PLoS ONE (Jan 2017)
Genome-wide association mapping in winter barley for grain yield and culm cell wall polymer content using the high-throughput CoMPP technique.
Abstract
A collection of 112 winter barley varieties (Hordeum vulgare L.) was grown in the field for two years (2008/09 and 2009/10) in northern Italy and grain and straw yields recorded. In the first year of the trial, a severe attack of barley yellow mosaic virus (BaYMV) strongly influenced final performances with an average reduction of ~ 50% for grain and straw harvested in comparison to the second year. The genetic determination (GD) for grain yield was 0.49 and 0.70, for the two years respectively, and for straw yield GD was low in 2009 (0.09) and higher in 2010 (0.29). Cell wall polymers in culms were quantified by means of the monoclonal antibodies LM6, LM11, JIM13 and BS-400-3 and the carbohydrate-binding module CBM3a using the high-throughput CoMPP technique. Of these, LM6, which detects arabinan components, showed a relatively high GD in both years and a significantly negative correlation with grain yield (GYLD). Overall, heritability (H2) was calculated for GYLD, LM6 and JIM and resulted to be 0.42, 0.32 and 0.20, respectively. A total of 4,976 SNPs from the 9K iSelect array were used in the study for the analysis of population structure, linkage disequilibrium (LD) and genome-wide association study (GWAS). Marker-trait associations (MTA) were analyzed for grain yield and cell wall determination by LM6 and JIM13 as these were the traits showing significant correlations between the years. A single QTL for GYLD containing three MTAs was found on chromosome 3H located close to the Hv-eIF4E gene, which is known to regulate resistance to BaYMV. Subsequently the QTL was shown to be tightly linked to rym4, a locus for resistance to the virus. GWAs on arabinans quantified by LM6 resulted in the identification of major QTLs closely located on 3H and hypotheses regarding putative candidate genes were formulated through the study of gene expression levels based on bioinformatics tools.