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Introduction to Population Genomics Methods.

Thibault Leroy1,2, Quentin Rougemont3

  • 1Montpellier Institute of Evolutionary Sciences (ISEM), Université de Montpellier, Montpellier, France. thibault.leroy@univie.ac.at.

Methods in Molecular Biology (Clifton, N.J.)
|December 10, 2020
PubMed
Summary
This summary is machine-generated.

This chapter introduces population genomics methods for beginners to analyze genetic diversity data. It covers evolutionary history and selection identification using practical examples and publicly available code.

Keywords:
AdmixtureArtificial and natural selectionBioinformaticsGenome scansMolecular evolutionNucleotide diversityPerseverancePool-seqPopulation structureWhole-genome sequencing

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Area of Science:

  • Evolutionary Biology
  • Genomics
  • Bioinformatics

Background:

  • High-throughput sequencing generates vast genetic data, necessitating advanced informatics and statistical skills for biologists.
  • Understanding evolutionary forces shaping genetic diversity is crucial for plant biology.
  • Population genomics offers tools to analyze these complex datasets.

Purpose of the Study:

  • To introduce population genomics methods to beginners using a practical, hands-on approach.
  • To equip researchers with the skills to analyze sequencing data independently.
  • To explore evolutionary history and identify genes under selection.

Main Methods:

  • Learning-by-doing strategy for data analysis.
  • Re-analysis of case studies using diverse datasets (domesticated rice, oak tree).
  • Utilizing publicly available code for reproducibility.

Main Results:

  • Demonstration of population genomics techniques for evolutionary analysis.
  • Practical insights into analyzing genetic diversity in different species.
  • Successful application of methods to both domesticated and wild plant species.

Conclusions:

  • Population genomics methods are accessible to beginners with practical guidance.
  • Hands-on analysis enhances understanding of evolutionary processes.
  • Open-source code facilitates replication and further research in plant genomics.