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Population genetic inference from genomic sequence variation

期刊

GENOME RESEARCH
卷 20, 期 3, 页码 291-300

出版社

COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1101/gr.079509.108

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资金

  1. National Institutes of Health (NIH) [F32 HG004182, UO1HL084706]
  2. Human Frontier Science Program [(LT00794/2006-L]
  3. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [U01HL084706] Funding Source: NIH RePORTER
  4. NATIONAL HUMAN GENOME RESEARCH INSTITUTE [F32HG004182, R01HG003229] Funding Source: NIH RePORTER

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Population genetics has evolved from a theory-driven field with little empirical data into a data-driven discipline in which genome-scale data sets test the limits of available models and computational analysis methods. In humans and a few model organisms, analyses of whole-genome sequence polymorphism data are currently under way. And in light of the falling costs of next-generation sequencing technologies, such studies will soon become common in many other organisms as well. Here, we assess the challenges to analyzing whole-genome sequence polymorphism data, and we discuss the potential of these data to yield new insights concerning population history and the genomic prevalence of natural selection.

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