Farmer and Field Survey in Cassava-Growing Districts of Rwanda Reveals Key Factors Associated With Cassava Brown Streak Disease Incidence and Cassava Productivity

Cassava (Manihot esculenta Crantz) is a vital crop in Rwanda where it ranks as the third most consumed staple. However, cassava productivity remains below its yield potential due to several constraints, including important viral diseases, such as cassava brown streak disease (CBSD). Because various factors can be addressed to mitigate the impact of viral diseases, it is essential to identify routes of virus contamination in the cassava agrosystems from the seed system to farmer's practices and knowledge. The present study aimed at (1) assessing the current cassava seed system and farmers' practices and their knowledge of the biotic constraints to cassava production, (2) determining the status of CBSD as well as critical factors associated with its spread through the seed system channels, and (3) determining factors that influence cassava productivity in Rwanda. A cross-sectional study was carried out from May to September 2019 in 13 districts of Rwanda. A total of 130 farmers and cassava fields were visited, and the incidence and severity of CBSD were evaluated. CBSD was detected in all cassava-producing districts. The highest field incidence of CBSD was recorded in the Nyanza district (62%; 95% CI = 56–67%) followed by the Bugesera district (60%; 95% CI = 54–65%), which recorded the highest severity score of 3.0 ± 0.6. RT-PCR revealed the presence of CBSD at the rate of 35.3%. Ugandan cassava brown streak virus was predominant (21.5%) although cassava brown streak virus was 4% and mixed infection was 10%. An informal cassava seed system was dominant among individual farmers, whereas most cooperatives used quality seeds. Cassava production was found to be significantly influenced by the use of fertilizer, size of the land, farming system, cassava viral disease, and type of cassava varieties grown (p < 0.001). Disease management measures were practiced by a half of participants only. Factors found to be significantly associated with CBSD infection (p < 0.05) were the source of cuttings, proximity to borders, age of cassava, and knowledge of CBSD transmission and management.

PAL1 gene of the phenylpropanoid pathway increases resistance to the Cassava brown streak virus in cassava

Background The phenylalanine ammonia lyase genes play crucial role in plant response to biotic and abiotic stresses. In this study, we characterized the role of PAL genes in increasing resistance to the Cassava brown streak virus that causes the economically important cassava brown streak disease (CBSD) on cassava in Africa. Methods The whole transcriptomes of eight cassava varieties differing in resistance to CBSD were obtained at 1, 5 and 8 weeks after CBSV infection. Results Analysis of RNA-Seq data identified the overexpression of PAL1, PAL2, cinnamic acid and two chalcone synthase genes in CBSD-resistant cassava varieties, which was subsequently confirmed by RT-qPCR. The exogenous application of Acibenzolar-S-Methyl induced PAL1 gene expression to enhance resistance in the susceptible var. Kalawe. In contrast, the silencing of PAL1 by RNA interference led to increased susceptibility of the resistant var. Kaleso to CBSD. Conclusions PAL1 gene of the phenylpropanoid pathway has a major role in inducing resistance to CBSD in cassava plants and its early induction is key for CBSD resistance.

Maf/ham1-like pyrophosphatases, host-specific partners of viral RNA-dependent RNA polymerases

Cassava brown streak disease (CBSD), dubbed the Ebola of plants, is a serious threat for food security in Africa caused by two viruses of the family Potyviridae: cassava brown streak virus (CBSV) and Ugandan (U)CBSV. Intriguingly, U/CBSV, along with another member of this family and one secoviridae, are the only known RNA viruses in nature encoding a protein of the Maf/ham1-like family, a group of widespread pyrophosphatase of non-canonical nucleotides (ITPase) expressed by all living organisms. Despite the socio-economic impact of CDSD, the relevance and role of this atypical viral factor has not been yet established. Here, using an infectious cDNA clone and reverse genetics, we demonstrate that UCBSV requires the ITPase activity in cassava, but not in the model plant Nicotiana benthamiana. HPLC-MS/MS experiments show that, quite likely, this host-specific constraint is due to an unexpected high concentration of non-canonical nucleotides in cassava. Finally, protein analyses and experimental evolution of mutant viruses indicate that keeping a fraction of the yielded UCBSV ITPase covalently bound to the viral RNA-dependent RNA polymerase (RdRP) optimizes viral fitness, and this seems to be a feature shared by the other members of the Potyviridae family expressing Maf/ham1-like proteins. All in all, our work (i) reveals that the over-accumulation of non-canonical nucleotides in the host might have a key role in antiviral defense, and (ii) provides the first example of an RdRP-ITPase partnership, reinforcing the idea that RNA viruses are incredibly inventive at adaptation to different host setups.

Differential Tropism in Roots and Shoots of Resistant and Susceptible Cassava (Manihot esculenta Crantz) Infected by Cassava Brown Streak Viruses

Cassava brown streak disease (CBSD) is a destructive disease of cassava in Eastern and Central Africa. Because there was no source of resistance in African varieties to provide complete protection against the viruses causing the disease, we searched in South American germplasm and identified cassava lines that did not become infected with the cassava brown streak viruses. These findings motivated further investigations into the mechanism of virus resistance. We used RNAscope® in situ hybridization to localize cassava brown streak virus in cassava germplasm lines that were highly resistant (DSC 167, immune) or that restricted virus infections to stems and roots only (DSC 260). We show that the resistance in those lines is not a restriction of long-distance movement but due to preventing virus unloading from the phloem into parenchyma cells for replication, thus restricting the virus to the phloem cells only. When DSC 167 and DSC 260 were compared for virus invasion, only a low CBSV signal was found in phloem tissue of DSC 167, indicating that there is no replication in this host, while the presence of intense hybridization signals in the phloem of DSC 260 provided evidence for virus replication in companion cells. In neither of the two lines studied was there evidence of virus replication outside the phloem tissues. Thus, we conclude that in resistant cassava lines, CBSV is confined to the phloem tissues only, in which virus replication can still take place or is arrested.

Topological clustering of regulatory genes confers pathogenic tolerance to cassava brown streak virus (CBSV) in cassava

Robustness, a naïve property of biological systems, enables organisms to maintain functions during perturbation and is crucial for improving the resilience of crops to prevailing stress conditions and diseases, guaranteeing food security. Most studies of robustness in crops have focused on genetic superiority based upon individual genes, overlooking the collaborative actions of multiple responsive genes and the regulatory network topology. This research aims to uncover patterns of gene cooperation leading to organismal robustness by studying the topology of gene co-expression networks (GCNs) of both CBSV virus resistant and susceptible cassava cultivars. The resulting GCNs show higher topological clustering of cooperative genes in the resistant cultivar, suggesting that the network architecture is central to attaining robustness. Despite a reduction in the number of hub genes in the resistant cultivar following the perturbation, essential biological functions contained in the network were maintained through neighboring genes that withstood the shock. The susceptible cultivar seemingly coped by inducing more gene actions in the network but could not maintain the functions required for plant growth. These findings underscore the importance of regulatory network architecture in ensuring phenotypic robustness and deepen our understanding of transcriptional regulation.

Expansion of the cassava brown streak disease epidemic in eastern Democratic Republic of Congo

Cassava plays a key role in assuring food security and generating income for smallholder farmers throughout central Africa, and particularly in the Democratic Republic of Congo (DRC). This status is threatened, however, by cassava brown streak disease (CBSD) which has recently expanded its incidence and range in eastern DRC. The study described here, comprises the first extensive assessment of temporal change in occurrence of CBSD and its causal viruses in DRC, based on surveys conducted during 2016 and 2018. Cassava fields were inspected in Ituri, Nord-Kivu, Sud-Kivu, Tanganyika and Haut-Katanga provinces within eastern DRC, to record foliar incidence and severity of CBSD. Leaf samples were collected for virus detection and species-level identification. New occurrences of CBSD, confirmed by virus diagnostic tests, were recorded in two provinces (Haut-Katanga and Sud-Kivu) and nine previously unaffected territories, covering an area of > 62,000 km2, and at up to 900 km from locations of previously published reports of CBSD in DRC. Overall, average CBSD incidence within fields was 13.2% in 2016 and 16.1% in 2018. In the new spread zone of Haut-Katanga, incidence increased from 1.7% to 15.9%. CBSD is now present in provinces covering 321,000 km2 which is approximately 14% of the total area of DRC. This represents a major expansion of the CBSD epidemic, which was only recorded from one province (Nord-Kivu) in 2012. Both cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) were detected in Ituri, Nord-Kivu and Sud-Kivu, but only CBSV was detected in Haut-Katanga. Considered overall, these results confirm the increasing threat that CBSD poses to cassava production in DRC and describe an important expansion in the African pandemic of CBSD.

A k-mer based approach for virus classification identifies coronavirus infections and viral associations in human and plant microbiomes

Background Viruses are underrepresented taxa in the study and identification of microbiome constituents; however, they play an essential role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which further limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus’ genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples. Methods To identify and quantify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses. We then integrated the viral classification tree with the NCBI taxonomy for use with ParaKraken (a parallelized version of Kraken), a metagenomic/transcriptomic classifier. The resulting Kraken2 database of the metagenomic viruses can be found here: https://www.osti.gov/biblio/1615774 and is compatible with Kraken2. Results To illustrate the breadth of our utility for classifying viruses with ParaKraken, especially samples without virus-induced pathophysiology, we analyzed data from a plant metagenome study identifying the differences between two Populus genotypes in three different compartments and on a human metatranscriptome study identifying the differences between Autism Spectrum Disorder patients and controls in post mortem brain tissue. In the Populus study, we identified genotype and compartment-specific viral signatures, while in the Autism study we identified a significant increase in abundance of eight viral sequences in post mortem brains. We also show the potential accuracy for classifying viruses by utilizing both the JGI and NCBI viral databases to identify the uniqueness of viral sequences. Finally, we utilize the NCBI databases to identify pathogenic viruses in known COVID-19 and cassava brown streak virus infection samples to validate the potential usefulness of classifying viruses. Conclusion Viruses represent an essential component of the microbiome. The ability to classify viruses represents the compulsory first step in better understanding their role in the microbiome. Our viral classification method allows for a more complete identification of viral sequences than previous methods. This will improve identification of associations between viruses and their hosts as well as viruses and other microbiome members and can be used with any tool that utilizes a taxonomy for classification (such as Kraken).

Screening for Resistance in Farmer-Preferred Cassava Cultivars from Ghana to a Mixed Infection of CBSV and UCBSV

Cassava brown streak disease (CBSD) caused by the Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) is a threat to cassava production in Africa. The potential spread of CBSD into West Africa is a cause for concern, therefore screening for resistance in farmer-preferred genotypes is crucial for effective control and management. We multiplied a selection of eleven cassava cultivars grown by farmers in Ghana to test their response to a mixed infection of CBSV (TAZ-DES-01) and UCBSV (TAZ-DES-02) isolates using a stringent top-cleft graft inoculation method. Virus titers were quantified in the inoculated scions and cuttings propagated from the inoculated scions to assess virus accumulation and recovery. All cultivars were susceptible to the mixed infection although their response and symptom development varied. In the propagated infected scions, CBSV accumulated at higher titers in leaves of eight of the eleven cultivars. Visual scoring of storage roots from six-month-old virus-inoculated plants revealed the absence of CBSD-associated necrosis symptoms and detectable titers of CBSVs in the cultivar, IFAD. Although all eleven cultivars supported the replication of CBSV and UCBSV in their leaves, the absence of virus replication and CBSD-associated symptoms in the roots of some cultivars could be used as criteria to rapidly advance durable CBSD tolerance using breeding and genetic engineering approaches.

A K-mer Based Approach for Virus Classification Identifies Coronavirus Infections and Viral Associations in Human and Plant Microbiomes

BackgroundViruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an essential role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which further limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus’ genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples.MethodsTo identify and quantify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses. We then integrated the viral classification tree with the NCBI taxonomy for use with ParaKraken (a parallelized version of Kraken), a metagenomic/transcriptomic classifier. The resulting Kraken2 database of the metagenomic viruses can be found here: https://www.osti.gov/biblio/1615774 and is compatible with Kraken2.ResultsTo illustrate the breadth of our utility for classifying viruses with ParaKraken, especially samples without virus-induced pathophysiology, we analyzed data from a plant metagenome study identifying the differences between two Populus genotypes in three different compartments and on a human metatranscriptome study identifying the differences between Autism Spectrum Disorder patients and controls in post mortem brain tissue. In the Populus study, we identified genotype and compartment-specific viral signatures, while in the Autism study we identified a significant increase in abundance of eight viral sequences in post mortem brains. We also show the potential accuracy for classifying viruses by utilizing the NCBI viral databases to identify the uniqueness of viral sequences and to identify pathogenic viruses in known COVID-19 and cassava brown streak virus infection samples.ConclusionViruses represent an essential component of the microbiome. The ability to classify viruses represents the compulsory first step in better understanding their role in the microbiome. The viral classification method presented here allows for a more complete identification of viral sequences for use in identifying associations between viruses and the host and viruses and other microbiome members and can be used with any tool that utilizes a taxonomy for classification (such as Kraken).

Diversity and Phylogenetic Relationships of Full Genome Sequences of Cassava Brown Streak Viruses in Kenya

Cassava brown streak disease is caused by cassava brown streak virus (CBSV) and Uganda cassava brown streak virus (UCBSV). Many of the CBSV and UCBSV diversity studies utilize partial coat protein sequences due to the unavailability of representative full genome sequences. Hence, there is little information on the diversity of cassava brown streak viruses in the rest of the genomes of the two species that are present in the farmers’ fields. The aim of this study was to determine Kenyan full CBSV and UCBSV genomes, and their sequence diversity and phylogenetic relationships within various genome and genome segments. Twenty four CBSVs positive samples tested by RT PCR from major cassava producing regions in Kenya were sequenced using Illumina MiSeq. Quality assessment of the output reads was done using the CLC Genomics 5.5.1 software programs. Genome assembly was done by de novo and reference guided assembly. Nucleotide sequence similarity of CBSV and UCBSV was determined. Phylogenetic relationships between CBSV and UCBSV were determined by performing the neighbour-joining analysis using MEGA 6.0 software. Six CBSV and 9 UCBSV genomes were generated from this study. The coat protein of the CBSV sequences had nucleotide sequence similarity of 92-100% while P1 and P3 gene had 75-100% and 76-100%, respectively. The coat protein of the UCBSV sequences had nucleotide sequence similarity of 91-99%. P1 and P3 gene had 83-100% and 86-99%, respectively. The phylogenetic analysis of full genomes revealed two distinct clusters one for UCBSV and another cluster for CBSV. Individual gene segments phylogenetic tree resembled that of the whole genome by clustering the nucleotide sequences into two clusters, one belonging to UCBSV and the other CBSV. The study revealed an average genome nucleotide diversity of 21.5% and 15.8% in CBSV and UCBSV respectively. A vast genetic diversity observed in CBSV and UCBSV in this study portends a lot of challenges in developing molecular diagnostic techniques as well as control strategies against the viruses.