Dr. Hanchard Neil
Assistant Professor of Molecular and Human Genetics
Baylor College of Medicine in Houston, TX
Dr. Hanchard is an Assistant Professor of Molecular and Human Genetics at Baylor College of Medicine in Houston, TX. He received his MBBS (Hons) from the University of the West Indies in Kingston, Jamaica, and his D.Phil. from the University of Oxford, UK, as Rhodes Scholar. During his time at Oxford, Dr. Hanchard worked in the laboratory of Prof. Dominic Kwiatkowski, using patterns of linkage disequilibrium to map complex disease traits. Thereafter he completed his formal training as a pediatrician at the Mayo Clinic in Rochester, MN and as a clinical geneticist at Baylor College of Medicine. His lab focuses on using genomics to explore complex pediatric disease traits, particularly among populations of African ancestry. The lab has ongoing projects on severe childhood malnutrition, pediatric HIV/AIDS, and sickle cell disease, and has published on population genetics in African and Afro-Caribbean populations. When not in his lab, he runs a translational genomics core lab at BCM and sees patients with rare Mendelian disorders at Texas Children’s Hospital.
Title of the talk: High-Depth Genome Sequencing in Diverse African Populations informs Migration History and Disease-mapping in Sub-Saharan Africa
Ananyo Choudhury, Shaun Aron, Laura Botigué, Dhriti Sengupta, Gerrit Botha, Taoufik Bensellak, Gordon Wells, Judit Kumuthini, Yasmina Jaufeerally Fakim, Anisah Wahed Ghoorah, Scott Hazelhurst, Oscar A. Nyangiri, Mamana Mbiyavanga, Samar Kassim, Eileen Dareng, Trust Odia, Dare Falola, Benard Kulohoma, Sally Adebamowo, Emile R. Chimusa, Nicola Mulder, Zane Lombard, Adeyemo Adebowale, Neil Hanchard, for the H3Africa Consortium
The African continent has consistently stood out as a major source of genetic variation, human diversity, and demographic ancestry; yet, to date, only a small number of African populations have been surveyed at the genomic level, mostly using common variation. We used whole-genome sequencing, 70% at high-depth, to explore genomic diversity and demography across 13 geographically disparate African countries, encompassing 426 individuals and 50 ethnolinguistic groups from the H3Africa Consortium.
We identified more than 3 million novel single nucleotide variants (SNVs), including between 35,000 and 50,000 novel common SNVs per population, and catalogued SNVs with derived allele frequencies that were highly differentiated between populations. Admixture analyses revealed evidence for a Non-Niger Kordofanian ancestry component constituting 7-18% of a major indigenous group from Nigeria that was not seen in other West African sequences, as well as a lack of Khoesan ancestry among Zambians, which distinguished them from their geographic neighbors in Botswana. The disparate geography of sampled populations enabled us to delineate contact zones and date interactions between Bantu-speakers and hunter-gatherer populations, with ancestral components and genetic distances suggesting Zambia to be en-route of Bantu-migration from West to Eastern and Southern Africa. Using a composite model that leverages high-depth data, we identified 63 loci with strong evidence of selection, including 33 novel loci. Selected loci converged upon genes involved in viral infection (CAMK2B, MVB12B, DKK2) and metabolism (ADRB3, GLIS3), with immune-system-associated loci harboring the highest proportion of shared, putative loss-of-function variants. ACMG medically-actionable variants were found in <2% of the cohort, although reportedly pathogenic ClinVar alleles had a mean frequency of 8%. Disease-alleles classically associated with African populations, including those for sickle cell disease and trypanosomiasis, were commonly observed, but showed substantial inter- and intra-country variation in frequency.
1) Highlight unexpected patterns of admixture and ancestry that inform current theories of early population migration;
2) Illustrate the role of viral and other infections in shaping African genomes, and
3) Demonstrate the importance of African genomic data to defining medically-relevant variation and mapping disease-genes in global populations.