Transcriptional regulation of gene expression, its timing, tissue distribution and response to both internal and environmental inputs, is a key link between the genome and phenotype. Variation in expression patterns across cell types is a primary determinant of tissue identity and function. Individual genetic variation in gene expression determines both our susceptibility to disease and provides the substrate for evolutionary adaptation. An integrated view of genome dynamics requires understanding these relationships in terms of genome organization. Toward this goal we will:
Aim 3 a. analyze publicly available gene expression data resources for physical correlates of tissue-specific gene expression patterns and for clustering of co-expression in LD domains and networks.
Aim 3 b. survey gene expression in 16 mouse strains using microarrays. The selected strains will include 'classical'inbred strains, inbred strains derived from M.m. musculus, M.m. domesticus, and M.m. castaneus origin, and inbred strains derived from hybrid origins. We will examine four tissues in mice of both sexes and relate our findings to genome organization and functional variation.
Aim 3 c. develop statistical methods and software for these analyses.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center (P50)
Project #
5P50GM076468-04
Application #
7798092
Study Section
Special Emphasis Panel (ZGM1)
Project Start
Project End
Budget Start
2009-04-01
Budget End
2010-03-31
Support Year
4
Fiscal Year
2009
Total Cost
$262,121
Indirect Cost
Name
Jackson Laboratory
Department
Type
DUNS #
042140483
City
Bar Harbor
State
ME
Country
United States
Zip Code
04609
Wang, Jeremy R; Holt, James; McMillan, Leonard et al. (2018) FMLRC: Hybrid long read error correction using an FM-index. BMC Bioinformatics 19:50
Ju, Chelsea J-T; Zhao, Zhuangtian; Wang, Wei (2017) Efficient Approach to Correct Read Alignment for Pseudogene Abundance Estimates. IEEE/ACM Trans Comput Biol Bioinform 14:522-533
Simecek, Petr; Forejt, Jiri; Williams, Robert W et al. (2017) High-Resolution Maps of Mouse Reference Populations. G3 (Bethesda) 7:3427-3434
Tyler, Anna L; Ji, Bo; Gatti, Daniel M et al. (2017) Epistatic Networks Jointly Influence Phenotypes Related to Metabolic Disease and Gene Expression in Diversity Outbred Mice. Genetics 206:621-639
Morgan, Andrew P; Gatti, Daniel M; Najarian, Maya L et al. (2017) Structural Variation Shapes the Landscape of Recombination in Mouse. Genetics 206:603-619
Parvanov, Emil D; Tian, Hui; Billings, Timothy et al. (2017) PRDM9 interactions with other proteins provide a link between recombination hotspots and the chromosomal axis in meiosis. Mol Biol Cell 28:488-499
Gu, Tongjun; Gatti, Daniel M; Srivastava, Anuj et al. (2016) Genetic Architectures of Quantitative Variation in RNA Editing Pathways. Genetics 202:787-98
Korstanje, Ron; Deutsch, Konstantin; Bolanos-Palmieri, Patricia et al. (2016) Loss of Kynurenine 3-Mono-oxygenase Causes Proteinuria. J Am Soc Nephrol 27:3271-3277
Powers, Natalie R; Parvanov, Emil D; Baker, Christopher L et al. (2016) The Meiotic Recombination Activator PRDM9 Trimethylates Both H3K36 and H3K4 at Recombination Hotspots In Vivo. PLoS Genet 12:e1006146
Jiang, Zixuan; Harrison, David E; Parsons, Makayla E et al. (2016) Heritability of in vitro phenotypes exhibited by murine adipose-derived stromal cells. Mamm Genome 27:460-8

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