Population genetics for large-scale sequencing studies of diverse populations

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Summary Population-based studies identifying the genetic variants that affect complex human diseases have relied heavily on population-genetic principles in important tasks such as study design, quality control, and genotype imputation. The dramatic growth of large-scale genotyping and sequencing studies of disease generates new challenges both for modeling the underlying generative population-genetic processes that give rise to evidence of disease association in data sets and for performing statistical analysis to uncover disease variants. These challenges magnify the potential for approaches grounded in population genetics to maximize the return from ongoing investigations. Because studies thus far have often focused on populations of European descent, it is critical that new methods provide tools for a greater diversity of populations. This project builds on productive efforts in two previous funding periods, capitalizing on the study of human population genetics to enhance the design, analysis, and interpretation of genomic studies of disease. It exploits the fundamental principle of human genetics that population-genetic phenomena are responsible for homozygous placement of recessive risk variants, and the recent recognition that accumulations of runs of homozygosity (ROH), and hence, of multiple recessive deleterious variants of small effect in homozygous form, can contribute to disease risk. Particularly for large-scale genotyping and low-coverage sequencing studies, in which rare recessive variants are difficult to analyze, this project uses the population genetics of ROH to enhance discovery. The project expands beyond the setting of rare diseases in small populations, building on observations that ROH and accumulations of recessive deleterious variants of small effect contribute to complex disease risk in outbred groups, including admixed populations. (1) We will construct models of the effects of interacting population- genetic forces on ROH. Such models will make it possible for researchers to attribute ROH patterns to effects of inbreeding, population size history, admixture, and selection against deleterious recessive variants. (2) We will develop powerful new tests that measure effects of ROH on complex disease risk. These tests will employ population-genetic models that incorporate features of genetic architecture and genomic parameters to assess if associations between ROH and disease reflect the likely presence of recessive disease variants. (3) We will differentiate between germline and somatically acquired homozygosity, leveraging signals in intermediate data types and genotype distributions from population genetics, to identify false-positive ROH and to refine detection of chromosomal alterations. (4) We will comprehensively evaluate the impact of ROH on medical traits in multiple disease studies, using the Michigan Genomics Initiative and UK Biobank to test and inform our approaches. The application of association testing between ROH and disease will contribute a phenome-wide association study to identify traits for which ROH variables possess meaningful predictive connections to phenotypes. To facilitate use of our methods, we will produce, test, and distribute new user-friendly software.