Target prediction of candidate miRNAs from Oryza sativa for silencing the RYMV genome

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

Cassava mosaic disease (CMD) is caused by several divergent species belonging to the genus Begomovirus (Geminiviridae) transmitted by the whitefly Bemisia tabaci cryptic species group. In India and other parts of Asia, the Indian cassava mosaic virus-Kerala (ICMV-Ker) is an emergent begomovirus of cassava causing damage that results in reduced yield loss and tuber quality. Double-stranded RNA-mediated interference (RNAi) is an evolutionary conserved mechanism in eukaryotes and highly effective, innate defense system to inhibit plant viral replication and/or translation. The objective of this study was to identify and characterize cassava genome-encoded microRNAs (mes-miRNA) that are predicted to target ICMV-Ker ssDNA-encoded mRNAs, based on four in silico algorithms: miRanda, RNA22, Tapirhybrid, and psRNA. The goal is to deploy the predicted miRNAs to trigger RNAi and develop cassava plants with resistance to ICMV-Ker. Experimentally validated mature cassava miRNA sequences (n = 175) were downloaded from the miRBase biological database and aligned with the ICMV-Ker genome. The miRNAs were evaluated for base-pairing with the cassava miRNA seed regions and to complementary binding sites within target viral mRNAs. Among the 175 locus-derived mes-miRNAs evaluated, one cassava miRNA homolog, mes-miR1446a, was identified to have a predicted miRNA target binding site, at position 2053 of the ICMV-Ker genome. To predict whether the cassava miRNA might bind predicted ICMV-Ker mRNA target(s) that could disrupt viral infection of cassava plants, a cassava locus-derived miRNA-mRNA regulatory network was constructed using Circos software. The in silico-predicted cassava locus-derived mes-miRNA-mRNA network corroborated interactions between cassava mature miRNAs and the ICMV-Ker genome that warrant in vivo analysis, which could lead to the development of ICMV-Ker resistant cassava plants.

A Review of Vector-Borne Rice Viruses

Rice (Oryza sativa L.) is one of the major staple foods for global consumption. A major roadblock to global rice production is persistent loss of crops caused by plant diseases, including rice blast, sheath blight, bacterial blight, and particularly various vector-borne rice viral diseases. Since the late 19th century, 19 species of rice viruses have been recorded in rice-producing areas worldwide and cause varying degrees of damage on the rice production. Among them, southern rice black-streaked dwarf virus (SRBSDV) and rice black-streaked dwarf virus (RBSDV) in Asia, rice yellow mottle virus (RYMV) in Africa, and rice stripe necrosis virus (RSNV) in America currently pose serious threats to rice yields. This review systematizes the emergence and damage of rice viral diseases, the symptomatology and transmission biology of rice viruses, the arm races between viruses and rice plants as well as their insect vectors, and the strategies for the prevention and control of rice viral diseases.

In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus

Sugarcane bacilliform virus (SCBV) is considered one of the most economically damaging pathogens for sugarcane production worldwide. Three open reading frames (ORFs) are characterized in the circular, ds-DNA genome of the SCBV; these encode for a hypothetical protein (ORF1), a DNA binding protein (ORF2), and a polyprotein (ORF3). A comprehensive evaluation of sugarcane (Saccharum officinarum L.) miRNAs for the silencing of the SCBV genome using in silico algorithms were carried out in the present study using mature sugarcane miRNAs. miRNAs of sugarcane are retrieved from the miRBase database and assessed in terms of hybridization with the SCBV genome. A total of 14 potential candidate miRNAs from sugarcane were screened out by all used algorithms used for the silencing of SCBV. The consensus of three algorithms predicted the hybridization site of sof-miR159e at common locus 5534. miRNA-mRNA interactions were estimated by computing the free-energy of the miRNA-mRNA duplex using the RNAcofold algorithm. A regulatory network of predicted candidate miRNAs of sugarcane with SCBV-ORFs, generated using Circos-is used to identify novel targets. The predicted data provide useful information for the development of SCBV-resistant sugarcane plants.

Novel targets for engineering Physostegia chlorotic mottle and tomato brown rugose fruit virus-resistant tomatoes: in silico prediction of tomato microRNA targets

Background

Physostegia chlorotic mottle virus (PhCMoV; genus: Alphanucleorhabdovirus, family: Rhabdoviridae) and tomato brown rugose fruit virus (ToBRFV; genus: Tobamovirus, family: Virgaviridae) are newly emerging plant viruses that have a dramatic effect on tomato production. Among various known virus-control strategies, RNAi-mediated defence has shown the potential to protect plants against various pathogens including viral infections. Micro(mi)RNAs play a major role in RNAi-mediated defence.

Methods

Using in silico analyses, we investigated the possibility of tomato-encoded miRNAs (TomiRNA) to target PhCMoV and ToBRFV genomes using five different algorithms, i.e., miRanda, RNAhybrid, RNA22, Tapirhybrid and psRNATarget.

Results

The results revealed that 14 loci on PhCMoV and 10 loci on ToBRFV can be targeted by the TomiRNAs based on the prediction of at least three algorithms. Interestingly, one TomiRNA, miR6026, can target open reading frames from both viruses, i.e., the phosphoprotein encoding gene of PhCMoV, and the two replicase components of ToBRFV. There are currently no commercially available PhCMoV- or ToBRFV-resistant tomato varieties, therefore the predicted data provide useful information for the development of PhCMoV- and ToBFRV-resistant tomato plants.

Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma

Esophageal cancer is a common malignant tumor in the world, and the aim of this study was to screen key genes related to the development of esophageal cancer using a variety of bioinformatics analysis tools and analyze their biological functions. The data of esophageal squamous cell carcinoma from the Gene Expression Omnibus (GEO) were selected as the research object, processed and analyzed to screen differentially expressed microRNAs (miRNAs) and differential methylation genes. The competing endogenous RNAs (ceRNAs) interaction network of differentially expressed genes was constructed by bioinformatics tools DAVID, String, and Cytoscape. Biofunctional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of the screened genes and the survival of the patients were verified. By analyzing GSE59973 and GSE114110, we found three down-regulated and nine up-regulated miRNAs. The gene expression matrix of GSE120356 was calculated by Pearson correlation coefficient, and the 11696 pairs of ceRNA relation were determined. In the ceRNA network, 643 lncRNAs and 147 mRNAs showed methylation difference. Functional enrichment analysis showed that these differentially expressed genes were mainly concentrated in the FoxO signaling pathway and were involved in the corresponding cascade of calcineurin. By analyzing the clinical data in The Cancer Genome Atlas (TCGA) database, it was found that four lncRNAs had an important impact on the survival and prognosis of esophageal carcinoma patients. QRT-PCR was also conducted to identify the expression of the key lncRNAs (RNF217-AS1, HCP5, ZFPM2-AS1 and HCG22) in ESCC samples. The selected key genes can provide theoretical guidance for further research on the molecular mechanism of esophageal carcinoma and the screening of molecular markers.