Abstract

BackgroundKnowledge of germplasm diversity and relationships among elite breeding materials is fundamentally important in crop improvement. We genotyped 450 maize inbred lines developed and/or widely used by CIMMYT breeding programs in both Kenya and Zimbabwe using 1065 SNP markers to (i) investigate population structure and patterns of relationship of the germplasm for better exploitation in breeding programs; (ii) assess the usefulness of SNPs for identifying heterotic groups commonly used by CIMMYT breeding programs; and (iii) identify a subset of highly informative SNP markers for routine and low cost genotyping of CIMMYT germplasm in the region using uniplex assays.ResultsGenetic distance for about 94% of the pairs of lines fell between 0.300 and 0.400. Eighty four percent of the pairs of lines also showed relative kinship values ≤ 0.500. Model-based population structure analysis, principal component analysis, neighbor-joining cluster analysis and discriminant analysis revealed the presence of 3 major groups and generally agree with pedigree information. The SNP markers did not show clear separation of heterotic groups A and B that were established based on combining ability tests through diallel and line x tester analyses. Our results demonstrated large differences among the SNP markers in terms of reproducibility, ease of scoring, polymorphism, minor allele frequency and polymorphic information content. About 40% of the SNPs in the multiplexed chip-based GoldenGate assays were found to be uninformative in this study and we recommend 644 of the 1065 for low to medium density genotyping in tropical maize germplasm using uniplex assays.ConclusionsThere were high genetic distance and low kinship coefficients among most pairs of lines, clearly indicating the uniqueness of the majority of the inbred lines in these maize breeding programs. The results from this study will be useful to breeders in selecting best parental combinations for new breeding crosses, mapping population development and marker assisted breeding.

Highlights

  • Knowledge of germplasm diversity and relationships among elite breeding materials is fundamentally important in crop improvement

  • The other objectives of our study were to assess the utility of single nucleotide polymorphisms (SNPs) in classifying maize inbred lines into one of two heterotic groups commonly used by the CIMMYT breeders, and identify a subset of highly informative SNP markers for routine and low cost genotyping of CIMMYT germplasm in the region

  • Heterotic grouping In order to assess if the SNP data show clear genetic differentiation between CIMMYT heterotic groups A and B that were established based on combining ability tests through diallel and line x tester analyses, we ran population structure analyses at both K = 2 and K = 3, and NJclustering and principal component analyses by selecting a subset of 220 out of the 450 lines that belong to heterotic group A (126 lines) and B (94 lines)

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Summary

Introduction

Knowledge of germplasm diversity and relationships among elite breeding materials is fundamentally important in crop improvement. Advances in molecular technology have produced a shift towards SNP markers [15,16] Because of their low cost per data point, high genomic abundance, locus-specificity, codominance, potential for high throughput analysis, and lower genotyping error rates [17,18,19], SNPs have emerged as a powerful tool for many genetic applications, including genetic diversity studies, linkage and quantitative trait loci (QTL) mapping, and markerassisted breeding [20]. High total cost and lengthy process of initial assay development are a drawback of chip-based platforms They may be unsuitable for studies where only a small to moderate number of SNPs are needed over a large number of samples, as is the case in mapping, marker assisted recurrent selection, marker assisted backcrossing, and quality control applications. It is necessary to select the best SNPs to provide a good level of discrimination for uniplex assays of each population under study

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