*Bodega Marine Laboratory
Department of Animal Science, University of CaliforniaDavis
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Microsatellites are thought to mutate predominantly by slippage of DNA polymerase during replication, which generally results in gains or losses of single repeat units, depending on the DNA strand in which the slippage occurs (Levinson and Gutman 1987b
; Schlötterer and Tautz 1992
; Weber and Wong 1993
; Primmer et al. 1996
; Wierdl, Dominska, and Petes 1997
). The mutation mechanism for microsatellites appears consistent with the theoretical stepwise mutation model (SMM; Kimura and Ohta 1978
) in which mutations are additions or subtractions of repeat units in the case of microsatellites. Convergent or recurrent types of mutations, although a fundamental part of SMM, are not consistent with the standard infinite alleles model (IAM, Kimura and Crow 1964
), which assumes that every mutation that occurs within a population creates a unique allele. A slippage mechanism of mutation, which may occur commonly only in microsatellites because of their molecular structure, clearly has implications for inferences based on population phenotypic diversity because alleles can return to previous allele sizes or states, retarding the separation of allele frequency profiles between populations.
If microsatellites evolve in a stepwise fashion, convergence of unrelated alleles to a common size, size homoplasy, should be common at these loci, yet homoplasy has rarely been observed within populations (Estoup et al. 1995
; Garza and Freimer 1996
; Grimaldi and Crouau-Roy 1997
; Culver, Menotti-Raymond, and O'Brien 2001
). Homoplasy should also obscure the actual genetic distance between populations (Goldstein et al. 1995
). This creates a paradox: microsatellites are useful because they are polymorphic, yet their mechanism of mutation obscures population differentiation by increasing homoplasy. Nevertheless, microsatellites do produce information generally concordant with other marker types, which suggests that homoplasy does not obscure differentiation of allelic frequencies. For example, microsatellites reliably discriminate the five major stocks of chinook salmon (Oncorhynchus tschawytscha) in California's Central Valley (Banks et al. 2000
) and corroborate information provided by allozymes (Bartley et al. 1992
; G. Winans and D. Teal, personal communication), mtDNA (Nielsen et al. 1994
), and MHC class-II B (Kim, Parker, and Hedrick 1999
; Hedgecock et al. 2001
).
A substantial proportion of the power to discriminate California's chinook populations comes from the Ots-2 locus, a simple dinucleotide microsatellite [CA]627 with confirmed disomic, Mendelian inheritance (Banks et al. 1999
). Of the 10 microsatellite loci surveyed in that study, the Ots-2 microsatellite exhibits the greatest allele-frequency divergence among chinook salmon populations in the Central Valley of California (Banks et al. 2000
). The Sacramento River winter-run chinook, listed under state and federal laws as endangered (NMFS 1994
), has a high frequency of the 7-repeat allele at the Ots-2 microsatellite, making it genetically more distinct from the other Californian populations. We sought to resolve the paradox of how microsatellites reveal population structure by sequencing nonrepeat regions flanking the microsatellite repeat regions of the Ots-2 locus, thereby placing the changes occurring at a putatively rapidly mutating microsatellite locus in the evolutionary context of its more slowly evolving flanking sequence. Point mutations are of the order of 10-9 to 10-10 events per locus per generation (Li and Graur 1991
, pp. 6973), several orders of magnitude less than the mutation rate estimates for microsatellites, which lie between 10-2 and 10-5 events per locus per generation (Levinson and Gutman 1987a
; Henderson and Petes 1992
; Weber and Wong 1993
). Banks et al. (1999)
estimated the mutation rate for the Ots-2 microsatellite at 10-4 events per locus per generation. The flanking sequence haplotype in which each microsatellite allele is embedded can be used to determine the historical relationship among microsatellite alleles, and specifically for the pure repeat Ots-2 locus, required for constructing genealogies. In previous studies, homoplasy has largely been characterized by differences in the composition of complex repeat arrays (Estoup et al. 1995
; Garza and Freimer 1996
; Grimaldi and Crouau-Roy 1997
; Angers, Estoup, and Jarne 2000
). In this study, if two microsatellite alleles of the same size differ at one or more flanking nucleotides, we assume that these alleles are homoplaseous, having converged by stepwise mutation to a common repeat number along separate flanking sequence lineages.
For multiple chinook populations, the Ots-2 tandem repeat array and 300 bp of associated flanking sequence were isolated for individual alleles. The sequence flanking the microsatellite repeat contains polymorphisms; hence, the sequence information for a chromosomal haplotype contains two loci: the tandem repeat and the flanking sequence with its complement of flanking single nucleotide polymorphisms (SNPs). In this study we compare the observed flanking sequence variation and the distribution of microsatellite repeats at the Ots-2 locus.
![]() |
Materials and Methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Primer Development and PCR
We developed a new primer based on the sequence of the genomic DNA clone from which Ots-2 was originally developed (Banks et al. 1999
). The new primer, 2A(2)-R, 5'-GTC AGG AGT AAC TTT AT-3', replaced the original primer Ots-2-R and was used in combination with the previously described PCR primer, Ots-2-L, 5'-ACA CCT CAC ACT TAG A-3' (Banks et al. 1999
) to amplify a fragment encompassing as much known flanking sequence as possible (GenBank accession #AF107030). The program Oligo 4.0 was used to select the exact primer sequence (Applied Biosystems). The new PCR primer, 2A(2)-R, and the original primer, Ots-2-L, amplified a fragment containing the microsatellite and 300 bp of flanking sequence. The PCR components for this locus were 1.0 mM MgCl2, 0.05 mM dNTPs, 1.0 µM PCR primer, 0.025 U/µl Taq (Promega), and 50 ng template DNA. Temperature and cycling parameters were denaturing at 94°C for 30 s, annealing at 45°C for 15 s, and extension at 72°C for 20 s, repeated for 35 cycles on a tetrad thermocycler (MJ Research). Amplified fragments were separated by electrophoresis on 8% denaturing polyacrylamide gel, and fluorescently end-labeled amplicons were visualized using the FMBIO II imaging system (Hitachi Software Engineering America Ltd.).
Evaluation of Flanking Haplotypes
Two methods were used to isolate haplotypes for sequencing purposes: subcloning and gel isolation. Because homozygous individuals were common, haplotypes were isolated predominantly by subcloning (95%), although some haplotypes were obtained through gel isolation (5%). Cloning of alleles was completed as described subsequently. PCR-amplified fragments were run onto a 2% agarose gel. Bands, visualized using ethidium bromide, were excised from the gel. DNA was recovered from the agarose and purified using QIAQuick purification columns (Qiagen). Purified DNA was cloned using the TOPO TA® cloning kit (Invitrogen). For each subclone, a minimum of six minipreps was performed. Plasmid DNA was isolated using either standard protocols (Sambrook, Fritsch, and Maniatis 1989
, pp. 1.231.28) or the Qiaprep kit (Qiagen). We sequenced cloned DNA using either the fmol® cycle sequencing kit (Promega) and fluorescently end-labeled primers or templates were sent to Davis Sequencing (Davis, CA). Gel isolation of haplotypes was also accomplished for a small number of individuals. PCR-amplified fragments were separated on 8% denaturing polyacrylamide gel and stained with SYBR® Gold nucleic acid stain (Molecular Probes). Stained fragments were visualized using the fluorescent imager. By aligning reference lines drawn on the gel plate with the gel image, individual bands were located in the gel for excision. Isolated bands were placed in 20 µl of ddH20 and incubated overnight at 4°C. Ten microliters of a 1:50 dilution of supernatant was used as template for 100 µl PCR reactions. Reaction products were concentrated using QIAQuick purification columns (Qiagen) and sequenced as described previously.
Genotyping
For the region flanking the microsatellite repeat array, sequence variation is referenced to the original clone sequence (GenBank accession #AF107030). A combination of polymorphisms is considered a flanking sequence haplotype. Genotype information for each allele at the Ots-2 locus consists of a flanking haplotype and a microsatellite repeat array (fig. 1
). Discrepancies in the length of the microsatellite repeat array occurred for some individuals because of sequence stutter. As a result, clones from a problematic sample could contain multiple sequences for repeat size (e.g., 8-, 9-, 10-repeat units). In such cases, cloned DNA was reamplified using PCR, and repeat length was independently determined through standard polyacrylamide electrophoresis. If a haplotype could not be reliably determined for an allele it was discarded; because both alleles were not identified in all individuals, sample sizes are not necessarily even numbers.
|
Between-Population Analysis
To obtain estimates of genetic differentiation between populations, statistics based on different mutation models, Wright's F-statistics and Slatkin's RST were calculated. Wright's F-statistics, based on the IAM, were calculated using the program Genetix, version 4.0. Calculations were made using microsatellite allele frequencies and frequencies of flanking sequence haplotypes. Additionally, because each microsatellite has a known flanking sequence haplotype, a composite allele was generated combining information from both loci. The composite locus was used to evaluate homoplasy, the occurrence of the same sized microsatellite with different flanking haplotypes. F-statistics were calculated using the composite alleles, and the estimates derived from this no-homoplasy (at the resolution of the data) alternative were compared with the estimates calculated for the flanking and the microsatellite loci alone. The significance of estimates was assessed using 1,000 permutations in Genetix. A measure of population differentiation assuming an SMM RST, was calculated using the program RST CALC, version 2.2 (Goodman 1997
). The estimate was calculated using only the microsatellite frequency data because the repeat array is the only locus that would be consistent with a stepwise model. All estimates were calculated using four population groupings, one using all four sample populations, one using only Central Valley stocks, one excluding winter-run, and one comparing fall and spring-run populations.
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
|
|
|
|
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Although a single marker measures population divergence imprecisely, data from the Ots-2 microsatellite parallels information derived from all marker types. Ots-2 microsatellite data show winter run to be a genetic outlier in California (Banks et al. 2000
), and this result is corroborated by allozymes (Bartley et al. 1992
; Winans and Teal, personal communication), mtDNA (Nielsen et al. 1994
), and MHC class II B (Kim, Parker, and Hedrick 1999
; Hedgecock et al. 2001
). In addition, microsatellite data from this study show Californian salmon populations to be more similar to each other than to the Quesnel population (Canada) (table 5
). Although the Ots-2 microsatellite is highly polymorphic, the variation is structured by flanking haplotype. The associations between haplotype and microsatellite allele are strikingly conserved across sample populations (fig. 2
). Haplotype information from genetically distinct groups has led us to conclude that changes in microsatellite allele frequencies are caused by shifts in frequencies of contextual haplotypes and not by stepwise mutation in the repeat region. Recent work in human genetics also points to the importance of chromosomal haplotypes for resolving population structure (Rioux et al. 2001
; Stephens et al. 2001
).
That nonrandom structure exists in the data sets is not necessarily surprising; however, what is not expected is that data from all populations should differ from random association in the same way (fig. 2 ). For example, flanking haplotype-2 is the most frequent haplotype; yet, it most commonly occurs with the 9-repeat microsatellite, and flanking haplotype-1 is associated most commonly with repeat 7. The correlation of repeat size with haplotype class is also shown by the strong linkage disequilibrium observed in the data (table 3 and fig. 2 ). Additionally, if the total linkage disequilibrium estimate is partitioned into the contribution of each allele combination, there is an excess of large, rare microsatellite alleles in haplotype-3 and an excess of common, small microsatellite alleles in nonhaplotype-3 classes. This observation is associated with the greater diversity seen in haplotype-3, irrespective of haplotype frequency (table 2 and fig. 2 ). This pattern of variation is not expected under a rapid stepwise mutation process, which should rapidly generate microsatellite allelic diversity, filling in the gaps of the microsatellite profiles for each haplotype and homogenizing the microsatellite allele frequency profiles within each population (S. M. Blankenship et al., unpublished data). This observation suggests that the microsatellite mutation rate is much slower than that expected, slower than changes in the frequencies of flanking haplotypes to which the Ots-2 microsatellite is linked.
Differences among populations are attributable primarily to differences in flanking haplotype frequencies. The correlation between microsatellite alleles and flanking haplotype, established by gametic disequilibrium, could explain how microsatellite markers produce concordant information with other marker types because population differentiation exists at the haplotype level. Conversely, populations are not different or are much more similar within a haplotype. For example, the microsatellite allele-frequency profiles at haplotype-3 are statistically equivalent among Californian populations (table 4 ). It appears possible that demographic effects (e.g., genetic bottleneck) alter the frequency of the flanking sequence haplotypes, which subsequently alter the microsatellite allele-frequency distributions. Demographic changes that alter flanking haplotype profiles could also account for the reduction in microsatellite allelic diversity observed in the winter and Quesnel populations (table 1 , parts a and d). We need to invoke a combination of slow mutation at the microsatellite locus and genetic drift or selection at the level of flanking sequence haplotypes to explain the pattern of variation seen at Ots-2.
That most microsatellite alleles have multiple flanking sequences confirms homoplasy for size. Moreover, the pattern of homoplasy is the same within and among sampled populations, with homoplasy occurring at almost every allele. For example, allele 9 showed homoplasy in every study population; however, it most commonly occurred in haplotype-2 (fig. 2
). Other examples are 11-repeat and 17-repeat alleles, which show homoplasy in 3 of 4 sample populations but most commonly occur in haplotype-3. This observation would not have been possible without the use of SNPs flanking the microsatellite repeat array. The older flanking sequence haplotypes can be used to define the evolutionary relationships among the microsatellite alleles, given that the unique noncoding sequence has a mutation rate of approximately 1 x 10-9 per locus/generation (Li and Graur 1991
), several orders of magnitude slower than that of microsatellite repeat arrays. Homoplasy, the recurrence of same-size alleles in different haplotypes, clearly does occur within populations for simple sequence repeat loci.
Population analysis is not affected by homoplasy, however, because microsatellite allele-frequency profiles are not solely influenced by stepwise mutation. The slow mutation at the microsatellite creates linkage disequilibrium and counteracts homoplasy by confining microsatellite alleles to haplotypes. Perhaps lower levels of homoplasy present at the Ots-2 microsatellite due to linkage result in greater diagnostic power for the locus. Data presented in this study show that RST and FST give similar estimates of population divergence (table 5
), although the RST value calculated for the population grouping that excluded the winter-run population is substantially higher than the FST estimates. The within-population component of variance was large for the population grouping excluding winter run, which contributed to a high value for RST even though the between-population component of variance was low in this grouping. Estimates of FST may have been reduced by high within-population heterozygosity (Hedrick 1999
). The composite locus, which had the highest observed heterozygosity, generally had lower genetic distance estimates.
Whether the pattern of variation seen at Ots-2 is typical for microsatellite loci remains to be seen in future studies of other loci. For example, Ots-2 is located on the pseudolinkage group Oii on the rainbow trout linkage map (Sakamoto et al. 2000
), where recombination may be reduced. If Ots-2 proves to be typical, then the usefulness of microsatellites for population genetics may come from associations with larger chromosomal fragments whose frequencies are responding more directly to demographic factors governing population differentiation. Microsatellites afford an easy entrée to genome variation and are clearly valuable for mapping and parentage studies; nevertheless, a shift toward SNPs in population genetics may provide a better insight into the evolution of populations below the species level.
![]() |
Acknowledgements |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
Footnotes |
---|
Keywords: evolution
microsatellite
simple sequence repeats
single nucleotide polymorphisms
linkage disequilibrium
Address for correspondence and reprints: Scott M. Blankenship, Bodega Marine Laboratory, University of CaliforniaDavis, P.O. Box 1192, Occidental, California 95465. szscottb{at}yahoo.com
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Angers B., A. Estoup, P. Jarne, 2000 Microsatellite size homoplasy, SSCP, and population structure: a case study in the freshwater snail Bulinus truncatus Mol. Biol. Evol 17:1926-1932
Banks M. A., M. S. Blouin, B. A. Baldwin, V. K. Rashbrook, H. A. Fitzgerald, S. M. Blankenship, D. Hedgecock, 1999 Isolation and inheritance of novel microsatellites in chinook salmon (Oncorhynchus tschawytscha) J. Hered 90:281-288
Banks M. A., V. K. Rashbrook, M. J. Calavetta, C. A. Dean, D. Hedgecock, 2000 Analysis of microsatellite DNA resolves genetic structure and diversity of chinook salmon (Oncorhynchus tshawytscha) in California's Central Valley Can. J. Fish. Aquat. Sci 57:915-927[ISI]
Bartley D., G. A. E. Gall, B. Bentley, J. Brodziak, R. Gomulkiewicz, M. Mangel, 1992 Geographic variation in population genetic structure of chinook salmon from California and Oregon Fish. Bull 90:77-100[ISI]
Belkhir K., P. Borsa, L. Chikhi, N. Raufaste, F. Bonhomme, 2001 19962001 GENETIX 4.02, logiciel sous Windows TM pour la génétique des populations Laboratoire Génome, Populations, Interactions, CNRS UMR 5000, Université de Montpellier II, Montpellier, France
Blouin M. S., M. Parsons, V. Lacaille, S. Lotz, 1996 Use of microsatellite loci to classify individuals by relatedness Mol. Ecol 5:393-401[ISI][Medline]
Bowcock A. M., A. Ruizlinares, J. Tomfohrde, E. Minch, J. R. Kidd, L. L. Cavallisforza, 1994 High resolution of human evolutionary trees with polymorphic microsatellites Nature 368:455-457[ISI][Medline]
Culver M., M. A. Menotti-Raymond, S. J. O'Brien, 2001 Patterns of size homoplasy at 10 microsatellite loci in pumas (Puma concolor) Mol. Biol. Evol 18:1151-1156
Estoup A., M. Solignac, J. M. Cornuet, J. Goudet, A. Scholl, 1996 Genetic differentiation of continental and Island populations of Bombus Terrestris (Hymenoptera, Apidae) in Europe Mol. Ecol 5:19-31[ISI][Medline]
Estoup A., C. Tailliez, J. M. Cornuet, M. Solignac, 1995 Size homoplasy and mutational processes of interrupted microsatellites in two bee species, Apis mellifera and Bombus terrestris (Apidae) Mol. Biol. Evol 12:1074-1084[Abstract]
Ford M. J., 1998 Testing models of migration and isolation among populations of chinook salmon (Oncorhynchus tschawytscha) Evolution 52:539-557[ISI]
Garza J. C., N. B. Freimer, 1996 Homoplasy for size at microsatellite loci in humans and chimpanzees Genome Res 6:211-217[Abstract]
Goldstein D. B., A. R. Linares, L. L. Cavallis-forza, M. W. Feldman, 1995 An evaluation of genetic distances for use with microsatellite loci Genetics 139:463-471
Goodman S. J., 1997 R-ST Calc: a collection of computer programs for calculating estimates of genetic differentiation from microsatellite data and determining their significance Mol. Ecol 6:881-885[ISI]
Grimaldi M. C., B. Crouau-Roy, 1997 Microsatellite allelic homoplasy due to variable flanking sequences J. Mol. Evol 44:336-340[ISI][Medline]
Hedgecock D., M. A. Banks, V. K. Rashbrook, C. A. Dean, S. M. Blankenship, 2001 Applications of population genetics to conservation of chinook salmon diversity in the Central Valley Pp. 4570 inR. L. Brown, ed. Fish Bulletin 179: contributions to the biology of Central Valley Salmonids. California Department of Fish and Game
Henderson S. T., T. D. Petes, 1992 Instability of simple sequence DNA in Saccharomyces cerevisiae Mol. Cell. Biol 12:2749-2757[Abstract]
Jarne P., P. J. L. Lagoda, 1996 Microsatellites, from molecules to populations and back Trends Ecol. Evol 11:424-429[ISI]
Kim T. J., K. M. Parker, P. W. Hedrick, 1999 Major histocompatibility complex differentiation in Sacramento River chinook salmon Genetics 151:1115-1122
Kimura M., J. F. Crow, 1964 The numbers of alleles that can be maintained in a finite population Genetics 49:725-738
Kimura M., T. Ohta, 1978 Stepwise mutation model and distribution of allelic frequencies in a finite population Proc. Natl. Acad. Sci. USA 75:2868-2872[Abstract]
Levinson G., G. A. Gutman, 1987a. High frequency of short frameshifts in poly-CA/TG tandem repeats borne by bacteriophage M13 in Escherichia coli K-12 Nucleic Acids Res 15:5323-5338[Abstract]
. 1987b. Slipped-strand mispairing: a major mechanism for DNA sequence evolution Mol. Biol. Evol 4:203-221[Abstract]
Li W.-H., D. Graur, 1991 Fundamentals of molecular evolution Sinauer, Sunderland, Mass
Litt M., J. A. Luty, 1989 A hypervariable microsatellite revealed by in vitro amplification of a dinucleotide repeat within the cardiac muscle actin gene Am. J. Hum. Genet 44:397-340[ISI][Medline]
National Marine Fisheries Service (NMFS). 1994 Endangered and threatened species; status of Sacramento River winter-run chinook salmon Fed. Reg 59:440-450
Nielsen J. L., C. Gan, J. M. Wright, W. K. Thomas, 1994 Phylogeographic patterns in California steelhead as determined by MtDNA and microsatellite analyses Calif. Coop. Oceanic Fish. Investig. Rep 35:90-92
Primmer C. R., H. Ellegren, N. Saino, A. P. Moller, 1996 Directional evolution in germline microsatellite mutations Nat. Genet 13:391-393[ISI][Medline]
Queney G., N. Ferrand, S. Weiss, F. Mougel, M. Monnerot, 2001 Stationary distributions of microsatellite loci between divergent population groups of the European rabbit (Oryctolagus cuniculus) Mol. Biol. Evol 18:2169-2178
Raymond M., F. Rousset, 1995 Genepop (Version 1.2)population genetics software for exact tests and Ecumenicism J. Hered 86:248-249[ISI]
Rioux J. D., M. J. Daly, M. S. Silverberg, et al. (31 co-authors) 2001 Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease Nat. Genet 29:223-228[ISI][Medline]
Sakamoto T., R. G. Danzmann, K. Gharbi, et al. (12 co-authors) 2000 A microsatellite linkage map of rainbow trout (Oncorhynchus mykiss) characterized by large sex-specific differences in recombination rates Genetics 155:1331-1345
Sambrook J., E. F. Fritsch, T. Maniatis, 1989 Molecular cloning a laboratory manual. 2nd edition Cold Spring Harbor Laboratory Press, New York
Schlötterer C., D. Tautz, 1992 Slippage synthesis of simple sequence DNA Nucleic Acids Res 20:211-215[Abstract]
Stephens J. C., J. A. Schneider, D. A. Tanguay, et al. (28 co-authors) 2001 Haplotype variation and linkage disequilibrium in 313 human genes Science 293:489-493
Tautz D., 1989 Hypervariability of simple sequences as a general source for polymorphic DNA markers Nucleic Acids Res 17:6463-6471[Abstract]
Utter F., G. Milner, G. Ståhl, D. Teel, 1989 Genetic population structure of chinook salmon (Oncorhynchus tshawytscha), in the Pacific Northwest Fish. Bull 87:239-264[ISI]
Weber J. L., P. E. May, 1989 Abundant class of human DNA polymorphisms which can be typed using the polymerase chain reaction Am. J. Hum. Genet 44:388-396[ISI][Medline]
Weber J. L., C. Wong, 1993 Mutation of human short tandem repeats Hum. Mol. Genet 2:1123-1128[Abstract]
Wierdl M., M. Dominska, T. D. Petes, 1997 Microsatellite instability in yeast: dependence on the length of the microsatellite Genetics 146:769-779
Zaykin D. V., A. I. Pudovkin, 1993 2 Programs to estimate significance of chi-square values using pseudo-probability tests J. Hered 84:152-152[ISI]