Garrett Hellenthal, PhD, University College London

Title: Inferring signatures of intermixing and adaptation in human populations using genetic variation data

Abstract: Garrett is an Associate Professor at University College London, working in the UCL Genetics Institute (UGI). He received his undergraduate degree in Mathematics at Santa Clara University. He then completed his PhD in Statistics at the University of Washington, followed by postdoctoral positions in the labs of Jotun Hein and Peter Donnelly at University of Oxford and the Wellcome Trust Centre for Human Genetics (WTCHG). His current interests include (i) inferring population structure and ancestry in world-wide populations, including countries in east and west Africa, and how this relates to historical events, (ii) pinpointing genetic loci facilitating humans' adaptations to new environments, and (iii) identifying loci whose methylation markings are likely established in the early embryo, sensitive to prenatal environmental exposures and implicated in lifelong health outcomes.

I describe statistical techniques developed with colleagues that leverage genetic variation data to identify and date past events when different human populations intermixed. Applying our approach to large-scale genome-wide data resources from >100 world-wide populations, we infer dozens of intermixing episodes occurring within the last 4,000 years among geographically separated human groups. Many of these events align with well-attested historical empires and migrations, though I demonstrate how such genetics-based inference can also unearth previously unknown interactions and help resolve archeological/anthropological controversies. Furthermore, I illustrate a new technique that uses these intermixing signatures to identify genetic variants that have facilitated humans' ability to adapt to new environments, while determining whether this adaptation occurred before or after the intermixing. In an analysis of ~4,000 Latin Americans, we infer adaptation signatures at different timescales, incorporating results from recent expression quantitative loci (eQTL) and genome-wide association (GWAS) studies to link these signatures to immune and metabolic phenotypes. Examples include evidence of recent adaptive responses plausibly related to infectious disease pressures brought by European contact, and of older adaptive responses to pregnancy complications associated with living at high elevation. Résumé Garrett is an Associate Professor at University College London, working in the UCL Genetics Institute (UGI). He received his undergraduate degree in Mathematics at Santa Clara University. He then completed his PhD in Statistics at the University of Washington, followed by postdoctoral positions in the labs of Jotun Hein and Peter Donnelly at University of Oxford and the Wellcome Trust Centre for Human Genetics (WTCHG). His current interests include (i) inferring population structure and ancestry in world-wide populations, including countries in east and west Africa, and how this relates to historical events, (ii) pinpointing genetic loci facilitating humans' adaptations to new environments, and (iii) identifying loci whose methylation markings are likely established in the early embryo, sensitive to prenatal environmental exposures and implicated in lifelong health outcomes.

I describe statistical techniques developed with colleagues that leverage genetic variation data to identify and date past events when different human populations intermixed. Applying our approach to large-scale genome-wide data resources from >100 world-wide populations, we infer dozens of intermixing episodes occurring within the last 4,000 years among geographically separated human groups. Many of these events align with well-attested historical empires and migrations, though I demonstrate how such genetics-based inference can also unearth previously unknown interactions and help resolve archeological/anthropological controversies. Furthermore, I illustrate a new technique that uses these intermixing signatures to identify genetic variants that have facilitated humans' ability to adapt to new environments, while determining whether this adaptation occurred before or after the intermixing. In an analysis of ~4,000 Latin Americans, we infer adaptation signatures at different timescales, incorporating results from recent expression quantitative loci (eQTL) and genome-wide association (GWAS) studies to link these signatures to immune and metabolic phenotypes. Examples include evidence of recent adaptive responses plausibly related to infectious disease pressures brought by European contact, and of older adaptive responses to pregnancy complications associated with living at high elevation.

Via Zoom: https://mcgill.zoom.us/j/84499453174?pwd=dVc5RkYreVlpV3BnQjNhU244VzJoQT09