Uncovering the genetic basis of agronomic traits in wheat landraces is important for ensuring global food security via the development of improved varieties. Here, 723 wheat landraces from 10 Chinese agro-ecological zones were evaluated for 23 agronomic traits in six environments. All accessions could be clustered into five subgroups based on phenotypic data via discriminant function analysis, which was highly consistent with genotypic classification. A genome-wide association study was conducted for these traits using 52 303 DArT-seq markers to identify marker-trait associations and candidate genes. Using both the general linear model and the mixed linear model, 149 significant markers were identified for 21 agronomic traits based on best linear unbiased prediction values. Considering the linkage disequilibrium decay distance in this study, significant markers within 10 cM were combined as a quantitative trait locus (QTL), with a total of 29 QTL identified for 15 traits. Of these, five QTL for heading date, flag leaf width, peduncle length, and thousand kernel weight had been reported previously. Twenty-five candidate genes associated with significant markers were identified. These included the known vernalization genes VRN-B1 and vrn-B3 and the photoperiod response genes Ppd and PRR. Overall, this study should be helpful in elucidating the underlying genetic mechanisms of complex agronomic traits and performing marker-assisted selection in wheat.
A high-density genetic map constructed with a wheat 55 K SNP array was highly consistent with the physical map of this species and it facilitated the identification of a novel major QTL for productive tiller number. Productive tiller number (PTN) plays a key role in wheat grain yield. In this study, a recombinant inbred line population with 199 lines derived from a cross between '20828' and 'Chuannong16' was used to construct a high-density genetic map using wheat 55 K single nucleotide polymorphism (SNP) array. The constructed genetic map contains 12,109 SNP markers spanning 3021.04 cM across the 21 wheat chromosomes. The orders of the genetic and physical positions of these markers are generally in agreement, and they also match well with those based on the 660 K SNP array from which the one used in this study was derived. The ratios of SNPs located in each of the wheat deletion bins were similar among the wheat 9 K, 55 K, 90 K, 660 K and 820 K SNP arrays. Based on the constructed maps, a novel major quantitative trait locus QPtn.sau-4B for PTN was detected across multi-environments in a 0.55 cM interval on 4B and it explained 17.23-45.46% of the phenotypic variance. Twenty common genes in the physical interval between the flanking markers were identified on chromosome 4B of 'Chinese Spring' and wild emmer. These results indicate that wheat 55 K SNP array could be an ideal tool in primary mapping of target genes and the identification of QPtn.sau-4B laid a foundation for the following fine mapping and cloning work.
Fusarium head blight (FHB) is a serious wheat disease all over the world. In this study, the relationships between plant height (PH) and FHB were investigated across the whole wheat genome by QTL meta-analysis from fifty-six experiments. Coincident meta-QTL (MQTL) for PH and FHB were found on chromosomes 2D, 3A, 4B, 4D and 7A. Rht-B1, Rht-D1, Rht8, MQTLs P7 and P26 were consistent with FHB MQTLs. The meta-analysis results confirmed the negative associations of Rht-B1, Rht-D1, and Rht8 with FHB resistance. The associations of PH and FHB resistance on chromosomes 3A and 7A have not been reported and need further investigation. These regions should be given attention in breeding programs. MQTLs derived from several resistance sources were also observed. Some FHB MQTLs for different types of resistance overlapped. These findings could be useful for improving wheat varieties with resistance to FHB.
The MADS-box genes encode transcription factors with key roles in plant growth and development. A comprehensive analysis of the MADS-box gene family in bread wheat (Triticum aestivum) has not yet been conducted, and our understanding of their roles in stress is rather limited. Here, we report the identification and characterization of the MADS-box gene family in wheat. A total of 180 MADS-box genes classified as 32 Mα, 5 Mγ, 5 Mδ, and 138 MIKC types were identified. Evolutionary analysis of the orthologs among T. urartu, Aegilops tauschii and wheat as well as homeologous sequences analysis among the three sub-genomes in wheat revealed that gene loss and chromosomal rearrangements occurred during and/or after the origin of bread wheat. Forty wheat MADS-box genes that were expressed throughout the investigated tissues and development stages were identified. The genes that were regulated in response to both abiotic stresses (i.e., phosphorus deficiency, drought, heat, and combined drought and heat) and biotic stresses (i.e., Fusarium graminearum, Septoria tritici, stripe rust and powdery mildew) were detected as well. A few notable MADS-box genes were specifically expressed in a single tissue and those showed relatively higher expression differences between the stress and control treatment. The expression patterns of considerable MADS-box genes differed from those of their orthologs in Brachypodium, rice, and Arabidopsis. Collectively, the present study provides new insights into the possible roles of MADS-box genes in response to stresses and will be valuable for further functional studies of important candidate MADS-box genes.
Background: Stripe rust is a serious fungal disease of wheat (Triticum aestivum L.) caused by Puccinia striiformis f. sp. tritici (Pst), which results in yield reduction and decreased grain quality. Breeding for genetic resistance to stripe rust is the most cost-effective method to control the disease. In the present study, a genome-wide association study (GWAS) was conducted to identify markers linked to stripe rust resistance genes (or loci) in 93 Northern Chinese wheat landraces, using Diversity Arrays Technology (DArT) and simple sequence repeat (SSR) molecular marker technology based on phenotypic data from two field locations over two growing seasons in China. Results: Seventeen accessions were verified to display stable and high levels of adult plant resistance (APR) to stripe rust via multi-environment field assessments. Significant correlations among environments and high heritability were observed for stripe rust infection type (IT) and disease severity (DS). Using mixed linear models (MLM) for the GWAS, a total of 32 significantly associated loci (P < 0.001) were detected. In combination with the linkage disequilibrium (LD) decay distance (6.4 cM), 25 quantitative trait loci (QTL) were identified. Based on the integrated map of previously reported genes and QTL, six QTL located on chromosomes 4A, 6A and 7D were mapped far from resistance regions identified previously, and represent potentially novel stripe rust resistance loci at the adult plant stage. Conclusions: The present findings demonstrated that identification of genes or loci linked to significant markers in wheat by GWAS is feasible. Seventeen elite accessions conferred with stable and high resistance to stripe rust, and six putative newly detected APR loci were identified among the 93 Northern Chinese wheat landraces. The results illustrate the potential for acceleration of molecular breeding of wheat, and also provide novel sources of stripe rust resistance with potential utility in the breeding of improved wheat cultivars.
SummaryWheat was introduced to China approximately 4500 years ago, where it adapted over a span of time to various environments in agro‐ecological growing zones. We investigated 717 Chinese and 14 Iranian/Turkish geographically diverse, locally adapted wheat landraces with 27 933 DArTseq (for 717 landraces) and 312 831 Wheat660K (for a subset of 285 landraces) markers. This study highlights the adaptive evolutionary history of wheat cultivation in China. Environmental stresses and independent selection efforts have resulted in considerable genome‐wide divergence at the population level in Chinese wheat landraces. In total, 148 regions of the wheat genome show signs of selection in at least one geographic area. Our data show adaptive events across geographic areas, from the xeric northwest to the mesic south, along and among homoeologous chromosomes, with fewer variations in the D genome than in the A and B genomes. Multiple variations in interdependent functional genes such as regulatory and metabolic genes controlling germination and flowering time were characterized, showing clear allelic frequency changes corresponding to the dispersion of wheat in China. Population structure and selection data reveal that Chinese wheat spread from the northwestern Caspian Sea region to South China, adapting during its agricultural trajectory to increasingly mesic and warm climatic areas.
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