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PubMed2025

Combining QTL mapping and RNA-Seq reveals candidate genes controlling flag leaf width in foxtail millet.

BACKGROUND: The flag leaf, a crucial component of plant architecture, significantly influences final grain yield in crops, including foxtail millet (Setaria italica L.). Optimizing flag leaf size is considered an effective strategy for enhancing grain yield potential under higher planting densities. However, the genetic mechanism underlying flag leaf size, particularly flag leaf width (FLW), remains largely unknown under varying planting densities in foxtail millet. RESULTS: An FLW phenotype variation analysis was conducted across multiple planting densities using a recombinant inbred line (RIL) population derived from Heizhigu (narrow leaf) and Changnong 35 (wide leaf). Based on a high-density genetic map with 3795 Bin markers, 11 flag leaf width (FLW) QTLs were identified on chromosomes 3, 5, and 6, explaining 2.35%-36.06%. Among these, qFLW5-2 was a major QTL, detected consistently across 3 environments and explaining a large proportion of FLW variation. The QTL was further validated with 9 InDel markers with its candidate region across different planting densities. Moreover, RNA-seq revealed 2,293 and 2,338 differentially expressed genes (DEGs) between biparents at heading stage and grain filling stage, respectively. There were 11 and 9 DEGs within the location range of qFLW5-2 among 2 comparison groups (HZG-H_vs_CN35-H and HZG-G_vs_CN35-G). Combining QTL mapping and RNA-seq, we speculated that Seita.5g134600 (encoding an auxin responsive protein Aux/IAA) and Seita.5G123900 (encoding a cytochrome P450 family protein) as key candidate genes for qFLW5-2. Furthermore, variation analysis confirmed that the lines or germplasm with Seita.5G1346005UTR277+ allele, both within the RIL population and natural populations, exhibited significantly wider leaves than those with Seita.5G1346005UTR277- allele. These findings advance our understanding of the genetic and molecular regulatory mechanisms governing flag leaf growth. CONCLUSIONS: This study elucidates genetic and molecular mechanism regulating flag leaf growth and development in foxtail millet. The results provide a theoretical foundation for improving plant architecture and facilitating molecular marker-assisted breeding in this crop.

Quantitative Trait Loci↗

PubMed2026

Proinsulin regulators identified with CRISPR screen and in vivo mouse QTL mapping.

Altered proinsulin levels in β-cells and bloodstream are hallmarks of diabetes and other diseases, but our knowledge about the proinsulin regulators remains limited. Here we perform a genome-wide CRISPR screen to identify 84 proinsulin regulators that alter intracellular proinsulin/insulin ratio in a mouse β-cell line. The proinsulin regulators are distinct from the insulin regulators from a previous orthogonal CRISPR screen. Functional annotation of the proinsulin regulators highlights Golgi as the primary organelle for proinsulin storage and regulation. Trafficking towards the Golgi increases the intra-cellular proinsulin/insulin ratio, while trafficking away from the Golgi, including exocytosis and Golgi-to-ER retrograde transport, decreases the intracellular proinsulin levels. We also map mouse quantitative trait loci (QTLs) associated with plasma proinsulin levels and use the CRISPR screen results to pinpoint the causal genes within the QTL loci. Interestingly, protein disulfide isomerase Pdia6 is the strongest hit from both CRISPR screen and the in vivo QTL mapping. Knocking down Pdia6 significantly reduce proinsulin accumulation in Golgi and secretory granules. Intriguingly, Pdia6-depletion in both human and mouse β-cells does not affect the folding status of proinsulin but causes significantly impaired proinsulin production through a UPR-independent mechanism. Taken together, our genetic profiles provide mechanistic insights into the regulation of proinsulin/insulin homeostasis.

Animals↗

PubMed2024

QTL mapping for seed vigor-related traits under artificial aging in common wheat in two introgression line (IL) populations.

BACKGROUND: Seed vigor recognized as a quantitative trait is of particular importance for agricultural production. However, limited knowledge is available for understanding genetic basis of wheat seed vigor. METHODS: The aim of this study was to identify quantitative trait loci (QTL) responsible for 10 seed vigor-related traits representing multiple aspects of seed-vigor dynamics during artificial aging with 6 different treatment times (0, 24, 36, 48, 60, and 72 h) under controlled conditions (48 °C, 95% humidity, and dark). The mapping populations were two wheat introgression lines (IL-1 and IL-2) derived from recipient parent (Lumai 14) and donor parent (Shaanhan 8675 or Jing 411). RESULTS: A total of 26 additive QTLs and 72 pairs of epistatic QTLs were detected for wheat seed-vigor traits. Importantly, chromosomes 1B and 7B contained several co-located QTLs, and chromosome 2A had a QTL-rich region near the marker Xwmc667, indicating that these QTLs may affect wheat seed vigor with pleiotropic effects. Furthermore, several possible consistent QTLs (hot-spot regions) were examined by comparison analysis of QTLs detected in this study and reported previously. Finally, a set of candidate genes for wheat seed vigor were predicted to be involved in transcription regulation, carbohydrate and lipid metabolism. CONCLUSION: The present findings lay new insights into the mechanism underlying wheat seed vigor, providing valuable information for wheat genetic improvement especially marker-assisted breeding to increase seed vigor and consequently achieve high grain yield despite of further investigation required.

Triticum↗

PubMed2025

The genetic basis of chloride exclusion in grapevines.

Mediterranean regions are among the most important areas for global grape production, characterized by dry climates and frequent challenges associated with soil salinity. In these environments, chloride toxicity is a major factor limiting vine growth and fruit quality. Despite the critical role of chloride exclusion in salinity tolerance, the genetic mechanisms underlying this trait remain poorly understood. In this study, we analyzed natural variation in chloride exclusion using a diverse panel of 335 accessions representing 18 wild and cultivated Vitis species. This panel, comprising accessions from the southwestern United States and Mexico, captures a broad range of evolutionary adaptations to abiotic stress and provides a valuable genetic resource for breeding efforts aimed at introducing novel traits. Using genome-wide association and quantitative trait loci (QTL) mapping, we identified a major QTL on chromosome 8, now designated qClEx8.1, containing candidate genes encoding cation/H⁺ exchangers (CHXs), which are involved in ion transport and homeostasis. To validate these findings, we analyzed a mapping population derived from Vitis acerifolia longii 9018 and the commercial rootstock GRN3, confirming the chromosome 8 locus as a major determinant of chloride exclusion. Structural variant analysis revealed nonsynonymous substitutions within CHX genes that may influence protein function and salinity tolerance. Additionally, we discovered a novel QTL on chromosome 19 enriched with G-type lectin S-receptor-like serine/threonine-protein kinases, known regulators of stress signaling. By integrating phenotypic and genomic data across a diverse Vitis collection, this study advances our understanding of the genetic architecture underlying chloride exclusion and highlights candidate genes for breeding salt-tolerant rootstocks.

Vitis↗

PubMed2025

Foliar disease resistance phenomics of fungal pathogens: image-based approaches for mapping quantitative resistance in cereal germplasm.

Host plant resistance is the most effective and environmentally sustainable means of reducing yield losses caused by fungal foliar pathogens of cereal species. Cereal genebank collections hold diverse pools of potentially underutilized disease resistance alleles, and cereal genomic resources are well advanced due to large-scale sequencing and genotyping efforts. Genome-Wide Association Studies (GWAS) have emerged as the predominant association genetics technique to initially discover novel disease resistance loci or alleles in these diverse collections. Traditional disease resistance phenotyping methods are reliant on visual estimation of disease symptom severity and have successfully supported genetic mapping studies either via GWAS or QTL mapping in biparental populations facilitating both marker development and gene cloning efforts. Due to foliar pathogens having a high capacity to evolve, there is a need to pyramid disease resistance genes with diverse mechanisms for durable control. Resistance expressed as a quantitative trait, known as quantitative resistance (QR), is hypothesized to be more durable, unlike major R-gene resistance that is race-specific and can be vulnerable to breaking down without gene stewardship. However, assessing QR visually is challenging, particularly when complicated by complex genotype × environment (G × E) effects in the field. High-throughput image-based phenotyping provides accurate and unbiased data that can support foliar disease resistance screening efforts of genebank collections using GWAS. In this review, we discuss image-based disease phenotyping based on macroscopic (visible symptoms) and microscopic features during the host-pathogen interaction. Quantitative image analysis approaches using conventional and artificial intelligence (AI) algorithms are also discussed.

Disease Resistance↗

PubMed2026

Genetic dissection of cardiac iron regulation using transcriptome network analysis and systems genetics in BXD mice.

Cardiac iron homeostasis is essential for myocardial energy metabolism and contractile function, yet the genetic and molecular mechanisms governing iron levels within the heart remain poorly understood. We used a systems genetics approach to dissect the transcriptional regulation of cardiac iron homeostasis. Myocardial iron level varies substantially across BXD strains (40-112 μg/g) and is under heritable genetic control (H2 = 0.38). Elevated cardiac iron is associated with reduced ventricular mass, increased ventricular ectopy, and prolonged atrioventricular conduction in the BXD population. Weighted gene co-expression network analysis of the BXD heart transcriptome identified a co-expression module that was significantly and negatively correlated with cardiac iron levels in both young and old BXD mice and enriched for pathways related to metabolic regulation, cyclic AMP (cAMP) signaling, circadian entrainment, and cardiovascular physiology. The module showed substantial overlap with a curated cardiac iron gene set, and cross-species enrichment analysis confirmed its conservation in human cardiomyopathy differentially expressed genes (enrichment ratio = 1.49; false discovery rate [FDR] = 0.0342). Quantitative trait locus (QTL) mapping of the first principal component of the overlapping module iron genes (n = 38), corroborated by individual gene mapping, identified trans-eQTL hotspots on multiple chromosomes, implicating Fcho2, Gcc2, and Rmdn1 as candidate upstream regulators operating through sequential steps of intracellular iron trafficking. Together, these findings establish a systems-level map of cardiac iron gene regulation, identify candidate genetic regulators, and provide a molecular framework linking disruption of iron-related transcriptional networks to structural and electrical cardiac dysfunction with implications for iron-related heart diseases.

BXD mouse population↗

PubMed2025

Indel mutation in transcription factor PabHLH2 regulates amygdalin accumulation and kernel bitterness in apricot.

Amygdalin, the phytochemical responsible for the characteristic bitterness of apricot (Prunus armeniaca L.) kernels, also exhibits significant bioactive properties and therapeutic potential. Genetic regulation of amygdalin content is therefore a key objective in apricot breeding programs aimed at quality improvement. In this study, we conducted quantitative trait loci (QTL) mapping to uncover the genetic basis of sweet-bitter differentiation in apricot kernels. We identified a 15-bp insertion/deletion (indel) polymorphism strongly related to kernel bitterness, with marker validation achieving 100% concordance across 601 apricot germplasm accessions. Notably, this polymorphic site is located within the helix-loop-helix (HLH) domain of the basic HLH (bHLH) transcription factor PabHLH2. Protein interaction analyses revealed that the 15-bp deletion variant impaired dimerization capacity, reducing transcriptional activation of downstream targets. Using yeast one-hybrid screening and dual-luciferase reporter assays, we identified PaCYP71AN24 and PaCYP79D16 as direct transcriptional targets of PabHLH2. Functional characterization further indicated that the PabHLH2a variant (harboring the 15-bp insertion) significantly enhanced the promoter activity of these cytochrome P450 genes compared with the deletion variant. Transient overexpression and silencing experiments in apricot kernels further confirmed that the 15-bp insertion positively regulates both PaCYP71AN24/PaCYP79D16 expression and prunasin accumulation, the immediate biosynthetic precursor of amygdalin. Overall, these findings provide mechanistic insights into the allelic variation underlying kernel bitterness and delineate the molecular cascade of amygdalin biosynthesis. The identified molecular markers and functional characterization establish a basis for marker-assisted breeding of low-amygdalin apricot cultivars, supporting the dual-purpose utilization of kernels in food and pharmaceutical industries.

Amygdalin↗

PubMed2026

Haplotype-specific expression of a terpene synthase underlies linalool variation in the grapevine cultivar Riesling.

Grapevine cultivars vary widely in monoterpenoid content, yet the genetic and regulatory mechanisms underlying this variation remain poorly characterized beyond highly aromatic Muscat types. We profiled free volatiles and monoterpenoid glycosides in a Riesling × Cabernet Sauvignon F1 mapping population, revealing extensive variation and transgressive segregation consistent with multigenic control. QTL mapping identified 70 significant loci associated with 48 volatile compounds and monoterpene glycosides, including two major QTLs explaining 33.6% and 33.4% of phenotypic variance in (3S)-linalool accumulation. Integration of haplotype-resolved transcriptomics with metabolite data, enabled by a chromosome-scale diploid Riesling genome assembly, resolved a (3S)-linalool/nerolidol synthase cluster on chromosome 10 and identified VviTPS54 as the strongest candidate underlying linalool variation. VviTPS54 exhibited haplotype-specific expression strongly correlated with (3S)-linalool accumulation across genotypes, while no QTL was detected at the 1-deoxy-D-xylulose-5-phosphate synthase 1 (VviDXS1) locus previously identified in Muscat cultivars. In addition, VviDXS1 expression was not correlated with terpene levels, indicating that regulatory variation within terpene synthase clusters, rather than methylerythritol phosphate (MEP) pathway flux, drives monoterpenoid composition in this population. These results establish regulatory variation of terpene synthases as a key mechanism underlying monoterpenoid diversity in grapevine and demonstrate that resolving such variation requires haplotype-phased genome assemblies coupled with haplotype-resolved transcriptomics to detect allele-specific expression differences at complex, heterozygous loci.

Grapevine↗

PubMed2026

Identification of Novel Sources and Genetic Mapping for Bacterial Leaf Streak Resistance in a Geographically Diverse Panel of Wheat.

Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa (Xtu), has recently emerged as a significant threat to wheat production in the Northern Great Plains region of the United States. Deploying resistant cultivars is an economical and practical method of controlling BLS. To identify novel sources of BLS resistance, we screened a set of 355 bread wheat landraces and cultivars representing global diversity for their response to BLS. A wide distribution of seedling responses against BLS was observed, with most genotypes displaying a moderately to highly susceptible response. Notably, we identified 5 resistant and 33 moderately resistant responses. A high-resolution genome-wide association study using 302,524 high-quality single-nucleotide polymorphisms (SNPs) identified 10 significant marker-trait associations (MTAs) on chromosomes 1A, 1D, 3B, 4A, and 5A corresponding to unique genomic regions associated with BLS resistance. Compared with previous studies, four of these genomic regions are likely novel. Of these, MTA 'scaffold15531_2782724' associated with q5A.1 was highly significant (-log10P = 9.39) and exhibited the highest SNP effect (0.35). An association on chromosome 3B validated a previously identified 3B quantitative trait locus (QTL) mapped at approximately 6 Mbp in the hard red spring wheat cultivar 'Boost', and the high-resolution mapping from our study further refined the interval for this QTL. Furthermore, the narrow haplotype blocks reported in this study could be valuable for fine mapping of important regions. The novel resistant sources, along with identified genomic loci and corresponding SNP markers from this study, would be helpful for wheat-breeding programs to enhance BLS resistance.[Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

BLS↗

PubMed2026

Co-regulation of HIV control and cytomegalovirus pp65-specific IL-1β and TNF-α responses by genetic variants in the MHC region.

The spontaneous control of HIV infection in the absence of antiretroviral therapy, termed HIV control, is associated with genetic variation in the Major Histocompatibility Complex (MHC) locus. These variants are known to influence the immune response to HIV itself. However, people living with HIV are often co-infected with other pathogens that can also elicit immune responses, which might also be regulated by these variants. Here, we assessed whether genetic variants associated with HIV control influence cytokine responses to various co-pathogens. HIV-control-associated single nucleotide polymorphisms (SNPs) were enriched among variants regulating TNF-α and IL-1β production upon CMV pp65 peptide pool stimulation. The top enriched SNPs, rs1128175-A and rs2853971-A, were linked to lower odds of HIV control and increased cytokine responses to CMV. These SNPs were in linkage disequilibrium (LD) with classical HLA alleles HLA-B*07:02 and HLA-C*07:02. Intracellular cytokine staining showed CMV serostatus-dependent production of TNF-α by monocytes and CD8 T cells. The rs1128175-A/rs2853971-A/HLA-B*07:02/HLA-C*07:02 haplotype was associated with increased IFN-γ production by CD8 T cells upon CMV pp65 peptide pool stimulation, indicating an effect on memory responses. Quantitative trait locus (QTL) mapping showed that rs1128175 and rs2853971 influence HLA-B and HLA-C expression, DNA methylation levels and cell-type-specific cis-effects on chromatin accessibility, as well as CD8 T cell subset abundance. These QTL associations suggest that variants associated with poor HIV control are linked to heightened pro-inflammatory responses to CMV pp65 through effects on antigen presentation, epigenetic modifications, gene expression and immune cell repertoire, potentially negatively affecting HIV control status.

Humans↗

PubMed2025

Automated chromatin profiling with spa-ChIP-seq uncovers the impacts of condition variations.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to study the genomic localization of DNA-associated proteins. However, conventional protocols include multiple manual steps that can introduce inconsistency and limit scalability, thereby restricting the inclusion of appropriate replicates and controls. Although the introduction of liquid handling platforms has improved reproducibility, most existing efforts have automated only a subset of the workflow, and extending automation to efficiently map non-histone proteins, such as chromatin regulators, remains challenging. Here, we present a fully automated implementation of our previously developed single-pot ChIP-seq protocol (Texari et al. 2021), named spa-ChIP-seq, which enables scalable processing of 8 to 96 ChIP-seq samples from crosslinked cells to sequencing-ready library in approximately three days with an estimated cost of $70 per sample. Benchmarking spa-ChIP-seq against manual ChIP-seq performed in parallel demonstrates comparable signal-to-noise ratio between the two workflows. Using spa-ChIP-seq, we systematically evaluate multiple parameters including shearing and crosslinking conditions, buffer compositions, and the ratio of antibody to cell-number. We find, for the first time to our knowledge, that weaker genomic localization signals are sensitive to changing the antibody to cell-number ratio, whereas the stronger signals remain unaffected. This finding underscores the importance of maintaining consistent antibody-to-cell-number ratio for comparative studies, such as treatment responses or chromatin-QTL mapping. The spa-ChIP-seq protocol is publicly available, including deck setups, operational parameters, and scripts. We envision that this robust, cost-efficient protocol will facilitate high-throughput, reproducible ChIP-seq analyses, supporting large-scale studies of antibody validation, compound screening, population genomics, and diagnostic frameworks.

Journal Article↗

PubMed2026

Integrated analysis uncovers exogenous induction and molecular regulation of erinacine A accumulation in Hericium erinaceus.

Erinacine A, a cyathane-type diterpenoid mainly from Hericium erinaceus mycelia, exhibits prominent neurotrophic and neuroprotective activities, making it a promising candidate for managing neurodegenerative diseases. However, its low abundance and unclear genetic regulatory mechanisms hinder its application as a nutraceutical. This study aimed to decipher its regulatory mechanisms and enhance production. Four exogenous inducers were screened, with salicylic acid (SA) and ergosterol (ERG) significantly increasing erinacine A content by 62.21% and 146.70% at 20 days, respectively. Transcriptome and WGCNA of inducer-treated sample identified darkorange and magenta modules associated with erinacine A biosynthesis, with the eri gene cluster enriched in the darkorange module and eriG and eriF as hub genes. Forward genetic analysis via QTL mapping of the HeD127 dikaryon population revealed significant phenotypic variation in erinacine A content (0.341-13.085 mg/g) and identified two loci (erA-1 and erA-2) explaining 18.63% of phenotypic variation. Integrating these forward and reverse genetic analyses revealed that salicylic acid and ergosterol synergistically regulate core carbon metabolic pathways to augment acetyl-CoA supply for the mevalonate pathway, suppressed competitive metabolism, enhanced diterpene skeleton construction and structural modification. These results deepen our understanding of the genetic and molecular basis governing accumulation of erinacine A, and facilitate its application in neuroprotective pharmaceuticals.

Diterpenes↗

PubMed2025

Identifying canopy wilting QTLs and evaluating remote sensing approaches for selecting drought-tolerant soybean.

Drought is the most damaging abiotic stress for soybean yield; cultivars with improved drought tolerance are needed to sustain and increase crop production. PI 603535 previously was identified as an ultra-slow canopy wilting (CW) line in a genome-wide association study but the quantitative trait loci (QTLs) underlying this phenotype have not been determined. In this study, a recombinant inbred line (RIL) population derived from Benning × PI 603535 was evaluated for three years under rain-fed conditions. CW was rated following extended periods of drought when CW variation was present. Aerial multispectral and thermal imagery was also captured in conjunction with visual ratings to explore the feasibility of implementing remote sensing to improve the efficiency and objectivity of drought evaluations. The normalized difference vegetation index (NDVI) and green-based NDVI (GNDVI) exhibited strong, significant correlations (|r|= 0.42-0.44) with CW across years. CW scores and the remote sensing traits were used as phenotypes for QTL mapping. Seven CW QTLs were identified across six chromosomes in the combined analysis, with NDVI and GNDVI QTLs generally colocalizing with the CW QTLs with the highest percentage of variation explained (PVE). The QTLs were not consistently identified among individual years, highlighting the complex genetics and gene expression of drought tolerance. The instability and low additive effect estimates of individual QTLs imply challenges of improving drought tolerance through the selection of a few QTLs. However, the slow CW RILs developed in this study can serve as valuable breeding stocks for future drought improvement breeding efforts and genetic studies.

Quantitative Trait Loci↗

PubMed2026

Esketamine multi-omic biomarker evaluation in major depressive disorder (EMBER-MDD): concept, objectives and methodologies of a non-clinical investigator-initiated study.

Treatment resistance (TR) in major depressive disorder (MDD) affects a substantial minority of patients and is hard to recognize early, delaying intensified care. The Esketamine multi-omic biomarker evaluation in MDD (EMBER-MDD) is a non-interventional, investigator-initiated, in-vitro study within the EU Psych-STRATA programme, analyzing biospecimens collected in the randomized INTENSIFY study and the mirror OBS-TR cohort after participants complete treatment. EMBER-MDD aims to discover individual-omic and integrated multi-omic (hypothesis-free) biomarkers and signatures associated with TR risk, and molecular correlates of clinical response to esketamine nasal spray versus treatment as usual (TAU). Biomaterials will derive from approximately 420 adults with MDD (estimated n = 210 esketamine; n = 210 TAU) and include whole blood, RNA-stabilized whole blood, plasma and serum, sampled at baseline and, when feasible, during and after treatment (up to ~ 5,040 aliquots stored at - 80 °C). Genomics will use baseline DNA genotyping on Illumina Infinium GSA v3.0+MD arrays; epigenomics will profile genome-wide DNA methylation across time points using MethylationEPIC v2.0; transcriptomics will employ mRNA-seq (NovaSeq X/ X Plus); and proteomics/ metabolomics will be generated using high-throughput Olink and/ or Biocrates platforms. Each layer will undergo state-of-the-art preprocessing and analyses (e.g., GWAS/ PRS, EWAS, differential expression, WGCNA, pathway and network analyses), followed by integrative strategies including QTL mapping (meQTL/ eQTL/ pQTL/ mQTL) and intermediate-fusion machine learning with nested cross-validation, explainable AI (SHAP/ LIME) and treatment-effect modelling. All outputs are research-only and will not support individual efficacy, tolerability, or clinical decision-making. The study will deliver robust biosignatures and mechanistic hypotheses to guide future validation and inform stratified, molecularly guided intervention strategies in subsequent prospective trials. Trial registration number: 2023-506617-21-00 and 2025-178-f-S.

Humans↗

PubMed2026

Holistic approaches for improvement of maize resistance against lodging stress: current status and future perspective.

Lodging is a major constraint in maize production, causing significant yield losses, reduced grain quality, and harvesting inefficiencies, thereby posing a serious challenge to global food security and climate-resilient agriculture. This review synthesizes current knowledge on the genetic, physiological, and agronomic determinants of maize lodging resistance and evaluates holistic strategies for improving tolerance to lodging stress. Recent advances in quantitative trait locus (QTL) mapping, genome-wide association studies (GWAS), functional gene characterization, genome editing, high-throughput phenotyping, and precision agronomy have provided powerful tools to enhance stalk biomechanics, root anchorage, and adaptive plant architecture. Integrating genomic discovery with advanced phenomics and optimized agronomic management offers a scalable framework for accelerating the development of high-yielding, lodging-resilient maize cultivars. However, critical gaps remain in understanding the genetic coordination between stalk strength and root system architecture, integrating multi-omics approaches to unravel regulatory networks, validating genome-editing interventions across diverse agro-ecologies, and developing environment-responsive predictive breeding models and cost-effective phenotyping tools, particularly for stress-prone regions. Addressing these challenges through coordinated multi-environment trials and integrative molecular-agronomic strategies will facilitate the translation of genomic discoveries into climate-resilient, high-performing maize cultivars. By consolidating molecular insights with applied breeding and management practices, this review provides a comprehensive framework that guides researchers in designing genome-informed and field-validated approaches to improve maize resistance to lodging stress and support sustainable crop production systems.

Zea mays↗

PubMed2026

Integrating genomics, multi-omics, CRISPR and speed breeding for stress-resilient vegetable legume improvement.

Vegetable legumes are nutritionally and ecologically important crops. However, their genetic improvement has not kept pace with the increasing challenges posed by climate change due to the polygenic nature of stress tolerance, narrow genetic diversity, and the persistent gap between molecular discoveries and field-level cultivar development. Although recent reviews have examined individual genomic tools or specific stress responses, a comprehensive synthesis integrating genomics-assisted breeding, multi-omics technologies, genome editing, and speed breeding within a unified crop improvement framework has been lacking. This review addresses that gap by critically evaluating how these complementary approaches can accelerate the development of stress-resilient vegetable legumes, including pea, common bean, cowpea, faba bean, cluster bean, yard-long bean, and hyacinth bean. This review synthesizes advances in QTL mapping, genome-wide association studies, transcriptomics, metabolomics, and CRISPR-based functional genomics that have identified key regulators and pathways underlying resistance to major biotic and abiotic stresses. Rather than considering these technologies independently, the review emphasizes their convergence into a systems-level breeding framework integrating genomic discovery, functional validation, predictive breeding, and accelerated generation advancement to improve breeding efficiency. Speed breeding, enabling up to seven to eight generations annually under optimized controlled-environment experimental conditions in cowpea, is discussed as a complementary strategy with genomic selection and genome editing. The review further identifies major translational bottlenecks, including transformation recalcitrance, limited genomic resources for underutilized vegetable legumes, inadequate multi-environment validation, and fragmented omics integration, and presents an integrated systems-breeding framework to bridge the gap between gene discovery and cultivar development.

Fabaceae↗

PubMed2026

Molecular mechanisms underlying low glycemic index in rice: Insights from Indian landrace diversity.

The rising prevalence of diabetes mellitus, especially among populations with high rice consumption, underscores the need for functional staple crops with a low glycemic index (GI). This review examines the molecular and genetic factors influencing low-GI traits in rice, highlighting the importance of diversity within Indian landraces. Traditional cultivars like Mappillai Samba, Karuppu Kavuni and Kattuyanam contains high level of Resistant starch, dietary fiber and bioactive phytochemicals. The Waxy (Wx) gene, which codes for granule-bound starch synthase I (GBSSI), is very important for controlling the production of amylose. For example, functional alleles like Wxa and Wxlv are linked to higher amylose levels and lower starch digestibility. Moreover, secondary metabolites, such as anthocyanins and phytosterols like stigmasterol, play a role in regulating blood sugar levels by stopping the activities of α-amylase and α-glucosidase. Interactions within the starch-dietary matrix, including starch-protein, starch-lipid, and starch-polyphenol complexes, further influence enzymatic hydrolysis and glucose release kinetics. Recent advancements in genomics, encompassing QTL mapping and gene editing techniques, offer innovative prospects for the creation of biofortified, low-GI rice cultivars. The integration of these molecular insights into rice breeding programs can facilitate the development of low-glycemic, nutritionally enhanced rice cultivars that contribute to improved metabolic health and food security.

Oryza↗

PubMed2026

Genomic Insights Into Heterosis: Dominance or Additive × Additive Interaction?

Heterosis was documented in the 18th century, but its biological basis has been debated since. The theoretical framework proposed by Hill, and adapted by Lynch, is based on two central parameters: admixed composition (S), and the heterozygosity (H). Using genomic information, it is now possible to estimate independently the individual realized Si and Hi. In this research, a methodology for estimating the contribution of dominance and additive × additive effects to heterosis is proposed. This approach would be especially relevant in cases where there is insufficient phenotypic information available, or an adequate genetic group experimental design, common in humans, wild species and other admixed populations. We also provide theoretical arguments highlighting the enhanced precision of the estimations of heterosis parameters through this method. Furthermore, we exemplify this procedure by analysing data from an experimental F2 pig population, which was initially designed for QTL mapping. Notably, all animals in this population were genotyped (including F1 and parental breeds), but phenotypic information was only available for F2 individuals and included 13 traits related to growth, fat deposition, carcass characteristics and meat quality. Significant additive effects (p < 0.05) were detected for longissimus muscle area and carcass temperature, suggesting complementary additive effects for these traits. Significant dominance and additive × additive effects were also detected for birth weight and carcass length, respectively (p < 0.05), indicating that heterosis for these traits is primarily attributable to dominance and additive × additive interactions. These results demonstrate that the proposed methodology can successfully estimate the genetic components underlying heterosis and underscores the utility of this approach in situations where we possess genomic data but limited phenotypic data.

SNP↗