The proposed research project involves detailed characterization of whole genome variation in understudied ethnically and geographically diverse Africans living in distinct environments and with distinct diets. The dataset represents the most detailed catalog of genomic variation in under-represented African populations created to date. Population genetic analyses will enable us to identify potential functional variants that play a role in adaptation to diverse environments and to infer the demographic history of populations. Despite immense amounts of genetic variation and significant public health challenges, African human genetics has largely been understudied. It is important that recent advances in genomics and genetic medicine do not ignore Africa populations. Using high-coverage whole genome sequencing we will analyze whole genome sequences of multiple individuals in multiple African populations in order to infer both recent and ancient demographic history in Africa and to identify targets of natural selection in the human genome. Existing statistical population genetics approaches will be applied, and novel theoretical approaches will be developed to analyze population genomics datasets using a combination of computer simulations and mathematical modeling. Whole genome sequences will also be combined with data generated from genotyping arrays to assess the impact of SNP ascertainment bias on diverse African populations. Genomic variation present in African populations living in diverse climates and with diverse diets (agriculturalists, pastoralists and hunter- gatherers) is relevant o diseases of modernity, such as hypertension and diabetes. In addition, genetic variation found will be useful for genome-wide association studies of African populations. This proposed study is also highly relevant to the NIH's Human Heredity and Health in Africa Project (H3Africa), and this research project will contribute substantially to postdoctoral training. Finally, analytic approaches developed for African populations will also be useful to other studies that utilize next-generation sequencing technology.

Public Health Relevance

This project is highly relevant to public health because African populations have substantial disease risks and African population genetics has largely been understudied. Sequencing the genomes of ethnically diverse African populations will greatly expand our knowledge of human genetic diversity and help identify genes of adaptive significance. The results of this study will be a powerful resource for understanding how genetic and environmental variation contributes to variable heritable traits and for designing and interpreting disease association studies.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
1F32HG006648-01
Application #
8255805
Study Section
Special Emphasis Panel (ZRG1-F08-E (20))
Program Officer
Junkins, Heather
Project Start
2011-12-15
Project End
2014-12-14
Budget Start
2011-12-15
Budget End
2012-12-14
Support Year
1
Fiscal Year
2012
Total Cost
$48,398
Indirect Cost
Name
University of Pennsylvania
Department
Genetics
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Hsieh, PingHsun; Woerner, August E; Wall, Jeffrey D et al. (2016) Model-based analyses of whole-genome data reveal a complex evolutionary history involving archaic introgression in Central African Pygmies. Genome Res 26:291-300
Hsieh, PingHsun; Veeramah, Krishna R; Lachance, Joseph et al. (2016) Whole-genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection. Genome Res 26:279-90
Lachance, Joseph; Tishkoff, Sarah A (2014) Biased gene conversion skews allele frequencies in human populations, increasing the disease burden of recessive alleles. Am J Hum Genet 95:408-20
Lachance, Joseph; Tishkoff, Sarah A (2013) SNP ascertainment bias in population genetic analyses: why it is important, and how to correct it. Bioessays 35:780-6
Wang, Shuoguo; Lachance, Joseph; Tishkoff, Sarah A et al. (2013) Apparent variation in Neanderthal admixture among African populations is consistent with gene flow from Non-African populations. Genome Biol Evol 5:2075-81
Lachance, Joseph; Tishkoff, Sarah A (2013) Population Genomics of Human Adaptation. Annu Rev Ecol Evol Syst 44:123-143
Lachance, Joseph; Jung, Lawrence; True, John R (2013) Genetic background and GxE interactions modulate the penetrance of a naturally occurring wing mutation in Drosophila melanogaster. G3 (Bethesda) 3:1893-901
Lachance, Joseph; Vernot, Benjamin; Elbers, Clara C et al. (2012) Evolutionary history and adaptation from high-coverage whole-genome sequences of diverse African hunter-gatherers. Cell 150:457-69
Johnson, Norman A; Lachance, Joseph (2012) The genetics of sex chromosomes: evolution and implications for hybrid incompatibility. Ann N Y Acad Sci 1256:E1-22
Pickrell, Joseph K; Patterson, Nick; Barbieri, Chiara et al. (2012) The genetic prehistory of southern Africa. Nat Commun 3:1143