Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 1,576

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Genomics and the future of conservation genetics

Allendorf, Fred W., Hohenlohe, Paul A., Luikart, Gordon·2010·Nature Reviews Genetics
DOI 10.1038/nrg2844
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nrg2844

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 10 references

Research works printed but not linked: 119

  1. Ellegren, H. & Sheldon, B. C. Genetic basis of fitness differences in natural populations. Nature 452, 169–175 (2008). An important paper that reviews current understanding of the molecular basis of fitness differences between individuals in natural populations. · DOI · Paper page
  2. Slate, J. et al. Gene mapping in the wild with SNPs: guidelines and future directions. Genetica 136, 97–107 (2009). · DOI
  3. Kohn, M. H., Murphy, W. J., Ostrander, E. A. & Wayne, R. K. Genomics and conservation genetics. Trends Ecol. Evol. 21, 629–637 (2006). · DOI · Paper page
  4. Pertoldi, C. et al. Genome variability in European and American bison detected using the BovineSNP50 BeadChip. Conserv. Genet. 11, 627–634 (2010). · DOI
  5. Thomson, R. C., Wang, I. J. & Johnson, J. R. Genome-enabled development of DNA markers for ecology, evolution and conservation. Mol. Ecol. 19, 2184–2195 (2010). · DOI
  6. Kerstens, H. et al. Large scale single nucleotide polymorphism discovery in unsequenced genomes using second generation high throughput sequencing technology: applied to turkey. BMC Genomics 10, 479 (2009). · DOI
  7. van Bers, N. E. M. et al. Genome-wide SNP detection in the great tit Parus major using high throughput sequencing. Mol. Ecol. 19, 89–99 (2010). · DOI
  8. Vega Thurber, R. L. et al. Metagenomic analysis indicates that stressors induce production of herpes-like viruses in the coral Porites compressa. Proc. Natl Acad. Sci. USA 47, 18413–18418 (2008). · DOI
  9. Nielsen, E. E., Hemmer-Hansen, J., Larsen, P. F. & Bekkevold, D. Population genomics of marine fishes: identifying adaptive variation in space and time. Mol. Ecol. 18, 3128–3150 (2009). · DOI · Paper page
  10. Murchison, E. P. et al. The Tasmanian devil transcriptome reveals Schwann cell origins of a clonally transmissible cancer. Science 327, 84–87 (2010). · DOI
  11. Avise, J. Perspective: conservation genetics enters the genomics era. Conserv. Genet. 11, 665–669 (2010). · DOI
  12. Ouborg, N. J., Pertoldi, C., Loeschcke, V., Bijlsma, R. & Hedrick, P. W. Conservation genetics in transition to conservation genomics. Trends Genet. 26, 177–187 (2010). · DOI · Paper page
  13. Primmer, C. R. From conservation genetics to conservation genomics. Ann. N. Y. Acad. Sci. 1162, 357–368 (2009). · DOI
  14. Romanov, M. N. et al. The value of avian genomics to the conservation of wildlife. BMC Genomics 10, S10 (2010). · DOI
  15. Allendorf, F. W. & Seeb, L. W. Concordance of genetic divergence among sockeye salmon populations at allozyme, nuclear DNA, and mitochondrial DNA markers. Evolution 54, 640–651 (2000). · DOI
  16. Luikart, G. H., England, P., Tallmon, D. A., Jordan, S. & Taberlet, P. The power and promise of population genomics: from genotyping to genome-typing. Nature Rev. Genet. 4, 981–994 (2003). · DOI · Paper page
  17. Storz, J. F. Using genome scans of DNA polymorphism to infer adaptive population divergence. Mol. Ecol. 14, 671–688 (2005). · DOI · Paper page
  18. Giger, T. et al. Life history shapes gene expression in salmonids. Curr. Biol. 16, R281–R282 (2006). · DOI
  19. Landry, P.-A., Koskinen, M. T. & Primmer, C. R. Deriving evolutionary relationships among populations using microsatellites and (δμ)2: all loci are equal, but some are more equal than others. Genetics 161, 1339–1347 (2002). · DOI
  20. Nordborg, M. Structured coalescent processes on different time scales. Genetics 146, 1501–1514 (1997). · DOI
  21. Beaumont, M. A. Detecting population expansion and decline using microsatellites. Genetics 153, 2013–2029 (1999). · DOI · Paper page
  22. Beerli, P. & Felsenstein, J. Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach. Proc. Natl Acad. Sci. USA 98, 4563–4568 (2001). · DOI · Paper page
  23. Skare, O., Sheehan, N. & Egeland, T. Identification of distant family relationships. Bioinformatics 25, 2376–2382 (2009). · DOI
  24. Browning, S. R. & Weir, B. S. Population structure with localized haplotype clusters. Genetics 10 May 2010 (doi:10.1534/genetics.110.116681). · DOI
  25. Lecis, R. et al. Bayesian analyses of admixture in wild and domestic cats (Felis silvestris) using linked microsatellite loci. Mol. Ecol. 15, 119–131 (2006). · DOI
  26. Anderson, C. & Meikle, D. Genetic estimates of immigration and emigration rates in relation to population density and forest patch area in Peromyscus leucopus. Conserv. Genet. 5 Feb 2010 (doi:10.1007/s10592-009-0033-8). · DOI
  27. Bollback, J. P., York, T. L. & Nielsen, R. Estimation of 2Nes from temporal allele frequency data. Genetics 179, 497–502 (2008). · DOI
  28. Wang, J. & Santure, A. W. Parentage and sibship inference from multilocus genotype data under polygamy. Genetics 181, 1579–1594 (2009). · DOI · Paper page
  29. Jones, O. R. & Wang, J. Molecular marker-based pedigrees for animal conservation biologists. Anim. Conserv. 13, 26–34 (2010). · DOI
  30. Keinan, A. & Reich, D. Human population differentiation is strongly correlated with local recombination rate. PLoS Genet. 6, e1000886 (2010). · DOI
  31. Santure, A. W. et al. On the use of large marker panels to estimate inbreeding and relatedness: empirical and simulation studies of a pedigreed zebra finch population typed at 771 SNPs. Mol. Ecol. 19, 1439–1451 (2010). · DOI
  32. Smouse, P. How many SNPs are enough? Mol. Ecol. 19, 1265–1266 (2010). · DOI
  33. Pemberton, J. M. Wild pedigrees: the way forward. Proc. Biol. Sci. 275, 613–621 (2008). A persuasive argument for the value of constructing pedigrees in wild populations to investigate major issues in evolutionary biology, including the genetic architecture of traits, inbreeding depression and inbreeding avoidance.
  34. Sham, P., Cherny, S. & Purcell, S. Application of genome-wide SNP data for uncovering pairwise relationships and quantitative trait loci. Genetica 136, 237–243 (2009). · DOI
  35. Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000). · DOI · Paper page
  36. Hubisz, M. J., Falush, D., Stephens, M. & Pritchard, J. K. Inferring weak population structure with the assistance of sample group information. Mol. Ecol. Resour. 9, 1322–1332 (2009). · DOI · Paper page
  37. Rosenberg, N. A. et al. Genetic structure of human populations. Science 298, 2381–2385 (2002). · DOI · Paper page
  38. Wilson, G. A. & Rannala, B. Bayesian inference of recent migration rates using multilocus genotypes. Genetics 163, 1177–1191 (2003). · DOI
  39. Faubet, P., Waples, R. S. & Gaggiotti, O. E. Evaluating the performance of a multilocus Bayesian method for the estimation of migration rates. Mol. Ecol. 16, 1149–1166 (2007). · DOI · Paper page
  40. Rannala, B. & Mountain, J. L. Detecting immigration by using multilocus genotypes. Proc. Natl Acad. Sci. USA 94, 9197–9201 (1997). · DOI
  41. Holderegger, R. & Wagner, H. H. Landscape genetics. BioScience 58, 199–207 (2008). An integrated review of the emerging field of landscape genetics. · DOI · Paper page
  42. Hagenblad, J., Olsson, M., Parker, H. G., Ostrander, E. A. & Ellegren, H. Population genomics of the inbred Scandinavian wolf. Mol. Ecol. 18, 1341–1351 (2009). · DOI
  43. Casellas, J., Varona, L., Ibanez-Scriche, N., Quintanilla, R. & Noguera, J. L. Skew distribution of founder-specific inbreeding depression effects on the longevity of landrace sows. Genet. Res. 90, 499–508 (2008). · DOI
  44. Lacy, R. C., Alaks, G. & Walsh, A. Hierarchical analysis of inbreeding depression in Peromyscus polionotus. Evolution 50, 2187–2200 (1996). · DOI
  45. Casellas, J., Piedrafita, J., Caja, G. & Varona, L. Analysis of founder-specific inbreeding depression on birth weight in Ripollesa lambs. J. Anim. Sci. 87, 72–79 (2009). · DOI
  46. Charlier, C. et al. Highly effective SNP-based association mapping and management of recessive defects in livestock. Nature Genet. 40, 449–454 (2008). · DOI · Paper page
  47. Vermeulen, C. J., Bijlsma, R. & Loeschcke, V. QTL mapping of inbreeding-related cold sensitivity and conditional lethality in Drosophila melanogaster. J. Evol. Biol. 21, 1236–1244 (2008). · DOI
  48. Kristensen, T. N., Pedersen, K. S., Vermeulen, C. J. & Loeschcke, V. Research on inbreeding in the 'omic' era. Trends Ecol. Evol. 25, 44–52 (2010). An important evaluation of the use of new technologies to understand the genetic basis of inbreeding depression. · DOI
  49. Nielsen, R. Molecular signatures of natural selection. Annu. Rev. Genet. 39, 197–218 (2005). · DOI · Paper page
  50. Garrigan, D. & Hedrick, P. W. Detecting adaptive molecular polymorphism: lessons from the MHC. Evolution 57, 1707–1722 (2003). · DOI · Paper page
  51. Antao, T., Lopes, A., Lopes, R., Beja-Pereira, A. & Luikart, G. LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method. BMC Bioinformatics 9, 323 (2008). · DOI · Paper page
  52. Beaumont, M. A. & Balding, D. J. Identifying adaptive genetic divergence among populations from genome scans. Mol. Ecol. 13, 969–980 (2004). · DOI · Paper page
  53. Beaumont, M. A. & Nichols, R. A. Evaluating loci for use in the genetic analysis of population structure. Proc. R. Soc. Lond. B 263, 1619–1626 (1996). · DOI · Paper page
  54. Foll, M. & Gaggiotti, O. A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180, 977–993 (2008). · DOI · Paper page
  55. Makinen, H. S., Cano, J. M. & Merilä, J. Identifying footprints of directional and balancing selection in marine and freshwater three-spined stickleback (Gasterosteus aculeatus) populations. Mol. Ecol. 17, 3565–3582 (2008). · DOI
  56. Namroud, M.-C., Beaulieu, J., Juge, N., Laroche, J. & Bousquet, J. Scanning the genome for gene single nucleotide polymorphisms involved in adaptive population differentiation in white spruce. Mol. Ecol. 17, 3599–3613 (2008). · DOI
  57. Nielsen, E. E. et al. Genomic signatures of local directional selection in a high gene flow marine organism; the Atlantic cod (Gadus morhua). BMC Evol. Biol. 9, 276 (2009). · DOI
  58. Oetjen, K. & Reusch, T. B. H. Genome scans detect consistent divergent selection among subtidal vs. intertidal populations of the marine angiosperm Zostera marina. Mol. Ecol. 16, 5156–5167 (2007). · DOI
  59. Vasemägi, A., Nilsson, J. & Primmer, C. R. Expressed sequence tag-linked microsatellites as a source of gene-associated polymorphisms for detecting signatures of divergence selection in Atlantic salmon (Salmo salar L.). Mol. Biol. Evol. 22, 1067–1076 (2005). · DOI · Paper page
  60. Hohenlohe, P. A. et al. Population genomic analysis of parallel adaptation in threespine stickleback using sequenced RAD tags. PLoS Genet. 6, e1000862 (2010). One of the first papers to use genomic scans of thousands of markers to understand the genetic basis of adaptation in natural populations. · DOI · Paper page
  61. Wilding, C. S., Butlin, R. K. & Grahame, J. Differential gene exchange between parapatric morphs of Littorina saxatilis detected using AFLP markers. J. Evol. Biol. 14, 611–619 (2001). · DOI · Paper page
  62. Pennings, P. S. & Hermisson, J. Soft sweeps II — molecular population genetics of adaptation from recurrent mutation or migration. Mol. Biol. Evol. 23, 1076–1084 (2006). · DOI · Paper page
  63. Voight, B. F., Kudaravalli, S., Wen, X. & Pritchard, J. K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006). · DOI
  64. Allendorf, F. W. & Hard, J. J. Human-induced evolution caused by unnatural selection through harvest of wild animals. Proc. Natl Acad. Sci. USA 106, 9987–9994 (2009). · DOI · Paper page
  65. Allendorf, F. W., England, P. R., Luikart, G., Ritchie, P. A. & Ryman, N. Genetic effects of harvest on wild animal populations. Trends Ecol. Evol. 23, 327–337 (2008). · DOI
  66. Frankham, R. Where are we in conservation genetics and where do we need to go? Conserv. Genet. 11, 661–663 (2010). · DOI · Paper page
  67. Allendorf, F. W., Leary, R. F., Spruell, P. & Wenburg, J. K. The problems with hybrids: setting conservation guidelines. Trends Ecol. Evol. 16, 613–622 (2001). · DOI · Paper page
  68. Levin, D. A., Franciscoortega, J. & Jansen, R. K. Hybridization and the extinction of rare plant species. Conserv. Biol. 10, 10–16 (1996). · DOI · Paper page
  69. Crandall, K. A., Binindaemonds, O. R. P., Mace, G. M. & Wayne, R. K. Considering evolutionary processes in conservation biology. Trends Ecol. Evol. 15, 290–295 (2000). · DOI
  70. Hedrick, P. W., Parker, K. M. & Lee, R. N. Using microsatellite and MHC variation to identify species, ESUs, and MUs in the endangered Sonoran topminnow. Mol. Ecol. 10, 1399–1412 (2001). · DOI
  71. Bonin, A., Nicole, F., Pompanon, F., Miaud, C. & Taberlet, P. Population adaptive index: a new method to help measure intraspecific genetic diversity and prioritize populations for conservation. Conserv. Biol. 21, 697–708 (2007). · DOI
  72. Hansen, M. M. Expression of interest: transcriptomics and the designation of conservation units. Mol. Ecol. 19, 1757–1759 (2010). · DOI
  73. Tymchuk, W. V., O'Reilly, P., Bittman, J., MacDonald, D. & Schulte, P. Conservation genomics of Atlantic salmon: variation in gene expression between and within regions of the Bay of Fundy. Mol. Ecol. 19, 1842–1859 (2010). · DOI
  74. Cornuet, J.-M., Piry, S., Luikart, G., Estoup, A. & Solignac, M. New methods employing multilocus genotypes for selecting or excluding populations as origins of individuals. Genetics 153, 1989–2000 (1999). · DOI · Paper page
  75. Witherspoon, D. J. et al. Genetic similarities within and between human populations. Genetics 176, 351–359 (2007). · DOI · Paper page
  76. Halbert, N. D. & Derr, J. N. A comprehensive evaluation of cattle introgression into US federal bison herds. J. Hered. 98, 1–12 (2007). · DOI
  77. Allendorf, F. W. et al. Cutthroat trouth hybridization and the U. S. Endangered Species Act: one species, two policies. Conserv. Biol. 19, 1326–1328 (2005). · DOI
  78. Campton, D. E. & Kaeding, L. R. Westslope cutthroat trout, hybridization, and the U. S. Endangered Species Act. Conserv. Biol. 19, 1323–1325 (2005). · DOI
  79. Marris, E. The genome of the American west. Nature 457, 950–952 (2009). · DOI
  80. Payseur, B. A. Using differential introgression in hybrid zones to identify genomic regions involved in speciation. Mol. Ecol. Resour. 10, 806–820 (2010). · DOI
  81. Fitzpatrick, B. M. et al. Rapid spread of invasive genes into a threatened native species. Proc. Natl Acad. Sci. USA 107, 3606–3610 (2010). A fascinating study showing that natural selection can rapidly accelerate the rate of introgression for certain regions of the genome from introduced into native species. · DOI
  82. Edmands, S. Between a rock and a hard place: evaluating the relative risks of inbreeding and outbreeding for conservation and management. Mol. Ecol. 16, 463–475 (2007). · DOI
  83. Shendure, J. & Ji, H. Next-generation DNA sequencing. Nature Biotech. 26, 1135–1145 (2008). · DOI · Paper page
  84. Hoffmann, A. A. & Rieseberg, L. H. Revisiting the impact of inversions in evolution: from population genetic markers to drivers of adaptive shifts and speciation? Annu. Rev. Ecol. Evol. Syst. 39, 21–42 (2008). An important synthesis that evaluates the importance of chromosomal inversions in population genetics and evolution using modern molecular approaches. · DOI · Paper page
  85. Muhlfeld, C. C. et al. Hybridization rapidly reduces fitness of a native trout in the wild. Biol. Lett. 5, 328–331 (2009). · DOI · Paper page
  86. Ljungqvist, M., Åkesson, M. & Hansson, B. Do microsatellites reflect genome-wide genetic diversity in natural populations? A comment on Väli. et al. (2008). Mol. Ecol. 19, 851–855 (2010). · DOI
  87. Miller, W., Wright, S. J., Zhang, Y., Schuster, S. C. & Hayes, V. M. Optimization methods for selecting founder individuals for captive breeding or reintroduction of endangered species. Pac. Symp. Biocomput. 2010, 43–53 (2010).
  88. Blouin, M. S. DNA-based methods for pedigree reconstruction and kinship analysis in natural populations. Trends Ecol. Evol. 18, 503–511 (2003). · DOI · Paper page
  89. Goddard, M. E. & Hayes, B. J. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Rev. Genet. 10, 381–391 (2009). · DOI · Paper page
  90. Lacy, R. C. in Conservation Genetics in the Age of Genomics (eds Amato, G., Ryder, O., Rosenbaum, H. & DeSalle, R.) 58–81 (Columbia Univ. Press, New York, 2009).
  91. Araki, H., Cooper, B. & Blouin, M. S. Genetic effects of captive breeding cause a rapid, cumulative fitness decline in the wild. Science 318, 100–103 (2007). One of the first papers to demonstrate a reduction in fitness in wild populations caused by gene flow from captive populations. · DOI · Paper page
  92. Frankham, R. Genetic adaptation to captivity in species conservation programs. Mol. Ecol. 17, 325–333 (2008). · DOI · Paper page
  93. Schwartz, M. K., Luikart, G. & Waples, R. S. Genetic monitoring as a promising tool for conservation and management. Trends Ecol. Evol. 22, 25–33 (2007). A foundation paper that defined and organized the emerging field of genetic monitoring. · DOI · Paper page
  94. Tallmon, D. A., Luikart, G. & Waples, R. S. The alluring simplicity and complex reality of genetic rescue. Trends Ecol. Evol. 19, 489–496 (2004). · DOI · Paper page
  95. Piertney, S. B. & Oliver, M. K. The evolutionary ecology of the major histocompatibility complex. Heredity 96, 7–21 (2006). · DOI · Paper page
  96. Holmes, G. D., James, E. A. & Hoffmann, A. A. Limitations to reproductive output and genetic rescue in populations of the rare shrub Grevillea repens (Proteaceae). Ann. Bot. 102, 1031–1041 (2008). · DOI
  97. Pogson, G. H. & Fevolden, S. E. Natural selection and the genetic differentiation of coastal and Arctic populations of the Atlantic cod in northern Norway: a test involving nucleotide sequence variation at the pantophysin (PanI) locus. Mol. Ecol. 12, 63–74 (2003). · DOI
  98. Wheat, C. Phosphoglucose isomerase (Pgi) performance and fitness effects among Arthropods and its potential role as an adaptive marker in conservation genetics. Conserv. Genet. 11, 387–397 (2010). · DOI
  99. Barbour, R. C., Forster, L. G., Baker, S. C., Steane, D. A. & Potts, B. M. Biodiversity consequences of genetic variation in bark characteristics within a foundation tree species. Conserv. Biol. 23, 1146–1155 (2009). · DOI
  100. Whitham, T. G. et al. Extending genomics to natural communities and ecosystems. Science 320, 492–495 (2008). · DOI
  101. Crutsinger, G. M. et al. Plant genotypic diversity predicts community structure and governs an ecosystem process. Science 313, 966–968 (2006). · DOI · Paper page
  102. Hodges, E. et al. Genome-wide in situ exon capture for selective resequencing. Nature Genet. 39, 1522–1527 (2007). · DOI · Paper page
  103. Nowrousian, M. Next-generation sequencing techniques for eukaryotic microorganisms: sequencing-based solutions to biological problems. Eukaryot. Cell 2 Jul 2010 (doi:10.1128/EC.00123-10). · DOI
  104. Haussler, D. et al. Genome 10K: a proposal to obtain whole-genome sequence for 10000 vertebrate species. J. Hered. 100, 659–674 (2009). · DOI · Paper page
  105. Bossdorf, O., Richards, C. L. & Pigliucci, M. Epigenetics for ecologists. Ecol. Lett. 11, 106–115 (2008). A valuable consideration of the future application of epigenetics to understanding the ecology of natural populations. · DOI · Paper page
  106. Richards, C. L., Bossdorf, O. & Pigliucci, M. What role does heritable epigenetic variation play in phenotypic evolution? BioScience 60, 232–237 (2010). · DOI
  107. Salmon, A., Ainouche, M. L. & Wendel, J. F. Genetic and epigenetic consequences of recent hybridization and polyploidy in Spartina (Poaceae). Mol. Ecol. 14, 1163–1175 (2005). · DOI · Paper page
  108. Richards, C. L. et al. Plasticity in salt tolerance traits allows for invasion of novel habitat by Japanese knotweed s. l. (Fallopia japonica and F. bohemica, Polygonaceae). Am. J. Bot. 95, 931–942 (2008). · DOI
  109. Allendorf, F. W. & Lundquist, L. L. Introduction: population biology, evolution, and control of invasive species. Conserv. Biol. 17, 24–30 (2003). · DOI
  110. Coulson, T. et al. Estimating individual contributions to population growth: evolutionary fitness in ecological time. Proc. Biol. Sci. 273, 547–555 (2006).
  111. Palsbøll, P. J., Berube, M. & Allendorf, F. W. Identification of management units using population genetic data. Trends Ecol. Evol. 22, 11–16 (2007). · DOI · Paper page
  112. Waples, R. S. Separating the wheat from the chaff: patterns of genetic differentiation in high gene flow species. J. Hered. 89, 438–450 (1998). An important paper that considers how to interpret the low genetic differentiation observed between marine populations that are apparently demographically isolated. · DOI · Paper page
  113. Pampoulie, C. et al. The genetic structure of Atlantic cod (Gadus morhua) around Iceland: insight from microsatellites, the PanI locus, and tagging experiments. Can. J. Fish. Aquat. Sci. 63, 2660–2674 (2006). · DOI
  114. Hemmer-Hansen, J., Nielsen, E. E., Frydenberg, J. & Loeschcke, V. Adaptive divergence in a high gene flow environment: Hsc70 variation in the European flounder (Platichthys flesus L.). Heredity 99, 592–600 (2007). · DOI
  115. Lowe, W. H. & Allendorf, F. W. What can genetics tell us about population connectivity? Mol. Ecol. 19, 3038–3051 (2010). · DOI · Paper page
  116. Waples, R. S. & Gaggiotti, O. What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Mol. Ecol. 15, 1419–1439 (2006). An extremely valuable paper that considers the fundamental problem of defining 'population' in population genetics. · DOI · Paper page
  117. Baird, N. A. et al. Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS ONE 3, e3376 (2008). · DOI · Paper page
  118. Perkel, J. SNP genotyping: six technologies that keyed a revolution. Nature Methods 5, 447–453 (2008). · DOI
  119. Decker, J. E. et al. Resolving the evolution of extant and extinct ruminants with high-throughput phylogenomics. Proc. Natl Acad. Sci. USA 106, 18644–18649 (2009). · DOI · Paper page

Cited by

See all 1,576

Metadata

Authors
Allendorf, F. W., Hohenlohe, P. A., & Luikart, G.
Venue
Nature Reviews Genetics
Publisher
Springer Science and Business Media LLC
Published
2010-09-17
Volume
11
Issue
10
Pages
697-709
ISSN
  • 1471-0056 (ISSN-L)
  • 1471-0064
DOI
10.1038/nrg2844
OpenAlex
W2040057823
Cited by
1,576
References
10
FWCI
4.67
Type
journal article
Language
en
Open access
closed
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Genomics and the future of conservation genetics. https://app.cochat.ai/papers/10.1038/nrg2844
The paper
Allendorf, F. W., Hohenlohe, P. A., & Luikart, G. (2010). Genomics and the future of conservation genetics. Nature Reviews Genetics. https://doi.org/10.1038/nrg2844

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.