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Genetic gain within the CIMMYT Eastern and Southern Africa (ESA) hybrid maize (Zea mays L.) breeding program from 2000 to 2010 was recently estimated at 0.85 to 2.2% yr-1 under various environmental conditions. Over 100 varieties were disseminated from CIMMYT to farmers in ESA, hence the need to check genetic diversity and frequency of use of parents to avoid potential narrowing down of the genetic base. Fifty-five parents from CIMMYT ESA used in the hybrids were fingerprinted using genotyping-by-sequencing. Data analysis in TASSEL and MEGA6 generated pairwise genetic distances between parents of 0.004 to 0.4005. Unweighted pair group method with arithmetic mean (UPGMA) analysis produced two clusters (I and II) with two subclusters each (A and B) and two sub-subclusters (IAi and IAii). Principal coordinate analysis produced three clusters where IAi and IIA from the UPGMA analysis formed independent clusters while IAii, IB, and IIB clustered together. Lines were separated by pedigree and origin. Ninety-five percent frequency of pairwise genetic distances ranged between 0.2001 and 0.4000. However, only four of the 55 parents (CML444, CML395, CML312, and CML442) were each used in 15 to 30 of the 52 hybrids evaluated in the genetic gain study. The remaining 51 were used in one to four hybrids. Frequent use of the four parents gave 29 to 58% of the hybrids a narrow genetic base, posing risk in case of pest or disease outbreaks. Parents evaluated do not represent the genetic base of CIMMYT ESA but parents of the best-performing hybrids selected from 2000 to 2010. Breeders should ensure a wide genetic base for released varieties to avoid breakdown in case of pest or disease outbreaks. [ABSTRACT FROM AUTHOR]

Genetic characterisation of breeding lines is of great importance as it enables breeders to maximise heterosis in hybrid combinations as well as in the breeding material. In this study 10 Department of Research and Specialist Services and 13 Centre for the Improvement of Maize and Wheat inbred lines were crossed using a North Carolina II mating scheme and were genotyped using 1,129 single nucleotide polymorphic (SNP) markers. The resultant 72 single cross hybrids together with eight different local checks were evaluated across seven locations in Zimbabwe in the 2009/2010 and 2010/2011 seasons. SNP markers yielded a total of 2,258 alleles and a moderate genetic diversity and polymorphic information content of 0.32 and 0.258, respectively. Clustering of lines did not relate to available pedigree information. Significant positive correlations were recorded for specific combining ability with mid parent heterosis (MPH), high parent heterosis (HPH) and per se performance of hybrids. However, correlations of genetic distances with heterosis under drought conditions were too low to be of predictive value. The HPH and MPH also showed significant positive associations along with high coefficients of determination with per se performance of hybrids, especially under drought. [ABSTRACT FROM AUTHOR]

Genomic selection incorporates all the available marker information into a model to predict genetic values of breeding progenies for selection. The objective of this study was to estimate genetic gains in grain yield from genomic selection (GS) in eight bi-parental maize populations under managed drought stress environments. In each population, 148 to 300 F2:3 (C0) progenies were derived and crossed to a single-cross tester from a complementary heterotic group. The resulting testcrosses of each population were evaluated under two to four managed drought stress and three to four well-watered conditions in different locations and genotyped with 191 to 286 single nucleotide polymorphism (SNP) markers. The top 10% families were selected from C0 using a phenotypic selection index and were intermated to form C1. Selections both at C1 and C2 were based on genomic estimated breeding values (GEBVs). The best lines from C0 were also advanced using a pedigree selection scheme. For genetic gain studies, a total of 55 entries representing the eight populations were crossed to a single-cross tester, and evaluated in four managed drought stress environments. Each population was represented by bulk seed containing equal amounts of seed of C0, C1, C2, C3, parents, F1s, and lines developed via pedigree selection. Five commercial checks were included for comparison. The average gain from genomic selection per cycle across eight populations was 0.086 Mg ha-1. The average grain yield of C3-derived hybrids was significantly higher than that of hybrids derived from C0. Hybrids derived from C3 produced 7.3% (0.176 Mg ha-1) higher grain yield than those developed through the conventional pedigree breeding method. The study demonstrated that genomic selection is more effective than pedigree-based conventional phenotypic selection for increasing genetic gains in grain yield under drought stress in tropical maize. [ABSTRACT FROM AUTHOR]

Molecular characterization of open-pollinated maize varieties (OPVs) is fundamentally important in maize germplasm improvement. We investigated the extent of genetic differences, patterns of relationships, and population structure among 218 diverse OPVs widely used in southern and eastern Africa using the model-based population structure, analysis of molecular variance, cluster analysis, principal component analysis, and discriminant analysis. The OPVs were genotyped with 51 microsatellite markers and the fluorescent detection system of the Applied Biosystems 3730 Capillary Sequencer. The number of alleles detected in each OPV varied from 72 to 155, with an overall mean of 127.6. Genetic distance among the OPVs varied from 0.051 to 0.434, with a mean of 0.227. The different multivariate methods suggest the presence of 2-4 possible groups, primarily by maturity groups but also with overlapping variation between breeding programs, mega-environments, and specific agronomic traits. Nearly all OPVs in group 1 and group 2 belong to the intermediate-late and early maturity groups, respectively. Group 3 consisted of mainly intermediate maturing OPVs, while group 4 contained OPVs of different maturity groups. The OPVs widely used in eastern Africa either originated from the southern African maize breeding programs, or the majority of inbred lines used as parents by the two breeding programs in developing the OPVs might be genetically related. Some of the OPVs are much older than others, but they still did not show a clear pattern of genetic differentiation as compared with the recently developed ones, which is most likely due to recycling of the best parental lines in forming new OPVs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]