In This Article Detecting Natural Selection in the Genome

  • Introduction
  • Combined approaches
  • Balancing Selection
  • Local adaptation: Population subdivision and genotype-environment correlations

Evolutionary Biology Detecting Natural Selection in the Genome
by
Joanna Kelley
  • LAST MODIFIED: 30 March 2017
  • DOI: 10.1093/obo/9780199941728-0088

Introduction

Genome-scale data is within our reach for nearly every organism. It is feasible to survey both population and divergence data using high-throughput sequencing technologies, which in turn makes it possible to detect natural selection in the genome without making assumptions about the loci on which selection has acted or is acting. The availability of high-throughput sequence data provides the means to answer important questions about the role of natural selection in the genome. Those questions include the following: (1) how genetic variation is generated and maintained in a population, (2) whether natural selection acts primarily on standing variation or on new mutations, (3) whether adaptation is mutation limited, (4) whether common adaptive evolutionary solutions are repeated in independent locations, (5) what the extent to which local adaptation across parallel environments is due to independent convergence or adaptations shared via migration, and (6) what the relative roles of different classes of genetic variation are, such as mutations in coding regions, regulatory regions, copy number, or chromosomal structure. Moreover, new advances in sampling small tissue amounts, extracting DNA from ancient genomes, and sophisticated experimental setups are pushing our boundaries of knowledge and will revise the way in which we detect natural selection in the genome. Detecting natural selection in the genome is fundamental to understanding how species adapt. The Oxford Bibliography articles “Natural Selection” and “Adaptation” are resources for the reader as background.

Methods for detecting natural selection in the genome

Many forces shape variation in the genome including demographic history as well as natural selection, including negative, positive, and balancing selection. Natural selection may be identified using divergence data, polymorphism data, or a combination of the two. Divergence data is used to identify natural selection between species, whereas polymorphism data is used to identify natural selection within a species. Each method detects selection on a different time scale. Divergence data identifies older selective events, whereas polymorphism data, using either site frequency spectrum or linkage disequilibrium–based data, can be used to identify recent selective events. Moreover, differentiation outlier and genetic–environment association methods can be used to detect local adaptation. The following sections have been split by the approach for detecting selection, which includes divergence-based methods, combined divergence and polymorphism-based methods, and polymorphism-based methods.

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