The inference of sex-biased human demography from whole-genome data

Autoři: Shaila Musharoff aff001;  Suyash Shringarpure aff001;  Carlos D. Bustmante aff001;  Sohini Ramachandran aff002
Působiště autorů: Department of Genetics, Stanford University, Stanford, CA, USA aff001;  Center for Computational Molecular Biology, Brown University, Providence, RI, USA aff002;  Ecology and Evolutionary Biology, Brown University, Providence, RI, USA aff003
Vyšlo v časopise: The inference of sex-biased human demography from whole-genome data. PLoS Genet 15(9): e32767. doi:10.1371/journal.pgen.1008293
Kategorie: Research Article


Sex-biased demographic events (“sex-bias”) involve unequal numbers of females and males. These events are typically inferred from the relative amount of X-chromosomal to autosomal genetic variation and have led to conflicting conclusions about human demographic history. Though population size changes alter the relative amount of X-chromosomal to autosomal genetic diversity even in the absence of sex-bias, this has generally not been accounted for in sex-bias estimators to date. Here, we present a novel method to identify sex-bias from genetic sequence data that models population size changes and estimates the female fraction of the effective population size during each time epoch. Compared to recent sex-bias inference methods, our approach can detect sex-bias that changes on a single population branch without requiring data from an outgroup or knowledge of divergence events. When applied to simulated data, conventional sex-bias estimators are biased by population size changes, especially recent growth or bottlenecks, while our estimator is unbiased. We next apply our method to high-coverage exome data from the 1000 Genomes Project and estimate a male bias in Yorubans (47% female) and Europeans (43%), possibly due to stronger background selection on the X chromosome than on the autosomes. Finally, we apply our method to the 1000 Genomes Project Phase 3 high-coverage Complete Genomics whole-genome data and estimate a female bias in Yorubans (63% female), Europeans (84%), Punjabis (82%), as well as Peruvians (56%), and a male bias in the Southern Han Chinese (45%). Our method additionally identifies a male-biased migration out of Africa based on data from Europeans (20% female). Our results demonstrate that modeling population size change is necessary to estimate sex-bias parameters accurately. Our approach gives insight into signatures of sex-bias in sexual species, and the demographic models it produces can serve as more accurate null models for tests of selection.

Klíčová slova:

Biology and life sciences – Cell biology – Chromosome biology – Chromosomes – Sex chromosomes – X chromosomes – Autosomes – Population biology – Population metrics – Population size – Evolutionary biology – Genetics – Population genetics – Genetic loci – People and places – Geographical locations – Europe – Research and analysis methods – Simulation and modeling – Mathematical and statistical techniques – Statistical methods – Test statistics – Physical sciences – Mathematics – Statistics


1. Oota H, Settheetham-Ishida W, Tiwawech D, Ishida T, Stoneking M. Human mtDNA and Y-chromosome variation is correlated with matrilocal versus patrilocal residence. Nature genetics. 2001;29(1):20–1. doi: 10.1038/ng711 11528385

2. Verdu P, Becker NSa, Froment A, Georges M, Grugni V, Quintana-Murci L, et al. Sociocultural behavior, sex-biased admixture, and effective population sizes in Central African Pygmies and non-Pygmies. Molecular biology and evolution. 2013;30(4):918–37. doi: 10.1093/molbev/mss328 23300254

3. Ségurel L, Martínez-Cruz B, Quintana-Murci L, Balaresque P, Georges M, Hegay T, et al. Sex-specific genetic structure and social organization in Central Asia: insights from a multi-locus study. PLoS genetics. 2008;4(9):e1000200. doi: 10.1371/journal.pgen.1000200 18818760

4. Cavalli-Sforza LL, Feldman MW. The application of molecular genetic approaches to the study of human evolution. Nature genetics. 2003;33 Suppl:266–75. doi: 10.1038/ng1113 12610536

5. Heyer E, Chaix R, Pavard S, Austerlitz F. Sex-specific demographic behaviours that shape human genomic variation. Molecular ecology. 2011; p. 597–612. doi: 10.1111/j.1365-294X.2011.05406.x 22211311

6. Wilder Ja, Mobasher Z, Hammer MF. Genetic evidence for unequal effective population sizes of human females and males. Molecular biology and evolution. 2004;21(11):2047–57. doi: 10.1093/molbev/msh214

7. Wilder JA, Kingan SSB, Mobasher Z, Pilkington MM, Hammer MF. Global patterns of human mitochondrial DNA and Y-chromosome structure are not influenced by higher migration rates of females versus males. Nature Genetics. 2004;36(10):1122–1125. doi: 10.1038/ng1428 15378061

8. Casto AM, Li JZ, Absher D, Myers R, Ramachandran S, Feldman MW. Characterization of X-linked SNP genotypic variation in globally distributed human populations. Genome biology. 2010;11(1):R10. doi: 10.1186/gb-2010-11-1-r10 20109212

9. Hammer MF, Garrigan D, Wood E, Wilder JA, Mobasher Z, Bigham A, et al. Heterogeneous patterns of variation among multiple human x-linked Loci: the possible role of diversity-reducing selection in non-africans. Genetics. 2004;167(4):1841–53. doi: 10.1534/genetics.103.025361 15342522

10. Gottipati S, Arbiza L, Siepel A, Clark AG, Keinan A. Analyses of X-linked and autosomal genetic variation in population-scale whole genome sequencing. Nature genetics. 2011;43(8):741–3. doi: 10.1038/ng.877 21775991

11. Goldberg A, Rosenberg NA. Beyond 2/3 and 1/3: The complex signatures of sex-biased admixture on the X chromosome. Genetics. 2015;201(1):263–279. doi: 10.1534/genetics.115.178509 26209245

12. Veeramah K, Gutenkunst R. Evidence for increased levels of positive and negative selection on the X chromosome versus autosomes in humans. Molecular Biology and Evolution. 2014;91(9):2267–2282. doi: 10.1093/molbev/msu166

13. Ramachandran S, Rosenberg NA, Zhivotovsky LA, Feldman MW. Robustness of the inference of human population structure: a comparison of X-chromosomal and autosomal microsatellites. Human genomics. 2004;1(2):87–97. 15601537

14. Labuda D, Lefebvre JF, Nadeau P, Roy-Gagnon MH. Female-to-male breeding ratio in modern humans-an analysis based on historical recombinations. American journal of human genetics. 2010;86(3):353–63. 20188344

15. Lohmueller KE, Degenhardt JD, Keinan A. Sex-averaged recombination and mutation rates on the X chromosome: a comment on Labuda et al. American journal of human genetics. 2010;86(6):978–80; author reply 980–1. doi: 10.1016/j.ajhg.2010.03.021 20541048

16. Labuda D, Lefebvre JF, Roy-Gagnon MH. Response to Lohmueller critique. The American Journal of Human Genetics. 2010;86(6):980–981.

17. Pool JE, Nielsen R. Population size changes reshape genomic patterns of diversity. Evolution; international journal of organic evolution. 2007;61(12):3001–6. doi: 10.1111/j.1558-5646.2007.00238.x

18. Hammer MF, Mendez FL, Cox MP, Woerner AE, Wall JD. Sex-biased evolutionary forces shape genomic patterns of human diversity. PLoS genetics. 2008;4(9):e1000202. doi: 10.1371/journal.pgen.1000202 18818765

19. Arbiza L, Gottipati S, Siepel A, Keinan A. Contrasting X-linked and autosomal diversity across 14 human populations. American journal of human genetics. 2014;94(6):827–44. doi: 10.1016/j.ajhg.2014.04.011 24836452

20. Emery LS, Felsenstein J, Akey JM. Estimators of the human effective sex ratio detect sex biases on different timescales. American journal of human genetics. 2010;87(6):848–56. doi: 10.1016/j.ajhg.2010.10.021 21109223

21. Keinan A, Mullikin JC, Patterson N, Reich D. Accelerated genetic drift on chromosome X during the human dispersal out of Africa. Nature genetics. 2009;41(1):66–70. doi: 10.1038/ng.303 19098910

22. Keinan A, Reich D. Can a sex-biased human demography account for the reduced effective population size of chromosome X in non-Africans? Molecular biology and evolution. 2010;27(10):2312–21. doi: 10.1093/molbev/msq117 20453016

23. Clemente F, Gautier M, Vitalis R. Inferring sex-specific demographic history from SNP data. PLoS Genetics. 2018;14(1). doi: 10.1371/journal.pgen.1007191 29385127

24. The 1000 Genomes Project Consortium, Boerwinkle E, Doddapaneni H, Han Y, Korchina V, Kovar C, et al. A global reference for human genetic variation. Nature. 2015;526(7571):68–74. doi: 10.1038/nature15393

25. Bustamante CD, Wakeley J, Sawyer S, Hartl DL. Directional Selection and the Site-Frequency Spectrum. Genetics. 2001;159(4):1779–1788. 11779814

26. Tennessen Ja, Bigham AW, O’Connor TD, Fu W, Kenny EE, Gravel S, et al. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science (New York, NY). 2012;337(6090):64–9. doi: 10.1126/science.1219240

27. 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(10):e1000695. doi: 10.1371/journal.pgen.1000695 19851460

28. Gravel S, Henn BM, Gutenkunst RN, Indap aR, Marth GT, Clark aG, et al. Demographic history and rare allele sharing among human populations. Proceedings of the National Academy of Sciences. 2011. doi: 10.1073/pnas.1019276108

29. Kong A, Frigge ML, Masson G, Besenbacher S, Sulem P, Magnusson G, et al. Rate of de novo mutations and the importance of father’s age to disease risk. Nature. 2012;488(7412):471–475. doi: 10.1038/nature11396 22914163

30. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, et al. The Human Genome Browser at UCSC. Genome Research. 2002;12(6):996–1006. doi: 10.1101/gr.229102 12045153

31. Keinan A, Mullikin JC, Patterson N, Reich D. Measurement of the human allele frequency spectrum demonstrates greater genetic drift in East Asians than in Europeans. Nature genetics. 2007;39(10):1251–5. doi: 10.1038/ng2116 17828266

32. Excoffier L, Foll M. Fastsimcoal: a Continuous-Time Coalescent Simulator of Genomic Diversity Under Arbitrarily Complex Evolutionary Scenarios. Bioinformatics (Oxford, England). 2011;27(9):1332–4. doi: 10.1093/bioinformatics/btr124

33. Miyata T, Hayashida H, Kuma K, Mitsuyasu K, Yasunata T. Male-driven molecular evolution: a model and nucleotide sequence analysis. Cold Spring Harbor Symp on Quan Biol. 1987;52:863–867. doi: 10.1101/SQB.1987.052.01.094

34. Nachman MW, Crowell SL. Estimate of the mutation rate per nucleotide in humans. Genetics. 2000;156(1):297–304. 10978293

35. Hudson RR. Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinformatics (Oxford, England). 2002;18(2):337–8. doi: 10.1093/bioinformatics/18.2.337

36. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w 1118; iso-2; iso-3. Fly. 2012;6(2):80–92. doi: 10.4161/fly.19695 22728672

37. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27(15):2156–2158. doi: 10.1093/bioinformatics/btr330 21653522

38. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MaR, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. American journal of human genetics. 2007;81(3):559–75. doi: 10.1086/519795 17701901

39. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–842. doi: 10.1093/bioinformatics/btq033 20110278

Genetika Reprodukční medicína

Článek vyšel v časopise

PLOS Genetics

2019 Číslo 9

Nejčtenější v tomto čísle

Zvyšte si kvalifikaci online z pohodlí domova

Hypertenze a hypercholesterolémie – synergický efekt léčby
nový kurz
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Multidisciplinární zkušenosti u pacientů s diabetem
Autoři: Prof. MUDr. Martin Haluzík, DrSc., prof. MUDr. Vojtěch Melenovský, CSc., prof. MUDr. Vladimír Tesař, DrSc.

Úloha kombinovaných preparátů v léčbě arteriální hypertenze
Autoři: prof. MUDr. Martin Haluzík, DrSc.

Autoři: MUDr. Ladislav Korábek, CSc., MBA

Terapie roztroušené sklerózy v kostce
Autoři: MUDr. Dominika Šťastná, Ph.D.

Všechny kurzy
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.


Nemáte účet?  Registrujte se