Biology subjects

Egesi, C.

Publications and source records attributed to Egesi, C..

4 recordsLinked to original sources

bioRxiv2022

Validation of SNP markers for marker-assisted selection of genotypes with increased carotenoid and dry matter contents in cassava

Provitamin A biofortification and increased dry matter content are important breeding targets in cassava improvement programs worldwide. Biofortified varieties contribute to the alleviation of provitamin A deficiency, a leading cause of preventable blindness in developing countries. Dry matter content is a major component of dry yield and thus underlies overall variety performance and acceptability by growers, processors, and consumers. SNP markers linked to these traits have recently been discovered through several genome-wide association studies but have not been deployed for marker-assisted selection (MAS). Assessment of marker performance in diverse genetic backgrounds is an important step towards their deployment for routine MAS. In the present study, seven previously identified markers for these traits were converted to a robust set of uniplex allele-specific PCR assays and validated in two independent pre-breeding and breeding populations. These assays were efficient in discriminating marker genotypic classes and had an average call rate greater than 98%. A high correlation was observed between the predicted and observed carotenoid content as inferred by root yellowness intensity in the breeding (r = 0.92) and pre-breeding (r = 0.95) populations. On the other hand, dry matter content-markers had moderately low predictive accuracy in both populations (r < 0.40) due to the more quantitative nature of the trait. This work confirmed marker effectiveness in multiple backgrounds, therefore, further strengthening its value in cassava biofortification to ensure nutritional security as well as dry matter content productivity. Our study provides a framework to guide future marker development, thus leading to more routine use of markers in MAS in cassava improvement programs.

genomics↗

bioRxiv2020

Genome-wide association analysis reveals new insights into the genetic architecture of defensive, agro-morphological and quality-related traits in cassava

Cassava (Manihot esculenta) is one of the most important starchy root crops in the tropics due to its adaptation to marginal environments. Genetic progress in this clonally propagated crop can be accelerated through the discovery of markers and candidate genes that could be used in cassava breeding programs. We carried out a genome-wide association study (GWAS) using a panel of 5,310 clones developed at the International Institute of Tropical Agriculture - Nigeria. The population was genotyped at more than 100,000 SNP markers via genotyping-by-sequencing (GBS). Genomic regions underlying genetic variation for 14 traits classified broadly into four categories: biotic stress (cassava mosaic disease and cassava green mite severity); quality (dry matter content and carotenoid content) and plant agronomy (harvest index and plant type). We also included several agro-morphological traits related to leaves, stems and roots with high heritability. In total, 41 significant associations were uncovered. While some of the identified loci matched with those previously reported, we present additional association signals for the traits. We provide a catalogue of favourable alleles at the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in cassava breeding programs and candidate genes for functional validation.

genetics↗

bioRxiv2019

Introgressed Manihot glaziovii Alleles in Modern Cassava Germplasm Benefit Important Traits and Are Under Balancing Selection

1.Introgression of alleles from wild relatives has often been adaptive, usually for disease resistance, in plant breeding. However, the significance of historical hybridization events in modern breeding is often not clear. Cassava (Manihot esculenta) is among the most important staple foods in the world, sustaining hundreds of millions of people in the tropics, especially in sub-Saharan Africa. Widespread genotyping makes cassava a model for clonally-propagated root and tuber crops in the developing world and provides an opportunity to study the modern benefits and consequences of historical introgression. We detected large introgressed M. glaziovii genome-segments in a collection of 2742 modern cassava landraces and elite germplasm, the legacy of 1930s era breeding to combat epidemics disease. African landraces and improved varieties were on average 3.8% (max 13.6%) introgressed. Introgressions accounted for significant (mean 20%, max 56%) portion of the heritability of tested traits M. glaziovii alleles on the distal 10Mb of chr. 1 increased dry matter and root number. On chr. 4, introgressed alleles in a 20Mb region improved harvest index and brown streak disease tolerance. Three cycles of selection initially doubled the introgression frequency on chr. 1. Later stage variety trials selectively excluded homozygotes which indicates a heterozygous advantage. We show that maintaining large recombination-suppressed introgressions in the heterozygous state allows the accumulation of deleterious mutations. We conclude that targeted recombination of introgression segments would therefore increase the efficiency of cassava breeding by allowing simultaneous fixation of beneficial alleles and purging of genetic load.\n\nSignificance StatementCrosses to wild relatives have often been adaptive for crop breeding, but their modern importance is usually poorly understood. Cassava (Manihot esculenta) is an important staple crop, feeding hundreds of millions in the developing world, and is a model for vegetatively-propagated non-inbred crops. In the 1930s, crossing to M. glaziovii averted mosaic disease epidemic in Africa. We reveal that large genome segments, the legacy of those crosses, benefit a number of traits including yield in modern cassava and are consistently favored during selection. Elite cultivars are almost exclusively heterozygous for wild alleles; homozygotes are rejected during early stage trials, suggesting inbreeding depression. More recombination around beneficial wild alleles will allow purging of genetic load and increase genetic gain in cassava.

genetics↗

bioRxiv2017

Prospects for genomic selection in cassava breeding

Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) reduces selection cycle times by the prediction of breeding value for selection of unevaluated lines based on genome-wide marker data. GS has been implemented at three breeding programs in sub-Saharan Africa. Initial studies provided promising estimates of predictive abilities in single populations using standard prediction models and scenarios. In the present study we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: (1) cross-validation within each population, (2) cross-population prediction and (3) cross-generation prediction. We also evaluated the impact of increasing training population size by phenotyping progenies selected either at random or using a genetic algorithm. Cross-validation results were mostly consistent across breeding programs, with non-additive models like RKHS predicting an average of 10% more accurately. Accuracy was generally associated with heritability. Cross-population prediction accuracy was generally low (mean 0.18 across traits and models) but prediction of cassava mosaic disease severity increased up to 57% in one Nigerian population, when combining data from another related population. Accuracy across-generation was poorer than within (cross-validation) as expected, but indicated that accuracy should be sufficient for rapid-cycling GS on several traits. Selection of prediction model made some difference across generations, but increasing training population (TP) size was more important. In some cases, using a genetic algorithm, selecting one third of progeny could achieve accuracy equivalent to phenotyping all progeny. Based on the datasets analyzed in this study, it was apparent that the size of a training population (TP) has a significant impact on prediction accuracy for most traits. We are still in the early stages of GS in this crop, but results are promising, at least for some traits. The TPs need to continue to grow and quality phenotyping is more critical than ever. General guidelines for successful GS are emerging. Phenotyping can be done on fewer individuals, cleverly selected, making for trials that are more focused on the quality of the data collected.\n\nAbbreviations

genetics↗