Comparing the efficiency of base and multiplicative selection indices for yield and quality traits in Cassava: Article Retracted by the Authors

The efficiency of two selection indices; base index and the multiplicative index was compared to determine the effectiveness of each in identifying superior genotypes in cassava (Manihot esculent Crantz) population. Genotypic data on various yield and quality traits among 570 cassava genotypes were used to construct these selection indices. The efficiency of these indices was compared by determining the performance means of each genotype for studied traits and computing selection differentials of each index. Best linear unbiased predictions (BLUPs) for dry matter content and harvest index were also used for comparison of the two selection indices.  The base index produced high-performance means of all five studied traits and proved to be more efficient compared to the multiplicative index in the improvement of cassava genotypes. In addition, the base index produced high selection differentials for three out of five studied traits. It was concluded that the base index is useful in cassava germplasm selectio

Adaptation and stability of vegetable soybean genotypes in Uganda

Vegetable soybean ( Glycine max L. Merr.) is a specialty soybean, harvested as a vegetable when seeds are immature (R6 stage) and have expanded to fill 80 to 90% of the pod. The objective of the study was to assess the adaptation and stability of vegetable soybean genotypes in different agro-ecological zones of Uganda to enable selection of genotypes. A total of 21 genotypes were planted in Uganda for two consecutive seasons. Genotypes PI615437-B had the highest number of pods, while AGS 329 matured earliest in 64 days. Only AGS 292, AGS 329 and AGS 338 had 100 seeds weight above 30 g. G10427 was the ideal genotype in terms of adaptation and stability for fresh seed yield, with mean yield of 4281kg ha-1; followed by G2843 with 4039 kg ha-1. PI615437-B came third with fresh seed yield of 4024 kg ha-1. The least stable and adapted genotype was AGS 329 with only 1609 kg ha-1. Nakabango 1 and MUARIK 1 were the ideal environments, which were the most discriminative and representative. We recommend that G10427 be used as a test genotype and for improvement to produce a variety with good attributes, especially large seed, high yield and adaptable to Uganda.Le soja ( Glycine max L. Merr.) Est un soja de sp\ue9cialit\ue9, r\ue9colt\ue9 comme l\ue9gume quand les graines sont immatures (stade R6) et s\u2019est d\ue9velopp\ue9 pour remplir 80 \ue0 90% de la gousse. L\u2019objectif de l\u2019\ue9tude \ue9tait d\u2019\ue9valuer l\u2019adaptation et la stabilit\ue9 des g\ue9notypes de soja v\ue9g\ue9tal dans diff\ue9rentes zones agro-\ue9cologiques de l\u2019Ouganda pour permettre la s\ue9lection des g\ue9notypes. Au total, 21 g\ue9notypes ont \ue9t\ue9 plant\ue9s en Ouganda pendant deux saisons cons\ue9cutives. Les g\ue9notypes PI615437-B avaient le plus grand nombre de gousses, tandis qu\u2019AGS 329 est arriv\ue9 \ue0 maturit\ue9 plus t\uf4t en 64 jours. Seulement AGS 292, AGS 329 et AGS 338 avaient un poids de 100 graines sup\ue9rieur \ue0 30 g. G10427 \ue9tait le g\ue9notype id\ue9al en termes d\u2019adaptation et de stabilit\ue9 pour le rendement en semences fra\ueeches, avec un rendement moyen de 4281 kg ha-1; suivi de G2843 avec 4039 kg ha-1. Le PI615437-B est arriv\ue9 troisi\ue8me avec un rendement en graines fra\ueeches de 4024 kg ha-1. Le g\ue9notype le moins stable et le plus adapt\ue9 \ue9tait AGS 329 avec seulement 1609 kg ha-1. Nakabango 1 et MUARIK 1 \ue9taient les environnements id\ue9aux, les plus discriminants et les plus repr\ue9sentatifs. Nous recommandons que G10427 soit utilis\ue9 comme g\ue9notype de test et pour l\u2019am\ue9lioration afin de produire une vari\ue9t\ue9 en particulier des graines de grande taille, \ue0 haut rendement et adaptable \ue0 l\u2019Ouganda

Field evaluation of selected cassava genotypes for cassava brown streak disease based on symptom expression and virus load

Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread.Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread.Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread.Background Production of cassava (Manihot esculenta Crantz), a food security crop in sub-Saharan Africa, is threatened by the spread of cassava brown streak disease (CBSD) which manifests in part as a corky necrosis in the storage root. It is caused by either of two virus species, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), resulting in up to 100% yield loss in susceptible varieties. Methods This study characterized the response of 11 cassava varieties according to CBSD symptom expression and relative CBSV and UCBSV load in a field trial in Uganda. Relative viral load was measured using quantitative RT-PCR using COX as an internal housekeeping gene. Results A complex situation was revealed with indications of different resistance mechanisms that restrict virus accumulation and symptom expression. Four response categories were defined. Symptom expression was not always positively correlated with virus load. Substantially different levels of the virus species were found in many genotypes suggesting either resistance to one virus species or the other, or some form of interaction, antagonism or competition between virus species. Conclusions A substantial amount of research still needs to be undertaken to fully understand the mechanism and genetic bases of resistance. This information will be useful in informing breeding strategies and restricting virus spread

Genomic prediction and quantitative trait locus discovery in a cassava training population constructed from multiple breeding stages

Open Access Article; Published online: 11 Dec 2019Assembly of a training population (TP) is an important component of effective genomic selection‐based breeding programs. In this study, we examined the power of diverse germplasm assembled from two cassava (Manihot esculenta Crantz) breeding programs in Tanzania at different breeding stages to predict traits and discover quantitative trait loci (QTL). This is the first genomic selection and genome‐wide association study (GWAS) on Tanzanian cassava data. We detected QTL associated with cassava mosaic disease (CMD) resistance on chromosomes 12 and 16; QTL conferring resistance to cassava brown streak disease (CBSD) on chromosomes 9 and 11; and QTL on chromosomes 2, 3, 8, and 10 associated with resistance to CBSD for root necrosis. We detected a QTL on chromosome 4 and two QTL on chromosome 12 conferring dual resistance to CMD and CBSD. The use of clones in the same stage to construct TPs provided higher trait prediction accuracy than TPs with a mixture of clones from multiple breeding stages. Moreover, clones in the early breeding stage provided more reliable trait prediction accuracy and are better candidates for constructing a TP. Although larger TP sizes have been associated with improved accuracy, in this study, adding clones from Kibaha to those from Ukiriguru and vice versa did not improve the prediction accuracy of either population. Including the Ugandan TP in either population did not improve trait prediction accuracy. This study applied genomic prediction to understand the implications of constructing TP from clones at different breeding stages pooled from different locations on trait accuracy

Genome-wide association and prediction reveals genetic architecture of cassava mosaic disease resistance and prospects for rapid genetic improvement

Published: 13 May 2016Cassava (Manihot esculenta Crantz) is a crucial, under-researched crop feeding millions worldwide, especially in Africa. Cassava mosaic disease (CMD) has plagued production in Africa for over a century. Biparental mapping studies suggest primarily a single major gene mediates resistance. To investigate this genetic architecture, we conducted the first genome-wide association mapping study in cassava with up to 6128 genotyping-by-sequenced African breeding lines and 42,113 reference genome-mapped single-nucleotide polymorphism (SNP) markers. We found a single region on chromosome 8 that accounts for 30 to 66% of genetic resistance in the African cassava germplasm. Thirteen additional regions with small effects were also identified. Further dissection of the major quantitative trait locus (QTL) on chromosome 8 revealed the presence of two possibly epistatic loci and/or multiple resistance alleles, which may account for the difference between moderate and strong disease resistances in the germplasm. Search of potential candidate genes in the major QTL region identified two peroxidases and one thioredoxin. Finally, we found genomic prediction accuracy of 0.53 to 0.58 suggesting that genomic selection (GS) will be effective both for improving resistance in breeding populations and identifying highly resistant clones as varieties

solGS: a webbased tool for genomic selection

Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.Background: Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results: We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions: solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program

Cassava haplotype map highlights fixation of deleterious mutations during clonal propagation

Article purchased; Published online: 17 April 2017Cassava (Manihot esculenta Crantz) is an important staple food crop in Africa and South America; however, ubiquitous deleterious mutations may severely decrease its fitness. To evaluate these deleterious mutations, we constructed a cassava haplotype map through deep sequencing 241 diverse accessions and identified >28 million segregating variants. We found that (i) although domestication has modified starch and ketone metabolism pathways to allow for human consumption, the concomitant bottleneck and clonal propagation have resulted in a large proportion of fixed deleterious amino acid changes, increased the number of deleterious alleles by 26%, and shifted the mutational burden toward common variants; (ii) deleterious mutations have been ineffectively purged, owing to limited recombination in the cassava genome; (iii) recent breeding efforts have maintained yield by masking the most damaging recessive mutations in the heterozygous state but have been unable to purge the mutation burden; such purging should be a key target in future cassava breeding

Validation of KASP markers associated with cassava mosaic disease resistance, storage root dry matter and provitamin A carotenoid contents in Ugandan cassava germplasm

Open Access Journal; Published online: 23 Nov 2022Introduction The intrinsic high heterozygosity of cassava makes conventional breeding ineffective for rapid genetic improvement. However, recent advances in next-generation sequencing technologies have enabled the use of high-density markers for genome-wide association studies, aimed at identifying single nucleotide polymorphisms (SNPs) linked to major traits such as cassava mosaic disease (CMD) resistance, dry matter content (DMC) and total carotenoids content (TCC). A number of these trait-linked SNPs have been converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers for downstream application of marker assisted selection. Methods We assayed 13 KASP markers to evaluate their effectiveness in selecting for CMD, DMC and TCC in 1,677 diverse cassava genotypes representing two independent breeding populations in Uganda. Results Five KASP markers had significant co-segregation with phenotypes; CMD resistance (2), DMC (1) and TCC (2), with each marker accounting for at least 30% of the phenotypic variation. Markers located within the chromosomal regions for which strong marker-trait association loci have been characterised (chromosome 12 markers for CMD, chromosome 1 markers for DMC and TCC) had consistently superior ability to discriminate the respective phenotypes. Discussion The results indicate varying discriminatory abilities of the KASP markers assayed and the need for their context-based use for MAS, with PSY2_572 particularly effective in selecting for high TCC. Availing the effective KASP markers on cost-effective genotyping platforms could facilitate practical implementation of marker-assisted cassava breeding for accelerated genetic gains for CMD, DMC and provitamin A carotenoids

Prospects for Genomic Selection in Cassava Breeding

Article purchased; Published online: 28 Sept 2017Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden.Bill & Melinda Gates FoundationUKaidCGIAR Research Program on Roots, Tubers and BananasPeer Revie

Training population optimization for prediction of cassava brown streak disease resistance in west African clones

Published online: 29 Oct 2018; Open Access JournalCassava production in the central, southern and eastern parts of Africa is under threat by cassava brown streak virus (CBSV). Yield losses of up to 100% occur in cases of severe infections of edible roots. Easy illegal movement of planting materials across African countries, and long-range movement of the virus vector (Bemisia tabaci) may facilitate spread of CBSV to West Africa. Thus, effort to pre-emptively breed for CBSD resistance in W. Africa is critical. Genomic selection (GS) has become the main approach for cassava breeding, as costs of genotyping per sample have declined. Using phenotypic and genotypic data (genotyping-by-sequencing), followed by imputation to whole genome sequence (WGS) for 922 clones from National Crops Resources Research Institute, Namulonge, Uganda as a training population (TP), we predicted CBSD symptoms for 35 genotyped W. African clones, evaluated in Uganda. The highest prediction accuracy (r = 0.44) was observed for cassava brown streak disease severity scored at three months (CBSD3s) in the W. African clones using WGS-imputed markers. Optimized TPs gave higher prediction accuracies for CBSD3s and CBSD6s than random TPs of the same size. Inclusion of CBSD QTL chromosome markers as kernels, increased prediction accuracies for CBSD3s and CBSD6s. Similarly, WGS imputation of markers increased prediction accuracies for CBSD3s and for cassava brown streak disease root severity (CBSDRs), but not for CBSD6s. Based on these results we recommend TP optimization, inclusion of CBSD QTL markers in genomic prediction models, and the use of high-density (WGS-imputed) markers for CBSD predictions across population