Biology subjects

Beyene, Y.

Publications and source records attributed to Beyene, Y..

3 recordsLinked to original sources

bioRxiv2026

From Diversity to Discovery: Genome-Wide Insights into the Genetic Landscape of Tropical Maize DH Lines

Understanding the extent and structure of genetic diversity within breeding populations is essential for sustaining long-term genetic gain in maize improvement programs. In this study, a panel of 2,555 maize doubled haploid (DH) lines representing diverse genetic backgrounds was genotyped using 3305 high-quality single nucleotide polymorphism (SNP) markers to assess genome-wide diversity, population structure, and relatedness. The SNPs were distributed across all ten chromosomes, with varying marker densities among genomic regions. Diversity indices revealed moderate polymorphism, with mean gene diversity (0.38) and polymorphic information content (0.30), while the minor allele frequency ranged from 0.04 to 0.50. The low observed heterozygosity (0.04) and high fixation index (0.89) confirmed the expected homozygosity of DH lines. Population structure analysis using sparse non-negative matrix factorization (sNMF) and principal coordinate analysis (PCoA) consistently identified two major genetic clusters corresponding to the established heterotic groups used in CIMMYTs tropical maize breeding pipelines. The Analysis of Molecular Variance (AMOVA) indicated that 36% of genetic variation occurred among populations, 58% among individuals within populations, and 6% within individuals (P = 0.001), confirming significant population differentiation and high within-group diversity. These results demonstrate that the DH panel represents a genetically diverse and well-structured population with limited relatedness among lines. The distinct clustering by heterotic group, coupled with substantial within-group variation, provides a strong foundation for genome-wide association studies, genomic selection, and allele mining for complex adaptive traits. The panels diversity and structure make it an invaluable genomic resource for dissecting trait architecture and accelerating genetic gain in tropical maize breeding programs targeting sub-Saharan Africa and similar environments.

genetics↗

bioRxiv2025

Genetic Insights from Line x Tester Analysis of Maize Lethal Necrosis Testcrosses for Developing Multi-Stress-Resilient Hybrids in Sub-Saharan Africa

A systematic evaluation of maize hybrid performance and combining ability was conducted to enhance resistance to maize lethal necrosis (MLN), drought tolerance, and grain yield (GY) in eastern and southern Africa. Thirty-eight MLN-tolerant, lines were crossed with 29 single-cross testers to generate 437 testcross hybrids, evaluated under managed MLN inoculation, drought stress, and optimum conditions across multiple locations. Continuous variation in GY, disease severity, and agronomic traits confirmed quantitative inheritance, with strong positive correlations between GY and ears per plant and negative correlations between MLN severity and yield. Variance analyses revealed highly significant genotypic and genotype x environment interactions, with additive effects predominating across environments (Bakers ratios 0.85-0.99; heritability 0.69-0.88), supporting effective selection based on general combining ability (GCA). Superior MLN-tolerant hybrids, such as (CKLMARSI0037/CKLTI0139)//CKDHL120312, achieved up to 5.75 t ha-{superscript 1} under MLN, exceeding commercial checks by over fivefold. Under optimum and drought conditions, top hybrids maintained high yield, foliar disease resistance, short anthesis-silking intervals, and delayed senescence. Specific combining ability (SCA) effects highlighted stress-specific non-additive interactions, particularly under drought, underscoring the need for targeted parental selection. GCA analyses identified across environment and environment-specific favorable parents, including CKDHL120312, CKDHL140910, CKLMARSI0037/CKLTI0139, and CML322/CML543, while GGE biplots confirmed tester discrimination and representativeness. These findings demonstrate that integrating MLN resistance, drought tolerance, and high yield is achievable without compromising other agronomic performance. The study provides a robust framework for selecting elite parents and testers, exploiting additive and non-additive genetic effects, and developing resilient, high-performing maize hybrids for sub-Saharan Africa.

plant biology↗

bioRxiv2025

Sparse testcrossing for early-stage genomic prediction of general combining ability to increase genetic gain in maize hybrid breeding programs

1Sparse testcrossing is an effective strategy for increasing both short- and long-term genetic gain in hybrid breeding programs. Maize hybrid breeding programs aim to develop new hybrid varieties by crossing genetically distinct parents from different heterotic pools, exploiting heterosis for improved performance. The programs typically consist of two main components: population improvement and product development. The population improvement component aims to enhance the heterotic pools through reciprocal recurrent selection based on general combining ability (GCA). However, especially in the early stages of testing, evaluating large numbers of hybrid combinations to estimate GCA is impractical due to considerable logistical challenges and costs. Therefore, breeders often evaluate the initial population of selection candidates using only a single tester to narrow down the candidate pool before further evaluation. Using a single tester, however, may not adequately represent the heterotic pool, leading to inaccurate GCA estimates and suboptimal selection decisions. To address this, we propose sparse testcrossing for early-stage testing, where subsets of candidate genotypes are testcrossed with different testers, connected through a genomic relationship matrix. We conducted stochastic simulations to compare various sparse testcrossing designs with a conventional testcross strategy using a single tester over 15 cycles of reciprocal recurrent genomic selection. Our results show that using 3-5 testers, sparsely distributed among full-sibs, sparse testcrossing offers breeders a practical balance between simple testcross designs, resource efficiency, and increased prediction accuracy for GCA, ultimately resulting in increased rates of genetic gain. Key messageSparse testcrossing with 3-5 testers enhances genetic gain in hybrid breeding programs, offering a practical balance of simple testcross designs, resource efficiency, and increased prediction accuracy for general combining ability.

genomics↗