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Understanding pollen and ovule fertility as factors influencing fruit and seed set is important in cassava breeding. Extended daylength with red light (RL) and plant growth regulators (PGRs) have been used to induce flowering and fruit set in cassava without any reference to effects on pollen viability or ovule fertilizability. This study investigated the effects of field-applied RL and PGR on pollen viability and ovule fertilizability. Panels of cassava genotypes with early or moderate flowering responses were used. RL was administered from dusk to dawn. Two PGRs, 6-benzyl adenine (BA), a cytokinin and silver thiosulphate (STS), an anti-ethylene, were applied. Pollen viability was assessed based on pollen grain diameter, in vitro stainability, in vivo germinability, ovule fertilizability, and ploidy level. Treating flowers with RL increased the pollen diameter from 145.6 in control to 148.5 µm in RL, 78.5 to 93.0% in stainability, and 52.0 to 56.9% in ovule fertilizability in treated female flowers. The fruit set also increased from 51.5 in control to 71.8% in RL-treated female flowers. The seed set followed a similar trend. The ploidy level of pollen from RL-treated flowers increased slightly and was positively correlated with pollen diameter (R2 = 0.09 *), ovule fertilization (R2 = 0.20 *), fruit set (R2 = 0.59 *), and seed set (R2 = 0.60 *). Treating flowers with PGR did not affect pollen diameter but increased stainability from 78.5% in control to 82.1%, ovule fertilizability from 42.9 to 64.9%, and fruit set from 23.2 to 51.9% in PGR-treated female flowers. Combined BA + STS application caused the highest ovule fertilizability, fruit, and seed set efficiency. These results show that RL and PGR treatments increase pollen viability and ovule fertilizability. This is important for planning pollination strategies in cassava breeding programmes.

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Breeding for low-hydrogen-cyanide (HCN) varieties is a major objective of programs targeting boiled cassava food products. To enhance the breeding of low-HCN varieties, knowledge of genetic variation and trait heritability is essential. In this study, 64 cassava clones were established across four locations and evaluated for HCN using three HCN assessment methods: one with a 1 to 9 scale, on with a 0 ppm to 800 ppm scale, and a quantitative assay based on spectrophotometer readings (HCN_Spec). Data were also collected on the weather variables precipitation, relative humidity, and temperature. Highly significant differences were observed among clones (p < 0.001) and locations (p < 0.001). There was also significant clone-environment interactions, varying from p < 0.05 to p < 0.001. Locations Arua and Serere showed higher HCN scores among clones and were associated with significantly higher (p < 0.001) mean daily temperatures (K) and lower relative humidity values (%) across 12 h and 18 h intervals. Within locations, HCN broad sense heritability estimates ranged from 0.22 to 0.64, while combined location heritability estimates ranged from 0.14 to 0.32. Relationships between the methods were positive and strong (r = 0.75-0.92). The 1 to 9 scale is more accurate and more reproducible than either the 0 to 800 ppm scale or spectrophotometric methods. It is expected that the information herein will accelerate efforts towards breeding for low-HCN cassava varieties.

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Flowering in cassava (Manihot esculenta Crantz) is crucial for the generation of botanical seed for breeding. However, genotypes preferred by most farmers are erect and poor at flowering or never flower. To elucidate the genetic basis of flowering, 293 diverse cassava accessions were evaluated for flowering-associated traits at two locations and seasons in Uganda. Genotyping using the Diversity Array Technology Pty Ltd. (DArTseq) platform identified 24,040 single-nucleotide polymorphisms (SNPs) distributed on the 18 cassava chromosomes. Population structure analysis using principal components (PCs) and kinships showed three clusters; the first five PCs accounted for 49.2% of the observed genetic variation. Linkage disequilibrium (LD) estimation averaged 0.32 at a distance of ~2850 kb (kilo base pairs). Polymorphism information content (PIC) and minor allele frequency (MAF) were 0.25 and 0.23, respectively. A genome-wide association study (GWAS) analysis uncovered 53 significant marker-trait associations (MTAs) with flowering-associated traits involving 27 loci. Two loci, SNPs S5_29309724 and S15_11747301, were associated with all the traits. Using five of the 27 SNPs with a Phenotype_Variance_Explained (PVE) ≥ 5%, 44 candidate genes were identified in the peak SNP sites located within 50 kb upstream or downstream, with most associated with branching traits. Eight of the genes, orthologous to Arabidopsis and other plant species, had known functional annotations related to flowering, e.g., eukaryotic translation initiation factor and myb family transcription factor. This study identified genomic regions associated with flowering-associated traits in cassava, and the identified SNPs can be useful in marker-assisted selection to overcome hybridization challenges, like unsynchronized flowering, and candidate gene validation.

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Cassava brown streak disease (CBSD) poses a substantial threat to food security. To address this challenge, we used PlantCV to extract CBSD root necrosis image traits from 320 clones, with an aim of identifying genomic regions through genome-wide association studies (GWAS) and candidate genes. Results revealed strong correlations among certain root necrosis image traits, such as necrotic area fraction and necrotic width fraction, as well as between the convex hull area of root necrosis and the percentage of necrosis. Low correlations were observed between CBSD scores obtained from the 1-5 scoring method and all root necrosis traits. Broad-sense heritability estimates of root necrosis image traits ranged from low to moderate, with the highest estimate of 0.42 observed for the percentage of necrosis, while narrow-sense heritability consistently remained low, ranging from 0.03 to 0.22. Leveraging data from 30,750 SNPs obtained through DArT genotyping, eight SNPs on chromosomes 1, 7, and 11 were identified and associated with both the ellipse eccentricity of root necrosis and the percentage of necrosis through GWAS. Candidate gene analysis in the 172.2kb region on the chromosome 1 revealed 24 potential genes with diverse functions, including ubiquitin-protein ligase, DNA-binding transcription factors, and RNA metabolism protein, among others. Despite our initial expectation that image analysis objectivity would yield better heritability estimates and stronger genomic associations than the 1-5 scoring method, the results were unexpectedly lower. Further research is needed to comprehensively understand the genetic basis of these traits and their relevance to cassava breeding and disease management.

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Cassava, a vital global food source, faces a threat from Cassava Brown Streak Disease (CBSD). CBSD results from two viruses: Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV). These viruses frequently pose challenges to the traditional symptom-based 1-5 phenotyping method due to its limitations in terms of accuracy and objectivity. Quantitative polymerase chain reaction (qPCR) offers precise virus quantification, although high costs hinder its widespread adoption. In this research, we utilized qPCR to measure the viral titer/load of CBSV and UCBSV. The objectives were to evaluate titer variability within the Cycle 2 (C2) population in two different environments, establish connections between viral titers and CBSD severity scores from the 1-5 scoring method, perform Genome-Wide Association Studies (GWAS) to identify genomic regions associated with CBSV and UCBSV titers, and investigate the functional annotated genes. The results demonstrated a significantly higher prevalence of CBSV (50.2%) in clones compared to UCBSV (12.9%) with mixed infections in some cases. Genotypic effects, particularly concerning UCBSV, were significant, with genotype-by-environment effects primarily influencing CBSV titer. GWAS Studies identified genomic regions associated with CBSV and UCBSV titers. Twenty-one SNP markers on chromosomes 10, 13, 17, and 18 exhibited significant associations with CBSV titer, collectively explaining 43.14% of the phenotypic variation. Additionally, 25 SNP markers on chromosomes 1, 2, 4, 5, 8, 11, 12, 13, 16, and 18 were associated with UCBSV titer, and explained 70.71% of the phenotypic variation. No shared genomic regions were identified between CBSV and UCBSV viral titers. Gene ontology analysis also revealed diverse gene functions, especially in transport and catalytic activities. These findings enhance our understanding of virus prevalence, genetics, and molecular functions in cassava plants, offering valuable insights for targeted breeding strategies.

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BACKGROUND: Consumers of boiled cassava in Africa, Latin America and Asia use specific preference criteria to evaluate its cooking quality, in terms of texture, colour and taste. To improve adoption rates of improved cassava varieties intended for consumption after boiling, these preference criteria need to be determined, quantified and integrated as post-harvest quality traits in the target product profile of boiled cassava, so that breeding programs may screen candidate varieties based on both agronomic traits and consumer preference traits. RESULTS: Surveys of various end-user groups identified seven priority quality attributes of boiled cassava covering root preparation, visual aspect, taste and texture. Three populations of contrasted cassava genotypes, from good-cooking to bad-cooking, in three countries (Uganda, Benin, Colombia) were then characterized according to these quality attributes by sensory quantitative descriptive analysis (QDA) and by standard instrumental methods. Consumers' preferences of the texture attributes mealiness and hardness were also determined. By analysis of correlations, the consumers' preferences scores were translated into thresholds of acceptability in terms of QDA scores, then in terms of instrumental measurements (water absorption during boiling and texture analysis). The thresholds of acceptability were used to identify among the Colombian and Benin populations promising genotypes for boiled cassava quality. CONCLUSION: This work demonstrates the steps of determining priority quality attributes for boiled cassava and establishing their corresponding quantitative thresholds of acceptability. The information can then be included in boiled cassava target product profiles used by cassava breeders, for better selection and adoption rates of new varieties. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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Matching crop varieties to their target use context and user preferences is a challenge faced by many plant breeding programs serving smallholder agriculture. Numerous participatory approaches proposed by CGIAR and other research teams over the last four decades have attempted to capture farmers' priorities/preferences and crop variety field performance in representative growing environments through experimental trials with higher external validity. Yet none have overcome the challenges of scalability, data validity and reliability, and difficulties in capturing socio-economic and environmental heterogeneity. Building on the strengths of these attempts, we developed a new data-generation approach, called triadic comparison of technology options (tricot). Tricot is a decentralized experimental approach supported by crowdsourced citizen science. In this article, we review the development, validation, and evolution of the tricot approach, through our own research results and reviewing the literature in which tricot approaches have been successfully applied. The first results indicated that tricot-aggregated farmer-led assessments contained information with adequate validity and that reliability could be achieved with a large sample. Costs were lower than current participatory approaches. Scaling the tricot approach into a large on-farm testing network successfully registered specific climatic effects of crop variety performance in representative growing environments. Tricot's recent application in plant breeding networks in relation to decision-making has (i) advanced plant breeding lines recognizing socio-economic heterogeneity, and (ii) identified consumers' preferences and market demands, generating alternative breeding design priorities. We review lessons learned from tricot applications that have enabled a large scaling effort, which should lead to stronger decision-making in crop improvement and increased use of improved varieties in smallholder agriculture.

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This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties with low cyanogenic potential (hydrogen cyanide potential [HCN]) by using near-infrared spectrometry (NIRS). This technology provides a fast, accurate, and reliable way to determine sample constituents with minimal sample preparation. The study aims to evaluate the effectiveness of machine learning (ML) algorithms such as logistic regression (LR), support vector machine (SVM), and partial least squares discriminant analysis (PLS-DA) in distinguishing between low and high HCN accessions. Low HCN accessions averagely scored 1-5.9, while high HCN accessions scored 6-9 on a 1-9 categorical scale. The researchers used 1164 root samples to test different NIRS prediction models and six spectral pretreatments. The wavelengths 961, 1165, 1403-1505, 1913-1981, and 2491 nm were influential in discrimination of low and high HCN accessions. Using selected wavelengths, LR achieved 100% classification accuracy and PLS-DA achieved 99% classification accuracy. Using the full spectrum, the best model for discriminating low and high HCN accessions was the PLS-DA combined with standard normal variate with second derivative, which produced an accuracy of 99.6%. The SVM and LR had moderate classification accuracies of 75% and 74%, respectively. This study demonstrates that NIRS coupled with ML algorithms can be used to identify low and high HCN accessions, which can help cassava breeding programs to select for low HCN accessions.

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BACKGROUND: Cassava utilization for food and/or industrial products depends on inherent properties of root dry matter content (DMC) and the starch fraction of amylose content (AC). Accordingly, in the present study, near-infrared reflectance spectroscopy (NIRS) models were developed to aid breeding and selection of DMC and AC as critical industrial traits taking care of root sample preparation and cassava germplasm diversity available in Uganda. RESULTS: Upon undertaking calibrations and cross-validations, best models were adopted for validation. DMC in calibration samples ranged from 20 to 45 g 100g-1 , whereas, for amylose content, it ranged from 14 to 33 g 100g-1 . In the validation set, average DMC was 29.5 g 100g-1 , whereas, for amylose content, it was 24.64 g 100g-1 . For DMC, a modified partial least square regression model had regression coefficients (R2 ) of 0.98 and 0.96, respectively, in the calibration and validation set. These were also associated with low bias (-0.018) and ratio of performance deviation that ranged from 4.7 to 5.0. In addition, standard error of prediction values ranged from 0.9 g 100g-1 to 1.06 g 100g-1 . For AC, the regression coefficient was 0.91 for the calibration set and 0.94 for the validation set. A bias equivalent to -0.03 and a ratio of performance deviation of 4.23 were observed. CONCLUSION: These findings confirm the robustness of NIRS in the estimation of dry matter content and amylose content in cassava roots and thus justify its use in routine cassava breeding operations. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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BACKGROUND: Cassava (Manihot esculenta Crantz) is staple food and major source of calories for over 500 million people in sub-Saharan Africa. The crop is also a source of income for smallholder farmers, and has increasing potential for industrial utilization. However, breeding efforts to match the increasing demand of cassava are impeded by its inability to flower, delayed or unsynchronized flowering, low proportion of female flowers and high fruit abortions. To overcome these sexual reproductive bottlenecks, this study investigated the effectiveness of using red lights to extend the photoperiod (RLE), as a gateway to enhancing flowering and fruit set under field conditions. MATERIALS AND METHODS: Panels of cassava genotypes, with non- or late and early flowering response, 10 in each case, were subjected to RLE from dusk to dawn. RLE was further evaluated at low (LL), medium (ML) and high (HL) red light intensities, at ~ ≤ 0.5; 1.0 and 1.5PFD (Photon Flux Density) in µmol m-2 s-1 respectively. Additionally, the effect of a cytokinin and anti-ethylene as plant growth regulators (PGR) and pruning under RLE treatment were examined. RESULTS: RLE stimulated earlier flower initiation in all genotypes, by up to 2 months in the late-flowering genotypes. Height and number of nodes at first branching, particularly in the late-flowering genotypes were also reduced, by over 50%. Number and proportion of pistillate flowers more than doubled, while number of fruits and seeds also increased. Number of branching levels during the crop season also increased by about three. Earlier flowering in many genotypes was most elicited at LL to ML intensities. Additive effects on flower numbers were detected between RLE, PGR and pruning applications. PGR and pruning treatments further increased number and proportion of pistillate flowers and fruits. Plants subjected to PGR and pruning, developed bisexual flowers and exhibited feminization of staminate flowers. Pruning at first branching resulted in higher pistillate flower induction than at second branching. CONCLUSIONS: These results indicate that RLE improves flowering in cassava, and its effectiveness is enhanced when PGR and pruning are applied. Thus, deployment of these technologies in breeding programs could significantly enhance cassava hybridizations and thus cassava breeding efficiency and impact.

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The 5-year project 'Breeding roots, tubers and banana products for end user preferences' (RTBfoods) focused on collecting consumers' preferences on 12 food products to guide breeding programmes. It involved multidisciplinary teams from Africa, Latin America, and Europe. Diverse data types were generated on preferred qualities of users (farmers, family and entrepreneurial processors, traders or retailers, and consumers). Country-based target product profiles were produced with a comprehensive market analysis, disaggregating gender's role and preferences, providing prioritised lists of traits for the development of new plant varieties. We describe the approach taken to create, in the roots, tubers, and banana breeding databases, a centralised and meaningful open access to sensory information on food products and genotypes. Biochemical, instrumental textural, and sensory analysis data are then directly connected to the specific plant record while user survey data, bearing personal information, were analysed, anonymised, and uploaded in a repository. Names and descriptions of food quality traits were added into the Crop Ontology for labelling data in the databases, along with the various methods of measurement used by the project. The development and application of standard operating procedures, data templates, and adapted trait ontologies improved the data quality and its format, enabling the linking of these to the plant material studied when uploaded in the breeding databases or in repositories. Some modifications to the database model were necessary to accommodate the food sensory traits and sensory panel trials. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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Introduction: 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.

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Cassava (Manihot esculenta Crantz) is a staple crop for ~800 million people in sub-Saharan Africa. Its production and productivity are being heavily affected by the two viral diseases: cassava brown streak disease (CBSD) and cassava mosaic disease (CMD), impacting greatly on edible root yield. CBSD is currently endemic to central, eastern and southern Africa, if not contained could spread to West Africa the largest cassava producer and consumer in the continent. Genomic selection (GS) has been implemented in Ugandan cassava breeding for accelerated development of virus resistant and high yielding clones. This study leveraged available GS training data in Uganda for pre-emptive CBSD breeding in W. Africa alongside CMD and fresh root yield (FRW). First, we tracked genetic gain through the current three cycles of GS in Uganda. The mean genomic estimated breeding values (GEBVs), indicated general progress from initial cycle zero (C0) to cycle one (C1) and cycle two (C2) for CBSD traits and yield except for CMD. Secondly, we used foliar data of both CBSD and CMD, as well as harvest root necrosis and yield data to perform cross-validation predictions. Cross-validation prediction accuracies of five GS models were tested for each of the three GS cycles and West African (WA) germplasm as a test set. In all cases, cross-validation prediction accuracies were low to moderate, ranging from -0.16 to 0.68 for CBSD traits, -0.27 to 0.57 for CMD and -0.22 to 0.41 for fresh root weight (FRW). Overall, the highest prediction accuracies were recorded in C0 for all traits tested across models and the best performing model in cross-validation was G-BLUP. Lastly, we tested the predictive ability of the Ugandan training sets to predict CBSD in W. African clones. In general, the Ugandan training sets had low prediction accuracies for all traits across models in West African germplasm, varying from -0.18 to 0.1. Based on the findings of this study, the cassava breeding program in Uganda has made progress through application of GS for most target traits, but the utility of the training population for pre-emptive breeding in WA is limiting. In this case, efforts should be devoted to sharing Ugandan germplasm that possess resistance with the W. African breeding programs for hybridization to fully enable deployment of genomic selection as a pre-emptive CBSD breeding strategy in W. Africa.

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Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem.

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Introduction: Cassava brown streak disease (CBSD) is a major threat to food security in East and central Africa. Breeding for resistance against CBSD is the most economical and sustainable way of addressing this challenge. Methods: This study seeks to assess the (1) performance of CBSD incidence and severity; (2) identify genomic regions associated with CBSD traits and (3) candidate genes in the regions of interest, in the Cycle 2 population of the National Crops Resources Research Institute. Results: A total of 302 diverse clones were screened, revealing that CBSD incidence across growing seasons was 44%. Severity scores for both foliar and root symptoms ranged from 1.28 to 1.99 and 1.75 to 2.28, respectively across seasons. Broad sense heritability ranged from low to high (0.15 - 0.96), while narrow sense heritability ranged from low to moderate (0.03 - 0.61). Five QTLs, explaining approximately 19% phenotypic variation were identified for CBSD severity at 3 months after planting on chromosomes 1, 13, and 18 in the univariate GWAS analysis. Multivariate GWAS analysis identified 17 QTLs that were consistent with the univariate analysis including additional QTLs on chromosome 6. Seventy-seven genes were identified in these regions with functions such as catalytic activity, ATP-dependent activity, binding, response to stimulus, translation regulator activity, transporter activity among others. Discussion: These results suggest variation in virulence in the C2 population, largely due to genetics and annotated genes in these QTLs regions may play critical roles in virus initiation and replication, thus increasing susceptibility to CBSD.

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Cassava, a food security crop in Africa, is grown throughout the tropics and subtropics. Although cassava can provide high productivity in suboptimal conditions, the yield in Africa is substantially lower than in other geographies. The yield gap is attributable to many challenges faced by cassava in Africa, including susceptibility to diseases and poor soil conditions. In this study, we carried out 3'RNA sequencing on 150 accessions from the National Crops Resources Research Institute, Uganda for 5 tissue types, providing population-based transcriptomics resources to the research community in a web-based queryable cassava expression atlas. Differential expression and weighted gene co-expression network analysis were performed to detect 8820 significantly differentially expressed genes (DEGs), revealing similarity in expression patterns between tissue types and the clustering of detected DEGs into 18 gene modules. As a confirmation of data quality, differential expression and pathway analysis targeting cassava mosaic disease (CMD) identified 27 genes observed in the plant-pathogen interaction pathway, several previously identified CMD resistance genes, and two peroxidase family proteins different from the CMD2 gene. Present research work represents a novel resource towards understanding complex traits at expression and molecular levels for the development of resistant and high-yielding cassava varieties, as exemplified with CMD.

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Cassava mosaic geminiviruses (CMGs) and cassava brown streak viruses (CBSVs) cause the highest yield losses in cassava production in Africa. In particular, cassava brown streak disease (CBSD) is and continues to be a significant constraint to optimal cassava production in Eastern and Southern Africa. While CBSD has not been reported in West Africa, its recent rapid spread and damage to cassava productivity in Eastern, and Southern Africa is alarming. The aim of this study was to evaluate Nigerian cassava genotypes in order to determine their responses to CBSD, in the event that it invades Nigeria, the world's largest cassava producer. The study gathered information on whether useful CBSD resistance alleles are present in the elite Nigerian cassava accessions. A total of 1,980 full-sib cassava seedlings from 106 families were assessed in the field at the seedling stage for a year. A subset of 569 clones were selected and assessed for another year at the clonal stage in Namulonge, central Uganda, a known hotspot for CBSD screening. Results indicated that foliar and root incidences and severities varied significantly (p ≤ 0.01, p ≤ 0.001) except for CBSD foliar incidence at 6 months (CBSD6i ). Highest and lowest plot-based heritability estimates for CBSD were registered for CBSD root severity (CBSD rs ) (0.71) and CBSD6i (0.5). Positive and highly significant correlations were noted between CBSD root incidence (CBSD ri ) and CBSD rs (r = 0.90***). Significant positive correlations were also noted between CBSD foliar severity at 3 months (CBSD3s ) and CBSD foliar incidence at 6 months (CBSD6i ) (r = 0.77***), CBSD3s and CBSD rs (r = 0.35***). Fresh root weight (Fresh RW ) negatively correlated with CBSD ri and CBSD rs , respectively (r = -0.21*** and r = -0.22***). Similarly, CBSD3s correlated negatively with cassava mosaic disease severity at 3 (CMD3s ) and 6 months (CMD6s ), respectively (r = -0.25*** and r = -0.21***). Fifteen clones were selected using a non-weighted summation selection index for further screening. In conclusion, results revealed that the elite Nigerian accessions exhibited significant susceptibility to CBSD within 2 years of evaluation period. It is expected that this information will aid future breeding decisions for the improvement of CBSD resistance among the Nigerian cassava varieties.

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Achieving food security for an ever-increasing human population requires faster development of improved varieties. To this end, assessment of genetic gain for key traits is important to inform breeding processes. Despite the improvements made to increase production and productivity of cassava in Uganda at research level, there has been limited effort to quantify associated genetic gains. Accordingly, a study was conducted in Uganda to assess whether or not genetic improvement was evident in selected cassava traits using cassava varieties that were released from 1940 to 2019. Thirty-two varieties developed during this period, were evaluated simultaneously in three major cassava production zones; central (Namulonge), eastern (Serere), and northern (Loro). Best linear unbiased predictors (BLUPs) of the genotypic value for each clone were obtained across environments and regressed on order of release year to estimate annual genetic gains. We observed that genetic trends were mostly quadratic. On average, cassava mosaic disease (CMD) resistance increased by 1.9% per year, while annual genetic improvements in harvest index (0.0%) and fresh root yield (-5 kg per ha or -0.03% per ha) were non-substantial. For cassava brown streak disease (CBSD) resistance breeding which was only initiated in 2003, average annual genetic gains for CBSD foliar and CBSD root necrosis resistances were 2.3% and 1.5%, respectively. It's evident that cassava breeding has largely focused on protecting yield against diseases. This underpins the need for simultaneous improvement of cassava for disease resistance and high yield for the crop to meet its current and futuristic demands for food and industry.

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Cassava production and productivity in Eastern, Central, and Southern Africa are ravaged by cassava brown streak disease (CBSD), causing yield losses of up to 100% when susceptible varieties are grown. Efforts to develop CBSD-resistant clones are underway. However, the methods for screening CBSD resistance currently vary between breeders and pathologists, with the limited empirical data to support their choices. In this study, we used the empirical CBSD foliar and root necrosis data from two breeding populations, termed cycle zero (C0) and cycle one (C1), to assess and compare the effectiveness of the CBSD screening methods of breeders vs. pathologists. On the one hand, the estimates of broad-sense heritability (H 2) for the CBSD root necrosis assessment of breeder ranged from 0.15 to 0.87, while for the assessment method of pathologists, H 2 varied from 0.00 to 0.71 in C0 clones. On the other hand, the marker-based heritability estimates (h 2) for C0 ranged from 0.00 to 0.70 for the assessment method of breeders and from 0.00 to 0.63 for the assessment method of pathologists. For cycle one (C1) population, where both foliar and root necrosis data were analyzed for clones assessed at clonal evaluation trials (CETs) and advanced yield trials (AYTs), H 2 varied from 0.10 to 0.59 for the assessment method of breeders, while the H 2 values ranged from 0.09 to 0.35 for the CBSD computation method of pathologists. In general, higher correlations were recorded for foliar severity from the assessment method of breeders (r = 0.4, p ≤ 0.01 for CBSD3s and r = 0.37, p ≤ 0.01 for CBSD6s) in C1 clones evaluated at both clonal and advanced breeding stages than from the approach of pathologists. Ranking of top 10 C1 clones by their indexed best linear unbiased predictors (BLUPs) for CBSD foliar and root necrosis showed four overlapping clones between clonal and advanced selection stages for the method of breeders; meanwhile, only a clone featured in both clonal and advanced selection stages from the CBSD assessment method of pathologists. Overall, the CBSD assessment method of breeders was more effective than the assessment method of pathologists, and thus, it justifies its continued use in CBSD resistance breeding.

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Global efforts are underway to develop cassava with enhanced levels of provitamin A carotenoids to sustainably meet increasing demands for food and nutrition where the crop is a major staple. Herein, we tested the effectiveness of genomic selection (GS) for rapid improvement of cassava for total carotenoids content and associated traits. We evaluated 632 clones from Uganda's provitamin A cassava breeding pipeline and 648 West African introductions. At harvest, each clone was assessed for level of total carotenoids, dry matter content, and resistance to cassava brown streak disease (CBSD). All clones were genotyped with diversity array technology and imputed to a set of 23,431 single nucleotide polymorphic markers. We assessed predictive ability of four genomic prediction methods in scenarios of cross-validation, across population prediction, and inclusion of quantitative trait loci markers. Cross-validations produced the highest mean prediction ability for total carotenoids content (0.52) and the lowest for CBSD resistance (0.20), with G-BLUP outperforming other models tested. Across population, predictions showed low ability of Ugandan population to predict the performance of West African clones, with the highest predictive ability recorded for total carotenoids content (0.34) and the lowest for CBSD resistance (0.12) using G-BLUP. By incorporating chromosome 1 markers associated with carotenoids content as independent kernel in the G-BLUP model of a cross-validation scenario, prediction ability slightly improved from 0.52 to 0.58. These results reinforce ongoing efforts aimed at integrating GS into cassava breeding and demonstrate the utility of this tool for rapid genetic improvement.

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