Demographic history shaped geographical patterns of deleterious mutation load in a broadly distributed Pacific Salmon
Autoři:
Quentin Rougemont aff001; Jean-Sébastien Moore aff001; Thibault Leroy aff002; Eric Normandeau aff001; Eric B. Rondeau aff004; Ruth E. Withler aff006; Donald M. Van Doornik aff007; Penelope A. Crane aff008; Kerry A. Naish aff009; John Carlos Garza aff010; Terry D. Beacham aff006; Ben F. Koop aff004; Louis Bernatchez aff001
Působiště autorů:
Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Québec, Canada
aff001; ISEM, Univ. Montpellier, CNRS, EPHE, IRD, Montpellier, France
aff002; Department of Botany & Biodiversity Research, University of Vienna, Vienna, Austria
aff003; Centre for Biomedical Research, University of Victoria, Victoria, BC, Canada
aff004; Department of Biology, University of Victoria, Victoria, BC, Canada
aff005; Department of Fisheries and Ocean, Pacific Biological Station, Nanaimo, British Columbia, Canada
aff006; National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Northwest Fisheries Science Center, Manchester Research Station, Port Orchard, Washington, United States of America
aff007; Conservation Genetics Laboratory, U.S. Fish and Wildlife Service, Anchorage, Alaska, United States of America
aff008; School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, United States of America
aff009; Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service and Institute of Marine Sciences, University of California–Santa Cruz, Santa Cruz, California, United States of America
aff010
Vyšlo v časopise:
Demographic history shaped geographical patterns of deleterious mutation load in a broadly distributed Pacific Salmon. PLoS Genet 16(8): e32767. doi:10.1371/journal.pgen.1008348
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1008348
Souhrn
A thorough reconstruction of historical processes is essential for a comprehensive understanding of the mechanisms shaping patterns of genetic diversity. Indeed, past and current conditions influencing effective population size have important evolutionary implications for the efficacy of selection, increased accumulation of deleterious mutations, and loss of adaptive potential. Here, we gather extensive genome-wide data that represent the extant diversity of the Coho salmon (Oncorhynchus kisutch) to address two objectives. We demonstrate that a single glacial refugium is the source of most of the present-day genetic diversity, with detectable inputs from a putative secondary micro-refugium. We found statistical support for a scenario whereby ancestral populations located south of the ice sheets expanded recently, swamping out most of the diversity from other putative micro-refugia. Demographic inferences revealed that genetic diversity was also affected by linked selection in large parts of the genome. Moreover, we demonstrate that the recent demographic history of this species generated regional differences in the load of deleterious mutations among populations, a finding that mirrors recent results from human populations and provides increased support for models of expansion load. We propose that insights from these historical inferences should be better integrated in conservation planning of wild organisms, which currently focuses largely on neutral genetic diversity and local adaptation, with the role of potentially maladaptive variation being generally ignored.
Klíčová slova:
California – Deletion mutation – Effective population size – Gene flow – Genomics – Phylogeography – Population genetics – Species diversity
Zdroje
1. Provan J, Bennett KD. Phylogeographic insights into cryptic glacial refugia. Trends Ecol Evol (Amst). 2008;23: 564–571. doi: 10.1016/j.tree.2008.06.010 18722689
2. Hewitt GM. Post-glacial re-colonization of European biota. Biological Journal of the Linnean Society. 1999;68: 87–112. doi: 10.1006/bijl.1999.0332
3. Hewitt GM. Genetic consequences of climatic oscillations in the Quaternary. Philos Trans R Soc Lond, B, Biol Sci. 2004;359: 183–195; discussion 195. doi: 10.1098/rstb.2003.1388 15101575
4. Bernatchez L, Wilson CC. Comparative phylogeography of Nearctic and Palearctic fishes. Molecular Ecology. 1998;7: 431–452. doi: 10.1046/j.1365-294x.1998.00319.x
5. Frankham R, Ballou JD, Briscoe DA. Introduction to Conservation Genetics by Richard Frankham. In: Cambridge Core [Internet]. Jan 2010 [cited 2 Jul 2019]. doi: 10.1017/CBO9780511809002
6. Funk WC, McKay JK, Hohenlohe PA, Allendorf FW. Harnessing genomics for delineating conservation units. Trends in Ecology & Evolution. 2012;27: 489–496. doi: 10.1016/j.tree.2012.05.012 22727017
7. Simons YB, Turchin MC, Pritchard JK, Sella G. The deleterious mutation load is insensitive to recent population history. Nature Genetics. 2014;46: 220–224. doi: 10.1038/ng.2896 24509481
8. Kirkpatrick M, Jarne P. The Effects of a Bottleneck on Inbreeding Depression and the Genetic Load. Am Nat. 2000;155: 154–167. doi: 10.1086/303312 10686158
9. Simons YB, Sella G. The impact of recent population history on the deleterious mutation load in humans and close evolutionary relatives. Curr Opin Genet Dev. 2016;41: 150–158. doi: 10.1016/j.gde.2016.09.006 27744216
10. Bierne N, Gagnaire P-A, David P. The geography of introgression in a patchy environment and the thorn in the side of ecological speciation. Curr Zool. 2013;59: 72–86. doi: 10.1093/czoolo/59.1.72
11. Barton N, Bengtsson BO. The barrier to genetic exchange between hybridising populations. Heredity. 1986;57: 357. doi: 10.1038/hdy.1986.135 3804765
12. Cruickshank TE, Hahn MW. Reanalysis suggests that genomic islands of speciation are due to reduced diversity, not reduced gene flow. Mol Ecol. 2014;23: 3133–3157. doi: 10.1111/mec.12796 24845075
13. Noor M a. F, Bennett SM. Islands of speciation or mirages in the desert? Examining the role of restricted recombination in maintaining species. Heredity (Edinb). 2009;103: 439–444. doi: 10.1038/hdy.2009.151 19920849
14. Charlesworth B. The Effects of Deleterious Mutations on Evolution at Linked Sites. Genetics. 2012;190: 5–22. doi: 10.1534/genetics.111.134288 22219506
15. Charlesworth B, Morgan MT, Charlesworth D. The effect of deleterious mutations on neutral molecular variation. Genetics. 1993;134: 1289–1303. 8375663
16. Pouyet F, Aeschbacher S, Thiéry A, Excoffier L. Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences. Veeramah K, Wittkopp PJ, Gronau I, editors. eLife. 2018;7: e36317. doi: 10.7554/eLife.36317 30125248
17. Roux C, Fraïsse C, Romiguier J, Anciaux Y, Galtier N, Bierne N. Shedding Light on the Grey Zone of Speciation along a Continuum of Genomic Divergence. PLOS Biology. 2016;14: e2000234. doi: 10.1371/journal.pbio.2000234 28027292
18. Comeron JM. Background selection as null hypothesis in population genomics: insights and challenges from Drosophila studies. Philos Trans R Soc Lond, B, Biol Sci. 2017;372. doi: 10.1098/rstb.2016.0471 29109230
19. Charlesworth D, Willis JH. The genetics of inbreeding depression. Nat Rev Genet. 2009;10: 783–796. doi: 10.1038/nrg2664 19834483
20. Kyriazis C, Wayne RK, Lohmueller KE. High genetic diversity can contribute to extinction in small populations | bioRxiv. [cited 10 Mar 2020]. Available: https://www.biorxiv.org/content/10.1101/678524v1
21. Robinson JA, Räikkönen J, Vucetich LM, Vucetich JA, Peterson RO, Lohmueller KE, et al. Genomic signatures of extensive inbreeding in Isle Royale wolves, a population on the threshold of extinction. Sci Adv. 2019;5: eaau0757. doi: 10.1126/sciadv.aau0757 31149628
22. Robinson JA, Ortega-Del Vecchyo D, Fan Z, Kim BY, vonHoldt BM, Marsden CD, et al. Genomic Flatlining in the Endangered Island Fox. Curr Biol. 2016;26: 1183–1189. doi: 10.1016/j.cub.2016.02.062 27112291
23. Abascal F, Corvelo A, Cruz F, Villanueva-Cañas JL, Vlasova A, Marcet-Houben M, et al. Extreme genomic erosion after recurrent demographic bottlenecks in the highly endangered Iberian lynx. Genome Biol. 2016;17: 251. doi: 10.1186/s13059-016-1090-1 27964752
24. Dobrynin P, Liu S, Tamazian G, Xiong Z, Yurchenko AA, Krasheninnikova K, et al. Genomic legacy of the African cheetah, Acinonyx jubatus. Genome Biol. 2015;16: 277. doi: 10.1186/s13059-015-0837-4 26653294
25. Yang Y, Ma T, Wang Z, Lu Z, Li Y, Fu C, et al. Genomic effects of population collapse in a critically endangered ironwood tree Ostrya rehderiana. Nat Commun. 2018;9: 5449. doi: 10.1038/s41467-018-07913-4 30575743
26. Xue Y, Prado-Martinez J, Sudmant PH, Narasimhan V, Ayub Q, Szpak M, et al. Mountain gorilla genomes reveal the impact of long-term population decline and inbreeding. Science. 2015;348: 242–245. doi: 10.1126/science.aaa3952 25859046
27. Grossen C, Guillaume F, Keller LF, Croll D. Accumulation and purging of deleterious mutations through severe bottlenecks in ibex. bioRxiv. 2019; 605147. doi: 10.1101/605147
28. Henn BM, Botigué LR, Peischl S, Dupanloup I, Lipatov M, Maples BK, et al. Distance from sub-Saharan Africa predicts mutational load in diverse human genomes. PNAS. 2016;113: E440–E449. doi: 10.1073/pnas.1510805112 26712023
29. Henn BM, Botigué LR, Bustamante CD, Clark AG, Gravel S. Estimating the mutation load in human genomes. Nat Rev Genet. 2015;16: 333–343. doi: 10.1038/nrg3931 25963372
30. Krkosek M, Ford JS, Morton A, Lele S, Myers RA, Lewis MA. Declining wild salmon populations in relation to parasites from farm salmon. Science. 2007;318: 1772–1775. doi: 10.1126/science.1148744 18079401
31. Irvine JR, Fukuwaka M. Pacific salmon abundance trends and climate change. ICES J Mar Sci. 2011;68: 1122–1130. doi: 10.1093/icesjms/fsq199
32. Gustafson RG, Waples RS, Myers JM, Weitkamp LA, Bryant GJ, Johnson OW, et al. Pacific Salmon Extinctions: Quantifying Lost and Remaining Diversity. Conservation Biology. 2007;21: 1009–1020. doi: 10.1111/j.1523-1739.2007.00693.x 17650251
33. Smith CT, Nelson RJ, Wood CC, Koop BF. Glacial biogeography of North American coho salmon (Oncorhynchus kisutch). Mol Ecol. 2001;10: 2775–2785. doi: 10.1046/j.1365-294x.2001.t01-1-01405.x 11903891
34. Beacham TD, Wetklo M, Deng L, MacConnachie C. Coho Salmon Population Structure in North America Determined from Microsatellites. Transactions of the American Fisheries Society. 2011;140: 253–270. doi: 10.1080/00028487.2011.558782
35. McPhail JD, Lindsey CC. Freshwater fishes of northwestern Canada and Alaska. Fisheries Research Board of Canada: available by mail from the Queen’s Printer; 1970.
36. UBC Press | Pacific Salmon Life Histories, By Cornelis Groot, Leo Margolis and Leo Margolis. In: UBC Press [Internet]. [cited 1 Jul 2019]. Available: https://www.ubcpress.ca/pacific-salmon-life-histories
37. Hocutt CH, Wiley EO, editors. The Zoogeography of North American Freshwater Fishes. 1 edition. New York: Wiley-Interscience; 1986.
38. Mee JA, Moore J-S. The ecological and evolutionary implications of microrefugia. Journal of Biogeography. 2014;41: 837–841. doi: 10.1111/jbi.12254
39. Warner BG, Mathewes RW, Clague JJ. Ice-free conditions on the queen charlotte islands, british columbia, at the height of late wisconsin glaciation. Science. 1982;218: 675–677. doi: 10.1126/science.218.4573.675 17791586
40. Li JZ, Devin AM, Tang H, Southwick AM, Casto AM, Ramachandran S, et al. Worldwide Human Relationships Inferred from Genome-Wide Patterns of Variation. Science. 2008;319: 1100–1104. doi: 10.1126/science.1153717 18292342
41. Petit RJ, Aguinagalde I, Beaulieu J-L de, Bittkau C, Brewer S, Cheddadi R, et al. Glacial Refugia: Hotspots But Not Melting Pots of Genetic Diversity. Science. 2003;300: 1563–1565. doi: 10.1126/science.1083264 12791991
42. Weir BS, Goudet J. A Unified Characterization of Population Structure and Relatedness. Genetics. 2017;206: 2085–2103. doi: 10.1534/genetics.116.198424 28550018
43. Cubry P, Vigouroux Y, François O. The Empirical Distribution of Singletons for Geographic Samples of DNA Sequences. Front Genet. 2017;8. doi: 10.3389/fgene.2017.00139 29033977
44. Gilbert-Horvath EA, Pipal KA, Spence BC, Williams TH, Garza JC. Hierarchical Phylogeographic Structure of Coho Salmon in California. Transactions of the American Fisheries Society. 2016;145: 1122–1138. doi: 10.1080/00028487.2016.1201003
45. Williams TH, Lindley ST, Spence BC, Boughton DA. STATUS REVIEW UPDATE FOR PACIFIC SALMON AND STEELHEAD LISTED UNDER THE ENDANGERED SPECIES ACT: SOUTHWEST.: 106.
46. Weir BS, Cockerham CC. Estimating F-Statistics for the Analysis of Population Structure. Evolution. 1984;38: 1358–1370. doi: 10.1111/j.1558-5646.1984.tb05657.x 28563791
47. Ward RD, Woodwark M, Skibinski DOF. A comparison of genetic diversity levels in marine, freshwater, and anadromous fishes. Journal of Fish Biology. 1994;44: 213–232. doi: 10.1111/j.1095-8649.1994.tb01200.x
48. Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet. 2006;2: e190. doi: 10.1371/journal.pgen.0020190 17194218
49. Novembre J, Stephens M. Interpreting principal component analyses of spatial population genetic variation. Nat Genet. 2008;40: 646–649. doi: 10.1038/ng.139 18425127
50. Frichot E, François O. LEA: An R package for landscape and ecological association studies. Methods in Ecology and Evolution. 2015;6: 925–929. doi: 10.1111/2041-210X.12382
51. Meirmans PG. The trouble with isolation by distance. Mol Ecol. 2012;21: 2839–2846. doi: 10.1111/j.1365-294X.2012.05578.x 22574758
52. Pickrell JK, Pritchard JK. Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data. PLOS Genetics. 2012;8: e1002967. doi: 10.1371/journal.pgen.1002967 23166502
53. Gutenkunst RN, Hernandez RD, Williamson SH, Bustamante CD. Inferring the Joint Demographic History of Multiple Populations from Multidimensional SNP Frequency Data. PLOS Genetics. 2009;5: e1000695. doi: 10.1371/journal.pgen.1000695 19851460
54. Excoffier L, Dupanloup I, Huerta-Sánchez E, Sousa VC, Foll M. Robust Demographic Inference from Genomic and SNP Data. PLOS Genetics. 2013;9: e1003905. doi: 10.1371/journal.pgen.1003905 24204310
55. Nicolas Alcala, Vuilleumier Séverine. Turnover and accumulation of genetic diversity across large time-scale cycles of isolation and connection of populations. Proceedings of the Royal Society B: Biological Sciences. 2014;281: 20141369. doi: 10.1098/rspb.2014.1369 25253456
56. COSEWIC assessment and status report on the coho salmon Oncorhynchus kisutch (Interior Fraser population) in Canada—Species at Risk Public Registry. [cited 1 Jul 2019]. Available: https://wildlife-species.canada.ca/species-risk-registry/document/default_e.cfm?documentID=105
57. J. Wang, Personal Communication.
58. Lapierre M, Lambert A, Achaz G. Accuracy of Demographic Inferences from the Site Frequency Spectrum: The Case of the Yoruba Population. Genetics. 2017;206: 439–449. doi: 10.1534/genetics.116.192708 28341655
59. Baharian S, Gravel S. On the decidability of population size histories from finite allele frequency spectra. Theoretical Population Biology. 2018;120: 42–51. doi: 10.1016/j.tpb.2017.12.008 29305873
60. Terhorst J, Song YS. Fundamental limits on the accuracy of demographic inference based on the sample frequency spectrum. PNAS. 2015;112: 7677–7682. doi: 10.1073/pnas.1503717112 26056264
61. Quinn TP. Homing and Straying in Pacific Salmon. In: McCleave JD, Arnold GP, Dodson JJ, Neill WH, editors. Mechanisms of Migration in Fishes. Boston, MA: Springer US; 1984. pp. 357–362. doi: 10.1007/978-1-4613-2763-9_21
62. Ewing GB, Jensen JD. The consequences of not accounting for background selection in demographic inference. Molecular Ecology. 2016;25: 135–141. doi: 10.1111/mec.13390 26394805
63. McVean G, Awadalla P, Fearnhead P. A Coalescent-Based Method for Detecting and Estimating Recombination From Gene Sequences. Genetics. 2002;160: 1231–1241. 11901136
64. data available on github at https://github.com/QuentinRougemont/coho_salmon_recomb/
65. Peischl S, Dupanloup I, Kirkpatrick M, Excoffier L. On the accumulation of deleterious mutations during range expansions. Molecular Ecology. 2013;22: 5972–5982. doi: 10.1111/mec.12524 24102784
66. Peischl S, Dupanloup I, Foucal A, Jomphe M, Bruat V, Grenier J-C, et al. Relaxed Selection During a Recent Human Expansion. Genetics. 2018;208: 763–777. doi: 10.1534/genetics.117.300551 29187508
67. Peischl S, Excoffier L. Expansion load: recessive mutations and the role of standing genetic variation. Molecular Ecology. 2015;24: 2084–2094. doi: 10.1111/mec.13154 25786336
68. Chen J, Glémin S, Lascoux M. Genetic Diversity and the Efficacy of Purifying Selection across Plant and Animal Species, Molecular Biology and Evolution, 2017, 34;6,1417–1428, doi: 10.1093/molbev/msx088 28333215
69. Kim BY, Huber CD, Lohmueller KE. Deleterious variation shapes the genomic landscape of introgression. PLOS Genetics. 2018;14: e1007741. doi: 10.1371/journal.pgen.1007741 30346959
70. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the functional effect of amino acid substitutions and indels. PLoS ONE. 2012;7: e46688. doi: 10.1371/journal.pone.0046688 23056405
71. Christensen KA, Leong JS, Sakhrani D, Biagi CA, Minkley DR, Withler RE, et al. Chinook salmon (Oncorhynchus tshawytscha) genome and transcriptome. PLOS ONE. 2018;13: e0195461. doi: 10.1371/journal.pone.0195461 29621340
72. Yáñez JM, Naswa S, López ME, Bassini L, Correa K, Gilbey J, et al. Genomewide single nucleotide polymorphism discovery in Atlantic salmon (Salmo salar): validation in wild and farmed American and European populations. Mol Ecol Resour. 2016;16: 1002–1011. doi: 10.1111/1755-0998.12503 26849107
73. Zhou Y, Massonnet M, Sanjak JS, Cantu D, Gaut BS. Evolutionary genomics of grape (Vitis vinifera ssp. vinifera) domestication. PNAS. 2017;114: 11715–11720. doi: 10.1073/pnas.1709257114 29042518
74. Nevado B, Wong ELY, Osborne OG, Filatov DA. Adaptive Evolution Is Common in Rapid Evolutionary Radiations. Current Biology. 2019;29: 3081–3086.e5. doi: 10.1016/j.cub.2019.07.059 31495580
75. Willi Y, Fracassetti M, Zoller S, Van Buskirk J. Accumulation of Mutational Load at the Edges of a Species Range. Mol Biol Evol. 2018;35: 781–791. doi: 10.1093/molbev/msy003 29346601
76. González-Martínez SC, Ridout K, Pannell JR. Range Expansion Compromises Adaptive Evolution in an Outcrossing Plant. Current Biology. 2017;27: 2544–2551.e4. doi: 10.1016/j.cub.2017.07.007 28803874
77. Bosshard L, Dupanloup I, Tenaillon O, Bruggmann R, Ackermann M, Peischl S, et al. Accumulation of Deleterious Mutations During Bacterial Range Expansions. Genetics. 2017;207: 669–684. doi: 10.1534/genetics.117.300144 28821588
78. Lohmueller KE. The distribution of deleterious genetic variation in human populations. Curr Opin Genet Dev. 2014;29: 139–146. doi: 10.1016/j.gde.2014.09.005 25461617
79. Moore J-S, Harris LN, Le Luyer J, Sutherland BJG, Rougemont Q, Tallman RF, et al. Genomics and telemetry suggest a role for migration harshness in determining overwintering habitat choice, but not gene flow, in anadromous Arctic Char. Mol Ecol. 2017;26: 6784–6800. doi: 10.1111/mec.14393 29087005
80. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:13033997 [q-bio]. 2013 [cited 3 Jul 2019]. Available: http://arxiv.org/abs/1303.3997
81. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25: 2078–2079. doi: 10.1093/bioinformatics/btp352 19505943
82. Catchen JM, Amores A, Hohenlohe P, Cresko W, Postlethwait JH. Stacks: Building and Genotyping Loci De Novo From Short-Read Sequences. G3: Genes, Genomes, Genetics. 2011;1: 171–182. doi: 10.1534/g3.111.000240 22384329
83. Korneliussen TS, Albrechtsen A, Nielsen R. ANGSD: Analysis of Next Generation Sequencing Data. BMC Bioinformatics. 2014;15: 356. doi: 10.1186/s12859-014-0356-4 25420514
84. Warmuth VM, Ellegren H. Genotype-free estimation of allele frequencies reduces bias and improves demographic inference from RADSeq data. Molecular Ecology Resources. 2019;19: 586–596. doi: 10.1111/1755-0998.12990 30633448
85. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27: 2156–2158. doi: 10.1093/bioinformatics/btr330 21653522
86. Goudet J. hierfstat, a package for r to compute and test hierarchical F-statistics. Molecular Ecology Notes. 2005;5: 184–186. doi: 10.1111/j.1471-8286.2004.00828.x
87. Benjamini Y., and Hochberg Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. _Journal of the Royal Statistical Society Series B, *57*, 289–300. <URL: http://www.jstor.org/stable/2346101>.
88. Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 2009;19: 1655–1664. doi: 10.1101/gr.094052.109 19648217
89. Dray S, Dufour A (2007). “The ade4 Package: Implementing the Duality Diagram for Ecologists.” Journal of Statistical Software, 22(4), 1–20. doi: 10.18637/jss.v022.i04
90. Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag; 2009. Available: https://www.springer.com/gp/book/9780387981413
91. Rougemont Q, Gagnaire P-A, Perrier C, Genthon C, Besnard A-L, Launey S, et al. Inferring the demographic history underlying parallel genomic divergence among pairs of parasitic and nonparasitic lamprey ecotypes. Molecular Ecology. 2017;26: 142–162. doi: 10.1111/mec.13664 27105132
92. Hudson RR. Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinformatics. 2002;18: 337–338. doi: 10.1093/bioinformatics/18.2.337 11847089
93. Leroy T, Anselmetti A, Tilak MK, Bérard S, Csukonyi L, Gabrielli M, Scornavacca C, Milá B, Thébaud C and Nabholz B. A bird’s white-eye view on neo-sex chromosome evolution. bioRxiv. 2019; 505610, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/505610
94. Government of Canada NRC. GEOSCAN Search Results: Fastlink [Internet]. 7 Dec 2015 [cited 26 Jul 2019]. Available: https://geoscan.nrcan.gc.ca/starweb/geoscan/servlet.starweb?path=geoscan/fulle.web&search1=R=214399
95. https://www.naturalearthdata.com/downloads/10m-physical-vectors/ last access 10-05-2020.
96. Clark PU, Dyke AS, Shakun JD, Carlson AE, Clark J, Wohlfarth B, et al. The Last Glacial Maximum. Science. 2009;325: 710–714. doi: 10.1126/science.1172873 19661421
97. Elias SA, Brigham-Grette J. GLACIATIONS | Late Pleistocene Events in Beringia. In: Elias SA, editor. Encyclopedia of Quaternary Science. Oxford: Elsevier; 2007. pp. 1057–1066. doi: 10.1016/B0-44-452747-8/00132-0
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 8
- Může hubnutí souviset s vyšším rizikem nádorových onemocnění?
- Polibek, který mi „vzal nohy“ aneb vzácný výskyt EBV u 70leté ženy – kazuistika
- AI může chirurgům poskytnout cenná data i zpětnou vazbu v reálném čase
- Antibiotika na nachlazení nezabírají! Jak můžeme zpomalit šíření rezistence?
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
Nejčtenější v tomto čísle
- Genomic imprinting: An epigenetic regulatory system
- Uptake of exogenous serine is important to maintain sphingolipid homeostasis in Saccharomyces cerevisiae
- A human-specific VNTR in the TRIB3 promoter causes gene expression variation between individuals
- Immediate activation of chemosensory neuron gene expression by bacterial metabolites is selectively induced by distinct cyclic GMP-dependent pathways in Caenorhabditis elegans