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Evolutionary GeneticsConcepts, Analysis, and Practice$
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Glenn-Peter Sætre and Mark Ravinet

Print publication date: 2019

Print ISBN-13: 9780198830917

Published to Oxford Scholarship Online: July 2019

DOI: 10.1093/oso/9780198830917.001.0001

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Inferring evolutionary processes from DNA sequence data

Inferring evolutionary processes from DNA sequence data

Chapter:
(p.145) Chapter 7 Inferring evolutionary processes from DNA sequence data
Source:
Evolutionary Genetics
Author(s):

Glenn-Peter Sætre

Mark Ravinet

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198830917.003.0007

The allelic evolutionary genetic models explored so far are applicable to genetic markers. However, DNA sequences harbor a lot of information about the evolutionary past that would be missed if different sequences were simply treated as different alleles. This chapter introduces some important methods and concepts applicable to the analysis of DNA-sequence data. The null models for analyzing sequence data are derived from the neutral theory of molecular evolution. Historically, however, the neutral theory has made a large impact on evolutionary genetics. Therefore, this chapter starts by reviewing its important contribution. Then, important parameters and statistics for analyzing sequence variation are introduced, including a plethora of neutrality tests. The chapter ends with a cautious focus on the powerful tool of genome scan analysis and its utility for identifying regions of the genomes potentially under selection. This includes a section on more recently derived statistics which incorporate information on haplotype structure.

Keywords:   neutral theory, molecular clock, Tajima’s D, coalescent theory, McDonald–Kreitman test, genome scan, sliding window, haplotype statistics

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