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.
|Peace, Jared M; Villwock, Sandra K; Zeytounian, John L et al. (2016) Quantitative BrdU immunoprecipitation method demonstrates that Fkh1 and Fkh2 are rate-limiting activators of replication origins that reprogram replication timing in G1 phase. Genome Res 26:365-75|
|Fear, Justin M; LeÃ³n-Novelo, Luis G; Morse, Alison M et al. (2016) Buffering of Genetic Regulatory Networks in Drosophila melanogaster. Genetics 203:1177-90|
|Kurmangaliyev, Yerbol Z; Ali, Sammi; Nuzhdin, Sergey V (2015) Genetic Determinants of RNA Editing Levels of ADAR Targets in Drosophila melanogaster. G3 (Bethesda) 6:391-6|
|Dubin, Manu J; Zhang, Pei; Meng, Dazhe et al. (2015) DNA methylation in Arabidopsis has a genetic basis and shows evidence of local adaptation. Elife 4:e05255|
|Wang, Wenhui; Zhou, Xianghong; Liu, Zhenqiu et al. (2015) Network tuned multiple rank aggregation and applications to gene ranking. BMC Bioinformatics 16 Suppl 1:S6|
|Kurmangaliyev, Yerbol Z; Favorov, Alexander V; Osman, Noha M et al. (2015) Natural variation of gene models in Drosophila melanogaster. BMC Genomics 16:198|
|Chen, Quan; Zhou, Xianghong J; Sun, Fengzhu (2015) Finding genetic overlaps among diseases based on ranked gene lists. J Comput Biol 22:111-23|
|Sasaki, Eriko; Zhang, Pei; Atwell, Susanna et al. (2015) "Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana. PLoS Genet 11:e1005597|
|Ostrow, A Zachary; Viggiani, Christopher J; Aparicio, Jennifer G et al. (2015) ChIP-Seq to Analyze the Binding of Replication Proteins to Chromatin. Methods Mol Biol 1300:155-68|
|Greenwood, Anna K; Ardekani, Reza; McCann, Shaugnessy R et al. (2015) Genetic mapping of natural variation in schooling tendency in the threespine stickleback. G3 (Bethesda) 5:761-9|
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