Development and evaluation of Fusarium wilt-resistant and high-yielding chickpea advanced breeding line, KCD 11.

Fusarium wilt (FW) is the most severe soil-borne disease of chickpea that causes yield losses up to 100%. To improve FW resistance in JG 11, a high-yielding variety that became susceptible to FW, we used WR 315 as the donor parent and followed the pedigree breeding method. Based on disease resistance and yield performance, four lines were evaluated in station trials during 2017-2018 and 2018-2019 at Kalaburagi, India. Further, two lines, namely, Kalaburagi chickpea desi 5 (KCD 5) and KCD 11, which possesses the resistance allele for a specific single-nucleotide polymorphism marker linked with FW resistance, were evaluated across six different locations (Bidar, Kalaburagi, Raichur, Siruguppa, Bhimarayanagudi and Hagari) over a span of 3 years (2020-2021, 2021-2022 and 2022-2023). KCD 11 exhibited notable performance, showcasing yield advantages of 8.67%, 11.26% and 23.88% over JG 11, and the regional checks Super Annigeri 1 (SA 1) and Annigeri 1, respectively, with enhanced FW resistance in wilt sick plot. Further, KCD 11 outperformed JG 11, SA 1 and Annigeri 1 in multi-location trials conducted across three seasons in the North Eastern Transition Zone, North Eastern Dry Zone, and North Dry Zones of Karnataka. KCD 11 was also tested in trials conducted by All India Coordinated Research Project on chickpea and was also nominated for state varietal trials for its release as a FW-resistant and high-yielding variety. The selected line is anticipated to cater the needs of chickpea growers with the dual advantage of yield increment and disease resistance.

Meta QTL analysis for dissecting abiotic stress tolerance in chickpea.

BACKGROUND: Chickpea is prone to many abiotic stresses such as heat, drought, salinity, etc. which cause severe loss in yield. Tolerance towards these stresses is quantitative in nature and many studies have been done to map the loci influencing these traits in different populations using different markers. This study is an attempt to meta-analyse those reported loci projected over a high-density consensus map to provide a more accurate information on the regions influencing heat, drought, cold and salinity tolerance in chickpea. RESULTS: A meta-analysis of QTL reported to be responsible for tolerance to drought, heat, cold and salinity stress tolerance in chickpeas was done. A total of 1512 QTL responsible for the concerned abiotic stress tolerance were collected from literature, of which 1189 were projected on a chickpea consensus genetic map. The QTL meta-analysis predicted 59 MQTL spread over all 8 chromosomes, responsible for these 4 kinds of abiotic stress tolerance in chickpea. The physical locations of 23 MQTL were validated by various marker-trait associations and genome-wide association studies. Out of these reported MQTL, CaMQAST1.1, CaMQAST4.1, CaMQAST4.4, CaMQAST7.8, and CaMQAST8.2 were suggested to be useful for different breeding approaches as they were responsible for high per cent variance explained (PVE), had small intervals and encompassed a large number of originally reported QTL. Many putative candidate genes that might be responsible for directly or indirectly conferring abiotic stress tolerance were identified in the region covered by 4 major MQTL- CaMQAST1.1, CaMQAST4.4, CaMQAST7.7, and CaMQAST6.4, such as heat shock proteins, auxin and gibberellin response factors, etc. CONCLUSION: The results of this study should be useful for the breeders and researchers to develop new chickpea varieties which are tolerant to drought, heat, cold, and salinity stresses.

Aspergillus flavus pangenome (AflaPan) uncovers novel aflatoxin and secondary metabolite associated gene clusters.

BACKGROUND: Aspergillus flavus is an important agricultural and food safety threat due to its production of carcinogenic aflatoxins. It has high level of genetic diversity that is adapted to various environments. Recently, we reported two reference genomes of A. flavus isolates, AF13 (MAT1-2 and highly aflatoxigenic isolate) and NRRL3357 (MAT1-1 and moderate aflatoxin producer). Where, an insertion of 310 kb in AF13 included an aflatoxin producing gene bZIP transcription factor, named atfC. Observations of significant genomic variants between these isolates of contrasting phenotypes prompted an investigation into variation among other agricultural isolates of A. flavus with the goal of discovering novel genes potentially associated with aflatoxin production regulation. Present study was designed with three main objectives: (1) collection of large number of A. flavus isolates from diverse sources including maize plants and field soils; (2) whole genome sequencing of collected isolates and development of a pangenome; and (3) pangenome-wide association study (Pan-GWAS) to identify novel secondary metabolite cluster genes. RESULTS: Pangenome analysis of 346 A. flavus isolates identified a total of 17,855 unique orthologous gene clusters, with mere 41% (7,315) core genes and 59% (10,540) accessory genes indicating accumulation of high genomic diversity during domestication. 5,994 orthologous gene clusters in accessory genome not annotated in either the A. flavus AF13 or NRRL3357 reference genomes. Pan-genome wide association analysis of the genomic variations identified 391 significant associated pan-genes associated with aflatoxin production. Interestingly, most of the significantly associated pan-genes (94%; 369 associations) belonged to accessory genome indicating that genome expansion has resulted in the incorporation of new genes associated with aflatoxin and other secondary metabolites. CONCLUSION: In summary, this study provides complete pangenome framework for the species of Aspergillus flavus along with associated genes for pathogen survival and aflatoxin production. The large accessory genome indicated large genome diversity in the species A. flavus, however AflaPan is a closed pangenome represents optimum diversity of species A. flavus. Most importantly, the newly identified aflatoxin producing gene clusters will be a new source for seeking aflatoxin mitigation strategies and needs new attention in research.

Cicer super-pangenome provides insights into species evolution and agronomic trait loci for crop improvement in chickpea.

Chickpea (Cicer arietinum L.)-an important legume crop cultivated in arid and semiarid regions-has limited genetic diversity. Efforts are being undertaken to broaden its diversity by utilizing its wild relatives, which remain largely unexplored. Here, we present the Cicer super-pangenome based on the de novo genome assemblies of eight annual Cicer wild species. We identified 24,827 gene families, including 14,748 core, 2,958 softcore, 6,212 dispensable and 909 species-specific gene families. The dispensable genome was enriched for genes related to key agronomic traits. Structural variations between cultivated and wild genomes were used to construct a graph-based genome, revealing variations in genes affecting traits such as flowering time, vernalization and disease resistance. These variations will facilitate the transfer of valuable traits from wild Cicer species into elite chickpea varieties through marker-assisted selection or gene-editing. This study offers valuable insights into the genetic diversity and potential avenues for crop improvement in chickpea.

Unraveling the genetics of heat tolerance in chickpea landraces (Cicer arietinum L.) using genome-wide association studies.

Chickpea, being an important grain legume crop, is often confronted with the adverse effects of high temperatures at the reproductive stage of crop growth, drastically affecting yield and overall productivity. The current study deals with an extensive evaluation of chickpea genotypes, focusing on the traits associated with yield and their response to heat stress. Notably, we observed significant variations for these traits under both normal and high-temperature conditions, forming a robust basis for genetic research and breeding initiatives. Furthermore, the study revealed that yield-related traits exhibited high heritability, suggesting their potential suitability for marker-assisted selection. We carried out single-nucleotide polymorphism (SNP) genotyping using the genotyping-by-sequencing (GBS) method for a genome-wide association study (GWAS). Overall, 27 marker-trait associations (MTAs) linked to yield-related traits, among which we identified five common MTAs displaying pleiotropic effects after applying a stringent Bonferroni-corrected p-value threshold of <0.05 [-log10(p) > 4.95] using the BLINK (Bayesian-information and linkage-disequilibrium iteratively nested keyway) model. Through an in-depth in silico analysis of these markers against the CDC Frontier v1 reference genome, we discovered that the majority of the SNPs were located at or in proximity to gene-coding regions. We further explored candidate genes situated near these MTAs, shedding light on the molecular mechanisms governing heat stress tolerance and yield enhancement in chickpeas such as indole-3-acetic acid-amido synthetase GH3.1 with GH3 auxin-responsive promoter and pentatricopeptide repeat-containing protein, etc. The harvest index (HI) trait was associated with marker Ca3:37444451 encoding aspartic proteinase ortholog sequence of Oryza sativa subsp. japonica and Medicago truncatula, which is known for contributing to heat stress tolerance. These identified MTAs and associated candidate genes may serve as valuable assets for breeding programs dedicated to tailoring chickpea varieties resilient to heat stress and climate change.

High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut.

BACKGROUND: Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits. RESULTS: Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation. CONCLUSION: In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs.

Designing future peanut: the power of genomics-assisted breeding.

KEY MESSAGE: Integrating GAB methods with high-throughput phenotyping, genome editing, and speed breeding hold great potential in designing future smart peanut cultivars to meet market and food supply demands. Cultivated peanut (Arachis hypogaea L.), a legume crop greatly valued for its nourishing food, cooking oil, and fodder, is extensively grown worldwide. Despite decades of classical breeding efforts, the actual on-farm yield of peanut remains below its potential productivity due to the complicated interplay of genotype, environment, and management factors, as well as their intricate interactions. Integrating modern genomics tools into crop breeding is necessary to fast-track breeding efficiency and rapid progress. When combined with speed breeding methods, this integration can substantially accelerate the breeding process, leading to faster access of improved varieties to farmers. Availability of high-quality reference genomes for wild diploid progenitors and cultivated peanuts has accelerated the process of gene/quantitative locus discovery, developing markers and genotyping assays as well as a few molecular breeding products with improved resistance and oil quality. The use of new breeding tools, e.g., genomic selection, haplotype-based breeding, speed breeding, high-throughput phenotyping, and genome editing, is probable to boost genetic gains in peanut. Moreover, renewed attention to efficient selection and exploitation of targeted genetic resources is also needed to design high-quality and high-yielding peanut cultivars with main adaptation attributes. In this context, the combination of genomics-assisted breeding (GAB), genome editing, and speed breeding hold great potential in designing future improved peanut cultivars to meet market and food supply demands.

Chromosome-level reference genome and resequencing of 322 accessions reveal evolution, genomic imprint and key agronomic traits in adzuki bean.

Adzuki bean (Vigna angularis) is an important legume crop cultivated in over 30 countries worldwide. We developed a high-quality chromosome-level reference genome of adzuki bean cultivar Jingnong6 by combining PacBio Sequel long-read sequencing with short-read and Hi-C technologies. The assembled genome covers 97.8% of the adzuki bean genome with a contig N50 of approximately 16 Mb and a total of 32 738 protein-coding genes. We also generated a comprehensive genome variation map of adzuki bean by whole-genome resequencing (WGRS) of 322 diverse adzuki beans accessions including both wild and cultivated. Furthermore, we have conducted comparative genomics and a genome-wide association study (GWAS) on key agricultural traits to investigate the evolution and domestication. GWAS identified several candidate genes, including VaCycA3;1, VaHB15, VaANR1 and VaBm, that exhibited significant associations with domestication traits. Furthermore, we conducted functional analyses on the roles of VaANR1 and VaBm in regulating seed coat colour. We provided evidence for the highest genetic diversity of wild adzuki (Vigna angularis var. nipponensis) in China with the presence of the most original wild adzuki bean, and the occurrence of domestication process facilitating transition from wild to cultigen. The present study elucidates the genetic basis of adzuki bean domestication traits and provides crucial genomic resources to support future breeding efforts in adzuki bean.

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity.

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

Genome-Wide Mapping of Quantitative Trait Loci for Yield-Attributing Traits of Peanut.

Peanuts (Arachis hypogaea L.) are important high-protein and oil-containing legume crops adapted to arid to semi-arid regions. The yield and quality of peanuts are complex quantitative traits that show high environmental influence. In this study, a recombinant inbred line population (RIL) (Valencia-C × JUG-03) was developed and phenotyped for nine traits under two environments. A genetic map was constructed using 1323 SNP markers spanning a map distance of 2003.13 cM. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified seventeen QTLs for nine traits. Intriguingly, a total of four QTLs, two each for 100-seed weight (HSW) and shelling percentage (SP), showed major and consistent effects, explaining 10.98% to 14.65% phenotypic variation. The major QTLs for HSW and SP harbored genes associated with seed and pod development such as the seed maturation protein-encoding gene, serine-threonine phosphatase gene, TIR-NBS-LRR gene, protein kinase superfamily gene, bHLH transcription factor-encoding gene, isopentyl transferase gene, ethylene-responsive transcription factor-encoding gene and cytochrome P450 superfamily gene. Additionally, the identification of 76 major epistatic QTLs, with PVE ranging from 11.63% to 72.61%, highlighted their significant role in determining the yield- and quality-related traits. The significant G × E interaction revealed the existence of the major role of the environment in determining the phenotype of yield-attributing traits. Notably, the seed maturation protein-coding gene in the vicinity of major QTLs for HSW can be further investigated to develop a diagnostic marker for HSW in peanut breeding. This study provides understanding of the genetic factor governing peanut traits and valuable insights for future breeding efforts aimed at improving yield and quality.

ScRNA-seq reveals dark- and light-induced differentially expressed gene atlases of seedling leaves in Arachis hypogaea L.

Although the regulatory mechanisms of dark and light-induced plant morphogenesis have been broadly investigated, the biological process in peanuts has not been systematically explored on single-cell resolution. Herein, 10 cell clusters were characterized using scRNA-seq-identified marker genes, based on 13 409 and 11 296 single cells from 1-week-old peanut seedling leaves grown under dark and light conditions. 6104 genes and 50 transcription factors (TFs) displayed significant expression patterns in distinct cell clusters, which provided gene resources for profiling dark/light-induced candidate genes. Further pseudo-time trajectory and cell cycle evidence supported that dark repressed the cell division and perturbed normal cell cycle, especially the PORA abundances correlated with 11 TFs highly enriched in mesophyll to restrict the chlorophyllide synthesis. Additionally, light repressed the epidermis cell developmental trajectory extending by inhibiting the growth hormone pathway, and 21 TFs probably contributed to the different genes transcriptional dynamic. Eventually, peanut AHL17 was identified from the profile of differentially expressed TFs, which encoded protein located in the nucleus promoted leaf epidermal cell enlargement when ectopically overexpressed in Arabidopsis through the regulatory phytohormone pathway. Overall, our study presents the different gene atlases in peanut etiolated and green seedlings, providing novel biological insights to elucidate light-induced leaf cell development at the single-cell level.

A genomic variation map provides insights into peanut diversity in China and associations with 28 agronomic traits.

Peanut (Arachis hypogaea L.) is an important allotetraploid oil and food legume crop. China is one of the world's largest peanut producers and consumers. However, genomic variations underlying the migration and divergence of peanuts in China remain unclear. Here we reported a genome-wide variation map based on the resequencing of 390 peanut accessions, suggesting that peanuts might have been introduced into southern and northern China separately, forming two cultivation centers. Selective sweep analysis highlights asymmetric selection between the two subgenomes during peanut improvement. A classical pedigree from South China offers a context for the examination of the impact of artificial selection on peanut genome. Genome-wide association studies identified 22,309 significant associations with 28 agronomic traits, including candidate genes for plant architecture and oil biosynthesis. Our findings shed light on peanut migration and diversity in China and provide valuable genomic resources for peanut improvement.

Multiple strategies, including 6mA methylation, affecting plant alternative splicing in allopolyploid peanut.

Alternative splicing (AS), an important post-transcriptional regulation mechanism in eukaryotes, can significantly increase transcript diversity and contribute to gene expression regulation and many other complicated developmental processes. While plant gene AS events are well described, few studies have investigated the comprehensive regulation machinery of plant AS. Here, we use multi-omics to analyse peanut AS events. Using long-read isoform sequencing, 146 464 full-length non-chimeric transcripts were obtained, resulting in annotation corrections for 1782 genes and the identification of 4653 new loci. Using Iso-Seq RNA sequences, 271 776 unique splice junctions were identified, 82.49% of which were supported by transcriptome data. We characterized 50 977 polyadenylation sites for 23 262 genes, 12 369 of which had alternative polyadenylation sites. AS allows differential regulation of the same gene by miRNAs at the isoform level coupled with polyadenylation. In addition, we identified many long non-coding RNAs and fusion transcripts. There is a suppressed effect of 6mA on AS and gene expression. By analysis of chromatin structures, the genes located in the boundaries of topologically associated domains, proximal chromosomal telomere regions, inter- or intra-chromosomal loops were found to have more unique splice isoforms, higher expression, lower 6mA and more transposable elements (TEs) in their gene bodies than the other genes, indicating that chromatin interaction, 6mA and TEs play important roles in AS and gene expression. These results greatly refine the peanut genome annotation and contribute to the study of gene expression and regulation in peanuts. This work also showed AS is associated with multiple strategies for gene regulation.

Effect of terminal heat stress on osmolyte accumulation and gene expression during grain filling in bread wheat (Triticum aestivum L.).

The grain-filling stage in Triticum aestivum (wheat) is highly vulnerable to increasing temperature as terminal heat stress diminishes grain quality and yield. To examine the mechanism of terminal heat tolerance, we performed the biochemical and gene expression analyses using two heat-tolerant (WH730 and WH1218) and two heat-sensitive (WH711 and WH157) wheat genotypes. We observed a significant increase in total soluble sugar (25%-47%), proline (7%-15%), and glycine betaine (GB) (22%-34%) contents in flag leaf, whereas a decrease in grain-filling duration, 1000-kernel weight (8%-25%), and grain yield per plant (11%-23%) was observed under the late-sown compared to the timely sown. The maximum content of osmolytes, including total soluble sugar, proline, and GB, was observed in heat-tolerant genotypes compared to heat-sensitive genotypes. The expression of 10 heat-responsive genes associated with heat shock proteins (sHsp-1, Hsp17, and HsfA4), flavonoid biosynthesis (F3'-1 and PAL), ß-glucan synthesis (CslF6 and CslH), and xyloglucan metabolism (XTH1, XTH2, and XTH5) was studied in flag leaf exposed to different heat treatments (34, 36, 38, and 40°C) at 15 days after anthesis by quantitative real-time polymerase chain reaction. A significant increase in the relative fold expression of these genes with increasing temperature indicated their involvement in providing heat-stress tolerance. The high differential expression of most of the genes in heat-tolerant genotype "WH730" followed by "WH1218" indicates the high adaptability of these genotypes to heat stress compared to heat-sensitive wheat genotypes. Based on the previous results, "WH730" performed better in terms of maximum osmolyte accumulation, grain yield, and gene expression under heat stress.

Integrated multi-omics analysis reveals drought stress response mechanism in chickpea (Cicer arietinum L.).

Drought is one of the major constraints limiting chickpea productivity. To unravel complex mechanisms regulating drought response in chickpea, we generated transcriptomics, proteomics, and metabolomics datasets from root tissues of four contrasting drought-responsive chickpea genotypes: ICC 4958, JG 11, and JG 11+ (drought-tolerant), and ICC 1882 (drought-sensitive) under control and drought stress conditions. Integration of transcriptomics and proteomics data identified enriched hub proteins encoding isoflavone 4'-O-methyltransferase, UDP-d-glucose/UDP-d-galactose 4-epimerase, and delta-1-pyrroline-5-carboxylate synthetase. These proteins highlighted the involvement of pathways such as antibiotic biosynthesis, galactose metabolism, and isoflavonoid biosynthesis in activating drought stress response mechanisms. Subsequently, the integration of metabolomics data identified six metabolites (fructose, galactose, glucose, myoinositol, galactinol, and raffinose) that showed a significant correlation with galactose metabolism. Integration of root-omics data also revealed some key candidate genes underlying the drought-responsive "QTL-hotspot" region. These results provided key insights into complex molecular mechanisms underlying drought stress response in chickpea.

Advances and opportunities in unraveling cold-tolerance mechanisms in the world's primary staple food crops.

Temperatures below or above optimal growth conditions are among the major stressors affecting productivity, end-use quality, and distribution of key staple crops including rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays L.). Among temperature stresses, cold stress induces cellular changes that cause oxidative stress and slowdown metabolism, limit growth, and ultimately reduce crop productivity. Perception of cold stress by plant cells leads to the activation of cold-responsive transcription factors and downstream genes, which ultimately impart cold tolerance. The response triggered in crops to cold stress includes gene expression/suppression, the accumulation of sugars upon chilling, and signaling molecules, among others. Much of the information on the effects of cold stress on perception, signal transduction, gene expression, and plant metabolism are available in the model plant Arabidopsis but somewhat lacking in major crops. Hence, a complete understanding of the molecular mechanisms by which staple crops respond to cold stress remain largely unknown. Here, we make an effort to elaborate on the molecular mechanisms employed in response to low-temperature stress. We summarize the effects of cold stress on the growth and development of these crops, the mechanism of cold perception, and the role of various sensors and transducers in cold signaling. We discuss the progress in cold tolerance research at the genome, transcriptome, proteome, and metabolome levels and highlight how these findings provide opportunities for designing cold-tolerant crops for the future.

Genomic approaches to enhance adaptive plasticity to cope with soil constraints amidst climate change in wheat.

Climate change is varying the availability of resources, soil physicochemical properties, and rainfall events, which collectively determines soil physical and chemical properties. Soil constraints-acidity (pH < 6), salinity (pH ≤ 8.5), sodicity, and dispersion (pH > 8.5)-are major causes of wheat yield loss in arid and semiarid cropping systems. To cope with changing environments, plants employ adaptive strategies such as phenotypic plasticity, a key multifaceted trait, to promote shifts in phenotypes. Adaptive strategies for constrained soils are complex, determined by key functional traits and genotype × environment × management interactions. The understanding of the molecular basis of stress tolerance is particularly challenging for plasticity traits. Advances in sequencing and high-throughput genomics technologies have identified functional alleles in gene-rich regions, haplotypes, candidate genes, mechanisms, and in silico gene expression profiles at various growth developmental stages. Our review focuses on favorable alleles for enhanced gene expression, quantitative trait loci, and epigenetic regulation of plant responses to soil constraints, including heavy metal stress and nutrient limitations. A strategy is then described for quantitative traits in wheat by investigating significant alleles and functional characterization of variants, followed by gene validation using advanced genomic tools, and marker development for molecular breeding and genome editing. Moreover, the review highlights the progress of gene editing in wheat, multiplex gene editing, and novel alleles for smart control of gene expression. Application of these advanced genomic technologies to enhance plasticity traits along with soil management practices will be an effective tool to build yield, stability, and sustainability on constrained soils in the face of climate change.