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Genetical Genomics for Evolutionary Studies

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Evolutionary Genomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 856))

Abstract

Genetical genomics combines acquired high-throughput genomic data with genetic analysis. In this chapter, we discuss the application of genetical genomics for evolutionary studies, where new high-throughput molecular technologies are combined with mapping quantitative trait loci (QTL) on the genome in segregating populations.

The recent explosion of high-throughput data—measuring thousands of proteins and metabolites, deep sequencing, chromatin, and methyl-DNA immunoprecipitation—allows the study of the genetic variation underlying quantitative phenotypes, together termed xQTL. At the same time, mining information is not getting easier. To deal with the sheer amount of information, powerful statistical tools are needed to analyze multidimensional relationships. In the context of evolutionary computational biology, a well-designed experiment may help dissect a complex evolutionary trait using proven statistical methods for associating phenotypical variation with genomic locations.

Evolutionary expression QTL (eQTL) studies of the last years focus on gene expression adaptations, mapping the gene expression landscape, and, tentatively, eQTL networks. Here, we discuss the possibility of introducing an evolutionary prior, in the form of gene families displaying evidence of positive selection, and using that in the context of an eQTL experiment for elucidating host–pathogen protein–protein interactions. Through the example of an experimental design, we discuss the choice of xQTL platform, analysis methods, and scope of results. The resulting eQTL can be matched, resulting in putative interacting genes and their regulators. In addition, a prior may help distinguish QTL causality from reactivity, or independence of traits, by creating QTL networks.

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Acknowledgments

The European Commission’s Integrated Project BIOEXPLOIT (FOOD-2005-513959 to GS and PP); the Netherlands Organization for Scientific Research/TTI Green Genetics (1CC029RP to PP); the EU 7th Framework Programme under the Research Project PANACEA (222936 to RJ).

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Authors and Affiliations

  1. Laboratory of Nematology, Wageningen University, Wageningen, The Netherlands

    Pjotr Prins & Geert Smant

  2. Groningen Bioinformatics Centre, University of Groningen, Groningen, The Netherlands

    Pjotr Prins & Ritsert C. Jansen

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  1. Pjotr Prins
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  2. Geert Smant
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  3. Ritsert C. Jansen
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Correspondence to Pjotr Prins .

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Editors and Affiliations

  1. Department of Computer Science, ETH Zürich, Universitätsstr. 6, Zürich, 8092, Switzerland

    Maria Anisimova

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Prins, P., Smant, G., Jansen, R.C. (2012). Genetical Genomics for Evolutionary Studies. In: Anisimova, M. (eds) Evolutionary Genomics. Methods in Molecular Biology, vol 856. Humana Press. https://doi.org/10.1007/978-1-61779-585-5_19

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  • DOI: https://doi.org/10.1007/978-1-61779-585-5_19

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-61779-584-8

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