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.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Postdoctoral Individual National Research Service Award (F32)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-F08-E (20))
Program Officer
Junkins, Heather
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Pennsylvania
Schools of Medicine
United States
Zip Code
Hey, Jody; Chung, Yujin; Sethuraman, Arun et al. (2018) Phylogeny Estimation by Integration over Isolation with Migration Models. Mol Biol Evol 35:2805-2818
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
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
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) Population Genomics of Human Adaptation. Annu Rev Ecol Evol Syst 44:123-143
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; 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
Pickrell, Joseph K; Patterson, Nick; Barbieri, Chiara et al. (2012) The genetic prehistory of southern Africa. Nat Commun 3:1143
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

Showing the most recent 10 out of 11 publications