Genetic variation is the primary source of evolutionary innovation and a major factor responsible for phenotypic variation. Consequently, understanding such variation has great importance in both basic biology and evolution, and ultimately Mendelian and complex disease. We will study the origin of genetic variation through spontaneous mutational processes. Computational analysis of sequencing datasets will shed light on the mechanistic forces underlying germ-line and somatic cancer mutations in human. We will design new statistical models of de novo mutation that will have applications in population genetics, cancer genomics and genetics of neuropsychiatric disease. Next, we will improve computational methods for interpreting and predicting the effect of mutation on molecular function, including both coding and non-coding variation. Our methods integrate data from evolutionary genetics and biophysics and rely on comparative, functional and structural data. The newly developed methods will have applications in both medical and population genetics. We will study the population dynamics of alleles to estimate the forces that shape genetic variation within populations. We will rely on population genetics models to analyze evolutionary maintenance and genetic architecture of human phenotypes. Fascinated by the relationship between genotype and phenotype, we will combine theoretical models and statistical analysis of large-scale sequencing datasets to infer properties of the allelic architecture of complex traits. We will design new approaches to characterize and predict the genetic component of common disease risk. !

Public Health Relevance

Our research will focus on several key aspects of human genetic variation. We will study de novo mutations, predict the functional effect of human alleles, and explore the probabilistic relationship between genotype and phenotype. !

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
5R35GM127131-02
Application #
9697367
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Krasnewich, Donna M
Project Start
2018-05-11
Project End
2023-04-30
Budget Start
2019-05-01
Budget End
2020-04-30
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115