A genome-wide association analysis of quantitative trait loci for protein fraction content in Tibetan wild barley

Association analysis for quality traits in a diverse panel of Chinese sesame (Sesamum indicum L.) germplasm

The main objective of this study was to evaluate the potential of a sesame (Sesamum indicum L.) panel for association analysis, and investigate the genetic basis of oil content (OC), protein content, oleic acid concentration, and linoleic acid concentration using association mapping. A panel of 216 sesame accessions was phenotyped in a multi-environment trial and fingerprinted with 608 polymorphic loci produced by 79 primers, including simple sequence repeats (SSRs), sequence-related amplified polymorphisms (SRAPs), and amplified fragment length polymorphisms (AFLPs). Population structure analysis revealed two subgroups in the population. The Q model performed better for its ability to re-identify associations for the four traits at highly significant P-values compared to the other three mixed models. And a total of 35 and 25 associations for the four traits in 2010 and 2011 were identified, respectively, with the Q model after Bonferroni correction. Among those associations, only one for OC was re-identified in two environments, and several markers associated simultaneously with multiple traits were discovered. These results suggest the power and stability of the Q model for association analysis of nutritional traits in this sesame panel for its slight population stratification and familial relationship, which could aid in dissecting complex traits, and could help to develop strategies for improving nutritional quality.

Grain protein content variation and its association analysis in barley

BACKGROUND

Grain protein content (GPC) is an important quality determinant for barley used as malt, feed as well as food. It is controlled by a complex genetic system. GPC differs greatly among barley genotypes and is also variable across different environments. It is imperative to understand the genetic control of barley GPC and identify the genotypes with less variation under the different environments.

RESULTS

In this study, 59 cultivated and 99 Tibetan wild barley genotypes were used for a genome-wide association study (GWAS) and a multi-platform candidate gene-based association analysis, in order to identify the molecular markers associated with GPC. Tibetan wild barley had higher GPC than cultivated barley. The significant correlation between GPC and diastatic power (DP), and malt extract confirmed the importance of GPC in determining malt quality. Diversity arrays technology (DArT) markers associated with barley GPC were detected by GWAS. In addition, GWAS revealed two HvNAM genes as the candidate genes controlling GPC. No association was detected between HvNAM1 polymorphism and GPC, while a single nucleotide polymorphism (SNP) (798, P < 0.01), located within the second intron of HvNAM2, was associated with GPC. There was a significant correlation between haplotypes of HvNAM1, HvNAM2 and GPC in barley.

CONCLUSIONS

The GWAS and candidate gene based-association study may be effectively used to determine the genetic variation of GPC in barley. The DArT markers and the polymorphism of HvNAM genes identified in this study are useful in developing high quality barley cultivars in the future. HvNAM genes could play a role in controlling barley GPC.