Summary Plants produce numerous metabolites that are important for their development and growth. However, the genetic architecture of the wheat metabolome has not been well studied. Here, utilizing a high‐density genetic map, we conducted a comprehensive metabolome study via widely targeted LC‐MS/MS to analyze the wheat kernel metabolism. We further combined agronomic traits and dissected the genetic relationship between metabolites and agronomic traits. In total, 1260 metabolic features were detected. Using linkage analysis, 1005 metabolic quantitative trait loci (mQTLs) were found distributed unevenly across the genome. Twenty‐four candidate genes were found to modulate the levels of different metabolites, of which two were functionally annotated by in vitro analysis to be involved in the synthesis and modification of flavonoids. Combining the correlation analysis of metabolite‐agronomic traits with the co‐localization of methylation quantitative trait locus (mQTL) and phenotypic QTL (pQTL), genetic relationships between the metabolites and agronomic traits were uncovered. For example, a candidate was identified using correlation and co‐localization analysis that may manage auxin accumulation, thereby affecting number of grains per spike (NGPS). Furthermore, metabolomics data were used to predict the performance of wheat agronomic traits, with metabolites being found that provide strong predictive power for NGPS and plant height. This study used metabolomics and association analysis to better understand the genetic basis of the wheat metabolism which will ultimately assist in wheat breeding.

BackgroundPhysiological and morphological traits of flag leaf play important roles in determining crop grain yield and biomass. In order to understand genetic basis controlling physiological and morphological traits of flag leaf, a double haploid (DH) population derived from the cross of Huaai 11 × Huadamai 6 was used to detect quantitative trait locus (QTL) underlying 7 physiological and 3 morphological traits at the pre-filling stage in year 2012 and 2013.ResultsTotal of 38 QTLs distributed on chromosome 1H, 2H, 3H, 4H, 6H and 7H were detected, and explained 6.53% - 31.29% phenotypic variation. The QTLs flanked by marker Bmag829 and GBM1218 on chromosome 2H were associated with net photosynthetic rate (Pn), stomatal conductance (Gs), flag leaf area (LA), flag leaf length (FLL), flag leaf width (FLW), relative chlorophyll content (SPD) and leaf nitrogen concentration (LNC).ConclusionTwo QTL cluster regions associated with physiological and morphological traits, one each on the chromosome 2H and 7H, were observed. The two markers (Bmag829 and GBM1218) may be useful for marker assisted selection (MAS) in barley breeding.

BackgroundIncreasing the yield of barley (Hordeum vulgare L.) is a main breeding goal in developing barley cultivars. A high density genetic linkage map containing 1894 SNP and 68 SSR markers covering 1375.8 cM was constructed and used for mapping quantitative traits. A late-generation double haploid population (DH) derived from the Huaai 11 × Huadamai 6 cross was used to identify QTLs and QTL × environment interactions for ten traits affecting grain yield including length of main spike (MSL), spikelet number on main spike (SMS), spikelet number per plant (SLP), grain number per plant (GP), grain weight per plant (GWP), grain number per spike (GS), thousand grain weight (TGW), grain weight per spike (GWS), spike density (SPD) and spike number per plant (SP).ResultsIn single environment analysis using composite interval mapping (CIM), a total of 221 QTLs underlying the ten traits were detected in five consecutive years (2009–2013). The QTLs detected in each year were 50, 48, 41, 41 and 41 for the year 2009 to 2013. The QTLs associated with these traits were generally clustered on chromosome 2H, 4H and 7H.In multi-environment analysis, a total of 111 significant QTLs including 18 for MSL, 16 for SMS, 15 for SPD, 5 for SP, 4 for SLP, 14 for TGW, 5 for GP, 11 for GS, 8 for GWP, and 15 for GWS were detected in the five years. Most QTLs showed significant QTL × environment interactions (QEI), nine QTLs (qIMSL3-1, qIMSL4-1, qIMSL4-2, qIMSL6-1, qISMS7-1, qISPD2-7, qISPD7-1, qITGW3-1 and qIGWS4-3) were detected with minimal QEI effects and stable in different years. Among 111 QTLs,71 (63.40 %) QTLs were detected in both single and multiple environments.ConclusionsThree main QTL cluster regions associated with the 10 agronomic traits on chromosome 2H, 4H and 7H were detected. The QTLs for SMS, SLP, GP and GWP were located in the region near Vrs1 on chromosome 2H. The QTLs underlying SMS, SPD and SLP were clustered on chromosome 4H. On the terminal of chromosome 7H, there was a QTL cluster associated with TGW, SPD, GWP and GWS. The information will be useful for marker-assisted selection (MAS) in barley breeding.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0409-y) contains supplementary material, which is available to authorized users.

Grain size and weight are crucial components of barley yield and quality and are the target characteristics of domestication and modern breeding. Despite this, little is known about the genetic and molecular mechanisms of grain size and weight in barley. Here, we evaluated nine traits determining grain size and weight, including thousand grain weight (Tgw), grain length (Gl), grain width (Gw), grain length-width ratio (Lwr), grain area (Ga), grain perimeter (Gp), grain diameter (Gd), grain roundness (Gr), and factor form density (Ffd), in a double haploid (DH) population for three consecutive years. Using five mapping methods, we successfully identified 60 reliable QTLs and 27 hotspot regions that distributed on all chromosomes except 6H which controls the nine traits of grain size and weight. Moreover, we also identified 164 barley orthologs of 112 grain size/weight genes from rice, maize, wheat and 38 barley genes that affect grain yield. A total of 45 barley genes or orthologs were identified as potential candidate genes for barley grain size and weight, including 12, 20, 9, and 4 genes or orthologs for barley, rice, maize, and wheat, respectively. Importantly, 20 of them were located in the 14 QTL hotspot regions on chromosome 1H, 2H, 3H, 5H, and 7H, which controls barley grain size and weight. These results indicated that grain size/weight genes of other cereal species might have the same or similar functions in barley. Our findings provide new insights into the understanding of the genetic basis of grain size and weight in barley, and new information to facilitate high-yield breeding in barley. The function of these potential candidate genes identified in this study are worth exploring and studying in detail.

BackgroundDwarfing genes have widely been used in barley breeding program. More than 30 types of dwarfs or semidwarfs have been reported, but a few has been exploited in barley breeding because pleiotropic effects of dwarfing genes cause some undesired traits. The plant architecture of newly discovered dwarfing germplasm "Huaai 11" consisted of desirable agronomic traits such as shortened stature and early maturity. Genetic factor controlling the plant height in dwarf line Huaai 11 was investigated.ResultsThe Huaai 11 was crossed with tall varieties Monker, Mpyt, Zhenongda 3, Zaoshu 3, Advance, Huadamai 1, Huadamai 6, Hyproly and Ris01508. All the F1 plants displayed tall trait. Both tall and dwarf plants appeared in all the F2 populations with a 3:1 segregation ratio, suggesting that dwarfism of Huaai 11 is controlled by a single recessive gene, btwd1. Allelism test indicated that this dwarfing gene in the Huaai 11 is nonallelic with the gene br, uzu, sdw1 and denso. Using a double haploid population derived from a cross of Huadamai 6 and Huaai 11 and SSR markers the novel dwarfing gene was mapped onto the long arm of chromosome 7H, and closely linked to Bmac031 and Bmac167 with genetic distance of 2.2 cM.ConclusionHuaai 11 is a new source of dwarf for broadening the genetic base of dwarfism. This dwarf source was controlled by a recessive dwarfing gene btwd1, was mapped onto the long arm of chromosome 7H.

Association mapping is a powerful approach to detect associations between traits of interest and genetic markers based on linkage disequilibrium (LD) in molecular plant breeding. In this study, 150 accessions of worldwide originated durum wheat germplasm (Triticum turgidum spp. durum) were genotyped using 1,366 SNP markers. The extent of LD on each chromosome was evaluated. Association of single nucleotide polymorphisms (SNP) markers with ten agronomic traits measured in four consecutive years was analyzed under a mix linear model (MLM). Two hundred and one significant association pairs were detected in the four years. Several markers were associated with one trait, and also some markers were associated with multiple traits. Some of the associated markers were in agreement with previous quantitative trait loci (QTL) analyses. The function and homology analyses of the corresponding ESTs of some SNP markers could explain many of the associations for plant height, length of main spike, number of spikelets on main spike, grain number per plant, and 1000-grain weight, etc. The SNP associations for the observed traits are generally clustered in specific chromosome regions of the wheat genome, mainly in 2A, 5A, 6A, 7A, 1B, and 6B chromosomes. This study demonstrates that association mapping can complement and enhance previous QTL analyses and provide additional information for marker-assisted selection.

The importance of wild barley from Qinghai-Tibet Plateau in the origin and domestication of cultivated barley has long been underestimated. Population-based phylogenetic analyses were performed to study the origin and genetic diversity of Chinese domesticated barley, and address the possibility that the Tibetan region in China was an independent center of barley domestication. Wild barley (Hordeum vulgare ssp. spontaneum) populations from Southwest Asia, Central Asia, and Tibet along with domesticated barley from China were analyzed using two nuclear genes. Our results showed that Tibetan wild barley distinctly diverged from Southwest Asian (Near East) wild barley, that Central Asian wild barley is related to Southwest Asian wild barley, and that Chinese domesticated barley shares the same haplotypes with Tibetan wild barley. Phylogenetic analysis showed a close relationship between Chinese domesticated barley and the Tibetan wild barley, suggesting that Tibetan wild barley was the ancestor of Chinese domesticated barley. Our results favor the polyphyletic origin for cultivated barley.

The agronomic traits, including morphological and yield component traits, are important in barley breeding programs. In order to reveal the genetic foundation of agronomic traits of interest, in this study 122 doubled haploid lines from a cross between cultivars “Huaai 11” (six-rowed and dwarf) and “Huadamai 6” (two-rowed) were genotyped by 9680 SNPs and phenotyped 14 agronomic traits in 3 years, and the two datasets were used to conduct multi-locus genome-wide association studies. As a result, 913 quantitative trait nucleotides (QTNs) were identified by five multi-locus GWAS methods to be associated with the above 14 traits and their best linear unbiased predictions. Among these QTNs and their adjacent genes, 39 QTNs (or QTN clusters) were repeatedly detected in various environments and methods, and 10 candidate genes were identified from gene annotation. Nineteen QTNs and two genes (sdw1/denso and Vrs1) were previously reported, and eight candidate genes need to be further validated. The Vrs1 gene, controlling the number of rows in the spike, was found to be associated with spikelet number of main spike, spikelet number per plant, grain number per plant, grain number per spike, and 1,000 grain weight in multiple environments and by multi-locus GWAS methods. Therefore, the above results evidenced the feasibility and reliability of genome-wide association studies in doubled haploid population, and the QTNs and their candidate genes detected in this study are useful for marker-assisted selection breeding, gene cloning, and functional identification in barley.