GENETICS OF RESISTANCE TO GROUNDNUT ROSETTE VIRUS DISEASE

Groundnut Rosette Virus disease (GRD) has long been regarded a major limiting biotic constraint to groundnut production in Sub-Saharan Africa (SSA). The disease is caused by a complex of three viral components that interact in a synergistic fashion resulting into severe crop losses. A study was conducted to better understand the genetics of inheritance of GRD resistance. Nineteen groundnut genotypes among which twelve F2 families populations arising from a 3x4 North Carolina II mating design, were evaluated for their percentage disease severity (PDS) and incidence (PDI). There was significant genetic variability for resistance to GRD among the materials studied with more significant additive gene action as compared to non additive. However, since specific combining ability effects were not so consistent among the F2 family populations, evaluation and testing of progenies alongside with their parents would be more meaningful and selection in the early generations would be the most effective strategy. Further, narrow sense heritability of 53% suggests that prerformance of groundnut progenies could be partly predicted by both parental and individual cross means.La rosette, une maladie virale de l\u2019arachide (GRD) a pendant longtemps \ue9t\ue9 consid\ue9r\ue9e comme une contrainte biotique majeur \ue0 la production de l\u2019arachide en Afrique Sub Saharienne (SSA). La maladie est caus\ue9e par un complexe de trois composants viraux qui interagissent de fa\ue7on synerg\ue9tique causant ainsi de pertes lourdes de la culture. Une \ue9tude \ue9tait men\ue9e afin de mieux comprendre l\u2019acquisition g\ue9n\ue9tique de la r\ue9sistance de GRD. Dix neuf g\ue9notypes d\u2019arachides parmi douze populations de famille F2 provenant de la disposition du mating 3x4 de Nord Caroline II \ue9taient \ue9valu\ue9s sur base de leur pourcentage de s\ue9verit\ue9 (PDS) et incidence maladie (PDI). Une variabilit\ue9 significative de la r\ue9sistance au GRD parmi le mat\ue9riel \ue9tudi\ue9 avec plus d\u2019 action additive significative du g\ue8ne en comparaison \ue0 la non additive. Par ailleurs, du fait que les effets de combinaison des aptitudes n\u2019\ue9taient pas consistants parmi les populations de familles F2, l\u2019\ue9valuation et le test des prog\ue9nies avec leurs parents pourraient \ueatre plus significatif et la s\ue9lection parmi les g\ue9n\ue9rations pr\ue9coces pourrait \ueatre une strat\ue9gie la plus efficace. Aussi, l\u2019heritabilit\ue9 de 53% sugg\ue8re que la performance des prog\ue9nies d\u2019arachide pourrait partiellement \ueatre pr\ue9dit par le moyen de croisements parentaux et individuals

Technological innovations for improving cassava production in sub-Saharan Africa

Open Access Journal; Published online: 21 Jan 2021Cassava is crucial for food security of millions of people in sub-Saharan Africa. The crop has great potential to contribute to African development and is increasing its income-earning potential for small-scale farmers and related value chains on the continent. Therefore, it is critical to increase cassava production, as well as its quality attributes. Technological innovations offer great potential to drive this envisioned change. This paper highlights genomic tools and resources available in cassava. The paper also provides a glimpse of how these resources have been used to screen and understand the pattern of cassava genetic diversity on the continent. Here, we reviewed the approaches currently used for phenotyping cassava traits, highlighting the methodologies used to link genotypic and phenotypic information, dissect the genetics architecture of key cassava traits, and identify quantitative trait loci/markers significantly associated with those traits. Additionally, we examined how knowledge acquired is utilized to contribute to crop improvement. We explored major approaches applied in the field of molecular breeding for cassava, their promises, and limitations. We also examined the role of national agricultural research systems as key partners for sustainable cassava production

Genome-wide diversity and structure variation among lablab [Lablab purpureus (L.) Sweet] accessions and their implication in a forage breeding program

Open Access Article; Published online: 19 Mar 2021Most orphan crops have not been fully sequenced, hence we rely on genome sequences of related species to align markers to different chromosomes. This hinders their utilisation in plant population improvement programs. Utilising the advances in the science of sequencing technologies, the population structure, relatedness, and genetic diversity among accessions can be assessed quickly for better exploitation in forage breeding programs. Using DArTseq technology, we studied the genetic and structural variation in 65 Lablab purpureus (L.) Sweet conserved gene-bank accessions using 9320 DArTseq-based SNPs and 15,719 SilicoDart markers. These markers had a low discriminating ability with mean polymorphic information content (P.I.C.) of 0.14 with DArTseq-based SNPs and 0.13 with SilicoDart markers. However, the markers had a high mean call rate of 73% with DArTseq-based SNPs and 97% with SilicoDart markers. Analysis of molecular variance revealed a high within populations variance (99.4%), indicating a high gene exchange or low genetic differentiation (PhiPT = 0.0057) among the populations. Structure analysis showed three allelic pools in variable clusters of ΔK = 3 and 6. Phylogenetic tree of lablab accessions showed three main groups with variable membership coefficients. Most pairs of accessions (40.3%) had genetic distances between 0.10 and 0.15 for SilicoDart markers, while for DArTseq-based SNPs, (46.5%) had genetic distances between 0.20 and 0.25. Phylogenetic clustering and minimum spanning analysis divided the 65 accessions into three groups, irrespective of their origin. For the first time, this study produced high-density markers with good genom coverage. The utilisation of these accessions in a forage program will base on the information from molecular-based grouping. The outcomes uncovered the presence of noteworthy measure of variety in Uganda, CIAT and ILRI accessions, thus demonstrating an opportunity for further marker-trait-association studies

Parsimonious genotype by environment interaction covariance models for cassava (Manihot esculenta)

Open Access Journal; Published online: 21 Sep 2022The assessment of cassava clones across multiple environments is often carried out at the uniform yield trial, a late evaluation stage, before variety release. This is to assess the differential response of the varieties across the testing environments, a phenomenon referred to as genotype-by-environment interaction (GEI). This phenomenon is considered a critical challenge confronted by plant breeders in developing crop varieties. This study used the data from variety trials established as randomized complete block design (RCBD) in three replicates across 11 locations in different agro-ecological zones in Nigeria over four cropping seasons (2016–2017, 2017–2018, 2018–2019, and 2019–2020). We evaluated a total of 96 varieties, including five checks, across 48 trials. We exploited the intricate pattern of GEI by fitting variance–covariance structure models on fresh root yield. The goodness-of-fit statistics revealed that the factor analytic model of order 3 (FA3) is the most parsimonious model based on Akaike Information Criterion (AIC). The three-factor loadings from the FA3 model explained, on average across the 27 environments, 53.5% [FA (1)], 14.0% [FA (2)], and 11.5% [FA (3)] of the genetic effect, and altogether accounted for 79.0% of total genetic variability. The association of factor loadings with weather covariates using partial least squares regression (PLSR) revealed that minimum temperature, precipitation and relative humidity are weather conditions influencing the genotypic response across the testing environments in the southern region and maximum temperature, wind speed, and temperature range for those in the northern region of Nigeria. We conclude that the FA3 model identified the common latent factors to dissect and account for complex interaction in multi-environment field trials, and the PLSR is an effective approach for describing GEI variability in the context of multi-environment trials where external environmental covariables are included in modeling

Genetic variability and genotype by environment interaction of two major cassava processed products in multi-environments

Open Access Journal; Published online: 17 Oct 2022Conversion of cassava (Manihot esculenta) roots to processed products such as gari and fufu before consumption is a common practice worldwide by cassava end-user for detoxification, prolonged shelf life or profitability. Fresh root and processed product yield are supposed to be equivalent for each genotype, however, that is not the case. Developing genotypes with high product conversion rate is an important breeding goal in cassava as it drives the adoption rates of new varieties. The objective of this study was to quantify the contribution of genetic and genotype-by-environment interaction (GEI) patterns on cassava root conversion rate to gari and fufu. Sixty-seven advanced breeding genotypes from the International Institute of Tropical Agriculture (IITA) were evaluated across eight environments in Nigeria. Root conversion rate means across trials ranges from 14.72 to 22.76% for gari% and 16.96–24.24% for fufu%. Heritability estimates range from 0.17 to 0.74 for trial bases and 0.71 overall environment for gari% and 0.03–0.65 for trial bases and 0.72 overall environment for fufu% which implies that genetic improvement can be made on these traits. Root conversion rate for both gari and fufu% showed a negative but insignificant correlation with fresh root yield and significant positive correlation to Dry Matter content. For all fitted models, environment and interaction had explained more of the phenotypic variation observed among genotypes for both product conversion rates showing the presence of a strong GEI. Wrickle ecovalence (Wi) stability analysis and Geometric Adaptability index (GAI) identified G40 (TMS14F1285P0006) as part of top 5 genotypes for gari% but no overlapping genotype was identified by both stability analysis for fufu%. This genotypic performance across environments suggests that it is possible to have genotype with dual-purpose for high gari and fufu conversion rate

Exploring genotype by environment interaction on cassava yield and yield related traits using classical statistical methods

Open Access Journal; Published online: 18 Jul 2022Variety advancement decisions for root quality and yield-related traits in cassava are complex due to the variable patterns of genotype-by-environment interactions (GEI). Therefore, studies focused on the dissection of the existing patterns of GEI using linear-bilinear models such as Finlay-Wilkinson (FW), additive main effect and multiplicative interaction (AMMI), and genotype and genotype-by-environment (GGE) interaction models are critical in defining the target population of environments (TPEs) for future testing, selection, and advancement. This study assessed 36 elite cassava clones in 11 locations over three cropping seasons in the cassava breeding program of IITA based in Nigeria to quantify the GEI effects for root quality and yield-related traits. Genetic correlation coefficients and heritability estimates among environments found mostly intermediate to high values indicating high correlations with the major TPE. There was a differential clonal ranking among the environments indicating the existence of GEI as also revealed by the likelihood ratio test (LRT), which further confirmed the statistical model with the heterogeneity of error variances across the environments fit better. For all fitted models, we found the main effects of environment, genotype, and interaction significant for all observed traits except for dry matter content whose GEI sensitivity was marginally significant as found using the FW model. We identified TMS14F1297P0019 and TMEB419 as two topmost stable clones with a sensitivity values of 0.63 and 0.66 respectively using the FW model. However, GGE and AMMI stability value in conjunction with genotype selection index revealed that IITA-TMS-IBA000070 and TMS14F1036P0007 were the top-ranking clones combining both stability and yield performance measures. The AMMI-2 model clustered the testing environments into 6 mega-environments based on winning genotypes for fresh root yield. Alternatively, we identified 3 clusters of testing environments based on genotypic BLUPs derived from the random GEI component

Pasting properties of high-quality cassava flour of some selected improved cassava varieties in Tanzania for baking

Open Access ArticlePartial substituting wheat with high-quality cassava flour (HQCF) in bread making would be economically beneficial in Tanzania. However, cassava varieties with the best pasting quality for this use are unknown. In addition, the appropriate time of harvesting the varieties to attain the best pasting quality is also unknown. This study, therefore, aimed at identifying the most appropriate cassava varieties and their appropriate harvesting time that could be used for production of HQCF for baking bread. Nine improved cassava varieties namely Kiroba, Mkuranga1, Pwani, Chereko, Mkumba, Hombolo, Orela, Kizimbani and Kipusa and two local varieties, Albert and Kibandameno were planted in 2020/2021 and 2021/2022 seasons at TARI-Ukiriguru using a split plot design. Harvesting was done at 10 and 12 months after planting (MAP). Pasting characteristics of the HQCF samples were determined at the International Centre of Tropical Agriculture, Dar es salaam, Tanzania using Perten Rapid Visco Analyzer (RVA) Tecmaster equipment, Model: N103802. The results indicated that KIPUSA had the lowest significant setback, while Hombolo had the highest significant setback both at 10 and 12 MAP suggesting that HQCF produced from KIPUSA should be considered for partial substitution of wheat in baking bread that is attractive to consumers

Conversion and validation of uniplex SNP markers for selection of resistance to Cassava Mosaic Disease in Cassava breeding programs

Open Access journal; Published online: 25 Feb 2021Cassava mosaic disease (CMD) is a major viral disease adversely affecting cassava production in Africa and Asia. Genomic regions conferring resistance to the disease have been mapped in African cassava germplasm through biparental quantitative trait loci (QTL) mapping and genome-wide association studies. To facilitate the utilization of these markers in breeding pipelines to support selections, proof-of-concept technical and biological validation research was carried out using independent pre-breeding and breeding populations. Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) assays were designed from three single nucleotide polymorphism (SNP) markers linked to a major resistance locus on chromosome 12 (S12_7926132, S12_7926163) and a minor locus on chromosome 14 (S14_4626854). The designed assays were robust and easy to score with >99% genotype call rate. The overall predictive accuracy (proportion of true positives and true negatives) of the markers (S12_7926132 and S14_4626854) was 0.80 and 0.78 in the pre-breeding and breeding population, respectively. On average, genotypes that carried at least one copy of the resistant allele at the major CMD2 locus had a significantly higher yield advantage. Nevertheless, variation was observed in prediction accuracies for the major locus (S12_7926132) among sub-families from the two populations, suggesting the need for context-specific utilization, for example, by screening for co-segregation of favorable SNP alleles with resistance in the parents being used for crosses. Availability of these validated SNP markers on the uniplex KASP genotyping platform represents an important step in translational genetics toward marker-assisted selection to accelerate introgression of favorable resistant alleles in breeding populations

Genome-wide association mapping and genomic prediction for CBSD resistance in Manihot esculenta

Open Access Journal; Published online: 24 Jan 2018Cassava (Manihot esculenta Crantz) is an important security crop that faces severe yield loses due to cassava brown streak disease (CBSD). Motivated by the slow progress of conventional breeding, genetic improvement of cassava is undergoing rapid change due to the implementation of quantitative trait loci mapping, Genome-wide association mapping (GWAS), and genomic selection (GS). In this study, two breeding panels were genotyped for SNP markers using genotyping by sequencing and phenotyped for foliar and CBSD root symptoms at five locations in Uganda. Our GWAS study found two regions associated to CBSD, one on chromosome 4 which co-localizes with a Manihot glaziovii introgression segment and one on chromosome 11, which contains a cluster of nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes. We evaluated the potential of GS to improve CBSD resistance by assessing the accuracy of seven prediction models. Predictive accuracy values varied between CBSD foliar severity traits at 3 months after planting (MAP) (0.27–0.32), 6 MAP (0.40–0.42) and root severity (0.31–0.42). For all traits, Random Forest and reproducing kernel Hilbert spaces regression showed the highest predictive accuracies. Our results provide an insight into the genetics of CBSD resistance to guide CBSD marker-assisted breeding and highlight the potential of GS to improve cassava breeding

Validation of KASP-SNP markers in cassava germplasm for marker-assisted selection of increased carotenoid content and dry matter content

Open Access Journal; Published online: 12 Oct 2022Provitamin 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 common among pre-school children and pregnant women in developing countries particularly Africa. Dry matter content is a major component of dry yield and thus underlies overall variety performance and acceptability by growers, processors, and consumers. Single nucleotide polymorphism (SNP) markers linked to these traits have recently been discovered through several genome-wide association studies but have not been deployed for routine marker-assisted selection (MAS). This is due to the lack of useful information on markers’ performances in diverse genetic backgrounds. To overcome this bottleneck, technical and biological validation of the loci associated with increased carotenoid content and dry matter content were carried out using populations independent of the marker discovery population. In the present study, seven previously identified markers for these traits were converted to a robust set of uniplex allele-specific polymerase chain reaction (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 the markers’ effectiveness in multiple backgrounds, therefore, further strengthening their value in cassava biofortification to ensure nutritional security as well as dry matter content productivity. Our study provides a framework to guide future marker validation, thus leading to the more routine use of markers in MAS in cassava improvement programs