Showing papers by "Cosmos Magorokosho published in 2012"
TL;DR: There 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.
Abstract: Knowledge 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. Genetic 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. There 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.
127 citations
TL;DR: A retrospective analysis of 704 elite hybrid trials conducted from 2001 to 2009 was used to determine the relative ability of optimal, low-N, and managed drought trials to predict performance under the conditions of random abiotic stress andLow-N fertility usually faced by African farmers.
Abstract: Maize (Zea mays L.) yields in southern Africa are low, due largely to drought and low-N stress. Selection of stress-tolerant genotypes by CIMMYT is conducted indirectly under managed stress conditions, although the selection effi ciency of this approach is not known. A retrospective analysis of 704 elite hybrid trials conducted from 2001 to 2009 was used to determine the relative ability of optimal, low-N, and managed drought trials to predict performance under the conditions of random abiotic stress and low-N fertility usually faced by African farmers. Well-fertilized trials in the rainy season were categorized as having experienced random abiotic stress if mean yield was <3 t ha -1 and the yield-anthesis date correlation was <0.1; otherwise they were classed as optimal. High genetic correlations were estimated between random abiotic stress and low-N or optimal conditions. Heritability was highest under optimal conditions and lowest under random abiotic stress. Indirect selection under low-N and optimal conditions was more effi cient than direct selection under random abiotic stress or indirect selection under managed drought, especially for early maturing genotypes, but direct selection was most effi cient for predicting performance under low N. Elite maize hybrids tolerant to random abiotic stress can be most effi ciently selected under optimal and/or low-N conditions while low-N tolerant genotypes should be selected directly under low N.
96 citations
TL;DR: In this article, yield data of 448 maize hybrids evaluated in 513 trials across 17 countries from 2001 to 2009 were used to study the extent of specific adaptation to these subregions and to determine whether selection within sub-regions results in greater gains than selection across the undivided TPE.
Abstract: To develop stable and high-yielding maize (Zea mays L.) hybrids for a diverse target population of environments (TPE), breeders have to decide whether greater gains result from selection across the undivided TPE or within more homogeneous subregions. Currently, CIMMYT subdivides the TPE in eastern and southern Africa into climatic and geographic subregions. To study the extent of specific adaptation to these subregions and to determine whether selection within subregions results in greater gains than selection across the undivided TPE, yield data of 448 maize hybrids evaluated in 513 trials across 17 countries from 2001 to 2009 were used. The trials were grouped according to five subdivision systems into climate, altitude, geographic, country, and yield-level subregions. For the first four subdivision systems, genotype × subregion interaction was low, suggesting broad adaptation of maize hybrids across eastern and southern Africa. In contrast, genotype × yield-level interactions and moderate genotypic correlations between low- and high-yielding subregions were observed. Therefore, hybrid means should be estimated by stratifying the TPE considering the yield-level effect as fixed and appropriately weighting information from both subregions. This strategy was at least 10% better in terms of predicted gains than direct selection using only data from the low- or high-yielding subregion and should facilitate the identification of hybrids that perform well in both subregions.
62 citations
TL;DR: Based on the data sets obtained for a wide range of sample sizes and diverse genetic backgrounds, a subset of 50–100 SNPs is recommended for routine and low-cost QC genotyping and a protocol is outlined that could be used to minimize errors in genetic analyses and breeding.
Abstract: Quality control (QC) genotyping is an important component in breeding, but to our knowledge there are not well established protocols for its implementation in practical breeding programs. The objectives of our study were to (a) ascertain genetic identity among 2-4 seed sources of the same inbred line, (b) evaluate the extent of genetic homogeneity within inbred lines, and (c) identify a subset of highly informative single-nucleotide polymorphism (SNP) markers for routine and low-cost QC genotyping and suggest guidelines for data interpretation. We used a total of 28 maize inbred lines to study genetic identity among different seed sources by genotyping them with 532 and 1,065 SNPs using the KASPar and GoldenGate platforms, respectively. An additional set of 544 inbred lines was used for studying genetic homogeneity. The proportion of alleles that differed between seed sources of the same inbred line varied from 0.1 to 42.3 %. Seed sources exhibiting high levels of genetic distance are mis-labeled, while those with lower levels of difference are contaminated or still segregating. Genetic homogeneity varied from 68.7 to 100 % with 71.3 % of the inbred lines considered to be homogenous. Based on the data sets obtained for a wide range of sample sizes and diverse genetic backgrounds, we recommended a subset of 50-100 SNPs for routine and low-cost QC genotyping, verified them in a different set of double haploid and inbred lines, and outlined a protocol that could be used to minimize errors in genetic analyses and breeding.
58 citations