Genetic gains in tropical maize hybrids across moisture regimes with multi-trait-based index selection

Unpredictable weather vagaries in the Asian tropics often increase the risk of a series of abiotic stresses in maize-growing areas, hindering the efforts to reach the projected demands. Breeding climate-resilient maize hybrids with a cross-tolerance to drought and waterlogging is necessary yet challenging because of the presence of genotype-by-environment interaction (GEI) and the lack of an efficient multi-trait-based selection technique. The present study aimed at estimating the variance components, genetic parameters, inter-trait relations, and expected selection gains (SGs) across the soil moisture regimes through genotype selection obtained based on the novel multi-trait genotype–ideotype distance index (MGIDI) for a set of 75 tropical pre-released maize hybrids. Twelve traits including grain yield and other secondary characteristics for experimental maize hybrids were studied at two locations. Positive and negative SGs were estimated across moisture regimes, including drought, waterlogging, and optimal moisture conditions. Hybrid, moisture condition, and hybrid-by-moisture condition interaction effects were significant (p ≤ 0.001) for most of the traits studied. Eleven genotypes were selected in each moisture condition through MGIDI by assuming 15% selection intensity where two hybrids, viz., ZH161289 and ZH161303, were found to be common across all the moisture regimes, indicating their moisture stress resilience, a unique potential for broader adaptation in rainfed stress-vulnerable ecologies. The selected hybrids showed desired genetic gains such as positive gains for grain yield (almost 11% in optimal and drought; 22% in waterlogging) and negative gains in flowering traits. The view on strengths and weaknesses as depicted by the MGIDI assists the breeders to develop maize hybrids with desired traits, such as grain yield and other yield contributors under specific stress conditions. The MGIDI would be a robust and easy-to-handle multi-trait selection process under various test environments with minimal multicollinearity issues. It was found to be a powerful tool in developing better selection strategies and optimizing the breeding scheme, thus contributing to the development of climate-resilient maize hybrids

Genomic-regions associated with cold stress tolerance in Asia-adapted tropical maize germplasm

Maize is gaining impetus in non-traditional and non-conventional seasons such as off-season, primarily due to higher demand and economic returns. Maize varieties directed for growing in the winter season of South Asia must have cold resilience as an important trait due to the low prevailing temperatures and frequent cold snaps observed during this season in most parts of the lowland tropics of Asia. The current study involved screening of a panel of advanced tropically adapted maize lines to cold stress during vegetative and flowering stage under field conditions. A suite of significant genomic loci (28) associated with grain yield along and agronomic traits such as flowering (15) and plant height (6) under cold stress environments. The haplotype regression revealed 6 significant haplotype blocks for grain yield under cold stress across the test environments. Haplotype blocks particularly on chromosomes 5 (bin5.07), 6 (bin6.02), and 9 (9.03) co-located to regions/bins that have been identified to contain candidate genes involved in membrane transport system that would provide essential tolerance to the plant. The regions on chromosome 1 (bin1.04), 2 (bin 2.07), 3 (bin 3.05–3.06), 5 (bin5.03), 8 (bin8.05–8.06) also harboured significant SNPs for the other agronomic traits. In addition, the study also looked at the plausibility of identifying tropically adapted maize lines from the working germplasm with cold resilience across growth stages and identified four lines that could be used as breeding starts in the tropical maize breeding pipelines

Elucidating molecular diversity and grouping of Indian maize (Zea mays L.) inbred lines using SNP markers

Information on genetic diversity and population structure in maize breeding lines can assist in selecting genetic resources and managing genetic variation in breeding programs. The ability to find ample single nucleotide polymorphisms in crops has recently been made possible by breakthroughs in sequencing technology. The present work is focused on the genetic diversity, population structure and clustering of 56 Indian maize inbreds using 1166 informative SNP markers. The inbreds were collected from eight different geographic locations across India. The average polymorphism information content, minor allele frequency and observed heterozygosity of the germplasm were 0.27, 0.25, and 0.10, respectively. The inbred lines were resolved into more meaningful groups based on the Bayesian structure model, Principal co-ordinate analysis, Neighbor-joining and Unweighted pair group with arithmetic mean clustering methods with slight variations in size and number. Inbreds maintained at the same geographical location were distributed into different clusters suggesting that classification based on geographical regions is ineffective. Additionally, information obtained from the study might be beneficial for grouping inbred lines into different heterotic groups and reducing cross-pollination between closely related lines