Fall Birches by Philip Barter
The past decade has seen a transformational change in our understanding of the human genome and the role it plays in influencing disease risk. Large-scale projects such as Encyclopedia of DNA Elements (ENCODE) have identified which non-coding regions correlate with gene regulatory function. Furthermore, the proliferation of genome wide association studies (GWAS) and scans for recent positive selection have identified thousands of loci that influence human health. Taken together, these efforts show the predominant contributors of heritability for complex phenotypes are common polymorphisms that reside within non-coding regions of the genome. However, despite our progress in mapping cis-regulatory elements (CREs) and genetic signatures correlated with disease, very few examples exist that mechanistically link genotypic variation to disease risk. This gap in our understanding is based on our inability to understand the sequence context of active CREs and their targets, without which it is difficult to identify single nucleotide variants that directly modulate gene expression. Thus, given the correct technological advances each disease association can become an untapped entry point that has the potential to transform our understanding of disease etiology.
(1) characterize and learn the grammar of cis-regulatory elements, in both mouse and human models, using novel technological approaches such as high-throughput reporter assays and CRISPR based screens of non-coding regions in the genome.
(2) Build upon the knowledge from genome wide association studies and leverage this resource of genetic risk to disease in human populations to construct better animal models that precisely reflect disease phenotypes.