Buffering of Genetic Regulatory Networks in Drosophila melanogaster. Issue 3 (1st July 2016)

• Record Type: Journal Article
• Authors: Fear, Justin M; León-Novelo, Luis G; Morse, Alison M; Gerken, Alison R; Van Lehmann, Kjong; Tower, John; Nuzhdin, Sergey V; McIntyre, Lauren M
• Is Part Of: Genetics. Volume 203:Issue 3(2016)
• Page Start: 1177
• Page End: 1190
• Publication Date: 2016-07-01
• Subjects: transcription -- genetic variation -- cis- or trans-effects -- allele-specific expression -- Drosophila -- regulatory mutations -- purifying selection; Genetics -- Periodicals; 576.5
• DOI: 10.1534/genetics.116.188797
• Languages: English
• ISSNs: 0016-6731

Abstract

Abstract: Regulatory variation in gene expression can be described by cis - and trans -genetic components. Here we used RNA-seq data from a population panel of Drosophila melanogaster test crosses to compare allelic imbalance (AI) in female head tissue between mated and virgin flies, an environmental change known to affect transcription. Indeed, 3048 exons (1610 genes) are differentially expressed in this study. A Bayesian model for AI, with an intersection test, controls type I error. There are ∼200 genes with AI exclusively in mated or virgin flies, indicating an environmental component of expression regulation. On average 34% of genes within a cross and 54% of all genes show evidence for genetic regulation of transcription. Nearly all differentially regulated genes are affected in cis, with an average of 63% of expression variation explained by the cis -effects. Trans -effects explain 8% of the variance in AI on average and the interaction between cis and trans explains an average of 11% of the total variance in AI. In both environments c is - and trans -effects are compensatory in their overall effect, with a negative association between cis - and trans -effects in 85% of the exons examined. We hypothesize that the gene expression level perturbed by cis -regulatory mutations is compensated through trans -regulatory mechanisms, e.g., trans and cis by trans -factors buffering cis -mutations. In addition, when AI is detected in both environments, cis-mated, cis-virgin, and trans-mated–trans-virgin estimates are highly concordant with 99% of all exons positively correlated with a median correlation of 0.83 for cis and 0.95 for trans . We conclude that the gene regulatory networks (GRNs) are robust and that trans -buffering explains robustness.