Mapping QTLs of yield-related traits using RIL population derived from common wheat and Tibetan semi-wild wheat

Natural allelic variation confers diversity in the regulation of flag leaf traits in wheat

Flag leaf (FL) dimension has been reported as a key ecophysiological aspect for boosting grain yield in wheat. A worldwide winter wheat panel consisting of 261 accessions was tested to examine the phenotypical variation and identify quantitative trait nucleotides (QTNs) with candidate genes influencing FL morphology. To this end, four FL traits were evaluated during the early milk stage under two growing seasons at the Leibniz Institute of Plant Genetics and Crop Plant Research. The results showed that all leaf traits (Flag leaf length, width, area, and length/width ratio) were significantly influenced by the environments, genotypes, and environments × genotypes interactions. Then, a genome-wide association analysis was performed using 17,093 SNPs that showed 10 novel QTNs that potentially play a role in modulating FL morphology in at least two environments. Further analysis revealed 8 high-confidence candidate genes likely involved in these traits and showing high expression values from flag leaf expansion until its senescence and also during grain development. An important QTN (wsnp_RFL_Contig2177_1500201) was associated with FL width and located inside TraesCS3B02G047300 at chromosome 3B. This gene encodes a major facilitator, sugar transporter-like, and showed the highest expression values among the candidate genes reported, suggesting their positive role in controlling flag leaf and potentially being involved in photosynthetic assimilation. Our study suggests that the detection of novel marker-trait associations and the subsequent elucidation of the genetic mechanism influencing FL morphology would be of interest for improving plant architecture, light capture, and photosynthetic efficiency during grain development.

Identification and validation of two major QTL for grain number per spike on chromosomes 2B and 2D in bread wheat (Triticum aestivum L.)

KEY MESSAGE

Major QTL for grain number per spike were identified on chromosomes 2B and 2D. Haplotypes and candidate genes of QGns.cib-2B.1 were analyzed. Grain number per spike (GNS) is one of the main components of wheat yield. Genetic dissection of their regulatory factors is essential to improve the yield potential. In present study, a recombinant inbred line population comprising 180 lines developed from the cross between a high GNS line W7268 and a cultivar Chuanyu12 was employed to identify quantitative trait loci (QTL) associated with GNS across six environments. Two major QTL, QGns.cib-2B.1 and QGns.cib-2D.1, were detected in at least four environments with the phenotypic variations of 12.99-27.07% and 8.50-13.79%, respectively. And significant interactions were observed between the two major QTL. In addition, QGns.cib-2B.1 is a QTL cluster for GNS, grain number per spikelet and fertile tiller number, and they were validated in different genetic backgrounds using Kompetitive Allele Specific PCR (KASP) markers. QGns.cib-2B.1 showed pleotropic effects on other yield-related traits including plant height, spike length, and spikelet number per spike, but did not significantly affect thousand grain weight which suggested that it might be potentially applicable in breeding program. Comparison analysis suggested that QGns.cib-2B.1 might be a novel QTL. Furthermore, haplotype analysis of QGns.cib-2B.1 indicated that it is a hot spot of artificial selection during wheat improvement. Based on the expression patterns, gene annotation, orthologs analysis and sequence variations, the candidate genes of QGns.cib-2B.1 were predicted. Collectively, the major QTL and KASP markers reported here provided a wealth of information for the genetic basis of GNS and grain yield improvement.

Alleles on locus chromosome 4B from different parents confer tiller number and the yield-associated traits in wheat

Pleiotropy is frequently detected in agronomic traits of wheat (Triticum aestivum). A locus on chromosome 4B, QTn/Ptn/Sl/Sns/Al/Tgw/Gl/Gw.caas-4B, proved to show pleiotropic effects on tiller, spike, and grain traits using a recombinant inbred line (RIL) population of Qingxinmai × 041133. The allele from Qingxinmai increased tiller numbers, and the allele from line 041133 produced better performances of spike traits and grain traits. Another 52 QTL for the eight traits investigated were detected on 18 chromosomes, except for chromosomes 5D, 6D, and 7B. Several genes in the genomic interval of the locus on chromosome 4B were differentially expressed in crown and inflorescence samples between Qingxinmai and line 041133. The development of the KASP marker specific for the locus on chromosome 4B is useful for molecular marker-assisted selection in wheat breeding.

Fine-mapping and validation of the major quantitative trait locus QFlANG-4B for flag leaf angle in wheat

KEY MESSAGE

This study precisely mapped and validated a quantitative trait locus (QTL) located on chromosome 4B for flag leaf angle in wheat. Flag leaf angle (FLANG) is closely related to crop architecture and yield. We previously identified the quantitative trait locus (QTL) QFLANG-4B for FLANG on chromosome 4B, located within a 14-cM interval flanked by the markers Xbarc20 and Xzyh357, using a mapping population of recombinant inbred lines (RILs) derived from a cross between Nongda3331 (ND3331) and Zang1817. In this study, we fine-mapped QFLANG-4B and validated its associated genetic effect. We developed a BC3F3 population using ND3331 as the recurrent parent through marker-assisted selection, as well as near-isogenic lines (NILs) by selfing BC3F3 plants carrying different heterozygous segments for the QFLANG-4B region. We obtained eight recombinant types for QFLANG-4B, narrowing its location down to a 5.3-Mb region. This region contained 76 predicted genes, 7 of which we considered to be likely candidate genes for QFLANG-4B. Marker and phenotypic analyses of individual plants from the secondary mapping populations and their progeny revealed that the FLANG of the ND3331 allele is significantly higher than that of the Zang1817 allele in multiple environments. These results not only provide a basis for the map-based cloning of QFLANG-4B, but also indicate that QFLANG-4B has great potential for marker-assisted selection in wheat breeding programs designed to improve plant architecture and yield.

Characterization of a wheat stable QTL for spike length and its genetic effects on yield-related traits

Spike length (SL) is one of the most important agronomic traits affecting yield potential and stability in wheat. In this study, a major stable quantitative trait locus (QTL) for SL, i.e., qSl-2B, was detected in multiple environments in a recombinant inbred line (RIL) mapping population, KJ-RILs, derived from a cross between Kenong 9204 (KN9204) and Jing 411 (J411). The qSl-2B QTL was mapped to the 60.06-73.06 Mb region on chromosome 2B and could be identified in multiple mapping populations. An InDel molecular marker in the target region was developed based on a sequence analysis of the two parents. To further clarify the breeding use potential of qSl-2B, we analyzed its genetic effects and breeding selection effect using both the KJ-RIL population and a natural mapping population, which consisted of 316 breeding varieties/advanced lines. The results showed that the qSl-2B alleles from KN9204 showed inconsistent genetic effects on SL in the two mapping populations. Moreover, in the KJ-RILs population, the additive effects analysis of qSl-2B showed that additive effect was higher when both qSl-2D and qSl-5A harbor negative alleles under LN and HN. In China, a moderate selection utilization rate for qSl-2B was found in the Huanghuai winter wheat area and the selective utilization rate for qSl-2B continues to increase. The above findings provided a foundation for the genetic improvement of wheat SL in the future via molecular breeding strategies.

Mining of QTLs for Spring Bread Wheat Spike Productivity by Comparing Spring Wheat Cultivars Released in Different Decades of the Last Century

Genome-wide association studies (GWAS) are among the genetic tools for the mining of genomic loci associated with useful agronomic traits. The study enabled us to find new genetic markers associated with grain yield as well as quality. The sample under study consisted of spring wheat cultivars developed in different decades of the last century. A panel of 186 accessions was evaluated at VIR's experiment station in Pushkin across a 3-year period of field trials. In total, 24 SNPs associated with six productivity characteristics were revealed. Along with detecting significant markers for each year of the field study, meta-analyses were conducted. Loci associated with useful yield-related agronomic characteristics were detected on chromosomes 4A, 5A, 6A, 6B, and 7B. In addition to previously described regions, novel loci associated with grain yield and quality were identified during the study. We presume that the utilization of contrast cultivars which originated in different breeding periods allowed us to identify new markers associated with useful agronomic characteristics.

Genetic insights into superior grain number traits: a QTL analysis of wheat-Agropyron cristatum derivative pubing3228

BACKGROUND

Agropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228.

METHODS

The study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits.

RESULTS

A total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25-17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds.

CONCLUSION

This study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield.

A novel variation of TaGW2-6B increases grain weight without penalty in grain protein content in wheat (Triticum aestivum L.)

Yield and quality are two crucial breeding objects of wheat therein grain weight and grain protein content (GPC) are two key relevant factors correspondingly. Investigations of their genetic mechanisms represent special significance for breeding. In this study, 199 F2 plants and corresponding F2:3 families derived from Nongda3753 (ND3753) and its EMS-generated mutant 564 (M564) were used to investigate the genetic basis of larger grain and higher GPC of M564. QTL analysis identified a total of 33 environmentally stable QTLs related to thousand grain weight (TGW), grain area (GA), grain circle (GC), grain length (GL), grain width (GW), and GPC on chromosomes 1B, 2A, 2B, 4D, 6B, and 7D, respectively, among which QGw.cau-6B.1, QTgw.cau-6B.1, QGa.cau-6B.1, and QGc.cau-6B.1 shared overlap confidence interval on chromosome 6B. This interval contained the TaGW2 gene playing the same role as the QTLs, so TaGW2-6B was cloned and sequenced. Sequence alignment revealed two G/A SNPs between two parents, among which the SNP in the seventh exon led to a premature termination in M564. A KASP marker was developed based on the SNP, and single-marker analysis on biparental populations showed that the mutant allele could significantly increase GW and TGW, but had no effect on GPC. Distribution detection of the mutant allele through KASP marker genotyping and sequence alignment against databases ascertained that no materials harbored this allele within natural populations. This allele was subsequently introduced into three different varieties through molecular marker-assisted backcrossing, and it was revealed that the allele had a significant effect on simultaneously increasing GW, TGW, and even GPC in all of three backgrounds. Summing up the above, it could be concluded that a novel elite allele of TaGW2-6B was artificially created and might play an important role in wheat breeding for high yield and quality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01455-y.

Chromosome genomics facilitates the marker development and selection of wheat-Aegilops biuncialis addition, substitution and translocation lines

The annual goatgrass, Aegilops biuncialis is a rich source of genes with considerable agronomic value. This genetic potential can be exploited for wheat improvement through interspecific hybridization to increase stress resistance, grain quality and adaptability. However, the low throughput of cytogenetic selection hampers the development of alien introgressions. Using the sequence of flow-sorted chromosomes of diploid progenitors, the present study enabled the development of chromosome-specific markers. In total, 482 PCR markers were validated on wheat (Mv9kr1) and Ae. biuncialis (MvGB642) crossing partners, and 126 on wheat-Aegilops additions. Thirty-two markers specific for U- or M-chromosomes were used in combination with GISH and FISH for the screening of 44 Mv9kr1 × Ae. biuncialis BC3F3 genotypes. The predominance of chromosomes 4M and 5M, as well as the presence of chromosomal aberrations, may indicate that these chromosomes have a gametocidal effect. A new wheat-Ae. biuncialis disomic 4U addition, 4M(4D) and 5M(5D) substitutions, as well as several introgression lines were selected. Spike morphology and fertility indicated that the Aegilops 4M or 5M compensated well for the loss of 4D and 5D, respectively. The new cytogenetic stocks represent valuable genetic resources for the introgression of key genes alleles into wheat.

Molecular characterization of stable QTL and putative candidate genes for grain zinc and iron concentrations in two related wheat populations

KEY MESSAGE

Major QTL for grain zinc and iron concentrations were identified on the long arm of chromosomes 2D and 6D. Gene-based KASP markers were developed for putative candidate genes TaIPK1-2D and TaNAS10-6D. Micronutrient malnutrition is one of the most common public health problems in the world. Biofortification, the most attractive and sustainable solution to surmount malnutrition requires the development of micronutrient enriched new crop cultivars. In this study, two recombinant inbred line (RIL) populations, ZM175/XY60 and ZM175/LX987, were used to identify QTL for grain zinc concentration (GZnC), grain iron concentration (GFeC) and thousand grain weight (TGW). Eight QTL for GZnC, six QTL for GFeC and five QTL for TGW were detected. Three QTL on chromosomes 2DL and 4BS and chromosome 6A showed pleiotropic effects on all three traits. The 4BS and 6A QTL also increased plant height and might be Rht-B1a and Rht25a, respectively. The 2DL locus within a suppressed recombination region was identified in both RIL populations and the favorable allele simultaneously increasing GZnC, GFeC and TGW was contributed by XY60 and LX987. A QTL on chromosome 6DL associated only with GZnC was detected in ZM175/XY60 and was validated in JD8/AK58 RILs using kompetitive allele-specific PCR (KASP) marker K_AX-110119937. Both the 2DL and 6DL QTL were new loci for GZnC. Based on gene annotations, sequence variations and expression profiles, the phytic acid biosynthesis gene TaIPK1-2D and nicotianamine synthase gene TaNAS10-6D were predicted as candidate genes. Their gene-based KASP markers were developed and validated in a cultivar panel of 343 wheat accessions. This study investigated the genetic basis of GZnC and GFeC and provided valuable candidate genes and markers for breeding Zn- and Fe-enriched wheat.

A high-resolution genotype-phenotype map identifies the TaSPL17 controlling grain number and size in wheat

BACKGROUND

Large-scale genotype-phenotype association studies of crop germplasm are important for identifying alleles associated with favorable traits. The limited number of single-nucleotide polymorphisms (SNPs) in most wheat genome-wide association studies (GWASs) restricts their power to detect marker-trait associations. Additionally, only a few genes regulating grain number per spikelet have been reported due to sensitivity of this trait to variable environments.

RESULTS

We perform a large-scale GWAS using approximately 40 million filtered SNPs for 27 spike morphology traits. We detect 132,086 significant marker-trait associations and the associated SNP markers are located within 590 associated peaks. We detect additional and stronger peaks by dividing spike morphology into sub-traits relative to GWAS results of spike morphology traits. We propose that the genetic dissection of spike morphology is a powerful strategy to detect signals for grain yield traits in wheat. The GWAS results reveal that TaSPL17 positively controls grain size and number by regulating spikelet and floret meristem development, which in turn leads to enhanced grain yield per plant. The haplotypes at TaSPL17 indicate geographical differentiation, domestication effects, and breeding selection.

CONCLUSION

Our study provides valuable resources for genetic improvement of spike morphology and a fast-forward genetic solution for candidate gene detection and cloning in wheat.

An intron-located single nucleotide variation of TaGS5-3D is related to wheat grain size through accumulating intron retention transcripts

KEY MESSAGE

Thirty-three stable QTL for 13 yield-related traits across ten environments were identified in the PD34/MY47 RIL population, and a candidate gene TaGS5-3D in Qmt.nwafu.3D was preliminarily identified to affect grain-related traits through accumulation of specific transcripts. Dissecting the genetic basis of yield-related traits is pivotal for improvement of wheat yield potential. In this study, a recombinant inbred line (RIL) population genotyped by SNP markers was used to detect quantitative trait loci (QTL) related to yield-related traits in ten environments. A total of 102 QTL were detected, including 33 environmentally stable QTL and 69 putative QTL. Among them, Qmt.nwafu.3D was identified as a pleiotropic QTL in the physical interval of 149.77-154.11 Mb containing a potential candidate gene TaGS5-3D. An SNP (T > C) was detected in its ninth intron, and TaGS5-3D-C was validated as a superior allele associated with larger grains using a CAPS marker. Interestingly, we found that TaGS5-3D-C was closely related to significantly up-regulated expression of intron-retained transcript (TaGS5-3D-PD34.1), while TaGS5-3D-T was related to dominant expression of normal splicing transcript (TaGS5-3D-MY47.1). Our results indicated that alternative splicing associated with the SNP T/C could be involved in the regulation of grain-related traits, laying a foundation for the functional analysis of TaGS5-3D and its greater potential application in high-yield wheat breeding.

Genome wide association and haplotype analyses for the crease depth trait in bread wheat (Triticum aestivum L.)

Wheat grain has a complex structure that includes a crease on one side, and tissues within the crease region play an important role in nutrient transportation during wheat grain development. However, the genetic architecture of the crease region is still unclear. In this study, 413 global wheat accessions were resequenced and a method was developed for evaluating the phenotypic data of crease depth (CD). The CD values exhibited continuous and considerable large variation in the population, and the broad-sense heritability was 84.09%. CD was found to be positively correlated with grain-related traits and negatively with quality-related traits. Analysis of differentiation of traits between landraces and cultivars revealed that grain-related traits and CD were simultaneously improved during breeding improvement. Moreover, 2,150.8-Mb genetic segments were identified to fall within the selective sweeps between the landraces and cultivars; they contained some known functional genes for quality- and grain-related traits. Genome-wide association study (GWAS) was performed using around 10 million SNPs generated by genome resequencing and 551 significant SNPs and 18 QTLs were detected significantly associated with CD. Combined with cluster analysis of gene expression, haplotype analysis, and annotated information of candidate genes, two promising genes TraesCS3D02G197700 and TraesCS5A02G292900 were identified to potentially regulate CD. To the best of our knowledge, this is the first study to provide the genetic basis of CD, and the genetic loci identified in this study may ultimately assist in wheat breeding programs.

FHB resistance conferred by Fhb1 is under inhibitory regulation of two genetic loci in wheat (Triticum aestivum L.)

KEY MESSAGE

Two loci inhibiting Fhb1 resistance to Fusarium head blight were identified through genome-wide association mapping and validated in biparental populations. Fhb1 confers Fusarium head blight (FHB) resistance by limiting fungal spread within spikes in wheat (type II resistance). However, not all lines with Fhb1 display the expected resistance. To identify genetic factors regulating Fhb1 effect, a genome-wide association study for type II resistance was first performed with 72 Fhb1-carrying lines using the Illumina 90 K iSelect SNP chip. Of 84 significant marker-trait associations detected, more than half were repeatedly detected in at least two environments, with the SNPs distributed in one region on chromosome 5B and one on chromosome 6A. This result was validated in a collection of 111 lines with Fhb1 and 301 lines without Fhb1. We found that these two loci caused significant resistance variations solely among lines with Fhb1 by compromising the resistance. In1, the inhibitory gene on chromosome 5B, was in close linkage with Xwgrb3860 in a recombinant inbred line population derived from Nanda2419 × Wangshuibai and a double haploid (DH) population derived from R-43 (Fhb1 near isogenic line) × Biansui7 (with Fhb1 and In1); and In2, the inhibitory gene on chromosome 6A, was mapped to the Xwgrb4113-Xwgrb4034 interval using a DH population derived from R-43 × PH8901 (with Fhb1 and In2). In1 and In2 are present in all wheat-growing areas worldwide. Their frequencies in China's modern cultivars are high but have significantly decreased in comparison with landraces. These findings are of great significance for FHB resistance breeding using Fhb1.

Identification and validation of two major QTLs for spikelet number per spike in wheat (Triticum aestivum L.)

The total number of spikelets (TSPN) and the number of fertile spikelets (FSPN) affect the final number of grains per spikelet in wheat. This study constructed a high-density genetic map using 55K single nucleotide polymorphism (SNP) arrays from a population of 152 recombinant inbred lines (RIL) from crossing the wheat accessions 10-A and B39. Twenty-four quantitative trait loci (QTLs) for TSPN and 18 QTLs for FSPN were localized based on the phenotype in 10 environments in 2019-2021. Two major QTLs, QTSPN/QFSPN.sicau-2D.4 (34.43-47.43 Mb) and QTSPN/QFSPN.sicau-2D.5(32.97-34.43 Mb), explained 13.97%-45.90% of phenotypic variation. Linked kompetitive allele-specific PCR (KASP) markers further validated these two QTLs and revealed that QTSPN.sicau-2D.4 had less effect on TSPN than QTSPN.sicau-2D.5 in 10-A×BE89 (134 RILs) and 10-A×Chuannong 16 (192 RILs) populations, and one population of Sichuan wheat (233 accessions). The alleles combination haplotype 3 with the allele from 10-A of QTSPN/QFSPN.sicau-2D.5 and the allele from B39 of QTSPN.sicau-2D.4 resulted in the highest number of spikelets. In contrast, the allele from B39 for both loci resulted in the lowest number of spikelets. Using bulk-segregant analysis-exon capture sequencing, six SNP hot spots that included 31 candidate genes were identified in the two QTLs. We identified Ppd-D1a from B39 and Ppd-D1d from 10-A and further analyzed Ppd-D1 variation in wheat. These results identified loci and molecular markers with potential utility for wheat breeding and laid a foundation for further fine mapping and cloning of the two loci.

Reducing brassinosteroid signalling enhances grain yield in semi-dwarf wheat

Modern green revolution varieties of wheat (Triticum aestivum L.) confer semi-dwarf and lodging-resistant plant architecture owing to the Reduced height-B1b (Rht-B1b) and Rht-D1b alleles1. However, both Rht-B1b and Rht-D1b are gain-of-function mutant alleles encoding gibberellin signalling repressors that stably repress plant growth and negatively affect nitrogen-use efficiency and grain filling2-5. Therefore, the green revolution varieties of wheat harbouring Rht-B1b or Rht-D1b usually produce smaller grain and require higher nitrogen fertilizer inputs to maintain their grain yields. Here we describe a strategy to design semi-dwarf wheat varieties without the need for Rht-B1b or Rht-D1b alleles. We discovered that absence of Rht-B1 and ZnF-B (encoding a RING-type E3 ligase) through a natural deletion of a haploblock of about 500 kilobases shaped semi-dwarf plants with more compact plant architecture and substantially improved grain yield (up to 15.2%) in field trials. Further genetic analysis confirmed that the deletion of ZnF-B induced the semi-dwarf trait in the absence of the Rht-B1b and Rht-D1b alleles through attenuating brassinosteroid (BR) perception. ZnF acts as a BR signalling activator to facilitate proteasomal destruction of the BR signalling repressor BRI1 kinase inhibitor 1 (TaBKI1), and loss of ZnF stabilizes TaBKI1 to block BR signalling transduction. Our findings not only identified a pivotal BR signalling modulator but also provided a creative strategy to design high-yield semi-dwarf wheat varieties by manipulating the BR signal pathway to sustain wheat production.

Variations in phenological, physiological, plant architectural and yield-related traits, their associations with grain yield and genetic basis

BACKGROUND AND AIMS

Physiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored.

METHODS

Here, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018-2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays.

KEY RESULTS

These traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P < 0.01), thousand-grain weight (r = 0.36, P < 0.01) and truncated and lanceolate shape, but shorter plant height (r = -0.63, P < 0.01), flag leaf angle (r = -0.49, P < 0.01) and spike number per square metre (r = -0.22, P < 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars.

CONCLUSIONS

This study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding.

QTL cluster analysis and marker development for kernel traits based on DArT markers in spring bread wheat (Triticum aestivum L.)

Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F₆ population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.

Genome-wide association study of yield-related traits in common wheat (Triticum aestivum L.) under normal and drought treatment conditions

The primary goal of modern wheat breeding is to develop new high-yielding and widely adaptable varieties. We analyzed four yield-related agronomic traits in 502 wheat accessions under normal conditions (NC) and drought treatment (DT) conditions over three years. The genome-wide association analysis identified 51 yield-related and nine drought-resistance-related QTL, including 13 for the thousand-grain weight (TGW), 30 for grain length (GL), three for grain width (GW), five for spike length (SL) and nine for stress tolerance index (STI) QTL in wheat. These QTL, containing 72 single nucleotide polymorphisms (SNPs), explained 2.23 - 7.35% of the phenotypic variation across multiple environments. Eight stable SNPs on chromosomes 2A, 2D, 3B, 4A, 5B, 5D, and 7D were associated with phenotypic stability under NC and DT conditions. Two of these stable SNPs had association with TGW and STI. Several novel QTL for TGW, GL and SL were identified on different chromosomes. Three linked SNPs were transformed into kompetitive allele-specific PCR (KASP) markers. These results will facilitate the discovery of promising SNPs for yield-related traits and/or drought stress tolerance and will accelerate the development of new wheat varieties with desirable alleles.

Pinb-D1p is an elite allele for improving end-use quality in wheat (Triticum aestivum L.)

We identified ten QTLs controlling SDS-SV trait in a RIL population derived from ND3331 and Zang1817. Pinb-D1p is an elite allele from Tibetan semi‑wild wheat for good end-use quality. Gluten strength is an important factor for wheat processing and end-product quality and is commonly characterized using the sodium dodecyl sulfate-sedimentation volume (SDS-SV) test. The objective of this study was to identify quantitative trait loci (QTLs) associated with wheat SDS-SV traits using a recombinant inbred line (RIL) population derived from common wheat line NongDa3331 (ND3331) and Tibetan semi-wild wheat accession Zang1817. We detected 10 QTLs controlling SDS-SV on chromosomes 1A, 1B, 3A, 4A, 4B, 5A, 5D, 6B and 7A, with individual QTLs explaining 2.02% to 15.53% of the phenotypic variation. They included four major QTLs, Qsdss-1A, Qsdss-1B.1, Qsdss-1B.2, and Qsdss-5D, whose effects on SDS-SV were due to the Glu-A1 locus encoding the high-molecular-weight glutenin subunit 1Ax1, the 1B/1R translocation, 1Bx7 + 1By8 at the Glu-B1 locus, and the hardness-controlling loci Pina-D1 and Pinb-D1, respectively. We developed KASP markers for the Glu-A1, Glu-B1, and Pinb-D1 loci. Importantly, we showed for the first time that the hardness allele Pinb-D1p positively affects SDS-SV, making it a good candidate for wheat quality improvement. These results broaden our understanding of the genetic characterization of SDS-SV, and the QTLs identified are potential target regions for fine-mapping and marker-assisted selection in wheat breeding programs.

Genetic architecture and candidate gene identification for grain size in bread wheat by GWAS

Grain size is a key trait associated with bread wheat yield. It is also the most frequently selected trait during domestication. After the phenotypic characterization of 768 bread wheat accessions in three plots for at least two years, the present study shows that the improved variety showed significantly higher grain size but lower grain protein content than the landrace. Using 55K SNP assay genotyping and large-scale phenotyping population and GWAS data, we identified 5, 6, 6, and 6 QTLs associated with grain length, grain weight, grain area, and thousand grain weight, respectively. Seven of the 23 QTLs showed common association within different locations or years. Most significantly, the key locus associated with grain length, qGL-2D, showed the highest association after years of multi-plot testing. Haplotype and evolution analysis indicated that the superior allele of qGL-2D was mainly hidden in the improved variety rather than in landrace, which may contribute to the significant difference in grain length. A comprehensive analysis of transcriptome and homolog showed that TraesCS2D02G414800 could be the most likely candidate gene for qGL-2D. Overall, this study presents several reliable grain size QTLs and candidate gene for grain length associated with bread wheat yield.

Identification and validation of quantitative trait loci for chlorophyll content of flag leaf in wheat under different phosphorus treatments

In wheat, the leaf chlorophyll content in flag leaves is closely related to the degree of phosphorus stress. Identifying major genes/loci associated with chlorophyll content in flag leaves under different phosphorus conditions is critical for breeding wheat varieties resistant to low phosphorus (P). Under normal, medium, and low phosphorus conditions, the chlorophyll content of flag leaves was investigated by a double haploid (DH) population derived from a cross between two popular wheat varieties Jinmai 47 and Jinmai 84, at different grain filling stages. Chlorophyll content of the DH population and parents decreased gradually during the S1 to the S3 stages and rapidly at the S4 stage. At the S4 stage, the chlorophyll content of the DH population under low phosphorus conditions was significantly lower than under normal phosphate conditions. Using a wheat 15K single-nucleotide polymorphism (SNP) panel, a total of 157 QTLs were found to be associated with chlorophyll content in flag leaf and were identified under three phosphorus conditions. The phenotypic variation explained (PVE) ranged from 3.07 to 31.66%. Under three different phosphorus conditions, 36, 30, and 48 QTLs for chlorophyll content were identified, respectively. Six major QTLs Qchl.saw-2B.1, Qchl.saw-3B.1, Qchl.saw-4D.1, Qchl.saw-4D.2, Qchl.saw-5A.9 and Qchl.saw-6A.4 could be detected under multiple phosphorus conditions in which Qchl.saw-4D.1, Qchl.saw-4D.2, and Qchl.saw-6A.4 were revealed to be novel major QTLs. Moreover, the closely linked SNP markers of Qchl.saw-4D.1 and Qchl.saw-4D.2 were validated as KASP markers in a DH population sharing the common parent Jinmai 84, showed extreme significance (P <0.01) in more than three environments under different phosphorus conditions, which has the potential to be utilized in molecular marker-assisted breeding for low phosphorus tolerance in wheat.

High-Density Linkage Mapping of Agronomic Trait QTLs in Wheat under Water Deficit Condition using Genotyping by Sequencing (GBS)

Improvement of grain yield is the ultimate goal for wheat breeding under water-limited environments. In the present study, a high-density linkage map was developed by using genotyping-by-sequencing (GBS) of a recombinant inbred line (RIL) population derived from the cross between Iranian landrace #49 and cultivar Yecora Rojo. The population was evaluated in three locations in Iran during two years under irrigated and water deficit conditions for the agronomic traits grain yield (GY), plant height (PH), spike number per square meter (SM), 1000 kernel weight (TKW), grain number per spike (GNS), spike length (SL), biomass (BIO) and harvest index (HI). A linkage map was constructed using 5831 SNPs assigned to 21 chromosomes, spanning 3642.14 cM of the hexaploid wheat genome with an average marker density of 0.62 (markers/cM). In total, 85 QTLs were identified on 19 chromosomes (all except 5D and 6D) explaining 6.06–19.25% of the traits phenotypic variance. We could identify 20 novel QTLs explaining 8.87–19.18% of phenotypic variance on chromosomes 1A, 1B, 1D, 2B, 3A, 3B, 6A, 6B and 7A. For 35 out of 85 mapped QTLs functionally annotated genes were identified which could be related to a potential role in drought stress.

Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits

Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, most of these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practical wheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs) were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by the breeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.

Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map

Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.

Genetic Dissection of Three Major Quantitative Trait Loci for Spike Compactness and Length in Bread Wheat (Triticum aestivum L.)

Spike compactness (SC) and length (SL) are the components of spike morphology and are strongly related to grain yield in wheat (Triticum aestivum L.). To investigate quantitative trait loci (QTL) associated with SC and SL, a recombinant inbred lines (RIL) population derived from the cross of Bailangmai (BLM, a Tibet landrace) and Chuanyu 20 (CY20, an improved variety) was employed in six environments. Three genomic regions responsible for SC and SL traits were identified on chromosomes 2A and 2D using bulked segregant exome sequencing (BSE-Seq). By constructing genetic maps, six major QTL were repeatedly detected in more than four environments and the best linear unbiased estimation (BLUE) datasets, explaining 7.00-28.56% of the phenotypic variation and the logarithm of the odd (LOD) score varying from 2.50 to 13.22. They were co-located on three loci, designed as QSc/Sl.cib-2AS, QSc/Sl.cib-2AL, and QSc/Sl.cib-2D, respectively. Based on the flanking markers, their interactions and effects on the corresponding trait and other agronomic traits were also analyzed. Comparison analysis showed that QSc/Sl.cib-2AS and QSc/Sl.cib-2AL were possibly two novel loci for SC and SL. QSc/Sl.cib-2AS and QSc/Sl.cib-2D showed pleiotropic effects on plant height and grain morphology, while QSc/Sl.cib-2AL showed effects on spikelet number per spike (SNS) and grain width (GW). Based on the gene annotation, orthologous search, and spatiotemporal expression patterns of genes, TraesCS2A03G0410600 and TraesCS2A03G0422300 for QSc/Sl.cib-2AS, and TraesCS2D03G1129300 and TraesCS2D03G1131500 for QSc/Sl.cib-2D were considered as potential candidate genes, respectively. These results will be useful for fine mapping and developing new varieties with high yield in the future.

Fine mapping of the tiller inhibition gene TIN4 contributing to ideal plant architecture in common wheat

A tiller inhibition gene, TIN4, was mapped to an approximately 311 kb genomic interval on chromosome arm 2DL of wheat. The tiller is one of the key components of plant morphological architecture and a central agronomic trait affecting spike number in wheat. Low tiller number has been proposed as a major component of crop ideotypes for high yield potential. In this study, we characterized the development of tillering in near-isogenic lines (NIL7A and NIL7B), indicating that the TIN4 gene inhibited the growth of tillering buds and negatively regulated tiller number. Low-tillering was controlled by a single gene (TIN4) located on chromosome 2DL by genetic analysis and bulked segregant RNA-seq analysis. A total of 17 new polymorphic markers were developed in this study, and 61 recombinants were identified in the secondary F2 population containing 4,266 individuals. TIN4 was finally mapped on a 0.35 cM interval, co-segregated with molecular marker M380, within a 311 kb genomic interval of the wheat cultivar Chinese Spring reference genome sequence that contained twelve predicted genes. Yield experiments showed that the yield of low-tillering lines was higher than that of high-tillering lines at a higher density. Overall, this study provides a foundation for the construction of a low-tillering ideotype for improving wheat yield and further cloning TIN4 by map-based cloning approach.

A Major Quantitative Trait Loci Cluster Controlling Three Components of Yield and Plant Height Identified on Chromosome 4B of Common Wheat

Wheat yield is not only affected by three components of yield, but also affected by plant height (PH). Identification and utilization of the quantitative trait loci (QTL) controlling these four traits is vitally important for breeding high-yielding wheat varieties. In this work, we conducted a QTL analysis using the recombinant inbred lines (RILs) derived from a cross between two winter wheat varieties of China, "Nongda981" (ND981) and "Nongda3097" (ND3097), exhibiting significant differences in spike number per unit area (SN), grain number per spike (GNS), thousand grain weight (TGW), and PH. A total of 11 environmentally stable QTL for these four traits were detected. Among them, four major and stable QTLs (QSn.cau-4B-1.1, QGns.cau-4B-1, QTgw.cau-4B-1.1, and QPh.cau-4B-1.2) explaining the highest phenotypic variance for SN, GNS, TGW, and PH, respectively, were mapped on the same genomic region of chromosome 4B and were considered a QTL cluster. The QTL cluster spanned a genetic distance of about 12.3 cM, corresponding to a physical distance of about 8.7 Mb. Then, the residual heterozygous line (RHL) was used for fine mapping of the QTL cluster. Finally, QSn.cau-4B-1.1, QGns.cau-4B-1, and QPh.cau-4B-1.2 were colocated to the physical interval of about 1.4 Mb containing 31 annotated high confidence genes. QTgw.cau-4B-1.1 was divided into two linked QTL with opposite effects. The elite NILs of the QTL cluster increased SN and PH by 55.71-74.82% and 14.73-23.54%, respectively, and increased GNS and TGW by 29.72-37.26% and 5.81-11.24% in two environments. Collectively, the QTL cluster for SN, GNS, TGW, and PH provides a theoretical basis for improving wheat yield, and the fine-mapping result will be beneficial for marker-assisted selection and candidate genes cloning.

Analysis of Genetic Regions Related to Field Grain Number per Spike From Chinese Wheat Founder Parent Linfen 5064

Wheat founder parents have been important in the development of new wheat cultivars. Understanding the effects of specific genome regions on yield-related traits in founder variety derivatives can enable more efficient use of these genetic resources through molecular breeding. In this study, the genetic regions related to field grain number per spike (GNS) from the founder parent Linfen 5064 were analyzed using a doubled haploid (DH) population developed from a cross between Linfen 5064 and Nongda 3338. Quantitative trait loci (QTL) for five spike-related traits over nine experimental locations/years were identified, namely, total spikelet number per spike (TSS), base sterile spikelet number per spike (BSSS), top sterile spikelet number per spike (TSSS), fertile spikelet number per spike (FSS), and GNS. A total of 13 stable QTL explaining 3.91-19.51% of the phenotypic variation were found. The effect of six of these QTL, Qtss.saw-2B.1, Qtss.saw-2B.2, Qtss.saw-3B, Qfss.saw-2B.2, Qbsss.saw-5A.1, and Qgns.saw-1A, were verified by another DH population (Linfen 5064/Jinmai 47), which showed extreme significance (P < 0.05) in more than three environments. No homologs of reported grain number-related from grass species were found in the physical regions of Qtss.saw-2B.1 and Qtss.saw-3B, that indicating both of them are novel QTL, or possess novel-related genes. The positive alleles of Qtss.saw-2B.2 from Linfen 5064 have the larger effect on TSS (3.30%, 0.62) and have 66.89% in Chinese cultivars under long-term artificial selection. This study revealed three key regions for GNS in Linfen 5064 and provides insights into molecular marker-assisted breeding.

Genetic dissection of quantitative trait loci for grain size and weight by high-resolution genetic mapping in bread wheat (Triticum aestivum L.)

Six major QTLs for wheat grain size and weight were identified on chromosomes 4A, 4B, 5A and 6A across multiple environments, and were validated in different genetic backgrounds. Grain size and weight are crucial components of wheat yield. Dissection of their genetic control is thus essential for the improvement of yield potential in wheat breeding. We used a doubled haploid (DH) population to detect quantitative trait loci (QTLs) for grain width (GW), grain length (GL), and thousand grain weight (TGW) in five environments. Six major QTLs, QGw.cib-4B.2, QGl.cib-4A, QGl.cib-5A.1, QGl.cib-6A, QTgw.cib-4B, and QTgw.cib-5A, were consistently identified in at least three individual environments and in best linear unbiased prediction (BLUP) datasets, and explained 5.65-34.06% of phenotypic variation. QGw.cib-4B.2, QTgw.cib-4B, QGl.cib-5A.1 and QGl.cib-6A had no effect on grain number per spike (GNS). In addition to QGl.cib-4A, the other major QTLs were further validated by using Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. Moreover, significant interactions between the three major GL QTLs and two major TGW QTLs were observed. Comparison analysis showed that QGl.cib-5A.1 and QGl.cib-6A are likely new loci. Notably, QGw.cib-4B.2 and QTgw.cib-4B were co-located on chromosome 4B and improved TGW by increasing only GW, unlike nearby or overlapped loci reported previously. Three genes associated with grain development within the QGw.cib-4B.2/QTgw.cib-4B interval were identified by searches on sequence similarity, spatial expression patterns, and orthologs. The major QTLs and KASP markers reported here will be useful for elucidating the genetic architecture of grain size and weight and for developing new wheat cultivars with high and stable yield.

Identification and Validation of Stable Quantitative Trait Loci for SDS-Sedimentation Volume in Common Wheat (Triticum aestivum L.)

Sodium dodecyl sulfate-sedimentation volume is an important index to evaluate the gluten strength of common wheat and is closely related to baking quality. In this study, a total of 15 quantitative trait locus (QTL) for sodium dodecyl sulfate (SDS)-sedimentation volume (SSV) were identified by using a high-density genetic map including 2,474 single-nucleotide polymorphism (SNP) markers, which was constructed with a doubled haploid (DH) population derived from the cross between Non-gda3753 (ND3753) and Liangxing99 (LX99). Importantly, four environmentally stable QTLs were detected on chromosomes 1A, 2D, and 5D, respectively. Among them, the one with the largest effect was identified on chromosome 1A (designated as QSsv.cau-1A.1) explaining up to 39.67% of the phenotypic variance. Subsequently, QSsv.cau-1A.1 was dissected into two QTLs named as QSsv.cau-1A.1.1 and QSsv.cau-1A.1.2 by saturating the genetic linkage map of the chromosome 1A. Interestedly, favorable alleles of these two loci were from different parents. Due to the favorable allele of QSsv.cau-1A.1.1 was from the high-value parents ND3753 and revealed higher genetic effect, which explained 25.07% of the phenotypic variation, mapping of this locus was conducted by using BC3F1 and BC3F2 populations. By comparing the CS reference sequence, the physical interval of QSsv.cau-1A.1.1 was delimited into 14.9 Mb, with 89 putative high-confidence annotated genes. SSVs of different recombinants between QSsv.cau-1A.1.1 and QSsv.cau-1A.1 detected from DH and BC3F2 populations showed that these two loci had an obvious additive effect, of which the combination of two favorable loci had the high SSV, whereas recombinants with unfavorable loci had the lowest. These results provide further insight into the genetic basis of SSV and QSsv.cau-1A.1.1 will be an ideal target for positional cloning and wheat breeding programs.

The Genetic Architecture of Grain Yield in Spring Wheat Based on Genome-Wide Association Study

Uncovering the genetic architecture for grain yield (GY)–related traits is important for wheat breeding. To detect stable loci for GY-related traits, a genome-wide association study (GWAS) was conducted in a diverse panel, which included 251 elite spring wheat accessions mainly from the Northeast of China. In total, 52,503 single nucleotide polymorphisms (SNPs) from the wheat 55 K SNP arrays were used. Thirty-eight loci for GY-related traits were detected and each explained 6.5–16.7% of the phenotypic variations among which 12 are at similar locations with the known genes or quantitative trait loci and 26 are likely to be new. Furthermore, six genes possibly involved in cell division, signal transduction, and plant development are candidate genes for GY-related traits. This study provides new insights into the genetic architecture of GY and the significantly associated SNPs and accessions with a larger number of favorable alleles could be used to further enhance GY in breeding.

A SNP-based GWAS and functional haplotype-based GWAS of flag leaf-related traits and their influence on the yield of bread wheat (Triticum aestivum L.)

The genetic architecture of five flag leaf morphology traits was dissected by the functional haplotype-based GWAS and a standard SNP-based GWAS in a diverse population consisting of 197 varieties. Flag leaf morphology (FLM) is a critical factor affecting plant architecture and grain yield in wheat. The genetic architecture of FLM traits has been extensively studied with QTL mapping in bi-parental populations, while few studies exploited genome-wide association studies (GWAS) in diverse populations. In this study, a panel of 197 elite and historical varieties from China was evaluated for five FLM traits including the length (FLL), width (FLW), ratio (FLR), area (FLA) and angle (FLANG) as well as yield in nine environments. Based on the phenotypic correlation between yield and FLL (-0.43), FLA (- 0.32) and FLW (0.11), an empirical FLM index combining the three FLM traits proved to be a good predictor for yield. Two GWAS approaches were applied to dissect the genetic architecture of five FLM traits with a Wheat660K SNP array. The functional haplotype-based GWAS revealed 6, 5 and 7 QTL for FLANG, FLL and FLR, respectively, whereas two QTL for FLW and one for FLR were identified by the standard SNP-based GWAS. Due to co-localization, there were 18 independent QTL and 10 of them were close to known ones. One co-localized QTL on chromosome 5A was associated with FLL, FLANG and FLR. Moreover, both GWAS approaches identified a novel QTL for FLR on chromosome 6B which was not reported in previous studies. This study provides new insights into the relationship between FLM and yield and broadens our understanding of the genetic architecture of FLM traits in wheat.

Identification and validation of two major QTLs for spike compactness and length in bread wheat (Triticum aestivum L.) showing pleiotropic effects on yield-related traits

Two major and stable QTLs for spike compactness and length were detected and validated in multiple genetic backgrounds and environments, and their pleiotropic effects on yield-related traits were analyzed. Spike compactness (SC) and length (SL) are greatly associated with wheat (Triticum aestivum L.) grain yield. To detect quantitative trait loci (QTL) associated with SC and SL, two biparental populations derived from crosses of Chuanmai42/Kechengmai1 and Chuanmai42/Chuannong16 were employed to perform QTL mapping in five environments. A total of 34 QTLs were identified, in which six major QTLs were repeatedly detected in more than four environments and the best linear unbiased prediction datasets, explaining 7.13-33.6% of phenotypic variation. These major QTLs were co-located in two genomic regions on chromosome 5A and 6A, namely QSc/Sl.cib-5A and QSc/Sl.cib-6A, respectively. By developing kompetitive allele-specific PCR (KASP) markers that linked to them, the two loci were validated in different genetic backgrounds, and their interactions were also analyzed. Comparison analysis showed that QSc/Sl.cib-5A was not Vrn-A1 and Q, and QSc/Sl.cib-6A was likely a new locus for SC and SL. Both QSc/Sl.cib-5A and QSc/Sl.cib-6A had pleiotropic effects on other yield-related traits including plant height, thousand grain weight and grain length. Therefore, the two loci combined with the developed KASP markers might be potentially applicable in wheat breeding. Furthermore, based on the spatiotemporal expression patterns, gene annotation, orthologous search and sequence differences, TraesCS5A01G301400 and TraesCS6A01G090300 were considered as potential candidates for QSc/Sl.cib-5A and QSc/Sl.cib-6A, respectively. These results provided valuable information for fine mapping and cloning of the two loci in the future.

Single-trait, multi-locus and multi-trait GWAS using four different models for yield traits in bread wheat

A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01240-1.

Utilization of a Wheat50K SNP Microarray-Derived High-Density Genetic Map for QTL Mapping of Plant Height and Grain Traits in Wheat

Plant height is significantly correlated with grain traits, which is a component of wheat yield. The purpose of this study is to investigate the main quantitative trait loci (QTLs) that control plant height and grain-related traits in multiple environments. In this study, we constructed a high-density genetic linkage map using the Wheat50K SNP Array to map QTLs for these traits in 198 recombinant inbred lines (RILs). The two ends of the chromosome were identified as recombination-rich areas in all chromosomes except chromosome 1B. Both the genetic map and the physical map showed a significant correlation, with a correlation coefficient between 0.63 and 0.99. However, there was almost no recombination between 1RS and 1BS. In terms of plant height, 1RS contributed to the reduction of plant height by 3.43 cm. In terms of grain length, 1RS contributed to the elongation of grain by 0.11 mm. A total of 43 QTLs were identified, including eight QTLs for plant height (PH), 11 QTLs for thousand grain weight (TGW), 15 QTLs for grain length (GL), and nine QTLs for grain width (GW), which explained 1.36–33.08% of the phenotypic variation. Seven were environment-stable QTLs, including two loci (Qph.nwafu-4B and Qph.nwafu-4D) that determined plant height. The explanation rates of phenotypic variation were 7.39–12.26% and 20.11–27.08%, respectively. One QTL, Qtgw.nwafu-4B, which influenced TGW, showed an explanation rate of 3.43–6.85% for phenotypic variation. Two co-segregating KASP markers were developed, and the physical locations corresponding to KASP_AX-109316968 and KASP_AX-109519968 were 25.888344 MB and 25.847691 MB, respectively. Qph.nwafu-4B, controlling plant height, and Qtgw.nwafu-4B, controlling TGW, had an obvious linkage relationship, with a distance of 7–8 cM. Breeding is based on molecular markers that control plant height and thousand-grain weight by selecting strains with low plant height and large grain weight. Another QTL, Qgw.nwafu-4D, which determined grain width, had an explanation rate of 3.43–6.85%. Three loci that affected grain length were Qgl.nwafu-5A, Qgl.nwafu-5D.2, and Qgl.nwafu-6B, illustrating the explanation rates of phenotypic variation as 6.72–9.59%, 5.62–7.75%, and 6.68–10.73%, respectively. Two QTL clusters were identified on chromosomes 4B and 4D.

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.

Identification of Candidate Genes for Root Traits Using Genotype-Phenotype Association Analysis of Near-Isogenic Lines in Hexaploid Wheat (Triticum aestivum L.)

Global wheat (Triticum aestivum L.) production is constrained by different biotic and abiotic stresses, which are increasing with climate change. An improved root system is essential for adaptability and sustainable wheat production. In this study, 10 pairs of near-isogenic lines (NILs)-targeting four genomic regions (GRs) on chromosome arms 4BS, 4BL, 4AS, and 7AL of hexaploid wheat-were used to phenotype root traits in a semi-hydroponic system. Seven of the 10 NIL pairs significantly differed between their isolines for 11 root traits. The NIL pairs targeting qDSI.4B.1 GR varied the most, followed by the NIL pair targeting qDT.4A.1 and QHtscc.ksu-7A GRs. For pairs 5-7 targeting qDT.4A.1 GR, pair 6 significantly differed in the most root traits. Of the 4 NIL pairs targeting qDSI.4B.1 GR, pairs 2 and 4 significantly differed in 3 and 4 root traits, respectively. Pairs 9 and 10 targeting QHtscc.ksu-7A GR significantly differed in 1 and 4 root traits, respectively. Using the wheat 90K Illumina iSelect array, we identified 15 putative candidate genes associated with different root traits in the contrasting isolines, in which two UDP-glycosyltransferase (UGT)-encoding genes, TraesCS4A02G185300 and TraesCS4A02G442700, and a leucine-rich repeat receptor-like protein kinase (LRR-RLK)-encoding gene, TraesCS4A02G330900, also showed important functions for root trait control in other crops. This study characterized, for the first time, that these GRs control root traits in wheat, and identified candidate genes, although the candidate genes will need further confirmation and validation for marker-assisted wheat breeding.

A novel, validated, and plant height-independent QTL for spike extension length is associated with yield-related traits in wheat

A novel, stably expressed, and plant height-independent QTL for spike extension length on 5AS was identified and validated in different populations using a newly developed and tightly linked KASP marker. As an important component of plant height (PH), spike extension length (SEL) plays a significant role in formation of an ideotype in wheat. Despite the fact that numerous loci for SEL in wheat have been reported, our knowledge on PH-independent loci remains to be limited. In this study, two recombinant inbred line (RIL) populations genotyped using the Wheat55K SNP were used to detect quantitative trait loci (QTL) controlling SEL across six environments. A total of 30 QTL for SEL were detected in these two RIL populations, and four of them, i.e., QSEL.sicau-2CN-4D, QSEL.sicau-2SY-4B.2, QSEL.sicau-2SY-4D.1, and QSEL.sicau-2CN-5A, were stably expressed. Genetic and conditional QTL analysis showed that the first three were significantly associated with PH, while the last one, QSEL.sicau-2CN-5A, is independent of PH. Comparison of genetic and physical maps suggested that only QSEL.sicau-2CN-5A located on chromosome arm 5AS is likely a novel QTL. A Kompetitive Allele-Specific PCR (KASP) marker, KASP-AX-110413733, tightly linked to this novel QTL was developed to successfully confirm its effect in three different genetic populations. Further, in the interval where QSEL.sicau-2CN-5A was located on 'Chinese Spring' wheat reference genome, three promising genes mainly expressed in wheat stem were predicated and they all encode the cytochrome P450 that was demonstrated to be closely associated with SEL elongation in rice. In addition, significant correlations between SEL and PH, spikelet number per spike, and thousand-grain weight were also detected. Altogether, our results broaden our understanding on genetic basis of SEL and will be useful for marker-based selection of lines with different SELs and fine mapping the novel and PH-independent QTL QSEL.sicau-2CN-5A.

Identification of modifiers of the plant height in wheat using an induced dwarf mutant controlled by RhtB4c allele

In wheat, 25 Rht genes for dwarfness are known, which include both, GA-insensitive and GA-responsive genes. The GA-insensitive Rht genes have been widely used, although, their suitability under abiotic stress conditions has been questioned. This necessitated a search for alternative GA-responsive, spontaneous and induced dwarfing genes. We earlier reported an induced dwarf mutant ('dwarf mutant-3'; 44 cm), and the mutant allele was named Rht4c allele (2BL). This dwarf mutant was not suitable for cultivation due to its extra dwarf nature. Therefore, we searched for naturally occurring QTLs, which would modify the phenotype of 'dwarf-mutant-3' using 'mutant-assisted gene identification and characterization' (MAGIC) approach. For this purpose, the 'dwarf mutant-3' was crossed with a tall wheat cv. NP114 and homozygous mutant F2 plants (~ 25% of the progeny) were selected, which were phenotyped for plant height and genotyped using SSR markers. The data were utilized for QTL analysis and plant height. Six modifier QTLs were identified on chromosomes 2A, 2B and 4A. Two QTLs each on 2A and 2B were responsible for increase in plant height (described as 'enhancer modifiers'), whereas the remaining two QTLs located on 4A were responsible for reducing the plant height (described as 'suppressor modifiers'). It was hypothesized that the enhancer QTLs could be exploited for the development of semi-dwarf high yielding genotypes containing Rht4c allele. This is the first study of its kind in wheat demontsrating that the MAGIC approach could be used for identification of modifiers of the mutant phenotypes of other traits for wheat improvement.

Identification and Validation of a Novel Major Quantitative Trait Locus for Plant Height in Common Wheat (Triticum aestivum L.)

Plant height (PH) plays a pivotal role in plant morphological architecture and is associated with yield potential in wheat. For the quantitative trait locus (QTL) analysis, a recombinant inbred line population was developed between varieties differing significantly in PH. Two major QTL were identified on chromosomes 4B (QPh.sicau-4B) and 6D (QPh.sicau-6D) in multiple environments, which were then validated in two different backgrounds by using closely linked markers. QPh.sicau-4B explained 10.1-21.3% of the phenotypic variance, and the location corresponded to the dwarfing gene Rht-B1. QPh.sicau-6D might be a novel QTL for PH, explaining 6.6-13.6% of the phenotypic variance and affecting spike length, thousand-kernel weight, and spikelet compactness. Three candidate genes associated with plant growth and development were identified in the physical interval of QPh.sicau-6D. Collectively, we identified a novel stable and major PH QTL, QPh.sicau-6D, which could aid in the development of closely linked markers for marker-assisted breeding and cloning genes underlying this QTL.

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.

QTL mapping for flag leaf-related traits and genetic effect of QFLW-6A on flag leaf width using two related introgression line populations in wheat

The flag leaf is the main organ of photosynthesis during grain-filling period of wheat, and flag leaf-related traits affect plant morphology and yield potential. In this study, two BC₃F₆ introgression line (IL) populations derived from the common recipient parent Lumai 14 with Jing 411 and Shaanhan 8675, respectively, were used to map quantitative trait loci (QTL) for flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA) and chlorophyll content (CC) at flowering stage and 15 and 20 days after anthesis (DAA) in 2016–2017 (E1) and 2017–2018 (E2) two environments. A total of 14 and 15 QTLs for flag leaf-related traits were detected in Lumai 14 / Jing 411 and Lumai 14 / Shaanhan 8675 populations, respectively. Among them, Both QFLW-6A and QFLA-6A were detected in Lumai 14 / Jing 411 population under E2 and in Lumai 14 / Shaanhan 8675 population under E1 and E2 environments, respectively. QCC_S2-3A from Lumai 14 / Jing 411 population and QCC_S3-1A, QFLL-4A and QFLL-6A from Lumai 14 / Shaanhan 8675 population were repeatedly identified under two tested environments. Moreover, eight QTL clusters controlling flag leaf-related traits were identified, which provided a genetic basis for significant correlations in phenotype among these traits. On the other hand, positive alleles of QFLW-6A for FLW detected in two populations were derived from their donors. Eighteen lines and 44 lines carried this QTL were found in Lumai 14 / Jing 411 and Lumai 14 / Shaanhan 8675 populations, respectively. The means of FLW in these lines were wider than that of the recipient parent, Lumai 14, in two environments, suggesting that QFLW-6A played an important role for increasing FLW. The IL 124 in Lumai 14 / Jing 411 population and the IL 59 and IL 127 in Lumai 14 / Shaanhan 8675 population had five, five and four donor chromosomal segments which carried no other QTL controlling FLW than QFLW-6A, respectively. And the FLWs of these lines were significantly greater than that of Lumai 14 under two environments. So these lines and their donor parent can be regarded as potential near-isogenic lines. Further, a synteny analysis found QFLW-6A was near the 574,283,851–574,283,613 bp fragment on chromosome 6A and 10 genes were in the range of 500 kb upstream and downstream of the fragment. These results provide the basis for identification of candidate gene and map-based cloning and functional verification of the QTL.

Dissection of genetic factors underlying grain size and fine mapping of QTgw.cau-7D in common wheat (Triticum aestivum L.)

Thirty environmentally stable QTL controlling grain size and/or plant height were identified, among which QTgw.cau-7D was delimited into the physical interval of approximately 4.4 Mb. Grain size and plant height (PHT) are important agronomic traits in wheat breeding. To dissect the genetic basis of these traits, we conducted a quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs). In total, 30 environmentally stable QTL for thousand grain weight (TGW), grain length (GL), grain width (GW) and PHT were detected. Notably, one major pleiotropic QTL on chromosome arm 3DS explained the highest phenotypic variance for TGW, GL and PHT, and two stable QTL (QGw.cau-4B and QGw.cau-7D) on chromosome arms 4BS and 7DS contributed greater effects for GW. Furthermore, the stable QTL controlling grain size (QTgw.cau-7D and QGw.cau-7D) were delimited into the physical interval of approximately 4.4 Mb harboring 56 annotated genes. The elite NILs of QTgw.cau-7D increased TGW by 12.79-21.75% and GW by 4.10-8.47% across all three environments. Collectively, these results provide further insight into the genetic basis of TGW, GL, GW and PHT, and the fine-mapped QTgw.cau-7D will be an attractive target for positional cloning and marker-assisted selection in wheat breeding programs.

Mapping of QTL for total spikelet number per spike on chromosome 2D in wheat using a high-density genetic map

Total spikelet number per spike (TSS) is one of the key components of grain yield in wheat. Chromosome (chr.) 2D contains numerous genes that control TSS. In this study, we evaluated 138 F₈ recombinant inbred lines (RILs) derived from an F₂ population of a synthetic hexaploid wheat line (SHW-L1) and a common wheat cultivar (Chuanmai 32) for TSS in six different environments. To identify quantitative trait loci (QTL) for TSS, we constructed an integrated high-density genetic map of chr. 2D containing two simple sequence repeats, 35 diversity array technology markers, and 143 single nucleotide polymorphisms. We identified three stable QTL for TSS that individually explained 9.7–19.2% of the phenotypic variation and predicted 23 putative candidate genes within the QTL mapping interval. Overall, our results provide insight into the genetic basis of TSS in synthetic hexaploid wheat that may be useful in breeding high-yielding wheat cultivars.

Dissecting genetic loci affecting grain morphological traits to improve grain weight via nested association mapping

The quantitative trait loci (QTLs) for grain morphological traits were identified via nested association mapping and validated in a natural wheat population via haplotype analysis. Grain weight, one of the three most important components of crop yield, is largely determined by grain morphological traits. Dissecting the genetic bases of grain morphology could facilitate the improvement of grain weight and yield production. In this study, four wheat recombinant inbred line populations constructed by crossing the modern variety Yanzhan 1 with three semi-wild wheat varieties (i.e., Chayazheda, Yutiandaomai, and Yunnanxiaomai from Xinjiang, Tibet, and Yunnan, respectively) and one exotic accession Hussar from Great Britain were investigated for grain weight and eight morphological traits in seven environments. Eighty-eight QTLs for all measured traits were totally identified through nested association mapping utilizing 14,643 high-quality polymorphic single nucleotide polymorphism (SNP) markers generated by 90 K SNP array. Among them, 64 (72.7%) QTLs have the most favorable alleles donated by semi-wild wheat varieties. For 14 QTL clusters affecting at least two grain morphological traits, nine QTL clusters were located in similar position with known genes/QTL, and the other five were novel. Three important novel QTLs (i.e., qTGW-1B.1, qTGW-1B.2, and qTGW-1A.1) were further validated in a natural wheat population via haplotype analysis. The favorable haplotypes for these three QTLs might be used in marker-assisted selection for the improvement of wheat yield by modifying morphological traits.

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.