTAATGGTAAGCTGGTGAAGCCCTCAGACCTG
GTGGTGATGGTGAAGAGAGACTTCTATGGTAATGGTAAGCTGGTGAAGCCCTCAGACCTG
GTGGTGATGGTGAAGAGAGACTTCTATGGTAATGGTAAGCTGGTGAAGCCCTCAGACCTG
GTGGTGATGGTGAAGAGAGACTTCTATGGTAATGGTAAGCTGGTGAAGCCCTCAGACCTG
GTGGTGATGGTGAAGAGAGACTTCTATGGTAATGGATATTTGGTGAAGCCCTCAGACCTG
AGGCTGACTGTGAATAGAGACCTGTTTGGCACTGGGAAATTGGTGAAAGTTTCAGATCTA
55
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
462
429
421
402
405
394
ACCCTGGGA------TCCTGCAGACCTGGAACACAAACTACTGATCCTAATGTGGTCTTT
ACCCTGGGA------TCCTGCAGACCCGGTGTACAGACTACAGATACTACGGTGGTCTTT
ACCCTGGGA------TCCTGCAGACCTGGAGCACAAACTACTGATCCTAATGTGGTCTTT
ACCCTGGGA------TCCTGCAGACCTGGTGTGCAGACTACAGATACTACAGTGGTCTTT
ACTTTAGGC------TCTTGTAGACCTGGACCCCAGAGTTCGGACACCGTGGTGGTCTTT
AGCCTGGGACCCCAATCTTGCCCTCCTGGTCCCCAGAATGAGGATGATGTAGTGTACTTT
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
516
483
475
456
459
454
GAAAATGGCCTTCAAGAATGTGGTAGTACCTTGGAGATGACTCAAGACTGGCTCATCTAC
GAAAATGGCCTTCAAGAATGTGGGAACATCCTAGAGATGAGACAAGACTTGCTGATCTAC
GAAAATGGCCTTCAAGAATGTGGCAGCAACCTGGAGATGACTCGAGACTGGCTCATCTAC
GAAAATGGCCTTCAAGAATGTGGAAGCAGCTTAGAGATGACTGCAGACTTTCTTCTGTAT
GATAATAACGTCCAGGCATGTGGCAGCACTCTACAGATGACTTCAGACTTCTTGATCTAC
CAGATTGGGCTTCAGGATTGTGGAAACCGTGTGCAGATGACGGCTGACTTGTTGACCTAC
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
576
543
535
516
519
514
AAAGTCAACCTGCAGTATACTCCCACCTCCTCCAGCAATGTGCCCATCACCCGGTTCAAC
CGCTCTATCCTACAATACACCCCCACTTCCTCCAGGAATGTGCCCATTATCCGGTCCAAC
AAGATCAACCTACAGTACAGCCCTACATCCTCCAGCAATGTACCCATCATCAGGTCCAAC
GAGACTATTCTGACCTATAGGCCAAC---CCCTGGTAATGTGCCCATTATCAGGACCAAC
AGAACAGTATTAAATTACAATCCAAT---TTCCAACAACGCTGTCGTAATAAGGTCAAAT
ACCACAACTCTGAACTACAACCCGACTGCCAACAGGAACAGTCCAATCATCCGAACCAAT
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
636
603
595
573
576
574
CCCGCTCTGGTTCCCATCCGGTGTTACTACCCCCGACATGGCAATGTGAGCAGTAAAGCC
GCTGCTGTGGTTCCCATTCAGTGCTTCTATCCAAGACATGGCAATGTGAGCAGCAAAGCA
CCGGCTTTGGTTCCCATCCAGTGTTACTACTCCAGACATGGCAATGTGAGCAGCAAAGCG
CCTGCTGCAGTGCCTATCCAGTGTGTCTACTTTAGACATGGGAATGTGAGCAGCAAGGCT
CCTGCTGTGGTTCCCATCATGCGTTATTATCCCCGGCATGGCAATGTGAGTAGCAAAGCA
TCAGCAACTGTTTCCATCCAGTGCAATTATCCAAGGCATGGTAATGTGAGCAGTAAAGCT
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
696
663
655
633
636
634
ATCAAGCCAACATGGGTTCCCTTCAGCACCACGGTGGCCACAGAAGAGCGGCTGTCCTTT
GTCAAGCCAACATGGGTTCCCTTCAGCACCACGGTGACCACAGAAGAGCGGCTGTCCTTT
GTCAAGCCAACATGGGTTCCCTTCAGCACCACTGTGACCACAGAAGAGCGGCTGTCCTTC
ATCAAACCAACATGGGCTCCATTTAGTACCACTGTGACCTCTGAGGAGCGGCTGGCTTTC
ATCGGGCCAACGTGGGCTCCATTTAGTACCACAGTCTCTACAGAAGAGAGGTTGGCCTTC
GTGAAACCCACATGGATTCCTTTCCACACCACCATATCCTCAGAGGAACGCTTGTCCTTC
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
756
723
715
693
696
694
GCATTACGTCTAATGACTGAGGACTGGAGCGCTCCCAGGCCATCGCTGGTCTTCCAGCTT
GCATTACGTCTAATGACTGAGGACTGGAGCGCTCCCAGGCCATCACTGGTCTTCCAGCTT
TCCTTGCGGCTAATGACAGAGGACTTGAACGCTCCTAGGCCATCACTGGTCTTCCAGCTT
TCCTTGAACTTGATGACTGATGGATGGGGAGCTCCCAGGACTTCTTCAGTCTTCCAGCTT
TCCTTGTACCTGATGACCGATGACTGGAGTAGTCGTAGAGCTTCCTCAATCTTCCAACTT
TCTCTGATGTTGATGAATGATGACTGGAGTGCACCAAGGTCTTCCTCAATCTTCAGTCTT
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
816
783
775
753
756
754
GGTGACATGTTCTACATAGAAGCCTCTCTGGACACTCAGAACCACCTCCCGATGACCCTT
GGTGACATGTTCTACATAGAAGCCTCTCTGGACACTCAGAACCACCTCCCGATGACCCTT
GGTGACATGTTCTACATAGAAGCCTCTCTGGACACTCAGAACCACCTCCCGATGACCCTT
GGGGACATGTTCTACATAGAGGCTTCAGTGGACACCCAGAACCACATCCCCATGATGCTG
GGGGACGTCTTCAACATAGAAGCCTCAGTGGAAACGGAGAATCATATCCCCATGACCTTG
GGAGAAATGTTCTACATTGAGGCCTCCCTTAACCTCGGTAATCACGTAGAAATGACCCTG
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
876
843
835
813
816
814
TTTGTTGATAGTTGTGTGGCCACCATTACTCCAGATGCGACCTCCAATCCTCATTATGAC
TTTGTTGATAGCTGTGTGGCCACCATAACTCCAGATGCGACCTCCAATCCTCATTATGAC
TTTGTTGATAGCTGTGTGGCCACCATAACTCCGGATGCAACCTCCAATCCTCATTATGAC
TTTGTTGACAGCTGTGTTGCCACTACTACATCCAATGTCAACTCCAACCCTCGTTATGAG
TTCGTTGACTCCTGTGTGGCCACCACTACATCAGATGTCAATTCCAACCCTCGTTACGAG
TTTGTTGATAGCTGTGTAGCTACACTGACTTCTGATGTCAACTCCATCCCTCGATATGAG
56
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
936
903
895
873
876
874
ATCATTGCTTATAATGGGTGCCTGATGGATGGGATGCAAGATGATTCTTCTTCAGTCTTT
ATCATTGCTTATAATGGGTGCTTAATGGATGGGATGCAAGAAGATTCCTCTTCAGTCTTT
ATCATTGCTTATAATGGGTGCTTGATGGATGGATTGCAAGAAGATTCCTCCTCTGCGTTT
TTCATAGCTTACAATGGGTGCCTGGTGGATGGTAAGGAAGAAGATGCTTCGTCAGCCTTT
ATTGTAGCCTTTTATGGGTGCCTGGTGGATGGGACACAAGACGATTCTTCTTCAGCCTTC
ATCATTGGGTCATATGGGTGTCTGCTTGATGGAAAACAGGAAGACTCCTCTTCATCCTTT
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
996
963
955
933
936
934
GATTCCCCAAGACCTCAAGCTGACAAACTTCGCTTCATGGTTGATGCCTTCAGGTTCACA
GATTCCCCAAGACCTCAAGCTGACAAACTTCGCTTCATGGTTGATGCCTTCAGGTTCACA
---TTGCAGAGACCCCAGGCTGACAAACTCCATTTCATGGTTGATGCCTTCAGGTTCATT
AGATCTCCAAGACTTCAACCAGACAAACTGCAGTTCATGGTTGATGCCTTCAGGTTTACT
AGATCTCCAAGGTCTCAACCAAATAAGATCCAGTTCATGGTCGATGCCTTCCGATTTATT
AAGGCTCCAAGGTCGCAGGCAAGCAAGCTCCAGTTCATGGTTGATGCCTTTAGGTTCAGA
Llzpc.3 1056 GACAGTCCTGTCTCTACGATCTACATTACCTGTGCTCTGAGAGCTGCTGCCATCAACCAG
Llzpc.6 1023 GACAGTGCTGTCTCTACGATCTATATTACTTGTTCTCTGAGAGCTGCTGCCATCAACCAG
Llzpc.1 1012 GACAGTGACCTTTCTACAATCTATATTACCTGTTCTCTGAGAGCTGCTGCCATCAACCAG
Llzpc.2 993 GCTTCAGATGTCTCATTGATCTATATTACCTGCCAACTAAGAGCAGTGGCTGCCTCCCAG
Llzpc.5 996 GAGACAGATGCCTCCACAATCTACATCACCTGTTCTCTAAGAGCAGCAGAAGCCACCCAG
Llzpc.4 994 GACTCGGATCTGTCAACTATTTATATTACCTGCACCTTAAGAGCTGCCTCAGCTACTCAG
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1116
1083
1072
1053
1056
1054
ACCCCTGATCCAATGAACAAAGCCTGCTCCTACAACAAGGTCTCTAGCGGCTGGTTACCT
ACCCCTGATCCAATGAACAAGGCCTGCTCCTACAACAAGGCAACTAGCAGTTGGTCTCCT
ACCCCTGATCCAACGAACAAGGCCTGCTCCTACAACAAGGCTACTAGCAGTTGGTCTCCT
GTCCCGGATCCCAAAAACAAGGCCTGTTCCTATAGCAAAACATCATCCAGGTGGTCTCCA
CCTCCTGATCCAATGAACAAGGCCTGCTCCTACAACAAGGCTACTAGAAGCTGGTCTCCT
GCTCCAGATTCTACAAACAAGGCTTGTTCATTCGATAAAACCAGGAACATGTGGACACCA
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1176
1143
1132
1113
1116
1114
GTGGAAGGTCCAAGTGGGATCTGCCAGTGCTGCACCACTGGGAACTGTGCCACTGCTGCA
GTGGAAGGTCCAAGTGGGATCTGCCAGTGCTGCACCACCGGGAACTGTGCCACTGCTGCA
GTGGATGGTCCAAGTGGGATCTGCCAGTGCTGCACCACCGGGAACTGTGCCACTGCTGCA
GTAGAAGGTTCTGCTGGTATCTGTCAATGCTGTGACACTGGTGACTGTG--ATAGATTGG
ATTGAGGGTCCCAATGATATCTGCCGCTGCTGTGAGTCCGGGAACTGTGCTGCTCCTCTT
CTGGAAGGCCCAAGTAACATCTGTTCCTGCTGTGAAACTGGGCTGTGTTCCCCATTTGGA
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1236
1203
1192
1171
1176
1174
GGCCAGAGAACAGCATGGGGCTCGTCTCCTGGGAGGCACAGAGGATTTGGGAAGCGAGAT
GGCCAGAGAACAGCATGGGGCTCATCCCCTGGGAGGCACAGAGGATTTGGGAAGAGAGAT
GGCCAGAGAACAGCATGGGGCTCATCTCCTGGGAGGTCCAGAGGATTTGGGAAGAGAGAT
GCTCATCAATTGGAATGGGGC----------AAAGAATTGGAAAAAGGGAAATTGCAGAA
GGCCAAACCAGAAGATGGGGCACAATATATGGAGGCTCAAGAGGGATTGGGAAGAGAGAA
GGTCAGACCCGAAGACTGGATGATTACTATCCTAGGTCAAGAAGAATTGGCAAAAGAACT
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1296
1263
1252
1221
1236
1234
GTTGGCTTTCCTGTAGAGAAACACGGCATGGCCACACTGGGACCTCTTCTAGTGACTGGA
GTTGGTTTTCCTGTAGAGAAAAACGGCATGGCCACATTGGGACCTCTTCTAGTGATTGGA
GTTGGTTCTCATCTGGAGAAACACGGCATGGCCACACTGGGACCTCTTCTAGTGATTGGA
GGTTCCCATCATTCAGTAGAACATGGACTGGCTGTTCTAGGTCCTCTGCTTGTTACTGGA
ATTGACCATCGTCCAGAGGAGCATGCTATGGCCACACTCGGCCCTCTACTGGTCATCGGT
GTGGA---------AGAGCCAACTCTACAAGCAACACTTGGGCCCCTGTATCTCAT----
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1356
1323
1312
1281
1296
1281
GCTGGGCCTAACCAGGTC---TCCGGAGCGGGAACCTCCCAAGCTTCCAGGATGACTGCA
GCTGGGCCTAACCAGGTC---TCCGGAGCAGGAACCACCCAAGCTTCCAGGATGACTGCA
GCTGGGCCTAACCAGGTC---TCTGAAGCGGGAACTGCCCGAGCTTCCAGGATGACTGCA
CCAGTGAAGGAGTCTCCC---CCTGTATCAGAACATCTCCAGGCTTCCAGAATGAT---G
GCTGAGAAGAACCACGTGGAATCCATTGCAGAACGTGTCCAGACTTCAAGAGTCCCTGAA
-----GAATGACTACCCC---TACAAGACACTGGCCCATCAGGAGCCCCGGGACAT----
57
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1413
1380
1369
1335
1356
1329
GGACAGGAACCTCTACAGCTGTGGATGCTGGTGGCCATCGGCTCAGTCTCTTCAGTAGTT
GGACAGGAACCTTTACAGCTGTGGATGCTGGTGGCCATTGGCTCTGTCTCTTCAGTAGTT
GAACAGGAACCTCTACAGCTGTGGATGCTGGTGGCCATCGGCTCTGTCTCTTCAGTAGTT
GACTCCGCACAGGTGGAACTCTGGGTCTTGGTTTCCGTCTGTTCTTTTAGTTTGGTTGTT
GAGTCCCAACCCTTAGAGCTGTGGATGTTGGTGGCCATCGGTTCTGTCAGTGTGGGGATT
-GGCAGTCAGACACTGGACTGTG----TTGGCATCTGTTAGTTTGGTTGTT---GTTGTC
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1473
1440
1429
1395
1416
1381
GTTGCCATTGCTCTTACTATTGCTGGAAAATGTCTTCTGAAAAGATTATCCCACAAAGAA
GTTGCCATTGCTCTTACTATTGCTGGAAAATGTCTTCTGAAAAAACTATCCCACAAAGAA
GTTGCCGTTGCTCTTACTATTGCTGGAAAATGTCTTCTGAAAAGATTTGTTCACCAATAG
TTAATACTTGGTCTTGCTCTGACTGTGAAATGTGCTGTAAAGAAACATGCTGAAGTCCTG
GTAGCTGTTGCTCTGGTTGTAATTGGTAGATACGTTGTAAAAAGGCTGTCACCCCAAGAA
CTTTCTGTATGTTTTGCTGTAACCGTTCAACGT-CTCTACAGACGAAATCC-----ACAA
Llzpc.3
Llzpc.6
Llzpc.1
Llzpc.2
Llzpc.5
Llzpc.4
1533
1500
1489
1455
1476
1435
TCTGAATAGAAATAAAAAACACTTTGGTTA-TCAGAATAGAAATAAAAAACACTTTGGTT--TTCAG--------------------------ACTGTCCAGAAGTAAAGCATCTCACAGCTCCT
GCTCTGT-GAAATAAAAGCTAAAACAGAA--TCTGATAAATAAAAAGCTCCACAACAG-----
Figure 17. Sequence alignment of L. laevis ZPC cDNAs. Full length ZPC cDNA
sequences were aligned by CLUSTALW and imported into BOXSHADE.
58
a. L. laevis
Llzpc.3
88
100
Llzpc.6
71
Llzpc.1
Llzpc.5
Llzpc.2
Llzpc.4
0.05
b. X. laevis
100
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
0.05
c. X. borealis
72
81
Xbzpc.1d
Xbzpc.1e
Xbzpc.1c
Xbzpc.2
Xbzpc.3
0.05
Figure 18. Phylogenetic tree of frog ZPC cDNAs. Neighbor-joining (distance based)
phylogenetic trees were constructed with MEGA from ZPC sequences derived from the
ovary of (a) L. laevis, (b) X. laevis, and (c) X. borealis . Branching order is based on the
level of sequence identity with highly identical sequences clustering together. The scale
bar represents the number of substitutions per site. Consensus trees are reported from the
results of 1000 bootstrap replicates with corresponding bootstrap values displayed at
nodes.
59
Table 2. Pairwise comparison of ZPC cDNA sequences. Each ZPC cDNA was globally
aligned to all other ZPC sequences found within the ovaries of the particular frog species:
(a) L. laevis, (b) X. laevis, and (c) X. borealis. The percent identity for each pairwise
alignment is shown.
a. L. laevis
Llzpc.1
Llzpc.2
Llzpc.3
Llzpc.4
Llzpc.5
Llzpc.6
Llzpc.1 Llzpc.2 Llzpc.3 Llzpc.4 Llzpc.5 Llzpc.6
75
85
65
75
90
71
65
75
76
62
71
88
64
64
76
b. X. laevis
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
Xlzpc.1a Xlzpc.1b Xlzpc.2 Xlzpc.3
98
90
65
90
65
64
c. X. borealis
Xbzpc.1e Xbzpc.1d Xbzpc.1c Xbzpc.2 Xbzpc.3
Xbzpc.1e
97
96
90
65
Xbzpc.1d
96
88
65
Xbzpc.1c
92
65
Xbzpc.2
64
Xbzpc.3
60
the comparison of Llzpc.4 with all other cDNAs, ranging from 62-65%. Given the high
sequence identities for a subset of the ZPC genes (Llzpc.3, Llzpc.6, Llzpc.1), the
exploitable regions to design qPCR primers were somewhat limited. However, primer
sets were designed for each of the L. laevis cDNAs (including GAPDH) using the
guiding principles for the optimal primer design as described above (Table 3).
X. laevis qPCR Primer Design
The four X. laevis ZPC cDNAs that were previously sequenced were globally
aligned using the CLUSTALW software program and then imported into the shading
program BOXSHADE to reveal sequence differences (Figure 19). The aligned order,
gene tree (Figure 18b), and pairwise comparison of identities for these ZPC cDNAs
reveals their relationships to each other (i.e. Xlzpc.1a, Xlzpc.1b, Xlzpc.2, and Xlzpc.3).
In particular, the pairwise comparison of the nucleotide identities shows that the highest
level of identity is 98% between Xlzpc.1a and Xlzpc.1b and the lowest level of identity
ranges from 64-65% for Xlzpc.3 compared to all others (Table 2b). As with L. laevis, the
highly identical ZPC genes (especially Xlzpc.1a and Xlzpc.1b) made primer design
challenging. Primer sets were designed for each of the X. laevis cDNAs (including
GAPDH) using the guiding principles for optimal parameters as described (Table 3).
However, for clones Xlzpc.1a, Xlzpc.1b, and Xlzpc.2, the amplicon sizes were slightly
larger than the optimal 100-150 bp range (187, 165, and 152 bases respectively) so as to
target divergent sequence regions.
Table 3. Summary of ZPC and GAPDH qPCR primers for L. laevis, X. laevis, and X. borealis. Primers used to amplify
ZPC and GAPDH genes from L. laevis, X. laevis, and X. borealis are outlined in the table.
61
62
63
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
1
1
1
1
AACATTGCAAACCATGCGCCAATGACTATATATGCTGACAGCTGTGTGGCCACAGTCACG
AACATTGCAAACCATGCGCCAATGACTATATATGCTGACAGCTGTGTGGCCACAGTCACG
AACATTGCAAACCATGCGCCAATGACAATTTATGTTGACAGCTGTGTGGCCACAGTCACG
GATACCAGAAACCTTGGTCCCATGATGATCTTTGTTGACCGTTGTGTGGCCACCCTGTCA
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
61
61
61
61
CCTGATGTCAATTCCAACCCCCGATATGAGATAATTAATCAAAATGGGTGTCTGGT
CCTGATGTCAATTCCAACCCCCGATATGAGATAATTAATCAAAATGGGTGTCTGGT
CCCGATATCAATTCAAACCCTCGTTATGAGATAATTAATCAAAATGGGTGTCTGGT
CCTGATTTGAACTCAAGCCCTCAGTATGAGATTATTGCTCTCAATGGGTGTTTAGT
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
117
117
117
117
AGATGGGAAACTGGATGACTCTTCTTCTGCCTTCCGATCTCCAAGGCCCCAGCCTG
AGATGGGAAACTGGATGACTCTTCTTCTGCCTTCCGATCTCCAAGGCCCCAGCCTG
AGATGGGAAACAGGATGACTCCTCTTCTGCCTTCCGATCGCCAAGGCCAACTCCGG
GGATAGTAAACAGGAAGACTCTTCCTCTACCTTCTGGTCTCCAAGACCTTCACCAG
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
173
173
173
173
ACAAGCTTCAGTTCTCTGTGGATGCATTCAGGTTTACTACATCAGATAGCGCTGTG
ACAAGCTTCAGTTCTCTGTGGATGCATTCAGGTTTACTACATCAGATAGCGCTGTG
ACAAGCTTCAGTTCTCTGTTGATGCGTTCAGGTTTACTACATCAGATAGCACTGTG
ACAAGCTGAGATTTAAGGTTGATGCATTCAAGTTCATTGGAGCAGATTCTCCTGTG
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
229
229
229
229
ATTTACATAACTTGCAATCTGAGAGCTGCTGCAACCACCCAAGTCCCAGACCCCAT
ATTTACATAACTTGCAATCTGAGAGCTGCTGCAACCACCCAAGTCCCAGACCCCAT
ATCTACATAACTTGCAATCTGAGAGCTGCTGCAACCACACAAGTCCCAGACACCAT
ATCTACATCACTTGCAGTGTGAGAGCAGCTGCAGCAAACCAGGGCCCAGATGTTCT
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
285
285
285
285
GAACAAAGCCTGTTCCTTCAGCAAATCTGCAAACAGTTGGTCTCCTCTTCAAGGAC
GAACAAAGCCTGTTCCTTCAGCAAATCTGCAAACAGTTGGTCTCCTGTTCAAGGAC
GAACAAAGCTTGCTCCTTCAGCAAAACCACAAACAGCTGGTCTCCTGTTCAAGGAC
GAACAGGGCCTGCTCCTTCAGTAAAGTCAGCAACACGTGGTTGTCACTAAATGGCC
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
341
341
341
341
CCAGTAACATATGCAGCTGCTGTGATACTGGAAACTGTGTCTCTGTACCAGGCCAA
CAAGTAACATATGYAGCTGCTGTGATACTGGAAACTGTGTCTCTGTACCAGGCCAA
CAAGTAACATATGTAGCTGCTGTGATACTGGAAACTGTGTCTCTCTACCAAGCCAA
CCAATAATATTTGTGACTGCTGTGACACAGGAGCGTGTGCTGC--TACTGG----A
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
397
397
397
391
AGCAGAAGACTGGGACCATATTTTTCAGGCTCTAGGTGGAACCAAAAAAGGGAAGC
AGCAGAAGACTAGGACCATATTTTTCAGGCTCTAGGTGGAACCAAAAAAGGGAAGC
AGCAGAAGATTGGGACCACAAT---CAGGTTCTAGGTGGAATAGAAAAAGAGAAGC
AGCAGA-----GGGGTCA-ATT------ATTTCAGG------AGATTAAGCAGATC
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
453
453
450
429
TGTGCATGTGTCTAAAATGGAGGAGGAAGAA---CATAGCTTGGCTACCATAGGGC
TGTGCATGTGACTAAAATGGAGGAGGAAGAA---CATAGCTTGGCTACCATAGGGC
CATACATGTGACTAAAATGGAGGAGGAAGAAGAACATAGCTTGGCTACTCTAGGGC
GGT-----TGATTCAAGCTTTGAAGTAGAA----------TTGGTAGCAGTTGGTC
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
506
506
506
470
CCATATTGGTGGTTGTACCTGAACAAACC------AAAACACAAGCTGTAAAGCAG
CCATATTGGTGGTTGCACCTGAACAAACC------AAAACACAAGCTGTAAAGCAG
CCATATTGGTGGTTGCACCTGAACAAGCCCAAGCCAAAACACAAGCTGTAAAGCAG
CTTTGTTCATCATTG-ACCCGAAAAGTCAT-----GTGGCTCCGTCCGTAAATCAA
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
556
556
562
520
GAACTGGAAGGGAAGACCTTGGAACTGTGGGAGCTGTTGGCATTGGGTTCTCTGGG
GAACTGGAAGGAAAGTCCTTGGAACTGTGGGAGCTGTTGGCATTGGGTTCTCTGGG
GAACTGGAAATCAAGACCTTGGAACTGTGGGAGCTGGTGGCATTGGGATCTTTGGG
GAATC--AAGCCAAATTGTTG-AGCTTTGGCTGTTGGTAGCACTGTGTTGTTTAAG
64
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
612
612
618
573
ACTTGTCCTGCTAGCTGCCTGTATTGCTGTCATTGCCTCCAAGCTTGCTAAAAGGA
ACTTGTCCTGCTAGCTGCCTGTATTGCTGTCATTGCCACTAAGCTTGCTAAAAGGA
GCTTGTTGTGCTAGTTGCCTGTATTGCTGTCATTATCACTAAGCTAACTAAAAGGA
TTTCATTGTGATTTCAGTTTGTGTTATTGTGAATATCCACAGATTTTGT---AGGA
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
668
668
674
626
AGCAATATATATCCACTATCCAGAAA
AGCAATATATATCCACTATCCAGAAA
AGCAATATATATCCACTATCCAGAAA
AACAAAGTATTTTTGTTTTTGCAAAA
753
753
759
711
Figure 19. Sequence alignment of X. laevis ZPC cDNAs. ZP domain regions (middle)
and sperm-binding regions (3’ end) of the ZPC cDNA sequences were aligned by
CLUSTALW and imported into BOXSHADE.
65
X. borealis qPCR Primer Design
The five X. borealis ZPC cDNAs that were previously sequenced were globally
aligned using the CLUSTALW software program and then imported into the shading
program BOXSHADE to reveal sequence differences (Figure 20). The aligned order,
gene tree (Figure 18c), and pairwise comparison of identities (Table 2c) for these ZPC
cDNAs reveals their relationships to each other (Xbzpc.1e, Xbzpc.1d, Xbzpc.1c,
Xbzpc.2, and Xbzpc.3). In particular, the pairwise comparison of nucleotide identities
shows that the highest level of identity is between clones Xbzpc.1e and Xbzpc.1d at 97%
whereas the lowest level of identity ranges from 64-65% for Xbzpc.3 when compared to
all others (Table 2c). Given these constraints, primer sets were designed for each of the X.
borealis cDNAs (including GAPDH) using the guiding principles for optimal parameters
as described (Table 3). Once again, the amplicon size for several of the clones deviated
from the optimal 100-150 bp range so as to target divergent sequence regions (Xbzpc.1d,
Xbzpc.1c, and Xbzpc.2 amplicons were 69, 76, and 90 bases, respectively).
Optimization of Primer Annealing Temperatures
Each designed primer set was tested for its optimal annealing temperature using
the MyCycler Thermal Cycler System (Bio-Rad) which contains a gradient temperature
block. The highest possible annealing temperature that generates significant amounts of
product would be the chosen optimum since this would maximize its specificity.
L. laevis Primer Optimization
66
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
1
1
1
1
1
AACATTGCAAACCATGCGCCGATGGCCATATATGTTGACAGCTGTGTGGCCACCATTGCA
AACATTGCAAACCATGCGCCGATGGCCATATATGTTGACAGCTGTGTGGCCACCATTGCA
AACATTGCAAACCATGCACCAATGACTATATATGTGGACAGCTGTGTGGCCACAGTCACA
AACATTGCAAACCATGCACCAATGACTATATATGTGGACAGCTGTGTGGCCACAGTCACA
GATACCAGAAATCTTGGTCCCATGATGCTCTTTGTTGGCCGTTGTGTGGCCACCCTGTCG
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
61
61
61
61
61
CCTGACGTCAATTCCAACCCTCGTTATGAGATAATTAATCAAAATGGGTGTCTGGT
CCTGACGTCAATTCCAACCCTCGTTATGAGATAATTAATCAAAATGGGTGTCTGGT
CCTGATGTCAATTCCAACCCTCGTTATGAGATAATTAATCAAAATGGGTGTCTGAT
CCTGATGTCAATTCCAACCCTCGTTATGAGATAATTAATCAAAATGGGTGTCTGAT
CCTGATATGAACTCAAGCCCTCAGTATGAGATTATTGCTCTCAATGGGTGTTTAGT
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
117
117
117
117
117
AGATGGGAAACAGGATGACTCCTCTTCTGCATTCCAATCTCCAAGGCCAACACCTG
AGATGGGAAACTGGATGACTCTTCTTCTGCCTTCCGATCTCCAAGGCTGCAGCCTG
AGATGGGACACAGGATGACTCCTCTTCTGCATTCCAATCTCCAAGGCCAACACCTG
AGATGGGAAACAGGATGACTCCTCTTCTGCATTCCAATCTCCAAGGCCAACACCTG
GGACAGTAAACAGGAAGACTCTTCCTCTACCTTCTGGTCTCCAAGACCTTCACCAG
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
173
173
173
173
173
ACAAGCTTCAATTCTCTGTTGATGCCTTCAGGTTTACTACATCTGACAGCACTGTG
ACAAGCTTCAGTTTTCTGTGGATGCATTCAGGTTTACTACATCAGATAGCGCTGTG
ACAAGCTTCAATTCTCTGTTGATGCATTCAGGTTTACTACATCAGATAGCGCTGTG
ACAAGCTTCAATTCTCTGTTGATGCCTTCAGGTTTACTACATCTGACAGCACTGTG
ACAAGCTGAGGTTTAAGGTTGATGCATTCAAGTTTGTTGGGGCAGATTCTCCTGTG
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
229
229
229
229
229
ATCTACATAACTTGCAATCTGAGGGCTGCTGCAACTACCCAAGTCCCAGACCCCAT
ATTTACATAACTTGCAATCTGAGGGCTGCTGCAACTACCCAAGTCCCAGACCCCAT
ATTTACATAACTTGCAATCTGAGGGCTGCTGCAACTACCCAAGTCCCAGACCCCAT
ATCTACATAACTTGCAATCTGAGAGCTGCTGCAACCACACAAGTCCCAGACACCAT
ATGTACATCACTTGCAGTGTGAGAGCAGCTGCAGCAAACCAGGGCCCAGATGCTCT
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
285
285
285
285
285
GAACAAAGCCTGCTCCTTCAGCAAATCCACAAACAGCTGGTCTCCTCTTCAAGGAC
TAACAAAGCCTGCTCCTTCAGCAAATCCACAAACAGCTGGTCTCCTCTTCAAGGAC
TAACAAAGCCTGCTCCTTCAGCAAATCCACAAACAGCTGGTCTCCTCTTCAAGGAC
GAACAAAGCTTGCTCCTTCAGCAAAACCACAAACAGCTGGTTTCCTCTTCAAGGGC
GAACAAGGCATGCTCCTTCAGTAAAGCCAGCAACACGTGGTCGTCACTAAATGGCC
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
341
341
341
341
341
CCAGTAACATCTGCAGCTGCTGTGATACTGGAAACTGTGTTTCTGTACCAGGCCAA
CCAGTAACATCTGCAGCTGCTGTGATACTGGAAACTGTGTCTCTGTACCAGGCCAA
CCAGTAACATCTGCAGCTGCTGTGATACTGGAAACTGTGTCTCTGTACCAGGCCAA
CAAGTAACGTTTGTAGCTGCTGTGATACTGGAAACTGTGTCTTTCTACCAAGCCAA
CCAATAATATATGTGAATGCTGTGATACGGGAGCATGTGTGGCT--ACTGG----A
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
397
397
397
397
391
AGCAGAAGACTGGAACCATATTT---AGGCTTTAGGTGGCC---CAGAAAAAGGGA
AGCAGAAGACTGGAACCATATTT---AGGCTCTAGGTGGCC---CAGAAAAAGGGA
AGCAGAAGACTGGAACCATATTT---AGGCTCTAGGTGGCC---CAGAAAAAGGGA
AGCAGAAGATTGGGAGAGAATTTTTCAGGTTTTAGGTGGTGGAACAGAAAACGGGA
AGCAGAGGGGT-------CAATT-----ATTTCAGGAGATT---------AAGCAG
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
447
447
447
453
426
AGCAGTGCATGTGACCAAATTGGAGGAGGAGGAGGAACATAGCTTGGCTACCCTGG
AGCAGTGCATGTGACCAAATTGGAGGAGGAGGAGGAACATAGCTTGGCTACCCTGG
AGCAGTGCATGTGACCAAATTGGAGGAGGAG---GAACATAGCTTGGCTACCCTGG
AGCCATACATGTGGCTAAAATGGAGGAAGAC------CATAGCTTGGCTACCATAG
ATCGGT---TGAGTCAAGCTTGGAAGTAGAA------------CTGGTAGCAGTTG
67
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
503
503
500
503
467
GGCCCATATTGGGGGTTGCGCCTGAACAAACCAAAACACAAGCTGTAAAGCAGGAA
GGCCCATATTGGTGGTTGCGCCTGAACAAACCAAAACACAAGCTGTAAAGCAGGAA
GGCCCATATTGGTGGTTGCGCCTGAACAAACCAAAACACAAGCTGTAAAGCAGGAA
GGCCCATATTGGTGGTTACACCTGATCAAGCCAAAACACAAGCTGTGAAGCAGGAA
GTCCTCTGTTCATCATTGACCCAGAAAGTCATGTGGCTCCATCAGTAAATGAAGAA
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
559
559
556
559
523
CTGGAAAGAAAGACCTTGGAACTGTGGGAGATGTTGGCATTGGGTTTTTTGGGACT
CTGGAAAGAAAGACCTTGGAACTGTGGGAGATGTTGGCATTGGGTTCTTTGGGACT
CTGGAAAGAAAGACCTTGGAACTGTGGGAGATGTTGGCATTGGGTTCTTTGGGACT
CTGGAAAGCAAGACCTTGGAACTGTGGGAGCTGGTGGCATTGGGTTCTTTGGGGCT
TC---AAGCCAACTTGTTGAGCTCTGGCTGTTGGTAGCATTGTGTTGTCTAAGTCT
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
615
615
612
615
576
TGTTTTGGTAGCTGCCTGTATTGCCGTCATTGCCATTAAGCTAACTAAAAGGAAGC
TGTTCTGGTAGCTGCCTGTATTGCCGTCATTGCCACTAAGCTAACTAAAAGGAAGC
TGTTCTGGTAGCTGCCTGTATTGCCGTCATTGCCACTAAGCTAACTAAAAGGAAGC
TGTTGTGTTAGCTGCCTGTATTGCGGTCATTGTCACTAAGCTAACTAAAAGGAAGC
TGTTGTGATTTCAGTTTGTGTTATTGTGAATATCCACAGATTTTGTAA---GAAAC
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
671
671
668
671
629
AATATATATTTACTATCCAGAAA
AATATATATCTACTATCCAGAAA
AATATATATCTACTATCCAGAAA
AATATGTATCCACTATCCAGAAA
AAAGTATCTTCGTTCTTGCAAAA
753
753
750
753
711
Figure 20. Sequence alignment of X. borealis ZPC cDNAs. ZP domain regions (middle)
and sperm-binding regions (3’ end) of the ZPC cDNA sequences were aligned by
CLUSTALW and imported into BOXSHADE.
68
After performing annealing temperature gradients on all primer sets for L. laevis,
the optimal annealing temperature for each primer set ranged from 65.8-69.2oC with
primers to Llzpc.3 being the highest and LlGAPDH primers being the lowest (Figure 21).
Interestingly, this empirically determined optimal range was significantly higher than the
Tm estimated from the primer design software program (60oC). Specifically, primers to
Llzpc.2, Llzpc.5, and Llzpc.6 all annealed at 67.3oC while Llzpc.4 annealed at 69.5oC. As
can be seen in Figure 21, an increase in temperature above these optimums yielded
minimal to no product. There was slight amplification for Llzpc.2 and Llzpc.6 at the next
highest temperature of 69.5oC (lane 6), but was a negligible amount compared to product
yield at 67.3oC. As for Llzpc.1, a tighter or shallower gradient was performed for this
primer set due to the high sequence identity to other ZPC cDNAs. In this case, it was
determined that 65.9oC was the best annealing temperature for specificity while yet still
yielding considerable amounts of product. GAPDH primers appeared optimal at 65.8oC
since it yielded significantly more product at this temperature as compared to 67.3oC
(Figure 21, lane 5). No template controls (Figure 21, lane 10) were performed for all
experiments to demonstrate the absence of contamination and to show that the primer set
does not form primer dimers (primer hybridization to each other and subsequent
amplification) at the optimal annealing temperature. It should be noted that a slight
doublet was evident for the Llzpc.5 and Llzpc.1 PCR reactions. Since these PCR
reactions were performed with plasmid DNA containing the ZPC cDNAs, it is very
possible that the primers may have annealed to alternative sites such as vector sequences.
However, it was not viewed as a problem since the template concentrations were higher
69
1
2
3
L
64.7
64.9
4
65.3
5
65.9
6
66.7
7
8
67.4
67.8
9
10
68.0
65.9
Llzpc.1
122 bp
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
112 bp
Llzpc.2
68.5
68.7
68.9
69.2
69.7
70.1
70.4
70.5
68.7
129 bp
Llzpc.3
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
130 bp
Llzpc.4
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
107 bp
Llzpc.5
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
121 bp
Llzpc.6
64.0
LlGAPDH
TA
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
152 bp
Figure 21. L. laevis ZPC and GAPDH qPCR primer optimization. Gradient annealing
temperatures are listed under lane numbers; genes are listed down the left column; and
amplicon size is listed down the right column. DNA ladder was loaded in lane 1, whereas
negative controls (no template control) were loaded in lane 10.
70
in these assays (0.025ng of each template) as compared to the level expected in the
cDNA libraries and that these same vector sequences are not found in the cDNA libraries
(which utilize small PCR adaptor sequences).
X. laevis Primer Optimization
After performing annealing temperature gradients on all primer sets for X. laevis,
the optimal annealing temperature for each primer set ranged from 66.0-67.3oC (Figure
22). In a similar observation to L. laevis, the empirically determined optimal range was
significantly higher than the Tm estimated from the primer design software program
(60oC). Specifically, primers to Xlzpc.1a annealed at 66.0oC while Xlzpc.1b, Xlzpc.2,
Xlzpc.3, and XlGAPDH all annealed at 67.3oC. As can be seen in Figure 22, an increase
in temperature above these optimums generates minimal to no product. There is no visual
amplification for Xlzpc.1b, Xlzpc.2, Xlzpc.3, and XlGAPDH at the next highest
temperature, 69.5oC (lane 6). As for Xlzpc.1a, amplification occurs at 67.3oC, but product
is minimal compared to other primer sets at that temperature. In this case, it was
determined that 66.0oC was the best annealing temperature for specificity while yet still
yielding considerable amounts of product. No template controls (lane 10) demonstrated
the absence of contamination and that the primer sets do not form primer dimers at the
optimal annealing temperature.
X. borealis Primer Optimization
After performing annealing temperature gradients on all primer sets for X.
71
1
2
3
L
64.0
64.7
4
65.8
5
67.3
6
69.5
7
71.2
8
72.2
9
10
73.0
67.3
Xlzpc.1a
187 bp
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
Xlzpc.1b
165 bp
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
Xlzpc.2
152 bp
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
Xlzpc.3
132 bp
64.0
XlGAPDH
TA
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
112 bp
Figure 22. X. laevis ZPC and GAPDH qPCR primer optimization. Gradient annealing
temperatures are listed under lane numbers; genes are listed down the left column; and
amplicon size is listed down the right column. DNA ladder was loaded in lane 1, whereas
negative controls (no template control) were loaded in lane 10.
72
borealis, the optimal annealing temperature for each primer set ranged from 64.2 –
70.8oC (Figure 23). Consistent with the prior optimization experiments, these annealing
temperatures were higher than estimated from the primer design software program
(60oC). Specifically, primers to Xlzpc.1e annealed at 70.8oC which was considerably
higher than the 60oC target. Xbzpc.1d and Xbzpc.2 both annealed at 67.3oC while
Xbzpc.1c and Xbzpc.3 optimally annealed at 68.2oC and 64.2oC, respectively. As can be
seen in Figure 23, the use of tighter gradients for X. borealis (because of high sequence
identity) yielded minimal product above optimal temperatures likely due to inefficient
amplification at the elevated temperature. GAPDH primers appeared optimal at 65.8oC.
Mixed Plasmid PCR Controls
Optimal annealing temperatures acquired from the gradient PCR experiments
were used in mixed plasmid experiments to demonstrate the specificity of each primer set
for the template it was designed to amplify. Although the optimal annealing temperature
maximizes the specificity of the primer set to its particular cDNA, it was essential to
show that the other ZPC cDNAs were not capable of being amplified at these
temperatures also. Thus, the plasmids containing the other ZPC cDNAs were mixed
together in an equal ratio (0.025ng of each template) and used as the starting template for
the mixed plasmid experiment. A positive control was included in the experiment which
consisted of the primer set and its corresponding ZPC cDNA plasmid that it was designed
to amplify.
For all three species, each primer set demonstrated the ability to amplify its
73
1
2
3
4
5
6
7
8
9
10
L
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
109 bp
Xbzpc.1e
64.0
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
69 bp
Xbzpc.1d
64.7
65.0
65.5
66.3
67.3
68.2
68.7
69.0
66.3
76 bp
Xbzpc.1c
65.0
65.4
66.2
67.3
68.9
70.2
71.0
71.4
67.3
Xbzpc.2
90 bp
62.0
62.4
63.1
64.2
65.6
66.8
67.6
68.0
64.2
129 bp
Xbzpc.3
64.0
XbGAPDH
TA
64.7
65.8
67.3
69.5
71.2
72.2
73.0
67.3
114 bp
Figure 23. X. borealis ZPC and GAPDH qPCR primer optimization. Gradient annealing
temperatures are listed under lane numbers; genes are listed down the left column; and
amplicon size is listed down the right column. DNA ladder was loaded in lane 1, whereas
negative controls (no template control) were loaded in lane 10.
74
specific ZPC template and the failure to amplify other ZPC templates at the optimized
annealing temperature (Figure 24). It should be noted that conventional end point PCR is
subject to variation with respect to the amount of product being synthesized at the end of
the cycles which explains the variation in staining intensity for the positive plasmid
controls (Figure 24, lane 2). The no template controls (NTC) were consistent with
previous experiments and showed no product.
Primer Efficiency
Although the use of carefully matched annealing temperatures increases the
specificity of primer sets to their templates, primers may behave in ways that prevent
them from amplifying products in a consistent and expected exponential manner during
PCR. Significant deviation from the optimal doubling of product in each cycle would not
allow the results to be interpreted in a quantitative manner. Thus, the efficiency of the
primer set needs to be determined to be in the range 90-110% of its expected doubling
over its cycles to validate the quantitative expression study. To test this, a 10-fold dilution
series is performed for the template (specifically over the range of 0.025ng/µl to
0.000025ng/µl) and the CT values compared between dilutions. If the reaction is 100%
efficient then the CT values should be staggered by 3.322 for each 10-fold dilution to
indicate perfect doubling each time (2n, n = cycle number). It should be noted that these
assays were performed by qPCR rather than conventional PCR so that CT values could be
determined. Percent efficiency is determined by plotting the CT values versus the log
starting template quantity to obtain a linear regression line (Figure 25). The coefficient of
75
a. L. laevis
1
L
2
+
3
Mix
4
NTC
Llzpc.1
122 bp
Llzpc.2
112 bp
Llzpc.3
129 bp
Llzpc.4
118 bp
Llzpc.5
107 bp
Llzpc.6
121 bp
b. X. laevis
1
L
2
+
3
Mix
4
NTC
Xlzpc.1a
187 bp
Xlzpc.1b
165 bp
Xlzpc.2
152 bp
Xlzpc.3
132 bp
c. X. borealis
1
L
2
+
3
Mix
4
NTC
Xbzpc.1e
109 bp
Xbzpc.1d
69 bp
Xbzpc.1c
76 bp
Xbzpc.2
90 bp
Xbzpc.3
129 bp
Figure 24. Mixed plasmid control PCR. Primer sets targeting (a) L. laevis, (b) X. laevis,
and (c) X. borealis ZPC cDNAs are listed down the left column, and their corresponding
amplicon size is listed down the right column. Lane 1= size ladder; Lane 2= positive
control (primer set and the targeted ZPC template); Lane 3= mixture of non-targeted ZPC
templates; Lane 4= no template control.
Threshold Cycle (CT)
76
E = 99.1%
R2 = 0.996
Log Starting Quantity (ng)
Figure 25. Representative qPCR primer efficiency plot. ZPC and GAPDH primer sets
were tested for their ability to efficiently amplify PCR products using the iQ5 Real-Time
Detection System (Bio-Rad). The graph displays how efficiency is determined using
primers to L. laevis GAPDH as an example. CTs were plotted against the log
concentration (ng) of starting template to determine efficiency (E) and the coefficient of
determination (R2).
77
determination (R2) is also determined by plotting the CT values with the log of the
starting template concentration. The R2 value represents how well the experimental data
fit the regression line and is a measure of whether the amplification efficiency is the same
for different DNA concentrations. When the data fits the regression line perfectly, the R2
value equals 1.0. Efficiencies less than 90% usually indicate that template DNA or
primers may be forming secondary structures during the PCR reaction and preventing
optimal doubling. Greater than 110% efficiency means that the PCR reaction is
producing more product than expected and is usually due to primer dimer products being
formed simultaneously while target is being amplified. Primer dimer products can be
detected by performing a melting curve at the end of the qPCR cycle which will show up
as an additional melt curve with a very low Tm due to its smaller size.
All L. laevis primer sets (ZPC and GAPDH) fell within the acceptable range of
90-110% efficient (Figure 25; Table 4) with 96.1% being the lowest and 101.5% being
the highest. As for X. laevis, all primer sets also fell within the acceptable range (Table 4)
with 99.2% being the lowest and 105.3% being the highest (Xlzpc.1b and Xlzpc.3,
respectively). And lastly, all X. borealis primer sets fell within the acceptable range
(Table 4) with 96.4% being the lowest and 105.7% being the highest (Xbzpc.1e and
Xlzpc.2, respectively). This data indicated that no primer dimers or secondary structures
were interfering with the PCR in all cases. Melt curves performed after all reactions were
completed indicated that only a single peak or PCR product was present, indicating that
the intended region was being amplified with no evidence of primer dimer formation. In
addition, the primer efficiency data fit the regression line well for all PCR reactions (R2
78
Table 4. qPCR primer efficiency summary. ZPC and GAPDH primer sets were tested for
their ability to efficiently amplify PCR products using the iQ5 Real-Time Detection
System (Bio-Rad). CT values were plotted against the log concentration (ng) of starting
template to determine percent efficiency (E) and the coefficient of determination (R2).
Gene
Llzpc.1
Llzpc.2
Llzpc.3
Llzpc.4
Llzpc.5
Llzpc.6
LlGAPDH
Percent Efficiency (E)
96.1
100.7
101.5
97.0
98.0
101.2
99.1
Coefficient of Determination (R2)
0.998
0.998
0.998
0.985
1.000
0.996
0.996
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
XlGAPDH
103.2
99.2
100.0
105.3
101.5
0.974
0.990
0.990
0.999
0.995
Xbzpc.1e
Xbzpc.1c
Xbzpc.1d
Xbzpc.2
Xbzpc.3
XbGAPDH
96.4
104.7
97.0
105.7
100.0
97.9
0.995
0.998
0.990
0.988
0.995
0.996
79
values ranging from 0.974-1.0) indicating that these primers amplify efficiently at each
template concentration tested.
qPCR Assays to Determine Gene Expression
Once primers were deemed specific and efficient, they were used in qPCR assays
to determine the expression of ZPC genes with respect to the GAPDH reference gene.
Assays were set up by first creating master mixes to contain all reaction components with
the goal of reducing or minimizing technical variability between trials. Since the
optimum primer annealing temperature for each ZPC cDNA varied, each ZPC gene was
assayed using separate 96-well plate trials. GAPDH qPCR served as an internal reference
control and was included on all ZPC 96-well plate trials in order to normalize ZPC CT
values and to control for unequal cDNA loading between different ZPC assays. Within
each trial experiment, three separate master mixes were constructed in order to have three
independent replicates for each ZPC. The amount of product was determined by the
fluorescent dye SYBR Green which was included in the master mix and is detected when
it binds to double stranded DNA. The CT value was then determined by establishing the
cycle number at which point the fluorescence was detected above a threshold value (in
essence, the baseline).
Upon completion of the qPCR amplification cycle, a melt curve was performed to
assess whether or not multiple sized products were formed during the assay. Initially, the
melt curve cycle starts at a low temperature (55.0oC) and is then slowly increased by
0.5oC increments. Each amplicon found in a reaction will generate a specific melt curve
80
Tm (generally larger products have a higher Tm). Primer dimers generally have a very low
Tm since they are small products (approx. 30-40 bp). The anticipated result for each
qPCR is one distinct melt curve peak representing a single amplicon (i.e. ZPC or
GAPDH).
Each qPCR gene trial/replicate was performed in triplicate and thus yielded three
CT values which were averaged to determine the CT value for that particular trial. This
was done two additional times to yield three CT values, one for each replicate. Since plate
to plate variability was minimal, CT values from three replicates are averaged to
determine the CT for that particular gene. This was continued for each ZPC gene
expressed within the ovary to yield an average CT. Plate to plate variability was also
minimal when measuring GAPDH so CT values from each replicate are averaged. The
averaged ZPC CT value for each gene was then normalized to the average GAPDH CT
value by plugging it into the following equation: 2Δ(ΔCT). The ZPC CT value was
subtracted from the GAPDH CT value to generate the ΔCT (CT GAPDH – CT ZPC). This was
done for each ZPC gene. Once each gene was normalized to GAPDH (ΔCT), ZPCs were
then compared to each other to determine relative fold expression. The ΔCT of the lowest
expressing gene served as the baseline and was subtracted from the ΔCT of each ZPC to
yield the Δ(ΔCT) (ΔCT.ZPC – ΔCT.lowest ZPC). Those values were used in the 2Δ(ΔCT) equation
to generate relative fold expression for each gene. Since the lowest expressed gene serves
as the baseline to which all expression data (ΔCTs) are compared, it was designated to
have a fold expression of 1.0 (ΔCT.lowest ZPC – ΔCT.lowest ZPC = 0, 20 = 1.0).
81
L. laevis ZPC qPCR assays
The qPCR expression results for the L. laevis ZPC cDNAs found within one
individual's ovary cDNA library revealed an unequal expression of genes (Table 5,
Figure 26). Upon conclusion of each qPCR trail, melt curves revealed only one sized
product indicating that CT values corresponded to the targeted amplicons (data not
shown). After calculating the ΔCT values for all L. laevis ZPC genes (normalization to
GAPDH), Llzpc.6 was found to be the lowest expressed gene so all ΔCT data was then
compared to the Llzpc.6 ΔCT value. The p-value derived from an ANOVA analysis was
0.000 indicating that expression differences were highly significant. ZPC expression
levels were then categorized into tiers of expression such as high and low based on
multiple pairwise comparisons. These categories are useful to qualitatively assess and
compare relative ZPC expression profiles across species. Significance was determined
using the Bonferroni corrected post hoc test to establish differences in expression level
and which genes would be categorized as high or low expressers. The Bonferroni
correction is a statistical adjustment for multiple comparisons that decreases the
likelihood that significant outcomes occurred by chance. Llzpc.4 and Llzpc.5 showed the
highest level of expression at 7.73 and 7.94 fold respectively followed by Llzpc.2 and
Llzpc.3 expressed at 5.21 and 5.35 fold. However, after performing the Bonferroni
correction (p-value < 0.0033 to reject the null hypothesis of equality) the expression
levels of these genes were not statistically distinct (meaning the 7.94 vs. 5.21 can not be
considered as significantly different). The expression levels of Llzpc.1 and Llzpc.6 are
also considered to be equal based on a pairwise comparison. However, the expression of
82
Table 5. L. laevis ZPC and GAPDH CT values. qPCR for each gene as performed in
triplicate on a single plate which yielded three CT values that were averaged (column 2)
along with it’s standard deviation (column 3). Three separate plates were performed for
each gene. All three plate’s CT averages was then averaged together (column 4) along
with standard deviations calculated (column 5). The final CT averages (column 4) were
subsequently used to determine expression level using the 2Δ(ΔCT) equation.
Gene
Llzpc.1
Llzpc.2
Llzpc.3
Llzpc.4
Llzpc.5
Llzpc.6
LlGAPDH
Plate Avg.
CT
36.83
36.99
36.91
35.21
35.17
34.98
35.36
34.82
35.05
34.70
34.71
34.23
34.37
34.45
34.72
37.11
37.84
37.55
35.16
35.09
35.20
Plate
St Dev.
1.07
0.45
0.12
1.07
1.28
0.36
0.77
0.68
0.08
0.07
0.20
0.13
0.31
1.14
0.87
0.88
0.10
0.26
0.87
1.28
1.26
Plate (1-3)
Avg.
Plate (1-3)
St. Dev.
Delta CT
Delta/Delta
CT
Fold
Expression
36.91
0.08
1.76
0.59
1.51
35.12
0.12
-0.03
2.38
5.21
35.08
0.27
-0.07
2.42
5.35
34.55
0.27
-0.60
2.95
7.73
34.51
0.18
-0.64
2.99
7.94
37.50
0.37
2.35
0.00
1.00
35.15
0.06
Relative Fold Expression
83
8
6
4
2
0
Llzpc.1
Llzpc.2
Llzpc.3
Llzpc.4
Llzpc.5
Llzpc.6
Gene
Figure 26. L. laevis ZPC expression levels using qPCR. Averaged CT values for each
ZPC gene were normalized to the averaged GAPDH CT and ΔCTs from each gene were
compared to the lowest expressing gene (Llzpc.6). Relative fold expression is determined
through the 2Δ(ΔCT) equation and is represented as positive expression over the lowest
expressed gene (which is designated a fold expression of 1.0).
84
Llzpc.1 and Llzpc.6 falls significantly below the level of Llzpc.2, Llzpc.3, Llzpc.4, and
Llzpc.5 (meaning the null hypothesis of equality was rejected in this case). Thus, there is
evidence for two categories: high producers vs. low producers.
X. laevis ZPC qPCR assays
X. laevis ZPC genes were also found to be unequally expressed within their ovary
as determined by the 2Δ(ΔCT) equation (Table 6, Figure 27). Upon conclusion of each
qPCR trial, melt curves revealed only one sized product indicating that the CT values
corresponded to the targeted amplicons (data not shown). The p-value derived from
ANOVA analysis was 0.000 indicating the expression differences observed are highly
significant. After normalization to GAPDH, Xlzpc.3 was found to be the lowest
expressed gene within this individual’s ovary so all ΔCT data first normalized to GAPDH
was then compared to the ΔCT of Xlzpc.3. Xlzpc.1b showed the highest level of
expression at 3.23 fold greater than Xlzpc.3, but not significantly distinct from Xlzpc.2
(2.69 fold) using the Bonferroni correction (p-value < 0.0083 to reject the null
hypothesis). Both Xlzpc.1b and Xlzpc.2 are more highly expressed when compared to
Xlzpc.1a (1.17 fold). Xlzpc.1a was expressed 1.17 fold greater than Xlzpc.3, but their
expression levels are also considered statistically equal. Similar to L. laevis, X. laevis
ZPC can be categorized as either high (Xlzpc.1b and Xlzpc.2) or low (Xlzpc.1a and
Xlzpc.3) producers.
X. borealis ZPC qPCR assays
85
Table 6. X. laevis ZPC and GAPDH CT values. qPCR for each gene as performed in
triplicate on a single plate which yielded three CT values that were averaged (column 2)
along with it’s standard deviation (column 3). Three separate plates were performed for
each gene. All three plate’s CT averages was then averaged together (column 4) along
with standard deviations calculated (column 5). The final CT averages (column 4) were
subsequently used to determine expression level using the 2Δ(ΔCT) equation.
Gene
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
XlGAPDH
Plate Avg.
CT
27.17
27.38
27.32
25.55
26.05
25.90
25.84
26.18
26.25
27.67
27.28
27.61
25.50
25.54
25.71
Plate
St. Dev.
0.13
0.29
0.29
0.10
0.04
0.06
0.06
0.13
0.29
0.18
0.12
0.17
0.15
0.13
0.20
Plate (1-3)
Avg.
Plate (1-3)
St. Dev.
Delta CT
Delta/Delta
CT
Fold
Expression
27.29
0.11
1.71
0.23
1.17
25.83
0.26
0.25
1.69
3.23
26.09
0.22
0.51
1.43
2.69
27.52
0.21
1.94
0.00
1
25.58
0.11
Relative Fold Expression
86
3.5
3
2.5
2
1.5
1
0.5
0
Xlzpc.1a
Xlzpc.1b
Xlzpc.2
Xlzpc.3
Gene
Figure 27. X. laevis ZPC expression levels using qPCR. Averaged CT values for each
ZPC gene were normalized to the averaged GAPDH CT and ΔCTs from each gene were
compared to the lowest expressing gene (Xlzpc.3). Relative fold expression is determined
through the 2Δ(ΔCT) equation and is represented as positive expression over the lowest
expressed gene (which is designated a fold expression of 1.0).
87
Comparable to L. laevis and X. laevis, the X. borealis ZPC genes were found to be
unequally expressed within the X. borealis ovary as determined by the 2Δ(ΔCT) equation
using the average of triplicate trials (Table 7, Figure 28). Upon conclusion of each qPCR
trail, melt curves revealed only one sized product indicating that the CT values
corresponded to the targeted amplicons (data not shown). The p-value derived from an
ANOVA analysis was 0.000 indicating that the expression differences observed are
highly significant. After normalization to GAPDH, Xbzpc.1e was found to be the lowest
expressed gene within this individual’s ovary so all GAPDH normalized ΔCT data was
then compared to the ΔCT of Xlzpc.3. This revealed that Xbzpc.1d and Xbzpc.2 had the
highest levels of expression at 16.56 and 17.63 fold respectively. Xbzpc.1d and Xbzpc.2
were considered statistically equal based on the Bonferroni correction using a p-value of
0.0050. Xbzpc.1c is relatively expressed at 13.55 fold, placing it as the third highest
expressed gene, however pairwise comparisons indicate that expression is statistically
equal to that of Xbzpc.1d and Xbzpc.3 (8.57 fold). Besides being considered statistically
equal to Xbzpc.1c, Xbzpc.3 is expressed to a significantly greater degree than Xbzpc.1e,
but expressed lower than Xbzpc.1d and Xbzpc.2. Thus, Xbzpc.3 was classified as
moderately expressed due to its intermediary ranking. Based on these statistical pairwise
comparisons, X. borealis ZPC gene expression levels are classified as being high
(Xbzpc.1d, Xbzpc.1c, Xbzpc.2), moderate (Xbzpc.3) and low (Xbzpc.1e.).
ZPC Phylogenetic Analysis
Once expression profiles of ZPC genes were determined by qPCR, the
88
Table 7. X. borealis ZPC and GAPDH CT values. qPCR for each gene as performed in
triplicate on a single plate which yielded three CT values that were averaged (column 2)
along with it’s standard deviation (column 3). Three separate plates were performed for
each gene. All three plate’s CT averages was then averaged together (column 4) along
with standard deviations calculated (column 5). The final CT averages (column 4) were
subsequently used to determine expression level using the 2Δ(ΔCT) equation.
Gene
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
XbGAPDH
Plate Avg.
CT
24.93
24.83
24.78
20.83
20.77
20.78
20.94
21.09
21.24
20.47
21.26
20.39
21.85
21.82
21.58
18.77
18.79
18.68
Plate
St Dev.
0.29
0.53
0.46
0.06
0.13
0.05
0.07
0.05
0.16
0.12
0.07
0.08
0.06
0.05
0.07
0.19
0.16
0.34
Plate (1-3)
Avg.
Plate (1-3)
St. Dev.
Delta CT
Delta/Delta
CT
Fold
Expression
24.85
0.08
6.10
0.00
1.00
20.79
0.03
2.05
4.05
16.56
21.09
0.15
2.34
3.76
13.55
20.71
0.48
1.96
4.14
17.63
21.75
0.15
3.00
3.10
8.57
18.75
0.06
89
Relative Gene Expression
20
15
10
5
0
Xbzpc.1e
Xbzpc.1d
Xbzpc.1c
Xbzpc.2
Xbzpc.3
Gene
Figure 28. X. borealis ZPC expression levels using qPCR. Averaged CT values for each
ZPC gene were normalized to the averaged GAPDH CT and ΔCTs from each gene were
compared to the lowest expressing gene (Xbzpc.1e). Relative fold expression is
determined through the 2Δ(ΔCT) equation and is represented as positive expression over the
lowest expressed gene (which is designated a fold expression of 1.0).
90
evolutionary relationships between species were assessed through the construction of
phylogenetic trees. Gene trees diagram possible evolutionary paths genes have taken and
reconstruct relationships such as being orthologous genes (diverged after a speciation
event) or paralogous genes (diverged after a duplication event within same species)
during their decent from a common ancestor. To evaluate the relationships of ZPC genes,
maximum likelihood and neighbor-joining phylogenetic trees were generated using the
program MEGA and ZPC protein sequences. Maximum likelihood trees use a statistical
method to determine the best estimation or probability of a particular evolutionary model
in generating the observed sequences. The tree with the highest probability is then
returned revealing how the proteins in question are most likely related. Distance-based or
neighbor-joining trees are created by calculating their sequence similarity to each other
which is then converted into distance measurements of amino acid substitutions per site.
In both cases, branch length corresponds to the level of divergence between two proteins
with longer branches suggesting greater evolution. The data is resampled 1000 times
(1000 bootstrap replicates) for both tree types to generate a consensus tree (the most
common branching pattern). The robustness of the branching pattern is indicated by
bootstrap values located at the branch node (values greater than 95% indicate high
confidence that this is the correct branching pattern).
Based upon the levels of expression and statistical significance, ZPC genes were
previously qualitatively classified as being high, moderate, or low expressers within each
individual’s ovary. Those designations were carried over to the phylogenetic trees to
91
hypothesize common functions of ZPC proteins based on relative gene expression and
evolutionary relationships.
X. laevis and X. borealis ZPC Evolutionary Relationship
The generation of maximum likelihood (Figure 29) and neighbor-joining (Figure
30) phylogenetic trees suggests an orthologous relationship for a subset of the genes that
are expressed to a similar degree. Two of the most highly expressed ZPC genes from the
ovaries of X. laevis (Xlzpc.2) and X. borealis (Xbzpc.2) cluster together suggesting an
orthologous relationship. A similar pattern is also observed between Xlzpc.3 and Xbzpc.3
which cluster together in both tree types indicating orthology. Additionally, these zpc.3
genes show a high degree of divergence from remaining ZPCs as illustrated by the
extended branch length connecting this cluster. Contrasting the high expression from the
cluster of Xlzpc.2 and Xbzpc.2, both Xlzpc.3 and Xbzpc.3 are not classified as highly
expressed genes.
Orthologous relationships cannot be determined between the remaining ZPC
genes from X. laevis (Xlzpc.1a and Xlzpc.1b) and X. borealis (Xbzpc.1e, Xbzpc.1d, and
Xbzpc.1c). Each set of genes cluster together suggesting the similarity is greater within
each species rather than across species. These could either be gene duplication events in
each lineage or alternatively allele variants (same gene location but different mutations of
the gene). However, it is to be noted within each cluster that there are variable levels of
expression. The cluster of Xbzpc.1e, Xbzpc.1d, and Xbzpc.1c possess both high and low
expressing genes which is similar to the X. laevis cluster where Xlzpc.1a is a low
92
59
95
85
100
98
Xbzpc.1d
High
Xbzpc.1e
Low
Xbzpc.1c
High
Xlzpc.1a
Low
Xlzpc.1b
High
High
Xbzpc.2
75
High
Xlzpc.2
Xbzpc.3
100
Xlzpc.3
Low
Llzpc.4
High
Llzpc.2
56
High
High
Llzpc.5
95
Llzpc.1
91
Llzpc.3
100
97
Moderate
Llzpc.6
Low
High
Low
0.1
Figure 29. ZPC maximum likelihood phylogenetic tree. A consensus tree of L. laevis, X.
laevis, and X. borealis ZPC protein sequences (ZP domain + sperm binding regions) is
constructed with MEGA version 4. Results of 1000 bootstrap replicates are indicated on
each branch. Relative levels of expression determined from qPCR are located next to
each gene. Branch length indicates the genetic distance between genes.
93
Xbzpc.1d
High
Xbzpc.1e
Low
Xbzpc.1c
High
Xlzpc.1a
Low
99 Xlzpc.1b
High
Xlzpc.2
High
43
49
93
38
100
100
High
Xbzpc.2
Moderate
Xbzpc.3
89
Low
Xlzpc.3
Llzpc.4
59
Low
Llzpc.1
Llzpc.2
Llzpc.6
25
Llzpc.3
15
37
High
Llzpc.5
High
Low
High
High
0.2
Figure 30. ZPC neighbor-joining phylogenetic tree. A consensus tree of L. laevis, X.
laevis, and X. borealis ZPC protein sequences (ZP domain + sperm binding regions) is
constructed with MEGA version 4. Results of 1000 bootstrap replicates are indicated on
each branch. Relative levels of expression determined from qPCR are located next to
each gene. Branch length indicates the genetic distance between genes.
94
expresser and Xlzpc.1b is expressed to a significantly greater degree.
Xenopus and Lepidobatrachus ZPC Evolutionary Relationships
Given the evolutionary distance between Lepidobatrachus and Xenopus (diverged
110-120 mya), L. laevis ZPC genes are most closely related to other L. laevis ZPC genes
when compared to X. laevis and X. borealis ZPCs (Figure 29, 30). However, Llzpc.4 is
most closely related to Xenopus ZPC genes which may suggest that it is a common
ancestral gene. Furthermore, Llzpc.4 is expressed relatively highly in the L. laevis ovary.
The rest of the ZPC genes have mixtures of high and low expressing genes (4 of the 6 are
high expressers in total).
95
Chapter 4
DISCUSSION
The discovery of multiple ZPC genes present within the genomes of L. laevis, X.
laevis, and X. borealis prompted the current research to determine ZPC gene expression
profiles and whether or not they are equally expressed in each species so as to further
formulate hypotheses as to their function. Relative ZPC expression levels were assessed
through qPCR after normalization to the housekeeping gene GAPDH and comparison to
each other. This revealed that ZPC genes were differentially expressed in each individual
with respect to mRNA levels. This finding was consistent with 2-D gel immunoblotting
data from L. laevis vitelline envelopes showing that the ZPC antiserum recognized
approximately 6 different products that varied in their intensity levels (see Figure 5 from
Introduction). Although mRNA levels do not always correspond directly to the amount of
protein product that is translated, similar genes such as from the ZPC gene family are
likely to be translated in a similar manner, thus giving credence to the assumption that the
qPCR data is indicative of their protein expression levels.
Furthermore, when comparing the differences in expression, multiple genes were
predominant in the expression profile while others had a significantly reduced expression.
These expression profiles may provide insight as to the role played by each translated
protein in the fertilization process. As outlined in the introduction, three alternative
scenarios were presented as to the potential expression levels: 1) a single ZPC gene is
predominantly expressed whereas all others are minimal, 2) all ZPC genes are equally
expressed, and 3) several ZPC genes are highly expressed relative to the others. The
96
results for all three species were consistent with scenario 3. The meaning of this data is
left for interpretation, largely speculative in nature since there is no functional data for
these different ZPC gene products to inform interpretation.
However, it is likely that ZPC genes that are predominantly expressed have high
potential for serving as sperm-binding proteins, whereas the lesser expressed genes serve
an alternative role such as a structural function in the envelope, potentially even a noncritical role since there are several other ZP proteins in the envelope that are known to be
important structurally (e.g. ZPA and ZPB). This notion of a diminished or alternative role
for duplicated genes with reduced expression levels is not new. For example, in the
zebrafish, the homeobox-1 gene duplicated to create the homeobox-2 gene (mbx1 and
mbx2, respectively). Mbx1 is highly expressed in the forebrain, midbrain, and cerebellum
early in neural development and functions as a transcription factor that gives rise to the
mesencephalon leading to the formation of the midbrain. Although the mbx2 gene shows
a high level of sequence identity, the reduced expression (expressed mainly in the
midbrain) of mbx2 during neural development revealed that its functional role had
changed [46]. Evidence from gene knockdown experiments indicate mbx1 maintains a
more critical role in neural development between the duplicates, however mbx2 is
required for the prolonged growth of the retina during embryonic development [57].
Thus, the responsibilities of the mbx2 gene compared to mbx1 are reduced which may be
a similar model to diminished function of low expressing ZPC genes.
It is very possible that the highly expressed ZPC genes in these frog species
compete for sperm-binding activity in the egg envelope. As mentioned in the
97
introduction, sperm competition and sexual conflict may be forces driving the evolution
of reproductive genes. Since frog ZPC genes appear to be rapidly evolving in the spermbinding region, complementary receptors on sperm that can bind to these ZPCs will be
selected during fertilization and thus co-evolve. However, this competition is thought to
be driven by the female reproductive genes as suggested by the research on mammalian
ZPC, sea urchin bindin, and abalone lysin genes [45,33,34,35,36]. Thus, the male
reproductive proteins such as sperm binding receptors are in competition for the
functional sperm binding ZPCs. Sperm competition is thought to be beneficial since this
would cause a decrease in the number of sperm that can actually penetrate and fuse with
the egg at one time and help prevent polyspermic fertilization. By keeping sperm one step
behind in the evolutionary race to fertilization, females are able to slow the process and
minimize the deleterious effects of polyspermy. The lock and key interactions between
ZPCs and sperm receptors would then be subject to relative affinity differences in their
binding whereby the highest affinity interactions will trigger the acrosome reaction for
subsequent sperm penetration through the envelope. The presence of multiple sperm
receptors would enhance the competition and diversity of interactions. In addition, having
back-up systems or alternative pathways for sperm-binding could help to ensure that
fertilization does occur. For example, alternative pathways do exist in many signal
transduction pathways as has been observed when one gene is knocked out in a pathway
and then a second similar pathway (usually involving gene family members) takes over
and accomplishes the same goal.
98
As for the actual data, in L. laevis it was found that the predominantly expressed
ZPC genes were Llzpc.4 and Llzpc.5 (7.73 and 7.94 fold higher than the lowest Llzpc.6)
but could not be distinguished statistically from Llzpc.2 and Llzpc.3 which were midlevel in expression (5.21 and 5.35 higher than Llzpc.6), thus they were grouped together
as high expressers. This was the case since the more stringent Bonferroni correction was
applied when determining significant expression differences between each expressed
gene. Since Llzpc.2 and Llzpc.3 were significantly expressed in greater amounts when
compared to Llzpc.1 and Llzpc.6 (low expressers) they were classified with Llzpc.4 and
Llzpc.5 as having high expression. However, if a slightly more relaxed statistical method
had been used Llzpc.2 and Llzpc.3 would have likely received a moderate or mid-level
expression classification. Following the reasoning above, it is likely that these four genes
function in sperm-binding whereas the minimally expressed genes (Llzpc.1 and Llzpc.6)
are either structural or non-functional neutral components of the envelope. For X. laevis,
Xlzpc.1b and Xlzpc.2 were found to be expressed at relatively high levels as compared to
the lower expressing genes Xlzpc.1a and Xlzpc.3; and for X. borealis, the Xbzpc.1d,
Xbzpc.1c, and Xbzpc.2 were found to be highly expressed as compared to the lower
expressing Xbzpc.1e and Xbzpc.3 genes. Thus, it seems that between 50-66% of the ZPC
genes found in the frog ovary cDNA libraries are expressed at high levels. Future studies
will need to be performed to assess whether these high expressing genes actually do bind
sperm through binding assays using purified preparations.
As for the comparison of Xenopus ZPC genes, it was mentioned in the
introduction that Xenopus experienced a whole genome duplication about 30 mya
99
creating multiple gene locations in the genomes of both X. laevis and X. borealis; and
furthermore these species diverged about 10 mya. Thus, it should be possible to
determine the relationships of the Xenopus ZPC genes to each other with respect to
designating them as orthologous (separated by speciation) versus paralogous (separated
by gene duplication). Based on maximum likelihood and neighbor-joining phylogenetic
trees, a subset of Xenopus ZPC genes can be classified as being orthologous. The gene
groupings of zpc.2 and zpc.3 from both X. laevis and X. borealis can be classified as
being orthologous genes. Furthermore, these orthologous genes show relatively similar
levels of expression in each individual’s ovary. For instance, Xlzpc.2 and Xbzpc.2 both
received the high classification while Xlzpc.3 and Xbzpc.3 were categorized as lower
expressers. Since the speculation is that high expressing ZPCs (Xlzpc.2 and Xbzpc.2)
function in sperm-binding whereas alternative/loss of function is the likely fate of genes
with minimal expression (Xlzpc.3 and Xbzpc.3), these orthologs may share a common
function within the vitelline envelope.
The remaining ZPC genes expressed in X. laevis (Xlzpc.1a and Xlzpc.1b) and X.
borealis (Xbzpc.1e, Xbzpc.1d, and Xbzpc.1c) appear to be related because they cluster
together a from a clade within both phylogenetic trees, however their orthologous
relationships are indistinguishable. The genes within each species’ cluster together
indicating they are more closely related to each other rather than to the other species. The
existence of paralogs may have been a result of independent gene duplications after the
split from a common ancestor which would account for the variable numbers of ZPC
genes in the two species. Alternatively, the extra gene copies may be allele variants due
100
to the fact that Xenopus experienced a whole genome duplication event creating
tetraploid organisms (4 allele variants possible at a particular orthologous locus).
Furthermore, within each cluster there are ZPC genes that received both the high and low
classification. Since the high expressers likely play an active role in sperm-binding, they
may have duplicated to give rise to genes that have lost function or perform an alternative
function. Based on the earlier observation of similar expression in orthologs, it is possible
that genes with similar expression levels within these groups have an orthologous
relationship, however this cannot be definitively determined at this point.
Orthology could not be determined for L. laevis ZPC genes which may be due to
the considerable evolutionary distance between Xenopus and Lepidobatrachus (diverged
110-120 mya). However, Llzpc.4 is evolutionarily most similar to Xenopus ZPCs
suggesting that it is the ancestral gene since remaining gene copies are highly divergent.
Numerous independent duplications may have been the fate of the ancestral copy after
the split from Xenopus during evolution explaining the six expressed ZPC genes observed
in the ovary of L. laevis today. Alternatively, since these species are distantly related and
there is evidence of rapid evolution (particularly in the 3’ region) [28], L. laevis ZPC
genes may have accumulated many mutations which obscure their phylogenic
relationships with Xenopus and prohibit orthologous classifications (if they exist).
Interestingly, X. laevis was found to have 4 ZPC genes whereas X. borealis had 5
ZPC genes expressed in their respective single individual ovary cDNA libraries. There
are several possible reasons for this disparity. The first possibility is that the fifth gene is
actually an allelic form for an orthologous gene in X. borealis within the zpc.1 clade
101
(found only in this species), as posed earlier. Another possibility is that X. borealis had an
independent ZPC gene duplication that occurred after the split with X. laevis providing a
paralogous gene unique to its lineage. The ZPC gene family seems to be prone to high
levels of the birth and death of genes such as in the MHC gene family. This notion of
independent duplications after an evolutionary split is common and may also explain the
existence of the six observed ZPC genes in L. laevis. Alternatively, X. laevis may have
initially had this fifth gene that is related to the zpc.1 group, but it could have been
deleted from the genome or turned into a pseudogene. Other studies have indicated that
such a case has happened in other duplicated genes [50,18].
On the other hand, X. laevis may indeed have a fifth gene that was not detected
during the PCR amplification and sequencing of the ZPC cDNAs from its respective
library likely due to being expressed in low amounts. This duplicated paralog may have
acquired mutations in its regulatory region (i.e. promoters/enhancers) and diminished its
expression thereby reducing the chances of its inclusion in this study since ZPC genes
were identified by random sequencing of PCR amplified products from an ovary cDNA
library. Even though ZPC genes were classified as being high or low expressers, the
degree of expression is variable between species. As explained earlier, the fold
expression of each ZPC gene was compared to the lowest expresser in each species using
their CT values. It should be noted that the CT value of the Xbzpc.1e transcript within the
X. borealis cDNA library was extremely high (meaning very low amounts), and thus the
remaining genes were shown to have much more expression when compared to it (i.e.
Xbzpc.2 was expressed 17.63 fold more than Xbzpc.1e). When Xbzpc.1e was removed
102
and data re-analyzed for expression levels, the profiles for X. laevis and X. borealis ZPC
genes were very similar (i.e. two high expressers in the range of being 2-3 fold higher
than the two low expressers). However, further studies will have to be performed to
determine which one of these explanations is correct.
Although all the ZPC genes examined in this study were assumed to have been
expressed from the oocyte itself, it is also possible that the origin of some of the
expressed ZPCs were derived from the follicle cells that surround and nurture the
growing oocyte. Studies in mice and X. laevis have demonstrated that the oocyte does
indeed express ZPC genes, but it has not been ruled out that the follicle cells do not
contribute any ZPC gene products to the zona pellucida vitelline envelope. In particular,
immunolabeling in mice has shown ZPC protein present within the oocyte’s golgi
apparatus, secretory vesicles, and vesicular aggregates near the membrane surface [22].
Transcription factors implicated in effecting ZP glycoprotein expression have been found
to be expressed by oocytes and, to a lesser degree, in surrounding follicle cells during
folliculogenesis [58,59]. However, there have been no exhaustive studies to determine
whether follicle cells could be expressing ZPC genes and secreting them for
incorporation into the growing matrix. This could very much impact the paradigm of how
the egg envelope structure is synthesized since the important location for the spermbinding ZPC glycoprotein is on the most exterior surface of the envelope and follicle
cells are located at the outer edge of the egg. This could be examined by in situ
hybridization experiments or separating follicle cells from oocytes to examine their
expression by PCR.
103
Another interesting nuance to consider is that the ovarian cDNA library
constructed for each of the anuran species used in this research was generated from
oocytes at all stages of development. ZPC expression begins during stage I of oocyte
development and continues until the egg reaches maturity just before ovulation (stage 5).
The differential ZPC gene expression observed in L. laevis, X. laevis, and X. borealis
may be due to the developmental timing of when the ovaries were collected. For
example, more mature oocytes may have a completely different profile of ZPC
expression than the early stage oocytes. Temporal changes in expression of each gene
copy could account for concentration differences observed by each transcript. However,
there is no evidence to indicate that hormonal induction of oogenesis in frogs causes a
bias toward one stage of egg development since it all stages can be observed in the ovary
by inspection. Developmental expression differences could be examined by removing
oocytes from ovaries and performing quantitative PCR experiments on cDNA libraries
generated from oocyte populations from each of the 5 stages of development.
In summary, the current research supports the hypothesis that ZPC genes
discovered in L. laevis, X. laevis, and X. borealis are unequally expressed within their
respective ovaries and that orthologs have a similar pattern of expression. Quantitative
assessment by qPCR indicated multiple genes were predominantly expressed while
remaining copies were lower expressers. The most likely scenario is that the highly
expressing ZPC genes function as sperm-binding molecules whereas the lesser expressed
genes have altered their function. This provides a testable hypothesis for further study in
which the different ZPC glycoproteins will need to be purified and tested in sperm
104
binding assays. These functional studies will be essential to further clarify the
phenomenon of the expression of multiple ZPC genes in different amounts within the
ovary of these frog species.
105
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