Speakers - 2026

Title: Genome-wide dissection of heat tolerance in Pakistani maize germplasm through multi-environment phenotyping and high-density SNP-based association mapping

Abstract

Climate change has substantially intensified the frequency and severity of heat stress, posing a major threat to global maize production. Developing climate-resilient germplasm requires a comprehensive understanding of the genetic mechanisms governing heat tolerance. This study integrates extensive multi-environment phenotyping with genome-wide association analysis to identify genomic regions and candidate genes controlling heat tolerance in the Pakistani maize gene pool. A diverse panel of 300 maize genotypes was assembled from public-sector breeding institutes and research stations across Pakistan and evaluated under normal and heat stress conditions during Spring 2022 and Spring 2023 at two contrasting environments. The trials were conducted using an augmented split-split-plot experimental design, and genotypes were characterized for 12 morphological and 11 physiological traits associated with heat adaptation. Significant effects of environment, year, temperature regime, and genotype were observed, demonstrating strong genotype × environment interactions. Multivariate analyses, including principal component analysis and GGE biplots, identified superior and stable genotypes exhibiting consistent heat tolerance across environments. To elucidate the molecular basis of heat tolerance, all 300 genotypes were subjected to genotyping-by-sequencing (GBS). Sequencing generated an average of 35.6 million reads per genotype, resulting in 17.58 million raw SNPs following alignment to the maize B73 reference genome (version 5). Stringent quality filtering retained 82,450 high-confidence SNPs for downstream analyses. Population structure, discriminant analysis of principal components (DAPC), and phylogenetic analyses classified the germplasm into six genetic groups while revealing varying levels of admixture. Genome-wide association analysis using the FarmCPU model identified 359 significant marker-trait associations for heat-responsive traits. Functional annotation mapped these loci to 87 genomic regions, including coding, intronic, promoter, and intergenic sequences. Gene ontology enrichment identified 27 significant candidate genes enriched in biological processes associated with stress signaling, molecular functions involved in transcriptional regulation and catalytic activity, and cellular components contributing to stress adaptation. Several candidate genes represent promising targets for marker-assisted selection, genomic selection, and genome editing approaches aimed at improving heat tolerance in maize. This work represents one of the most comprehensive genomic investigations of heat tolerance in Pakistani maize germplasm and provides valuable genomic resources for accelerating climate-resilient maize breeding. The identified genomic regions and candidate genes establish a strong foundation for functional validation and precision breeding strategies to enhance maize productivity under rising global temperatures

Key takeaways from Presentation:

• Learn an integrated approach combining multi-environment phenotyping, GBS, and GWAS to dissect heat tolerance in maize.
• Gain insights into the genetic diversity, population structure, and genomic architecture of Pakistani maize germplasm.
• Discover candidate genes and molecular markers for marker-assisted breeding, genomic selection, and genome editing.
• Understand practical applications of genomics for developing climate-resilient maize cultivars.
• Obtain transferable methodologies and genomic resources applicable to maize and other cereal crop improvement programs.