Identification of F1 cassava (Manihot esculenta Crantz) progeny using microsatellite markers and capillary electrophoresis

Generation of genetic diversity is necessary in improving on the potential of cassava when faced with various biotic and abiotic challenges. Presently, cassava breeders are breeding for a number of traits, such as drought tolerance, early root bulking, yield, starch, beta-carotene, protein, dry matter, pest and disease resistance, by relying on genetic diversity that exists in manihot esculenta germplasm. Controlled pollination is one of the main methods used to generate genetic diversity in cassava. However, the process of controlled pollination especially in an open field is prone to contamination by illegitimate pollen right from the time of pollination, seed collection, nursery bed establishment to planting of the trials. Therefore, authentication of the progeny obtained from cas-sava crosses is very important for genetic studies. Twelve informative microsatellite markers were used to verify the authenticity of 364 F1 progeny thought to come from four controlled parental crosses. The transmission of each allele at nine microsatellite loci was tracked from parents to progeny in each of the four Namikonga-derived F1 cassava families. Out of the 364 F1 progeny, 317 (87.1%) were true-to-type, 44 (12.1%) were a product of self-pollination and 3 (0.8%) were a product of open pollination. The consistency of the results obtained using microsatellite markers makes this technique a reliable tool for assessing the purity of progeny generated from cassava crosses

Comparison of Near-infrared Spectroscopy with other options for total carotenoids content phenotyping in fresh cassava roots

This study compared the relationship of different phenotyping methods including iCheckTM CAROTENE (iCheck), Chromameter, colour chart and visible/near-infrared spectroscopy (Vis/NIRS) used in quantifying total carotenoids content (TCC) in fresh cassava roots. Using a total of 194 cassava clones harvested from the International Institute of Tropical Agriculture (IITA), Ibadan, we compared the repeatability precision, accuracy of measurement and correlations of these phenotyping methods. From the results, Vis/NIRS-analyzed TCC had high and positive correlations with Chromameter and Color chart (r = 0.91 and 0.71, respectively). On the other hand, the result revealed somewhat moderate correlation (r = 0.67) between Vis/NIRS and iCheck measurements. Vis/NIRS, iCheck and chromameter methods gave high and nearly equal heritability estimates (0.95, 0.98 and 0.98, respectively) illustrating high repeatability precision of these methods; an indication that they can be used for germplasm selection in the early stages of breeding. Conversely, with Bland-Altman plot at 95% confidence level, the accuracy of iCheck was not comparable with that of Vis/ NIRS. The information derived from this analysis directly contributes towards the genetic improvement of root quality traits in cassava and facilitates the sharing of data across cassava breeding consortium

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

Genetic Gains for Yield and Virus Disease Resistance of Cassava Varieties Developed Over the Last Eight Decades in Uganda

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

Limits of phytosanitation and host plant resistance towards the control of cassava viruses in Uganda

Published online: 30 Sept 2017Cassava (Manihot esculenta Crantz) and the viruses that infect it, notably cassava mosaic virus and cassava brown streak viruses, have a unique history of co-evolution and co-existence. While cassava originated in South America, both viruses and the diseases they cause have largely been limited to the East African region, where they have, and continue to be key yield-robbing stresses. For sustainable control, we assume that deployment of resistant varieties when carefully combined with phytosanitation will combat these viruses. We have thus generated empirical data and tested the limits, i.e., how long this strategy can last. This entailed the comparison of elite cassava varieties, one set of virus-indexed tissue culture plantlets, and the other set, re-cycled planting materials under farmer’s cyclic propagation for 6-23 years. Trials were established at diverse sites in Uganda. We observed that both officially-released and unofficially-released cassava varieties are common in farmer’s fields; these varieties have varying susceptibility levels to viruses. Worrisome was that some officially-released varieties like NASE 3 registered cassava mosaic disease (CMD) incidences of up to 71% (virus-indexed), which was not any different from its re-cycled counterparts. Other varieties like NASE 14 have maintained high levels of CMD resistance six years after official release. Predominant re-cycled cassava varieties notably TME 204, I92/0057, TME 14, and to a limited extent NASE 14, are key reservoirs for cassava brown streak disease (CBSD) associated viruses. These findings highlight the limits of phytosanitation, i.e., in areas like Kaberamaido associated with high CMD pressure, varieties NASE 1 and NASE 3 can not be recommended; on the contrary, these varieties can be deployed in Kalangala, where they can survive with phytosanitation. And for CBSD, the findings justify the urgent need for phytosanitation (community-led) and development of varieties with higher levels of resistance and/or tolerance, as no immune variety has so far been identified

A method for generating virus-free cassava plants to combat viral disease epidemics in Africa

Here, we report a method to clean cassava plants from viral infections that cause cassava mosaic and brown streak diseases in Africa. Infected plants of resistant or tolerant varieties from Malawi, Mozambique, Kenya, Tanzania and Uganda were cleaned in the UK using a combination of tissue culture, chemotherapy and thermotherapy. In the first cycle of our virus-indexing procedure, we successfully cleaned 27 of the 31 varieties (87%), and after an additional three cleaning cycles, all plants were virus-free. Virus-free tissue-cultured plants were shipped back to Africa for distribution to farmers. This first cross-boundary effort provides important lessons for mitigating the two-major cassava viral diseases

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

Expansion of the cassava brown streak pandemic in Uganda revealed by annual field survey data for 2004 to 2017

Funder: Uganda Government Association for Strengthening Agricultural Research in Eastern and Central AfricaFunder: Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation)Abstract: Cassava brown streak disease (CBSD) is currently the most devastating cassava disease in eastern, central and southern Africa affecting a staple crop for over 700 million people on the continent. A major outbreak of CBSD in 2004 near Kampala rapidly spread across Uganda. In the following years, similar CBSD outbreaks were noted in countries across eastern and central Africa, and now the disease poses a threat to West Africa including Nigeria - the biggest cassava producer in the world. A comprehensive dataset with 7,627 locations, annually and consistently sampled between 2004 and 2017 was collated from historic paper and electronic records stored in Uganda. The survey comprises multiple variables including data for incidence and symptom severity of CBSD and abundance of the whitefly vector (Bemisia tabaci). This dataset provides a unique basis to characterize the epidemiology and dynamics of CBSD spread in order to inform disease surveillance and management. We also describe methods used to integrate and verify extensive field records for surveys typical of emerging epidemics in subsistence crops