A genomic study of soybean iron deficiency chlorosis

O'Rourke, Jamie
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Soybeans grown in the farmlands of the upper Midwest of the United States often suffer from iron deficiency chlorosis which results in end of season yield loss. Previous studies in soybean have identified 19 Quantitative Trait Loci (QTL) regions with an association to iron deficiency chlorosis. However, specific genes involved in the process of iron reduction, uptake and transport have not been identified in soybean. Through the use of near isogenic soybean lines (NILs), Expressed Sequence Tag (EST) microarrays, and Affymetrix RTM GeneChipsRTM, I have identified a suite of candidate genes putatively involved in the soybean iron deficiency response. Single linkage cluster analysis of the candidate genes and genes known to be induced by biotic and abiotic stresses determined that under iron stress conditions, iron efficient soybeans initiate both a general stress response and an iron specific stress response. Iron inefficient soybeans do not initiate a complete complement of either response. We also determined that periods of iron deficiency stress have effects on soybean gene expression that continue after the iron deficiency is alleviated. Candidate genes identified through AffymetrixRTM GeneChipRTM analysis confirmed both these results. Candidate genes have been aligned with the 7X soybean genome sequence to identify 56 candidate genes from the iron efficient NIL and 22 candidate genes from the iron inefficient NIL located within the previously identified QTLs. The hybridization data from the AffymetrixRTM GeneChipsRTM were also used to identify single feature polymorphisms. The identified sequence differences between the NILs have the potential to be developed as iron specific molecular markers. The promoter regions of the candidate genes were bioinformatically mined to identify conserved motifs, most likely indicative of transcription factor binding sites involved in soybean iron deficiency response. These motifs can be used to query the genome sequence to identify additional genes, which might be involved in soybean iron deficiency chlorosis but were not identified by microarray analysis. Finally, the genome alignment shows genes differentially expressed due to iron deficiency chlorosis are not randomly dispersed throughout the genome, but are instead clustered together. This fact, taken together with the identification of conserved promoter motifs, suggests that the clustered genes are most likely coordinately regulated. These analyses have provided the first suite of candidate genes for iron deficiency chlorosis in soybean.