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The Reference Transcriptomic Dataset (RTD) is an accurate and comprehensive collection of transcripts originating from a given organism. It holds the key to precise transcript quantification and downstream analysis of differential expressions and regulations. Currently, transcriptome annotations for most crop plants are far from complete. For example, Oryza sativa indica (O. sativa indica) is reported to have 40,759 transcripts in the Ensembl database without alternative transcript isoforms and alternative splicing (AS) events. To generate a high-quality RTD, we conducted RNA sequencing of rice leaf samples collected at various time points during Rhizoctonia solani infection. The obtained reads were analyzed by adopting the recently developed computational analysis pipeline to assemble the RTD with increased transcript and AS diversity for O. sativa indica (IndicaRTD). After stringent quality filtering, the newly constructed transcriptome annotation was comprised of 122,968 non-redundant transcripts from 53,695 genes. This study identified many novel transcripts compared to Ensembl deposited data that are important for regulating molecular and physiological processes in the plant system. Currently, the assembled IndicaRTD must allow fast quantification of transcript and gene expression with high precision.

Sheath blight (ShB) disease, caused by Rhizoctonia solani, is one of the major biotic stress-oriented diseases that adversely affect the rice productivity worldwide. However, the regulatory mechanisms are not understood yet comprehensively. In the current study, we had investigated the potential roles of miRNAs in economically important indica rice variety Pusa Basmati-1 upon R. solani infection by carrying out in-depth, high-throughput small RNA sequencing with a total data size of 435 million paired-end raw reads from rice leaf RNA samples collected at different time points. Detailed data analysis revealed a total of 468 known mature miRNAs and 747 putative novel miRNAs across all the libraries. Target prediction and Gene Ontology functional analysis of these miRNAs were found to be unraveling various cellular, molecular, and biological functions by targeting various plant defense-related genes. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to validate the miRNAs and their putative target genes. Out of the selected miRNA-specific putative target genes, miR395a binding and its cleavage site on pentatricopeptide were determined by 5’ RACE-PCR. It might be possible that R. solani instigated chloroplast degradation by modulating the pentatricopeptide which led to increased susceptibility to fungal infection.

Covalently closed circular RNAs are neoteric to the eukaryotic family of long non-coding RNAs emerging as a result of 5′–3′ backsplicing from exonic, intronic, or intergenic regions spanning the parental gene. Owing to their unique structure and stability, circular RNAs have a multitude of functional properties such as micro-RNA and protein sponges, direct and indirect modulators of gene expression, protein translation, and many unproven activities apart from being potential biomarkers. However, due to their low abundance, most of the global circular RNA identification is carried out by high-throughput NGS-based approaches requiring millions of sequencing reads. This lag in methodological advancements demands for newer, more refined, and efficient identification techniques. Here, we aim to show an improved version of our previously reported template-dependent multiple displacement amplification (tdMDA)-NGS method by superimposing the ribosomal depletion step and use of H minus reverse transcriptase and RNase H. Implication of tdMDA using highly replicative Phi29 DNA polymerase after minimizing the linear and ribosomal RNA content further intensifies its detection limit toward even the abysmally expressing circular RNA at a low NGS depth, thereby decreasing the cost of identifying a single circular RNA. A >11-fold and >6-fold increase in total circular RNA was identified from the improved-tdMDA-NGS method over the traditional method of circRNA sequencing using DCC and CIRI2 pipelines, respectively, from Oryza sativa subsp. Indica. Furthermore, the reliability of the improved-tdMDA-NGS method was also asserted in HeLa cell lines, showing a significant fold difference in comparison with the existing traditional method of circRNA sequencing. Among the identified circular RNAs, a significant percentage from both rice (∼58%) and HeLa cell lines (∼84%) is found to be matched with the previously reported circular RNAs, suggesting that the improved-tdMDA-NGS method can be adapted to detect and characterize the circular RNAs from different biological systems.