Cosmos Magorokosho

Genomic Selection and Prediction in Plant Breeding

The availability of thousands of genome-wide molecular markers has made possible the use of genomic selection in plants and animals. However, the evaluation of models for genomic selection in plant breeding populations remains limited. In this study, we provide an overview of several models for genomic selection, whose predictive ability we investigate using two plant data sets. The first data set comprises historical phenotypic records of a series of wheat (Triticum aestivum L.) trials evaluated in 10 environments and recently generated genomic data. The second data set pertains to international maize (Zea mays L.) trials in which two disease traits (Exserohilum turcicum and Cercospora zeae-maydis) of maize lines evaluated in five environments were measured. Results showed that models including marker information yielded important gains in predictive ability relative to that of a pedigree-based model, this with a modest number of markers. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction was an important component of genetic variability. Overall, the study provided evidence from real populations indicating that genomic selection could be an effective tool for improving traits of economic importance in commercial crops.

Molecular characterization of diverse CIMMYT maize inbred lines from eastern and southern Africa using single nucleotide polymorphic markers

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.

Genome-wide association mapping reveals novel sources of resistance to northern corn leaf blight in maize

BackgroundNorthern corn leaf blight (NCLB) caused by Exserohilum turcicum is a destructive disease in maize. Using host resistance to minimize the detrimental effects of NCLB on maize productivity is the most cost-effective and appealing disease management strategy. However, this requires the identification and use of stable resistance genes that are effective across different environments.ResultsWe evaluated a diverse maize population comprised of 999 inbred lines across different environments for resistance to NCLB. To identify genomic regions associated with NCLB resistance in maize, a genome-wide association analysis was conducted using 56,110 single-nucleotide polymorphism markers. Single-marker and haplotype-based associations, as well as Anderson-Darling tests, identified alleles significantly associated with NCLB resistance. The single-marker and haplotype-based association mappings identified twelve and ten loci (genes), respectively, that were significantly associated with resistance to NCLB. Additionally, by dividing the population into three subgroups and performing Anderson-Darling tests, eighty one genes were detected, and twelve of them were related to plant defense. Identical defense genes were identified using the three analyses.ConclusionAn association panel including 999 diverse lines was evaluated for resistance to NCLB in multiple environments, and a large number of resistant lines were identified and can be used as reliable resistance resource in maize breeding program. Genome-wide association study reveals that NCLB resistance is a complex trait which is under the control of many minor genes with relatively low effects. Pyramiding these genes in the same background is likely to result in stable resistance to NCLB.

Genetic relationships and structure among open-pollinated maize varieties adapted to eastern and southern Africa using microsatellite markers

Abstract 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.

Validation of the use of secondary traits and selection indices for drought tolerance in tropical maize (Zea mays L.)

Breeding progress for drought tolerance in maize has been slow since drought tolerance is a complex trait controlled by many genes. Breeders improving maize for drought tolerance have therefore been using secondary traits and selection indices for selecting the best genotypes under drought stress. The objectives of this study were to determine the combining ability of the inbred lines in stress and non stress environments as well as compare the use and efficacy of secondary traits and selection indices in selecting for drought tolerant genotypes. Fifty hybrids formed through a North Carolina Design II and four checks were evaluated using the 0.1 alpha lattice planting design under optimum and drought environments. General combining ability (GCA), specific combining ability (SCA) and seven drought indices (SDI), stress susceptibility index (SSI), tolerance (TOL), yield index (YI), yield stability index (YSI), mean productivity index (MPI), stress tolerance index (STI) and geometric productivity index (GMP) were used in the computation of results. Results showed that under drought conditions, GCA was highly significant (P<0.001) for grain yield, anthesis-silking interval (ASI) and ears per plant (EPP) while SCA was significant for grain yield and EPP. Selection indices STI and GMP had positive and significant correlation (P<0.01) with grain yield under both drought stress (Ys) and optimum (Yp) conditions. EPP also had significant (P<0.01) and positive correlation with Ys and Yp. ASI had significant and negative correlation with Ys (P<0.01) and TOL (P <0.05). In addition EPP had a positive and significant correlation with STI (P<0.05) and GMP (P<0.01). The results indicated that ASI, EPP, STI and GMP are effective in identifying high yielding genotypes under different moisture regimes. Narrow sense heritability showed that phenotypic variation attributed to genetic effects increased under stress conditions for EPP and ASI and making them more reliable parameters for use in selecting for genotypes under stress conditions. The two secondary traits (ASI and EPP) together with two drought indices; (STI and GMP) can therefore be used in tandem for increased efficiency in selecting for genotypes under stress environments.

Relationships between heterosis, genetic distances and specific combining ability among CIMMYT and Zimbabwe developed maize inbred lines under stress and optimal conditions

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.

High-Throughput and Precision Phenotyping for Cereal Breeding Programs

Cereals hold unique position in world agriculture as a source of food, feed and diverse products of industrial importance. For several million farmers and consumers in countries with low- and middle-income, cereals (especially rice, wheat and maize) are the preferred staple food crops. The future of cereal production, and consequently, the livelihoods of several million small farmers worldwide, is therefore, dependent to a great extent on developing improved high yielding varieties of cereals.

Impact of adoption of drought-tolerant maize varieties on total maize production in south Eastern Zimbabwe

Drought is a huge limiting factor in maize production, mainly in the rain-fed agriculture of sub-Saharan Africa. In response to this threat, drought-tolerant (DT) maize varieties have been developed with an aim to ensure maize production under mild drought conditions. We conducted a study to assess the impact of smallholder farmers’ adoption of DT maize varieties on total maize production. Data for the study came from a survey of 200 randomly sampled households in two districts of Chiredzi and Chipinge in southeastern Zimbabwe. The study found that 93% of the households were growing improved maize varieties and that 30% of the sampled households were growing DT maize varieties. Total maize yield was 436.5 kg/ha for a household that did not grow DT maize varieties and 680.5 kg/ha for households that grew DT maize varieties. We control for the endogeneity of the DT adoption variable, by using the control function approach to estimate total maize production in a Cobb–Douglas model. The results show that households that grew DT maize varieties had 617 kg/ha more maize than households that did not grow the DT maize varieties. Given that almost all farmers buy their seeds in the market, a change in varieties to DT maize seeds gives an extra income of US

High-Throughput Phenotyping of Canopy Cover and Senescence in Maize Field Trials Using Aerial Digital Canopy Imaging

240/ha or more than nine months of food at no additional cost. This has huge implications in curbing food insecurity and simultaneously saving huge amounts of resources at the household and national levels, which are used to buy extra food during the lean season.

Combining Ability for Grain Yield Performance among CIMMYT Germplasm Adapted to the Mid-Altitude Conditions

In the crop breeding process, the use of data collection methods that allow reliable assessment of crop adaptation traits, faster and cheaper than those currently in use, can significantly improve resource use efficiency by reducing selection cost and can contribute to increased genetic gain through improved selection efficiency. Current methods to estimate crop growth (ground canopy cover) and leaf senescence are essentially manual and/or by visual scoring, and are therefore often subjective, time consuming, and expensive. Aerial sensing technologies offer radically new perspectives for assessing these traits at low cost, faster, and in a more objective manner. We report the use of an unmanned aerial vehicle (UAV) equipped with an RGB camera for crop cover and canopy senescence assessment in maize field trials. Aerial-imaging-derived data showed a moderately high heritability for both traits with a significant genetic correlation with grain yield. In addition, in some cases, the correlation between the visual assessment (prone to subjectivity) of crop senescence and the senescence index, calculated from aerial imaging data, was significant. We concluded that the UAV-based aerial sensing platforms have great potential for monitoring the dynamics of crop canopy characteristics like crop vigor through ground canopy cover and canopy senescence in breeding trial plots. This is anticipated to assist in improving selection efficiency through higher accuracy and precision, as well as reduced time and cost of data collection.