Journal of Heredity Advance Access originally published online on August 28, 2007
Journal of Heredity 2007 98(6):620-628; doi:10.1093/jhered/esm068
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High Incidence of Nonslippage Mechanisms Generating Variability and Complexity in Eurasian Badger Microsatellites
From the Genètica de la Conservació, Institut de Recerca i Tecnologia Agroalimentàries, Carretera de Cabrils s/n, Cabrils (Barcelona), Spain (López-Giráldez, Marmi, and Domingo-Roura); the Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Dr Aiguader 80, 08003 Barcelona, Spain (López-Giráldez and Domingo-Roura); and the Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain (Marmi)
Address correspondence to Dr F. López-Giráldez at the address above, or e-mail: francesc.lopez{at}gmail.com.
The use of microsatellites in population genetics is hindered by a lack of understanding of the pattern and origin of mutations, the need to develop more specific and better computational models, and a paucity of information about specific taxa and loci. We analyzed between 4 and 10 allele sequences from 10 different microsatellites in Eurasian badgers in order to determine the compliance of the sequences with stepwise mutation models and the origin of that variability which cannot be detected through standard genotyping procedures. All microsatellite loci exhibited imperfections and/or substitutions and indels in the flanking region, as well as additions or deletions of repeat units. Our data set of sequences showed a higher number of imperfect repeats than other published badger and carnivore sequences. This could be attributed to the process of loci isolation because when genetic variability is low, researchers may be more likely to use imperfect loci if these are variable in the population being studied. Locus Mel15 had 2 repetitive arrays: one was part of a polypyrimidine region of a carnivoran short interspersed nuclear element (CAN-SINE) and the other was located in an A-rich region typical of these insertions. In spite of this complexity, heterozygosity was correlated with the maximum number of repeats. Thus, although new theoretical models are being evolved to cover complex patterns of microsatellite mutation, sequencing electromorphs is needed to identify microsatellites or portions of them whose evolution can be modeled under simple models.
Microsatellites are abundant and widespread repetitive sequences in animal genomes (Kashi et al. 1990). Their high polymorphism and ease of use have made them the marker of choice for individual identification and paternity testing. Their variability and evolutionary history also provide information about relationships between both populations and species. Therefore, it is tempting to use them in population genetics and phylogenetic analyses. However, patterns of mutation in microsatellites are often poorly understood, and adequate analytical tools are rarely available (reviewed in Jarne and Lagoda 1996; Goldstein and Pollock 1997; Schlötterer 2000; Ellegren 2004).
The high mutation rates of microsatellites (10–2–10–5 events per locus per generation) are mainly attributed to variations in the number of copies of the repeated motif, resulting from DNA (replication) slippage (Levinson and Gutman 1987; Schlötterer and Tautz 1992). Unequal crossing over and recombination might also be involved, but their roles in the generation of mutation are less important (Eichler et al. 1995; Gordenin et al. 1997). A combination of these mechanisms together with base substitutions and insertions and deletions (indels) results in 3 main sources of variability: the addition or deletion of repeat units, mutations interrupting the repeat, and substitutions and indels occurring in the microsatellite flanking regions (Makova et al. 2000).
The assumption that microsatellites evolve under the stepwise mutational model (SMM, Kimura and Ohta 1978) has been widely used because mutational mechanisms of slippage during replication are often consistent with this model (Schlötterer and Tautz 1992; Weber and Wong 1993), and the model is also attractive from a computational perspective. Microsatellite applications mainly involve comparing the mobility of different alleles through electrophoresis of polymerase chain reaction (PCR) products. Nevertheless, size homoplasy, in which alleles have the same length but are not identical by descent, has been detected both within and between species. It is not therefore possible to determine allelic coalescence simply from information on allele size (Garza and Freimer 1996; Grimaldi and Crouau-Roy 1997). Furthermore, the origin of simple mutational events cannot be assumed, and the role of point mutations or simple slippage in the origin of microsatellites cannot always be discerned (Gordon 1997).
The Mustelidae is a diverse and widespread carnivore family of increasing relevance in evolution and conservation genetics. Low levels of mitochondrial and nuclear variability, reduced repeat numbers, and a high number of imperfect repeats have been described in the Eurasian badger, Meles meles L. (Burke et al. 1996; Domingo-Roura et al. 2003). In this study, we sequenced 4–10 alleles from each of 10 Eurasian badger microsatellites in badgers and other mustèlids for a total of 65 sequences. It has been established, based on the combination of morphological and molecular data, that these species shared a common ancestor around 20.8 million years ago (Bininda-Emonds et al. 1999). The sequences were obtained in order to detect microsatellites that follow SMM and to determine and inquire into the origin of variability that cannot be detected through standard genotyping procedures. Microsatellite variability and structure might be related to a wide range of processes, such as: 1) genome-wide dynamics, including demographic history; 2) the laboratory methodology of each study, including library construction and the effort devoted to cloning and sequencing; and 3) the use of one or another definition of microsatellite categories. We standardized our microsatellite definition and explored whether the high incidence of imperfections and compound microsatellites were exclusive to our data set or to Eurasian badgers by comparing our data with other Eurasian badger and carnivore sequences available from GenBank. We then assigned 3 possible sources of variability: the addition or deletion of repeat units (presumably following SMM); mutations interrupting the repeat; and substitutions and indels in the flanking regions of each of our microsatellites, in order to determine compliance with SMM. Finally, we correlated heterozygosity with the maximum number of perfect repeats in order to determine whether, in spite of this complexity, a portion of the microsatellite that can be modeled under SMM could be used for phylogenetic and population genetic inferences.
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The present study was based on 7 wild Eurasian badgers (M. meles L.) collected throughout their geographical distribution in Europe (Austria, Greece [Crete Island], Germany, Poland, Spain, Sweden, and the United Kingdom); 2 further Eurasian badgers from East Asia (one each from Japan and Mongolia); individuals from other mustelid species (a European river otter [Lutra lutra L.], a pine marten [Martes martes L.], a weasel [Mustela nivalis L.], an American mink [Mustela vison Schreber]); and a spotted skunk (Spilogale putorius L.). Tissue samples were frozen or kept in ethanol and were obtained from museums and road kills.
Total DNA was extracted from either blood or muscular tissue according to standard phenol–chloroform protocols. DNA was amplified using the PCR primers Mel08-Mel16 and Mel18 (see primer sequences in Table 1), which were designed from badger libraries constructed from the DNA of a British badger. Two nonenriched libraries were constructed following the conditions described in Domingo-Roura (2002) and Domingo-Roura et al. (2003). Briefly stated, genomic DNA extracted from muscle tissue was digested with MboI or AluI, and 100- to 500-bp fragments were recovered. These fragments were ligated into pUC18 vector and then transformed into XL-1 Blue cells (Stratagene, La Jolla, CA). The resulting colonies were plated into nylon membranes, which were hybridized with (GC)10, (CA)15, (AT)10, (GAAA)10, or (GATA)10 probes. An enriched DNA library was also constructed by Genetic Identification Services, as described in Kays et al. (2000). More detailed information on isolation procedures for each marker can be found in Domingo-Roura (2000).
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Amplifications were performed with fluorescently labeled forward primers in a 15-µl reaction volume. Products were combined with size standard (ABI500 TAMRA; Applied Biosystems, Foster City, CA) and loaded into a 6% denaturing acrylamide gel in an ABI377 DNA sequencer. GeneScan v3.1 (Applied Biosystems) was used to determine fragment sizes.
Nonfluorescent versions of the same primers and the same protocol were used to sequence between 3 and 9 electromorphs per marker (Table 1). Twenty-five microliters of PCR products were purified using Geneclean (BIO101, La Jolla, CA). Neither of the badgers from Mongolia and Japan was homozygous for markers Mel12, Mel15, and Mel16. In these cases to include geographically diverse samples, we sequenced alleles from heterozygous individuals after cloning. We also cloned both the otter and the German badger for marker Mel14 because they were heterozygotes and their electromorph sizes were not congruent with the addition or deletion of whole repeat units. Overall, 26 electromorphs were sequenced from homozygous badgers and 10 from heterozygous specimens, including the clones sequenced in the original library. The amplification product from these markers was cloned and transformed into Escherichia coli using the pMosBlue Blunt Ended Cloning Kit (Amersham Pharmacia Biotech, Piscataway, NJ). Plasmid DNA isolation was performed using Wizard Plus SV Minipreps DNA Purification System (Promega, Madison, WI). Transgenic plasmids and simple PCR products were sequenced in both directions using Dye Terminator Cycle Sequencing Kit (Applied Biosystems) and an ABI377 DNA sequencer following the manufacturer's instructions. Resultant sequences were deposited in GenBank under accession numbers AJ309052–AJ309057, AJ309059, AJ309847–AJ309849, AJ489574, AJ489566, AJ489568, AJ489578, AJ489579, and AJ543956–AJ543992.
Alleles, including sequences from the original badger libraries, were visually aligned. Because automated scoring can produce slightly inaccurate estimates of allele size, fragment lengths obtained with Genescan v3.1 were adjusted with sequences. We defined a microsatellite as a sequence containing at least 6 consecutive repeats in at least one of the species sequenced. Microsatellite length, limits, and classification as perfect, imperfect, or compound were determined according to Weber (1990). Weber considered perfect repeat sequences as repeats without interruptions and without adjacent repeats of another sequence; imperfect repeat sequences as 2 or more runs of uninterrupted repeats separated by no more than 3 consecutive nonrepeat bases and with terminal runs of at least 3 full repeats in length; and compound repeat sequences as runs of repeats separated by no more than 3 consecutive nonrepeat bases from a run of 
5 uninterrupted repeats of other repeat motif. Although Weber's work was based entirely on dinucleotide repeats, our study also considered tetranucleotide and mononucleotide repeat units (Table 1). The remaining sequence between the primers was considered the flanking region.
By sequencing different electromorphs for a given marker, we were able to determine which mutational records were present in the microsatellites: the addition and deletion of repeat units (presumably a result of slippage), the presence of interruptions in the repeat array, and changes in the flanking region including substitutions and indels (Table 2).
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Fisher's exact tests were conducted to compare the number of single and compound repeats and the number of perfect and imperfect repeats obtained in this study with those of sequences available from GenBank of other Eurasian badgers (Carpenter et al. 2003) and of other carnivore species (M. vison, O'Connell et al. 1996; Gulo gulo L., Davis and Strobeck 1998; Walker et al. 2001; Canis familiaris L., Spriggs et al. 2003; Ursus arctos L., Taberlet et al. 1997; Suricata suricatta Schreber, Griffin et al. 2001; Panthera tigris L., Williamson et al. 2002; Crocuta crocuta Erxleben, Libants et al. 2000; Wilhelm et al. 2003). These microsatellites were isolated in a similar way to in our laboratory from partial genomic libraries (selected for small insert size) of species of interest and screening several thousands of clones through colony hybridization with repeat containing probes, most of which use (CA)n or (GT)n.
Finally, we attempted to assess—once alleles had been sequenced—the relationship between variability and microsatellite structure in order to determine whether, in spite of complexity, the microsatellite (or a portion of this) could be modeled under SMM. For this, we performed a Spearman's nonparametric coefficient for rank correlation of the number of alleles in British badgers from Wytham Woods, Oxfordshire (Domingo-Roura et al. 2003), and in our worldwide badger sample against microsatellite length including imperfections and the maximum number of consecutive perfect repeats. All statistical analyses were performed with SPSS v11.0.1 (SPSS Inc., Chicago, IL).
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Information Extracted from Electromorphs
Amplification success and the electromorphs obtained and sequenced for the different markers and species are indicated in Table 1. Cross-species amplification was possible for 8 of the 10 microsatellites, indicating the conservation of flanking regions more than the approximately 20.8 million years that separate the badger from outgroup species (Bininda-Emonds et al. 1999; Table 1). The region-flanking locus Mel08 was able to amplify S. putorius and species belonging to 5 different carnivore families (Domingo-Roura et al. 2005). This indicates the conservation of priming sites more than approximately 35.5 million years. Amplification failed for the badgers from Crete and Austria using Mel12 and Mel18, respectively. Because both markers could amplify across species, this probably indicated the presence of null alleles (Callen et al. 1993).
Sequencing to Explore Sources of Variation
One particular characteristic of our data set was a high incidence of multiple repetitive arrays in a single clone, supporting a previously observed tendency for microsatellites to cluster (Bachtrog et al. 1999). Mel09, Mel14, and Mel18 each contained 2 separate repetitive arrays—one of which was a mononucleotide—between their priming sites (Figure 1), whereas Mel08, Mel09, Mel10, Mel15, and Mel18 each contained 2 adjacent arrays of different repetitive motif; in other words, they were compound microsatellites. All 6 microsatellite clones showed size variability in more than one repeat array across species, whereas 4 of them (Mel09, Mel10, Mel14, and Mel15) also showed this variability within Eurasian badgers. The presence of more than one repeat array would probably preclude a unique stepwise mutation process, which is an assumption of the SMM. Because Mel08 was not a compound microsatellite in badgers, 4 out of the 14 repeat arrays in this species were compounds. The proportion of compound repeats in badgers was not significantly different from the proportion calculated from other Eurasian badger sequences available from GenBank (17 compound; n = 174, Fisher's exact test, P = 0.055) and from other carnivore species (17 compound; n = 151, Fisher's exact test, P = 0.083). The proportion of compound repeats was also not significantly different between other Eurasian badger and carnivore sequences (Fisher's exact test, P = 0.378). Note that the number of compound microsatellites reported in the original carnivore studies was lower than the number we used in these comparisons. This was due to differences between the criteria used to define compound microsatellites in these studies and our criteria, which were based on Weber (1990) and have already been detailed in the methods section. The evolution of compound microsatellites is still poorly understood, but the fact remains that clustering is an indicator that repeat arrays are unlikely to evolve independently.
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When comparing sequences within the badger, all loci except Mel08 and Mel11 showed different perfect repeat copy numbers. In addition to this variability—that was presumably caused by slippage, all of them except Mel14 also showed interruptions in at least one repeat array. It has been suggested that point mutations break up perfect repeats, reducing the mutation rates of microsatellite loci and precluding infinite growth in repeat number (Kruglyak et al. 1998). This is in disagreement with another assumption of the SMM, which states that the number of repeats should vary at a fixed rate and does not consider an upper limit to their growth in copy number. None of the 10 microsatellites analyzed within the badger showed a variable single repeat array without interruptions or indels in the flanking region (Table 2), demonstrating the complexity of our database. In all, 10 repeats were perfect and 8 were imperfect within the badger. The proportion of imperfect repeats was not significantly different from the proportion calculated for other badger sequences (47 imperfect; n = 192, Fisher's exact test, P = 0.064), but it was significantly larger than the proportion obtained for other carnivore species (34 imperfect; n = 169, Fisher's exact test, P = 0.025). The proportion of imperfect repeats was not significantly different between other badger and carnivore sequences (Fisher's exact test, P = 0.216). It is not possible to differentiate between interruptions created by substitutions, those arising as a result of gains or losses of multiple repeat units—one of which is imperfect—and those resulting from slippage involving partial repeat units (Palsbøll et al. 1999; Zhu et al. 2000).
Thus, once microsatellite definition had been standardized, our badger microsatellites showed a high number of imperfect repeats. Because our primers were designed from 4 different genomic libraries in 2 different laboratories, it is unlikely that imperfections and complexities only result from a systematic bias in probing efficiency during library production (Domingo-Roura et al. 2003). Even so, our loci were screened on the British population inhabiting Wytham Woods, Oxfordshire, where variability is known to be low (Domingo-Roura et al. 2003) and where 4 different libraries were needed to achieve a moderate level of variability when trying to identify the individuals of this population. Thus, when variability is low and there is a need to obtain a large number of variable microsatellites, for instance for paternity testing, in addition to microsatellite clones with a large number of perfect repeats, researches may tend to sequence, design primers, and include sequences from imperfect microsatellites in GenBank.
Even when electromorph sizes within badger and between species showed a pattern congruent with the addition or deletion of repeat units, the sequencing of alleles demonstrated the existence of other repeat arrays or indels in the flanking regions that mimicked the addition or deletion of repeat units. Three loci (Mel09, Mel15, and Mel16) had one or more indels in the flanking regions (Table 2) in badgers, which again contradicted the SMM assumptions that only predict changes in size in the repeat array. This could also be a reason for misclassifying allele size relative to the number of repeat units and therefore also a possible form of homoplasy not assumed by SMM. In addition, all markers had either indels and/or base differences in their flanking regions across species, and therefore, electromorph size is clearly inadequate for phylogenetic inference.
A CAN Short Interspersed Element Insertion in the Data set
When exploring the sequences shown in Figure 1, the (complementary) sequence of Mel15 was of particular interest as it contained an almost complete short interspersed element (SINE). As with typical SINEs, the insertion contained internal promoters and terminators of RNA polymerase III, a polypyrimidine region and an A-rich 3'-tail (the T-rich tail in the complementary sequence shown in the Figure 1). This element shared more than 80% sequence identity with other CAN SINE sequences (data not shown), a family of short retroposons frequently repeated in carnivore genomes. One of the 2 repeat arrays present in this locus, the GA-based repeat (CT in the complementary chain), was part of the polypyrimidine region, which is variable both in sequence and length within the CAN SINE family (Vassetzky and Kramerov 2002). Accordingly, we found a large deletion in the badger from Crete and smaller deletions in martens, which both followed this GA-based repeat. The second repeat array in the Mel15 locus had a (CTTT)n motif. Its complementary chain contained a (GAAA)n motif and was located in the A-rich tail of the SINE. We also found a CAN SINE inserted in the flanking region of the Mel08 locus in the American mink: that is useful for differentiating between this species from similar mustelid species (López-Giráldez et al. 2005). A-rich tails in Alu sequences have been shown as important sources for the genesis of primate microsatellites (Arcot et al. 1995; Nadir et al. 1996).
Microsatellite Structure and Variation in the BADGER
The alleles found in a badger population from Wytham Woods, Oxfordshire, UK (Domingo-Roura et al. 2003) and in our sample of 9 badgers from 9 different countries were available as variability data for each of the microsatellites that we studied. Only 5 markers (Mel10, Mel12, Mel14, Mel15, and Mel16) were variable in Wytham Woods, whereas the others were monomorphic. The number of alleles was positively correlated with the maximum number of consecutive perfect repeats (n = 10, rho = 0.751, P = 0.012), but not with microsatellite length, including imperfections (n = 10, rho = 0.208, P = 0.564). The comparison of allele numbers across Eurasia gave a better view of the relationship between structure and variation because the number of alleles and heterozygosity values might differ considerably across populations for a single species. With the exception of monomorphic Mel08, between 4 and 11 electromorphs were found in the Eurasian sample. The number of electromorphs positively correlated with the maximum number of consecutive perfect repeats (n = 10, rho = 0.858, P = 0.001), and also, with a lower correlation coefficient, with microsatellite length, including imperfections (n = 10, rho = 0.640, P = 0.046). Thus, in spite of the complexity of the data set, the number of perfect repeats was still a good predictor of variability, and this parameter can be easily modeled under SMM.
It is becoming progressively more evident that the rate and patterns of microsatellite mutation depend on multiple factors including the sequence and chromosomal position of the loci involved, as well as the genotype, age, and sex of the individual hosting the microsatellite (reviewed in Schlötterer 2000; Ellegren 2004). In addition, molecular mechanisms that affect microsatellites, such as the efficiency of slippage or recombination, are related to stress, environmental, demographic, and life history correlates (Neff and Gross 2001; Li et al. 2002). Theoretical models have been evolved to cover some of these complexities (Nauta and Weissing 1996; Kruglyak et al. 1998; Calabrese et al. 2001; Sainudiin et al. 2004), whereas new models, following distributions such as power-law and Bernouilli, have also been proposed (Li et al. 2002).
Mutational models and statistics applicable in population genetics need to be properly tested, but parameterizing complex models promise to be a difficult and long-term task. Our data indicate that many microsatellite mutation patterns are more complex than represented by generalized stepwise mutation models. None of the 10 microsatellites loci studied here showed, within the badger, a variable single repeat array without interruptions or indels in the flanking region. Moreover, we found complex microsatellites structures (Mel15) associated with the presence of a SINE that is been shown an important source of complex microsatellites and genotyping problems in carnivores (López-Giráldez et al. 2006). All these results highlight that care should be taken when inferring population or phylogenetic relationships from microsatellite size data alone. However, our analyses also indicate that, in spite of their complexity, a portion of the microsatellite (the number of perfect repeats) can more closely match the assumptions of stepwise models. Thus, evaluation of sequence structure, through moderate sequencing efforts, is necessary to identify microsatellites or portion of them that can be used as markers for phylogenetic and population genetic inferences.
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Funding |
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European Commission under contract INPRIMAT (QLRI-CT-2002-01325); the Comissionat per a Universitats i Recerca, Generalitat de Catalunya (ref. 2000SGR00093); the Departament d'Universitats, Recerca i Societat de la Informació, Generalitat de Catalunya (refs. 2001FI00625 and 2000FI00698, respectively) to F. L-G. and J.M.
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Acknowledgments |
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We thank A. Arrizabalaga (Museu de Granollers), J. Brabec (University of Innsbruck), A. Bradshaw (University of Cardiff), P. Fakler (Universität Heidelberg), A. Laurie (Eastern Steppes Biodiversity Project), M. Miralles (Rectoria Vella), M. Nadolska (Agricultural University of Wroc
aw), M. Saeki (Wildlife Conservation Research Unit, University of Oxford), V. Sidorovich (National Academy of Sciences of Belarus), N. Yamaguchi (Wildlife Conservation Research Unit, University of Oxford), and R. Woodroffe (Wildlife Conservation Research Unit, University of Oxford) for providing samples used in the study. D. Macdonald (Wildlife Conservation Research Unit, University of Oxford) provided logistical support. We thank O. Andrés, A. Antonell, G. Fernández, L.F. Magano, A. Pérez-Lezaun, and M. Vallès for their help in the laboratory and S. Baker and 2 anonymous reviewers for their useful comments on the manuscript. |
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Corresponding Editor: Oliver Ryder
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Arcot SS, Wang Z, Weber JL, Deininger PL, Batzer MA. Alu repeats: a source for the genesis of primate microsatellites. Genomics (1995) 29:136–144.[CrossRef][ISI][Medline]
Bachtrog D, Weiss S, Zangerl B, Brem G, Schlötterer C. Distribution of dinucleotide microsatellites in the Drosophila melanogaster genome. Mol Biol Evol. (1999) 16:602–610.[Abstract]
Bininda-Emonds ORP, Gittleman JL, Purvis A. Building large trees by combining phylogenetic information: a complete phylogeny of the extant Carnivora (Mammalia). Biol Rev. (1999) 74:143–175.
Burke T, Hanotte O, Van Pijlen I. Minisatellite analysis in conservation genetics. In: Molecular genetic approaches in conservation—Smith TB, Wayne RK, eds. (1996) New York: Oxford University Press. 251–277.
Calabrese PP, Durrett RT, Aquadro CF. Dynamics of microsatellite divergence under stepwise mutation and proportional slippage/point mutation models. Genetics (2001) 159:839–852.
Callen DF, Thompson AD, Shen Y, Phillips HA, Richards RI, Mulley JC, Sutherland GR. Incidence and origin of "null" alleles in the (AC)n microsatellite marker. Am J Hum Genet. (1993) 52:922–927.[ISI][Medline]
Carpenter PJ, Dawson DA, Greig C, Parham A, Cheeseman CL, Burke T. Isolation of 39 polymorphic microsatellite loci and the development of a fluorescent marker set for the Eurasian badger (Meles meles) (Carnivora: Mustelidae). Mol Ecol Notes (2003) 3:610–615.[CrossRef][ISI]
Davis CS, Strobeck C. Isolation, variability, and cross-species amplification of polymorpic microsatellite loci in the family Mustelidae. Mol Ecol (1998) 7:1776–1178.[Medline]
Domingo-Roura X. Biochemical and molecular ecology of Eurasian badgers, Meles meles, and Japanese macaques, Macaca fuscata: nutritional and reproductive requirements [PhD thesis]. (2000) Oxford: University of Oxford.
Domingo-Roura X. Genetic distinction of marten species by the fixation of a microsatellite region. J Mammal (2002) 83:907–912.[CrossRef][ISI]
Domingo-Roura X, López-Giráldez F, Saeki M, Marmi J. Phylogenetic inference and comparative evolution of a complex microsatellite and its flanking regions in carnivores. Genet Res. (2005) 85:223–233.[CrossRef][ISI][Medline]
Domingo-Roura X, Macdonald DW, Roy MS, Marmi J, Terradas J, Woodroffe RJ, Burke T, Wayne RK. Confirmation of low genetic diversity and multiple breeding females in a social group of Eurasian badgers from microsatellite and field data. Mol Ecol (2003) 12:533–539.[CrossRef][Medline]
Eichler EE, Kunst CB, Lugenbeel KA, Ryder OA, Davison D, Warren ST, Nelson DL. Evolution of the cryptic FMR1 CGG repeat. Nat Genet. (1995) 11:301–308.[CrossRef][ISI][Medline]
Ellegren H. Microsatellites: simple sequences with complex evolution. Nat Rev Genet. (2004) 5:435–445.[CrossRef][ISI][Medline]
Garza JC, Freimer NB. Homoplasy for size at microsatellite loci in humans and chimpanzees. Genome Res. (1996) 6:211–217.
Goldstein DB, Pollock DD. Launching microsatellites: a review of mutation processes and methods of phylogenetic inference. J Hered (1997) 88:335–342.
Gordenin DA, Kunkel TA, Resnick MA. Repeat expansion–all in a flap? Nat Genet. (1997) 16:116–118.[CrossRef][ISI][Medline]
Gordon AJ. Microsatellite birth register. J Mol Evol. (1997) 45:337–338.[ISI][Medline]
Griffin AS, Nürnberger B, Pemberton JM. A panel of microsatellites developed for meerkats (Suricata suricatta) by cross-species amplification and species-specific cloning. Mol Ecol Notes (2001) 1:83–85.[CrossRef][ISI]
Grimaldi MC, Crouau-Roy B. Microsatellite allelic homoplasy due to variable flanking sequences. J Mol Evol. (1997) 44:336–340.[CrossRef][ISI][Medline]
Jarne P, Lagoda PJL. Microsatellites, from molecules to populations and back. Trends Ecol Evol. (1996) 11:424–429.[CrossRef]
Kashi Y, Tikochinsky Y, Genislav E, Iraqi F, Nave A, Beckmann JS, Gruenbaum Y, Soller M. Large restriction fragments containing poly-GT are highly polymorphic in a variety of vertebrates. Nucleic Acids Res. (1990) 21:1111–1115.[CrossRef]
Kays RW, Gittleman JL, Wayne RK. Microsatellite analysis of kinkajou social organization. Mol Ecol (2000) 9:734–751.
Kimura M, Ohta T. Stepwise mutation model and distribution of allelic frequencies in a finite population. Proc Natl Acad Sci USA (1978) 75:2868–2872.
Kruglyak S, Durres RT, Schug MD, Aquadro CF. Equilibrium distributions of microsatellite repeat length resulting from balance between slippage events and point mutations. Proc Natl Acad Sci USA (1998) 95:10774–10778.
Levinson G, Gutman GA. Slipped-strand mispairing: a major mechanism for DNA sequence evolution. Mol Biol Evol. (1987) 4:203–221.[Abstract]
Li Y-C, Korol AB, Fahima T, Beiles A, Nevo E. Microsatellites: genomic distribution, putative functions and mutational mechanisms: a review. Mol Ecol (2002) 11:2453–2465.[CrossRef][Medline]
Libants S, Olle E, Oswald K, Scribner KT. Microsatellite loci in the spotted hyena Crocuta crocuta. Mol Ecol (2000) 9:1443–1445.[CrossRef][Medline]
López-Giráldez F, Andrés O, Domingo-Roura X, Bosch M. Analyses of carnivore microsatellites and their intimate association with tRNA-derived SINEs. BMC Genomics. (2006) 7:269.[CrossRef][Medline]
López-Giráldez F, Gómez-Moliner BJ, Marmi J, Domingo-Roura X. Genetic distinction of American and European mink (Mustela vison and M. lutreola) and European polecat (M. putorius) hair samples by detection of a species-specific SINE and a RFLP assay. J Zool (Lond) (2005) 265:1–6.[CrossRef]
Makova KD, Nekrutenko A, Baker RJ. Evolution of microsatellite alleles in four species of mice (genus Apodemus). J Mol Evol. (2000) 51:166–172.[ISI][Medline]
Nadir E, Margalit H, Gallily T, Ben-Sasson SA. Microsatellite spreading in the human genome: evolutionary mechanisms and structural implications. Proc Natl Acad Sci USA (1996) 93:6470–6475.
Nauta MJ, Weissing FJ. Constraints in allele size at microsatellite loci: implications for genetic differentiation. Genetics (1996) 143:1021–1032.[Abstract]
Neff BD, Gross MR. Microsatellite evolution in vertebrates: inference from AC dinucleotide repeats. Evolution (2001) 55:1717–1733.[CrossRef][ISI][Medline]
O'Connell M, Wright JM, Farid A. Development of PCR primers for nine polymorphic American mink, Mustela vison, microsatellite loci. Mol Ecol (1996) 5:311–312.[CrossRef][Medline]
Palsbøll PJ, Bérubé M, Jørgensen H. Multiple levels of single-strand slippage at cetacean tri- and tetranucleotide repeat microsatellite loci. Genetics (1999) 151:285–296.
Sainudiin R, Durrett RT, Aquadro CF, Nielsen R. Microsatellite mutation models: insights from a comparison of humans and chimpanzees. Genetics (2004) 168:383–395.
Schlötterer C. Evolutionary dynamics of microsatellite DNA. Chromosoma (2000) 109:365–371.[ISI][Medline]
Schlötterer C, Tautz D. Slippage synthesis of simple sequence DNA. Nucleic Acids Res (1992) 20:211–215.
Spriggs HF, Holmes NG, Breen MG, Deloukas PG, Langford CF, Ross MT, Carter NP, Davis ME, Knights CE, Smith AE, et al. Construction and integration of radiation-hybrid and cytogenetic maps of dog Chromosome X. Mamm Genome (2003) 14:214–221.[CrossRef][ISI][Medline]
Taberlet P, Camarra JJ, Griffin S, Uhres E, Hanotte O, Waits LP, Dubois-Paganon C, Burke T, Bouvet J. Noninvasive genetic tracking of the endangered Pyrenean brown bear population. Mol Ecol (1997) 6:869–876.[CrossRef][Medline]
Vassetzky NS, Kramerov DA. CAN—a pan-carnivore SINE family. Mamm Genome (2002) 13:50–57.[CrossRef][ISI][Medline]
Walker CW, Vilà C, Landa A, Lindén M, Ellegren H. Genetic variation and population structure in Scandinavian wolverine (Gulo gulo) populations. Mol Ecol (2001) 10:53–63.[CrossRef][Medline]
Weber JL. Informativeness of human (dC-dA)n·(dG-dT)n polymorphisms. Genomics (1990) 7:524–530.[CrossRef][ISI][Medline]
Weber JL, Wong C. Mutation of human short tandem repeats. Hum Mol Genet (1993) 2:1123–1128.
Wilhelm K, Dawson DA, Gentle LK, Horsfield GF, Schlötterer C, Greig C, East M, Hofer H, Tautz D, Burke T. Characterization of spotted hyena, Crocuta crocuta, microsatellite loci. Mol Ecol Notes (2003) 3:360–362.[CrossRef][ISI]
Williamson JE, Huebinger RM, Sommer JA, Louis EE Jr, Barber RC. Development and cross-species amplification of 18 microsatellite markers in the Sumatran tiger (Panthera tigris sumatrae). Mol Ecol Notes (2002) 2:110–112.[CrossRef][ISI]
Zhu Y, Strassmann JE, Queller DC. Insertions, substitutions, and the origin of microsatellites. Genet Res. (2000) 76:227–236.[CrossRef][ISI][Medline]
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