Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation

The differentiation of self-renewingprogenitor cells requires not only the regulation of lineage-and developmental stage-specific genes, but also the coordinated adaptation of housekeeping functionsfrom a metabolically active, proliferative state towards quiescence. How metabolic and cell cycle states are coordinated with the regulation of cell type-specific genes is an important question, as dissociation between differentiation, cell cycle, and metabolic states is a hallmark of cancer. Here we use a model system to systematically identify key transcriptional regulators of Ikaros-dependent B cell progenitor differentiation. We find that the coordinated regulation of housekeeping functions and tissue-specific gene expressionrequires afeedforward circuit whereby Ikarosdownregulates the expression of Myc. Our findings show how coordination between differentiation and housekeeping statescan be achieved by interconnected regulators. Similar principles likely coordinate differentiation and housekeeping functions during progenitor cell differentiation in other cell lineages

On the identification of potential regulatory variants within genome wide association candidate SNP sets

BACKGROUND: Genome wide association studies (GWAS) are a population-scale approach to the identification of segments of the genome in which genetic variations may contribute to disease risk. Current methods focus on the discovery of single nucleotide polymorphisms (SNPs) associated with disease traits. As there are many SNPs within identified risk loci, and the majority of these are situated within non-coding regions, a key challenge is to identify and prioritize variants affecting regulatory sequences that are likely to contribute to the phenotype assessed. METHODS: We focused investigation on SNPs within lung and breast cancer GWAS loci that reached genome-wide significance for potential roles in gene regulation with a specific focus on SNPs likely to disrupt transcription factor binding sites. Within risk loci, the regulatory potential of sub-regions was classified using relevant open chromatin and epigenetic high throughput sequencing data sets from the ENCODE project in available cancer and normal cell lines. Furthermore, transcription factor affinity altering variants were predicted by comparison of position weight matrix scores between disease and reference alleles. Lastly, ChIP-seq data of transcription associated factors and topological domains were included as binding evidence and potential gene target inference. RESULTS: The sets of SNPs, including both the disease-associated markers and those in high linkage disequilibrium with them, were significantly over-represented in regulatory sequences of cancer and/or normal cells; however, over-representation was generally not restricted to disease-relevant tissue specific regions. The calculated regulatory potential, allelic binding affinity scores and ChIP-seq binding evidence were the three criteria used to prioritize candidates. Fitting all three criteria, we highlighted breast cancer susceptibility SNPs and a borderline lung cancer relevant SNP located in cancer-specific enhancers overlapping multiple distinct transcription associated factor ChIP-seq binding sites. CONCLUSION: Incorporating high throughput sequencing epigenetic and transcription factor data sets from both cancer and normal cells into cancer genetic studies reveals potential functional SNPs and informs subsequent characterization efforts