Genomic dissection of stable meta-quantitative trait loci and candidate genes enabling durable disease and insect resistance in maize to safeguard food production.

Mapping quantitative trait loci (QTLs) for plant architecture traits using a high-density genetic linkage map in diploid potato (Solanum chacoense)

Identification of stable and high-yielding maize genotypes using BLUP-based stability and multi-trait selection indices across diverse environments

Maize (Zea mays L.) is one of the most important cereal crops worldwide and serves as a major source of food, feed, and industrial raw material; however, identification of high-yielding and stable maize genotypes across diverse environments is a key objective of maize improvement programs. A total of 60 maize genotypes were evaluated across four environments [summer 2023 (E1), winter 2023 (E2), summer 2024 (E3), and winter 2024 (E4)] in an alpha lattice design with two replications, comprising six incomplete blocks with 10 entries per block. Subsequently, 15 morphological and yield-related traits were assessed to identify superior and stable maize genotypes across environments. A pooled analysis of variance revealed highly significant effects of genotypes, environments, and genotype × environment interaction for all traits. Broad-sense heritability was high for grain yield (92.40%), biological yield (97.10%), cob yield (92.60%), and plant height (99.20%), whereas anthesis silking interval showed low heritability (12.70%), indicating strong environmental influence. Grain yield exhibited strong positive genotypic correlations with cob yield, biological yield, plant height, kernels per ear, ear length, seed index, and ear diameter. Factor analysis under MGIDI identified three factors explaining 76.06% of total variation, representing yield components, partitioning efficiency, and ear morphology traits. Based on 15% selection intensity, nine genotypes were selected with predicted genetic gains ranging from −0.523% for anthesis–silking interval (indicating a desirable reduction in ASI) to 50.6% for grain yield. The highest coincidence index was observed between MGIDI and FAI-BLUP (66.67%). Genotypes G26 and G27 were consistently selected across all indices, indicating superior performance and stability. These genotypes are promising candidates for multi-location evaluation and can serve as potential parents in hybridization programs aimed at improving grain yield and adaptability in maize.

Meta-QTL Analysis Reveals Consensus Genomic Regions and Candidate Genes for Resistance to Sudden Death Syndrome in Soybean

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is one of the most economically important diseases limiting soybean production worldwide. Although numerous quantitative trait loci (QTL) associated with SDS resistance have been reported, inconsistencies among mapping populations, marker systems, and experimental conditions have hindered the identification of robust resistance loci for soybean improvement. In this study, a comprehensive meta-analysis was conducted to integrate published QTL and identify stable consensus genomic regions associated with SDS resistance. After a systematic literature survey and data curation, 153 QTL derived from 14 linkage-mapping studies were analyzed using a custom R-based workflow, resulting in the identification of 23 consensus meta-QTL (MQTL) distributed across 17 chromosomes. Several MQTL, particularly those located on chromosomes 6, 8, 18, and 20, were supported by multiple independent studies and represented major genomic hotspots for SDS resistance. Physical localization and functional annotation of these MQTL identified 217 candidate genes, including genes predicted to be involved in plant defense, signal transduction, transcriptional regulation, and secondary metabolism. Gene Ontology enrichment analysis identified response to salicylic acid as the only biological process that remained significant after FDR correction, whereas Kyoto Encyclopedia of Genes and Genomes pathway analysis did not identify significantly enriched pathways. Independent support using five published genome-wide association studies further supported several MQTL, especially those on chromosomes 6, 18, and 20, thereby increasing confidence in these genomic regions. The identified MQTL and prioritized candidate genes provide potential genomic resources for future marker development, improvement applications, and functional validation aimed at improving soybean resistance to SDS.

Genetic Dissection and Fine-Mapping of QTL for Salinity Tolerance at the Reproductive Stage on Chromosome 2 of Rice Variety Nona Bokra

Soil salinity is a major constraint limiting rice productivity, particularly at the reproductive stage. To elucidate the genetic basis of reproductive stage salinity tolerance, this study validated and fine-mapped quantitative trait loci (QTL) for yield-related traits using a salinity-tolerant line SL506, identified through screening of Nona Bokra–CSSLs in a Koshihikari background. In 2016, the F2 population derived from SL506/Koshihikari was evaluated under long-term salt stress; three QTLs associated with plant dry weight, panicle number, and grain weight were detected on chromosome 2. In 2023, validation analysis using F3 individuals confirmed the presence of these QTLs. Subsequent fine-mapping using F4 near-isogenic lines (NILs) delimited the QTL to a 1.7 Mb interval and high-resolution mapping using an F5 recombinant population progressively refined it to a 473 kb genomic region containing 69 annotated genes. Variant Effect Predictor analysis identified 15 deleterious nonsynonymous variants (SIFT < 0.05) in six candidate genes. Based on annotated gene functions, predicted variant effects, and their membership in stress-related gene families, OsPP2C24, OsFbox102, and OsWAK14 were suggested as the most promising candidate genes underlying qPDW2. These findings provide insights into the genetic basis of reproductive-stage salinity tolerance from valuable resources for the future improvement of salt tolerance and yield stability in rice.

A systems breeding framework integrating pangenomics multiomics phenomics and precision genome editing for reproductive stage drought resilience in rice

Rice (Oryza sativa L.) is highly vulnerable to drought during the reproductive phase, with yield losses exceeding 50% due to spikelet sterility, pollen abortion, and impaired grain filling. Progress through conventional breeding has been constrained by the polygenic nature of drought tolerance and by strong genotype × environment (G × E) interactions. This review proposes a systems breeding strategy integrating five complementary approaches rice pangenomics, genome-wide association studies (GWAS), genomic selection (GS), high-throughput phenomics, and precision genome editing to strengthen drought resilience at the reproductive stage. Structural variants identified through pangenome analyses across diverse Oryza accessions have been implicated in abscisic acid (ABA) signalling, osmolyte biosynthesis, antioxidant defence, and root system architecture pathways central to reproductive-stage drought adaptation. Multi-omics-informed GWAS, combined with co-localisation of eQTLs and protein QTLs in drought-stressed reproductive tissues, highlights high-confidence candidate genes including OsNAC14, OsbZIP23, and DRO1 that help explain the physiological basis of water-deficit adaptation. Incorporating envirotyping data into GS models has been shown to improve predictive accuracy across diverse rainfed environments. Alongside marker-assisted selection, base editing and prime editing enable targeted allelic refinement with minimal off-target effects. We present a proposed tiered candidate prioritisation pipeline that advances loci supported by convergent genomic, transcriptomic, proteomic, and field-level evidence toward practical breeding deployment. Translating these discoveries into climate-resilient varieties will require FAIR data sharing, coordinated phenotyping networks, and multi-environment validation platforms linking genomic discovery to scalable breeding pipelines for drought-resistant, high-yielding rice in rainfed systems.

Multi-Environment Multi-Locus Association Mapping Reveals Genomic Regions for Drought-Related Traits in Tropical Maize.

Maize grain yield is frequently constrained by water scarcity, particularly in tropical regions characterized by irregular rainfall patterns. Dissecting the genetic basis of drought-related traits remains challenging because their expression is strongly influenced by environmental conditions. In this study, we applied a multi-environment multi-locus genome-wide association study (MEML-GWAS) to identify genomic regions associated with drought-related traits in tropical maize. The association panel comprised 190 inbred lines from the Embrapa breeding program, which were genotyped with 500,108 GBS-derived SNPs, and crossed with two tester lines. Phenotypic data corresponded to the performance of the testcross hybrids, divided in Dent and Flint heterotic groups, evaluated across two years at two locations in Brazil under well-watered and water-stressed conditions. Traits analyzed included grain yield, anthesis-silking interval, female and male flowering time, and plant and ear height. Drought stress reduced grain yield by approximately 50% and increased the anthesis-silking interval by about two days. A total of 179 significant SNP-trait associations were detected, of which 166 showed significant SNP-by-environment interaction effects, while 13 displayed stable effects across environments. Several associations were detected specifically under water-stressed conditions, highlighting genomic regions potentially involved in drought adaptation. Functional annotation revealed candidate genes previously implicated in abiotic stress responses, including ZmTIP1, which encodes an S-acyltransferase regulating root hair development and drought tolerance. Among the novel candidate genes, GRMZM2G159125, encoding a phospholipase D, emerged as a particularly promising candidate due to its strong association with grain yield and its role in membrane lipid signaling pathways related to stress responses. Although a few associations overlapped genomic regions previously reported for drought tolerance in maize, most loci represent potentially novel genetic factors that may contribute to improving drought resilience in tropical maize breeding programs.