Identification of genomic loci associated with 21chlorophyll fluorescence phenotypes by genome-wide association analysis in soybean

BackgroundPhotosynthesis is able to convert solar energy into chemical energy in the form of biomass, but the efficiency of photosynthetic solar energy conversion is low. Chlorophyll fluorescence measurements are rapid, non-destructive, and can provide a wealth of information about the efficiencies of the photosynthetic light reaction processes. Efforts aimed at assessing genetic variation and/or mapping of genetic loci associated with chlorophyll fluorescence phenotypes have been rather limited.ResultsEvaluation of SoySNP50K iSelect SNP Beadchip data from the 189 genotypes phenotyped in this analysis identified 32,453 SNPs with a minor allele frequency (MAF)5%. A total of 288 (non-unique) SNPs were significantly associated with one or more of the 21 chlorophyll fluorescence phenotypes. Of these, 155 were unique SNPs and 100 SNPs were only associated with a single fluorescence phenotype, while 28, 11, 2, and 14 SNPs, were associated with two, three, four and five or more fluorescence phenotypes, respectively. The 288 non-unique SNPs represent 155 unique SNPs that mark 53 loci. The 155 unique SNPs included 27 that were associated with three or more phenotypes, and thus were called multi-phenotype SNPs. These 27 multi-phenotype SNPs marked 13 multi-phenotype loci (MPL) identified by individual SNPs associated with multiple chlorophyll fluorescence phenotypes or by more than one SNP located within 0.5MB of other multi-phenotype SNPs.ConclusionA search in the genomic regions highlighted by these 13 MPL identified genes with annotations indicating involvement in photosynthetic light dependent reactions. These, as well as loci associated with only one or two chlorophyll fluorescence traits, should be useful to develop a better understanding of the genetic basis of photosynthetic light dependent reactions as a whole as well as of specific components of the electron transport chain in soybean. Accordingly, additional genetic and physiological analyses are necessary to determine the relevance and effectiveness of the identified loci for crop improvement efforts.