Boyle et al. 2017

Citation

Boyle, E. A., Li, Y. I., & Pritchard, J. K. (2017). An expanded view of complex traits: from polygenic to omnigenic. Cell, 169(7), 1177--1186.

Links

• https://www.sciencedirect.com/science/article/pii/S0092867417306293
• http://hawaiireedlab.com/pdf/b/boyleetal2017.pdf (internal lab link only)

Published Abstract

A central goal of genetics is to understand the links between genetic variation and disease. Intuitively, one might expect disease-causing variants to cluster into key pathways that drive disease etiology. But for complex traits, association signals tend to be spread across most of the genome—including near many genes without an obvious connection to disease. We propose that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways. We refer to this hypothesis as an “omnigenic” model.

Notes

This is very well written and starts off by placing it in the broad historical overview of understanding the relationship between genotypes and phenotypes. This emphasizes that the results from GWAS suggest that pleiotropy and genetic heterogeneity are widespread and play a very important role in connecting genotype to phenotype (versus classical views like strict Mendalism, Garrod's one gene one function, and the philosophy of genetic dissection, yet these have been very successful approaches).

Figure 3 is a very important result and point to make.

Simply searching for GO enrichment categories in GWAS may be a fundamental mistake.

This brings to mind a number of questions of the importance for the evolution of traits within and between species, and the authors spend some time discussing this.

I can't help thinking that associations from population structure might be inflating the genome-wide effect (and no one knows this better than the last author, Pritchard). This is mentioned on p. 1179, P. 3, "the signals are not driven by confounding from population structure". Also, this would be widely distributed regardless of gene expression levels or chromatin context.

Positive selection on a quantitative phenotype could help distribute the diversity reducing hitchhiking effect over a number of loci, smoothing out the correlation between diversity and rates of recombination seen across the genome of some species (Stephan 2010).

...to be continued.