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Cited by 95Forensic and Genetic ResearchGenetic diversity and population structureGenetic Associations and Epidemiology

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Sex-Specific Genetic Structure and Social Organization in Central Asia: Insights from a Multi-Locus Study

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Ségurel, Laure, Martínez-Cruz, Begoña, Quintana-Murci, Lluis, Balaresque, Patricia, Georges, Myriam, Hegay, Tatiana, Aldashev, Almaz, Nasyrova, Firuza, Jobling, Mark A., Heyer, Evelyne, Vitalis, Renaud·2008·PLoS Genetics
DOI 10.1371/journal.pgen.1000200PMC PMC2535577
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Abstract

In the last two decades, mitochondrial DNA (mtDNA) and the non-recombining portion of the Y chromosome (NRY) have been extensively used in order to measure the maternally and paternally inherited genetic structure of human populations, and to infer sex-specific demography and history. Most studies converge towards the notion that among populations, women are genetically less structured than men. This has been mainly explained by a higher migration rate of women, due to patrilocality, a tendency for men to stay in their birthplace while women move to their husband's house. Yet, since population differentiation depends upon the product of the effective number of individuals within each deme and the migration rate among demes, differences in male and female effective numbers and sex-biased dispersal have confounding effects on the comparison of genetic structure as measured by uniparentally inherited markers. In this study, we develop a new multi-locus approach to analyze jointly autosomal and X-linked markers in order to aid the understanding of sex-specific contributions to population differentiation. We show that in patrilineal herder groups of Central Asia, in contrast to bilineal agriculturalists, the effective number of women is higher than that of men. We interpret this result, which could not be obtained by the analysis of mtDNA and NRY alone, as the consequence of the social organization of patrilineal populations, in which genetically related men (but not women) tend to cluster together. This study suggests that differences in sex-specific migration rates may not be the only cause of contrasting male and female differentiation in humans, and that differences in effective numbers do matter.

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TL;DR

The paper develops a multi-locus autosomal/X-linked approach to separate sex-biased migration from sex-specific effective numbers in Central Asian populations. It finds that patrilineal herders, unlike bilineal agriculturalists, show a higher effective number of women than men, alongside likely higher female migration.

Key findings

  • In 780 adult men from 21 Central Asian populations, NRY differentiation exceeded mtDNA differentiation, giving female-to-male effective migrant ratios of ≈2.1 for bilineal agriculturalists and ≈21.6 for patrilineal herders.
  • Among patrilineal herders, autosomal differentiation was significantly higher than X-linked differentiation (one-tailed Wilcoxon; p = 0.02), implying Nf/N > 0.55 (Nf > 1.27Nm) and mf > 0.67mm; among bilineal agriculturalists the same test was not significant (p = 0.36).
  • Jackknife analyses were significant in 8 of 11 patrilineal herder groupings, with multi-locus ratios ranging from 1.7 to 3.5; bilineal agriculturalist groupings were non-significant (p > 0.109), with ratios from 0.9 to 1.2.
  • In the HGDP-CEPH worldwide sample, X-linked differentiation was larger than autosomal differentiation, confirming no major male/female demographic difference at that scale; a Pakistani patrilineal subset showed higher autosomal than X-linked differentiation but non-significantly (p = 0.12).

Methods

  • Sampled 780 healthy adult men from 10 bilineal agriculturalist and 11 patrilineal herder populations, representing Tajiks, Kyrgyz, Karakalpaks, Kazaks, and Turkmen; genotyped mtDNA HVS-I and 11 NRY microsatellites in 18 of 21 populations.
  • Genotyped 27 autosomal and 9 X-linked microsatellites in the same individuals, selected using the informativeness for assignment index In.
  • Analyzed genetic differentiation with Weir and Cockerham’s FST, compared autosomal and X-linked FST via Wilcoxon tests under an infinite island model, and evaluated power and robustness with coalescent simulations and jackknife resampling.

Limitations

  • Stated: the approach assumes Wright’s infinite island model—no selection, negligible mutation, equal population sizes, constant migration, and migration–mutation–drift equilibrium; the authors tested for selection and isolation by distance and argue these limits do not undermine the result.
  • Stated: simulations show the method is conservative and likely detects only strong differences in male and female effective numbers for similarly sized datasets.
  • Stated/evident: the authors lack ethnological data to determine the extent of past or present polygyny among herders, and the HGDP-CEPH dataset lacks detailed ethnic information, limiting interpretation of global comparisons.

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Registry

Crossref · 10.1371/journal.pgen.1000200

Cites

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Figures

Figure 1 Geographic map of the sampled area, with the 21 populations studied. Bilineal agriculturalist populations are in blue (Tajiks); Patrilineal herders with a semi-nomadic lifestyle are in red (Kazaks, Karakalpaks, Kyrgyz and Turkmen).
Figure 1 Geographic map of the sampled area, with the 21 populations studied. Bilineal agriculturalist populations are in blue (Tajiks); Patrilineal herders with a semi-nomadic lifestyle are in red (Kazaks, Karakalpaks, Kyrgyz and Turkmen).CC BY · PubMed Central
Figure 2 Diagram representing the relative values of expected genetic differentiation for autosomal markers and for X-linked markers . In the red upper right triangle, the F ST estimates for autosomal markers are higher than for X-linked markers. In this case, N f/N is necessarily larger than 0.5. In the blue region of the figure, the F ST estimates for autosomal markers are lower than for X-linked markers. The white plain line, at which , represents the set of (N f/N, m f/m) values where the autosomal and X-linked F ST estimates are equal. In this case , if N f = N m, then the lower effective size of X-linked markers (which would be three-quarters that of autosomal markers) can only be balanced by a complete female-bias in dispersal (m f/m = 1). Conversely, if m f = m m, the large female fraction of effective numbers compensates exactly the low effective size of X-linked markers only for N f = 7N m. Last, if m f = m m/2, then the autosomal and X-linked F ST estimates can only be equal as the number of males tends towards zero.
Figure 2 Diagram representing the relative values of expected genetic differentiation for autosomal markers and for X-linked markers . In the red upper right triangle, the F ST estimates for autosomal markers are higher than for X-linked markers. In this case, N f/N is necessarily larger than 0.5. In the blue region of the figure, the F ST estimates for autosomal markers are lower than for X-linked markers. The white plain line, at which , represents the set of (N f/N, m f/m) values where the autosomal and X-linked F ST estimates are equal. In this case , if N f = N m, then the lower effective size of X-linked markers (which would be three-quarters that of autosomal markers) can only be balanced by a complete female-bias in dispersal (m f/m = 1). Conversely, if m f = m m, the large female fraction of effective numbers compensates exactly the low effective size of X-linked markers only for N f = 7N m. Last, if m f = m m/2, then the autosomal and X-linked F ST estimates can only be equal as the number of males tends towards zero.CC BY · PubMed Central
Figure 3 p-values of Wilcoxon tests plotted in the (N f/N, m f/m) parameter space. For each set of (N f/N, m f/m) values, we applied the transformation in eq. (4), and tested whether our data on autosomal and X-linked markers were consistent, given the hypothesis defined by the set of (N f/N, m f/m) values. (A) Surface plot of the p-values, as a function of the female fraction of effective number and the female fraction of migration rate, for the herders (11 populations). The arrow indicates the line that separates the region where p≤0.05 from that where p>0.05. Non-significant p-values (p>0.05) correspond to the values of (N f/N, m f/m) that could not be rejected, given our data. (B) Contour plots, for the same data. The dashed line indicates the range of (N f/N, m f/m) values inferred from the ratio of NRY and mtDNA population structure, as obtained from the relationship: . The dotted lines correspond to the cases where N f = N m (vertical line) and m f = m m (horizontal line). (C) and (D) as (A) and (B), respectively, for the agriculturalists (10 populations).
Figure 3 p-values of Wilcoxon tests plotted in the (N f/N, m f/m) parameter space. For each set of (N f/N, m f/m) values, we applied the transformation in eq. (4), and tested whether our data on autosomal and X-linked markers were consistent, given the hypothesis defined by the set of (N f/N, m f/m) values. (A) Surface plot of the p-values, as a function of the female fraction of effective number and the female fraction of migration rate, for the herders (11 populations). The arrow indicates the line that separates the region where p≤0.05 from that where p>0.05. Non-significant p-values (p>0.05) correspond to the values of (N f/N, m f/m) that could not be rejected, given our data. (B) Contour plots, for the same data. The dashed line indicates the range of (N f/N, m f/m) values inferred from the ratio of NRY and mtDNA population structure, as obtained from the relationship: . The dotted lines correspond to the cases where N f = N m (vertical line) and m f = m m (horizontal line). (C) and (D) as (A) and (B), respectively, for the agriculturalists (10 populations).CC BY · PubMed Central
Figure 4 Percentage of significant tests in the (N f/N, m f/m) parameter space, for simulated data. We chose a range of 49 (N f m f/N m m m) ratios, varying from 0.0004 to 2401, and for each of these ratios we chose 29 sets of (N f/N, m f/m) values. By doing this, we obtained 1421 sets of (N f/N, m f/m) values, represented as white dots in the right-hand side panel B, covering the whole parameter space. For each set, we simulated 100 independent datasets using a coalescent-based algorithm, and taking the same number of individuals and the same number of loci for each genetic system as in the observed data. For each dataset, we calculated the p-value for a one-sided Wilcoxon sum rank test , and for each set of (N f/N, m f/m) values we calculated the percentage of significant p-values (at the α = 0.05 level). A. Surface plot of the proportion of significant p-values (at the α = 0.05 level), as a function of the female fraction of effective number and the female fraction of migration rate. B. Contour plot, for the same data. The dotted line, at which , represents the set of (N f/N, m f/m) values where the autosomal and X-linked F ST's are equal. The theory predicts that we should only find in the upper-right triangle defined by the dotted line. Hence, the proportion of significant p-values for any set of (N f/N, m f/m) values in this upper right triangle gives an indication of the power of the method.
Figure 4 Percentage of significant tests in the (N f/N, m f/m) parameter space, for simulated data. We chose a range of 49 (N f m f/N m m m) ratios, varying from 0.0004 to 2401, and for each of these ratios we chose 29 sets of (N f/N, m f/m) values. By doing this, we obtained 1421 sets of (N f/N, m f/m) values, represented as white dots in the right-hand side panel B, covering the whole parameter space. For each set, we simulated 100 independent datasets using a coalescent-based algorithm, and taking the same number of individuals and the same number of loci for each genetic system as in the observed data. For each dataset, we calculated the p-value for a one-sided Wilcoxon sum rank test , and for each set of (N f/N, m f/m) values we calculated the percentage of significant p-values (at the α = 0.05 level). A. Surface plot of the proportion of significant p-values (at the α = 0.05 level), as a function of the female fraction of effective number and the female fraction of migration rate. B. Contour plot, for the same data. The dotted line, at which , represents the set of (N f/N, m f/m) values where the autosomal and X-linked F ST's are equal. The theory predicts that we should only find in the upper-right triangle defined by the dotted line. Hence, the proportion of significant p-values for any set of (N f/N, m f/m) values in this upper right triangle gives an indication of the power of the method.CC BY · PubMed Central

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Citations

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  1. JV Neel, 1970, Lessons from a “primitive” people., Science, 170, 815

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Metadata

Authors
Ségurel, L., Martínez-Cruz, B., Quintana-Murci, L., Balaresque, P., Georges, M., Hegay, T., Aldashev, A., Nasyrova, F., Jobling, M. A., Heyer, E., & Vitalis, R.
Affiliations
  • Centre National de la Recherche Scientifique (FR)
  • University of Leicester (GB)
  • National Center of Cardiology and Internal Medicine (KG)
  • Academy of Sciences of the Republic of Tajikistan (TJ)
Corresponding author
Ségurel, Laure
ORCID
Venue
PLoS Genetics
Publisher
Public Library of Science (PLoS)
Published
2008-09-26
Volume
4
Issue
9
Pages
e1000200
ISSN
  • 1553-7390 (ISSN-L)
  • 1553-7404
DOI
10.1371/journal.pgen.1000200
PMC
PMC2535577
OpenAlex
W2049455202
Semantic Scholar
566e3bf0a229d08da0c47de921c5b378b0a4bbb7
Cited by
95
References
76
Citations by year
2026: 1 · 2025: 2 · 2024: 4 · 2023: 3 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 8 · 2017: 8 · 2016: 2 · 2015: 5 · 2014: 7 · 2013: 7 · 2012: 5
FWCI
5.45
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS Genetics (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • HAL (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Leicester Research Archive (University of Leicester) (submittedVersion, other-oa)
Funders
  • Wellcome Trust (057559/Z/99/B)
  • European Science Foundation
  • Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche
  • Centre National de la Recherche Scientifique
  • Muséum National d'Histoire Naturelle
  • European Social Fund
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
genetic differentiation, Central Asia, sex-biased dispersal, patrilocality, social organization, uniparental markers, multilocus analysis
MeSH terms
Adult, Asia, Central, Computer Simulation, DNA, Mitochondrial, Emigration and Immigration, Female, Genetics, Population, Humans, Male, Population Dynamics, Sex Factors, Social Environment, Microsatellite Repeats, Polymorphism, Single Nucleotide, Chromosomes, Human, Y

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Ségurel, L., Martínez-Cruz, B., Quintana-Murci, L., Balaresque, P., Georges, M., Hegay, T., Aldashev, A., Nasyrova, F., Jobling, M. A., Heyer, E., & Vitalis, R. (2008). Sex-Specific Genetic Structure and Social Organization in Central Asia: Insights from a Multi-Locus Study. PLoS Genetics. https://doi.org/10.1371/journal.pgen.1000200