High-Resolution Genome-wide Association Study Identifies Genomic Regions and Candidate Genes for Important Agronomic Traits in Wheat

Genotype selection identified elite lines through quantitative trait loci mapping of agronomically important traits in wheat

Wheat is one of the most important staple foods in the world. Genetic characterization of wheat agronomically important traits is crucial for yield improvement through molecular breeding. In this study, a recombinant inbred line (RIL) population was developed by crossing a local adapted high yield variety Jimai 22 (JM22) with an external variety Cunmai no.1 (CM1). A high-density genetic map containing 7,359 single nucleotide polymorphism (SNP) markers was constructed. Quantitative trait loci (QTL) mapping identified 61 QTL for eight yield-related traits under six environments (years). Among them, 17 QTL affecting spike number per plant, grain number per spike and thousand grain weight showed high predictability for theoretical yield per plant (TYP), of which, 12 QTL alleles positively contributed to TYP. Nine promising candidate genes for seven of the 12 QTL were identified including three known wheat genes and six rice orthologs. Four elite lines with TYP increased by 5.6%-15.2% were identified through genotype selection which carried 7-9 favorable alleles from JM22 and 2-3 favorable alleles from CM1 of the 12 QTL. Moreover, the linked SNPs of the 12 QTL were converted to high-throughput kompetitive allele-specific PCR (KASP) markers and validated in the population. The mapped QTL, identified promising candidate genes, developed elite lines and KASP markers are highly valuable in future genotype selection to improve wheat yield.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01496-3.

Genomic insights into the modifications of spike morphology traits during wheat breeding

Over the past century, environmental changes have significantly impacted wheat spike morphology, crucial for adaptation and grain yield. However, the changes in wheat spike modifications during this period remain largely unknown. This study examines 16 spike morphology traits in 830 accessions released from 1900 to 2020. It finds that spike weight, grain number per spike (GN), and thousand kernel weight have significantly increased, while spike length has no significant change. The increase in fertile spikelets is due to fewer degenerated spikelets, resulting in a higher GN. Genome-wide association studies identified 49,994 significant SNPs, grouped into 293 genomic regions. The accumulation of favorable alleles in these genomic regions indicates the genetic basis for modification in spike morphology traits. Genetic network analysis of these genomic regions reveals the genetic basis for phenotypic correlations among spike morphology traits. The haplotypes of the identified genomic regions display obvious geographical differentiation in global accessions and environmental adaptation over the past 120 years. In summary, we reveal the genetic basis of adaptive evolution and the interactions of spike morphology, offering valuable resources for the genetic improvement of spike morphology to enhance environmental adaptation.

GWAS elucidated grain yield genetics in Indian spring wheat under diverse water conditions

KEY MESSAGE

Underpinned natural variations and key genes associated with yield under different water regimes, and identified genomic signatures of genetic gain in the Indian wheat breeding program. A novel KASP marker for TKW under water stress was developed and validated. A comprehensive genome-wide association study was conducted on 300 spring wheat genotypes to elucidate the natural variations associated with grain yield and its eleven contributing traits under fully irrigated, restricted water, and simulated no water conditions. Utilizing the 35K Wheat Breeders' Array, we identified 1155 quantitative trait nucleotides (QTNs), with 207 QTNs exhibiting stability across diverse conditions. These QTNs were further delimited into 539 genomic regions using a genome-wide LD value of 3.0 Mbp, revealing pleiotropic control across traits and conditions. Sub-genome A was significantly associated with traits under irrigated conditions, while sub-genome B showed more QTNs under water stressed conditions. Favourable alleles with significantly associated QTNs were delineated, with a notable pyramiding effect for enhancing trait performance. Additionally, allele of only 921 QTNs significantly affected the population mean. Allele profiling highlighted C-306 as a most potential source of drought tolerance. Moreover, 762 genes overlapping significant QTNs were identified, narrowing down to 27 putative candidate genes overlapping 29 novel and functional SNPs expressing (≥ 0.5 tpm) relevance across various growth conditions. A new KASP assay was developed, targeting a gene TraesCS2A03G1123700 regulating thousand kernel weight under severe drought condition. Genomic selection models (GBLUP, BayesB, MxE, and R-Norm) demonstrated an average prediction accuracy of 0.06-0.58 across environments, indicating potential for trait selection. Retrospective analysis of the Indian wheat breeding program supported a genetic gain in GY at the rate of ca. 0.56% per breeding cycle, since 1960, supporting the identification of genomic signatures driving trait selection and genetic gain. These findings offer insight into improving the rate of genetic gain in wheat breeding programs globally.

Integrative gene duplication and genome-wide analysis as an approach to facilitate wheat reverse genetics: An example in the TaCIPK family

INTRODUCTION

Reverse genetic studies conducted in the plant with a complex or polyploidy genome enriched with large gene families (like wheat) often meet challenges in identifying the key candidate genes related to important traits and prioritizing the genes for functional experiments.

OBJECTIVE

To overcome the above-mentioned challenges of reverse genetics, this work aims to establish an efficient multi-species strategy for genome-wide gene identification and prioritization of the key candidate genes.

METHODS

We established the integrative gene duplication and genome-wide analysis (iGG analysis) as a strategy for pinpointing key candidate genes deserving functional research. The iGG captures the evolution, and the expansion/contraction of large gene families across phylogeny-related species and integrates spatial-temporal expression information for gene function inference. Transgenic approaches were also employed to functional validation.

RESULTS

As a proof-of-concept for the iGG analysis, we took the wheat calcineurin B-like protein-interacting protein kinases (CIPKs) family as an example. We identified CIPKs from seven monocot species, established the orthologous relationship of CIPKs between rice and wheat, and characterized Triticeae-specific CIPK duplicates (e.g., CIPK4 and CIPK17). Integrated with our analysis of CBLs and CBL-CIPK interaction, we revealed that divergent expressions of TaCBLs and TaCIPKs could play an important role in keeping the stoichiometric balance of CBL-CIPK. Furthermore, we validated the function of TaCIPK17-A2 in the regulation of drought tolerance by using transgenic approaches. Overexpression of TaCIPK17 enhanced antioxidant capacity and improved drought tolerance in wheat.

CONCLUSION

The iGG analysis leverages evolutionary and comparative genomics of crops with large genomes to rapidly highlight the duplicated genes potentially associated with speciation, domestication and/or particular traits that deserve reverse-genetic functional studies. Through the identification of Triticeae-specific TaCIPK17 duplicates and functional validation, we demonstrated the effectiveness of the iGG analysis and provided a new target gene for improving drought tolerance in wheat.

Deciphering the Transcriptional Regulatory Network Governing Starch and Storage Protein Biosynthesis in Wheat for Breeding Improvement

Starch and seed storage protein (SSP) composition profoundly impact wheat grain yield and quality. To unveil regulatory mechanisms governing their biosynthesis, transcriptome, and epigenome profiling is conducted across key endosperm developmental stages, revealing that chromatin accessibility, H3K27ac, and H3K27me3 collectively regulate SSP and starch genes with varying impact. Population transcriptome and phenotype analyses highlight accessible promoter regions' crucial role as a genetic variation resource, influencing grain yield and quality in a core collection of wheat accessions. Integration of time-serial RNA-seq and ATAC-seq enables the construction of a hierarchical transcriptional regulatory network governing starch and SSP biosynthesis, identifying 42 high-confidence novel candidates. These candidates exhibit overlap with genetic regions associated with grain size and quality traits, and their functional significance is validated through expression-phenotype association analysis among wheat accessions and loss-of-function mutants. Functional analysis of wheat abscisic acid insensitive 3-A1 (TaABI3-A1) with genome editing knock-out lines demonstrates its role in promoting SSP accumulation while repressing starch biosynthesis through transcriptional regulation. Excellent TaABI3-A1Hap1 with enhanced grain weight is selected during the breeding process in China, linked to altered expression levels. This study unveils key regulators, advancing understanding of SSP and starch biosynthesis regulation and contributing to breeding enhancement.

Genome-wide association study and candidate gene identification for agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum

Pepper agronomic traits serve as pivotal indicators for characterizing germplasm attributes and correlations. It is important to study differential genotypic variation through phenotypic differences of target traits. Whole genome resequencing was used to sequence the whole genome among different individuals of species with known reference genomes and annotations, and based on this, differential analyses of individuals or populations were carried out to identify SNPs for agronomic traits related to pepper. This study conducted a genome-wide association study encompassing 26 key agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum. The population structure (phylogenetics, population structure, population principal component analysis, genetic relationship) and linkage disequilibrium analysis were realized to ensure the accuracy and reliability of GWAS results, and the optimal statistical model was determined. A total of 929 SNPs significantly associated with 26 agronomic traits, were identified, alongside the detection of 519 candidate genes within 100 kb region adjacent to these SNPs. Additionally, through gene annotation and expression pattern scrutiny, genes such as GAUT1, COP10, and DDB1 correlated with fruit traits in Capsicum frutescens and Capsicum annuum were validated via qRT-PCR. In the CH20 (Capsicum annuum) and YB-4 (Capsicum frutescens) cultivars, GAUT1 and COP10 were cloned with cDNA lengths of 1065 bp and 561 bp, respectively, exhibiting only a small number of single nucleotide variations and nucleotide deletions. This validation provides a robust reference for molecular marker-assisted breeding of pepper agronomic traits, offering both genetic resources and theoretical foundations for future endeavors in molecular marker-assisted breeding for pepper.

Analysis of population structure and genetic diversity of Camellia tachangensis in Guizhou based on SNP markers

BACKGROUND

Camellia tachangensis F. C. Zhang is a five-compartment species in the ovary of tea group plants, which represents the original germline of early differentiation of some tea group plants.

METHODS AND RESULTS

In this study, we analyzed single-nucleotide polymorphisms (SNPs) at the genome level, constructed a phylogenetic tree, analyzed the genetic diversity, and further investigated the population structure of 100 C. tachangensis accessions using the genotyping-by-sequencing (GBS) method. A total of 91,959 high-quality SNPs were obtained. Population structure analysis showed that the 100 C. tachangensis accessions clustered into three groups: YQ-1 (Village Group), YQ-2 (Forest Group) and YQ-3 (Transition Group), which was further consistent with the results of phylogenetic analysis and principal component analyses (PCA). In addition, a comparative analysis of the genetic diversity among the three populations (Forest, Village, and Transition Groups) detected the highest genetic diversity in the Transition Group and the highest differentiation between Forest and Village Groups.

CONCLUSIONS

C. tachangensis plants growing in the forest had different genetic backgrounds from those growing in villages. This study provides a basis for the effective protection and utilization of C. tachangensis populations and lays a foundation for future C. tachangensis breeding.

Genome-wide association study for seedling heat tolerance under two temperature conditions in bread wheat (Triticum aestivum L.)

BACKGROUND

As the greenhouse effect intensifies, global temperatures are steadily increasing, posing a challenge to bread wheat (Triticum aestivum L.) production. It is imperative to comprehend the mechanism of high temperature tolerance in wheat and implement breeding programs to identify and develop heat-tolerant wheat germplasm and cultivars.

RESULTS

To identify quantitative trait loci (QTL) related to heat stress tolerance (HST) at seedling stage in wheat, a panel of 253 wheat accessions which were re-sequenced used to conduct genome-wide association studies (GWAS) using the factored spectrally transformed linear mixed models (FaST-LMM). For most accessions, the growth of seedlings was found to be inhibited under heat stress. Analysis of the phenotypic data revealed that under heat stress conditions, the main root length, total root length, and shoot length of seedlings decreased by 47.46%, 49.29%, and 15.19%, respectively, compared to those in normal conditions. However, 17 varieties were identified as heat stress tolerant germplasm. Through GWAS analysis, a total of 115 QTLs were detected under both heat stress and normal conditions. Furthermore, 15 stable QTL-clusters associated with heat response were identified. By combining gene expression, haplotype analysis, and gene annotation information within the physical intervals of the 15 QTL-clusters, two novel candidate genes, TraesCS4B03G0152700/TaWRKY74-B and TraesCS4B03G0501400/TaSnRK3.15-B, were responsive to temperature and identified as potential regulators of HST in wheat at the seedling stage.

CONCLUSIONS

This study conducted a detailed genetic analysis and successfully identified two genes potentially associated with HST in wheat at the seedling stage, laying a foundation to further dissect the regulatory mechanism underlying HST in wheat under high temperature conditions. Our finding could serve as genomic landmarks for wheat breeding aimed at improving adaptation to heat stress in the face of climate change.

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.

Dissecting the molecular basis of spike traits by integrating gene regulatory networks and genetic variation in wheat

Spike architecture influences both grain weight and grain number per spike, which are the two major components of grain yield in bread wheat (Triticum aestivum L.). However, the complex wheat genome and the influence of various environmental factors pose challenges in mapping the causal genes that affect spike traits. Here, we systematically identified genes involved in spike trait formation by integrating information on genomic variation and gene regulatory networks controlling young spike development in wheat. We identified 170 loci that are responsible for variations in spike length, spikelet number per spike, and grain number per spike through genome-wide association study and meta-QTL analyses. We constructed gene regulatory networks for young inflorescences at the double ridge stage and the floret primordium stage, in which the spikelet meristem and the floret meristem are predominant, respectively, by integrating transcriptome, histone modification, chromatin accessibility, eQTL, and protein-protein interactome data. From these networks, we identified 169 hub genes located in 76 of the 170 QTL regions whose polymorphisms are significantly associated with variation in spike traits. The functions of TaZF-B1, VRT-B2, and TaSPL15-A/D in establishment of wheat spike architecture were verified. This study provides valuable molecular resources for understanding spike traits and demonstrates that combining genetic analysis and developmental regulatory networks is a robust approach for dissection of complex traits.

TaCRTISO dosage modulates plant height and spike number per plant in wheat

An allelic variation of TaCRTISO is valuable in adjusting spike number per plant and plant height in wheat breeding.

Genome-Wide Association Study to Identify Marker-Trait Associations for Seed Color in Colored Wheat (Triticum aestivum L.)

This study conducted phenotypic evaluations on a wheat F3 population derived from 155 F2 plants. Traits related to seed color, including chlorophyll a, chlorophyll b, carotenoid, anthocyanin, L*, a*, and b*, were assessed, revealing highly significant correlations among various traits. Genotyping using 81,587 SNP markers resulted in 3969 high-quality markers, revealing a genome-wide distribution with varying densities across chromosomes. A genome-wide association study using fixed and random model circulating probability unification (FarmCPU) and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) identified 11 significant marker-trait associations (MTAs) associated with L*, a*, and b*, and chromosomal distribution patterns revealed predominant locations on chromosomes 2A, 2B, and 4B. A comprehensive annotation uncovered 69 genes within the genomic vicinity of each MTA, providing potential functional insights. Gene expression analysis during seed development identified greater than 2-fold increases or decreases in expression in colored wheat for 16 of 69 genes. Among these, eight genes, including transcription factors and genes related to flavonoid and ubiquitination pathways, exhibited distinct expression patterns during seed development, providing further approaches for exploring seed coloration. This comprehensive exploration expands our understanding of the genetic basis of seed color and paves the way for informed discussions on the molecular intricacies contributing to this phenotypic trait.

Integrated VIS/NIR Spectrum and Genome-Wide Association Study for Genetic Dissection of Cellulose Crystallinity in Wheat Stems

Cellulose crystallinity is a crucial factor influencing stem strength and, consequently, wheat lodging. However, the genetic dissection of cellulose crystallinity is less reported due to the difficulty of its measurement. In this study, VIS/NIR spectra and cellulose crystallinity were measured for a wheat accession panel with diverse genetic backgrounds. We developed a reliable VIS/NIR model for cellulose crystallinity with a high determination coefficient (R2) (0.95) and residual prediction deviation (RPD) (4.04), enabling the rapid screening of wheat samples. A GWAS of the cellulose crystallinity in 326 wheat accessions revealed 14 significant SNPs and 13 QTLs. Two candidate genes, TraesCS4B03G0029800 and TraesCS5B03G1085500, were identified. In summary, this study establishes an efficient method for the measurement of cellulose crystallinity in wheat stems and provides a genetic basis for enhancing lodging resistance in wheat.

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.

Systematic identification of wheat spike developmental regulators by integrated multi-omics, transcriptional network, GWAS, and genetic analyses

The spike architecture of wheat plays a crucial role in determining grain number, making it a key trait for optimization in wheat breeding programs. In this study, we used a multi-omic approach to analyze the transcriptome and epigenome profiles of the young spike at eight developmental stages, revealing coordinated changes in chromatin accessibility and H3K27me3 abundance during the flowering transition. We constructed a core transcriptional regulatory network (TRN) that drives wheat spike formation and experimentally validated a multi-layer regulatory module involving TaSPL15, TaAGLG1, and TaFUL2. By integrating the TRN with genome-wide association studies, we identified 227 transcription factors, including 42 with known functions and 185 with unknown functions. Further investigation of 61 novel transcription factors using multiple homozygous mutant lines revealed 36 transcription factors that regulate spike architecture or flowering time, such as TaMYC2-A1, TaMYB30-A1, and TaWRKY37-A1. Of particular interest, TaMYB30-A1, downstream of and repressed by WFZP, was found to regulate fertile spikelet number. Notably, the excellent haplotype of TaMYB30-A1, which contains a C allele at the WFZP binding site, was enriched during wheat breeding improvement in China, leading to improved agronomic traits. Finally, we constructed a free and open access Wheat Spike Multi-Omic Database (http://39.98.48.156:8800/#/). Our study identifies novel and high-confidence regulators and offers an effective strategy for dissecting the genetic basis of wheat spike development, with practical value for wheat breeding.

Genome and GWAS analysis identified genes significantly related to phenotypic state of Rhododendron bark

As an important horticultural plant, Rhododendron is often used in urban greening and landscape design. However, factors such as the high rate of genetic recombination, frequent outcrossing in the wild, weak linkage disequilibrium, and the susceptibility of gene expression to environmental factors limit further exploration of functional genes related to important horticultural traits, and make the breeding of new varieties require a longer time. Therefore, we choose bark as the target trait which is not easily affected by environmental factors, but also has ornamental properties. Genome-wide association study (GWAS) of Rhododendron delavayi (30 samples), R. irroratum (30 samples) and their F1 generation R. agastum (200 samples) was conducted on the roughness of bark phenotypes. Finally, we obtained 2416.31 Gbp of clean data and identified 5 328 800 high-quality SNPs. According to the P-value and the degree of linkage disequilibrium of SNPs, we further identified 4 out of 11 candidate genes that affect bark roughness. The results of gene differential expression analysis further indicated that the expression levels of Rhdel02G0243600 and Rhdel08G0220700 in different bark phenotypes were significantly different. Our study identified functional genes that influence important horticultural traits of Rhododendron, and illustrated the powerful utility and great potential of GWAS in understanding and exploiting wild germplasm genetic resources of Rhododendron.

Innovative computational tools provide new insights into the polyploid wheat genome

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

Identification of Single Nucleotide Polymorphic Loci and Candidate Genes for Seed Germination Percentage in Okra under Salt and No-Salt Stresses by Genome-Wide Association Study

Excessive soil salinity is a major stressor inhibiting crops' growth, development, and yield. Seed germination is a critical stage of crop growth and development, as well as one of the most salt-sensitive stages. Salt stress has a significant inhibitory effect on seed germination. Okra is a nutritious vegetable, but its seed germination percentage (GP) is low, whether under salt stress conditions or suitable conditions. In this study, we used 180 okra accessions and conducted a genome-wide association study (GWAS) on the germination percentage using 20,133,859 single nucleotide polymorphic (SNP) markers under 0 (CK, diluted water), 70 (treatment 1, T1), and 140 mmol/L (treatment 2, T2) NaCl conditions. Using the mixed linear model (MLM) in Efficient Mixed-model Association eXpedated (EMMAX) and Genome-wide Efficient Mixed Model Association (GEMMA) software, 511 SNP loci were significantly associated during germination, of which 167 SNP loci were detected simultaneously by both programs. Among the 167 SNPs, SNP2619493 on chromosome 59 and SNP2692266 on chromosome 44 were detected simultaneously under the CK, T1, and T2 conditions, and were key SNP loci regulating the GP of okra seeds. Linkage disequilibrium block analysis revealed that nsSNP2626294 (C/T) in Ae59G004900 was near SNP2619493, and the amino acid changes caused by nsSNP2626294 led to an increase in the phenotypic values in some okra accessions. There was an nsSNP2688406 (A/G) in Ae44G005470 near SNP2692266, and the amino acid change caused by nsSNP2688406 led to a decrease in phenotypic values in some okra accessions. These results indicate that Ae59G004900 and Ae44G005470 regulate the GP of okra seeds under salt and no-salt stresses. The gene expression analysis further demonstrated these results. The SNP markers and genes that were identified in this study will provide reference for further research on the GP of okra, as well as new genetic markers and candidate genes for cultivating new okra varieties with high GPs under salt and no-salt stress conditions.

Efficient identification of QTL for agronomic traits in foxtail millet (Setaria italica) using RTM- and MLM-GWAS

KEY MESSAGE

Eleven QTLs for agronomic traits were identified by RTM- and MLM-GWAS, putative candidate genes were predicted and two markers for grain weight were developed and validated. Foxtail millet (Setaria italica), the second most cultivated millet crop after pearl millet, is an important grain crop in arid regions. Seven agronomic traits of 408 diverse foxtail millet accessions from 15 provinces in China were evaluated in three environments. They were clustered into two divergent groups based on genotypic data using ADMIXTURE, which was highly consistent with their geographical distribution. Two models for genome-wide association studies (GWAS), namely restricted two-stage multi-locus multi-allele (RTM)-GWAS and mixed linear model (MLM)-GWAS, were used to dissect the genetic architecture of the agronomic traits based on 13,723 SNPs. Eleven quantitative trait loci (QTLs) for seven traits were identified using two models (RTM- and MLM-GWAS). Among them, five were considered stable QTLs that were identified in at least two environments using MLM-GWAS. One putative candidate gene (SETIT_006045mg, Chr4: 744,701-746,852) that can enhance grain weight per panicle was identified based on homologous gene comparison and gene expression analysis and was validated by haplotype analysis of 330 accessions with high-depth (10×) resequencing data (unpublished). In addition, homologous gene comparison and haplotype analysis identified one putative foxtail millet ortholog (SETIT_032906mg, Chr2: 5,020,600-5,029,771) with rice affecting the target traits. Two markers (cGWP6045 and kTGW2906) were developed and validated and can be used for marker-assisted selection of foxtail millet with high grain weight. The results provide a fundamental resource for foxtail millet genetic research and breeding and demonstrate the power of integrating RTM- and MLM-GWAS approaches as a complementary strategy for investigating complex traits in foxtail millet.

Heat and Wheat: Adaptation strategies with respect to heat shock proteins and antioxidant potential; an era of climate change

Extreme changes in weather including heat-wave and high-temperature fluctuations are predicted to increase in intensity and duration due to climate change. Wheat being a major staple crop is under severe threat of heat stress especially during the grain-filling stage. Widespread food insecurity underscores the critical need to comprehend crop responses to forthcoming climatic shifts, pivotal for devising adaptive strategies ensuring sustainable crop productivity. This review addresses insights concerning antioxidant, physiological, molecular impacts, tolerance mechanisms, and nanotechnology-based strategies and how wheat copes with heat stress at the reproductive stage. In this study stress resilience strategies were documented for sustainable grain production under heat stress at reproductive stage. Additionally, the mechanisms of heat resilience including gene expression, nanomaterials that trigger transcription factors, (HSPs) during stress, and physiological and antioxidant traits were explored. The most reliable method to improve plant resilience to heat stress must include nano-biotechnology-based strategies, such as the adoption of nano-fertilizers in climate-smart practices and the use of advanced molecular approaches. Notably, the novel resistance genes through advanced molecular approach and nanomaterials exhibit promise for incorporation into wheat cultivars, conferring resilience against imminent adverse environmental conditions. This review will help scientific communities in thermo-tolerance wheat cultivars and new emerging strategies to mitigate the deleterious impact of heat stress.

Genome resources for the elite bread wheat cultivar Aikang 58 and mining of elite homeologous haplotypes for accelerating wheat improvement

Despite recent progress in crop genomics studies, the genomic changes brought about by modern breeding selection are still poorly understood, thus hampering genomics-assisted breeding, especially in polyploid crops with compound genomes such as common wheat (Triticum aestivum). In this work, we constructed genome resources for the modern elite common wheat variety Aikang 58 (AK58). Comparative genomics between AK58 and the landrace cultivar Chinese Spring (CS) shed light on genomic changes that occurred through recent varietal improvement. We also explored subgenome diploidization and divergence in common wheat and developed a homoeologous locus-based genome-wide association study (HGWAS) approach, which was more effective than single homoeolog-based GWAS in unraveling agronomic trait-associated loci. A total of 123 major HGWAS loci were detected using a genetic population derived from AK58 and CS. Elite homoeologous haplotypes (HHs), formed by combinations of subgenomic homoeologs of the associated loci, were found in both parents and progeny, and many could substantially improve wheat yield and related traits. We built a website where users can download genome assembly sequence and annotation data for AK58, perform blast analysis, and run JBrowse. Our work enriches genome resources for wheat, provides new insights into genomic changes during modern wheat improvement, and suggests that efficient mining of elite HHs can make a substantial contribution to genomics-assisted breeding in common wheat and other polyploid crops.

Integration of genome-wide association study, linkage analysis, and population transcriptome analysis to reveal the TaFMO1-5B modulating seminal root growth in bread wheat

Bread wheat, one of the keystone crops for global food security, is challenged by climate change and resource shortage. The root system plays a vital role in water and nutrient absorption, making it essential for meeting the growing global demand. Here, using an association-mapping population composed of 406 accessions, we identified QTrl.Rs-5B modulating seminal root development with a genome-wide association study and validated its genetic effects with two F5 segregation populations. Transcriptome-wide association study prioritized TaFMO1-5B, a gene encoding the flavin-containing monooxygenases, as the causal gene for QTrl.Rs-5B, whose expression levels correlate negatively with the phenotyping variations among our population. The lines silenced for TaFMO1-5B consistently showed significantly larger seminal roots in different genetic backgrounds. Additionally, the agriculture traits measured in multiple environments showed that QTrl.Rs-5B also affects yield component traits and plant architecture-related traits, and its favorable haplotype modulates these traits toward that of modern cultivars, suggesting the application potential of QTrl.Rs-5B for wheat breeding. Consistently, the frequency of the favorable haplotype of QTrl.Rs-5B increased with habitat expansion and breeding improvement of bread wheat. In conclusion, our findings identified and demonstrated the effects of QTrl.Rs-5B on seminal root development and illustrated that it is a valuable genetic locus for wheat root improvement.

Whole-genome sequencing of diverse wheat accessions uncovers genetic changes during modern breeding in China and the United States

Breeding has dramatically changed the plant architecture of wheat (Triticum aestivum), resulting in the development of high-yielding varieties adapted to modern farming systems. However, how wheat breeding shaped the genomic architecture of this crop remains poorly understood. Here, we performed a comprehensive comparative analysis of a whole-genome resequencing panel of 355 common wheat accessions (representing diverse landraces and modern cultivars from China and the United States) at the phenotypic and genomic levels. The genetic diversity of modern wheat cultivars was clearly reduced compared to landraces. Consistent with these genetic changes, most phenotypes of cultivars from China and the United States were significantly altered. Of the 21 agronomic traits investigated, 8 showed convergent changes between the 2 countries. Moreover, of the 207 loci associated with these 21 traits, more than half overlapped with genomic regions that showed evidence of selection. The distribution of selected loci between the Chinese and American cultivars suggests that breeding for increased productivity in these 2 regions was accomplished by pyramiding both shared and region-specific variants. This work provides a framework to understand the genetic architecture of the adaptation of wheat to diverse agricultural production environments, as well as guidelines for optimizing breeding strategies to design better wheat varieties.

Transposable element-initiated enhancer-like elements generate the subgenome-biased spike specificity of polyploid wheat

Transposable elements (TEs) comprise ~85% of the common wheat genome, which are highly diverse among subgenomes, possibly contribute to polyploid plasticity, but the causality is only assumed. Here, by integrating data from gene expression cap analysis and epigenome profiling via hidden Markov model in common wheat, we detect a large proportion of enhancer-like elements (ELEs) derived from TEs producing nascent noncoding transcripts, namely ELE-RNAs, which are well indicative of the regulatory activity of ELEs. Quantifying ELE-RNA transcriptome across typical developmental stages reveals that TE-initiated ELE-RNAs are mainly from RLG_famc7.3 specifically expanded in subgenome A. Acquisition of spike-specific transcription factor binding likely confers spike-specific expression of RLG_famc7.3-initiated ELE-RNAs. Knockdown of RLG_famc7.3-initiated ELE-RNAs resulted in global downregulation of spike-specific genes and abnormal spike development. These findings link TE expansion to regulatory specificity and polyploid developmental plasticity, highlighting the functional impact of TE-driven regulatory innovation on polyploid evolution.

Genome wide association in Spanish bread wheat landraces identifies six key genomic regions that constitute potential targets for improving grain yield related traits

KEY MESSAGE

Association mapping conducted in 189 Spanish bread wheat landraces revealed six key genomic regions that constitute stable QTLs for yield and include 15 candidate genes. Genetically diverse landraces provide an ideal population to conduct association analysis. In this study, association mapping was conducted in a collection of 189 Spanish bread wheat landraces whose genomic diversity had been previously assessed. These genomic data were combined with characterization for yield-related traits, including grain size and shape, and phenological traits screened across five seasons. The association analysis revealed a total of 881 significant marker trait associations, involving 434 markers across the genome, that could be grouped in 366 QTLs based on linkage disequilibrium. After accounting for days to heading, we defined 33 high density QTL genomic regions associated to at least four traits. Considering the importance of detecting stable QTLs, 6 regions associated to several grain traits and thousand kernel weight in at least three environments were selected as the most promising ones to harbour targets for breeding. To dissect the genetic cause of the observed associations, we studied the function and in silico expression of the 413 genes located inside these six regions. This identified 15 candidate genes that provide a starting point for future analysis aimed at the identification and validation of wheat yield related genes.

Main Habitat Factors Driving the Phenotypic Diversity of Litsea cubeba in China

Litsea cubeba (Lour.) Pers. is an important woody spice tree in southern China, and its fruit is a rich source of valuable essential oil. We surveyed and sampled L. cubeba germplasm resources from 36 provenances in nine Chinese provinces, and detected rich phenotypic diversity. The survey results showed that plants of SC-KJ, SC-HJ, and SC-LS provenance presented higher leaf area (LA); YN-SM and YN-XC plants had larger thousand-grain fresh weight (TFW); and HN-DX plants had the highest essential oil content (EOC). To explain the large differences in the phenotypes of L. cubeba among different habitats, we used Pearson's correlation analysis, multiple stepwise regression path analysis, and redundancy analysis to evaluate the phenotypic diversity of L. cubeba. It was found that compared to other traits, leaf and fruit traits had more significant geographical distributions, and that leaf phenotypes were correlated to fruit phenotypes. The results showed that elevation, latitude, longitude, total soil porosity (SP), soil bulk density (SBD), and average annual rainfall (AAR, mm) contributed significantly to the phenotypic diversity of L. cubeba. Geographical factors explained a higher percentage of variation in phenotypic diversity than did soil factors and climate factors. Plants of SC-KJ and HN-DX provenances could be important resources for domestication and breeding to develop new high-yielding varieties of this woody aromatic plant. This study describes significant phenotypic differences in L. cubeba related to adaptation to different environments, and provides a theoretical basis for the development of a breeding strategy and for optimizing L. cubeba cultivation.

Mining novel genomic regions and candidate genes of heading and flowering dates in bread wheat by SNP- and haplotype-based GWAS

Bread wheat (Triticum aestivum L.) is a global staple crop vital for human nutrition. Heading date (HD) and flowering date (FD) are critical traits influencing wheat growth, development, and adaptability to diverse environmental conditions. A comprehensive study were conducted involving 190 bread wheat accessions to unravel the genetic basis of HD and FD using high-throughput genotyping and multi-environment field trials. Seven independent quantitative trait loci (QTLs) were identified to be significantly associated with HD and FD using two GWAS methods, which explained a proportion of phenotypic variance ranging from 1.43% to 9.58%. Notably, QTLs overlapping with known vernalization genes Vrn-D1 were found, validating their roles in regulating flowering time. Moreover, novel QTLs on chromosome 2A, 5B, 5D, and 7B associated with HD and FD were identified. The effects of these QTLs on HD and FD were confirmed in an additional set of 74 accessions across different environments. An increase in the frequency of alleles associated with early flowering in cultivars released in recent years was also observed, suggesting the influence of molecular breeding strategies. In summary, this study enhances the understanding of the genetic regulation of HD and FD in bread wheat, offering valuable insights into crop improvement for enhanced adaptability and productivity under changing climatic conditions. These identified QTLs and associated markers have the potential to improve wheat breeding programs in developing climate-resilient varieties to ensure food security.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01422-z.

Genetic analysis of iron, zinc and grain yield in wheat-Aegilops derivatives using multi-locus GWAS

BACKGROUND

Wheat is a major staple crop and helps to reduce worldwide micronutrient deficiency. Investigating the genetics that control the concentrations of iron (Fe) and zinc (Zn) in wheat is crucial. Hence, we undertook a comprehensive study aimed at elucidating the genomic regions linked to the contents of Fe and Zn in the grain.

METHODS AND RESULTS

We performed the multi-locus genome-wide association (ML-GWAS) using a panel of 161 wheat-Aegilops substitution and addition lines to dissect the genomic regions controlling grain iron (GFeC), and grain zinc (GZnC) contents. The wheat panel was genotyped using 10,825 high-quality SNPs and phenotyped in three different environments (E1-E3) during 2017-2019. A total of 111 marker-trait associations (MTAs) (at p-value < 0.001) were detected that belong to all three sub-genomes of wheat. The highest number of MTAs were identified for GFeC (58), followed by GZnC (44) and yield (9). Further, six stable MTAs were identified for these three traits and also two pleiotropic MTAs were identified for GFeC and GZnC. A total of 1291 putative candidate genes (CGs) were also identified for all three traits. These CGs encode a diverse set of proteins, including heavy metal-associated (HMA), bZIP family protein, AP2/ERF, and protein previously associated with GFeC, GZnC, and grain yield.

CONCLUSIONS

The significant MTAs and CGs pinpointed in this current study are poised to play a pivotal role in enhancing both the nutritional quality and yield of wheat, utilizing marker-assisted selection (MAS) techniques.

Deciphering the evolution and complexity of wheat germplasm from a genomic perspective

Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.

Deciphering spike architecture formation towards yield improvement in wheat

Wheat is the most widely grown crop globally, providing 20% of the daily consumed calories and protein content around the world. With the growing global population and frequent occurrence of extreme weather caused by climate change, ensuring adequate wheat production is essential for food security. The architecture of the inflorescence plays a crucial role in determining the grain number and size, which is a key trait for improving yield. Recent advances in wheat genomics and gene cloning techniques have improved our understanding of wheat spike development and its applications in breeding practices. Here, we summarize the genetic regulation network governing wheat spike formation, the strategies used for identifying and studying the key factors affecting spike architecture, and the progress made in breeding applications. Additionally, we highlight future directions that will aid in the regulatory mechanistic study of wheat spike determination and targeted breeding for grain yield improvement.

Wheat adaptation to environmental stresses under climate change: Molecular basis and genetic improvement

Wheat (Triticum aestivum) is a staple food for about 40% of the world's population. As the global population has grown and living standards improved, high yield and improved nutritional quality have become the main targets for wheat breeding. However, wheat production has been compromised by global warming through the more frequent occurrence of extreme temperature events, which have increased water scarcity, aggravated soil salinization, caused plants to be more vulnerable to diseases, and directly reduced plant fertility and suppressed yield. One promising option to address these challenges is the genetic improvement of wheat for enhanced resistance to environmental stress. Several decades of progress in genomics and genetic engineering has tremendously advanced our understanding of the molecular and genetic mechanisms underlying abiotic and biotic stress responses in wheat. These advances have heralded what might be considered a "golden age" of functional genomics for the genetic improvement of wheat. Here, we summarize the current knowledge on the molecular and genetic basis of wheat resistance to abiotic and biotic stresses, including the QTLs/genes involved, their functional and regulatory mechanisms, and strategies for genetic modification of wheat for improved stress resistance. In addition, we also provide perspectives on some key challenges that need to be addressed.

Genome-Wide Association Study of Asian and European Common Wheat Accessions for Yield-Related Traits and Stripe Rust Resistance

Identifying novel loci of yield-related traits and resistance to stripe rust (caused by Puccinia striiformis f. sp. tritici) in wheat will help in breeding wheat that can meet projected demands in diverse environmental and agricultural practices. We performed a genome-wide association study with 24,767 single nucleotide polymorphisms (SNPs) in 180 wheat accessions that originated in 16 Asian or European countries between latitudes 30°N and 45°N. We detected seven accessions with desirable yield-related traits and 42 accessions that showed stable, high degrees of stripe rust resistance in multienvironment field assessments. A marker-trait association analysis of yield-related traits detected 18 quantitative trait loci (QTLs) in at least two test environments and two QTLs related to stripe rust resistance in at least three test environments. Five of these QTLs were identified as potentially novel QTLs by comparing their physical locations with those of known QTLs in the Chinese Spring (CS) reference genome RefSeq v1.1 published by the International Wheat Genome Sequencing Consortium; two were for spike length, one was for grain number per spike, one was for spike number, and one was for stripe rust resistance at the adult plant stage. We also identified 14 candidate genes associated with the five novel QTLs. These QTLs and candidate genes will provide breeders with new germplasm and can be used to conduct marker-assisted selection in breeding wheat with improved yield and stripe rust resistance.

Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.

Unravelling the Genetic Basis of Moisture Deficit Stress Tolerance in Wheat for Seedling Vigour-Related Traits and Root Traits Using Genome-Wide Association Study

A key abiotic stress that negatively affects seed germination, plant development, and crop yield is moisture deficit stress. Achieving higher vigour and uniform germination under stress conditions is essential for crop establishment and productivity and to enhance the yield. Hence, revealing wheat's capacity to withstand moisture deficit stress during seed germination and early growth stages is fundamental in improving its overall performance. However, the genetic regulation of moisture deficit stress tolerance during the seed germination phase remains largely unexplored. In this study, a total of 193 wheat genotypes were subjected to simulated moisture deficit stress using PEG-6000 (-0.4 MPa) during the seed germination stage. The induced moisture deficit stress significantly reduced various seedling-vigour-related traits. The genetic regions linked to these traits were found using a genome-wide association study (GWAS). The analysis identified 235 MTAs with a significance -log10(p) value of >4. After applying the Bonferroni correction, the study identified 47 unique single nucleotide polymorphisms (SNPs) that are linked to candidate genes important for the trait of interest. The current study emphasises the effectiveness of genome-wide association studies (GWAS) in identifying promising candidate genes, improving wheat seedling vigour and root traits, and offering essential information for the development of wheat cultivars tolerant to moisture deficit stress.

Meta-analysis of the quantitative trait loci associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits in pigeonpea (Cajanus cajan L.)

A meta-analysis of quantitative trait loci (QTLs), associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits was conducted for the first time in pigeonpea (Cajanus cajan L.). Data on 498 QTLs was collected from 9 linkage mapping studies (involving 21 biparental populations). Of these 498, 203 QTLs were projected onto "PigeonPea_ConsensusMap_2022," saturated with 10,522 markers, which resulted in the prediction of 34 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs (2.54 cM) was 3.37 times lower than the CI of the initial QTLs (8.56 cM). Of the 34 MQTLs, 12 high-confidence MQTLs with CI (≤5 cM) and a greater number of initial QTLs (≥5) were utilized to extract 2255 gene models, of which 105 were believed to be associated with different traits under study. Furthermore, eight of these MQTLs were observed to overlap with several marker-trait associations or significant SNPs identified in previous genome-wide association studies. Furthermore, synteny and ortho-MQTL analyses among pigeonpea and four related legumes crops, such as chickpea, pea, cowpea, and French bean, led to the identification of 117 orthologous genes from 20 MQTL regions. Markers associated with MQTLs can be employed for MQTL-assisted breeding as well as to improve the prediction accuracy of genomic selection in pigeonpea. Additionally, MQTLs may be subjected to fine mapping, and some of the promising candidate genes may serve as potential targets for positional cloning and functional analysis to elucidate the molecular mechanisms underlying the target traits.

Genome-wide association study unravels genomic regions associated with chlorophyll fluorescence parameters in wheat (Triticum aestivum L.) under different sowing conditions

KEY MESSAGE

Genome-wide association study identified 205 significant marker-trait associations for chlorophyll fluorescence parameters in wheat. Candidate gene mining, in silico expression, and promoter analyses revealed the potential candidate genes associated with the studied parameters. The present study investigated the effect of varied sowing conditions (viz., early, timely, and late) on different chlorophyll fluorescence parameters in diverse wheat germplasm set comprising of 198 lines over two cropping seasons (2020-2021 and 2021-2022). Further, a genome-wide association study was conducted to identify potential genomic regions associated with these parameters. The results revealed significant impacts of sowing conditions on all fluorescence parameters, with the maximum and minimum effects on FI (26.64%) and FV/FM (2.12%), respectively. Among the 205 marker-trait associations (MTAs) identified, 11 high-confidence MTAs were chosen, exhibiting substantial effects on multiple fluorescence parameters, and each explaining more than 10% of the phenotypic variation. Through gene mining of genomic regions encompassing high-confidence MTAs, we identified a total of 626 unique gene models. In silico expression analysis revealed 42 genes with an expression value exceeding 2 TPM. Among them, 10 genes were identified as potential candidate genes with functional relevance to enhanced photosynthetic efficiency. These genes mainly encoded for the following important proteins/products-ankyrin repeat protein, 2Fe-2S ferredoxin-type iron-sulfur-binding domain, NADH-ubiquinone reductase complex-1 MLRQ subunit, oxidoreductase FAD/NAD(P)-binding, photosystem-I PsaF, and protein kinases. Promoter analysis revealed the presence of light-responsive (viz., GT1-motif, TCCC-motif, I-box, GT1-motif, TCT-motif, and SP-1) and stress-responsive (viz., ABRE, AuxRR-core, GARE-motif, and ARE) cis-regulatory elements, which may be involved in the regulation of identified putative candidate genes. Findings from this study could directly help wheat breeders in selecting lines with favorable alleles for chlorophyll fluorescence, while the identified markers will facilitate marker-assisted selection of potential genomic regions for improved photosynthesis.

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.

Genetic diversity and genome-wide association study of 13 agronomic traits in 977 Beta vulgaris L. germplasms

BACKGROUND

Sugar beet (Beta vulgaris L.) is an economically essential sugar crop worldwide. Its agronomic traits are highly diverse and phenotypically plastic, influencing taproot yield and quality. The National Beet Medium-term Gene Bank in China maintains more than 1700 beet germplasms with diverse countries of origin. However, it lacks detailed genetic background associated with morphological variability and diversity.

RESULTS

Here, a comprehensive genome-wide association study (GWAS) of 13 agronomic traits was conducted in a panel of 977 sugar beet accessions. Almost all phenotypic traits exhibited wide genetic diversity and high coefficient of variation (CV). A total of 170,750 high-quality single-nucleotide polymorphisms (SNPs) were obtained using the genotyping-by-sequencing (GBS). Neighbour-joining phylogenetic analysis, principal component analysis, population structure and kinship showed no obvious relationships among these genotypes based on subgroups or regional sources. GWAS was carried out using a mixed linear model, and 159 significant associations were detected for these traits. Within the 25 kb linkage disequilibrium decay of the associated markers, NRT1/PTR FAMILY 6.3 (BVRB_5g097760); nudix hydrolase 15 (BVRB_8g182070) and TRANSPORT INHIBITOR RESPONSE 1 (BVRB_8g181550); transcription factor MYB77 (BVRB_2g023500); and ethylene-responsive transcription factor ERF014 (BVRB_1g000090) were predicted to be strongly associated with the taproot traits of root groove depth (RGD); root shape (RS); crown size (CS); and flesh colour (FC), respectively. For the aboveground traits, UDP-glycosyltransferase 79B6 (BVRB_9g223780) and NAC domain-containing protein 7 (BVRB_5g097990); F-box protein At1g10780 (BVRB_6g140760); phosphate transporter PHO1 (BVRB_3g048660); F-box protein CPR1 (BVRB_8g181140); and transcription factor MYB77 (BVRB_2g023500) and alcohol acyltransferase 9 (BVRB_2g023460) might be associated with the hypocotyl colour (HC); plant type (PT); petiole length (PL); cotyledon size (C); and fascicled leaf type (FLT) of sugar beet, respectively. AP-2 complex subunit mu (BVRB_5g106130), trihelix transcription factor ASIL2 (BVRB_2g041790) and late embryogenesis abundant protein 18 (BVRB_5g106150) might be involved in pollen quantity (PQ) variation. The candidate genes extensively participated in hormone response, nitrogen and phosphorus transportation, secondary metabolism, fertilization and embryo maturation.

CONCLUSIONS

The genetic basis of agronomical traits is complicated in heterozygous diploid sugar beet. The putative valuable genes found in this study will help further elucidate the molecular mechanism of each phenotypic trait for beet 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.

Association mapping reveals novel genes and genomic regions controlling grain size architecture in mini core accessions of Indian National Genebank wheat germplasm collection

Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E₁, E₂, E₃, E₄, E₅, E₅, E₆, and E₇). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.

Genome-wide association mapping of genomic regions associated with drought stress tolerance at seedling and reproductive stages in bread wheat

Understanding the genetic architecture of drought stress tolerance in bread wheat at seedling and reproductive stages is crucial for developing drought-tolerant varieties. In the present study, 192 diverse wheat genotypes, a subset from the Wheat Associated Mapping Initiative (WAMI) panel, were evaluated at the seedling stage in a hydroponics system for chlorophyll content (CL), shoot length (SLT), shoot weight (SWT), root length (RLT), and root weight (RWT) under both drought and optimum conditions. Following that, a genome-wide association study (GWAS) was carried out using the phenotypic data recorded during the hydroponics experiment as well as data available from previously conducted multi-location field trials under optimal and drought stress conditions. The panel had previously been genotyped using the Infinium iSelect 90K SNP array with 26,814 polymorphic markers. Using single as well as multi-locus models, GWAS identified 94 significant marker-trait associations (MTAs) or SNPs associated with traits recorded at the seedling stage and 451 for traits recorded at the reproductive stage. The significant SNPs included several novel, significant, and promising MTAs for different traits. The average LD decay distance for the whole genome was approximately 0.48 Mbp, ranging from 0.07 Mbp (chromosome 6D) to 4.14 Mbp (chromosome 2A). Furthermore, several promising SNPs revealed significant differences among haplotypes for traits such as RLT, RWT, SLT, SWT, and GY under drought stress. Functional annotation and in silico expression analysis revealed important putative candidate genes underlying the identified stable genomic regions such as protein kinases, O-methyltransferases, GroES-like superfamily proteins, NAD-dependent dehydratases, etc. The findings of the present study may be useful for improving yield potential, and stability under drought stress conditions.

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.

Identification of major QTLs for yield-related traits with improved genetic map in wheat

INTRODUCTION

Identification of stable major quantitative trait loci (QTLs) for yield-related traits is important for yield potential improvement in wheat breeding.

METHODS

In the present study, we genotyped a recombinant inbred line (RIL) population using the Wheat 660K SNP array and constructed a high-density genetic map. The genetic map showed high collinearity with the wheat genome assembly. Fourteen yield-related traits were evaluated in six environments for QTL analysis.

RESULTS AND DISCUSSION

A total of 12 environmentally stable QTLs were identified in at least three environments, explaining up to 34.7% of the phenotypic variation. Of these, QTkw-1B.2 for thousand kernel weight (TKW), QPh-2D.1 (QSl-2D.2/QScn-2D.1) for plant height (PH), spike length (SL) and spikelet compactness (SCN), QPh-4B.1 for PH, and QTss-7A.3 for total spikelet number per spike (TSS) were detected in at least five environments. A set of Kompetitive Allele Specific PCR (KASP) markers were converted based on the above QTLs and used to genotype a diversity panel comprising of 190 wheat accessions across four growing seasons. QPh-2D.1 (QSl-2D.2/QScn-2D.1), QPh-4B.1 and QTss-7A.3 were successfully validated. Compared with previous studies, QTkw-1B.2 and QPh-4B.1 should be novel QTLs. These results provided a solid foundation for further positional cloning and marker-assisted selection of the targeted QTLs in wheat breeding programs.

GWAS scans of cereal cyst nematode (Heterodera avenae) resistance in Indian wheat germplasm

Significant yield losses in major cereal-growing regions around the world have been linked to cereal cyst nematodes (Heterodera spp.). Identifying and deploying natural sources of resistance is of utmost importance due to increasing concerns associated with chemical methods over the years. We screened 141 diverse wheat genotypes collected from pan-Indian wheat cultivation states for nematode resistance over two years, alongside two resistant (Raj MR1, W7984 (M6)) and two susceptible (WH147, Opata M85) checks. We performed genome-wide association analysis using four single-locus models (GLM, MLM, CMLM, and ECMLM) and three multi-locus models (Blink, FarmCPU, and MLMM). Single locus models identified nine significant MTAs (-log10 (P) > 3.0) on chromosomes 2A, 3B, and 4B whereas, multi-locus models identified 11 significant MTAs on chromosomes 1B, 2A, 3B, 3D and 4B. Single and multi-locus models identified nine common significant MTAs. Candidate gene analysis identified 33 genes like F-box-like domain superfamily, Cytochrome P450 superfamily, Leucine-rich repeat, cysteine-containing subtype Zinc finger RING/FYVE/PHD-type, etc., having a putative role in disease resistance. Such genetic resources can help to reduce the impact of this disease on wheat production. Additionally, these results can be used to design new strategies for controlling the spread of H. avenae, such as the development of resistant varieties or the use of resistant cultivars. Finally, the obtained results can also be used to identify new sources of resistance to this pathogen and develop novel control methods.

Genome-Wide Association Study for Grain Protein, Thousand Kernel Weight, and Normalized Difference Vegetation Index in Bread Wheat (Triticum aestivum L.)

Genomic regions governing grain protein content (GPC), 1000 kernel weight (TKW), and normalized difference vegetation index (NDVI) were studied in a set of 280 bread wheat genotypes. The genome-wide association (GWAS) panel was genotyped using a 35K Axiom array and phenotyped in three environments. A total of 26 marker-trait associations (MTAs) were detected on 18 chromosomes covering the A, B, and D subgenomes of bread wheat. The GPC showed the maximum MTAs (16), followed by NDVI (6), and TKW (4). A maximum of 10 MTAs was located on the B subgenome, whereas, 8 MTAs each were mapped on the A and D subgenomes. In silico analysis suggest that the SNPs were located on important putative candidate genes such as NAC domain superfamily, zinc finger RING-H2-type, aspartic peptidase domain, folylpolyglutamate synthase, serine/threonine-protein kinase LRK10, pentatricopeptide repeat, protein kinase-like domain superfamily, cytochrome P450, and expansin. These candidate genes were found to have different roles including regulation of stress tolerance, nutrient remobilization, protein accumulation, nitrogen utilization, photosynthesis, grain filling, mitochondrial function, and kernel development. The effects of newly identified MTAs will be validated in different genetic backgrounds for further utilization in marker-aided breeding.

Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat

A better understanding of the genetic control of spike and kernel traits that have higher heritability can help in the development of high-yielding wheat varieties. Here, we identified the marker-trait associations (MTAs) for various spike- and kernel-related traits in winter wheat (Triticum aestivum L.) through genome-wide association studies (GWAS). An association mapping panel comprising 297 hard winter wheat accessions from the U.S. Great Plains was evaluated for eight spike- and kernel-related traits in three different environments. A GWAS using 15,590 single-nucleotide polymorphisms (SNPs) identified a total of 53 MTAs for seven spike- and kernel-related traits, where the highest number of MTAs were identified for spike length (16) followed by the number of spikelets per spike (15) and spikelet density (11). Out of 53 MTAs, 14 were considered to represent stable quantitative trait loci (QTL) as they were identified in multiple environments. Five multi-trait MTAs were identified for various traits including the number of spikelets per spike (NSPS), spikelet density (SD), kernel width (KW), and kernel area (KA) that could facilitate the pyramiding of yield-contributing traits. Further, a significant additive effect of accumulated favorable alleles on the phenotype of four spike-related traits suggested that breeding lines and cultivars with a higher number of favorable alleles could be a valuable resource for breeders to improve yield-related traits. This study improves the understanding of the genetic basis of yield-related traits in hard winter wheat and provides reliable molecular markers that will facilitate marker-assisted selection (MAS) in wheat breeding programs.

Conservatively transmitted alleles of key agronomic genes provide insights into the genetic basis of founder parents in bread wheat (Triticum aestivum L.)

BACKGROUND

Founder parents play extremely important roles in wheat breeding. Studies into the genetic basis of founder parents and the transmission rules of favorable alleles are of great significance in improving agronomically important traits in wheat.

RESULTS

Here, a total of 366 founder parents, widely grown cultivars, and derivatives of four representative founder parents were genotyped based on efficient kompetitive allele-specific PCR (KASP) markers in 87 agronomically important genes controlling yield, quality, adaptability, and stress resistance. Genetic composition analysis of founder parents and widely grown cultivars showed a consistently high frequency of favorable alleles for yield-related genes. This analysis further showed that other alleles favorable for resistance, strong gluten, dwarf size, and early heading date were also subject to selective pressure over time. By comparing the transmission of alleles from four representative founder parents to their derivatives during different breeding periods, it was found that the genetic composition of the representative founder parents was optimized as breeding progressed over time, with the number and types of favorable alleles carried gradually increasing and becoming enriched. There are still a large number of favorable alleles in wheat founder parents that have not been fully utilized in breeding selection. Eighty-seven agronomically important genes were used to construct an enrichment map that shows favorable alleles of four founder parents, providing an important theoretical foundation for future identification of candidate wheat founder parents.

CONCLUSIONS

These results reveal the genetic basis of founder parents and allele transmission for 87 agronomically important genes and shed light on breeding strategies for the next generation of elite founder parents in wheat.

Effects of genetic components of plant development on yield-related traits in wheat (Triticum aestivum L.) under stress-free conditions

The dynamics of plant development not only has an impact on ecological adaptation but also contributes to the realization of genetically determined yield potentials in various environments. Dissecting the genetic determinants of plant development becomes urgent due to the global climate change, which can seriously affect and even disrupt the locally adapted developmental patterns. In order to determine the role plant developmental loci played in local adaptation and yield formation, a panel of 188 winter and facultative wheat cultivars from diverse geographic locations were characterized with the 15K Illumina Single Nucleotide Polymorphism (SNP) chip and functional markers of several plant developmental genes and included into a multiseason field experiment. Genome-wide association analyses were conducted on five consecutive developmental phases spanning from the first node appearance to full heading together with various grain yield-related parameters. The panel was balanced for the PPD-D1 photoperiod response gene, which facilitated the analyses in the two subsets of photoperiod-insensitive and -sensitive genotypes in addition to the complete panel. PPD-D1 was the single highest source, explaining 12.1%-19.0% of the phenotypic variation in the successive developmental phases. In addition, 21 minor developmental loci were identified, each one explaining only small portions of the variance, but, together, their effects amounted to 16.6%-50.6% of phenotypic variance. Eight loci (2A_27, 2A_727, 4A_570, 5B_315, 5B_520, 6A_26, 7A_1-(VRN-A3), and 7B_732) were independent of PPD-D1. Seven loci were only detectable in the PPD-D1-insensitive genetic background (1A_539, 1B_487, 2D_649, 4A_9, 5A_584-(VRN-A1), 5B_571-(VRN-B1), and 7B_3-(VRN-B3)), and six loci were only detectable in the sensitive background, specifically 2A_740, 2D_25, 3A_579, 3B_414, 7A_218, 7A_689, and 7B_538. The combination of PPD-D1 insensitivity and sensitivity with the extremities of early or late alleles in the corresponding minor developmental loci resulted in significantly altered and distinct plant developmental patterns with detectable outcomes on some yield-related traits. This study examines the possible significance of the above results in ecological adaptation.

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.