J. Zool. Syst. Evol. Research 42 (2004) 215–222
Ó 2004 Blackwell Verlag, Berlin
ISSN 0947–5745
Received on 25 May 2004
1
Section for Zoology, Natural History Museums and Botanical Garden, University of Oslo, Oslo, Norway; 2Division of General
Human Genetics, Institute of Anthropology and Human Genetics, University of Tübingen, Tübingen, Germany
Allelic variation, fragment length analyses and population genetic models: a case
study on Drosophila microsatellites*
L. Bachmann1, P. Bareiß1,2 and J. Tomiuk2
Abstract
The allelic variation of 16 microsatellite loci from selected species of the Drosophila melanogaster and D. obscura group was determined. Intraand interspecific sequence comparisons allowed discrimination of mutations affecting the repetitive microsatellite from those affecting the flanking
regions. The hypotheses that slippage needs a minimum number of repeats in order to become efficient with respect to microsatellite variability,
and of an increased mutation rate with increased length of the microsatellite are supported by the results of our analyses. There is in particular at
the interrupted complex microsatellite locus BICOID in the species of the D. obscura group, extensive variation in the flanking regions in addition
to length and sequence variation of the repetitive microsatellite. The allelic variation at this locus can hardly be explained by slippage alone.
Estimates of microsatellite variability by fragment length analyses will pick up only a minor fraction of allelic variation at such loci, and
conclusions that are based on the stepwise mutation model will not hold.
Key words: Drosophila melanogaster group – Drosophila obscura group – microsatellites – repetitive DNA – sequence analysis – slippage
replication
Introduction
Microsatellites or simple sequence repeats are tandemly
repeated 1–6 bp long sequence motifs (Tautz and Schlötterer
1994; Goldstein and Pollock 1997; Li et al. 2002). Homopolymers, however, are excluded in some definitions (Chambers
and MacAvoy 2000). According to these authors, microsatellites can be grouped into six categories. (1) Microsatellites can
consist of identical repeats (perfect microsatellites). (2) Few
point mutations can interrupt the perfect microsatellites
(interrupted microsatellites). (3) Microsatellites can consist of
two adjacent perfect microsatellites with different motifs
(compound microsatellites). (4) The two repetitive sequences
of compound microsatellites can be interrupted by a short
non-repetitive sequence (interrupted compound microsatellites). (5) Complex microsatellites can contain several different
perfect repetitive sequences (complex microsatellites). (6)
Complex microsatellites can be interrupted by non-repetitive
sequences (interrupted complex microsatellites).
Microsatellites are more or less randomly dispersed in the
genomes of all eukaryotes although there are differences in
structure, length and number of microsatellites between species
(Bachtrog et al. 1999; Chambers and MacAvoy 2000; Harr
and Schlötterer 2000). Microsatellites occur more frequently
and are longer in vertebrates than in invertebrates. In
Drosophila, microsatellites are relatively short and most of
them are dinucleotide repeats (66%), followed by trinucleotide
repeats (30%) and a small fraction of tetranucleotide repeats
(4%) (Schug et al. 1998).
The mode of evolution of microsatellites has been discussed
in particular with respect to their mutational instability.
Compared with other loci, the mutation rate of microsatellite
loci seems to be high with 10)2–10)6 per locus and generation,
for example, 10)4–10)6 for Drosophila melanogaster (Schlötterer et al. 1998) and 10)3–10)5 in mammals (Schug et al.
1997). Studies of Drosophila species (Goldstein and Clark
1995) and yeast (Wierdl et al. 1997) indicate that the mutation
rate of microsatellites is positively correlated with the number
of repeats but the impact of the length of microsatellite motifs
is still discussed. A study of human families revealed, for
example, a four times higher mutation rate for tetranucleotide
than dinucleotide repeats (Weber and Wong 1993), whereas
Chakraborty et al. (1997) observed in a population study, a
two times higher rate for dinucleotide microsatellites.
There are two major mutational processes that can change
the number of repeats of microsatellites: (1) Slippage replication, a mispairing of the matrix and replicated strands during
DNA replication (Levinson and Gutman 1987), and (2)
recombination processes such as unequal crossing-over and
gene conversion (Garza et al. 1995). Slippage is considered the
dominant process for the generation of microsatellite variability (Schlötterer 2000) and it is assumed that slippage needs a
minimum number of repeats in order to become efficient with
respect to microsatellite variability. This implies that mutation
processes different than slippage must first extend short
repetitive sequences (protomicrosatellites), before slippage
can generate microsatellite variability (Rose and Falush
1998; Lai and Sun 2003). According to theoretical analyses
(e.g. Stephan and Kim 1998), slippage becomes efficient when
protomicrosatellites consist of more than five repeats. However, our understanding of the evolution of protomicrosatellites is far from being complete.
Various models have been put forward in order to explain
allelic variability of microsatellite loci. Parameters such as
increasing mutation rates with increasing repeat numbers,
limited length of microsatellites, higher probability for microsatellite expansion than for reduction, or uncoupling of the
slippage by interruptions of perfect repetitive sequences
through point mutations (e.g. Zhivotovsky et al. 1997; Kruglyak et al. 1998; Sibly et al. 2001) were used to modify simple
stepwise mutation models (Otha and Kimura 1973). However,
to date, there is no model available that can perfectly predict
the allelic variation observed in experimental or natural
*Dedicated to Prof. Ernst Mayr on the occasion of his 100th birthday.
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216
populations (e.g. Colson and Goldstein 1999). Nevertheless,
statistical tools that are based on stepwise mutation models
were developed to analyse population structures by means of
microsatellite variation (Goldstein et al. 1995a,b; Slatkin 1995;
Pritchard and Feldman 1996). However, processes creating
microsatellite variation are more complex and simple stepwise
mutation models should not be applied easily (Colson and
Goldstein 1999). Coulson et al. (1998) proposed an individual
heterogeneity measure d2 that is also based on the number of
repeats and can easily be expanded to a grand mean over
groups and populations.
Microsatellites are frequently used markers for analysing
various problems in biology. The high variability along with
almost fully automated analyses techniques allows a rapid
screening of large sample sizes. Microsatellites are efficient
tools for the identification of individuals and for the assessment of individualsÕ relationships (Chambers and MacAvoy
2000). In almost all studies conducted at present, microsatellite
variation is determined by automated fragment length analysis. The length of microsatellites (usually PCR products) is,
therefore, the only criterion for the identification of alleles and
subsequent statistical analyses may be affected by this experimental approach. Fragment length analysis cannot discriminate length variation of the microsatellite and length variation
of the flanking regions that are amplified together with the
microsatellite. Allelic diversity of microsatellite loci may,
therefore, be underestimated.
In this study, we analyse sequence data of microsatellites in
coding and non-coding regions of selected Drosophila species.
We determined the sequence variation of microsatellites and
their flanking sequences and the impact of the most likely
mutation processes in order to explain the observed variation
of the respective microsatellite loci.
Material and methods
Database search for microsatellite sequences
GenBank and personal websites, such as, http://www.mbg.cornell.edu/
aquadro/aquadrolab.html of C. Aquadro (Cornell University Ithaca,
NY, USA), were searched for microsatellite sequences that allowed an
intra- and interspecific comparison. The search was guided by three
criteria: (1) Sequence data must be available for closely related species.
(2) Several microsatellite loci must be described for these species. (3)
Sequence data of several microsatellite alleles must be available at least
in one species.
Experimental studies of microsatellite sequences
Microsatellites previously described for D. pseudoobscura were amplified and sequenced from individuals of laboratory cultures of eight
species of the D. obscura group. They are: D. miranda, D. obscura,
D. ambigua, D. tristis, D. bifasciata, D. subobscura, D. madeirensis and
D. guanche. The microsatellites BICOID and DPSX006 were characterized for individuals from natural populations of D. subobscura,
D. obscura, and D. helvetica that were collected in Tübingen, Germany,
during summer 2003 by D. Sperlich.
DNA isolation, PCR amplification of microsatellites and
sequencing
The DNA from Drosophila individuals was isolated according to the
manual of the ÔDNA Isolation KitÕ (Gentra Systems, Minneapolis,
MN, USA). Cloned Pfu DNA polymerase (Stratagene, La Jolla,
CA, USA) was used for the PCR-based amplification of microsatellites according to the supplier’s instructions. PCR products were
Bachmann, Bareiß and Tomiuk
subsequently purefied by means of the QIAquick PCR purification kit
(Qiagen, Hilden, Germany) and sequenced on an ABI 3100 automatic
sequencer (Applied Biosystems, Foster City, CA, USA) according to
the chain termination method (Sanger et al. (1977) using Big Dye
chemistry (Applied Biosystems).
The microsatellite loci DPS2003, DPS2004, DPS2005, DPS2007,
DPS4001, DPSX001, DPSX003, DPSX006, DPSX009, RUNT,
TROP1, E74A, and BICOID were tested using primers described by
Noor et al. (2000).
Results
To our surprise sequences of only 15 microsatellite loci that
met the selection criteria could be retrieved from databases.
Eleven loci occur in species of the D. melanogaster group and
four in species of the D. obscura group. Eleven of them had a
dinucleotide, three loci a trinucleotide, and one locus a
tetranucleotide motif (see Tables 1 and 2). The majority of
microsatellite sequences from D. melanogaster group species
were published by Colson and Goldstein (1999). The following
sequences were retrieved (locus: accession number): RHOb:
AF067878-AF067882; ABDB: AF067865-AF067868, L07835,
X51663; U1951: AF067911-AF067914, X53543; DSRC:
AF067908-AF067910, AC010665; NANOS: AF067873AF067876, AY075406, AE003725, M72421; SIDNA:
AF067892-AF067895,
X79340;
CLONE:
AF067883AF067886, AE003710; DME2910: AJ271561, AJ291063,
DMA246211, DME291016, DME29104, DME291052,
DME291055, DME291056, DME291058, DME291061,
DME291064, DME291066, DME291071, DME291072,
DME291088, DME291092, DME291096, DME291100,
DME291103, DME291105, DME291107, DME291110,
DME291111, DME291113, DSE246210, DSI246209; HOX:
AF067869-AF067872;
SIMA:
AF067928-AF0679233,
U43090; EHAB: AF067924, AF067934, AF067935, X72303;
DPS4002: AF320181, AF320182, AF320185, AF320187AF320189, AF450831, AF450833, AF450835-AF450840,
AF450865, AF450869; DECPENT: AY012610-AY012617;
DPSX006: AF157573; DPSX010: AF320138, AF320152,
AF320154, AF320166, AF450643, AF450644, AF450648,
AF450649, AF450656, AF450657, AF450659, AF450662,
AF450665, AF450666, AF450672; BICOID: AF450963,
AF450964, AF450949, AF450954, AF450955, AF450962.
In order to extend the data set, we attempted to amplify the
microsatellite loci DPS2003, DPS2004, DPS2005, DPS2007,
DPS4001, DPSX001, DPSX003, DPSX006, DPSX009,
RUNT, TROP1, E74A, and BICOID in various species of
the D. obscura group using the primers described by Noor
et al. (2000). These primers have been developed in order to
amplify the respective microsatellites in D. pseudoobscura.
They all amplified homologous microsatellites in D. miranda,
but only the two loci DPSX006 and BICOID could be
amplified from all D. obscura group species tested.
The compiled data set was subsequently analysed for
sequence variability, i.e. the number of tandemly repeated
motifs, length variation of the microsatellite, length variation
of the flanking region, and sequence variation of the flanking
region. Furthermore, we estimated the ratio of the number of
alleles and length variants detectable by automated fragment
length analyses (Tables 1 and 2). The variability of microsatellites cannot, as already observed by Colson and Goldstein
(1999), be assigned exclusively to the variation of the number
of tandemly repeated motifs. In addition, most loci show
10–26
10, 7 + 2
10/9 + 2
8–11 + 2
8–11 + 2
Number of repeats
D. melanogaster
D. simulans
D. sechellia
+
)
+
)
Length variation of flanking regions
D. melanogaster
D. simulans
+
D. sechellia
)
Sequence variation in flanking regions
D. melanogaster
)
D. simulans
)
D. sechellia
)
3
1
1
+
n.a.
n.a.
+
n.a.
n.a.
+
n.a.
n.a.
1
According to the definitions given in the introduction.
n.a., not applicable.
Number of alleles detectable with fragment analysis
D. melanogaster
2
4
D. simulans
2
1
D. sechellia
2
+
)
Length variation of microsatellite
D. melanogaster
+
D. simulans
+
D. sechellia
+
6
6
2–17
1
1
1
1
1, 2
1, 2
2
2
AT
Microsatellite type1
D. melanogaster
D. simulans
D. sechellia
CA
U1951
3
1
1
AC
Motif
ABDB
Number of different alleles available from data bases
D. melanogaster
2
4
D. simulans
2
2
D. sechellia
2
RHOb
Locus
2
1
1
)
n.a.
n.a.
)
n.a.
n.a.
+
n.a.
n.a.
5+3
5+3
6–7 + 3
2
2
2
2
1
1
TA
DSRC
4
2
1
)
)
n.a.
+
)
n.a.
+
+
n.a.
6, 7
6
8–21
1
1
1
4
2
1
TA
NANOS
2
2
1
)
)
n.a.
+
+
n.a.
)
)
n.a.
5
5
5
1
1
1
2
2
1
GC
SIDNA
2
2
1
+
+
n.a.
)
)
n.a.
)
+
n.a.
8, 9
10
10
1
1
1
2
2
1
GT
CLONE
15
2
1
+
)
n.a.
+
+
n.a.
+
)
n.a.
6–13, 5+(4–11), 5+(7–9)+9,
5 + 2 + 5, 5 + 3 + 4
5+4+3
5+4+3
1, 2
2
2
22
2
1
GT
DME2910
1
2
1
n.a.
)
n.a.
n.a.
)
n.a.
n.a.
+
n.a.
3, 4
4
5
1
1
1
1
2
1
CAG
HOX
3
2
1
+
)
n.a.
)
)
n.a.
+
+
n.a.
5 + 2, 6 + 3
5+3
7, 5 + 3, 8 + 3
1, 2
2
2
4
2
1
CAG
SIMA
1
2
1
n.a.
)
n.a.
n.a.
)
n.a.
n.a.
+
n.a.
4, 5
5
6
1
1
1
1
2
1
AGCC
EHAB
Table 1. Sequence variation of eleven microsatellite loci from species of the Drosophila melanogaster group. Sequences were retrieved from databases. Only sequences of different alleles were compiled and
analysed
Allelic variation of Drosophila microsatellites
217
218
Bachmann, Bareiß and Tomiuk
Table 2. Sequence variation of eleven microsatellite loci from species of the Drosophila obscura group. Sequences were either retrieved from
databases or determined in this study. Only sequences of different alleles were compiled and analysed
Locus
DPS4002
DECPENT
DPSX010
DPSX06
BICOID
Motif
CA
CA
TG
TG
CAG
12
1
1
1
15
4
2
1
1
1
1
2
1
1
8
5
1
1
1
15
1
1
3
4
4
6
6
6
4
4
4
4
4
4
4
4
6
6
6
6
6
6
6
6
6 + 13
5+7
(4–5)+(0–3)+(1–2)+(1–2)+3
(0–4)+3 + 2 + 2 + 3
5+3+2+2+3
4+1
4+1
4+1
4+1
4+1
(1 + 2)+1
4+1
(8–15)+1
3 + 2 + 2 + 2+(3–5)
n.a.
n.a.
n.a.
3+(1–2)+2+(2–7)+(0–5)
n.a.
n.a.
4+5+2+3+3
n.a.
n.a.
+
+
)
)
n.a.
n.a.
n.a.
)
n.a.
n.a.
+
+
n.a.
n.a.
n.a.
+
n.a.
n.a.
)
n.a.
n.a.
+
+
)
)
n.a.
n.a.
n.a.
)
n.a.
n.a.
+
)
n.a.
n.a.
n.a.
+
n.a.
n.a.
)
Number of different alleles available from databases
D. pseudoobscura
10
3
D. persimilis
4
2
D. miranda
1
1
D. affinis
1
D. obscura
D. ambigua
D. tristis
D. bifasciata
D. subobscura
D. madeirensis
D. guanche
D. helvetica
Microsatellite type1
D. pseudoobscura
D. persimilis
D. miranda
D. affinis
D. obscura
D. ambigua
D. tristis
D. bifasciata
D. subobscura
D. madeirensis
D. guanche
D. helvetica
Number of repeats
D. pseudoobscura
D. persimilis
D. miranda
D. affinis
D. obscura
D. ambigua
D. tristis
D. bifasciata
D. subobscura
D. madeirensis
D. guanche
D. helvetica
1, 2
1, 2
1
11–17, 4 + 8
8–10, 6 + 8
9
Length variation of microsatellite
D. pseudoobscura
+
D. persimilis
+
D. miranda
n.a.
D. affinis
D. obscura
D. ambigua
D. tristis
D. bifasciata
D. subobscura
D. madeirensis
D. guanche
D. helvetica
Length variation of flanking regions
D. pseudoobscura
)
D. persimilis
)
D. miranda
n.a.
D. affinis
D. obscura
D. ambigua
D. tristis
D. bifasciata
D. subobscura
D. madeirensis
D. guanche
D. helvetica
1
1
1
1
5–9
7, 8
5
2
+
+
n.a.
n.a.
+
)
n.a.
n.a.
1, 2
1
7–19, 8 + 4
5
+
n.a.
)
n.a.
Allelic variation of Drosophila microsatellites
219
Table 2. (Continued)
Locus
DPS4002
Sequence variation in flanking regions
D. pseudoobscura
+
D. persimilis
)
D. miranda
n.a.
D. affinis
D. obscura
D. ambigua
D. tristis
D. bifasciata
D. subobscura
D. madeirensis
D. guanche
D. helvetica
Number of alleles detectable with fragment analysis
D. pseudoobscura
7
D. persimilis
4
D. miranda
1
D. affinis
D. obscura
D. ambigua
D. tristis
D. bifasciata
D. subobscura
D. madeirensis
D. guanche
D. helvetica
DECPENT
DPSX010
DPSX06
BICOID
)
)
n.a.
n.a.
+
n.a.
n.a.
n.a.
+
+
+
)
n.a.
n.a.
n.a.
+
n.a.
n.a.
+
+
n.a.
n.a.
n.a.
+
n.a.
n.a.
+
1
1
3
1
1
1
1
1
1
1
1
1
6
3
1
1
1
4
1
1
1
3
2
1
1
10
1
1
According to the definitions given in the introduction.
n.a., not applicable.
variation in sequence and/or length of the flanking regions.
In 16 of 20 possible intraspecific sequence comparisons in the
D. melanogaster group species, the allelic variation of microsatellites is caused by varying numbers of the repeated motifs
whereas length and sequence variation in the flanking regions
occur six and five times, respectively (Table 1). There is a
similar pattern for the microsatellite loci in of the D. obscura
group species. Of the 15 possible intraspecific comparisons,
variable numbers of the microsatellite motif was observed 10
times, and length and sequence variation of the flanking region
six and 11 times, respectively (Table 2). Thus, in many
instances, alleles are defined by mutations affecting the
flanking region rather than the tandemly repeated microsatellite motif.
In the compiled data set, estimates of the number of
alleles by sequence analysis and fragment length analysis are
fairly consistent for most loci, i.e. most alleles can be
detected by both methods. However, this is most likely the
result of the low number of sequences (alleles) available for
the majority of species and loci. In those instances with a
higher number of different sequences available (more than
five alleles), i.e. D. melanogaster (DME 2910), D. pseudoobscura (DPS4002, DPSX010, BICOID), D. obscura (BICOID), D. subobscura (BICOID) and D. helvetica
(DPSX06), the numbers of alleles detectable by sequence
and fragment length analyses, respectively, can differ substantially (Fig. 1). There are, for example, 15 known alleles
for the locus BICOID in D. subobscura but only four length
variants can be distinguished. In D. pseudoobscura, only
three of 15 alleles can be distinguished by fragment length
analysis. Thus, many alleles remain undetectable for fragment length analysis methods.
Discussion
The enormous variability that may be observed at microsatellite loci (Tautz and Renz 1984; Litt and Luty 1989; Tautz
1993) make them suitable genetic markers for the characterization of population structures, linkage studies in human
genetics, animal and plant breeding as well as the identification
of individuals and family analyses. In many studies of allelic
variation of microsatellites, alleles are simply characterized by
their length, and fragment length is assumed to correlate
closely with the number of repeats. The stepwise mutation
model (Otha and Kimura 1973) and its modifications (e.g. Orti
et al. 1997; Zhivotovsky et al. 1997; Kruglyak et al. 1998;
Sibly et al. 2001) are considered to explain better the evolutionary changes of microsatellite structures than classical finite
mutation models (see, e.g. Hartl and Clark 1997). Basic
stepwise mutation models assume that an allele has the same
probability to mutate to a longer or shorter state, whereas
modified stepwise mutation models limit the number of repeats
(e.g. Falush and Iwasa 1999) and assume length-dependent
mutation rates. It has also been proposed that interruptions of
the tandemly repeated motif through point mutations increase
the mutational stability of a microsatellite region (Kruglyak
et al. 1998), i.e. slippage processes become more unlikely.
The genesis of the repetitive structure is of particular interest
for an understanding of the evolutionary dynamics of microsatellite loci. It has been suggested that a minimum number
of repeats is necessary before slippage can operate efficiently
(>4 repeats: Lai and Sun 2003; >5 repeats: Sibly et al. 2001;
>8 repeats: Rose and Falush 1998). The inter- and intraspecific comparison of the microsatellite locus DPSX006 in species
of the D. obscura group supports this threshold hypothesis.
220
Bachmann, Bareiß and Tomiuk
DPSX06
DME2910
25
Alleles
Length variants
20
15
10
5
0
D. melanogaster
12
D. helvetica
DPS4002
8
6
4
ra
s
ob
o
d
eu
s
D. subobscura
10
s
er
p
D.
ira
D.
m
D.
a
ur
ur
nd
m
si
a
a
a
ili
cu
p
D.
D. simulans
BICOID
16
14
12
10
8
6
4
2
0
9
8
7
6
5
4
3
2
1
0
c
bs
c
bs
bo
o
D
u
.s
tic
e
lv
D.
he
2
0
D. pseudoobscura
D. persimilis
Fig. 1. Number of alleles as determined by sequencing (alleles) versus number of alleles as defined by fragment length analysis (length variants) at
the microsatellite loci DME2910, DPSX06, BICOID and DPS4002. Only Drosophila species with two or more sequenced alleles are included
DPSX006, an interrupted compound microsatellites consisting
of at least two stretches of tandemly repeated TG motifs,
shows intraspecifically high variability (8–15 repeats) of one
repetitive stretch in D. helvetica whereas there is no variation
of this stretch with respect to repeat number in the other
European D. obscura group species studied. These data
support the two-phase mutation model of di Rienzo et al.
(1994). The model assumes that a protomicrosatellite has to
evolve first through point mutations that randomly increase
the number of tandemly repeated sequence motifs before a
multiple-step process can change the length of the repeated
array by several units. Such enlarged repetitive fragments have
an increased probability of being disturbed by point mutations. As a consequence, slippage rates might be reduced
(Schug et al. 1998). However, slippage can also remove point
mutations and, thus, create again a perfect repetitive pattern
(Harr et al. 2000). Such a process may explain the variation
observed at the microsatellite BICOID in D. subobscura. In
this species, the last two repeated CAG stretches are homogenized in three of 15 alleles.
In recent years, there has been substantial effort in order to
develop statistical methods for the analysis of population
divergence (Goldstein et al. 1995a,b; Slatkin 1995; Nauta and
Weissing 1996; Pritchard and Feldman 1996; Feldman et al.
1997) and genetic heterogeneity of individuals and populations
(Coulson et al. 1998) based on microsatellite data. It is believed
that the evolution of microsatellite variation is complex and
cannot be explained by simple stepwise mutation models
(Colson and Goldstein 1999, for review see Li et al. 2002).
Various mutational events affect microsatellite structures and
the mutation rate of microsatellites is expected to correlate
positively with the number of repeats. In addition, a mutation
bias towards increased numbers of repeats has been observed
(e.g. Harr and Schlötterer 2000; Vigouroux et al. 2002). This
likelihood for an ascertainment bias has been challenged.
Primmer and Ellegren (1998), for example, did not find any
indication for a mutational length bias. Thus, it is difficult or
even impossible to develop a realistic model for the evolutionary dynamics of microsatellite structures. It is therefore not
surprising that the results of several experiments contradict
conclusions drawn on the basis of basic stepwise mutation
models (Angers and Bernatchez 1997; Orti et al. 1997; Colson
and Goldstein 1999). More recent studies (e.g. Tsitrone et al.
2001) showed theoretically that the classical degree of heterozygosity H might be a more reliable measure for the association between heterozygosity and fitness of individuals or
populations than the diversity measure d2 (Coulson et al. 1998)
that is based on discrete changes of repeat numbers. The
substantial variation in the flanking regions of the microsatellite loci DME2910 in D. melanogaster and BICOID in
D. pseudoobscura and D. obscura supports this point of view.
Apart from our currently limited understanding of the
evolutionary dynamics of microsatellites, technical obstacles
may affect conclusions drawn from the analyses of microsatellite variation. Primers used for the amplification of microsatellite loci do not exclusively amplify the tandemly repeated
motifs but to various extent the flanking regions as well. The
subsequent fragment analyses, which is the most frequently
applied technique for the assessment of microsatellite variation,
cannot discriminate mutations affecting the repeated region
and mutations affecting the flanking regions, and base substitutions cannot be detected at all. Thus, allelic diversity of loci
may be substantially underestimated. However, the extent of
such underestimation is difficult to assess, because sequence
data are limited. As can be seen in our compiled list (Tables 1
and 2), there are rarely more than two microsatellite sequences
Allelic variation of Drosophila microsatellites
per species available. We estimated the ratio of alleles and
alleles detectable by fragment analyses for the most comprehensive data sets of the four loci DME2910, BICOID, DPSX06
and DPS4002 in those species with at least two alleles
sequenced (Fig. 1). It turned out that the majority of
DME2910, DPSX06 and DPS4002 alleles can be detected by
fragment analyses. However, in the instance of BICOID, a
substantial fraction of microsatellite variation (73.3–80%)
would remain undetected. Although the data set does not
allow for an extensive analysis, the discrepancy of the numbers
of alleles and length fragments may be related to the complex
structure of the microsatellite and the relatively low number of
repeated motifs. The loci DME2910, DPSX06 and DPS4002
with better congruence of both estimates have a more simple
structure (i.e. perfect or interrupted microsatellites) and higher
numbers of repeated motifs. In these instances, mutation
through slippage is most important. In instances of interrupted
complex microsatellites such as BICOID, slippage contributes
much less to the generation of allelic variation and estimates
obtained by fragment length analyses will not meet any of the
current models on the mode of evolution of microsatellites.
Acknowledgements
We thank D. Sperlich for collecting D. subobscura, D. obscura, and
D. helvetica. We thank H. Esmer for his valuable technical assistance in
the laboratory and W. D. Braun for assistance in the database
searches. This work was supported by a grant from the fortüneprogramm of the Universitätsklinikum Tübingen (project no. 1189-00), PB and JT were supported by a travel grant of the German
Academic Exchange Service DAAD 13/PPP-N1, and LB was supported by a grant from the Research Council of Norway (National Centre
for Biosystematics, 146515/420).
Zusammenfassung
Allelische Variabilität, Fragmentlängen-Analysen und populationsgenetische Modelle: Eine Fallstudie an Mikrosatelliten von Drosophila
Die allelische Variabilität von 16 Mikrosatelliten-Loci von Arten der
Drosophila melanogaster und D. obscura Gruppe wurde auf Sequenzebene analysiert. Durch den inner- und zwischenartlichen Sequenzvergleich konnten Mutationen in den flankierenden Bereichen der
Mikrosatelliten von Mutationen in den repetitiven Bereichen
unterschieden werden. Die Ergebnisse erlauben Rückschlüsse auf
Mutationsmechanismen, die die Variabilität von Mikrosatelliten
bestimmen. Die Hypothesen, dass repetitive Mikrosatellitenbereiche
eine gewisse Mindestanzahl an Repeats benötigen, um ausgepräge
Längenvariation durch Slippage zu zeigen, und dass die Mutationsrate bei längeren Mikrosatelliten höher ist als bei kurzen, werden
durch die zwischenartlichen Sequenzergleiche gestützt. Neben der
Längen- und Sequenzvariation der repetitiven Mikrosatellitenbereiche
findet sich vor allem bei dem komplexen unterbrochenen Mikrosatellitenlocus BICOID in den Arten der D. obscura Gruppe
ausgeprägte Variabilität in den flankierenden Regionen. Die allelische
Variabilität an diesem Locus lässt sich nicht allein durch Slippage
erklären. Die Bestimmung der Mikrosatellitenvariation durch Fragmentlängenanalyse kann an solchen Loci nur einen geringen Anteil
der vorhandenen Variation erfassen und Schlussfolgerungen, die auf
einem stepwise mutation model basieren, haben eine nur eingeschränkte Gültigkeit.
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Authors’ addresses: Dr Lutz Bachmann (for correspondence), Section
for Zoology, Natural History Museums and Botanical Garden,
University of Oslo, PO Box 1172 Blindern, N-0318 Oslo, Norway.
E-mail: bachmann@nhm.uio.no; Petra Bareiß and Jürgen Tomiuk,
Division of General Human Genetics, Institute of Anthropology and
Human Genetics, University of Tübingen, Wilhelmstrasse 27, D-72074
Tübingen, Germany