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.

Quantitative trait loci detection for three tiller-related traits and the effects on wheat (Triticum aestivum L.) yields.

KEY MESSAGE: A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for tiller-related traits were reported, and the candidate genes underlying qMtn-KJ-5D, a novel major and stable QTL for maximum tiller number, were characterized. Tiller-related traits play an important role in determining the yield potential of wheat. Therefore, it is important to elucidate the genetic basis for tiller number when attempting to use genetic improvement as a tool for enhancing wheat yields. In this study, a quantitative trait locus (QTL) analysis of three tiller-related traits was performed on the recombinant inbred lines (RILs) of a mapping population, referred to as KJ-RILs, that was derived from a cross between the Kenong 9204 (KN9204) and Jing 411 (J411) lines. A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for spike number per plant (SNPP), maximum tiller number (MTN), and ear-bearing tiller rate (EBTR) were detected in eight different environments. Among these QTLs with additive effects, three major and stable QTLs were first documented herein. Almost all but two pairwise epistatic QTLs showed minor interaction effects accounting for no more than 3.0% of the phenotypic variance. The genetic effects of two colocated major and stable QTLs, i.e., qSnpp-KJ-5D.1 and qMtn-KJ-5D, for yield-related traits were characterized. The breeding selection effect of the beneficial allele for the two QTLs was characterized, and its genetic effects on yield-related traits were evaluated. The candidate genes underlying qMtn-KJ-5D were predicted based on multi-omics data, and TraesKN5D01HG00080 was identified as a likely candidate gene. Overall, our results will help elucidate the genetic architecture of tiller-related traits and can be used to develop novel wheat varieties with high yields.

Genome-wide association study and genomic selection of spike-related traits in bread wheat.

KEY MESSAGE: Identification of 337 stable MTAs for wheat spike-related traits improved model accuracy, and favorable alleles of MTA259 and MTA64 increased grain weight and yield per plant. Wheat (Triticum aestivum L.) is one of the three primary global, staple crops. Improving spike-related traits in wheat is crucial for optimizing spike and plant morphology, ultimately leading to increased grain yield. Here, we performed a genome-wide association study using a dataset of 24,889 high-quality unique single-nucleotide polymorphisms (SNPs) and phenotypic data from 314 wheat accessions across eight diverse environments. In total, 337 stable and significant marker-trait associations (MTAs) related to spike-related traits were identified. MTA259 and MTA64 were consistently detected in seven and six environments, respectively. The presence of favorable alleles associated with MTA259 and MTA64 significantly reduced wheat spike exsertion length and spike length, while enhancing thousand kernel weight and yield per plant. Combined gene expression and network analyses identified TraesCS6D03G0692300 and TraesCS6D03G0692700 as candidate genes for MTA259 and TraesCS2D03G0111700 and TraesCS2D03G0112500 for MTA64. The identified MTAs significantly improved the prediction accuracy of each model compared with using all the SNPs, and the random forest model was optimal for genome selection. Additionally, the eight stable and major MTAs, including MTA259, MTA64, MTA66, MTA94, MTA110, MTA165, MTA180, and MTA164, were converted into cost-effective and efficient detection markers. This study provided valuable genetic resources and reliable molecular markers for wheat breeding programs.

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.

The pathway of melatonin biosynthesis in common wheat (Triticum aestivum).

Melatonin (Mel) is a multifunctional biomolecule found in both animals and plants. In plants, the biosynthesis of Mel from tryptophan (Trp) has been delineated to comprise of four consecutive reactions. However, while the genes encoding these enzymes in rice are well characterized no systematic evaluation of the overall pathway has, as yet, been published for wheat. In the current study, the relative contents of six Mel-pathway-intermediates including Trp, tryptamine (Trm), serotonin (Ser), 5-methoxy tryptamine (5M-Trm), N-acetyl serotonin (NAS) and Mel, were determined in 24 independent tissues spanning the lifetime of wheat. These studies indicated that Trp was the most abundant among the six metabolites, followed by Trm and Ser. Next, the candidate genes expressing key enzymes involved in the Mel pathway were explored by means of metabolite-based genome-wide association study (mGWAS), wherein two TDC genes, a T5H gene and one SNAT gene were identified as being important for the accumulation of Mel pathway metabolites. Moreover, a 463-bp insertion within the T5H gene was discovered that may be responsible for variation in Ser content. Finally, a ASMT gene was found via sequence alignment against its rice homolog. Validations of these candidate genes were performed by in vitro enzymatic reactions using proteins purified following recombinant expression in Escherichia coli, transient gene expression in tobacco, and transgenic approaches in wheat. Our results thus provide the first comprehensive investigation into the Mel pathway metabolites, and a swift candidate gene identification via forward-genetics strategies, in common wheat.

Fine mapping of QFlw-5B, a major QTL for flag leaf width in common wheat (Triticum aestivum L.).

KEY MESSAGE: A major stable QTL for flag leaf width was narrowed down to 2.5 Mb region containing two predicated putative candidate genes, and its effects on yield-related traits was characterized. Flag leaf width (FLW) is important to production in wheat. In a previous study, a major quantitative trait locus for FLW (QFlw-5B) was detected on chromosome 5B, within an interval of 6.5 cM flanked by the markers of XwPt-9103 and Xbarc142, using a mapping population of recombinant inbred lines derived from a cross between Kenong9204 (KN9204) and Jing411 (J411) (denoted as KJ-RILs). The aim of this study was to fine map QFlw-5B and characterize its genetic effects on yield-related traits. Multiple near-isogenic lines (NILs) were developed using one residual heterozygous line for QFlw-5B. Five recombinants for QFlw-5B were identified, and its location was narrowed to a 2.5 Mb region based on combined phenotypic and genotypic data analysis. This region contained 27 predicted genes, two of which were considered as the most likely candidate genes for QFlw-5B. The FLW of NIL-KN9204 was significantly higher than that of NIL-J411 across all the tested environments. Meanwhile, significant increases in plant height, grain width and 1000-grain weight were observed in NIL-KN9204 compared with that in NIL-J411. These results indicate that QFlw-5B has great potential for marker-assisted selection in wheat breeding programs designed to improve both plant architecture and yield. This study also provides a basis for the map-based cloning of QFlw-5B.

The brassinosteroid biosynthesis gene TaD11-2A controls grain size and its elite haplotype improves wheat grain yields.

KEY MESSAGE: TaD11-2A affects grain size and root length and its natural variations are associated with significant differences in yield-related traits in wheat. Brassinosteroids (BRs) control many important agronomic traits and therefore the manipulation of BR components could improve crop productivity and performance. However, the potential effects of BR-related genes on yield-related traits and stress tolerance in wheat (Triticum aestivum L.) remain poorly understood. Here, we identified TaD11 genes in wheat (rice D11 orthologs) that encoded enzymes involved in BR biosynthesis. TaD11 genes were highly expressed in roots (Zadoks scale: Z11) and grains (Z75), while expression was significantly suppressed by exogenous BR (24-epiBL). Ectopic expression of TaD11-2A rescued the abnormal panicle structure and plant height (PH) of the clustered primary branch 1 (cpb1) mutant, and also increased endogenous BR levels, resulting in improved grain yields and grain quality in rice. The tad11-2a-1 mutant displayed dwarfism, smaller grains, sensitivity to 24-epiBL, and reduced endogenous BR contents. Natural variations in TaD11-2A were associated with significant differences in yield-related traits, including PH, grain width, 1000-grain weight, and grain yield per plant, and its favorable haplotype, TaD11-2A-HapI was subjected to positive selection during wheat breeding. Additionally, TaD11-2A influenced root length and salt tolerance in rice and wheat at seedling stages. These results indicated the important role of BR TaD11 biosynthetic genes in controlling grain size and root length, and also highlighted their potential in the molecular biological analysis of wheat.

Metabolomics analysis and metabolite-agronomic trait associations using kernels of wheat (Triticum aestivum) recombinant inbred lines.

Plants produce numerous metabolites that are important for their development and growth. However, the genetic architecture of the wheat metabolome has not been well studied. Here, utilizing a high-density genetic map, we conducted a comprehensive metabolome study via widely targeted LC-MS/MS to analyze the wheat kernel metabolism. We further combined agronomic traits and dissected the genetic relationship between metabolites and agronomic traits. In total, 1260 metabolic features were detected. Using linkage analysis, 1005 metabolic quantitative trait loci (mQTLs) were found distributed unevenly across the genome. Twenty-four candidate genes were found to modulate the levels of different metabolites, of which two were functionally annotated by in vitro analysis to be involved in the synthesis and modification of flavonoids. Combining the correlation analysis of metabolite-agronomic traits with the co-localization of methylation quantitative trait locus (mQTL) and phenotypic QTL (pQTL), genetic relationships between the metabolites and agronomic traits were uncovered. For example, a candidate was identified using correlation and co-localization analysis that may manage auxin accumulation, thereby affecting number of grains per spike (NGPS). Furthermore, metabolomics data were used to predict the performance of wheat agronomic traits, with metabolites being found that provide strong predictive power for NGPS and plant height. This study used metabolomics and association analysis to better understand the genetic basis of the wheat metabolism which will ultimately assist in wheat breeding.

QTL for spike-layer uniformity and their influence on yield-related traits in wheat.

BACKGROUND: Common wheat (Triticum aestivum L.) is one of the most important food crops worldwide. Wheat spike-layer uniformity related traits (SLURTs) were complex traits that directly affect yield potential and appearance. In this study, quantitative trait locus (QTL) for five SLURTs among inter-tillers were first documented using a recombinant inbred line (RIL) mapping population derived from a cross between Kenong9204 and Jing411 (represented by KJ-RILs). Genetic relationships between SLURTs and yield were characterized in detail. RESULTS: The trait phenotypic performances for the 188 KJ-RILs and their parents were evaluated in eight different environments. The genetic data included in a high-density genetic map derived from the Affymetrix 660 K SNP Array and the corresponding genotypes in each lines. Of 99 putative additive QTL 11 were stable across environments and 57 showed significant additive-by-environment interaction effects. These QTL individually explained 1.05-39.62% of the phenotypic variance, with log of odds (LOD) values ranging from 2.00 to 34.01. Genetic relationships between SLURTs and yield indicated that plants with slight uneven spike spatial distribution should be an ideotype for super high-yield in wheat. CONCLUSIONS: The present study will provide assistance in understanding the genetic relationships between SLURTs and yield potential. The 11 stable QTL for SLURTs identified herein may facilitate breeding new wheat varieties with scientifically reasonable spike-layer distribution by marker assisted selection.

Identification of QTL regions for seedling root traits and their effect on nitrogen use efficiency in wheat (Triticum aestivum L.).

KEY MESSAGE: QTL for a wheat ideotype root system and its plasticity to nitrogen deficiency were characterized. Root system architecture-related traits (RRTs) and their plasticity to nitrogen availability are important for nitrogen acquisition and yield formation in wheat (Triticum aestivum L.). In this study, quantitative trait loci (QTL) analysis was conducted under different nitrogen conditions, using the seedlings of 188 recombinant inbred lines derived from a cross between Kenong 9204 and Jing 411. Fifty-three QTL for seven RRTs and fourteen QTL for the plasticity of these RRTs to nitrogen deficiency were detected. Thirty of these QTL were mapped in nine clusters on chromosomes 2B, 2D, 3A, 3D, 6B, 6D, 7A and 7B. Six of these nine clusters were also colocated with loci for nitrogen use efficiency (NUE)-related traits (NRTs). Among them, three QTL clusters (C2B, C6D and C7B) were highlighted, considering that they individually harbored three stable robust QTL (i.e., QMrl-2B.1, QdRs-6D and QMrl-7B). C2B and C7B stably contributed to the optimal root system, and C6D greatly affected the plasticity of RRTs in response to nitrogen deficiency. However, strong artificial selection was only observed for C7B in 574 derivatives of Kenong 9204. Covariance analysis identified QMrl-7B as the major contributor in C7B that affected the investigated NRTs in mature plants. Phenotypic analysis indicated that thousand kernel weight might represent a "concomitant" above-ground trait of the "hidden" RRTs controlled by C7B, which are used for breeding selection. Dissecting these QTL regions with potential breeding value will ultimately facilitate the selection of donor lines with both high yield and NUE in wheat breeding programs.

Characterization of the temporal and spatial expression of wheat (Triticum aestivum L.) plant height at the QTL level and their influence on yield-related traits.

KEY MESSAGE: The temporal and spatial expression patterns of stable QTL for plant height and their influences on yield were characterized. Plant height (PH) is a complex trait in wheat (Triticum aestivum L.) that includes the spike length (SL) and the internode lengths from the first to the fifth internode, which are counted from the top and abbreviated as FIRITL, SECITL, THIITL, FOUITL, and FIFITL, respectively. This study identified eight putative additive quantitative trait loci (QTL) for PH. In addition, unconditional and conditional QTL mapping were used to analyze the temporal and spatial expression patterns of five stable QTL for PH. qPh-3A mainly regulated SL, FIRITL, and FIFITL to affect PH during the booting-heading stage (BS-HS); qPh-3D regulated all internode lengths to affect PH, especially during the BS-HS; before HS, qPh-4B mainly affected FIRITL, SECITL, THIITL, and FOUITL and qPh-5A.1 mainly affected SECITL, THIITL, and FOUITL to regulate PH; and qPh-6B mainly regulated FIRITL to affect the PH after the booting stage (BS). qPhdv-4B, a QTL for the response of PH to nitrogen stress, was stable and co-localized with qPh-4B. All five stable QTL, except for qPh-3A, were related to the 1000 kernel weight and yield per plant. Regions of qPh-3A, qPh-3D, qPh-4B, qPh-5A.1, and qPh-6B showed synteny to parts of rice chromosomes 1, 1, 3, 9, and 2, respectively. Based on comparative genomics analysis, Rht-B1b was cloned and mapped in the CI of qPh-4B. This report provides useful information for fine mapping of the stable QTL for PH and the genetic improvement of wheat plant type.

QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress.

KEY MESSAGE: QTLs for kernel characteristics and tolerance to N stress were identified, and the functions of ten known genes with regard to these traits were specified. Kernel size and quality characteristics in wheat (Triticum aestivum L.) ultimately determine the end use of the grain and affect its commodity price, both of which are influenced by the application of nitrogen (N) fertilizer. This study characterized quantitative trait loci (QTLs) for kernel size and quality and examined the responses of these traits to low-N stress using a recombinant inbred line population derived from Kenong 9204 × Jing 411. Phenotypic analyses were conducted in five trials that each included low- and high-N treatments. We identified 109 putative additive QTLs for 11 kernel size and quality characteristics and 49 QTLs for tolerance to N stress, 27 and 14 of which were stable across the tested environments, respectively. These QTLs were distributed across all wheat chromosomes except for chromosomes 3A, 4D, 6D, and 7B. Eleven QTL clusters that simultaneously affected kernel size- and quality-related traits were identified. At nine locations, 25 of the 49 QTLs for N deficiency tolerance coincided with the QTLs for kernel characteristics, indicating their genetic independence. The feasibility of indirect selection of a superior genotype for kernel size and quality under high-N conditions in breeding programs designed for a lower input management system are discussed. In addition, we specified the functions of Glu-A1, Glu-B1, Glu-A3, Glu-B3, TaCwi-A1, TaSus2, TaGS2-D1, PPO-D1, Rht-B1, and Ha with regard to kernel characteristics and the sensitivities of these characteristics to N stress. This study provides useful information for the genetic improvement of wheat kernel size, quality, and resistance to N stress.

Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations.

A novel high-density consensus wheat genetic map was obtained based on three related RIL populations, and the important chromosomal regions affecting yield and related traits were specified. A prerequisite for mapping quantitative trait locus (QTL) is to build a genetic linkage map. In this study, three recombinant inbred line populations (represented by WL, WY, and WJ) sharing one common parental line were used for map construction and subsequently for QTL detection of yield-related traits. PCR-based and diversity arrays technology markers were screened in the three populations. The integrated genetic map contains 1,127 marker loci, which span 2,976.75 cM for the whole genome, 985.93 cM for the A genome, 922.16 cM for the B genome, and 1,068.65 cM for the D genome. Phenotypic values were evaluated in four environments for populations WY and WJ, but three environments for population WL. Individual and combined phenotypic values across environments were used for QTL detection. A total of 165 putative additive QTL were identified, 22 of which showed significant additive-by-environment interaction effects. A total of 65 QTL (51.5%) were stable across environments, and 23 of these (35.4%) were common stable QTL that were identified in at least two populations. Notably, QTkw-5B.1, QTkw-6A.2, and QTkw-7B.1 were common major stable QTL in at least two populations, exhibiting 11.28-16.06, 5.64-18.69, and 6.76-21.16% of the phenotypic variance, respectively. Genetic relationships between kernel dimensions and kernel weight and between yield components and yield were evaluated. Moreover, QTL or regions that commonly interact across genetic backgrounds were discussed by comparing the results of the present study with those of previous similar studies. The present study provides useful information for marker-assisted selection in breeding wheat varieties with high yield.

A novel genetic map of wheat: utility for mapping QTL for yield under different nitrogen treatments.

BACKGROUND: Common wheat (Triticum aestivum L.) is one of the most important food crops worldwide. Wheat varieties that maintain yield (YD) under moderate or even intense nitrogen (N) deficiency can adapt to low input management systems. A detailed genetic map is necessary for both wheat molecular breeding and genomics research. In this study, an F6:7 recombinant inbred line population comprising 188 lines was used to construct a novel genetic map and subsequently to detect quantitative trait loci (QTL) for YD and response to N stress. RESULTS: A genetic map consisting of 591 loci distributed across 21 wheat chromosomes was constructed. The map spanned 3930.7 cM, with one marker per 6.7 cM on average. Genomic simple sequence repeat (g-SSR), expressed sequence tag-derived microsatellite (e-SSR), diversity arrays technology (DArT), sequence-tagged sites (STS), sequence-related amplified polymorphism (SRAP), and inter-simple sequence repeat (ISSR) molecular markers were included in the map. The linear relationships between loci found in the present map and in previously compiled physical maps were presented, which were generally in accordance. Information on the genetic and physical positions and allele sizes (when possible) of 17 DArT, 50 e-SSR, 44 SRAP, five ISSR, and two morphological markers is reported here for the first time. Seven segregation distortion regions (SDR) were identified on chromosomes 1B, 3BL, 4AL, 6AS, 6AL, 6BL, and 7B. A total of 22 and 12 QTLs for YD and yield difference between the value (YDDV) under HN and the value under LN were identified, respectively. Of these, QYd-4B-2 and QYddv-4B, two major stable QTL, shared support interval with alleles from KN9204 increasing YD in LN and decreasing YDDV. We probe into the use of these QTLs in wheat breeding programs. Moreover, factors affecting the SDR and total map length are discussed in depth. CONCLUSIONS: This novel map may facilitate the use of novel markers in wheat molecular breeding programs and genomics research. Moreover, QTLs for YD and YDDV provide useful markers for wheat molecular breeding programs designed to increase yield potential under N stress.

Epigenetic modifications regulate cultivar-specific root development and metabolic adaptation to nitrogen availability in wheat.

The breeding of crops with improved nitrogen use efficiency (NUE) is crucial for sustainable agriculture, but the involvement of epigenetic modifications remains unexplored. Here, we analyze the chromatin landscapes of two wheat cultivars (KN9204 and J411) that differ in NUE under varied nitrogen conditions. The expression of nitrogen metabolism genes is closely linked to variation in histone modification instead of differences in DNA sequence. Epigenetic modifications exhibit clear cultivar-specificity, which likely contributes to distinct agronomic traits. Additionally, low nitrogen (LN) induces H3K27ac and H3K27me3 to significantly enhance root growth in KN9204, while remarkably inducing NRT2 in J411. Evidence from histone deacetylase inhibitor treatment and transgenic plants with loss function of H3K27me3 methyltransferase shows that changes in epigenetic modifications could alter the strategy preference for root development or nitrogen uptake in response to LN. Here, we show the importance of epigenetic regulation in mediating cultivar-specific adaptation to LN in wheat.

Boosting wheat functional genomics via an indexed EMS mutant library of KN9204.

A better understanding of wheat functional genomics can improve targeted breeding for better agronomic traits and environmental adaptation. However, the lack of gene-indexed mutants and the low transformation efficiency of wheat limit in-depth gene functional studies and genetic manipulation for breeding. In this study, we created a library for KN9204, a popular wheat variety in northern China, with a reference genome, transcriptome, and epigenome of different tissues, using ethyl methyl sulfonate (EMS) mutagenesis. This library contains a vast developmental diversity of critical tissues and transition stages. Exome capture sequencing of 2090 mutant lines using KN9204 genome-designed probes revealed that 98.79% of coding genes had mutations, and each line had an average of 1383 EMS-type SNPs. We identified new allelic variations for crucial agronomic trait-related genes such as Rht-D1, Q, TaTB1, and WFZP. We tested 100 lines with severe mutations in 80 NAC transcription factors (TFs) under drought and salinity stress and identified 13 lines with altered sensitivity. Further analysis of three lines using transcriptome and chromatin accessibility data revealed hundreds of direct NAC targets with altered transcription patterns under salt or drought stress, including SNAC1, DREB2B, CML16, and ZFP182, factors known to respond to abiotic stress. Thus, we have generated and indexed a KN9204 EMS mutant library that can facilitate functional genomics research and offer resources for genetic manipulation of wheat.

Comparative genomic and transcriptomic analyses uncover the molecular basis of high nitrogen-use efficiency in the wheat cultivar Kenong 9204.

Studying the regulatory mechanisms that drive nitrogen-use efficiency (NUE) in crops is important for sustainable agriculture and environmental protection. In this study, we generated a high-quality genome assembly for the high-NUE wheat cultivar Kenong 9204 and systematically analyzed genes related to nitrogen uptake and metabolism. By comparative analyses, we found that the high-affinity nitrate transporter gene family had expanded in Triticeae. Further studies showed that subsequent functional differentiation endowed the expanded family members with saline inducibility, providing a genetic basis for improving the adaptability of wheat to nitrogen deficiency in various habitats. To explore the genetic and molecular mechanisms of high NUE, we compared genomic and transcriptomic data from the high-NUE cultivar Kenong 9204 (KN9204) and the low-NUE cultivar Jing 411 and quantified their nitrogen accumulation under high- and low-nitrogen conditions. Compared with Jing 411, KN9204 absorbed significantly more nitrogen at the reproductive stage after shooting and accumulated it in the shoots and seeds. Transcriptome data analysis revealed that nitrogen deficiency clearly suppressed the expression of genes related to cell division in the young spike of Jing 411, whereas this suppression of gene expression was much lower in KN9204. In addition, KN9204 maintained relatively high expression of NPF genes for a longer time than Jing 411 during seed maturity. Physiological and transcriptome data revealed that KN9204 was more tolerant of nitrogen deficiency than Jing 411, especially at the reproductive stage. The high NUE of KN9204 is an integrated effect controlled at different levels. Taken together, our data provide new insights into the molecular mechanisms of NUE and important gene resources for improving wheat cultivars with a higher NUE trait.

Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat.

Plant height (PH) in wheat is a complex trait; its components include spike length (SL) and internode lengths. To precisely analyze the factors affecting PH, two F(8:9) recombinant inbred line (RIL) populations comprising 485 and 229 lines were generated. Crosses were performed between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY). Possible genetic relationships between PH and PH components (PHC) were evaluated at the quantitative trait locus (QTL) level. PH and PHC (including SL and internode lengths from the first to the fourth counted from the top, abbreviated as FIITL, SITL, TITL, and FOITL, respectively) were measured in four environments. Individual and the pooled values from four trials were used in the present analysis. A QTL for PH was mapped using data on PH and on PH conditioned by PHC using IciMapping V2.2. All 21 chromosomes in wheat were shown to harbor factors affecting PH in two populations, by both conditional and unconditional QTL mapping methods. At least 11 pairwise congruent QTL were identified in the two populations. In total, ten unconditional QTL and five conditional QTL that could be detected in the conditional analysis only have been verified in no less than three trials in WJ and WY. In addition, three QTL on the short arms of chromosomes 4B, 4D, and 7B were mapped to positions similar to those of the semi-dwarfing genes Rht-B1, Rht-D1 and Rht13, respectively. Conditional QTL mapping analysis in WJ and WY proved that, at the QTL level, SL contributed the least to PH, followed by FIITL; TITL had the strongest influence on PH, followed by SITL and FOITL. The results above indicated that the conditional QTL mapping method can be used to evaluate possible genetic relationships between PH and PHC, and it can efficiently and precisely reveal counteracting QTL, which will enhance the understanding of the genetic basis of PH in wheat. The combination of two related populations with a large/moderate population size made the results authentic and accurate.

The brassinosteroid biosynthesis gene, ZmD11, increases seed size and quality in rice and maize.

Brassinosteroids (BRs) are a group of plant steroid hormones that regulate many important agronomic traits. Studies on the functional mechanisms of BR-related genes in crop plants are necessary for the application of BRs in agriculture. In this study, ZmD11, an ortholog of rice DWARF11 (D11), and 42 other BR biosynthesis-related genes were identified in maize (Zea mays). Complementary experiments confirmed that ZmD11 completely rescued the abnormal panicle architecture and plant height of the rice cpb1 mutant. A phylogenetic analysis indicated that ZmD11-like proteins were found in other monocots and dicots, but not in lower plants and that alternative splicing variants of these homologues mainly exist in Triticeae crops. A subcellular localization analysis showed that ZmD11 localized to the endoplasmic reticulum. The ZmD11 gene was predominantly expressed in young ears and seeds from 10 to 16 days after pollination, especially in the scutellar aleurone layer and pericarp. Furthermore, the constitutive expression of the ZmD11 gene significantly increased seed length, seed area, seed weight and both seed starch and protein contents in rice and maize. Our results suggest that ZmD11 is a key gene in the regulation of seed size and quality and that it has a potential application value in the molecular breeding of crops.