Novel function of a putative TaCOBL ortholog associated with cold response.

The plant COBRA protein family plays an important role in secondary cell wall biosynthesis and the orientation of cell expansion. The COBRA gene family has been well studied in Arabidopsis thaliana, maize, rice, etc., but no systematic studies were conducted in wheat. In this study, the full-length sequence of TaCOBLs was obtained by homology cloning from wheat, and a conserved motif analysis confirmed that TaCOBLs belonged to the COBRA protein family. qRT-PCR results showed that the TaCOBL transcripts were induced by abiotic stresses, including cold, drought, salinity, and abscisic acid (ABA). Two haplotypes of TaCOBL-5B (Hap5B-a and Hap5B-b), harboring one indel (----/TATA) in the 5' flanking region (- 550 bp), were found on chromosome 5BS. A co-dominant marker, Ta5BF/Ta5BR, was developed based on the polymorphism of the two TaCOBL-5B haplotypes. Significant correlations between the two TaCOBL-5B haplotypes and cold resistance were observed under four environmental conditions. Hap5B-a, a favored haplotype acquired during wheat polyploidization, may positively contribute to enhanced cold resistance in wheat. Based on the promoter activity analysis, the Hap5B-a promoter containing a TATA-box was more active than that of Hap5B-b without the TATA-box under low temperature. Our study provides valuable information indicating that the TaCOBL genes are associated with cold response in wheat.

Development and validation of high-throughput and low-cost STARP assays for genes underpinning economically important traits in wheat.

KEY MESSAGE: We developed and validated 56 gene-specific semi-thermal asymmetric reverse PCR (STARP) markers for 46 genes of important wheat quality, biotic and abiotic stress resistance, grain yield, and adaptation-related traits for marker-assisted selection in wheat breeding. Development of high-throughput, low-cost, gene-specific molecular markers is important for marker-assisted selection in wheat breeding. In this study, we developed 56 gene-specific semi-thermal asymmetric reverse PCR (STARP) markers for wheat quality, tolerance to biotic and abiotic stresses, grain yield, and adaptation-related traits. The STARP assays were validated by (1) comparison of the assays with corresponding diagnostic STS/CAPS markers on 40 diverse wheat cultivars and (2) characterization of allelic effects based on the phenotypic and genotypic data of three segregating populations and 305 diverse wheat accessions from China and 13 other countries. The STARP assays showed the advantages of high-throughput, accuracy, flexibility, simple assay design, low operational costs, and platform compatibility. The state-of-the-art assays of this study provide a robust and reliable molecular marker toolkit for wheat breeding programs.

Genetic architecture of grain yield in bread wheat based on genome-wide association studies.

BACKGROUND: Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits. RESULTS: A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4-725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS. CONCLUSIONS: The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers.

KEY MESSAGE: We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

Genome-wide association mapping of black point reaction in common wheat (Triticum aestivum L.).

BACKGROUND: Black point is a serious threat to wheat production and can be managed by host resistance. Marker-assisted selection (MAS) has the potential to accelerate genetic improvement of black point resistance in wheat breeding. We performed a genome-wide association study (GWAS) using the high-density wheat 90 K and 660 K single nucleotide polymorphism (SNP) assays to better understand the genetic basis of black point resistance and identify associated molecular markers. RESULTS: Black point reactions were evaluated in 166 elite wheat cultivars in five environments. Twenty-five unique loci were identified on chromosomes 2A, 2B, 3A, 3B (2), 3D, 4B (2), 5A (3), 5B (3), 6A, 6B, 6D, 7A (5), 7B and 7D (2), respectively, explaining phenotypic variation ranging from 7.9 to 18.0%. The highest number of loci was detected in the A genome (11), followed by the B (10) and D (4) genomes. Among these, 13 were identified in two or more environments. Seven loci coincided with known genes or quantitative trait locus (QTL), whereas the other 18 were potentially novel loci. Linear regression showed a clear dependence of black point scores on the number of favorable alleles, suggesting that QTL pyramiding will be an effective approach to increase resistance. In silico analysis of sequences of resistance-associated SNPs identified 6 genes possibly involved in oxidase, signal transduction and stress resistance as candidate genes involved in black point reaction. CONCLUSION: SNP markers significantly associated with black point resistance and accessions with a larger number of resistance alleles can be used to further enhance black point resistance in breeding. This study provides new insights into the genetic architecture of black point reaction.

A Genome-Wide Association Study Reveals a Rich Genetic Architecture of Flour Color-Related Traits in Bread Wheat.

Flour color-related traits, including brightness (L*), redness (a*), yellowness (b*) and yellow pigment content (YPC), are very important for end-use quality of wheat. Uncovering the genetic architecture of these traits is necessary for improving wheat quality by marker-assisted selection (MAS). In the present study, a genome-wide association study (GWAS) was performed on a collection of 166 bread wheat cultivars to better understand the genetic architecture of flour color-related traits using the wheat 90 and 660 K SNP arrays, and 10 allele-specific markers for known genes influencing these traits. Fifteen, 28, 25, and 32 marker-trait associations (MTAs) for L*, a*, b*, and YPC, respectively, were detected, explaining 6.5-20.9% phenotypic variation. Seventy-eight loci were consistent across all four environments. Compared with previous studies, Psy-A1, Psy-B1, Pinb-D1, and the 1B•1R translocation controlling flour color-related traits were confirmed, and four loci were novel. Two and 11 loci explained much more phenotypic variation of a* and YPC than phytoene synthase 1 gene (Psy1), respectively. Sixteen candidate genes were predicted based on biochemical information and bioinformatics analyses, mainly related to carotenoid biosynthesis and degradation, terpenoid backbone biosynthesis and glycolysis/gluconeogenesis. The results largely enrich our knowledge of the genetic basis of flour color-related traits in bread wheat and provide valuable markers for wheat quality improvement. The study also indicated that GWAS was a powerful strategy for dissecting flour color-related traits and identifying candidate genes based on diverse genotypes and high-throughput SNP arrays.