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

Ancient diversity of Triticum aestivum subspecies as source of novel loci for bread wheat improvement

Ancient subspecies of hexaploid wheat, not yet subjected to intensive selection, harbor potentially valuable alternative genetic variability for the genetic improvement of modern cultivated bread wheat. To investigate these hitherto unexplored resources, we established a panel, currently unique, consisting of 190 accessions of Triticum aestivum belonging to five different neglected subspecies, compactum, sphaerococcum, macha, spelta, and vavilovii, with few aestivum references. The panel was genotyped through the iSelect Illumina arrays (20K and 25K) and phenotyped for 25 traits related to phenology, morphology, yield, and physiology for 4 years under field conditions. We found wide variability for all traits analyzed, both within and among subspecies, demonstrating the richness contained therein. Through a genome-wide association study (GWAS), we identified a total of 126 marker-trait associations (MTAs), including 4 for years, 58 for morphological traits, 39 related to yield, and 25 for physiological traits, some of them confirming loci previously published and others being novel. Fourteen MTAs were associated with multiple traits. Among them, one on chromosome 2D at 360.2 Mb was associated with spike density, length, and shape, and thus is of particular interest because it may underlie the compactum (C) gene, until now considered difficult to clone because of its centromeric position. The physical distance defined by this MTA is considerably smaller (1.7 Mb) than what is reported so far in the literature, paving the way toward physical mapping of the C gene. A potential candidate gene has been identified for the trait grain number per spike. This is TraesCS6A03G0476500, coding for a monosaccharide-sensing protein 2, located on chromosome 6A at 233 Mb and identified through an MTA that segregates exclusively in compactum accessions. The results obtained confirm the remarkable potential present in the panel of wheat subspecies analyzed in this study, which, being characterized by a very short linkage disequilibrium (LD) decay, allowed the definition of rather narrow ranges around key traits, such as those related to yield, providing new perspectives on transferring genes across subspecies for wheat improvement.

Analysis of allohexaploid wheatgrass genome reveals its Y haplome origin in Triticeae and high-altitude adaptation

Phylogenetic origin of the Y haplome present in allopolyploid Triticeae species remains unknown. Here, we report the 10.47 Gb chromosome-scale genome of allohexaploid Elymus nutans (StStYYHH). Phylogenomic analyses reveal that the Y haplome is sister to the clade comprising V and Jv haplomes from Dasypyrum and Thinopyum. In addition, H haplome from the Hordeum-like ancestor, St haplome from the Pseudoroegneria-like ancestor and Y haplome are placed in the successively diverged clades. Resequencing data reveal the allopolyploid origins with St, Y, and H haplome combinations in Elymus. Population genomic analyses indicate that E. nutans has expanded from medium to high/low-altitude regions. Phenotype/environmental association analyses identify MAPKKK18 promoter mutations reducing its expression, aiding UV-B adaptation in high-altitude populations. These findings enhance understanding of allopolyploid evolution and aid in breeding forage and cereal crops through intergeneric hybridization within Triticeae.

Deciphering the regulatory network of lignocellulose biosynthesis in bread wheat through genome-wide association studies

KEY MESSAGE

This study identified 46 key QTL and 17 candidate genes and developed a KASP marker, providing valuable molecular tools for enhancing lignocellulose traits, lodging resistance, and bioenergy potential in wheat. Wheat lignocellulose, composed of lignin, cellulose, and hemicellulose, plays a crucial role in strengthening plant cell walls, enhancing lodging resistance, and contributing to bioenergy production. However, the genetic basis underlying the variation in lignocellulose content in wheat remains poorly understood. The stem lignin, cellulose, and hemicellulos contents in the second stem internode of a panel of 166 wheat accessions grown in three environments were measured, combined with the genotyping data with 660 K wheat SNP chip; a genome-wide association studies (GWAS) were conducted to identify loci associated with the lignocellulose content in wheat. Significant variations in lignin, cellulose, and hemicellulose contents were observed among the wheat accessions. GWAS identified 1146 significant SNPs associated with lignin, cellulose, and hemicellulose contents, distributed across the A, B, and D sub-genomes of wheat. Joint analysis of haplotype blocks refined these associations, identifying 46 significant quantitative trait loci (QTL) regions and 17 candidate genes, primarily linked to vascular development, hemicellulose synthesis, internode elongation regulation, and lignin biosynthesis. A KASP marker (NW_CC5951) for lignocellulose was developed. These findings provide valuable molecular markers for marker-assisted selection, supporting wheat breeding for improved stem quality and lodging resistance, and offer insights into balancing grain yield with lodging resistance and lignocellulosic energy production.

Genome-wide association study reveals of a FtS1Fa1 gene regulating rutin biosynthesis in Tartary buckwheat

Tartary buckwheat (Fagopyrum tataricum Gaertn, TB) is an annual multigrain crop belonging to the genus Fagopyrum within the Polygonaceae family. TB is valued for its balanced nutrient composition and high flavonoid content, particularly rutin, which possesses various health and medicinal benefits. Therefore, rutin has become a critical trait in determining the quality of TB. The rutin content (RC) of 101 natural TB materials measured in this study ranged from 14.08 to 24.50 mg/g, with an average value of 19.46 mg/g. This result revealed substantial natural variation in RC within the TB population. Furthermore, 314,166 high-quality single nucleotide polymorphisms (SNPs) were identified through whole-genome resequencing. Population structure analysis demonstrated that genetic information was consistent among the samples, while significant structural differences were observed among the groups. A genome-wide association study (GWAS) employing a mixed linear model (MLM) identified the SNP site Ft4:1777524 as significantly associated with rutin levels. Within the 400 kb candidate region, 27 key genes were identified. Further joint analysis of previous transcriptome data revealed that FtS1Fa1 is closely linked to RC. Molecular biological characterization revealed that this gene belongs to the S1Fa-like family, is localized in chloroplasts, but lacks transcriptional activation capabilities. Functional studies indicated that FtS1Fa1 can promote rutin accumulation in TB by upregulating the expression of the rutin biosynthesis gene. In conclusion, this study enhances the understanding of the regulatory mechanisms governing rutin biosynthesis in TB and provides important germplasm resources for the molecular breeding of high-rutin TB varieties.

Candidate Gene for Kernel-Related Traits in Maize Revealed by a Combination of GWAS and Meta-QTL Analyses

Maize kernel traits represent crucial agronomic characteristics that significantly determine yield potential. Analyzing the genetic basis of these traits is essential for yield improvement. In this study, we utilized 1283 maize inbred lines to investigate three kernel-related characteristics: kernel length (KL), kernel width (KW), and 100-kernel weight (HKW). We conducted a genome-wide association study (GWAS) on three kernel-related traits, resulting in the identification of 29 significantly associated SNPs and six candidate genes. Additionally, we compiled quantitative trait loci (QTL) information for 765 maize kernel-related traits from 56 studies, conducted a meta-analysis of QTL, and identified 65 meta-QTLs (MQTLs). Among the 23 MQTLs, we found 25 functional genes and reported candidate genes related to kernel traits. We identified 26 maize homologs across 19 MQTLs by utilizing 25 genes that affect rice grain traits. We compared the 29 significant SNPs detected with the physical locations of 65 MQTLs and found that 3 significant SNPs were located within these MQTL intervals, and another 10 significant SNPs were in proximity to these intervals, being less than 2 Mb away, although they were not included within the MQTL intervals. The results of this study provide a theoretical foundation for elucidating the genetic basis of maize kernel-related traits and advancing molecular marker-assisted breeding selection.

Unraveling the genetic basis of heat tolerance and yield in bread wheat: QTN discovery and Its KASP-assisted validation

BACKGROUND

Wheat (Triticum aestivum L.), a globally significant cereal crop and staple food, faces major production challenges due to abiotic stresses such as heat stress (HS), which pose a threat to global food security. To address this, a diverse panel of 126 wheat genotypes, primarily landraces, was evaluated across twelve environments in India, comprising of three locations, two years and two growing conditions. The study aimed to identify genetic markers associated with key agronomic traits in bread wheat, including germination percentage (GERM_PCT), ground cover (GC), days to booting (DTB), days to heading (DTHD), days to flowering (DTFL), days to maturity (DTMT), plant height (PH), grain yield (GYLD), thousand grain weight (TGW), and the normalized difference vegetation index (NDVI) under both timely and late-sown conditions using 35 K SNP genotyping assays. Multi-locus GWAS (ML-GWAS) was employed to detect significant marker-trait associations, and the identified markers were further validated using Kompetitive Allele Specific PCR (KASP).

RESULTS

Six ML-GWAS models were employed for this purpose, leading to the identification of 42 highly significant and consistent quantitative trait nucleotides (QTNs) under both timely and late sown conditions, controlled by 20 SNPs, explaining 3-58% of the total phenotypic variation. Among these, noteworthy QTNs were a major grain yield QTN (qtn_nbpgr_GYLD_3B) on chromosome 3B, a pleiotropic SNP AX-95018072 on chromosome 7A influencing phenology and NDVI, and robust TGW QTNs on chromosomes 2B (qtn_nbpgr_TGW_2B), 1A (qtn_nbpgr_TGW_1A), and 4B (qtn_nbpgr_TGW_4B). Furthermore, annotation revealed that candidate genes near these QTNs encoded stress-responsive proteins, such as chaperonins, glycosyl hydrolases, and signaling molecules. Additionally, three major SNPs AX-95018072 (7A), AX-94946941 (6B), and AX-95232570 (1B) were successfully validated using KASP assay.

CONCLUSION

Our study effectively uncovered novel QTNs and candidate genes linked to heat tolerance and yield-related traits in wheat through an extensive genetic approaches. These QTNs not only corresponded with previously identified QTLs and genes associated with yield traits but also highlighted several new loci, broadening the existing genetic understanding. These findings provide valuable insights into the genetic basis of heat tolerance in wheat and offer genomic resources, including validated markers that could accelerate marker-assisted breeding and the development of next-generation heat-resilient cultivars.

Genetic dissection of flag leaf morphology traits and fine mapping of a novel QTL (Qflw.sxau-6BL) in bread wheat (Triticum aestivum L.)

KEY MESSAGE

Total 60-QRC for FLM traits were detected by meta-genomics analysis, nine major and stable QTL identified by DH population and validated, and a novel QTL  Qflw.sxau-6BL was fine mapped. The flag leaf is an "ideotypic" morphological trait providing photosynthetic assimilates in wheat. Although flag leaf morphology (FLM) traits had been extensively investigated through genetic mapping, there is a desire for FLM-related loci to be validated in multi-environments and fine mapping. In order to identify the stable genomic regions for FLM traits, we conducted a meta-genomic analysis based on reports from 2008 to 2024. Experimentally, a doubled haploid (DH) population was used to assess the genetic regions associated with FLM traits in nine environments. The meta-genomic analysis extracted 60 QTL-rich clusters (QRC), 45 of which were verified in marker-trait association (MTA) study. Nine major and stable QTL were found being associated with FLM traits across three-to-seven environments including BLUP, with phenotypic variance explained (PVE) ranging from 5.05 to 34.95%. The KASP markers of the nine QTL were validated (P < 0.005) in more than three environments using a panel of diverse wheat collections from Shanxi Province in China. Two co-located major and stable QTL viz. Qflw.sxau-6B.5 and Qfla.sxau-6B.4 were found novel and contributed to increase FLW by 12.09-19.21% and FLA by 5.45-13.28%. They also demonstrated high recombination rates in LD analysis based on the resequencing of 145 wheat landmark cultivars. The fine mapping of Qflw.sxau-6BL narrowed it down to a 1.27 Mb region as a result of the combined genotypic and phenotypic analysis for secondary mapping population. Comparing to NIL-ND3338, the NIL-LF5064 showed higher FLW by 20.45-27.37%, thousand-grain weight by 1.88-2.57% and grain length by 0.47-2.30% across all environments. The expression analysis of 11 tissues revealed seven highly expressed genes within the fine map region. This study provides a genetic basis for the FLM traits for further map-based cloning of FLW genes in wheat.

The Genetics and Breeding of Heat Stress Tolerance in Wheat: Advances and Prospects

Heat stress is one of the major concerns for wheat production worldwide. Morphological parameters such as germination, leaf area, shoot, and root growth are affected by heat stress, with affected physiological parameters including photosynthesis, respiration, and water relation. Heat stress also leads to the generation of reactive oxygen species that disrupt the membrane systems of thylakoids, chloroplasts, and the plasma membrane. The deactivation of the photosystems, reduction in photosynthesis, and inactivation of Rubisco affect the production of photo-assimilates and their allocation, consequently resulting in reduced grain yield and quality. The development of thermo-tolerant wheat varieties is the most efficient and fundamental approach for coping with global warming. This review provides a comprehensive overview of various aspects related to heat stress tolerance in wheat, including damages caused by heat stress, mechanisms of heat stress tolerance, genes or QTLs regulating heat stress tolerance, and the methodologies of breeding wheat cultivars with high heat stress tolerance. Such insights are essential for developing thermo-tolerant wheat cultivars with high yield potential in response to an increasingly warmer environment.

Exploring the genetic diversity and population structure of an ancient hexaploid wheat species Triticum sphaerococcum using SNP markers

BACKGROUND

Understanding genetic diversity and population structure is crucial for strategizing and enhancing breeding efficiency. Wheat, a globally cultivated crop, is a significant source of daily calories for humans. To overcome challenges such as extreme climatic fluctuations, stagnant yields, and diminishing genetic variation, it is essential to develop diverse germplasms with new alleles. Triticum sphaerococcum, an underutilized ancient hexaploid wheat species, shows promise for contributing beneficial alleles. However, the genetic diversity of its germplasms remains unstudied. This is the first report where we have examined the genetic diversity and population structure of 116 T. sphaerococcum accessions using a 35 K SNP Array. The objective of this study is to apply these findings to improve wheat breeding programs.

RESULTS

Analysis of the population's genetic structure identified four potential subpopulations, which was supported by principal coordinate analysis. Allele neutrality tests showed an abundance of intermediate genotypes, suggesting that many beneficial alleles are maintained through balancing selection. Among the three subgenomes, subgenome B exhibited the highest genetic diversity. AMOVA (Analysis of Molecular Variance) revealed significant variation both among (35%) and within (65%) the four subpopulations. The high genetic differentiation between subpopulations was corroborated by a moderate level of haploid migrant numbers (Nm = 1.286), indicating sufficient gene flow. SP4 emerged as the most diverse subpopulation, showing the highest values for allelic pattern indices due to its larger size and higher percentage of polymorphic loci. The D subgenome displayed a faster linkage disequilibrium (LD) decay rate compared to the A and B subgenomes. Haplotype block analysis identified 260 haplotype blocks of varying sizes distributed across the genome.

CONCLUSIONS

This research demonstrates that Indian dwarf wheat accessions, sourced from three distinct gene banks and local collections, possess considerable genetic diversity. These germplasm collections offer valuable opportunities to investigate their unexplored genetic potential. They can be utilized in wheat improvement initiatives to tackle both present and future breeding challenges. Furthermore, these accessions can introduce new alleles to broaden the genetic base of modern wheat varieties, enhancing their overall diversity.

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.

High-throughput root phenotyping and association analysis identified potential genomic regions for phosphorus use efficiency in wheat (Triticum aestivum L.)

MAIN CONCLUSION

Association analysis identified 77 marker-trait associations (MTAs) for PUE traits, of which 10 were high-confidence MTAs. Candidate-gene mining and in-silico expression analysis identified 13 putative candidate genes for PUE traits. Bread wheat (Triticum aestivum L.) is a major cereal crop affected by phosphorus (P) deficiency, which affects root characteristics, plant biomass, and other attributes related to P-use efficiency (PUE). Understanding the genetic mechanisms of PUE traits helps in developing bread wheat cultivars that perform well in low-P environments. With this objective, we evaluated a bread wheat panel comprising 304 accessions for 14 PUE traits with high-throughput phenotyping under low-P and optimum-P treatments and observed a significant genetic variation among germplasm lines for studied traits. Genome-wide association study (GWAS) using 14,025 high-quality single-nucleotide polymorphisms identified 77 marker-trait associations (MTAs), of which 10 were chosen as high-confidence MTAs as they had > 10% phenotypic variation with logarithm of odds (LOD) scores of more than five. Candidate-gene (CG) mining from high-confidence MTAs identified 180 unique gene models, of which 78 were differentially expressed (DEGs) with at least twofold change in expression under low-P over optimum-P. Of the 78-DEGs, 13 were thought to be putative CGs as they exhibited functional relevance to PUE traits. These CGs mainly encode for important proteins and their products involved in regulating root system architecture, P uptake, transport, and utilization. Promoter analysis from 1500 bp upstream of gene start site for 13 putative CGs revealed the presence of light responsive, salicylic-acid responsive, gibberellic-acid (GA)-responsive, auxin-responsive, and cold responsive cis-regulatory elements. High-confidence MTAs and putative CGs identified in this study can be employed in breeding programs to improve PUE traits in bread wheat.

Identification and validation of two quantitative trait loci showing pleiotropic effect on multiple grain-related traits in bread wheat (Triticum aestivum L.)

KEY MESSAGE

QKl/Tgw/Gns.yaas-2D associates with KL, TGW, and GNS, and QKl/Tgw.yaas-5A associates with KL and TGW. Significantly pleiotropic and additive effects of these two QTL were validated. The YM5 allele both at QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A was proved to be the best allelic combination for improving yield potential. Kernel length (KL), kernel width (KW), thousand grain weight (TGW), and grain number per spike (GNS) play important roles in the yield improvement of wheat. In this study, one recombinant inbred line (RIL) derived from a cross between Yangmai 5 (YM5) and Yanzhan 1 (YZ1) was used to identify quantitative trait loci (QTL) associated with KL, KW, TGW, and GNS across three years. Two pleiotropic QTL namely QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A were located in two genomic regions on chromosomes 2D and 5A, respectively. Breeder-friendly Kompetitive Allele-Specific PCR (KASP) markers for QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A were developed and validated in a set of 246 wheat cultivars/lines. Analysis of allelic combinations indicated that the YM5 allele both at QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A is probably the best one to promote TGW, GNS, and grain weight per spike. Based on the analysis of gene annotation, sequence variations, expression patterns, and GO enrichment, twenty-five and twenty-four candidate genes of QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A, respectively, were identified. These results provide the basis of fine-mapping the target QTL and marker-assisted selection in wheat yield-breeding programs.

GWAS for identification of genomic regions and candidate genes in vegetable crops

Genome-wide association Studies (GWAS), initially developed for human genetics, have been highly effective in plant research, particularly for vegetable crops. GWAS is a robust tool for identifying genes associated with key traits such as yield, nutritional value, disease resistance, adaptability, and bioactive compound biosynthesis. Unlike traditional methods, GWAS does not require prior biological knowledge and can accurately pinpoint loci, minimizing false positives. The process involves developing a diverse panel, rigorous phenotyping and genotyping, and sophisticated statistical analysis using various models and software tools. By scanning the entire genome, GWAS identifies specific loci or single nucleotide polymorphisms (SNPs) linked to target traits. When a causal SNP variant is not directly genotyped, GWAS identifies SNPs in linkage disequilibrium (LD) with the causal variant, mapping the genetic interval. The method begins with careful panel selection, phenotyping, and genotyping, controlling for environmental effects and utilizing Best Linear Unbiased Prediction (BLUP). High-correlation, high-heritability traits are prioritized. Various genotyping methods address confounders like population structure and kinship. Bonferroni correction (BC) prevents false positives, and significant associations are shown in Manhattan plots. Candidate genes are identified through LD analysis and fine mapping, followed by functional validation. GWAS offers critical insights for enhancing vegetable crop breeding efficiency and precision, driving breakthroughs through advanced methods.

Integrating genetic analysis of germplasm wealth for enhanced selection and improvement in olive (Olea europaea L.): insights from leaves

KEY MESSAGE

High-throughput next-generation sequencing of 161 olive germplas. 33 samples were selected as core olive germplasm and Fingerprints were constructed. After GWAS analysis of olive leaf shape, 14 candidate genes were localized. Olive (Olea europaea L.) has been introduced to China since the 1960s. After a prolonged period of variation and domestication, there is a lack of comprehensive research on its genetics. The olive oil directly extracted from Olea europaea L. is recognized as 'liquid gold', nevertheless, people constantly overlook the valuable wealth of olive leaves. High-throughput next-generation sequencing was performed on 161 olive germplasm to analyze the kinship, genetic structure and diversity of olives, and the core germplasm of olives were selected and fingerprints were constructed. Meanwhile, Genome-wide association analysis (GWAS) was performed to locate the gene for regulating olive leaf shape. Herein, the results parsed that most of the Chinese olive germplasm was more closely related to the Italian germplasm. A wealth of hybridized germplasm possessed high genetic diversity and had the potential to be used as superior parental material for olive germplasm. A total of 33 samples were selected and characterized as core germplasm of olive and Fingerprints were also constructed. A total of 14 candidate genes were localized after GWAS analysis of four olive leaf shape phenotypes, including leaf shape, leaf curvature shape, leaf tip and leaf base shape. Collectively, this study revealed the genetic basis of olives in China and also succeeded in constructing the core germplasm that stands for the genetic diversity of olives, which can contribute to the scientific and effective collection and preservation of olive germplasm resources, and provide a scientific basis for the in-depth excavation and utilization of genes regulating olive leaf shape.

Genetic architecture of kernel-related traits in sweet and waxy maize revealed by genome-wide association analysis

Introduction

Maize (Zea mays L.) is one of the most important crops worldwide, the kernel size-related traits are the major components of maize grain yield.

Methods

To dissect the genetic architecture of four kernel-related traits of 100-kernel weight, kernel length, kernel width, and kernel diameter, a genome-wide association study (GWAS) was conducted in the waxy and sweet maize panel comprising of 447 maize inbred lines re-sequenced at the 5× coverage depth. GWAS analysis was carried out with the mixed linear model using 1,684,029 high-quality SNP markers.

Results

In total, 49 SNPs significantly associated with the four kernel-related traits were identified, including 46 SNPs on chromosome 3, two SNPs on chromosome 4, and one SNP on chromosome 7. Haplotype regression analysis identified 338 haplotypes that significantly affected these four kernel-related traits. Genomic selection (GS) results revealed that a set of 10,000 SNPs and a training population size of 30% are sufficient for the application of GS in waxy and sweet maize breeding for kernel weight and kernel size. Forty candidate genes associated with the four kernel-related traits were identified, including both Zm00001d000707 and Zm00001d044139 expressed in the kernel development tissues and stages with unknown functions.

Discussion

These significant SNPs and important haplotypes provide valuable information for developing functional markers for the implementation of marker-assisted selection in breeding. The molecular mechanism of Zm00001d000707 and Zm00001d044139 regulating these kernel-related traits needs to be investigated further.

Identification of Quantitative Trait Loci Associated with Plant Adaptation Traits Using Nested Association Mapping Population

This study evaluated 290 recombinant inbred lines (RILs) of the nested association mapping (NAM) population from the UK. The population derived from 24 families, where a common parent was "Paragon," one of the UK's spring wheat cultivar standards. All genotypes were tested in two regions of Kazakhstan at the Kazakh Research Institute of Agriculture and Plant Industry (KRIAPI, Almaty region, Southeast Kazakhstan, 2019-2022 years) and Alexandr Barayev Scientific-Production Center for Grain Farming (SPCGF, Shortandy, Akmola region, Northern Kazakhstan, 2019-2022 years). The studied traits consisted of plant adaptation-related traits, including heading date (HD, days), seed maturation date (SMD, days), plant height (PH, cm), and peduncle length (PL, cm). In addition, the yield per m2 was analyzed in both regions. Based on a field evaluation of the population in northern and southeastern Kazakhstan and using 10,448 polymorphic SNP (single-nucleotide polymorphism) markers, the genome-wide association study (GWAS) allowed for detecting 74 QTLs in four studied agronomic traits (HD, SMD, PH, and PL). The literature survey suggested that 16 of the 74 QTLs identified in our study had also been detected in previous QTL mapping studies and GWASs for all studied traits. The results will be used for further studies related to the adaptation and productivity of wheat in breeding projects for higher grain productivity.

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.

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.

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.

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 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.

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.

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.