Dan Gatti wins Student Poster Award at CTC Meeting
| June 01, 2006 | |
| Daniel M. Gatti (MS, Rusyn Advisor) won a Student Poster Award at the 5th Annual Meeting of the Complex Trait Consortium (CTC) held on May 6-10, 2006 at UNC’s Friday Center in Chapel Hill, North Carolina. The CTC is an international group of scientists, working to identify networks of genes and allelic variants that modulate complex phenotypes in diverse environments. Six poster winners were presented a $50 cash prize and award certificate. Poster details are provided below.Title: Examination of genetic networks that regulate gene expression in liver using complex trait analysis.
Authors: Daniel Gatti, Akira Maki, Elissa J. Chesler, Roumyana Kirova, Lu Lu, Jintao Wang, Yanhua Qu, Robert W. Williams, Andy Perkins, Michael A. Langston, David W. Threadgill, and Ivan Rusyn Abstract: The liver is a primary site for metabolism of nutrients, drugs and chemical agents. While metabolic pathways are complex and tightly regulated, genetic variation among individuals introduces yet another level of complexity into liver research. This study aimed to dissect genetic networks that control liver-specific gene expression by combining large-scale mRNA expression analysis and gene mapping in a reference population of BXD recombinant inbred strains for which extensive SNP, haplotype and phenotypic data exists. We profiled gene expression in livers of naive mice (both sexes) from C57BL/6J, DBA/2J, B6D2F1, and 40 BXD strains, using Agilent oligonucleotide arrays. This data was used to map quantitative trait loci (QTLs) associated with variation in expression of thousands of transcripts. We identified polymorphic cis- and trans-acting genes in liver by comparing the physical transcript position with the location of the controlling QTL. Several trans-acting control loci that modify expression of large numbers of genes in liver were found and these appear to be tissue-specific. We illustrate this concept with the identification of candidate genes involved in xenobiotic metabolism and oxidative stress. The data is available through public web-based resource that allows custom genetic linkage analysis, identification of co-regulated transcripts and correlated phenotypes, cross-tissue and species comparison, as well as testing of a broad array of hypotheses. For further information please contact Rebecca Riggsbee Lloyd by email at Rebecca_Lloyd@unc.edu |
