|Bolon, Yung Tsi|
|Orf, James -|
|Muehlbauer, Gary -|
Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: November 2, 2010
Publication Date: January 17, 2011
Citation: Bolon, Y.E., Hyten, D.L., Orf, J., Vance, C.P., Muehlbauer, G. 2011. Genetic analysis of genome-wide transcriptional regulation through eQTL mapping in soybean [abstract]. XIX Plant and Animal Genome Conference Proceedings, January 15-19, 2011, San Diego, California. Abstract No. W550. Available: http://www.intl-pag.org/19/abstracts/W88_PAGXIX_550.html. Technical Abstract: Gene expression Quantitative Trait Loci (eQTL) mapping is a powerful tool for identifying the genetic basis of gene expression variation. Coincident genetic locations of eQTL and phenotypic QTL provide the basis for further investigation of the molecular mechanisms involved. Genetic analysis of expression trait (e-trait) variation also possesses the power to establish relationships between multiple regions of the genome and to identify transcriptional regulators. In this study, gene transcript profiling by Soy Genome Affymetrix Genechip was conducted on the developing seed of the Minsoy x Noir1 soybean recombinant inbred line (RIL) population. This RIL population was chosen due to the existence of wide genetic variation and extensive prior phenotypic characterization. In parallel, we refined the Minsoy x Noir1 genetic map with 500 SNP markers. We combined the SNP map and transcript accumulation data to map 2,500 eQTL among 30,681 e-traits across the soybean genome. We observed that the eQTL location for many e-traits mapped back to their genomic positions, as expected for cis-acting regulatory effects. In addition, eQTL positions were found that correlated with previously mapped phenotypic QTL for seed traits. Notably, a strong cis-acting eQTL on chromosome 20 was identified for a previously reported candidate gene for the regulation of seed protein levels. Finally, more than 20 different hotspots of trans-acting eQTL were identified, forming the basis for additional study of gene regulatory networks.