Key considerations for measuring allelic expression on a genomic scale using high-throughput sequencing

Authors

  • PIERRE FONTANILLAS,

    1. Department of Ecology and Evolution, University of Lausanne, Le Biophore, CH-1015 Lausanne, Switzerland
    2. Department of Organismic and Evolutionary Biology, Harvard University, 16 Divinity Avenue, Cambridge, MA 01398, USA
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  • CHRISTIAN R. LANDRY,

    1. Department of Organismic and Evolutionary Biology, Harvard University, 16 Divinity Avenue, Cambridge, MA 01398, USA
    2. Département de Biochimie, Université de Montréal, C.P. 6128, Succ. Centre-Ville, Montréal, Québec, Canada
    3. Institut de Biologie Intégrative et des Systèmes (IBIS), Département de Biologie, Université Laval, G1V 0A6, Québec, Canada
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  • PATRICIA J. WITTKOPP,

    1. Department of Ecology and Evolutionary Biology, Department of Molecular, Cellular, and Developmental Biology, University of Michigan, 830 North University Avenue, Ann Arbor, MI 48109, USA
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  • CARSTEN RUSS,

    1. Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA
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  • JONATHAN D. GRUBER,

    1. Department of Ecology and Evolutionary Biology, Department of Molecular, Cellular, and Developmental Biology, University of Michigan, 830 North University Avenue, Ann Arbor, MI 48109, USA
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  • CHAD NUSBAUM,

    1. Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA
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  • DANIEL L. HARTL

    1. Department of Organismic and Evolutionary Biology, Harvard University, 16 Divinity Avenue, Cambridge, MA 01398, USA
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  • Research interests: PF studies gene expression evolution and mechanisms of molecular evolution. CRL studies gene expression regulatory networks and protein-protein interaction networks. PJW studies genetic changes responsible for phenotypic differences within and between species. JDG is exploring fundamental characteristics of gene expression evolution. CN and CR are responsible for development, implementation and application of new sequencing technologies at the Broad Institute. DLH’s research interests include evolutionary genomics, molecular evolution and population genetics.

Pierre Fontanillas, Fax: +41 21 692 4165; E-mail: pierre.fontanillas@unil.ch

Abstract

Differences in gene expression are thought to be an important source of phenotypic diversity, so dissecting the genetic components of natural variation in gene expression is important for understanding the evolutionary mechanisms that lead to adaptation. Gene expression is a complex trait that, in diploid organisms, results from transcription of both maternal and paternal alleles. Directly measuring allelic expression rather than total gene expression offers greater insight into regulatory variation. The recent emergence of high-throughput sequencing offers an unprecedented opportunity to study allelic transcription at a genomic scale for virtually any species. By sequencing transcript pools derived from heterozygous individuals, estimates of allelic expression can be directly obtained. The statistical power of this approach is influenced by the number of transcripts sequenced and the ability to unambiguously assign individual sequence fragments to specific alleles on the basis of transcribed nucleotide polymorphisms. Here, using mathematical modelling and computer simulations, we determine the minimum sequencing depth required to accurately measure relative allelic expression and detect allelic imbalance via high-throughput sequencing under a variety of conditions. We conclude that, within a species, a minimum of 500–1000 sequencing reads per gene are needed to test for allelic imbalance, and consequently, at least five to 10 millions reads are required for studying a genome expressing 10 000 genes. Finally, using 454 sequencing, we illustrate an application of allelic expression by testing for cis-regulatory divergence between closely related Drosophila species.

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