Project E: Data Driven Systems Genetics Workflow for New Experimental Platforms; Elissa J. Chesler, Matthew A. Hibbs (Jackson) Systems genetics experiments typically involve separate acquisition of genotype, gene expression and phenotypic data in a genetically diverse population (Fig. 7 left). Conventional QTL and co-expression methods are applied to these data to construct genotype and phenotype networks. Application of this approach is reliant on existing resources, including a well-established reference genome, a dense genetic marker map often derived relative to the reference genome, and microarrays that are biased toward specific transcript structures and alleles. We will develop an approach that avoids these intrinsic biases through the development and application of high throughput RNA sequencing technology (HTPS) as the sole source of transcription and polymorphism data for an expression QTL experiment (Fig. 7 right). These new methods will minimize initial knowledge requirements. We will create software for our data-driven systems genetics approach, called SEQQTL, for use with highly diverse mouse populations, newly sequenced organisms, or in populations without an established genetic map. We will develop and validate these techniques in the DO mouse population.
| 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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