A map of constrained coding regions in the human genome

Abstract

Deep catalogs of genetic variation collected from many thousands of humans enable the detection of intraspecies constraint by revealing coding regions with a scarcity of variation. While existing techniques summarize constraint for entire genes, single metrics cannot capture the fine-scale variability in constraint within each protein-coding gene. To provide greater resolution, we have created a detailed map of constrained coding regions (CCRs) in the human genome by leveraging coding variation observed among 123,136 humans from the Genome Aggregation Database (gnomAD). The most constrained coding regions in our map are enriched for both pathogenic variants in ClinVar and de novo mutations underlying developmental disorders. CCRs also reveal protein domain families under high constraint, suggest unannotated or incomplete protein domains, and facilitate the prioritization of previously unseen variation in studies of disease. Finally, a subset of CCRs with the highest constraint likely exist within genes that cause yet unobserved human phenotypes owing to strong purifying selection.

Predicting the occurrence of variants in RAG1 and RAG2

“…Havrilla et al [61] have recently developed a method with similar possible applications for human health mapping constrained coding regions. Their study employed a method that included weighting by sequencing depth.…”

From Sanger Sequencing to Genome Databases and Beyond

“…A team of researchers led by Aaron Quinlan from University of Utah Health (UT, USA) has developed a detailed map of the human genome, documenting regions of DNA that experience very little heterogeneity between different genomes [9]. These regions of low genetic variation are referred to as being highly constrained and the team believes that they could indicate genes involved in the pathogenesis of developmental disorders.…”

Co-expression patterns define epigenetic regulators associated with neurological dysfunction

“…We therefore asked if the EM-specific domain(s) in an EM gene had a different local mutational constraint than other domains in the same gene. To answer this, we used the constrained coding region (CCR) model (Havrilla et al, 2017) to derive a constraint score at the domain level, which we call CCR local constraint. This score reflects how devoid the domain is of missense or loss of function mutations in the gnomAD database (Lek et al, 2016), compared to other similar regions.…”

“…The CCR model (Havrilla et al, 2017) identifies regions of the genome without any missense or loss of function mutations in gnomAD (Lek et al, 2016). Each region devoid of mutations is assigned a CCR percentile score; the greater the difference between the observed and expected coverage-weighted length for regions with similar CpG density, the higher the constraint.…”