Project E: Data Driven Systems Genetics Workflow for New Experimental Platforms
Elissa J. Chesler (Jackson)
Systems genetics experiments typically involve separate acquisition of genotype, gene expression and phenotypic data in a genetically diverse population. Conventional quantitative trait loci (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 are developing an approach that avoids these intrinsic biases through the development and application of high throughput RNA sequencing technology as the sole source of transcription and polymorphism data for an expression QTL experiment. These new methods will minimize initial knowledge requirements. We are creating 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 are developing and validating these techniques in the Diversity Outbred mouse population.
Center related publications
High-precision genetic mapping of behavioral traits in the diversity outbred mouse population
Logan RW, Robledo RF, Recla JM, Philip VM, Bubier JA, Jay JJ, Harwood C, Wilcox T, Gatti DM, Bult CJ, Churchill GA, Chesler EJ.
Genes Brain Behav. 2013 Feb 21. doi: 10.1111/gbb.12029.
Genetic Analysis of Hematologic Parameters in Incipient Lines of the Collaborative Cross
Kelada SNP, Aylor DL, Peck BCE, Ryan JF, Tavarez U, Buus RJ, Miller DR, Chesler EJ, Threadgill DW, Churchill GA, Pardo-Manuel de Villena F, Collins FS.
G3 (Bethesda). 2012 Feb;2(2):157-65. PMCID: PMC3284323 [ Full Text ] [ datasets ]
High-Resolution Genetic Mapping Using the Mouse Diversity Outbred Population
Svenson KL, Gatti DM, Valdar W, Welsh CE, Cheng R, Chesler EJ, Palmer AA, McMillan L, Churchill GA.
Genetics. 2012 Feb;190(2):437-47. PMCID: PMC3276626 [ Full Text ] [ datasets ]
Genetic analysis of albuminuria in Collaborative Cross and multiple mouse intercross populations
Thaisz J, Tsaih SW, Feng M, Philip V, Zhang Y, Yanas L, Sheehan S, Xu L, Miller DR, Paigen B, Chesler EJ, Churchill GA, Dipetrillo KJ.
Am J Physiol Renal Physiol. 2012 Oct;303(7):F972-81. PMCID: PMC3469684 [Available on 2013/10/1]