Division of Biological Sciences, University of Montana, Missoula
The tendency of microsatellites to be highly polymorphic is a major factor responsible for their popularity as markers for ecological and evolutionary studies. Microsatellite polymorphism is generally attributed to slip-strand mispairing errors, causing the addition or deletion of repeat units during replication (Levinson and Gutman 1987
). Valdes, Slatkin, and Freimer (1993)
found that human microsatellite evolution appears to follow a stepwise mutation model (SMM) (Ohta and Kimura 1973
). Following the SMM, single repeat units are added or deleted with equal and constant probability across all alleles. Several statistical methods to evaluate patterns of microsatellite variability and differentiation that assume variants of the SMM have since been developed (e.g., Goldstein et al. 1995a,
1995b;
Slatkin 1995
; Rousset 1996
) and incorporated into widely used software programs such as GENEPOP (Raymond and Rousset 1995
).
Although slippage during replication clearly plays a key role in the overall instability of the microsatellites (reviewed by Eisen 1999
), mounting evidence indicates that microsatellite mutation dynamics are more complex than is reflected by the SMM. Numerous examples of mutations that do not constitute single repeat unit changes or those that reflect heterogeneity or bias in the mutational processes of particular loci or alleles have been documented (see reviews by Ellegren 2000a,
2000b
and Schlotterer 2000
). In particular, the length, type, and number of repeat units have been identified as important factors contributing to the complexity of microsatellite evolution.
Mutation events occurring early in gametogenesis can further complicate mutation dynamics. An underlying assumption of many population genetics models is that mutations occur and enter the gene pool independently. However, Woodruff and Thompson (1992)
found that as many as 20% of new mutations detected in large-scale Drosophila screens did not occur as independent events but rather represented clusters of identical mutant alleles sharing a common premeiotic origin. Subsequently, Woodruff, Huai, and Thompson (1996)
have shown that the occurrence of premeiotic cluster mutations can not only bias estimates of mutation rates but can also influence basic population genetic processes such as fixation probabilities. Cluster mutations have been documented at microsatellite loci in only two species: pipefishes (Sygnathus typhle, Jones et al. 1999
) and green turtles (Chelonia mydas, FitzSimmons 1998
). However, as pointed out by Ellegren (2000a,
2000b)
, this may be because of the difficulty in detecting cluster mutations in organisms that produce small numbers of offspring per generation.
As stressed by Chambers and MacAvoy (2000)
, "a clear knowledge of the process of mutational change at microsatellite loci is imperative for the correct selection of theoretical models upon which statistical methods can be based" however, a knowledge of mutation dynamics requires more information than is typically available. In particular, a lack of inheritance data often precludes direct evaluation of the markers used in population studies. However, this is not the case for many salmonid fishes that are commonly raised in hatcheries and for which many microsatellite markers have been developed (e.g., Scribner, Gust, and Fields 1996
; Olsen, Bentzen, and Seeb 1998
; Banks et al. 1999
). In this paper, we examine the transmission of nine microsatellite loci in 50 families to evaluate the dynamics of microsatellite mutations in pink salmon (Oncorhyncus gorbuscha).
We raised families of pink salmon by randomly pairing mature adults collected in Resurrection Bay, Alaska. We collected embryos from each of the families after eye pigment became apparent in the embryo. We extracted DNA from the embryos and fin clips taken from adults using the PuregeneTM DNA isolation kit (Gentra Systems Inc., Minneapolis, Minn.). We amplified microsatellites using primers for salmonid fishes developed in other laboratories: OGO1c and OGO8 (Ogo1c and Ogo8, Olsen, Bentzen, and Seeb 1998
); OMY301 (Omy301UoG, R. Danzmann, personal communication); OMYRGT6-1,2 (OmyTRG6/I,iiTUF, N. Okamoto, personal communication); ONEµ3 (Oneµ3, Scribner, Gust, and Fields 1996
); OTS1 (Ots1, Banks et al. 1999
); SSA20.19-1,2 (µ-20.19*, Sanchez et al. 1996
); and SSA408 (Ssa408, M. Cairney, personal communication). We used fluorescent primers and followed the PCR conditions recommended by the original authors. We visualized PCR products with a Hitachi FMBIO-100 or FMBIO II fluorescent imager after electrophoresis in 4.5% denaturing polyacrylamide gels. We scored alleles relative to commercial size standards (BioVentures, Inc.).
For the seven loci isolated from species other than pink salmon, we determined the repeat arrays in pink salmon by sequencing at least one allele. If multiple products were produced in the PCR reaction, we isolated bands in 3%4% agarose gels. We then either purified and sequenced the bands or reamplified, purified, and sequenced them with both the forward and reverse primers. We purified PCR products with QiaquickTM columns (Qiagen) following the supplier's protocol. Direct sequencing of PCR products was performed by a commercial laboratory. We did not sequence alleles from the two loci that were developed from pink salmon (OGO1c and OGO8).
We initially genotyped parents and 10 progeny from each of the 50 families. Alleles present in progeny that were not present in either of that individual's parents were considered to be mutants after confirming that correct parentage could be assigned at the other loci. The progenitor of the mutant allele was assumed to be the parental allele that was closest in size to the mutant allele. Because we detected multiple mutations at SSA408 in progeny from two of the families (9823 and 9826) in the initial analysis, we analyzed all the remaining embryos available from these families (38 and 40 embryos, respectively). To increase our sample size, we also genotyped 36 additional progeny from each of the five randomly selected families.
Our sequence analysis of alleles at six of the seven loci originally developed from other salmonids confirmed that these markers comprise similar microsatellites in pink salmon (table 1
). The one exception (OMYRGT6-1,2) is a duplicated locus that was reported as a CA repeat in rainbow trout (Oncorhynchus mykiss, Sakamoto et al. 2000
, table 1
). In pink salmon, PCR amplifications using OMYRGT6-1,2 primers consistently produced a smaller band that is present in all individuals as well as larger polymorphic bands that segregated after Mendelian inheritance. The polymorphic OMYRGT6-1,2 locus in pink salmon contains a CACT repeat array, and the smaller monomorphic locus contains the short interrupted repeat (CA)7-TA-(CA)2 (table 1
). The flanking sequences of the rainbow trout CA repeat and the pink salmon CA and CACT repeats can be readily aligned, suggesting that OMYRGT6-1 and OMYRGT6-2 have evolved two different microsatellite arrays. In the rainbow trout, the two copies of OMYRGT6-1,2 map to different linkage groups (Sakamoto et al. 2000
). However, whether these loci comprise different microsatellite arrays in the rainbow trout has not been determined (T. Sakamoto, personal communication).
|
|
In zebrafish (Danio rerio), researchers combining morphological and mRNA expression studies using germ line markers have recently determined that by the 5-somite (32-cell) stage and until about the 1,000-cell stage, there are four PGCs (Braat et al. 1999
). During their migration toward the gonads, the four PGCs give rise to a total of 2030 cells that populate the gonad and differentiate into germ cells (Braat et al. 1999
). If a mutation occurs in one of the original four PGCs (and there is no attrition of cell lines), approximately one out of eight (12.5%) of the progeny should inherit the mutant allele. If gametogenesis is similar in pink salmon, our findings of 9 identical mutant alleles out of the 50 transmitted maternally (18%) in family 98-26 and 4 of the 46 identical mutant alleles (8.7%) transmitted paternally in family 98-23 suggest that each of these mutations likely occurred either in one of the four PGCs or in the subsequent one or two generations of cells that populated the gonad.
The occurrence of clustered mutations results in nonuniform distributions of novel alleles in a population which could influence interpretations of mutation rates and patterns as well as estimates of genetic population structure. For example, Woodruff, Huai, and Thompson (1996)
have shown that mutant alleles that are a part of clusters are more likely to persist and be fixed in a population than mutant alleles entering the population independently. In the present study, 15 of the 24 mutant alleles detected at SSA408 (54%) apparently resulted from premeiotic mutations. Jones et al. (1999)
similarly found that a high proportion (40%) of new mutants observed in pipefish occurred in clusters.
We estimated mutation rates by counting each mutant allele detected as one mutation, regardless of whether the allele appeared to be part of a mutational cluster. However, we only included randomly selected individuals in this analysis (i.e., we eliminated the 78 additional progeny from families 98-23 and 98-26 that we analyzed because we had detected multiple mutations in our initial analysis). The remaining 11 mutations in 1,300 transmissions at SSA408 and 5 mutations in 1,278 transmissions at OGO1c yield mutation rate estimates of 0.0085 (0.00420.0151) and 0.0039 (0.00130.0091) mutations per gamete, respectively, with the numbers in parentheses being the 95% Poisson confidence intervals. We did not detect mutations at any of the other seven loci; the upper 95% confidence limit using a Poisson distribution for detecting zero mutations in 1,300 transmissions is 0.0028. The proportion of mutations observed varied significantly among the nine loci (contingency chi-square, P < 0.001). However, our mutation rate estimates for all the loci are within the range reported for other organisms (see Ellegren 2000b,
table 1 ).
All the mutations detected were size changes of four bases (table 2 ) which is consistent with single-step addition or deletion mutations at both SSA408 and OGO1c. Determining to what degree our data reflect a tendency for mutations to result in size increases or decreases depends on how mutations are counted. If all mutations are treated as single events, 17 mutations at SSA408 reflected size increases and two reflected size decreases (table 2 ). Similarly, two mutations detected at OGO1c resulted in size increases and three resulted in size decreases (table 2 ). Alternatively, treating all within-family clusters of the same mutant allele as single mutations that were propagated during gametogenesis reduces the number of size increases at SSA408 to six and size decreases to one (table 2 ). Similarly, because two of the progeny in family 98-71 share the same mutation at OGO1c, the number of size decreases would be two rather than three (table 2 ).
Is the SMM appropriate for pink salmon microsatellites? All 11 of the unique mutations detected in this study were consistent with the addition or deletion of a single repeat unit, which is in accordance with the SMM. Furthermore, our data reflect a high incidence of homoplasy, as 7 of the 11 different mutant alleles detected were alleles already present in other families in this study (E. K. Steinberg et al., unpublished data). Because SMM-based estimators assume that alleles of similar sizes are related, these estimators are expected to be more accurate in the presence of size homoplasy than estimators that assume all mutations are independent and result in novel alleles (Estoup and Angers 1998
). These findings suggest that genetic differentiation estimators based on the SMM would be appropriate. However, we also detected a tendency toward size increases in mutant alleles. Estoup and Angers (1998)
recommend comparing results from estimators based on different underlying mutational models for concordance because it is not clear how different types of mutational biases affect SMM-based estimators. Given our findings, we agree with this recommendation.
The duplicated locus OMYRGT6-1,2 apparently comprises two different microsatellite arrays in pink salmon. In rainbow trout, the two copies of this duplicated locus map to different linkage groups (Sakamoto et al. 2000
). However, whether these loci comprise different microsatellite arrays in rainbow trout has not been analyzed (T. Sakamoto, personal communication). It would be informative to compare the sequences of OMYRGT6-1 and OMYRGT6-2 in rainbow trout, as well as other salmonid fishes, to study the evolution of these two divergent paralogous microsatellite loci. Salmonid fishes have undergone extensive gene duplication compared with other organisms, having diverged from a tetraploid ancestor approximately 2550 MYA (Allendorf and Thorgaard 1984
). Given the prevalence of duplicated loci in salmonid fishes, these organisms may provide an exceptional opportunity to use comparative approaches to study the molecular evolution of microsatellites.
In conclusion, we found evidence for heterogeneity in the rates and patterns of mutation among loci, suggesting that no single model will likely represent the complexity underlying the evolutionary dynamics of microsatellites. Our findings add to the evidence in support of the argument made by Woodruff, Huai, and Thompson (1996)
that the occurrence of premeiotic cluster mutations may play an important role in the evolutionary dynamics of microsatellites. Finally, our identification of duplicated microsatellite loci comprising different repeat arrays indicates that the use of comparative analysis to study mutation dynamics (e.g., Amos 1999
) could be misleading if the duplication is not detected.
Acknowledgements
We thank S. Forbes, K. Knudsen, M. Skinner, P. Spruell, and J. Wenburg for comments on the manuscript, R. Leary, M. Steinberg, and A. Whiteley for helpful discussions, and G. Chambers for his suggestions and references on the process of mutations in microsatellites. E.K.S. was supported by a postdoctoral fellowship from the National Science Foundation. This research was funded by the Exxon Valdez Oil Spill Trustee Council (Project/190). However, the findings and the conclusions of the authors are their own and do not necessarily reflect the views or positions of the Trustee Council.
Footnotes
Keywords: microsatellite
mutation
salmon
Oncorhyncus gorbuscha
Address for correspondence and reprints: Fred W. Allendorf, Division of Biological Sciences, University of Montana, Missoula, Montana 59812. darwin{at}selway.umt.edu
References
Allendorf F. W., G. H. Thorgaard, 1984 Tetraploidy and the evolution of salmonid fishes Pp. 153 in B. J. Turner, ed. Evolutionary genetics of fishes. Plenum Publishing Corporation, New York
Amos W., 1999 A comparative approach to the study of microsatellite evolution Pp. 6679 in D. B. Goldstein and C. Schlotterer, eds. Microsatellites: evolution and applications. Oxford University Press, Oxford
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 tshawytscha) J. Hered 90:281-288
Braat A. K., T. Zandbergen, S. Van de Water, H. J. T.H. Goos, D. Zivkovic, 1999 Characterization of zebrafish primordial germ cells: morphology and early distribution of vasa RNA Dev. Dynam 216:153-167[ISI][Medline]
Chambers G. K., E. S. MacAvoy, 2000 Microsatellites: consensus and controversy Comp. Biochem. Physiol 126:455-476[ISI]
Eisen J. A., 1999 Mechanistic basis for microsatellite instability Pp. 3448 in D. B. Goldstein and C. Schlotterer, eds. Microsatellites: evolution and applications. Oxford University Press, Oxford
Ellegren H., 2000a. Heterogeneous mutation processes in human microsatellite DNA sequences Nat. Genet 24:400-402[ISI][Medline]
. 2000b. Microsatellite mutations in the germline: implications for evolutionary inference Trends Genet 16:551-558[ISI][Medline]
Estoup A., B. Angers, 1998 Microsatellites and minisatellites for molecular ecology: theoretical and empirical considerations Pp. 5586 in G. R. Carvalho, ed. Advances in molecular ecology. Nato Sciences Series, IOS Press, Amsterdam
FitzSimmons N. N., 1998 Single paternity of clutches and sperm storage in the promiscuous green turtle (Chelonia mydas) Mol. Ecol 7:575-584[ISI][Medline]
Goldstein D. B., A. Ruiz Linares, L. L. Cavalli-Sforza, M. W. Feldman, 1995a. Genetic absolute dating based on microsatellites and the origin of modern humans Proc. Natl. Acad. Sci. USA 92:6723-6727[Abstract]
. 1995b. An evaluation of genetic distances for use with microsatellite loci Genetics 139:463-471
Jones A. G., G. Rosenqvist, A. Berglund, J. C. Avise, 1999 Clustered microsatellite mutations in the pipefish Syngathus typhle Genetics 152:1057-1063
Lee J. S., M. G. Hanford, J. L. Genova, R. A. Farber, 1999 Relative stabilities of dinucleotide and tetranucleotide repeats in cultured mammalian cells Hum. Mol. Genet 8:2567-2572
Levinson G., G. A. Gutman, 1987 Slipped-strand mispairing: a major mechanism for DNA sequence evolution Mol. Biol. Evol 4:203-221[Abstract]
Matova N., L. Cooley, 2001 Comparative aspects of animal oogenesis Dev. Biol 231:291-320[ISI][Medline]
Ohta T., M. Kimura, 1973 A model of mutation appropriate to estimate the number of electrophoretically detectable alleles in a finite population Genet. Res 22:201-204[ISI][Medline]
Olsen J. B., P. Bentzen, J. E. Seeb, 1998 Characterization of seven microsatellite loci derived from pink salmon Mol. Ecol 7:1087-1089[ISI][Medline]
Raymond M., F. Rousset, 1995 GENEPOP: population genetics software for exact tests and ecumenicism J. Hered 86:248-249[ISI]
Rousset F., 1996 Equilibrium values of measures of population subdivision for stepwise mutation processes Genetics 142:1357-1362
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
Sanchez J. A., C. Clabby, D. Ramos, G. Blanco, F. Flavin, E. Vasquez, R. Powell, 1996 Protein and microsatellite single locus variability in Salmo salar L. (Atlantic salmon) Heredity 77:423-432[ISI][Medline]
Schlotterer C., 2000 Evolutionary dynamics of microsatellite DNA Chromosoma 109:365-371[ISI][Medline]
Schlotterer C., R. Ritter, B. Harr, G. Brem, 1998 High mutation rates of long microsatellite alleles in Drosophila melanogaster provide evidence for allele specific mutation rates Mol. Biol. Evol 15:1269-1274
Scribner K. T., J. R. Gust, R. L. Fields, 1996 Isolation and characterization of novel microsatellite loci: cross-species amplification and population genetic applications Can. J. Fish. Aquat. Sci 53:685-693[ISI]
Slatkin M., 1995 A measure of population subdivision based on microsatellite allele frequencies Genetics 139:457-462
Valdes A. M., M. Slatkin, N. B. Freimer, 1993 Allele frequencies at microsatellite loci: the stepwise mutation model revisited Genetics 133:737-749
Weber J. L., C. Wong, 1993 Mutation of human short tandem repeats Hum. Mol. Genet 2:1123-1128[Abstract]
Woodruff R. C., H. Huai, J. N. Thompson Jr., 1996 Clusters of identical new mutations in the evolutionary landscape Genetica 98:149-160[ISI][Medline]
Woodruff R. C., J. N. Thompson Jr., 1992 Have premeiotic clusters of mutation been overlooked in evolutionary theory? J. Evol. Biol 5:457-464[ISI]