Combining computational and experimental methods of analyze gene expression divergence by loss of conserved non-coding elements

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A challenging question in evolutionary developmental biology is which genes show a different expression pattern between species. The project described here aims at addressing this question by computational and experimental analyses. There is strong support that highly conserved non-proteincoding elements (CNEs) are often associated with regulation of gene expression. I will conduct a systematic computational search for genomic regions that are highly conserved in many species but lost in another species. Since strong conservation implies function, the underlying hypothesis is that loss of such a CNE leads to changes in the expression pattern of a target gene. This hypothesis will be experimentally tested by (i) verifying a cis-regulatory role for the CNE and (ii) comparing the expression pattern of a gene having the CNE to a gene lacking the CNE. For example, the experiments might reveal that (i) a CNE is a brain-specific transcriptional enhancer and that (ii) the target gene in a species having this CNE is expressed in brain while the target gene in another species lacking this CNE is not expressed in brain. This computational and experimental hybrid approach allows to associate CNE loss with divergence in gene expression. The experiments are preceded by computational analyses of transcription factor binding site clusters aiming at directing the experiments to the spatio-temporal domain where the respective transcription factors are expressed, thus increasing the chance for successful experiments. The goal of this project is to provide insight into the evolution of CNEs, to contribute to our understanding of gene expression regulation by conserved regions and to associate diverged gene expression with lost conserved elements.