Genetic Structure of Endangered Northeastern Bulrush (Scirpus ancistrochaetus) in
Pennsylvania, USA using information from RAPDs and SNPs
Kendra Cipollini • Kendra Millam • Douglas Burks • Don Cipollini • Sarah Girod • Zachary
VanGundy • Jeffrey Peters
Kendra Cipollini () • Douglas Burks • Sarah Girod • Kendra Millam • Zachary VanGundy
Wilmington College
1870 Quaker Way
Wilmington, OH USA 45177
e-mail: KAL143@alumni.psu.edu, FAX : 937-383-8530, Phone : 937-382-6661 x367
Don Cipollini • Kendra Millam • Jeffrey Peters
Wright State University
3640 Colonel Glenn Hwy
Dayton, OH USA 45435
1
Abstract Northeastern bulrush, Scirpus ancistrochaetus, is a federally endangered wetland plant
species found primarily in Pennsylvania, USA. Data on the population genetic structure of this
species is needed by conservation managers to prioritize conservation efforts. In this study, we
used two genetic marker systems to examine diversity and structure of this species in populations
throughout Pennsylvania. The first simple and inexpensive approach utilized RAPD primers,
while our second more detailed approach relied on DNA sequencing of single nucleotide
polymorphisms (SNPs). We found genetic variation using both RAPDs and sequencing and
found some overlap in information between the two methods, including clusters of related
populations and the identification of a genetically unique population. Future studies will seek to
examine variation across the full geographic range of the species.
Keywords conservation • Cyperaceae • plant • population structure
Introduction
Northeastern bulrush, Scirpus ancistrochaetus Schuyler (Cyperaceae), is a sedge that is currently
classified as endangered in the United States (Schuyler 1962, USFWS 1991). This species is
found in eight states in the northeastern United States, with over half of the known populations
located in the state of Pennsylvania (USFWS 1991). Nearly all of the existing research on this
species involves studies of ecological factors that may limit its distribution, such as water levels
(Lentz and Dunson 1998), light availability and herbivory (Lentz and Cipollini 1998; Cipollini
and Cipollini 2011) and water chemistry (Lentz and Dunson 1999; Lentz-Cipollini and Dunson
2006). Its habitat in Pennsylvania consists of fairly small, usually ephemeral, wetlands isolated
2
from each other in a forested landscape (Cipollini and Cipollini 2011). The species can be found
either in a single isolated wetland or in a small percentage of wetlands within a complex of
wetlands clustered together, yet still generally isolated from other such complexes.
Very little is known about gene flow and seed dispersal in S. ancistrochaetus and whether
populations are genetically isolated from one another. Because the seeds have barbed bristles
(e.g., Carter 1993) and easily attach to clothing (K. Cipollini, personal observation), it is
hypothesized that seeds are dispersed by animals (Cipollini and Cipollini 2011). However, there
appears to be little recruitment into the population through seedlings (K. Cipollini, personal
observation). The primary mode of reproduction once a population establishes is most likely
clonal, both through the expansion of an individual clump by shoots forming from the roots and
by shoots forming in the nodes and heads of the flowering culms, which subsequently fall into
the water and form roots (Bartgis 1992). This reproductive strategy, whereby one or a few
individuals found a population, followed by extensive clonal growth, is termed the “Initial
Seedling Recruitment (ISR)” strategy (Eriksson 1989). Some plant species rely heavily on
clonal reproduction (Jusaitis and Adams 2005), and this strategy could result in strong
differentiation even among populations within close proximity to each other (McLellan et al.
1997). Like animal dispersal of seeds, wind pollination may also facilitate gene flow among
populations and thereby inhibit genetic differentiation (Loveless and Hamrick 1984); populations
of S. ancistrochaetus are often widely separated in the field and it would appear unlikely that
many exchange genetic material through wind pollination over long distances.
The extent to which populations of S. ancistrochaetus vary genetically at either a local or
regional scale is unknown. Because this species appears to reproduce primarily asexually, some
of the populations may consist of one or a few clones and exhibit low within-population
3
variation (Vandepitte et al. 2010). However, genetic diversity of some clonal species can be high
(Esselman et al. 2009; Goertzen et al. 2011). Additionally, the population size within a wetland
can fluctuate from year to year, which can decrease genetic variation due to the effects of genetic
drift (Loveless and Hamrick 1984). Genetic diversity is critical for endangered populations to
maintain the capacity to respond to environmental change (Barrett and Kohn 1991).
Unfortunately, the long-term viability of wild populations is frequently assessed by monitoring
adult census sizes only. In fact, a recent recommendation to change the legal status of S.
ancistrochaetus from “endangered” to “threatened” was based primarily on census information
(USFWS 2009; Cipollini and Cipollini 2011). However, the genetic effective population size is
of primary importance for long-term viability, and monitoring of adult census size can give
misleading impressions of this variable (Brede and Beebee 2006). Examining genetic diversity
within and among populations can provide information that can be used to examine effective
population sizes. Such data will also allow identification of ecologically significant units to
target for enhanced protection and management of a species of concern (Pillon et al. 2007).
Measures of population genetic structure and history can be obtained using co-dominant
DNA markers such as RAPDs (Randomly Amplified Polymorphic DNA) or DNA sequences
including SNPs (Single Nucleotide Polymorphisms). RAPDs are a relatively low cost method
that can quickly produce a large number of dominant markers, even when there is no DNA
information available on the species of interest (Williams et al. 1990), and have been used in the
study of diversity in endangered clonal plants (McGlaughlin and Friar 2007). However, RAPDs
can have a low level of reproducibility (Jones et al. 1997) and are best used in conjunction with
other markers. With advances in sequencing technology, single nucleotide polymorphisms
(SNPs) have been increasingly used as a method for elucidating population history (Brumfield et
4
al. 2003). SNPs are particularly useful in the case of species with limited genetic diversity (e.g.,
Foster et al. 2010), and have been used to study population structure in fungal species of
conservation interest (Amend et al. 2010). Segments of DNA containing SNPs can be identified
in species for which little or no sequence information is available by using the sequences of
microsatellites previously developed for closely related species (Primmer et al. 2002). In this
study, we used two approaches – RAPDs and SNPs - to examine genetic diversity and structure
in S. ancistrochaetus from 17 populations sampled throughout Pennsylvania.
Materials and Methods
Sampling and DNA Extraction
Seventeen sites were chosen based on their distribution in Pennsylvania, with an attempt to
sample fairly evenly across the range (Fig. 1). Distances between sites ranged from ~4 km to
~250 km. Population sizes of the sampled populations ranged from only 50 stems to over
100,000 estimated stems. When multiple samples were collected per site, we took care to avoid
collection from the same clump, though we cannot rule out the possibility that samples may be
part of the same clone. Leaf samples were placed in bags with anhydrous silica gel desiccant
(Fisher Scientific, Pittsburgh, PA, USA) until returned to the laboratory, where they were stored
at -4°C. Approximately 2 mg of leaf material was homogenized in liquid nitrogen using a tissue
homogenizer or approximately 10 mg of leaf material was ground using a mortar and pestle in
liquid nitrogen. DNA was then isolated using DNeasy Plant Mini Kits (Qiagen Sciences,
Germantown, MD, USA), following manufacturer instructions.
5
RAPDs
RAPD analyses were performed in laboratories at Wilmington College. PCR amplification of
RAPD bands was performed using RAPD 10mer primers (Operon Technologies, Inc., Alameda,
CA, USA). Approximately 20 ng of genomic DNA was mixed with 200 nmol of primer in a
buffer containing 1X reaction buffer, 6 mM MgCl2, 100uM of each dNTP, and 2.5 units of Taq
DNA polymerase (Qiagen Sciences, Germantown, MD, USA), with a final volume of 50μL.
Amplification was done with a denaturing temperature of 94°C for 30 seconds for renaturation,
34°C to 39°C, depending on primer, for 30 seconds, and 74°C for the polymerization reaction for
90 seconds. This cycle was repeated 39 times. A final polishing cycle was done at 74°C for
2,400 seconds. Amplified DNA was separated on 1.7% agarose gels (MBL International
Corporation, Woburn, MA, USA) at 150 V for four hours at 7°C and stained with ethidium
bromide (EtBr). Bands were scored by visual methods from enlarged photographs.
We screened ten RAPD primers for variation. Three RAPD primers (OPC-06 [5′GAACGGACTC-3’], OPC-19 [5′-GGTGCACGTT-3′], OPC-20[5′-ACTTCGCCAC-3′)
produced diverse banding patterns across sites. To examine variation within a site, we used one
RAPD primer (which showed variation between sites) for 10 individuals collected from one
wetland and failed to find variation in RAPD banding patterns. Because we did not find
variation for our RAPD marker within our populations, we arbitrarily selected one individual
from each site for our final population structure analyses to focus on variation between
populations. We constructed equally weighted maximum parsimony trees for the RAPD data
using PAUP* 4.0b10 (Swofford 1999). We used a Mantel test in the program ZT (Bonnet & Van
de Peer 2002) to test for an association between geographic and genetic distance. This test
6
accounts for the non-independence of correlating distance matrices. Genetic distances
(uncorrected p-distance) were calculated for RAPDs using MEGA 5.05 (Tamura 2011).
SNPs
We discovered anonymous loci containing nucleotide polymorphisms (SNPs) during the process
of screening microsatellites developed for other sedges for their possible utility within S.
ancistrochaetus; work related to SNPs and microsatellites were performed in laboratories at
Wright State University. In this study, we initially attempted to locate species-specific
microsatellites for S. ancistrochaetus by amplifying S. ancistrochaetus DNA using microsatellite
primers developed for two species of Scirpus L. s.l.: Schoenoplectus americanus (Pers.) Volkart
ex Schinz & R. Keller (Blum et al. 2005) and Scirpus mariqueter Wang et Tang (Zhou et al.
2009), using the respective methods of each author.
DNA was amplified using RedMix PLUS Taq master mix kits (GeneChoice, Inc., USA)
on Eppendorf Mastercycler and BioRad i-cycler thermal cyclers. Resulting DNA fragments
were visualized on agarose gels stained with EtBr. Negative controls were used to check for
DNA contamination. Resulting bands were excised and purified with QIAquick Gel Extraction
Kits (Qiagen, Inc.), and if necessary were amplified and gel-purified a second time (using the
same primers). Purified PCR product was directly cycle sequenced using ABI Prism Big Dye
terminator V 3.1 reagents (Applied Biosystems, Inc., Foster City, CA, USA), purified with
Sephadex G-50 Fine powder on Multiscreen column loader plates, and run on an ABI 3730
automated sequencer (Applied Biosystems).
Of the sixteen primer-pairs developed for S. americanus, three produced clean DNA
sequences of a useful length: SCAM.01, SCAM.06, and SCAM.08 (Blum et al. 2005). However,
7
of these, only SCAM.01 matched the DNA region containing a microsatellite in S. americanus
(though minus the repetitive motif), whereas the remaining primers amplified and sequenced
novel, anonymous loci (hereafter designated SA.06a, and SA.08, respectively). Of the eight S.
mariqueter primer-pairs (Zhou et al. 2009), only one (SM6) produced clean sequences of
sufficient length in S. ancistrochaetus, which consisted of an anonymous locus hereafter referred
to as SA.06b. We then designed new primers to specifically target each of the four products and
to further screen these loci for SNPs within S. ancistrochaetus (Table 1).
We chose two representatives from each of the 17 sampled sites to screen for
polymorphic DNA sequences in S. ancistrochaetus. Approximately 20 ng of genomic DNA was
amplified in 25μL reactions using Go Taq Green pcr Master Mix (Promega), and 1.25 μM of
each forward and reverse primer. PCR was conducted on Eppendorf Mastercycler Pro thermal
cyclers with an initial denaturing step of 94°C for 7 min., followed by 45 cycles of 94 °C for 20
seconds, 57 °C for 20 seconds., and 72 °C for 1 min., and a final elongation step at 72 °C for 7
min. PCR products were visualized on 1.5% agarose gels using SYBR Green (Invitrogen),
magnetic-bead cleaned with Ampure (Agencourt) and sequenced using the forward primers and
BigDye v. 3.1 Terminator Cycle Sequencing Kits (Applied Biosystems, Foster City, CA). The
cycle-sequencing products were sephadex-cleaned and sequenced at the DNA Sequencing
Facility at Yale University (New Haven, CT, USA) on an ABI 3730xl DNA Genetic Analyzer
(Applied Biosystems, Foster City, CA). We constructed a haplotype network for DNA sequence
data using the median-joining algorithm in NETWORK (Bandelt et al. 1999).
We tested whether SNP alleles were randomly distributed among wetlands using a
binomial test. For this analysis, we calculated the probability that two individuals sampled from
the same wetland would have identical alleles as
8
,
where pi is the frequency of the ith allele, and n is the total number of alleles. We then calculated
P(x > I), where I is the number of wetlands with two identical individuals and x is the number
from the binomial distribution. We assumed haploidy because we did not find any heterozygotes
that would indicate that these loci were diploid; thus, our analyses were conservative.
Results and Discussion
In this study, we found genetic variation within the endangered species S. ancistrochaetus using
two markers – RAPDs and SNPs. The presence or absence of 28 loci were scored for the three
RAPD primers (OPC-06, N = 9 loci; OPC-19, N = 13 loci; OPC-20, N = 6 loci). Eighteen
(64.3%) loci were polymorphic across the 17 sites, and eight (28.6%) loci were parsimony
informative. On average, individuals from different sites differed from each other at 3.5 loci
(range = 0–9 loci; Fig. 2). Among the four loci sequenced for these samples, only SA.06b and
SA.08 were polymorphic (nucleotide diversity = 0.0041 and 0.0046, respectively).
Data from both RAPDs and SNPs interestingly identified one site, Site BBG, as the most
genetically distinct. For the RAPD data, Site BBG differed from all others at a mean of 6.9 loci
(range = 5–9 loci), whereas the maximum number of differences between any other two sites was
seven loci. For the SNP data, SA.06b contained a single polymorphic position that differentiated
Site BBG from all other sites. SA.08 contained six polymorphic positions (Fig. 3), with the
greatest difference being found between Site BBG and the remaining sites (five differences for
each pairwise comparison). The congruence of the RAPD and SNP results in identifying the
most distinct population suggests that RAPDs may be able to provide useful information about
the genetic differences between populations at the coarsest scale in this species. Other studies
9
using RAPDs in conjunction with other markers have found this to be the case; for example,
Longheed et al. (2000) found that RAPDs were as sufficient as microsatellites at the regional
scale for analyzing population structure. The genetic uniqueness of Site BBG suggests that it
might rank as a high priority when designing conservation strategies to conserve the full
complement of genetic diversity within this species. For example, conservation managers may
implement enhanced monitoring of Site BBG to potentially mitigate against any threats from
canopy closure, herbivore damage, animal activity or invasive species, the primary threats to this
species in its southern range (Cipollini and Cipollini 2011).
Some evidence suggesting geographic patterns in genetic variation of populations was
found with both RAPD and SNP markers. Among the eight parsimony-informative RAPD loci,
the rarer of the two variants tended to be clustered geographically (Fig. 4). Likewise, Sites FH,
CRB and GFT were the only sites that shared the presence or absence of all loci (Fig. 2), and
these were three of the four most northern sites. These qualitative assessments suggest some
evidence of isolation-by-distance; however, there was not a significant relationship between
geographic distance and genetic distance at RAPD markers (Mantel test, r = 0.101, P = 0.26).
There was some evidence of geographic patterns for the SNP data as well. Sites BK, 3SH, and
MKR differed from the remaining 13 sites at two nucleotide positions (Fig. 3); these three sites
were among the most southerly sampled sites in our data set and clustered together
geographically. However, Site TM, the most southern site, was identical to the central and
northern sites (Fig. 3) for SNPs and clustered with these sites for one of the rare RAPD variants
(Fig. 4). Distance alone may not be a good measure of dispersal, as corridors and connectivity
can influence genetic structure (Hu et al. 2010). Advances in geospatial technology and analysis
will allow more detailed investigation of genetic structure and gene flow in future studies (Chan
10
et al. 2011). The habitat of S. ancistrochaetus, which is found primarily on forested ridges
separated from other such ridges by agricultural landscapes, facilitates north-south dispersal
along ridges rather than east-west across human-dominated valleys; therefore, genetic distance
via connectivity may be more relevant than simple geographic distance for this species (e.g.,
Pérez-Espona et al. 2008).
For SNP loci, all pairs of individuals sampled from each of the 17 wetlands shared
identical alleles. Given the overall level of genetic diversity, the probability of sampling the same
allele twice at every site was low (P = 0.0003 for SA.08 and P = 0.1 for SA.06b). Furthermore,
the probability of sampling two copies of the rare allele from the same wetland for SA.06b was
low (P = 0.003; the frequency of the rare allele squared). Thus, the distribution of alleles among
wetlands deviated significantly from a random distribution for both loci; this deviation would be
stronger if the loci are diploid. However, because our SNPs occur on anonymous loci, which
potentially could be located on haploid chloroplast or mitochondrial DNA, our sequence data
could represent only the maternal population history. To determine whether sexual reproduction
is occurring and whether populations are genetically isolated, a genomic approach is required
that unequivocally provides data on both maternal and paternal contributions to wetlands.
However, the preliminary results from the RAPDs for one population presumably include
nuclear markers, and we also failed to find variation within one wetland.
Divergence between populations rather than within populations could indicate adaptation
to local ecological conditions (Xie et al. 2001; Jusaitis and Adams 2005). Previous studies found
no ecotypic variation in response to the environmental variable of water level (Lentz and
Cipollini 1998). Regardless, the lack of genetic variation within wetlands is consistent with
11
clonal reproduction, and genetic differentiation among populations can be low for clonal plants
(Honnay et al. 2006).
A number of population genetic measures important for addressing conservation issues,
such as effective population size, genetic diversity and genetic population structure have been
difficult to quantify with adequate statistical power in this study. Our results indicate the need
for developing additional nuclear DNA markers (such as SNPs) suitable for quantifying fine
scale patterns of genetic diversity. To more fully understand limitations to the amount of genetic
variation within individual wetland sites, more extensive within-population sampling with these
sensitive nuclear DNA markers is needed. We are currently pursuing a next-gen genome
sequencing study to identify additional SNPs and will use this information to study population
structure in greater detail, both in Pennsylvania wetlands and in other states throughout the range
of S. ancistrochaetus.
Acknowledgments We thank the Pennsylvania Wild Resource Conservation Fund, Western
Pennsylvania Conservancy, US Fish and Wildlife Service and Pennsylvania Natural Heritage
Program for their roles in funding and otherwise supporting this research. We thank Doug
Woodmansee, Don Troike and the students of BIO440-441 for their helpful comments during the
development of this project. We thank Christy Clark and Philip Lavretsky for laboratory
support. We thank the Pennsylvania Game Commission, Pennsylvania Department of
Conservation and Natural Resources (Bureau of Forestry) and The Nature Conservancy for
permission to collect plant samples. We thank Emmett and Otto Cipollini for field assistance.
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Figure Legends
Fig. 1 Map of sampling sites in Pennsylvania.
Fig. 2 One of 634 equally parsimonious trees constructed from RAPD loci (length = 24,
consistency index = 0.75).
Fig. 3 Network topology (A) and distribution of alleles (B) at locus SA.08 for 17 sampling
localities. In (A), each circle indicates an allele, the area of the circle is proportional to the
number of sites from which the allele was sampled, and each line separated by a square indicates
a mutation separating the alleles. In (B), the color of circles corresponds to the alleles presented
in (A). Note that in all cases, both individuals sampled at each site shared the same allele.
Fig. 4 Distribution of variants at 8 parsimony-informative loci from four RAPD markers. Open
circles indicate that a band for that locus was present; closed circles indicate the band was
absent.
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Table 1. Primers designed to amplify and sequence SNP loci for Scirpus ancistrochaetus.
Locus
SA.06b
Primers
F- CTCATGCTGCTCGGCATT
R- GAAGAAGGTTCATTGGTATTGGTT
SA.06a
F- TTTACTTTCAGAGAAACAGGCAAC
R- GACTTGCAGGAGCAATGGAT
SA.08
F- CGTGTATACTCCAGCCGACA
R- GGTAAGGAGGTGCAGAAGGA
SA_SCAM.01
F- AGCACAAAGATCACACCTTTT
R- AAGCACAAACTTGAGAAAACC
19