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Systems Genetics for Evolutionary Studies.

Pjotr Prins1,2, Geert Smant3, Danny Arends4

  • 1Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht University, CG, Utrecht, The Netherlands. pjotr2018@thebird.nl.

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|July 7, 2019
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Summary
This summary is machine-generated.

Systems genetics integrates high-throughput genomic data with evolutionary studies. This approach uses expression quantitative trait locus (eQTL) analysis to map gene expression adaptations and understand trait evolution.

Keywords:
EvolutionGEMMAGeneNetworkGenetical genomicsGenomicsLMMMetabolomicsNGSNetwork inferenceQTLR-genesR/qtlSystems geneticseQTLxQTL

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Area of Science:

  • Evolutionary biology
  • Genetics
  • Genomics

Background:

  • Systems genetics leverages high-throughput genomic data and genetic analysis.
  • High-throughput molecular technologies combined with quantitative trait locus (QTL) analysis are crucial for evolutionary studies.
  • Analyzing vast amounts of data requires advanced statistical tools to understand genetic variation in phenotypes.

Purpose of the Study:

  • To review and discuss the application of systems genetics in evolutionary studies.
  • To explore how high-throughput data and QTL analysis can dissect complex traits under selection.
  • To discuss the use of evolutionary priors in eQTL experiments for host-pathogen interactions.

Main Methods:

  • Utilizing high-throughput molecular technologies (deep sequencing, mass spectrometry, etc.).
  • Applying quantitative trait locus (QTL) analysis in segregating populations.
  • Employing statistical methods to associate phenotypic variation with chromosomal locations and analyze multidimensional relationships.

Main Results:

  • Recent evolutionary expression QTL (eQTL) studies focus on mapping gene expression adaptations.
  • eQTL networks of transcripts and proteins are being defined.
  • The potential to use evolutionary priors, like gene families under positive selection, in eQTL experiments is discussed.

Conclusions:

  • Systems genetics provides powerful tools for dissecting the genetic basis of complex traits in an evolutionary context.
  • eQTL analysis is instrumental in understanding gene expression evolution and network dynamics.
  • Integrating evolutionary information can enhance the elucidation of molecular mechanisms, such as host-pathogen interactions.