Analysis of transcription factor binding at cis-regulatory elements during blood development and differentiation

The overall aim of this work is to understand how regulatory sequences (enhancers, promoters) are bound and interpreted by TFs during erythroid development and differentiation. This is becoming increasingly important as DNA sequence variants in enhancers may alter protein binding and consequently may contribute to changes in gene expression that affect susceptibility to common diseases. We hypothesised that by using high-resolution analysis of chromatin accessibility data, we would identify relevant differences in sequence usage at regulatory regions in erythroid cells at various stages of development and differentiation. To test this, we developed a robust and efficient method to isolate HS regions in erythroid cells by performing DNase-Seq and ATAC-Seq. When analysed at high resolution, open-chromatin assays, namely DNase-Seq, reveal a genome-wide profile of “footprints” - transcription factor bound sites at regulatory elements in different erythroid cell types. The two dynamic contexts, development and differentiation, in which we analysed the changes in HS regions share a common pattern: we identified approximately 10% cell specific HS regions. The differential open-chromatin regions correspond mainly to enhancers, but also promoters. Majority of these elements (∼80%) occur in different genomic regions. These observations reinforce the fact that differentiation and development are driven by TF binding at distal elements. At the α-globin locus, the quantitative changes of HS regions are correlated with the activity of gene promoters. The level of HS enrichment refines the chromatin signature of functional enhancers. Novel analysis of HS genome-wide data, "average footprinting", provides a constrained set of transcription factor binding sites ranked by their usage in a specific cell type. We also adapted this approach to predict the effect of a variant in a sequence on altering affinity to TF and potentially causing changes in gene expression. This predicted damage score approach can be used to prioritise variants for functional analysis. Finally, we have identified families with unexplained anaemia, which have a SNP in a binding site of the major enhancer of the human α-globin cluster. This variant has a high damage score based on our prediction analysis. We are currently investigating if, and how, this non-coding SNP affects gene expression as an example of how regulatory SNPs in general may contribute to human genetic disease.