DEVELOPING MOLECULAR MARKERS FOR IRON DEFICIENCY CHLOROSIS
Corn Insects and Crop Genetics Research
2011 Annual Report
1a.Objectives (from AD-416)
1. Develop molecular markers (SNPs) that distinguish iron efficient and iron inefficient soybean. 2. Screen ~ 350 genotypes representing public and private IDC breeding lines and cultivars. 3. Score ~ 30 previously untested Accessions and Plant Introductions for iron efficiency and screen them against the markers developed in #1 above. 4. Correlate molecular marker scores with iron efficiency scores. 5. Identify the markers optimal for selecting iron efficient germplasm and make the markers publicly available.
1b.Approach (from AD-416)
Use the soybean whole genome sequence to search two major iron QTL regions to identify all recognizable regulatory genes and all 'candidate' genes residing within the QTL region. Regulatory genes and selected candidate genes will be re-sequenced in eight genotypes representing iron efficient and iron inefficient soybean types (Efficient: Clark, A15, Hawkeye, and PI 437654; Inefficient: Anoka, BSR 101, Pride B216, T203). From this resequencing single nucleotide polymorphisms will be identified and SNP markers will be designed. The SNPs will be screened against approximately 350 genotypes representing midwest breeding lines. Screening will be done using the 'Sequenome' technology at Iowa State University. Statistical methods will be employed to identify those markers with prediction capabilities in IDC breeding programs. Markers selected will be made available to the public.
During this reporting period, scientists at Ames, Iowa worked with collaborators at North Dakota State University to complete the association mapping of the molecular genetic markers identified in gene regulatory sequences in the vicinity of iron deficiency chlorosis (IDC) quantitative trait loci (QTLs). Markers were tested against 275 soybean lines with two years visual IDC scores in field studies in 2005 and 2006. Of the 270 markers that were successfully processed using the `Sequenome’ genotyping platform. Collaborators at North Dakota State University were able to use 232 of them for association mapping. Twenty-two markers were significant at the p=0.05 and pFDR=0.10 significance levels, in their ability to detect chromosomal regions having an effect on iron efficiency. These markers, and 80 other molecular markers were used to narrow down the QTL region in an attempt to identify the best candidate genes for iron efficiency. Project progress is monitored by weekly meetings and quarterly written reports.