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

Abstract

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 0.5 MB 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.Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1517-9) contains supplementary material, which is available to authorized users.

Variation in relaxation of non-photochemical quenching in a soybean nested association mapping panel as a potential source for breeding improved photosynthesis

“…Subsequently, we observed a low (< 0.5) heritability value for NPQ relaxation parameters in the NAM population using current screening approaches in a field environment. This is similar to heritability estimates from OJIP measurements of chlorophyll fluorescence in a larger panel of soybean genotypes (Herritt et al, 2018), and those reported for other photosynthetic traits such as Jmax in wheat (0.32; (Driever et al, 2014)).…”

“…Chlorophyll fluorescence was evaluated in two studies with field grown soybean, using canopy reflectance to calculate photochemical reflectance index (PRI), which is a proxy for NPQ (Herritt et al, 2016), and OJIP transients to look at variation in fluorescence kinetics (Herritt et al, 2018).…”

“…However, the individual components of NPQ relaxation was not assessed by Herritt et al (2016Herritt et al ( , 2018. Therefore, the extent to which individual components of NPQ co-vary in natural populations and whether they can be easily selected in breeding programs remains unclear.…”

Photosynthesis in a Changing Global Climate: Scaling Up and Scaling Down in Crops

“…However, when starting any experiment, a set of standard A-Ci curves should be performed to test that the method is working for each species and/or environmental condition. Therefore, this RACiR methodology only appears to be worth the effort when analyzing hundreds of samples at the same environmental condition as is often the case for GWAS and/or QTL experiments ( Dhanapal et al, 2015 ; Herritt et al, 2018 ; Luo et al, 2018 ). For small experiments where only a few cultivars/species are to be analyzed, it is more reasonable to do standard A-Ci curve measurements even if it is more time consuming, as they can be used to obtain other important information such as C c , g m ( Harley et al, 1992 ), R d and Γ that can give further valuable information about the physiological state of the plant.…”

Special issue in honour of Prof. Reto J. Strasser - Additive main effect and digenic epistatic quantitative trait loci for chlorophyll fluorescence traits influencing salt tolerance at seedling stage in rice

“…Some studies have been conducted to discover QTLs associated with Chl fluorescence traits under various conditions, such as normal (Zhang et al 2010), heat stress (Azam et al 2015, Bhusal et al 2018, and waterlogging (Bertholdsson et al 2015) in wheat and barley. Herritt et al (2018) identified several genomic loci associated with JIP-test parameters through genome-wide association study in soybean. However, till date no attempt has been made to identify QTLs associated with Chl fluorescence parameters under salt stress in rice.…”