Medical and Population Genetics Program

The Program in Medical and Population Genetics is a diverse community of experts from a variety of fields — population genetics, statistics, molecular biology, genomics, and bioinformatics — who collaborate to characterize genetic variants and establish their role in disease. The program is a vibrant hub for scientific groups to share ideas and launch collaborative projects. Techniques and methods developed for the study of one disease are then shared and applied to other disease research areas.

Mark Daly

Fetal hemoglobin, which is normally replaced by adult hemoglobin a few months after birth, can ameliorate symptoms of beta-thalassemia and sickle cell anemia. Boosting fetal hemoglobin by inhibiting the transcription factor BCL11A holds therapeutic promise, but BCL11A's role in the body isn’t fully understood. To study its in vivo effects, a team led by Ó³»­´«Ã½ associate member Vijay Sankaran, Mark Daly, co-director of the Ó³»­´«Ã½â€™s Medical and Population Genetics Program, and Zdenek Sedlacek of University Hospital Motol (Czech Republic) identified and characterized three patients with an autism spectrum disorder and developmental delay who harbored deletions of the BCL11A gene. , appearing in the Journal of Clinical Investigation, provides evidence of BCL11A’s role in neurodevelopment and suggests caution when developing BCL11A-targeting therapies.

This week, Nature Genetics included papers on two new methods for leveraging large cohort studies. One paper — from the Ó³»­´«Ã½â€™s Program in (MPG) and , along with a team of collaborators — shares a powerful in genome-wide association studies (GWAS). The other — also with contributions from MPG — that vastly increases computation speed while simultaneously increasing the statistical power of large data sets.

In a recent study , Ó³»­´«Ã½-affiliated researchers Ron Do, Daniel Balick, Heng Li, Shamil Sunyaev, and David Reich challenged the theory that natural selection has been less effective removing deleterious genetic mutations in non-Africans versus West Africans over the course of human evolution. The team used simulations to show that observed mutation patterns that have been interpreted as evidence supporting the theory are not likely to reflect changes in the effectiveness of selection after the populations diverged, but are instead likely to be driven by other factors of population genetics.