Genetic Diversity and Population Structure of Maize Doubled Haploid Lines from Drought and Low Nitrogen Tolerant Populations
Ehemba, G. L.; Ifie, B. E.; DAS, B.; Abu, P.; Adjei, E. A.; Ayenan, M. A. T.; Garcia-Oliveira, A.; Ribeiro, P.; Manilal, W.; Tongoona, P.; Danquah, E. Y.
Show abstract
Understanding the genetic diversity and population structure of breeding materials is essential for developing stress-resilient cultivars. In tropical maize, where drought and low soil nitrogen (low N) severely limit productivity, continuous development of tolerant varieties remains a priority. This study assessed the genetic diversity and population structure of 250 doubled haploid lines (DHLs) derived from five drought- and low N-tolerant tropical populations. Genotyping was performed using mid-density DArTseq markers, yielding 3,305 high-quality SNPs for analysis. Results revealed a moderate level of diversity among the DHLs, with an average genetic distance of 0.39, a polymorphism information content (PIC) of 0.33, and a minor allele frequency (MAF) of 0.29. These values reflect substantial allelic variation, important for identifying complementary parental combinations in hybrid development. Discriminant analysis of principal components (DAPC) grouped the DHLs into five distinct clusters, largely corresponding to their source populations, although some admixture was observed. This indicates that while the genetic backgrounds of the source populations were mostly retained, recombination introduced useful variation. Overall, the clear population structure and high diversity observed among these DHLs provide a strong genetic foundation for future maize improvement. These lines represent valuable resources for heterotic group formation, hybrid development, and recurrent selection schemes aimed at enhancing drought and low nitrogen tolerance in tropical maize.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Genetic Insights from Line x Tester Analysis of Maize Lethal Necrosis Testcrosses for Developing Multi-Stress-Resilient Hybrids in Sub-Saharan Africa 97%
- SNP- Based Assessment of Genetic Purity and Diversity in Maize Hybrid Breeding 97%
- Genetic diversity and population structure of soybean (Glycine max (L.) Merril) germplasm. 96%
Similar papers in this journal
- The de novo reference genome and transcriptome assemblies of the wild tomato species Solanum chilense 93%
- Genetic Architecture of Chilling Tolerance in Sorghum Dissected with a Nested Association Mapping Population 93%
- Fine mapping using whole-genome sequencing confirms anti Mullerian hormone as a major gene for sex determination in farmed Nile tilapia (Oreochromis niloticus L.) 92%
Similar papers in this journal
- Genome-wide association study of multiple yield components in a diversity panel of polyploid sugarcane (Saccharum spp.) 96%
- Effectiveness of Genomic Selection by Response to Selection for Winter Wheat Variety Improvement 95%
- Genome Wide Association Study of Resistance to PstS2 and Warrior Races of Stripe (Yellow) Rust in Bread Wheat Landraces. 94%
Similar papers in this journal
- Trends in stomatal density and size in maize hybrids representing 100 years of long-term breeding for yield 96%
- CGIAR BARLEY BREEDING TOOLBOX: A diversity panel to facilitate breeding and genomic research in the Developing World 95%
- A novel QTL conferring Fusarium crown rot resistance located on chromosome arm 6HL in barley 95%
Similar papers in this journal
- BREAKING THE TIGHT GENETIC LINKAGE BETWEEN THE a1 AND sh2 GENES LED TO THE DEVELOPMENT OF ANTHOCYANIN-RICH PURPLE-PERICARP SUPER-SWEETCORN 96%
- Predicting flowering time using integrated morphophysiological and genomic data with machine learning models 95%
- Bivariate analysis of barley scald resistance with relative maturity reveals a new major QTL on chromosome 3H 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.