Comparative Transcriptome Analysis Reveals the Transcriptional Alterations in Growth- and Development-Related Genes in Sweet Potato Plants Infected and Non-Infected by SPFMV, SPV2, and SPVG

High-throughput characterization and phenotyping of resistance and tolerance to virus infection in sweetpotato

Breeders have made important efforts to develop genotypes able to resist virus attacks in sweetpotato, a major crop providing food security and poverty alleviation to smallholder farmers in many regions of Sub-Saharan Africa, Asia and Latin America. However, a lack of accurate objective quantitative methods for this selection target in sweetpotato prevents a consistent and extensive assessment of large breeding populations. In this study, an approach to characterize and classify resistance in sweetpotato was established by assessing total yield loss and virus load after the infection of the three most common viruses (SPFMV, SPCSV, SPLCV). Twelve sweetpotato genotypes with contrasting reactions to virus infection were grown in the field under three different treatments: pre-infected by the three viruses, un-infected and protected from re-infection, and un-infected but exposed to natural infection. Virus loads were assessed using ELISA, (RT-)qPCR, and loop-mediated isothermal amplification (LAMP) methods, and also through multispectral reflectance and canopy temperature collected using an unmanned aerial vehicle. Total yield reduction compared to control and the arithmetic sum of (RT-)qPCR relative expression ratios were used to classify genotypes into four categories: resistant, tolerant, susceptible, and sensitives. Using 14 remote sensing predictors, machine learning algorithms were trained to classify all plots under the said categories. The study found that remotely sensed predictors were effective in discriminating the different virus response categories. The results suggest that using machine learning and remotely sensed data, further complemented by fast and sensitive LAMP assays to confirm results of predicted classifications could be used as a high throughput approach to support virus resistance phenotyping in sweetpotato breeding.

Foliar transcriptomes reveal candidate genes for late blight resistance in cultivars of diploid potato Solanum tuberosum L. Andigenum Group

Characterization of major resistance (R) genes to late blight (LB) -caused by the oomycete Phytophthora infestans- is very important for potato breeding. The objective of this study was to identify novel genes for resistance to LB from diploid Solanum tuberosum L. Andigenum Group (StAG) cultivar accessions. Using comparative analysis with a edgeR bioconductor package for differential expression analysis of transcriptomes, two of these accessions with contrasting levels of resistance to LB were analyzed using digital gene expression data. As a result, various differentially expressed genes (P ≤ 0.0001, Log2FC ≥ 2, FDR < 0.001) were noted. The combination of transcriptomic analysis provided 303 candidate genes that are overexpressed and underexpressed, thereby giving high resistance to LB. The functional analysis showed differential expression of R genes and their corresponding proteins related to disease resistance, NBS-LRR domain proteins, and specific disease resistance proteins. Comparative analysis of specific tissue transcriptomes in resistant and susceptible genotypes can be used for rapidly identifying candidate R genes, thus adding novel genes from diploid StAG cultivar accessions for host plant resistance to P. infestans in potato.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

Bioactive compounds and their libraries: An insight into prospective phytotherapeutics approach for oral mucocutaneous cancers

Oral mucocutaneous cancers (OMCs) are cancers that affect both the oral mucosa and perioral cutaneous structures. Common OMCs are squamous cell carcinoma (SCC), basal cell carcinoma (BCC) and malignant melanoma (MM). Anatomical similarities and conventions which categorizes these lesions blur the magnitude of OMCs in diverse populations. The burden of OMC is high in the sub-Saharan Africa and Indian subcontinents, and the cost of management is prohibitive in the resource-limited, developing world. Hence, there is a pressing demand for the use of cost-effective in silico approaches to identify diagnostic tools and treatment targets for diseases with high burdens in these regions. Due to their ubiquitousness and accessibility, the use of therapeutic efficacy of plant bioactive compounds in the management of OMC is both appropriate and plausible. Furthermore, screening known mechanistic disease targets with well annotated plant bioactive compound libraries is poised to improve the routine management of OMCs provided that the requisite access to database resources are available and accessible. Using natural products minimizes the side effects and morbidities associated with conventional therapies. The development of innovative treatments approaches would tremendously benefit the African and Indian populace and reduce the mortalities associated with OMCs in the developing world. Hence, we discuss herein, the potential benefits, opportunities and challenges of using bioactive compound libraries in the management of OMCs.

The Spread and Transmission of Sweet Potato Virus Disease (SPVD) and Its Effect on the Gene Expression Profile in Sweet Potato

Sweet potato virus disease (SPVD) is the most devastating viral disease in sweet potato (Ipomoea batatas (L.) Lam.), causing substantial yield losses worldwide. We conducted a systemic investigation on the spread, transmission, and pathogenesis of SPVD. Field experiments conducted over two years on ten sweet potato varieties showed that SPVD symptoms first occurred in newly developed top leaves, and spread from adjacent to distant plants in the field. The SPVD incidence was mainly (but not only) determined by the resistance of the varieties planted, and each variety exhibited a characteristic subset of SPVD symptoms. SPVD was not robustly transmitted through friction inoculation, but friction of the main stem might contribute to a higher SPVD incidence rate compared to friction of the leaf and branch tissues. Furthermore, our results suggested that SPVD might be latent in the storage root. Therefore, using virus-free storage roots and cuttings, purposeful monitoring for SPVD according to variety-specific symptoms, and swiftly removing infected plants (especially during the later growth stages) would help control and prevent SPVD during sweet potato production. Comparative transcriptome analysis revealed that numerous genes involved in photosynthesis, starch and sucrose metabolism, flavonoid biosynthesis, and carotenoid biosynthesis were downregulated following SPVD, whereas those involved in monolignol biosynthesis, zeatin biosynthesis, trehalose metabolism, and linoleic acid metabolism were upregulated. Notably, critical genes involved in pathogenesis and plant defense were significantly induced or suppressed following SPVD. These data provide insights into the molecular changes of sweet potato in response to SPVD and elucidate potential SPVD pathogenesis and defense mechanisms in sweet potato. Our study provides important information that can be used to tailor sustainable SPVD control strategies and guide the molecular breeding of SPVD-resistant sweet potato varieties.

Differential Accumulation of Innate- and Adaptive-Immune-Response-Derived Transcripts during Antagonism between Papaya Ringspot Virus and Papaya Mosaic Virus

Papaya ringspot virus (PRSV), a common potyvirus infecting papaya plants worldwide, can lead to either antagonism or synergism in mixed infections with Papaya mosaic virus (PapMV), a potexvirus. These two unrelated viruses produce antagonism or synergism depending on their order of infection in the plant. When PRSV is inoculated first or at the same time as PapMV, the viral interaction is synergistic. However, an antagonistic response is observed when PapMV is inoculated before PRSV. In the antagonistic condition, PRSV is deterred from the plant and its drastic effects are overcome. Here, we examine differences in gene expression by high-throughput RNA sequencing, focused on immune system pathways. We present the transcriptomic expression of single and mixed inoculations of PRSV and PapMV leading to synergism and antagonism. Upregulation of dominant and hormone-mediated resistance transcripts suggests that the innate immune system participates in synergism. In antagonism, in addition to innate immunity, upregulation of RNA interference-mediated resistance transcripts suggests that adaptive immunity is involved.

Phenotyping viral infection in sweetpotato using a high-throughput chlorophyll fluorescence and thermal imaging platform

BACKGROUND

Virus diseases caused by co-infection with Sweet potato feathery mottle virus (SPFMV) and Sweetpotato chlorotic stunt virus (SPCSV) are a severe problem in the production of sweetpotato (Ipomoea batatas L.). Traditional molecular virus detection methods include nucleic acid-based and serological tests. In this study, we aimed to validate the use of a non-destructive imaging-based plant phenotype platform to study plant-virus synergism in sweetpotato by comparing four virus treatments with two healthy controls.

RESULTS

By monitoring physiological and morphological effects of viral infection in sweetpotato over 29 days, we quantified photosynthetic performance from chlorophyll fluorescence (ChlF) imaging and leaf thermography from thermal infrared (TIR) imaging among sweetpotatoes. Moreover, the differences among different treatments observed from ChlF and TIR imaging were related to virus accumulation and distribution in sweetpotato. These findings were further validated at the molecular level by related gene expression in both photosynthesis and carbon fixation pathways.

CONCLUSION

Our study validated for the first time the use of ChlF- and TIR-based imaging systems to distinguish the severity of virus diseases related to SPFMV and SPCSV in sweetpotato. In addition, we demonstrated that the operating efficiency of PSII and photochemical quenching were the most sensitive parameters for the quantification of virus effects compared with maximum quantum efficiency, non-photochemical quenching, and leaf temperature.

Comparison of Transcriptome Differences in Soybean Response to Soybean Mosaic Virus under Normal Light and in the Shade

Shading in the intercropping system is a major abiotic factor which influences soybean growth and development, while soybean mosaic virus (SMV) is a biotic factor that limits the yield and quality of soybean. However, little is known about the defense response of soybean to SMV in the shade. Thus, in the current study, both intensity and quality (red:far-red, R:FR) of the light were changed to simulate the shaded environment and comparative transcriptome analysis was performed. Morphologically, plant growth was inhibited by SMV, which decreased 35.93% of plant height and 8.97% of stem diameter in the shade. A total of 3548 and 4319 differentially expressed genes (DEGs) were identified in soybean plants infected with SMV under normal light and in the shade. Enrichment analysis showed that the plant defense-related genes were upregulated under normal light but downregulated in the shade. Pathways that were repressed include plant-pathogen interaction, secondary metabolism, sugar metabolism, and vitamin metabolism. In addition, genes associated with signaling pathways such as salicylic acid (SA), jasmonic acid (JA), and ethylene (ETH) were also downregulated in the shade. A qRT-PCR assay of 15 DEGs was performed to confirm transcriptome results. According to our knowledge, this is the first report on soybean response to dual stress factors. These results provide insights into the molecular mechanisms in which soybean plants were infected with SMV in the shade.