CISREGVAR · Cis-regulatory variation: Using natural genetic variation to dissect cis-regulatory control of embryonic development.

Embryonic development is very robust: In the midst of segregating mutations and fluctuating environments, a fertilized egg has the remarkable capacity to give rise to a precisely patterned embryo. The stereotypic progression of development is driven by tightly regulated programs of gene expression. However, this deterministic view from genetics is at odds with an emerging view of transcription from genomics as a “noisy” process, variable and changing both within and between individuals. How variable transcriptional programs can regulate robust embryonic development remains a long-standing question, which this proposal aims to address. By combining population genetics, genomics, and developmental genetics in Drosophila we will dissect the relationship between DNA sequence variation, transcription factor (TF) occupancy, and the regulatory control of developmental gene expression.The backdrop for this work is extensive information generated by my lab on the location and function of over 12,000 developmental cis-regulatory elements, including accurate, predictive models of their spatio-temporal activity. To understand the impact of variation on transcription and development, we will make use of a powerful experimental resource – 192 sequenced Drosophila strains, collected from a highly genetically diverse wild population. The proposed research has three Specific Aims: 1) Perform the first high-resolution study associating SNPs and structural variants (eQTLs) with gene expression variation during embryonic development, 2) Quantify in vivo the relationship between cis-regulatory variation, TF occupancy, and gene expression, 3) Incorporate these data into an integrated, predictive model of transcription. These Aims, together with our cis-regulatory data, will offer unique, mechanistic insights into how cis-regulatory variation impacts developmental gene regulation, and into the molecular bases of robustness in developmental regulatory networks.