Key Considerations for Measuring Allelic Expression on a Genomic Scale Using High-throughput Sequencing

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. A major challenge in evolutionary biology today is understanding the genetic and molecular mechanisms that give rise to phenotypic differences within and between species. Such differences can arise from mutations affecting the function of gene products (i.e. proteins or RNAs) or mutations that affect expression of these genes. Historically, researchers have looked almost exclusively for (and often found) changes in protein coding regions that appeared to contribute to phenotypic evolution; however, during the last decade, there has been a dramatic increase in the number of studies showing that changes affecting gene regulation can also bring about diversity in ecologically relevant traits that affect behaviour, physiology and morphology (e.g. Duda & Remigio 2008; Giger et al. 2008; Voelckel et al