Analyses of quantitative trait loci (QTLs) for expression levels (eQTLs) of genes reveal a genetic relationship between expression variation and the regulator, thus unlocking information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used an Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. In total, 1632 single-feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hot spots in the rice genome, each of which controls transcript variations of many e-traits. Gene ontology analysis revealed an enrichment of certain functional categories of genes in some of the eQTL hot spots. In particular, eQTLs for e-traits involving the DNA metabolic process was significantly enriched in several eQTL hot spots on chromosomes 3, 5 and 10. Several e-traits co-localizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided clues for the identification and characterization of the regulatory network in the whole genome at the transcriptional level.
© 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.