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Cited by 121Forensic and Genetic ResearchLanguage and cultural evolutionGenetic diversity and population structure

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Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck

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Zeng, Tian Chen, Aw, Alan J., Feldman, Marcus W.·2018·Nature Communications
DOI 10.1038/s41467-018-04375-6PMC PMC5970157
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Abstract

In human populations, changes in genetic variation are driven not only by genetic processes, but can also arise from cultural or social changes. An abrupt population bottleneck specific to human males has been inferred across several Old World (Africa, Europe, Asia) populations 5000–7000 BP. Here, bringing together anthropological theory, recent population genomic studies and mathematical models, we propose a sociocultural hypothesis, involving the formation of patrilineal kin groups and intergroup competition among these groups. Our analysis shows that this sociocultural hypothesis can explain the inference of a population bottleneck. We also show that our hypothesis is consistent with current findings from the archaeogenetics of Old World Eurasia, and is important for conceptions of cultural and social evolution in prehistory.

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TL;DR

The paper proposes that the post-Neolithic Y-chromosome bottleneck (5000–7000 BP) was caused by cultural hitchhiking between Y-chromosomes and patrilineal kin groups under intergroup competition, rather than by demographic collapse alone. Mathematical models and archaeogenetic comparisons support this sociocultural hypothesis.

Key findings

  • Karmin et al. inferred a Y-chromosome bottleneck 5000–7000 BP across the Old World, with male effective population size declining to approximately one-twentieth of its pre-Neolithic level and a 1:17 male-to-female disparity, while mitochondrial DNA indicated a stable or increasing female population.
  • The authors argue three alternatives fail: ecological/climatic sex-specific effects are too small; Neolithic founder effects are contradicted by larger Neolithic precursor populations and greater Y/mt diversity than hunter-gatherers; and intragroup inequality does not track bottleneck timing because the bottleneck lifts as social stratification rises.
  • A modified Lotka–Volterra model shows that two competing male subpopulations sharing a female population drive one male subpopulation to extinction when interpopulation competition dominates intrapopulation competition, corresponding to extinction of a patrilineal descent group.
  • In a computational grid model run for 60 generations (~1.5 millennia) across 18 parameter sets, patrilineal simulations consistently produced large haplogroup diversity losses and dominance by one or a few haplogroups, while non-patrilineal simulations showed few or no extinctions and roughly equal haplogroup representation; archaeogenetic support includes 81% of sampled Bell Beaker males sharing R1b-S116 and nearly all sampled Corded Ware males sharing R1a-M417.

Methods

  • Analytical approach: a modified Lotka–Volterra competition model with two male subpopulations and an exogenous shared female population; the proof is in Supplementary Note 1.
  • Computational approach: a discrete-time grid model with cultural groups as rows and haplogroups as columns, including intergroup killing (Poisson-distributed, with smaller groups suffering higher proportional deaths), mutation, regeneration to constant total population size, group extinction below 20 individuals, and group fission; simulations ran 60 generations with 18 parameter combinations (total population 10,000/20,000/30,000; death rate 15%/25%/50%; patrilineal/non-patrilineal), plus model modifications.
  • Evidence synthesis: the paper compares model outcomes with published Y-chromosome and mtDNA bottleneck findings and archaeogenetic phylogenies; no new primary genetic data were generated, and simulation code is available online.

Limitations

  • Stated: the model’s mutation step changes haplogroup identity rather than real Y-chromosome haplotypes, uses a haplogroup mutation rate much lower than literature Y-haplotype rates, treats patrilineality exogenously, and does not include spatial structure.
  • Stated: the archaeogenetic phylogeny in Fig. 6 is preliminary because most ancient samples were sequenced by hybridization capture, which may miss private mutations and alter inferred coalescence patterns.
  • Evident: the hypothesis is supported by qualitative fit and robustness across simulations rather than a formal statistical test against genetic data, and the authors call for further archaeogenetic sampling and modelling to test it.

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Figures

Fig. 1 Cumulative Bayesian skyline plots of Y-chromosome and mtDNA diversity by world regions. Reprinted from Karmin et al.4 with permission from Monika Karmin and under a Creative Commons License (Attribution-NonCommercial 4.0 International)
Fig. 1 Cumulative Bayesian skyline plots of Y-chromosome and mtDNA diversity by world regions. Reprinted from Karmin et al.4 with permission from Monika Karmin and under a Creative Commons License (Attribution-NonCommercial 4.0 International)CC BY · PubMed Central
Fig. 2 Explosive male-lineage expansions of the last 15,000 years. Each circle represents a phylogenetic node whose branching pattern suggests rapid expansion. The horizontal axis indicates the timings of the expansions, and circle radii reflect growth rates, namely the minimum number of sons per generation, as estimated by a two-phase growth model of Poznik et al.6. Nodes are grouped by continental superpopulation (AFR: African, AMR: admixed American, EAS: East Asian, EUR: European, SAS: South Asian) and coloured by haplogroup. Line segments connect phylogenetically nested lineages. Reprinted from Poznik et al.6 with permission from Carlos D. Bustamante and Nature Publishing Group
Fig. 2 Explosive male-lineage expansions of the last 15,000 years. Each circle represents a phylogenetic node whose branching pattern suggests rapid expansion. The horizontal axis indicates the timings of the expansions, and circle radii reflect growth rates, namely the minimum number of sons per generation, as estimated by a two-phase growth model of Poznik et al.6. Nodes are grouped by continental superpopulation (AFR: African, AMR: admixed American, EAS: East Asian, EUR: European, SAS: South Asian) and coloured by haplogroup. Line segments connect phylogenetically nested lineages. Reprinted from Poznik et al.6 with permission from Carlos D. Bustamante and Nature Publishing GroupCC BY · PubMed Central
Fig. 3 Male-specific Y (MSY) chromosome phylogeny from next-generation sequencing data, and associated demographic reconstruction. a MSY phylogeny based on 456 samples and 35,700 SNPs. Major haplogroups are labelled. The orange box highlights recent expansions identified in several haplogroups, and the yellow box highlights more ancient expansion of deep-rooting lineages. b MSY Bayesian Skyline Plots (of effective population size against time), with different world regions indicated by colours as shown in the key. Reprinted from Batini and Jobling78 with permission from Mark A. Jobling and Springer Science+Business Media
Fig. 3 Male-specific Y (MSY) chromosome phylogeny from next-generation sequencing data, and associated demographic reconstruction. a MSY phylogeny based on 456 samples and 35,700 SNPs. Major haplogroups are labelled. The orange box highlights recent expansions identified in several haplogroups, and the yellow box highlights more ancient expansion of deep-rooting lineages. b MSY Bayesian Skyline Plots (of effective population size against time), with different world regions indicated by colours as shown in the key. Reprinted from Batini and Jobling78 with permission from Mark A. Jobling and Springer Science+Business MediaCC BY · PubMed Central
Fig. 4 Schematic of the steps in the simulation, according to the order described in the algorithm. a (i) Patrilineal (PT) starting conditions, where cultural groups strictly determine haplogroup type. a (ii) The non-patrilineal (NPT) condition where they are perfectly uncorrelated. b The killing step, with a more (PT) and less (NPT) patrilineal starting condition. The number of deaths in each group is inversely related to group size. The blue cultural group goes extinct in both cases. This causes the haplogroup represented by the diamonds to go extinct in PT, but no haplogroup extinction occurs in NPT. c The mutation step, where a small number of individuals in the largest haplogroup change their haplogroup. d The regeneration step, where (i) is a replica of (b) PT (iii), and (d) (ii) shows how the original number of individuals before the killing step is restored by proportionally increasing the number of individuals in all cells. e Group fission step. Where an empty row occurs, the largest cultural group splits, and half the individuals form a new cultural group in the empty row. The step in which we remove cultural groups that are too small—between (c, d) (see Methods)—is not shown
Fig. 4 Schematic of the steps in the simulation, according to the order described in the algorithm. a (i) Patrilineal (PT) starting conditions, where cultural groups strictly determine haplogroup type. a (ii) The non-patrilineal (NPT) condition where they are perfectly uncorrelated. b The killing step, with a more (PT) and less (NPT) patrilineal starting condition. The number of deaths in each group is inversely related to group size. The blue cultural group goes extinct in both cases. This causes the haplogroup represented by the diamonds to go extinct in PT, but no haplogroup extinction occurs in NPT. c The mutation step, where a small number of individuals in the largest haplogroup change their haplogroup. d The regeneration step, where (i) is a replica of (b) PT (iii), and (d) (ii) shows how the original number of individuals before the killing step is restored by proportionally increasing the number of individuals in all cells. e Group fission step. Where an empty row occurs, the largest cultural group splits, and half the individuals form a new cultural group in the empty row. The step in which we remove cultural groups that are too small—between (c, d) (see Methods)—is not shownCC BY · PubMed Central
Fig. 5 Cultural group and haplogroup dynamics in competing completely non-patrilineal groups (NPT) and in competing patrilineal kin groups (PT). These correspond to Figs. 2 and 3 of Supplementary Note 3. There are 100 cultural groups, or ‘tribes,’ each with size 100 at the beginning, and 500 possible haplogroups. Dynamics of the number of distinct cultural groups, cultural group diversity, the number of distinct haplogroups and haplogroup diversity are obtained by averaging over 100 simulation runs (details in Supplementary Note 3). Left panels: a Number of distinct haplogroups. b Haplogroup diversity. c Number of distinct cultural groups. d Cultural group diversity. Each graph consists of 100 pink trajectories representing 100 distinct simulation runs, and one thick solid red trajectory representing the average of the 100 pink trajectories. Black dotted lines representing confidence intervals covering two standard deviations from this mean trajectory. Note that the total number of haplogroups does not increase in this model as each haplogroup-cultural group pair has too few representatives for the mutation step of our algorithm to operate on; this is a methodological artifact and not a significant result. e The mean dynamics of the size of each of the 500 haplogroups over T = 60 generations. f The dynamics of each of the 500 haplogroups for one single run. Right panel: g–j Dynamics for the patrilineal configuration, correspond to a–d of the non-patrilineal configuration. Similarly, k, l correspond to e, f
Fig. 5 Cultural group and haplogroup dynamics in competing completely non-patrilineal groups (NPT) and in competing patrilineal kin groups (PT). These correspond to Figs. 2 and 3 of Supplementary Note 3. There are 100 cultural groups, or ‘tribes,’ each with size 100 at the beginning, and 500 possible haplogroups. Dynamics of the number of distinct cultural groups, cultural group diversity, the number of distinct haplogroups and haplogroup diversity are obtained by averaging over 100 simulation runs (details in Supplementary Note 3). Left panels: a Number of distinct haplogroups. b Haplogroup diversity. c Number of distinct cultural groups. d Cultural group diversity. Each graph consists of 100 pink trajectories representing 100 distinct simulation runs, and one thick solid red trajectory representing the average of the 100 pink trajectories. Black dotted lines representing confidence intervals covering two standard deviations from this mean trajectory. Note that the total number of haplogroups does not increase in this model as each haplogroup-cultural group pair has too few representatives for the mutation step of our algorithm to operate on; this is a methodological artifact and not a significant result. e The mean dynamics of the size of each of the 500 haplogroups over T = 60 generations. f The dynamics of each of the 500 haplogroups for one single run. Right panel: g–j Dynamics for the patrilineal configuration, correspond to a–d of the non-patrilineal configuration. Similarly, k, l correspond to e, fCC BY · PubMed Central
Fig. 6 Tree of Y-chromosome genotypes from samples found among cultures with hunter-gatherer subsistence, and agropastoralist subsistence. The blue background represents hunter-gatherer subsistence while the green background represents agropastoralist subsistence. Letters in red circles match individuals from sites with their archaeological context. Note that R1b-P321 is synonymous with R1b-S116. Adapted from Figs. 3, 4, 5 and 6 of Kivisild67, with addition of information from Olalde et al.64. The vertical axis represents time; the position of branch points represent the ages of branch-defining mutations, with nomenclature and age from yfull (https://www.yfull.com/tree/)
Fig. 6 Tree of Y-chromosome genotypes from samples found among cultures with hunter-gatherer subsistence, and agropastoralist subsistence. The blue background represents hunter-gatherer subsistence while the green background represents agropastoralist subsistence. Letters in red circles match individuals from sites with their archaeological context. Note that R1b-P321 is synonymous with R1b-S116. Adapted from Figs. 3, 4, 5 and 6 of Kivisild67, with addition of information from Olalde et al.64. The vertical axis represents time; the position of branch points represent the ages of branch-defining mutations, with nomenclature and age from yfull (https://www.yfull.com/tree/)CC BY · PubMed Central

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  1. Bellwood, P. S. & Renfrew, C. Examining the Farming/Language Dispersal Hypothesis (McDonald Institute for Archaeological Research, Cambridge, 2002).
  2. Kirch, P. V. The Evolution of the Polynesian Chiefdoms (Cambridge University Press, Cambridge, 1989).
  3. Kristiansen, K. in The World System and the Earth System: Global Socioenvironmental Change and Sustainability Since the Neolithic (ed. Hornborg, A.) 149–162 (Left Coast Press, Walnut Creek, CA, 2007).

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Metadata

Authors
Zeng, T. C., Aw, A. J., & Feldman, M. W.
Affiliations
Stanford University (US)
Corresponding author
Feldman, Marcus W.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2018-05-25
Volume
9
Issue
1
Pages
2077-2077
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-018-04375-6
PMC
PMC5970157
OpenAlex
W2803342971
Semantic Scholar
5bf90c0f141f9c51a91d7d062bbf013d8eaed85e
Cited by
121
References
80
Citations by year
2026: 16 · 2025: 11 · 2024: 10 · 2023: 10 · 2022: 11 · 2021: 39 · 2020: 13 · 2019: 7 · 2018: 4
FWCI
8.27
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Science Foundation (1515127)
  • Center for Computational, Evolutionary and Human Genomics, Stanford University
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
  • Social Sciences › Cultural Studies › Language and cultural evolution
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
Keywords
intergroup competition, archaeogenetics
MeSH terms
Africa, Asia, Computer Simulation, Cultural Characteristics, DNA, Mitochondrial, Europe, Haplotypes, Hierarchy, Social, Humans, Male, Models, Genetic, Population Dynamics, Genetic Variation, Chromosomes, Human, Y

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