Inferring Human Population Sizes, Divergence Times and Rates of Gene Flow From Mitochondrial, X and Y Chromosome Resequencing Data

Abstract

We estimate parameters of a general isolation-with-migration model using resequence data from mitochondrial DNA (mtDNA), the Y chromosome, and two loci on the X chromosome in samples of 25–50 individuals from each of 10 human populations. Application of a coalescent-based Markov chain Monte Carlo technique allows simultaneous inference of divergence times, rates of gene flow, as well as changes in effective population size. Results from comparisons between sub-Saharan African and Eurasian populations estimate that 1500 individuals founded the ancestral Eurasian population ∼40 thousand years ago (KYA). Furthermore, these small Eurasian founding populations appear to have grown much more dramatically than either African or Oceanian populations. Analyses of sub-Saharan African populations provide little evidence for a history of population bottlenecks and suggest that they began diverging from one another upward of 50 KYA. We surmise that ancestral African populations had already been geographically structured prior to the founding of ancestral Eurasian populations. African populations are shown to experience low levels of mitochondrial DNA gene flow, but high levels of Y chromosome gene flow. In particular, Y chromosome gene flow appears to be asymmetric, i.e., from the Bantu-speaking population into other African populations. Conversely, mitochondrial gene flow is more extensive between non-African populations, but appears to be absent between European and Asian populations.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 01, 2007
Source ID
10.1534/genetics.107.077495

Entities

People

  • Andrea Novelletto
  • Beverly Strassmann
  • Daniel Garrigan
  • Giovanni Destro-bisol
  • Himla Soodyall
  • Jason A Wilder
  • Jonathan Friedlaender
  • Maya M Pilkington
  • Michael F Hammer
  • Murray P Cox
  • Peter De Knijff
  • Sarah B Kingan

Organizations

  • Australian RL Commission
  • Harvard University
  • Leiden University
  • Santa Fe Institute
  • Sapienza University of Rome
  • Temple University
  • University of Arizona
  • University of Michigan
  • Williams College

Tags

Fields of Study

  • Biology
  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Molecular and genetic basis of cancer.
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference