Mutational scans reveal differential evolvability of Drosophila promoters and enhancers

• Published in: Philosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 378; no. 1877; p. 20220054
• Main Authors: Li, Xueying C, Fuqua, Timothy, van Breugel, Maria Elize, Crocker, Justin
• Format: Journal Article
• Language: English
• Published: England The Royal Society 22-05-2023
• Subjects: Animals; Drosophila - genetics; Drosophila melanogaster - genetics; Drosophila melanogaster - metabolism; Drosophila Proteins - genetics; Enhancer Elements, Genetic; Gene Expression Regulation, Developmental; Mutation; Transcription Factors - metabolism; shavenbaby; enhancer; promoter; transcription; Drosophila; cis-regulatory evolution
• ISSN: 0962-8436; 1471-2970
• DOI: 10.1098/rstb.2022.0054

Rapid enhancer and slow promoter evolution have been demonstrated through comparative genomics. However, it is not clear how this information is encoded genetically and if this can be used to place evolution in a predictive context. Part of the challenge is that our understanding of the potential for regulatory evolution is biased primarily toward natural variation or limited experimental perturbations. Here, to explore the evolutionary capacity of promoter variation, we surveyed an unbiased mutation library for three promoters in
. We found that mutations in promoters had limited to no effect on spatial patterns of gene expression. Compared to developmental enhancers, promoters are more robust to mutations and have more access to mutations that can increase gene expression, suggesting that their low activity might be a result of selection. Consistent with these observations, increasing the promoter activity at the endogenous locus of
led to increased transcription yet limited phenotypic changes. Taken together, developmental promoters may encode robust transcriptional outputs allowing evolvability through the integration of diverse developmental enhancers. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.