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Population Genomics of Parallel Adaptation in Threespine Stickleback using Sequenced RAD Tags
Open accessAbstract
Next-generation sequencing technology provides novel opportunities for gathering genome-scale sequence data in natural populations, laying the empirical foundation for the evolving field of population genomics. Here we conducted a genome scan of nucleotide diversity and differentiation in natural populations of threespine stickleback (Gasterosteus aculeatus). We used Illumina-sequenced RAD tags to identify and type over 45,000 single nucleotide polymorphisms (SNPs) in each of 100 individuals from two oceanic and three freshwater populations. Overall estimates of genetic diversity and differentiation among populations confirm the biogeographic hypothesis that large panmictic oceanic populations have repeatedly given rise to phenotypically divergent freshwater populations. Genomic regions exhibiting signatures of both balancing and divergent selection were remarkably consistent across multiple, independently derived populations, indicating that replicate parallel phenotypic evolution in stickleback may be occurring through extensive, parallel genetic evolution at a genome-wide scale. Some of these genomic regions co-localize with previously identified QTL for stickleback phenotypic variation identified using laboratory mapping crosses. In addition, we have identified several novel regions showing parallel differentiation across independent populations. Annotation of these regions revealed numerous genes that are candidates for stickleback phenotypic evolution and will form the basis of future genetic analyses in this and other organisms. This study represents the first high-density SNP-based genome scan of genetic diversity and differentiation for populations of threespine stickleback in the wild. These data illustrate the complementary nature of laboratory crosses and population genomic scans by confirming the adaptive significance of previously identified genomic regions, elucidating the particular evolutionary and demographic history of such regions in natural populations, and identifying new genomic regions and candidate genes of evolutionary significance.
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
The genetical theory of natural selection
Fisher, R. A. (1930) · doi:10.5962/bhl.title.27468 · Cited by 17,617
The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490
Methods of Meta-Analysis: Correcting Error and Bias in Research Findings
Schmidt, F. L., & Hunter, J. E. (2015) · doi:10.4135/9781483398105 · Cited by 5,542
The Ecology of Adaptive Radiation
Schluter, D. (2000) · doi:10.1093/oso/9780198505235.001.0001 · Cited by 4,974
Widespread parallel evolution in sticklebacks by repeated fixation of Ectodysplasin alleles.
Colosimo, P. F., Hosemann, K. E., Balabhadra, S., Villarreal, G., Dickson, M., Grimwood, J., Schmutz, J., Myers, R. M., Schluter, D., & Kingsley, D. M. (2005) · Science · doi:10.1126/science.1107239 · Cited by 1,448
Genetics of global gene expression
Rockman, M. V., & Kruglyak, L. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1964 · Cited by 666 · cited 1×
“analyses [42–47].”
Stinchcombe, J. R., & Hoekstra, H. E. (2008) · Heredity · doi:10.1038/sj.hdy.6800937 · Cited by 622
Localizing Recent Adaptive Evolution in the Human Genome.
Williamson, S. H., Hubisz, M. J., Clark, A. G., Payseur, B. A., Bustamante, C. D., & Nielsen, R. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030090 · Cited by 507
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Abbott, R., Albach, D., Ansell, S., Arntzen, J. W., Baird, S. J. E., Bierne, N., Boughman, J., Brelsford, A., Buerkle, C. A., Buggs, R., et al. (2013) · Journal of Evolutionary Biology · doi:10.1111/j.1420-9101.2012.02599.x · Cited by 2,194
Cruickshank, T. E., & Hahn, M. W. (2014) · Molecular Ecology · doi:10.1111/mec.12796 · Cited by 1,061
Assessing the benefits and risks of translocations in changing environments: a genetic perspective
Weeks, A. R., Sgro, C. M., Young, A. G., Frankham, R., Mitchell, N. J., Miller, K. A., Byrne, M., Coates, D. J., Eldridge, M. D. B., Sunnucks, P., et al. (2011) · Evolutionary Applications · doi:10.1111/j.1752-4571.2011.00192.x · Cited by 916
The genetic causes of convergent evolution
Stern, D. L. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3483 · Cited by 818
Whiteley, A. R., Fitzpatrick, S. W., Funk, W. C., & Tallmon, D. A. (2015) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2014.10.009 · Cited by 813
Polygenic adaptation: a unifying framework to understand positive selection
Barghi, N., Hermisson, J., & Schlötterer, C. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0250-z · Cited by 425
Harpur, B. A., Kent, C. F., Molodtsova, D., Lebon, J. M. D., Alqarni, A. S., Owayss, A. A., & Zayed, A. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1315506111 · Cited by 201
Widespread selection and gene flow shape the genomic landscape during a radiation of monkeyflowers
Stankowski, S., Chase, M. A., Fuiten, A. M., Rodrigues, M. F., Ralph, P. L., & Streisfeld, M. A. (2019) · PLOS Biology · doi:10.1371/journal.pbio.3000391 · Cited by 134
A new model army: Emerging fish models to study the genomics of vertebrate Evo-Devo.
Braasch, I., Peterson, S. M., Desvignes, T., McCluskey, B. M., Batzel, P., & Postlethwait, J. H. (2015) · Journal of Experimental Zoology Part B: Molecular and Developmental Evolution · doi:10.1002/jez.b.22589 · Cited by 122
Indirect evolution of hybrid lethality due to linkage with selected locus in Mimulus guttatus
Wright, K. M., Lloyd, D., Lowry, D. B., Macnair, M. R., & Willis, J. H. (2013) · PLoS Biology · doi:10.1371/journal.pbio.1001497 · Cited by 121
Genome-wide signatures of population bottlenecks and diversifying selection in European wolves
Pilot, M., Greco, C., vonHoldt, B. M., Jędrzejewska, B., Randi, E., Jędrzejewski, W., Sidorovich, V. E., Ostrander, E. A., & Wayne, R. K. (2014) · Heredity · doi:10.1038/hdy.2013.122 · Cited by 111
Andrew, R. L., & Rieseberg, L. H. (2013) · Evolution · doi:10.1111/evo.12106 · Cited by 116
Characterizing bias in population genetic inferences from low-coverage sequencing data
Han, E., Sinsheimer, J. S., & Novembre, J. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/mst229 · Cited by 94
The probability of parallel genetic evolution from standing genetic variation
MacPherson, A., & Nuismer, S. L. (2017) · Journal of Evolutionary Biology · doi:10.1111/jeb.13006 · Cited by 79
Overview on the Role of Advance Genomics in Conservation Biology of Endangered Species
Khan, S., Nabi, G., Ullah, M. W., Yousaf, M., Manan, S., Siddique, R., & Hou, H. (2016) · International Journal of Genomics · doi:10.1155/2016/3460416 · Cited by 63
Johnson, J. L., Wittgenstein, H., Mitchell, S. E., Hyma, K. E., Temnykh, S. V., Kharlamova, A. V., Gulevich, R. G., Vladimirova, A. V., Fong, H. W. F., Acland, G. M., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0127013 · Cited by 38
The hybrid history of zebrafish
McCluskey, B. M., Batzel, P., & Postlethwait, J. H. (2025) · G3: Genes, Genomes, Genetics · doi:10.1093/g3journal/jkae299 · Cited by 5
Metadata
- Authors
- Hohenlohe, P. A., Bassham, S., Etter, P. D., Stiffler, N., Johnson, E. A., & Cresko, W. A.
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-02-26
- Volume
- 6
- Issue
- 2
- Pages
- e1000862
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- OpenAlex
- W1968423560
- Cited by
- 1,395
- References
- 16
- FWCI
- 63.20
- Type
- journal article
- Language
- en
- Open access
- gold
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