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Map showing the distribution of RYMV in various countries in Africa. Note: countries with RYMV epidemics are labelled (adapted from Banwo 2002).
Source publication
Rice is the world’s second most produced staple cereal crop after wheat. Currently, rice production and consumption have steadily increased in Sub-Saharan Africa (SSA). To date, rice is the largest imported commodity crop in the region. The low productivity is due to a number of biotic and abiotic stresses, and socio-economic constraints. Among the...
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Rice cultivars from japonica and indica lineage possess differential resistance against blast fungus on an account genetic divergence. Whether different rice cultivars also show distinct metabolomic changes in response to P. oryzae, and their role in host resistance, are poorly understood. Here, we examine the responses of six different rice cultiv...
Citations
... RYMV is transmitted by insect vectors through the tripartite connection between plants, insects and viruses and or mechanical movement [26]. The virus is transmitted by several species of beetles, most of which belong to the Coleoptera: Chrysomelidae [27]. ...
... 4 Farm implements, human activities (such as fertilizer application), and plant-to-plant contact, also result in mechanical transmission of the virus. Wind-mediated leaf-to-leaf contact, guttation fluids and irrigation water can also spread the virus [26]. Grazing livestock on infected field spread the viruses as they trample upon infected plant to healthy plants [37]. ...
... There is drastic reduction in the yield of the plant and the few grains that would develop turn brown. Infected plants might eventually die [26]. ...
Rice (Oryza spp.) is mostly grown directly from seed and sown on wet or dry seed beds or usually used as transplants on nursery bed. With all the economically important viral diseases in the world, Rice yellow mottle virus (RYMV), is only prevalent in rice-growing countries in Africa. RYMV had turned out to be the main rice production constraint in Africa, throughout the last 20–25 years, causing yield loss of 10 to 100%, depending on age of the plant at the time of infection, degree of varietal susceptibility and the exiting climatic conditions. Good agricultural practices and utilization of biotechnological tools in the development of improved resistant cultivars have been extensively active in controlling the disease. This review focused on RYMV, its epidemiology, serological and molecular typing, disease management and the way forward for sustainable rice production.
... Identifying RGMoV in these diverse locations suggests the necessity for ongoing monitoring of this virus, especially considering several other sobemoviruses are of high economic importance, such as RYMV and papaya lethal yellowing virus (PLYV) [4]. For instance, RYMV is responsible for significant rice yield losses in sub-Saharan Africa, ranging from 20% to 100% [49]. This virus has also been detected in other species of the Poaceae family [8,[50][51][52] (formerly Gramineae), includes various grasses [53], indicating its potential to affect a wide range of plants. ...
Ryegrass mottle virus (RGMoV; genus: Sobemovirus ) is a single-stranded positive RNA virus with a 30 nm viral particle size. It exhibits T = 3 symmetry with 180 coat protein (CP) subunits forming a viral structure. The RGMoV genome comprises five open reading frames that encode P1, Px, a membrane-anchored 3C-like serine protease, a viral genome-linked protein, P16, an RNA-dependent RNA polymerase, and CP. The RGMoV genome size varies, ranging from 4175 nt (MW411579.1) to 4253 nt (MW411579.1) in the deposited sequences. An earlier deposited RGMoV complete genome sequence of 4212 nt length (EF091714.1) was used to develop an infectious complementary DNA (icDNA) construct for in vitro gRNA transcription from the T7 promoter. However, viral infection was not induced when the transcribed gRNA was introduced into oat plants, indicating the potential absence of certain sequences in either the 5’ or 3’ untranslated regions (UTR) or both. The complete sequence of the 3’ UTR was determined through 3’ end RACE, while the 5’ UTR was identified using high-throughput sequencing (HTS)-RNA-Seq to resolve the potential absences. Only the icDNA vector containing the newly identified UTR sequences proved infectious, resulting in typical viral infection symptoms and subsequent propagation of progeny viruses, exhibiting the ability to cause repeated infections in oat plants after at least one passage. The successful generation of icDNA highlighted the synergistic potential of utilizing both methods when a single approach failed. Furthermore, this study demonstrated the reliability of HTS as a method for determining the complete genome sequence of viral genomes.
... Selection on interbred progeny has contributed to the local diversity of rice in the region [54], which can be better understood with the phylogeny. In Africa and America, selection on rice tends to be more environmentally oriented [55,56]. In China, breeders have focused on taking advantage of hybrid vigor. ...
Asian rice (Oryza sativa L.) has become a model for understanding gene functions and domestication in recent decades; however, its own diversification is still controversial. Although the division of indica and japonica and five subgroups (aus, indica (sensu stricto), japonica (sensu stricto), tropical japonica, and aromatic) are broadly accepted, how they are phylogenetically related is not transparent. To clarify their relationships, a sample of 121 diverse genes was chosen here from 12 Oryza genomes (two parental and ten O. sativa (Os)) in parallel to allow gene genealogy-based mutation (GGM) analysis. From the sample, 361 Os mutations were shared by two or more subgroups (referred to here as trans mutations) from 549 mutations identified at 51 Os loci. The GGM analysis and related tests indicates that aus diverged from indica at a time significantly earlier than when tropical japonica split from japonica. The results also indicate that aromatic was selected from hybrid progeny of aus and tropical japonica and that all five subgroups share a significant number of the early mutations identified previously. The results suggest that aus, tropical japonica, and aromatic emerged sequentially within the most recent 4–5 millennia of rice domestication after the split of indica and japonica.
... Since then, this virus has progressively been reported in almost all rice-producing countries of sub-Saharan Africa and Madagascar (Abo et al., 1997;Pinel-Galzi et al., 2015). Endemic to Africa, RYMV has become one of the most important biotic constraints to rice production in Africa (Kouassi et al., 2005;Savary et al., 2019;Séré et al., 2013), where it causes large yield losses in most rice-growing agroecosystems (Agnoun et al., 2019;Suvi et al., 2018). ...
Rice yellow mottle virus (RYMV) has persisted as a major biotic constraint to rice production in Africa. However, no data on RYMV epidemics were available in Ghana, although it is an intensive rice-producing country. Surveys were performed from 2010 to 2020 in eleven rice-growing regions of Ghana. Symptom observations and serological detections confirmed that RYMV is circulating in most of these regions. Coat protein gene and complete genome sequencings revealed that RYMV in Ghana almost exclusively belongs to the strain S2, one of the strains covering the largest area in West Africa. We also detected the presence of the S1ca strain which is being reported for the first time outside its area of origin. These results suggested a complex epidemiological history of RYMV in Ghana and a recent expansion of S1ca to West Africa. Phylogeographic analyses reconstructed at least five independent RYMV introductions in Ghana for the last 40 years, probably due to rice cultivation intensification in West Africa leading to a better circulation of RYMV. In addition to identifying some routes of RYMV dispersion in Ghana, this study contributes to the epidemiological surveillance of RYMV and helps to design disease management strategies, especially through breeding for rice disease resistance.
... RYMV disease causes 10-100% yield loss depending on plant age, cultivar susceptibility, and environmental factors (Kouassi et al. 2005). Therefore, RYMV is considered a major constraint on rice production in sub-Saharan Africa and Madagascar (Savary et al. 2019;Suvi et al. 2019). ...
Rice yellow mottle virus (RYMV) causes severe rice ( Oryza sativa L.) yield loss. It has been endemic to sub-Saharan Africa and Madagascar since 1966. Transmission (plant community level) and long-dispersal (regional and continental scale) models have been established but viral spread in farming communities continues, while the conditions causing local disease outbreaks remain unclear. We hypothesized that local outbreaks, comprising inter-plot virus spread and intra-plot disease aggravation, are significantly associated with individual farmers’ attributes and agronomic practices. To test this hypothesis, spatial autoregressive models were constructed using variables collected by visual observation and farmer interviews. Field surveys were conducted during four consecutive cropping seasons from 2011 to 2013 in the Lower Moshi Irrigation Scheme of Kilimanjaro, Tanzania. Our models detected spatial dependence in inter-plot virus spread, but not in intra-plot disease aggravation. The probability of inter-plot virus spread increased with use of the IR64 cultivar (26.9%), but decreased with straw removal (27.8%) and crop rotation (47.7%). The probability of intra-plot disease aggravation decreased with herbicide application (24.3%) and crop rotation (35.4%). A simple cost-benefit analysis suggested that inter-plot virus spread should be mitigated by cultivar replacement and straw removal. When disease severity is critical, intra-plot disease aggravation should be inhibited by herbicide application, and rice should be rotated with other crops. This is the first study to upscale the spatial autoregressive model from the experimental field level to the farming community level, by obtaining variables through easy-to-implement techniques such as visual observation and farmer interview. Our models successfully identified candidate agronomic practices for the control of RYMV. However, as the causal relationships between agronomic practices and RYMV outbreaks remain unknown, field trials are needed to develop robust control measures.
... In East and Southern Africa region, Tanzania is the second largest producer of rice after Madagascar. Rice is ranked as the second most important staple crop after maize (Zea mays) in Tanzania [6,7]. ...
... The low productivity of rice in Tanzania is caused by a combination of biotic and abiotic stresses, and socio-economic constraints [8]. The rice yellow mottle virus (RYMV) disease Agronomy 2021, 11, 12 2 of 16 has been identified as a major biotic constraint limiting rice productivity in SSA countries including Tanzania [7,9]. The disease has since become endemic in all the rice-growing regions under both rain-fed and irrigated production farming systems [10]. ...
Selecting genetically diverse and complementary parental lines and superior crosses are pre-requisites in developing improved cultivars. The objectives of this study were to determine the combining ability effects and gene action conditioning rice yellow mottle virus disease (RYMVD) resistance and agronomic traits in rice (Oryza sativa L.). Ten parental lines and their 45 F2 progenies were field evaluated in three locations using a 5 × 11 alpha lattice design with two replications. The genotype × site interaction effects were significant (p < 0.05) for the number of tillers (NT), number of panicles per plant (NPP), number of grains per panicle (NGP), percentage of filled grains (PFG), thousand grain weight (TGW), RYMVD resistance and grain yield (GY). The analysis of general and specific combining ability (GCA and SCA) indicated involvement of both additive and non-additive gene action governing inheritance of traits. High GCA/SCA ratio estimate revealed additive genetic effect was predominant. Parental lines Mwangaza, Lunyuki, Salama M-57, Salama M-19, IRAT 256 and Salama M-55, which had negative GCA effects for RYMVD, and families such as SARO 5 × Salama M-55, IRAT 245 × Rangimbili, Rangimbili × Gigante and Rangimbili × Mwangaza, which had negative SCA effects for RYMVD, were selected for RYMV resistance breeding. The crosses Rangimbili × Gigante, Gigante × Salama M-19 and Rangimbili × Salama M-55 were selected due to their desirable SCA effects for GY. The predominance of additive gene effects for agronomic traits and RYMVD resistance in the present breeding populations suggested that rice improvement could be achieved through gene introgression using recurrent selection.
... This is reflected by the rice production loss analyses (heatmaps), in which we find some countries to suffer high losses, with the greatest predicted for Liberia and Sierra Leone. Despite this data, these countries are reported to suffer less economic damage due to their cropping systems (uplands rice crops), which are less susceptible to pulla group attack (Mogga et al., 2012;Oludare et al., 2016;Suvi, Shimelis & Laing, 2019). In fact, according to Oludare et al. (2016), uplands crops can resist RYMV attack better than lowland and irrigated croplands, which are instead widely used in Central Africa Republic, Madagascar, and Guinea. ...
Aims
Rice is a staple food for many countries, being fundamental for a large part of the worlds’ population. In sub-Saharan Africa, its importance is currently high and is likely to become even more relevant, considering that the number of people and the per-capita consumption are both predicted to increase. The flea beetles belonging to the Chaetocnema pulla species group ( pulla group), a harmful rice pest, are an important vector of the Rice Yellow Mottle Virus, a disease which leads even to 80–100% yield losses in rice production. We present a continental-scale study aiming at: (1) locating current and future suitable territories for both pulla group and rice; (2) identifying areas where rice cultivations may occur without suffering the presence of pulla group using an Ecological Niche Modelling (ENM) approach; (3) estimating current and future connectivity among pulla group populations and areas predicted to host rice cultivations, based on the most recent land-use estimates for future agricultural trends; (4) proposing a new connectivity index called “Pest Aggression Index” (PAI) to measure the agricultural susceptibility to the potential future invasions of pests and disease; (5) quantifying losses in terms of production when rice cultivations co‐occur with the pulla group and identifying the SSA countries which, in the future inferred scenarios, will potentially suffer the greatest losses.
Location
Sub-Saharan Africa.
Methods
Since the ongoing climate and land-use changes affect species’ distributions, we first assess the impact of these changes through a spatially-jackknifed Maxent-based Ecological Niche Modelling in GIS environment, for both the pulla group and rice, in two climatic/socioeconomic future scenarios (SSP_2.45 and 3.70). We then assess the connectivity potential of the pulla group populations towards rice cultivations, for both current and future predictions, through a circuit theory-based approach (Circuitscape implemented in Julia language). We finally measure the rice production and GPD loss per country through the spatial index named “Pest Aggression Index”, based on the inferred connectivity magnitude.
Results
The most considerable losses in rice production are observed for Liberia, Sierra Leone and Madagascar in all future scenarios (2030, 2050, 2070). The future economic cost, calculated as USD lost from rice losses/country’s GDP results are high for Central African Republic (−0.6% in SSP_2.45 and −3.0% in SSP_3.70) and Guinea–Bissau (−0.4% in SSP_2.45 and −0.68% in SSP_3.70), with relevant losses also obtained for other countries.
Main conclusions
Since our results are spatially explicit and focused on each country, we encourage careful land-use planning. Our findings could support best practices to avoid the future settlement of new cultivations in territories where rice would be attacked by pulla group and the virus, bringing economic and biodiversity losses.
... Rice yields in Tanzania remain low, with yields of 1.0 and 1.5 tons per hectare (t ha −1 ) compared to the yield potential of the crop of 5.0 t ha −1 [6,7]. The low yields are caused by biotic, abiotic, and socio-economic constraints prevalent in sub-Sahara Africa [8][9][10]. ...
... Rice yellow mottle virus (RYMV) disease is the major biotic constraint under both the rain-fed and irrigated rice production agro-ecologies in Tanzania [10,11]. Due to RYMV infection, yield losses between 20 and 100% have been recorded in susceptible rice varieties [12][13][14]. ...
... RYMV transmission and distribution is mainly facilitated by insect vectors, irrigation water, wind, field workers, and farm animals [19]. Infected volunteer rice plants from a previous crop are ideal sources of RYMV infection to newly planted and healthy crops [10]. Several chewing insect species, notably the Chrysomelid beetles (Sesselia pusilla, Chaetocnema pulla, Trichispa sericea, Dicladispa viridicyanea) and grasshoppers (Conocephalus merumontanus) are among the key vectors that transmit RYMV from cultivated rice, wild hosts, and weeds to healthy rice crop stands [20]. ...
Rice (Oryza species) is a commercial crop worldwide. Across Africa, the potential yield and quality of rice is diminished by a lack of high performance, locally adapted varieties, and the impact of rice yellow mottle virus (RYMV). The objective of this study was to assess the performance of a diverse collection of rice germplasm for RYMV resistance and agronomic traits, and to select promising lines for breeding for Tanzanian conditions. Fifty-four rice genotypes were field evaluated in two important rice production sites (Ifakara and Mkindo) in Tanzania, which are recognized as RYMV hotspots, using a 6 × 9 alpha lattice design with two replications. There was significant (p < 0.05) genotypic variation for agronomic traits and RYMV susceptibility in the tested germplasm. Seven genotypes with moderate to high RYMV resistance were identified, including Salama M-57, SSD1, IRAT 256, Salama M-55, Mwangaza, Lunyuki, and Salama M-19, which were identified as new sources of resistance genes. Positive and significant correlations were detected between grain yield and number of panicles per plant (NPP), panicle length (PL), number of grains per panicle (NGP), percentage-filled grains (PFG), and thousand-grain weight (TGW), which are useful traits for simultaneous selection for rice yield improvement. A principal component analysis allocated five principal components, accounting for 79.88% of the total variation present in the assessed germplasm collection. Traits that contributed most to variability included NPP, number of tillers/plant (NT), PL, grain yield (GY), and days to 50% flowering (DFL). The genotypes Rangimbili, Gigante, and SARO possess complementary agronomic traits and RYMV resistance, and can be recommended for further evaluation, genetic analysis, and breeding.
... Restricted distributions were further supported by the discovery of a spatially localized and hypervirulent pathotype of RYMV that overcomes all known sources of high resistance in West Africa . Restricted pathotype distributions serve as a reference for the use of landraces of rice that are adapted to local environments as sources for breeding rice cultivars with RYMV resistance in Africa (Suvi et al. 2019). ...
The genomics era has revolutionized studies of adaptive evolution by monitoring large numbers of loci throughout the genomes of many individuals. Ideally, the investigation of emergence in plant viruses requires examining the population dynamics of both virus and host, their interactions with each other, with other organisms and the abiotic environment. Genetic mechanisms that affect demographic processes are now being studied with high-throughput technologies, traditional genetics methods, and new computational tools for big-data. In this review, we discuss the utility of these approaches to monitor and detect changes in virus populations within cells and individuals, and over wider areas across species and communities of ecosystems. The advent of genomics in virology has fostered a multidisciplinary approach to tackling disease risk. The ability to make sense of the information now generated in this integrated setting is by far the most substantial obstacle to the ultimate goal of plant virology to minimize the threats to food security posed by disease. To achieve this goal, it is imperative to understand and forecast how populations respond to future changes in complex natural systems.
... In Nigeria, an increase in the incidence of the disease was observed in addition to increase in severity from 30 to 90 % after one year period (Odedara et al., 2016). No variety is yet commercially available that has both high resistance and other desirable agronomic traits (Kouassi et al., 2005;Suvi et al., 2018). In Ghana, the most popular rice varieties are the Jasmine types but they very susceptible to RYMV disease (Asante et al., 2013;Traore et al., 2015). ...
Rice yellow mottle virus (RYMV) is the most damaging viral disease of rice in Africa and can cause yield losses of up to 100%. The objective of this study was to characterize newly introduced rice lines from Korea into Ghana for their reaction to RYMV infection. One hundred and seventy-two rice lines from Korea were screened for their level of resistance RYMV in a screen house at Fumesua, Ghana. Four checks consisting of two highly resistant lines (Tog7291 and Gigante with rymv1-2 (resistant gene1-allele2) and rymv2 (resistant gene2) respectively), a moderately resistant line (CRI-Amankwatia) and a susceptible cultivar Jasmine 85 were used. The experiment was carried out in a 4 x 44 lattice design with four replicates. Screening for RYMV resistance was conducted by visual symptom scoring and virus-assessment through serology using enzyme linked immunosorbent assay (ELISA) test. Disease incidence and severity were assessed from 2 to 42 dpi. Data for disease severity and incidence were transformed (Log x+1) for ANOVA.
Five lines (8261112, 8261119, 8261133, 8261588, and 8261634) were identified to be highly resistant to the disease just like Tog7291 and Gigante. The study also revealed 24 lines that were resistant but not grouping with Tog7291 and Gigante, whereas 100 moderately resistant lines clustered with the moderately resistance check CRI-Amankwatia in a distinct group. Forty-three (43) susceptible lines were identified with the susceptible check Jasmine 85 falling in this group. No highly susceptible line was identified. The newly idenfied resistant genotypes can be used by breeders to develop RYMV resistant varieties.
