4.8 Article

The Counteracting Effects of Demography on Functional Genomic Variation: The Roma Paradigm

期刊

MOLECULAR BIOLOGY AND EVOLUTION
卷 38, 期 7, 页码 2804-2817

出版社

OXFORD UNIV PRESS
DOI: 10.1093/molbev/msab070

关键词

demography; admixture; adaptation; exomes; Roma; mutational load

资金

  1. Spanish Ministry of Science, Innovation and Universities (MCIU)
  2. Agencia Estatal de Investigacion (AEI) [CGL2016-75389-P, PID2019-106485GB-I00/AEI/10.13039/501100011033]
  3. Unidad de Excelencia Maria de Maeztu(AEI) [CEX2018-000792-M]
  4. [FPU17/03501]

向作者/读者索取更多资源

The study reveals that the Roma genomes exhibit a long-term balance under the effects of founder effects and gene flow, providing insights into the genetic variation in admixed populations.
Demographic history plays a major role in shaping the distribution of genomic variation. Yet the interaction between different demographic forces and their effects in the genomes is not fully resolved in human populations. Here, we focus on the Roma population, the largest transnational ethnic minority in Europe. They have a South Asian origin and their demographic history is characterized by recent dispersals, multiple founder events, and extensive gene flow from non-Roma groups. Through the analyses of new high-coverage whole exome sequences and genome-wide array data for 89 Iberian Roma individuals together with forward simulations, we show that founder effects have reduced their genetic diversity and proportion of rare variants, gene flow has counteracted the increase in mutational load, runs of homo-zygosity show ancestry-specific patterns of accumulation of deleterious homozygotes, and selection signals primarily derive from preadmixture adaptation in the Roma population sources. The present study shows how two demographic forces, bottlenecks and admixture, act in opposite directions and have long-term balancing effects on the Roma genomes. Understanding how demography and gene flow shape the genome of an admixed population provides an opportunity to elucidate how genomic variation is modeled in human populations.

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