Detecting Natural Selection in Genomic Data

2013/11/23 by Joseph J. Vitti, Sharon R. Grossman, Pardis C. Sabeti · 733 citations
Biochemistry, Genetics and Molecular Biology · #Artificial intelligence #Biology #Computational biology #Computer science #Data science #Evolution and Genetic Dynamics #Evolutionary biology #Gene #Genetic Associations and Epidemiology #Genetic Mapping and Diversity in Plants and Animals #Genetics #Genome #Genomics #Human evolutionary genetics #Microevolution #Natural selection #Population #Population genomics #Selection (genetic algorithm) #Sociology

paper · open access · doi:10.1146/annurev-genet-111212-133526

published in Annual Review of Genetics 47(1), 97-120 (Annual Reviews)

openalex publication_date 2013/11/23 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/06

Abstract

The past fifty years have seen the development and application of numerous statistical methods to identify genomic regions that appear to be shaped by natural selection. These methods have been used to investigate the macro- and microevolution of a broad range of organisms, including humans. Here, we provide a comprehensive outline of these methods, explaining their conceptual motivations and statistical interpretations. We highlight areas of recent and future development in evolutionary genomics methods and discuss ongoing challenges for researchers employing such tests. In particular, we emphasize the importance of functional follow-up studies to characterize putative selected alleles and the use of selection scans as hypothesis-generating tools for investigating evolutionary histories.

Citations

• Transgenerational Epigenetic Inheritance: Prevalence, Mechanisms, and Implications for the Study of Heredity and Evolution
• The Neutral Theory of Molecular Evolution

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