This proposal is for the renewal of our existing Center of Excellence in Genomic Science ("Implication of Haplotype Structure in the Human Genome"). Since the start of our Center in 2003, there have been extraordinary advance in genomics. Genome-wide association studies using Single Nucleotide Polymorphisms are now routine, and we are rapidly moving toward having whole-genome sequence data for large samples of individuals. Our Center has undergone similar dramatic change. While the underlying theme of our proposal remains the same - making sense of genetic variation - our focus is now explicitly on how we can use the heterogeneous data produced by modern genomics to achieve such an understanding. The overall goal of our proposal is to develop an intellectual framework, together with computational and statistical analysis tools, for illuminating the path from genotype to phenotype, and for predicting the latter from the former. We will address three broad questions related to this problem: 1) How do we infer mechanisms by which genetic variation leads to changes in phenotype? 2) How do we improve the design, understanding and interpretation of association studies by exploiting prior information? 3) How do we identify general principles about the genotype-phenotype map? We will approach these questions through a series of interrelated projects that combine computational and experimental methods, and involve a wide range of researchers including molecular biologists, population geneticists, genetic epidemiologists, statisticians, computer scientists, and mathematicians.
- One of the most important challenges facing biology today is understanding how genetic variation between individuals translates (or maps) into variation we can see or measure, like blood pressure, and how this mapping is affected by the environment. The goal of this project is to increase our understanding of the general principles that underlie the genotype-phenotype map by studying model organisms.
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|Lehmann, Kjong-Van; Chen, Ting (2013) Exploring functional variant discovery in non-coding regions with SInBaD. Nucleic Acids Res 41:e7|
|Zhong, Yuan; Nellimoottil, Tittu; Peace, Jared M et al. (2013) The level of origin firing inversely affects the rate of replication fork progression. J Cell Biol 201:373-83|
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