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

Genome-Wide Association Mapping of Seedling Biomass and Root Traits Under Different Water Conditions in Wheat

Drought is a major threat to global wheat production. In this study, an association panel containing 200 Chinese wheat germplasms was used for genome-wide association studies (GWASs) of genetic loci associated with eight root and seedling biomass traits under normal water and osmotic stress conditions. The following traits were investigated in wheat seedlings at the four-leaf stage: root length (RL), root number (RN), root fresh weight (RFW), root dry weight (RDW), shoot fresh weight (SFW), shoot dry weight (SDW), total fresh weight (TFW), and total dry weight (TDW). A total of 323 and 286 SNPs were detected under two water environments, respectively. Some of these SNPs were near known loci for root traits. Eleven SNPs on chromosomes 1B, 2B, 4B, and 2D had pleiotropic effects on multiple traits under different water conditions. Further analysis indicated that several genes located inside the 4 Mb LD block on each side of these 11 SNPs were known to be associated with plant growth and development and thus may be candidate genes for these loci. Results from this study increased our understanding of the genetic architecture of root and seedling biomass traits under different water conditions and will facilitate the development of varieties with better drought tolerance.

Dissection of Genetic Basis Underpinning Kernel Weight-Related Traits in Common Wheat

Genetic dissection kernel weight-related traits is of great significance for improving wheat yield potential. As one of the three major yield components of wheat, thousand kernel weight (TKW) was mainly affected by grain length (GL) and grain width (GW). To uncover the key loci for these traits, we carried out a quantitative trait loci (QTL) analysis of an F₆ recombinant inbred lines (RILs) population derived from a cross of Henong 5290 (small grain) and 06Dn23 (big grain) with a 50 K single nucleotide polymorphism (SNP) array. A total of 17 stable and big effect QTL, including 5 for TKW, 8 for GL and 4 for GW, were detected on the chromosomes 1B, 2A, 2B, 2D, 4B, 5A, 6A and 6D, respectively. Among these, there were two co-located loci for three traits that were mapped on the chromosome 4BS and 6AL. The QTL on 6AL was the most stable locus and explained 15.4–24.8%, 4.1–8.8% and 15.7–24.4% of TKW, GW and GL variance, respectively. In addition, two more major QTL of GL were located on chromosome arm 2BL and 2DL, accounting for 9.7–17.8% and 13.6–19.8% of phenotypic variance, respectively. In this study, we found one novel co-located QTL associated with GL and TKW in 2DL, QGl.haaf-2DL.2/QTkw.haaf-2DL.2, which could explain 13.6–19.8% and 9.8–10.7% phenotypic variance, respectively. Genetic regions and linked markers of these stable QTL will help to further refine mapping of the corresponding loci and marker-assisted selection (MAS) breeding for wheat grain yield potential improvement.

Predominant wheat-alien chromosome translocations in newly developed wheat of China

Founder wheat lines have played key role in Chinese wheat improvement. Wheat-Dasypyrum villosum translocation T6VS·6AL has been widely used in wheat breeding in recent years due to its high level of powdery mildew resistance and other beneficial genes. Reference oligo-nucleotide multiplex probe (ONMP)-FISH karyotypes of six T6VS·6AL donor lines were developed and used for characterizing 32 derivative cultivars and lines. T6VS·6AL was present in 27 cultivar/lines with 20 from southern China. Next, ONMP-FISH was used to study chromosome constitution of randomly collected wheat cultivars and advanced breeding lines from southern and northern regions of China: 123 lines from the regional test plots of southern China and 110 from northern China. In southern China, T6VS·6AL (35.8%) was the most predominant variation, while T1RS·1BL (27.3%) was the most predominant in northern China. The pericentric inversion perInv 6B derived from its founder wheat Funo and Abbondaza was the second most predominant chromosome variant in both regions. Other chromosome variants were present in very low frequencies. Additionally, 167 polymorphic chromosome types were identified. Based on these variations, 271 cultivars and lines were clustered into three groups, including southern, northern, and mixed groups that contained wheat from both regions. Different dominant chromosome variations were seen, indicating chromosome differentiation in the three groups of wheat. The clearly identified wheat lines with T6VS·6AL in different backgrounds and oligonucleotide probe set will facilitate their utilization in wheat breeding and in identifying other beneficial traits that may be linked to this translocation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01206-3.

Genome-wide association study reveals the genetic basis of yield- and quality-related traits in wheat

BACKGROUND

Identifying the loci and dissecting the genetic architecture underlying wheat yield- and quality-related traits are essential for wheat breeding. A genome-wide association study was conducted using a high-density 90 K SNP array to analyze the yield- and quality-related traits of 543 bread wheat varieties.

RESULTS

A total of 11,140 polymorphic SNPs were distributed on 21 chromosomes, including 270 significant SNPs associated with 25 yield- and quality-related traits. Additionally, 638 putative candidate genes were detected near the significant SNPs based on BLUP data, including three (TraesCS7A01G482000, TraesCS4B01G343700, and TraesCS6B01G295400) related to spikelet number per spike, diameter of the first internode, and grain volume. The three candidate genes were further analyzed using stage- and tissue- specific gene expression data derived from an RNA-seq analysis. These genes are promising candidates for enhancing yield- and quality-related traits in wheat.

CONCLUSIONS

The results of this study provide a new insight to understand the genetic basis of wheat yield and quality. Furthermore, the markers detected in this study may be applicable for marker-assisted selection in wheat breeding programs.

Utilization of a Wheat55K SNP array-derived high-density genetic map for high-resolution mapping of quantitative trait loci for important kernel-related traits in common wheat

This study mapped QTLs associated with kernel-related traits by high-density genetic map. Five new major and stable QTLs for KL, KDR, SN, and KWPS were mapped in multiple environments. In the present study, a recombinant inbred line population including 371 lines derived from the cross of Chuannong18 and T1208 was genotyped using the Wheat55K single nucleotide polymorphism array. A novel high-density genetic map consisting of 11,583 markers spanning 4192.62 cM and distributed across 21 wheat chromosomes was constructed. QTLs for important kernel-related traits were mapped in multiple environments. A total of 96 and 151 QTLs were mapped by using the ICIM method and the MET method, respectively. And a total of 114 digenic epistatic QTLs were also detected across 21 chromosomes, and the epistatic effects of each trait were analyzed. BLAST analysis showed that 23 QTLs for different kernel-related traits were first time mapped and five of them were major and stable QTLs for kernel diameter ratio (121.34-126.83 cM on 4BS), spike number per square meter (71.32-73.84 cM on 2DS), kernel weight per spike (71.32-75.26 cM on 2DS), and kernel length (16.78-31.64 cM on 6A and 51.63-58.40 cM on 3D), respectively. Fifteen QTL clusters that contained 58 QTLs were also detected, and all most stable QTLs were contained in these QTL clusters. Significant correlations between different traits were detected and discussed. These results lay the foundation for fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

Genetic Mapping by Integration of 55K SNP Array and KASP Markers Reveals Candidate Genes for Important Agronomic Traits in Hexaploid Wheat

Agronomic traits such as heading date (HD), plant height (PH), thousand grain weight (TGW), and spike length (SL) are important factors affecting wheat yield. In this study, we constructed a high-density genetic linkage map using the Wheat55K SNP Array to map quantitative trait loci (QTLs) for these traits in 207 recombinant inbred lines (RILs). A total of 37 QTLs were identified, including 9 QTLs for HD, 7 QTLs for PH, 12 QTLs for TGW, and 9 QTLs for SL, which explained 3.0-48.8% of the phenotypic variation. Kompetitive Allele Specific PCR (KASP) markers were developed based on sequencing data and used for validation of the stably detected QTLs on chromosomes 3A, 4B and 6A using 400 RILs. A QTL cluster on chromosome 4B for PH and TGW was delimited to a 0.8 Mb physical interval explaining 12.2-22.8% of the phenotypic variation. Gene annotations and analyses of SNP effects suggested that a gene encoding protein Photosynthesis Affected Mutant 68, which is essential for photosystem II assembly, is a candidate gene affecting PH and TGW. In addition, the QTL for HD on chromosome 3A was narrowed down to a 2.5 Mb interval, and a gene encoding an R3H domain-containing protein was speculated to be the causal gene influencing HD. The linked KASP markers developed in this study will be useful for marker-assisted selection in wheat breeding, and the candidate genes provide new insight into genetic study for those traits in wheat.

Genome-wide association study of yield and related traits in common wheat under salt-stress conditions

BACKGROUND

Soil salinization is a major threat to wheat production. It is essential to understand the genetic basis of salt tolerance for breeding and selecting new salt-tolerant cultivars that have the potential to increase wheat yield.

RESULT

In this study, a panel of 191 wheat accessions was subjected to genome wide association study (GWAS) to identify SNP markers linked with adult-stage characters. The population was genotyped by Wheat660K SNP array and eight phenotype traits were investigated under low and high salinity environments for three consecutive years. A total of 389 SNPs representing 11 QTLs were significantly associated with plant height, spike number, spike length, grain number, thousand kernels weight, yield and biological mass under different salt treatments, with the phenotypic explanation rate (R²) ranging from 9.14 to 50.45%. Of these, repetitive and pleiotropic loci on chromosomes 4A, 5A, 5B and 7A were significantly linked to yield and yield related traits such as thousand kernels weight, spike number, spike length, grain number and so on under low salinity conditions. Spike length-related loci were mainly located on chromosomes 1B, 3B, 5B and 7A under different salt treatments. Two loci on chromosome 4D and 5A were related with plant height in low and high salinity environment, respectively. Three salt-tolerant related loci were confirmed to be important in two bi-parental populations. Distribution of favorable haplotypes indicated that superior haplotypes of pleiotropic loci on group-5 chromosomes were strongly selected and had potential for increasing wheat salt tolerance. A total of 14 KASP markers were developed for nine loci associating with yield and related traits to improve the selection efficiency of wheat salt-tolerance breeding.

CONCLUSION

Utilizing a Wheat660K SNPs chip, QTLs for yield and its related traits were detected under salt treatment in a natural wheat population. Important salt-tolerant related loci were validated in RIL and DH populations. This study provided reliable molecular markers that could be crucial for marker-assisted selection in wheat salt tolerance breeding programs.

Mapping QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population

QTL for 15 agronomic traits under two levels of salt stress in dry salinity field were mapped in a new constructed RIL population utilizing a Wheat55K SNP array. Furthermore, eight QTL were validated in a collected natural population. Soil salinity is one of the major abiotic stresses causing serious impact on crop growth, development and yield. As one of the three most important crops in the world, bread wheat (Triticum aestivum L.) is severely affected by salinity, too. In this study, an F₇ recombinant inbred line (RIL) population derived from a cross between high-yield wheat cultivar Zhongmai 175 and salt-tolerant cultivar Xiaoyan 60 was constructed. The adult stage performances of the RIL population and their parent lines under low and high levels of salt stress were evaluated for three consecutive growing seasons. Utilizing a Wheat55K SNP array, a high-density genetic linkage map spinning 3250.71 cM was constructed. QTL mapping showed that 90 stable QTL for 15 traits were detected, and they were distributed on all wheat chromosomes except 4D, 6B and 7D. These QTL individually explained 2.34-32.43% of the phenotypic variation with LOD values ranging from 2.68 to 47.15. It was found that four QTL clusters were located on chromosomes 2D, 3D, 4B and 6A, respectively. Notably, eight QTL from the QTL clusters were validated in a collected natural population. Among them, QPh-4B was deduced to be an allele of Rht-B1. In addition, three kompetitive allele-specific PCR (KASP) markers derived from SNPs were successfully designed for three QTL clusters. This study provides an important base for salt-tolerant QTL (gene) cloning in wheat, and the markers, especially the KASP markers, will be useful for marker-assisted selection in salt-tolerant wheat breeding.

QTL Mapping and Validation for Kernel Area and Circumference in Common Wheat via High-Density SNP-Based Genotyping

As an important component, 1,000 kernel weight (TKW) plays a significant role in the formation of yield traits of wheat. Kernel size is significantly positively correlated to TKW. Although numerous loci for kernel size in wheat have been reported, our knowledge on loci for kernel area (KA) and kernel circumference (KC) remains limited. In the present study, a recombinant inbred lines (RIL) population containing 371 lines genotyped using the Wheat55K SNP array was used to map quantitative trait loci (QTLs) controlling the KA and KC in multiple environments. A total of 54 and 44 QTLs were mapped by using the biparental population or multienvironment trial module of the inclusive composite interval mapping method, respectively. Twenty-two QTLs were considered major QTLs. BLAST analysis showed that major and stable QTLs QKc.sau-6A.1 (23.12-31.64 cM on 6A) for KC and QKa.sau-6A.2 (66.00-66.57 cM on 6A) for KA were likely novel QTLs, which explained 22.25 and 20.34% of the phenotypic variation on average in the 3 year experiments, respectively. Two Kompetitive allele-specific PCR (KASP) markers, KASP-AX-109894590 and KASP-AX-109380327, were developed and tightly linked to QKc.sau-6A.1 and QKa.sau-6A.2, respectively, and the genetic effects of the different genotypes in the RIL population were successfully confirmed. Furthermore, in the interval where QKa.sau-6A.2 was located on Chinese Spring and T. Turgidum ssp. dicoccoides reference genomes, only 11 genes were found. In addition, digenic epistatic QTLs also showed a significant influence on KC and KA. Altogether, the results revealed the genetic basis of KA and KC and will be useful for the marker-assisted selection of lines with different kernel sizes, laying the foundation for the fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

Molecular Mapping and Genomics of Grain Yield in Durum Wheat: A Review

Durum wheat is the most relevant cereal for the whole of Mediterranean agriculture, due to its intrinsic adaptation to dryland and semi-arid environments and to its strong historical cultivation tradition. It is not only relevant for the primary production sector, but also for the food industry chains associated with it. In Mediterranean environments, wheat is mostly grown under rainfed conditions and the crop is frequently exposed to environmental stresses, with high temperatures and water scarcity especially during the grain filling period. For these reasons, and due to recurrent disease epidemics, Mediterranean wheat productivity often remains under potential levels. Many studies, using both linkage analysis (LA) and a genome-wide association study (GWAS), have identified the genomic regions controlling the grain yield and the associated markers that can be used for marker-assisted selection (MAS) programs. Here, we have summarized all the current studies identifying quantitative trait loci (QTLs) and/or candidate genes involved in the main traits linked to grain yield: kernel weight, number of kernels per spike and number of spikes per unit area.

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

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.

Identification of the vernalization gene VRN-B1 responsible for heading date variation by QTL mapping using a RIL population in wheat

BACKGROUND

Heading time is one of the most important agronomic traits in wheat, as it largely affects both adaptation to different agro-ecological conditions and yield potential. Identification of genes underlying the regulation of wheat heading and the development of diagnostic markers could facilitate our understanding of genetic control of this process.

RESULTS

In this study, we developed 400 recombinant inbred lines (RILs) by crossing a γ-ray-induced early heading mutant (eh1) with the late heading cultivar, Lunxuan987. Bulked Segregant Analysis (BSA) of both RNA and DNA pools consisting of various RILs detected a quantitative trait loci (QTL) for heading date located on chromosomes 5B, and further genetic linkage analysis limited the QTL to a 3.31 cM region. We then identified a large deletion in the first intron of the vernalization gene VRN-B1 in eh1, and showed it was associated with the heading phenotype in the RIL population. However, it is not the mutation loci that resulted in early heading phonotype in the mutant compared to that of wildtype. RNA-seq analysis suggested that Vrn-B3 and several newly discovered genes, including beta-amylase 1 (BMY1) and anther-specific protein (RTS), were highly expressed in both the mutant and early heading pool with the dominant Vrn-B1 genotype compared to that of Lunxuan987 and late heading pool. Enrichment analysis of differentially expressed genes (DEGs) identified several key pathways previously reported to be associated with flowering, including fatty acid elongation, starch and sucrose metabolism, and flavonoid biosynthesis.

CONCLUSION

The development of new markers for Vrn-B1 in this study supplies an alternative solution for marker-assisted breeding to optimize heading time in wheat and the DEGs analysis provides basic information for VRN-B1 regulation study.

Characterization of a major quantitative trait locus on the short arm of chromosome 4B for spike number per unit area in common wheat (Triticum aestivum L.)

An InDel marker closely linked with a major and stable quantitative trait locus (QTL) on chromosome 4BS, QSnpa.cau-4B, controlling spike number per unit area will benefit wheat yield improvement. Spike number per unit area (SNPA) is an essential yield-related trait, and analyzing its genetic basis is important for cultivar improvement in wheat (Triticum aestivum L.). In this study, we used the F₂ population derived from a cross between two wheat accessions displaying significant differences in SNPA to perform quantitative trait locus (QTL) analysis. Through bulked segregant analysis, a major and stable QTL that explained 18.11-82.11% of the phenotypic variation was identified on chromosome 4BS. The QTL interval was validated using F_4:5 and F_6:7 families and narrowed it to a 24.91-38.36 Mb region of chromosome 4BS according to the 'Chinese Spring' reference genome sequence. In this region, variations in 16 genes caused amino acid changes and three genes were present in only one parent. Among these, we annotated a gene orthologous to TB1 in maize (Zea mays), namely TraesCS4B01G042700, which carried a 44-bp deletion in its promoter in the higher-SNPA parent. An InDel marker based on the insertion/deletion polymorphism was designed and used to diagnose the allelic distribution within a natural population. The frequency of the 44-bp deletion allele associated with higher SNPA was relatively low (13.24%), implying that this favorable allele has not been widely utilized and could be valuable for wheat yield improvement. In summary, we identified a major and stable QTL for SNPA and developed a diagnostic marker for the more-spiked trait, which will be beneficial for molecular-assisted breeding in wheat.

Genetic architecture underpinning yield component traits in wheat

Genetic atlas, reliable QTL and candidate genes of yield component traits in wheat were figured out, laying concrete foundations for map-based gene cloning and dissection of regulatory mechanisms underlying yield. Mining genetic loci for yield is challenging due to the polygenic nature, large influence of environment and complex relationship among yield component traits (YCT). Many genetic loci related to wheat yield have been identified, but its genetic architecture and key genetic loci for selection are largely unknown. Wheat yield potential can be determined by three YCT, thousand kernel weight, kernel number per spike and spike number. Here, we summarized the genetic loci underpinning YCT from QTL mapping, association analysis and homology-based gene cloning. The major loci determining yield-associated agronomic traits, such as flowering time and plant height, were also included in comparative analyses with those for YCT. We integrated yield-related genetic loci onto chromosomes based on their physical locations. To identify the major stable loci for YCT, 58 QTL-rich clusters (QRC) were defined based on their distribution on chromosomes. Candidate genes in each QRC were predicted according to gene annotation of the wheat reference genome and previous information on validation of those genes in other species. Finally, a technological route was proposed to take full advantage of the resultant resources for gene cloning, molecular marker-assisted breeding and dissection of molecular regulatory mechanisms underlying wheat yield.

Mapping Quantitative Trait Loci for 1000-Grain Weight in a Double Haploid Population of Common Wheat

Thousand-grain weight (TGW) is a very important yield trait of crops. In the present study, we performed quantitative trait locus (QTL) analysis of TGW in a doubled haploid population obtained from a cross between the bread wheat cultivar "Superb" and the breeding line "M321" using the wheat 55-k single-nucleotide polymorphism (SNP) genotyping assay. A genetic map containing 15,001 SNP markers spanning 2209.64 cM was constructed, and 9 QTLs were mapped to chromosomes 1A, 2D, 4B, 4D, 5A, 5D, 6A, and 6D based on analyses conducted in six experimental environments during 2015-2017. The effects of the QTLs qTgw.nwipb-4DS and qTgw.nwipb-6AL were shown to be strong and stable in different environments, explaining 15.31-32.43% and 21.34-29.46% of the observed phenotypic variance, and they were mapped within genetic distances of 2.609 cM and 5.256 cM, respectively. These novel QTLs may be used in marker-assisted selection in wheat high-yield breeding.

Linking fundamental science to crop improvement through understanding source and sink traits and their integration for yield enhancement

Understanding processes in sources and sinks that contribute to crop yields has taken years of painstaking research. For crop yield improvement, processes need to be understood as standalone mechanisms in addition to how these mechanisms perform at the crop level; currently there is often a chasm between the two. Fundamental mechanisms need to be considered in the context of crop ideotypes and the agricultural environment which is often more water limited than carbon limited. Different approaches for improvement should be considered, namely is there genetic variation? Or if not, could genetic modification, genome editing, or alternative approaches be utilized? Currently, there are few examples where genetic modification has improved intrinsic yield in the field for commercial application in a major crop. Genome editing, particularly of negative yield regulators as a first step, is providing new opportunities. Here we highlight key mechanisms in source and sink, arguing that for large yield increases integration of key processes is likely to produce the biggest successes within the framework of crop ideotypes with optimized phenology. We highlight a plethora of recent papers that show breakthroughs in fundamental science and the promise of the trehalose 6-phosphate signalling pathway, which regulates carbohydrate allocation which is key for many crop traits.

QTL mapping for quality traits using a high-density genetic map of wheat

Protein- and starch-related quality traits, which are quantitatively inherited and significantly influenced by the environment, are critical determinants of the end-use quality of wheat. We constructed a high-density genetic map containing 10,739 loci (5,399 unique loci) using a set of 184 recombinant inbred lines (RILs) derived from a cross of 'Tainong 18 × Linmai 6' (TL-RILs). In this study, a quantitative trait loci (QTLs) analysis was used to examine the genetic control of grain protein content, sedimentation value, farinograph parameters, falling number and the performance of the starch pasting properties using TL-RILs grown in a field for three years. A total of 106 QTLs for 13 quality traits were detected, distributed on the 21 chromosomes. Of these, 38 and 68 QTLs for protein- and starch-related traits, respectively, were detected in three environments and their average values (AV). Twenty-six relatively high-frequency QTLs (RHF-QTLs) that were detected in more than two environments. Twelve stable QTL clusters containing at least one RHF-QTL were detected and classified into three types: detected only for protein-related traits (type I), detected only for starch-related traits (type II), and detected for both protein- and starch-related traits (type III). A total of 339 markers flanked with 11 QTL clusters (all except C6), were found to be highly homologous with 282 high confidence (HC) and 57 low confidence (LC) candidate genes based on IWGSC RefSeq v 1.0. These stable QTLs and RHF-QTLs, especially those grouped into clusters, are credible and should be given priority for QTL fine-mapping and identification of candidate genes with which to explain the molecular mechanisms of quality development and inform marker-assisted breeding in the future.

QTL mapping for grain yield-related traits in bread wheat via SNP-based selective genotyping

We identified four chromosome regions harboring QTL for grain yield-related traits, and breeder-friendly KASP markers were developed and validated for marker-assisted selection. Identification of major stable quantitative trait loci (QTL) for grain yield-related traits is important for yield potential improvement in wheat breeding. In the present study, 266 recombinant inbred lines (RILs) derived from a cross between Zhongmai 871 (ZM871) and its sister line Zhongmai 895 (ZM895) were evaluated for thousand grain weight (TGW), grain length (GL), grain width (GW), and grain number per spike (GNS) in 10 environments and for grain filling rate in six environments. Sixty RILs, with 30 higher and 30 lower TGW, respectively, were genotyped using the wheat 660 K SNP array for preliminary QTL mapping. Four genetic regions on chromosomes 1AL, 2BS, 3AL, and 5B were identified to have a significant effect on TGW-related traits. A set of Kompetitive Allele Specific PCR markers were converted from the SNP markers on the above target chromosomes and used to genotype all 266 RILs. The mapping results confirmed the QTL named Qgw.caas-1AL, Qgl.caas-3AL, Qtgw.caas-5B, and Qgl.caas-5BS on the targeted chromosomes, explaining 5.0-20.6%, 5.7-15.7%, 5.5-17.3%, and 12.5-20.5% of the phenotypic variation for GW, GL, TGW, and GL, respectively. A novel major QTL for GNS on chromosome 5BS, explaining 5.2-15.2% of the phenotypic variation, was identified across eight environments. These QTL were further validated using BC₁F₄ populations derived from backcrosses ZM871/ZM895//ZM871 (121 lines) and ZM871/ZM895//ZM895 (175 lines) and 186 advanced breeding lines. Collectively, selective genotyping is a simple, economic, and effective approach for rapid QTL mapping and can be generally applied to genetic mapping studies for important agronomic traits.

QTL mapping for yield-related traits in wheat based on four RIL populations

Eight environmentally stable QTL for grain yield-related traits were detected by four RIL populations, and two of them were validated by a natural wheat population containing 580 diverse varieties or lines. Yield and yield-related traits are important factors in wheat breeding. In this study, four RIL populations derived from the cross of one common parent Yanzhan 1 (a Chinese domesticated cultivar) and four donor parents including Hussar (a British domesticated cultivar) and three semi-wild wheat varieties in China were phenotyped for 11 yield-related traits in eight environments. An integrated genetic map containing 2009 single-nucleotide polymorphism (SNP) markers generated from a 90 K SNP array was constructed to conduct quantitative trait loci (QTL) analysis. A total of 161 QTL were identified, including ten QTL for grain yield per plant (GYP) and yield components, 49 QTL for spike-related traits, 43 QTL for flag leaf-related traits, 22 QTL for plant height (PH), and 37 QTL for heading date and flowering date. Eight environmentally stable QTL were validated in individual RIL population where the target QTL was notably detected, and six of them had a significant effect on GYP. Furthermore, Two QTL, QSPS-2A.4 and QSL-4A.1, were also validated in a natural wheat population containing 580 diverse varieties or lines, which provided valuable resources for further fine mapping and genetic improvement in yield in wheat.

SNP-based association study of kernel architecture in a worldwide collection of durum wheat germplasm

Durum wheat, genetic resource with favorable alleles is considered as natural gene pool for wheat breeding. Kernel size and weight are important factors affecting grain yield in crops. Here, association analysis was performed to dissect the genetic constitution of kernel-related traits in 150 lines collected from 46 countries and regions using a set of EST-derived and genome-wide SNP markers with five consecutive years of data. Total 109 significant associations for eight kernel-related traits were detected under a mix linear model, generating 54 unique SNP markers distributed on 13 of 14 chromosomes. Of which, 19 marker-trait associations were identified in two or more environments, including one stable and pleiotropic SNP BE500291_5_A_37 on chromosome 5A correlated with six kernel traits. Although most of our SNP loci were overlapped with the previously known kernel weight QTLs, several novel loci for kernel traits in durum were reported. Correlation analysis implied that the moderate climatic variables during growth and development of durum are needed for the large grain size and high grain weight. Combined with our previous studies, we found that chromosome 5A might play an important role in durum growth and development.

Rapid identification and characterization of genetic loci for defective kernel in bread wheat

BACKGROUND

Wheat is a momentous crop and feeds billions of people in the world. The improvement of wheat yield is very important to ensure world food security. Normal development of grain is the essential guarantee for wheat yield formation. The genetic study of grain phenotype and identification of key genes for grain filling are of great significance upon dissecting the molecular mechanism of wheat grain morphogenesis and yield potential.

RESULTS

Here we identified a pair of defective kernel (Dek) isogenic lines, BL31 and BL33, with plump and shrunken mature grains, respectively, and constructed a genetic population from the BL31/BL33 cross. Ten chromosomes had higher frequency of polymorphic single nucleotide polymorphism (SNP) markers between BL31 and BL33 using Wheat660K chip. Totally 783 simple sequence repeat (SSR) markers were chosen from the above chromosomes and 15 of these were integrated into two linkage groups using the genetic population. Genetic mapping identified three QTL, QDek.caas-3BS.1, QDek.caas-3BS.2 and QDek.caas-4AL, explaining 14.78-18.17%, 16.61-21.83% and 19.08-28.19% of phenotypic variances, respectively. Additionally, five polymorphic SNPs from Wheat660K were successfully converted into cleaved amplified polymorphic sequence (CAPS) markers and enriched the target regions of the above QTL. Biochemical analyses revealed that BL33 has significantly higher grain sucrose contents at filling stages and lower mature grain starch contents than BL31, indicating that the Dek QTL may be involved in carbohydrate metabolism. As such, the candidate genes for each QTL were predicated according to International Wheat Genome Sequence Consortium (IWGSC) RefSeq v1.0.

CONCLUSIONS

Three major QTL for Dek were identified and their causal genes were predicted, laying a foundation to conduct fine mapping and dissect the regulatory mechanism underlying Dek trait in wheat.

Agronomic and Physiological Traits, and Associated Quantitative Trait Loci (QTL) Affecting Yield Response in Wheat (Triticum aestivum L.): A Review

Enhanced grain yield has been achieved in bread wheat (Triticum aestivum L.) through development and cultivation of superior genotypes incorporating yield-related agronomic and physiological traits derived from genetically diverse and complementary genetic pool. Despite significant breeding progress, yield levels in wheat have remained relatively low and stagnant under marginal growing environments. There is a need for genetic improvement of wheat using yield-promoting morpho-physiological attributes and desired genotypes under the target production environments to meet the demand for food and feed. This review presents breeding progress in wheat for yield gains using agronomic and physiological traits. Further, the paper discusses globally available wheat genetic resources to identify and select promising genotypes possessing useful agronomic and physiological traits to enhance water, nutrient-, and radiation-use efficiency to improve grain yield potential and tolerance to abiotic stresses (i.e. elevated CO2, high temperature, and drought stresses). Finally, the paper highlights quantitative trait loci (QTL) linked to agronomic and physiological traits to aid breeding of high-performing wheat genotypes.

Genetic dissection of a major QTL for kernel weight spanning the Rht-B1 locus in bread wheat

Genetic dissection uncovered a major QTL QTKW.caas-4BS corresponding with a 483 kb deletion that included genes ZnF, EamA and Rht-B1. This deletion was associated with increased grain weight and semi-dwarf phenotype. Previous studies identified quantitative trait loci (QTL) for thousand kernel weight (TKW) in the region spanning the Rht-B1 locus in wheat (Triticum aestivum L.). We recently mapped a major QTL QTKW.caas-4BS for TKW spanning the Rht-B1 locus in a recombinant inbred line (RIL) population derived from Doumai/Shi 4185 using the wheat 90K array. The allele from Doumai at QTKW.caas-4BS significantly increased TKW and kernel number per spike, and conferred semi-dwarf trait, which was beneficial to improve grain yield without a penalty to lodging. To further dissect QTKW.caas-4BS, we firstly re-investigated the genotypes and phenotypes of the RILs and confirmed the QTL using cleaved amplified polymorphic sequence (CAPS) markers developed from flanking SNP markers IWA102 and IWB54814. The target sequences of the CAPS markers were used as queries to BLAST the wheat reference genome RefSeq v1.0 and hit an approximate 10.4 Mb genomic region. Based on genomic mining and SNP loci from the wheat 660K SNP array in the above genomic region, we developed eight new markers and narrowed QTKW.caas-4BS to a genetic interval of 1.5 cM. A 483 kb deletion in Doumai corresponded with QTKW.caas-4BS genetically, including three genes ZnF, EamA and Rht-B1. The other 15 genes with either differential expressions and/or sequence variations between parents were also potential candidate genes for QTKW.caas-4BS. The findings not only provide a toolkit for marker-assisted selection of QTKW.caas-4BS but also defined candidate genes for further functional analysis.

Dissection of loci conferring resistance to stripe rust in Chinese wheat landraces from the middle and lower reaches of the Yangtze River via genome-wide association study

Stripe rust (Yr), caused by the fungal pathogen Puccinia striiformis f. sp. tritici, is a devastating foliar disease of wheat in China. Chinese wheat landraces originating from the middle and lower reaches of the Yangtze River are potential stripe-rust resistance resources. To identify APR genes for stripe-rust resistance, a panel of 188 accessions derived from the middle and lower reaches of the Yangtze River were inoculated with a mixture of Chinese P. striiformis f. sp. tritici races and resistance evaluated under field conditions in five environments at adult-plant stages. Seventy-three accessions showed degrees of stable resistance. Combining phenotypic datasets from multiple field experiments with high-quality Diversity Arrays Technology and simple sequence repeat markers, we detected 21 marker-trait associations spanning 18 quantitative trait loci (QTLs) on chromosomes 1B, 2A, 2B, 3B, 4A, 5A, 5B, 6B, and 6D, respectively. Single QTLs explained 9.67% to 16.14% of the observed phenotypic variation. Nine QTLs co-localized with previously reported Yr genes or genomic regions. The remaining QTLs were potential novel loci associated with adult-stage stripe-rust resistance. Two novel QTLs, QYr.sicau-3B.2 and QYr.sicau-5B.3, located on chromosomes 3B and 5B significantly explained 16.14% and 11.16% of the phenotypic variation, respectively. Haplotype analysis revealed that accessions carrying APR variants or their combinations showed enhanced degrees of resistance. The potentially novel loci or genomic regions associated with adult-stage resistance may be useful to improve stripe-rust resistance in current wheat cultivars and for future isolation of stripe-rust resistance genes.

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.