Use of near-isogenic lines to precisely map and validate a major QTL for grain weight on chromosome 4AL in bread wheat (Triticum aestivum L.)

Exploring the Drought Tolerant Quantitative Trait Loci in Spring Wheat

Drought-induced stress poses a significant challenge to wheat throughout its growth, underscoring the importance of identifying drought-stable quantitative trait loci (QTLs) for enhancing grain yield. Here, we evaluated 18 yield-related agronomic and physiological traits, along with their drought tolerance indices, in a recombinant inbred line population derived from the XC7 × XC21 cross. These evaluations were conducted under both non-stress and drought-stress conditions. Drought stress significantly reduced grain weight per spike and grain yield per plot. Genotyping the recombinant inbred line population using the wheat 90K single nucleotide polymorphism array resulted in the identification of 131 QTLs associated with the 18 traits. Drought stress also exerted negative impacts on grain formation and filling, directly leading to reductions in grain weight per spike and grain yield per plot. Among the identified QTLs, 43 were specifically associated with drought tolerance across the 18 traits, with 6 showing direct linkages to drought tolerance in wheat. These results provide valuable insights into the genetic mechanisms governing wheat growth and development, as well as the traits contributing to the drought tolerance index. Moreover, they serve as a theoretical foundation for the development of new wheat cultivars having exceptional drought tolerance and high yield potentials under both drought-prone and drought-free conditions.

Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat

KEY MESSAGE

A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individuals derived from residual heterozygous lines (RHLs) self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19 Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, which provides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.

Characterization and fine mapping analysis of a major stable QTL qKnps-4A for kernel number per spike in wheat

KEY MESSAGE

A major stable QTL for kernel number per spike was narrowed down to a 2.19-Mb region containing two potential candidate genes, and its effects on yield-related traits were characterized. Kernel number per spike (KNPS) in wheat is a key yield component. Dissection and characterization of major stable quantitative trait loci (QTLs) for KNPS would be of considerable value for the genetic improvement of yield potential using molecular breeding technology. We had previously reported a major stable QTL controlling KNPS, qKnps-4A. In the current study, primary fine-mapping analysis, based on the primary mapping population, located qKnps-4A to an interval of approximately 6.8-Mb from 649.0 to 655.8 Mb on chromosome 4A refering to 'Kenong 9204' genome. Further fine-mapping analysis based on a secondary mapping population narrowed qKnps-4A to an approximately 2.19-Mb interval from 653.72 to 655.91 Mb. Transcriptome sequencing, gene function annotation analysis and homologous gene related reports showed that TraesKN4A01HG38570 and TraesKN4A01HG38590 were most likely to be candidate genes of qKnps-4A. Phenotypic analysis based on paired near-isogenic lines in the target region showed that qKnps-4A increased KNPS mainly by increasing the number of central florets per spike. We also evaluated the effects of qKnps-4A on other yield-related traits. Moreover, we dissected the QTL cluster of qKnps-4A and qTkw-4A and proved that the phenotypic effects were probably due to close linkage of two or more genes rather than pleiotropic effects of a single gene. This study provides molecular marker resource for wheat molecular breeding designed to improve yield potential, and lay the foundation for gene functional analysis of qKnps-4A.

Precisely mapping a major QTL for grain weight on chromosome 5B of the founder parent Chuanmai42 in the wheat-growing region of southwestern China

KEY MESSAGE

QTgw.saas-5B was validated as a major thousand-grain weight-related QTL in a founder parent used for wheat breeding and then precisely mapped to a 0.6 cM interval. Increasing the thousand-grain weight (TGW) is considered to be one of the most important ways to improve yield, which is a core objective among wheat breeders. Chuanmai42, which is a wheat cultivar with high TGW and a high and stable yield, is a parent of more than 30 new varieties grown in southwestern China. In this study, a Chuanmai42-derived recombinant inbred line (RIL) population was used to dissect the genetic basis of TGW. A major QTL (QTgw.saas-5B) mapped to the Xgwm213-Xgwm540 interval on chromosome 5B of Chuanmai42 explained up to 20% of the phenotypic variation. Using 71 recombinants with a recombination in the QTgw.saas-5B interval identified from a secondary RIL population comprising 1818 lines constructed by crossing the QTgw.saas-5B near-isogenic line with the recurrent parent Chuannong16, QTgw.saas-5B was delimited to a 0.6 cM interval, corresponding to a 21.83 Mb physical interval in the Chinese Spring genome. These findings provide the foundation for QTgw.saas-5B cloning and its use in molecular marker-assisted 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.

A wheat integrative regulatory network from large-scale complementary functional datasets enables trait-associated gene discovery for crop improvement

Gene regulation is central to all aspects of organism growth, and understanding it using large-scale functional datasets can provide a whole view of biological processes controlling complex phenotypic traits in crops. However, the connection between massive functional datasets and trait-associated gene discovery for crop improvement is still lacking. In this study, we constructed a wheat integrative gene regulatory network (wGRN) by combining an updated genome annotation and diverse complementary functional datasets, including gene expression, sequence motif, transcription factor (TF) binding, chromatin accessibility, and evolutionarily conserved regulation. wGRN contains 7.2 million genome-wide interactions covering 5947 TFs and 127 439 target genes, which were further verified using known regulatory relationships, condition-specific expression, gene functional information, and experiments. We used wGRN to assign genome-wide genes to 3891 specific biological pathways and accurately prioritize candidate genes associated with complex phenotypic traits in genome-wide association studies. In addition, wGRN was used to enhance the interpretation of a spike temporal transcriptome dataset to construct high-resolution networks. We further unveiled novel regulators that enhance the power of spike phenotypic trait prediction using machine learning and contribute to the spike phenotypic differences among modern wheat accessions. Finally, we developed an interactive webserver, wGRN (http://wheat.cau.edu.cn/wGRN), for the community to explore gene regulation and discover trait-associated genes. Collectively, this community resource establishes the foundation for using large-scale functional datasets to guide trait-associated gene discovery for crop improvement.

Mapping a leaf rust resistance gene LrOft in durum wheat Ofanto and its suppressor SuLrOft in common wheat

Epidemics of leaf rust (caused by the fungal pathogen Puccinia triticina Erikss., Pt) raise concerns regarding sustainability of wheat production. Deployment of resistant cultivars is the most effective and economic strategy for combating this disease. Ofanto is a durum wheat cultivar that exhibits high resistance to Pt race PHT throughout its entire growing period. In the present study, we identified a leaf rust resistance gene in Ofanto and temporarily designated it as LrOft. LrOft was mapped to a 2.5 cM genetic interval in chromosome arm 6BL between Indel markers 6B6941 and 6B50L24. During introgression of LrOft from Ofanto to common wheat it was observed that F₁ plants of Ofanto crossed with Shi4185 exhibited leaf rust resistance whereas the F₁ of Ofanto crossed with ND4503 was susceptible. In order to map the presumed suppressor locus, a Shi4185/ND4503//Ofanto three-way pentaploid population was generated and SuLrOft was mapped on chromosome arm 2AS. SuLrOft was mapped within a 2.6 cM genetic interval flanked by 2AS50L14 and 2AS50L6. Fine mapping using 2,268 plants of the three-way cross narrowed the suppressor locus to a 68.2-kbp physical interval according to IWGSC RefSeq v1.1. Sequence analysis of genes in the physical interval revealed that TraesCS2A02G110800 encoding an RPP-13-like protein with an NB-ARC domain was a potential candidate for SuLrOft.

A 'wiring diagram' for sink strength traits impacting wheat yield potential

Identifying traits for improving sink strength is a bottleneck to increasing wheat yield. The interacting processes determining sink strength and yield potential are reviewed and visualized in a set of 'wiring diagrams', covering critical phases of development (and summarizing known underlying genetics). Using this framework, we reviewed and assembled the main traits determining sink strength and identified research gaps and potential hypotheses to be tested for achieving gains in sink strength. In pre-anthesis, grain number could be increased through: (i) enhanced spike growth associated with optimized floret development and/or a reduction in specific stem-internode lengths and (ii) improved fruiting efficiency through an accelerated rate of floret development, improved partitioning between spikes, or optimized spike cytokinin levels. In post-anthesis, grain, sink strength could be augmented through manipulation of grain size potential via ovary size and/or endosperm cell division and expansion. Prospects for improving spike vascular architecture to support all rapidly growing florets, enabling the improved flow of assimilate, are also discussed. Finally, we considered the prospects for enhancing grain weight realization in relation to genetic variation in stay-green traits as well as stem carbohydrate remobilization. The wiring diagrams provide a potential workspace for breeders and crop scientists to achieve yield gains in wheat and other field crops.

Genetic identification of the pleiotropic gene Tasg-D1/2 affecting wheat grain shape by regulating brassinolide metabolism

Improving yield potential is a major goal of wheat breeding that depends on identifying key genetic loci. In this study, two residual heterozygous line RHL351- and RHL78-derived populations were employed for genetic linkage map construction and QTL detection. Two genetic populations indicated a robust grain-size QTL between Marker6 and Marker10. It covered a 95.54-99.38 Mb physical interval and was named Qpleio.nwafu.3D, containing the candidate gene Tasg (TraesCS3D02G137200). Intriguingly, RNA-seq analysis and sequencing revealed two different allelic variants in Tasg, named Tasg-D1 (G>A) and Tasg-D2 (C>G), respectively. Although the relationship between Tasg-D1 and grain size had been demonstrated previously, here we provided the first genetic evidence that C/G allelic variation in Tasg-D2 was associated with grain shape and size through a newly developed dCAPS marker. In addition, transcriptome comparison indicated that Tasg-D1/2 might primarily contribute to significant expression differences in brassinolide (BR) metabolism-related genes rather than those related to BR responses in developing grains and spikes. Our study provided new evidence and a breeder-friendly dCAPS marker for improving grain size through the selection of Tasg, as well as a basis to understand Tasg function in the future.

Cloning and Functional Analysis of TaWRI1Ls, the Key Genes for Grain Fatty Acid Synthesis in Bread Wheat

WRINKLED1 (WRI1), an APETALA2 (AP2) transcription factor (TF), critically regulates the processes related to fatty acid synthesis, storage oil accumulation, and seed development in plants. However, the WRI1 genes remain unknown in allohexaploid bread wheat (Triticum aestivum L.). In this study, based on the sequence of Arabidopsis AtWRI1, two TaWRI1Ls genes of bread wheat, TaWRI1L1 and TaWRI1L2, were cloned. TaWRI1L2 was closely related to monocotyledons and clustered in one subgroup with AtWRI1, while TaWRI1L1 was clustered in another subgroup with AtWRI3 and AtWRI4. Both were expressed highly in the developmental grain, subcellular localized in the nucleus, and showed transcriptional activation activity. TaWRI1L2, rather than TaWRI1L1, promoted oil body accumulation and significantly increased triglyceride (TAG) content in tobacco leaves. Overexpression of TaWRI1L2 compensated for the functional loss of AtWRI1 in an Arabidopsis mutant and restored the wild-type phenotypes of seed shape, generation, and fatty acid synthesis and accumulation. Knockout of TaWRI1L2 reduced grain size, 1000 grain weight, and grain fatty acid synthesis in bread wheat. Conclusively, TaWRI1L2, rather than TaWRI1L1, was the key transcriptional factor in the regulation of grain fatty acid synthesis in bread wheat. This study lays a foundation for gene regulation and genetic manipulation of fatty acid synthesis in wheat genetic breeding programs.

Combined morpho-physiological, ionomic and transcriptomic analyses reveal adaptive responses of allohexaploid wheat (Triticum aestivum L.) to iron deficiency

BACKGROUND

Plants worldwide are often stressed by low Fe availability around the world, especially in aerobic soils. Therefore, the plant growth, seed yield, and quality of crop species are severely inhibited under Fe deficiency. Fe metabolism in plants is controlled by a series of complex transport, storage, and regulatory mechanisms in cells. Allohexaploid wheat (Triticum aestivum L.) is a staple upland crop species that is highly sensitive to low Fe stresses. Although some studies have been previously conducted on the responses of wheat plants to Fe deficiency, the key mechanisms underlying adaptive responses are still unclear in wheat due to its large and complex genome.

RESULTS

Transmission electron microscopy showed that the chloroplast structure was severely damaged under Fe deficiency. Paraffin sectioning revealed that the division rates of meristematic cells were reduced, and the sizes of elongated cells were diminished. ICP-MS-assisted ionmics analysis showed that low-Fe stress significantly limited the absorption of nutrients, including N, P, K, Ca, Mg, Fe, Mn, Cu, Zn, and B nutrients. High-throughput transcriptome sequencing identified 378 and 2,619 genome-wide differentially expressed genes (DEGs) were identified in the shoots and roots between high-Fe and low-Fe conditions, respectively. These DEGs were mainly involved in the Fe chelator biosynthesis, ion transport, photosynthesis, amino acid metabolism, and protein synthesis. Gene coexpression network diagrams indicated that TaIRT1b-4A, TaNAS2-6D, TaNAS1a-6A, TaNAS1-6B, and TaNAAT1b-1D might function as key regulators in the adaptive responses of wheat plants to Fe deficiency.

CONCLUSIONS

These results might help us fully understand the morpho-physiological and molecular responses of wheat plants to low-Fe stress, and provide elite genetic resources for the genetic modification of efficient Fe use.

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.

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 fine mapping of alien fragments associated with enhanced grain weight from Agropyron cristatum chromosome 7P in common wheat backgrounds

An enhanced grain weight locus from Agropyron cristatum chromosome 7P was verified in two wheat backgrounds, localized to the 7PS1-2 region. Novel translocation lines with this locus were evaluated. Agropyron cristatum is a wild relative of wheat that harbours elite genes for wheat improvement. The wheat-A. cristatum 7P disomic addition line II-5-1 exhibits high grain weight. Here, to dissect the genetic basis of grain weight contributed by A. cristatum chromosome 7P in wheat backgrounds, four segregated populations of the addition line were developed and evaluated in two wheat backgrounds. The results showed that A. cristatum chromosome 7P can stably and significantly increase the grain weight by approximately 2 g, mainly by increasing grain length at different grain weight levels of the wheat background. The locus for increased grain weight from chromosome 7P shows dominant inheritance independent of the wheat background. Moreover, two deletion lines and 23 translocation lines were identified by cytological methods and molecular markers, and an enlarged chromosome 7P bin map was constructed with 158 STS markers and 40 bin intervals. With the genetic populations of these deletion and translocation lines, the genetic locus of increased grain weight was narrowed down to bin 7PS1-2. Two translocation lines (7PT-A18 and 7PT-B4) with smaller 7P chromosomal segments exhibited an increase in grain weight, grain length and grain width simultaneously. These translocation lines carrying the 7PS1-2 chromosomal fragment will be valuable genetic resources for wheat grain weight improvement. Collectively, this study uncovers the grain weight locus from chromosome 7P and provides novel pre-breeding lines with enhanced grain weight.

Fine mapping and validation of a major QTL for grain weight on chromosome 5B in bread wheat

A major QTL QTgw.caas-5B for thousand grain weight in wheat was fine mapped on chromosome 5B, and TraesCS5B02G044800 was predicted to be the candidate gene. Thousand grain weight (TGW), determined by grain length and width, and is an important yield component in wheat; understanding of the underlying genes and molecular mechanisms remains limited. A stable QTL QTgw.caas-5B for TGW was identified previously in a RIL population developed from a cross between Zhongmai 871 (ZM871) and a sister line Zhongmai 895 (ZM895), and the aim of this study was to perform fine mapping and validate the genetic effect of the QTL. It was delimited to an interval of approximately 2.0 Mb flanked by markers Kasp_5B29 and Kasp_5B31 (49.6-51.6 Mb) using 12 heterozygous recombinant plants obtained by selfing a residual BC₁F₆ line selected from the ZM871/ZM895//ZM871 population. A candidate gene was predicted following sequencing and differential expression analyses. Marker Kasp_5B_Tgw based on a SNP in TraesCS5B02G044800, the QTgw.caas-5B candidate, was developed and validated in a diversity panel of 166 cultivars. The precise mapping of QTgw.caas-5B laid a foundation for cloning of a predicted causal gene and provides a molecular marker for improving grain yield in wheat.

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.

A Collinearity-Incorporating Homology Inference Strategy for Connecting Emerging Assemblies in the Triticeae Tribe as a Pilot Practice in the Plant Pangenomic Era

Plant genome sequencing has dramatically increased, and some species even have multiple high-quality reference versions. Demands for clade-specific homology inference and analysis have increased in the pangenomic era. Here we present a novel method, GeneTribe (https://chenym1.github.io/genetribe/), for homology inference among genetically similar genomes that incorporates gene collinearity and shows better performance than traditional sequence-similarity-based methods in terms of accuracy and scalability. The Triticeae tribe is a typical allopolyploid-rich clade with complex species relationships that includes many important crops, such as wheat, barley, and rye. We built Triticeae-GeneTribe (http://wheat.cau.edu.cn/TGT/), a homology database, by integrating 12 Triticeae genomes and 3 outgroup model genomes and implemented versatile analysis and visualization functions. With macrocollinearity analysis, we were able to construct a refined model illustrating the structural rearrangements of the 4A-5A-7B chromosomes in wheat as two major translocation events. With collinearity analysis at both the macro- and microscale, we illustrated the complex evolutionary history of homologs of the wheat vernalization gene Vrn2, which evolved as a combined result of genome translocation, duplication, and polyploidization and gene loss events. Our work provides a useful practice for connecting emerging genome assemblies, with awareness of the extensive polyploidy in plants, and will help researchers efficiently exploit genome sequence resources.

Identification and validation of quantitative trait loci for kernel traits in common wheat (Triticum aestivum L.)

BACKGROUND

Kernel weight and morphology are important traits affecting cereal yields and quality. Dissecting the genetic basis of thousand kernel weight (TKW) and its related traits is an effective method to improve wheat yield.

RESULTS

In this study, we performed quantitative trait loci (QTL) analysis using recombinant inbred lines derived from the cross 'PuBing3228 × Gao8901' (PG-RIL) to dissect the genetic basis of kernel traits. A total of 17 stable QTLs related to kernel traits were identified, notably, two stable QTLs QTkw.cas-1A.2 and QTkw.cas-4A explained the largest portion of the phenotypic variance for TKW and kernel length (KL), and the other two stable QTLs QTkw.cas-6A.1 and QTkw.cas-7D.2 contributed more effects on kernel width (KW). Conditional QTL analysis revealed that the stable QTLs for TKW were mainly affected by KW. The QTLs QTkw.cas-7D.2 and QKw.cas-7D.1 associated with TKW and KW were delimited to the physical interval of approximately 3.82 Mb harboring 47 candidate genes. Among them, the candidate gene TaFT-D1 had a 1 bp insertions/deletion (InDel) within the third exon, which might be the reason for diversity in TKW and KW between the two parents. A Kompetitive Allele-Specific PCR (KASP) marker of TaFT-D1 allele was developed and verified by PG-RIL and a natural population consisted of 141 cultivar/lines. It was found that the favorable TaFT-D1 (G)-allele has been positively selected during Chinese wheat breeding. Thus, these results can be used for further positional cloning and marker-assisted selection in wheat breeding programs.

CONCLUSIONS

Seventeen stable QTLs related to kernel traits were identified. The stable QTLs for thousand kernel weight were mainly affected by kernel width. TaFT-D1 could be the candidate gene for QTLs QTkw.cas-7D.2 and QKw.cas-7D.1.

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.

Dissection and validation of a QTL cluster linked to Rht-B1 locus controlling grain weight in common wheat (Triticum aestivum L.) using near-isogenic lines

This study dissected and validated a QTL cluster associated with thousand grain weight on chromosome 4B using multiple near-isogenic lines in common wheat. Grain size and weight are crucial components of wheat yield. Previously, we identified a QTL cluster for thousand grain weight (TGW) on chromosome 4B using the Nongda3338 (ND3338)/Jingdong6 (JD6) doubled haploid population. Here, near-isogenic lines (NILs) in the ND3338 background were developed to dissect and validate the QTL cluster. Based on six independent BC₃F_3:4 heterogeneous inbred families, the 4B QTL cluster was divided into two linked QTL intervals (designated 4B.1 and 4B.2 QTL). For the 4B.1 QTL, the Rht-B1 gene, of which Rht-B1b allele reduces plant height (PH) by 21.18-29.34 cm (34.34-53.71%), was demonstrated to be the most likely candidate gene with pleiotropic effects on grain size and TGW. For the 4B.2 QTL, the NIL^JD6 consistently showed an increase in TGW of 3.51-7.68 g (8.84-22.77%) compared with NIL^ND3338 across different field trials, along with a significant increase in PH of 2.26-6.71 cm (3.92-12.01%). Moreover, both QTL intervals had a larger effect on grain width than on grain length. Additionally, the first significant difference in 100-grain fresh weight and 100-grain dry weight between the NIL pairs of the 4B.1 QTL interval (Rht-B1) was observed at 6 days after pollination (DAP), while the differences were first visible at 30 DAP for the 4B.2 QTL interval. Collectively, our work provides a new example of QTL dissection for grain weight in wheat and lays a foundation for further map-based cloning of the major QTL that have potential applications in wheat molecular breeding for high yield.

Genome-Wide Association Analysis Identifies Candidate Genes Regulating Seed Number Per Silique in Arabidopsis thaliana

Seed weight and number ultimately determine seed yield. Arabidopsis seed number comprised of silique number and seed number per silique (SNS). Comparing seed development and weight, determinants of seed number remain largely uncharacterized. In this study, taking advantage of 107 available Arabidopsis accessions, genome-wide association analysis (GWAS) was employed to identify the candidate genes regulating SNS. GWAS-based genotype and phenotype association analysis identified 38 most significant SNPs marker sites that were mapped to specific chromosomal positions and allowed us to screen for dozens of candidate genes. One of them (PIN3) was selected for functional validation based on gene expression analysis. It is a positive regulator of Arabidopsis SNS. Although silique length of PIN3 loss of function mutant was not significantly changed, its SNS and seed density (SD) were significantly reduced as compared with the wild type. Notably, PIN3 overexpression lines driven by a placenta-specific promoter STK exhibited significantly shorter siliques, slightly reduced SNS, but significant increased SD compared with wild type, suggesting that PIN3 positively regulates SD through inducing ovule primordia initiation regardless of the placenta size. Ovule initiation determines the maximal possibility of SNS, and new genes and mechanism regulating SNS through modulating ovule initiation is worth further investigated.

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.

Quantitative trait loci for seeding root traits and the relationships between root and agronomic traits in common wheat

A completely developed and vigorous root system can provide a stable platform for aboveground plant organs. To identify loci controlling root traits that could be used in wheat (Triticum aestivum L.) breeding, 199 recombinant inbred lines were used to measure and analyze eight root traits. A total of 18 quantitative trait loci (QTL) located on chromosomes 1A, 2A, 2B, 2D, 4B, 4D, 6A, 7A, and 7B were identified. The phenotypic variation explained by these 18 QTL ranged from 3.27% to 11.75%, and the logarithm of odds scores ranged from 2.50 to 6.58. A comparison of physical intervals indicated several new QTL for root traits were identified. In addition, significant correlations between root and agronomic traits were detected and discussed. The results presented in this study, along with those of previous reports, suggest that chromosomes 2 and 7 likely play important roles in the growth and development of wheat roots.