Submit to IJMS Review for IJMS Propose a Special Issue

Journal Menu

Journal Browser

Plant Non-coding RNAs in the Era of Biological Big Data 2.0

Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Plant Sciences".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 6009

Share This Special Issue

Special Issue Editors

Prof. Dr. Mohan B. Singh

E-Mail Website
Guest Editor

Plant Molecular Biology and Biotechnology Laboratory, University of Melbourne, Parkville, Australia
Interests: plant noncoding RNA
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Prem L. Bhalla

E-Mail Website
Guest Editor

Plant Molecular Biology and Biotechnology Laboratory, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Melbourne, VIC 3010, Australia
Interests: plant reproduction; plant biotechnology; crop biotechnology

Prof. Dr. Lin Li

E-Mail Website
Guest Editor

National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
Interests: plant systems biology; plant architecture; plant genomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the advancement of next-generation sequencing, plant biological research has entered the era of big data. It is an exciting time to study plant non-coding RNAs. A large number of non-coding RNAs have been detected to be expressed in a surprisingly wide range of tissue-type or cell-type expression. More and more evidence suggests that non-coding RNAs are involved in a wide range of biological processes. However, many fundamental questions in regard to their mechanism of molecular function remain largely unexplored in plants. In this Special Issue, we call for research papers addressing how different regulatory non-coding RNAs are processed and regulated; how they function in different physiological, developmental, and abiotic and biotic environments; how they interact with proteins and other functional elements to carry out their functions; and finally, how to translate our understanding of non-coding RNAs into plant breeding. Here, we would like to provide an integrated platform for the plant research community to share the latest available technologies, methodologies, and new exciting discoveries on plant non-coding RNAs. Therefore, I warmly welcome original research and review articles in these fields.

Prof. Dr. Mohan B. Singh
Prof. Dr. Prem L. Bhalla
Prof. Dr. Lin Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

non-coding RNAs
small RNAs
long non-coding RNAs
circular RNAs
regulatory networks
next-generation sequencing
biological big data
small peptides
plant breeding

Published Papers (3 papers)

Download All Papers

Research

Jump to: Review

18 pages, 5992 KiB

Open AccessArticle

Pokkali: A Naturally Evolved Salt-Tolerant Rice Shows a Distinguished Set of lncRNAs Possibly Contributing to the Tolerant Phenotype

by Shalini Tiwari, Mukesh Jain, Sneh Lata Singla-Pareek, Prem L. Bhalla, Mohan B. Singh and Ashwani Pareek

Int. J. Mol. Sci. 2023, 24(14), 11677; https://doi.org/10.3390/ijms241411677 - 20 Jul 2023

Cited by 2 | Viewed by 1857

Abstract

Pokkali is a strong representation of how stress-tolerant genotypes have evolved due to natural selection pressure. Numerous omics-based investigations have indicated different categories of stress-related genes and proteins, possibly contributing to salinity tolerance in this wild rice. However, a comprehensive study towards understanding the role of long-noncoding RNAs (lncRNAs) in the salinity response of Pokkali has not been done to date. We have identified salt-responsive lncRNAs from contrasting rice genotypes IR64 and Pokkali. A total of 63 and 81 salinity-responsive lncRNAs were differentially expressed in IR64 and Pokkali, respectively. Molecular characterization of lncRNAs and lncRNA-miRNA-mRNA interaction networks helps to explore the role of lncRNAs in the stress response. Functional annotation revealed that identified lncRNAs modulate various cellular processes, including transcriptional regulation, ion homeostasis, and secondary metabolite production. Additionally, lncRNAs were predicted to bind stress-responsive transcription factors, namely ERF, DOF, and WRKY. In addition to salinity, expression profiling was also performed under other abiotic stresses and phytohormone treatments. A positive modulation in TCONS_00035411, TCONS_00059828, and TCONS_00096512 under both abiotic stress and phytohormone treatments could be considered as being of potential interest for the further functional characterization of IncRNA. Thus, extensive analysis of lncRNAs under various treatments helps to delineate stress tolerance mechanisms and possible cross-talk. Full article

(This article belongs to the Special Issue Plant Non-coding RNAs in the Era of Biological Big Data 2.0)

► Show Figures

Figure 1

16 pages, 4140 KiB

Open AccessArticle

PINC: A Tool for Non-Coding RNA Identification in Plants Based on an Automated Machine Learning Framework

by Xiaodan Zhang, Xiaohu Zhou, Midi Wan, Jinxiang Xuan, Xiu Jin and Shaowen Li

Int. J. Mol. Sci. 2022, 23(19), 11825; https://doi.org/10.3390/ijms231911825 - 5 Oct 2022

Cited by 5 | Viewed by 1535

Abstract

There is evidence that non-coding RNAs play significant roles in the regulation of nutrient homeostasis, development, and stress responses in plants. Accurate identification of ncRNAs is the first step in determining their function. While a number of machine learning tools have been developed for ncRNA identification, no dedicated tool has been developed for ncRNA identification in plants. Here, an automated machine learning tool, PINC is presented to identify ncRNAs in plants using RNA sequences. First, we extracted 91 features from the sequence. Second, we combined the F-test and variance threshold for feature selection to find 10 features. The AutoGluon framework was used to train models for robust identification of non-coding RNAs from datasets constructed for four plant species. Last, these processes were combined into a tool, called PINC, for the identification of plant ncRNAs, which was validated on nine independent test sets, and the accuracy of PINC ranged from 92.74% to 96.42%. As compared with CPC2, CPAT, CPPred, and CNIT, PINC outperformed the other tools in at least five of the eight evaluation indicators. PINC is expected to contribute to identifying and annotating novel ncRNAs in plants. Full article

(This article belongs to the Special Issue Plant Non-coding RNAs in the Era of Biological Big Data 2.0)

► Show Figures

Figure 1

Review

Jump to: Research

16 pages, 2062 KiB

Open AccessReview

Regulatory Small RNAs for a Sustained Eco-Agriculture

by Selvaraj Barathi, Nadana Sabapathi, Kandasamy Nagarajan Aruljothi, Jin-Hyung Lee, Jae-Jin Shim and Jintae Lee

Int. J. Mol. Sci. 2023, 24(2), 1041; https://doi.org/10.3390/ijms24021041 - 5 Jan 2023

Cited by 2 | Viewed by 1970

Abstract

Small RNA (sRNA) has become an alternate biotechnology tool for sustaining eco-agriculture by enhancing plant solidity and managing environmental hazards over traditional methods. Plants synthesize a variety of sRNA to silence the crucial genes of pests or plant immune inhibitory proteins and counter adverse environmental conditions. These sRNAs can be cultivated using biotechnological methods to apply directly or through bacterial systems to counter the biotic stress. On the other hand, through synthesizing sRNAs, microbial networks indicate toxic elements in the environment, which can be used effectively in environmental monitoring and management. Moreover, microbes possess sRNAs that enhance the degradation of xenobiotics and maintain bio-geo-cycles locally. Selective bacterial and plant sRNA systems can work symbiotically to establish a sustained eco-agriculture system. An sRNA-mediated approach is becoming a greener tool to replace xenobiotic pesticides, fertilizers, and other chemical remediation elements. The review focused on the applications of sRNA in both sustained agriculture and bioremediation. It also discusses limitations and recommends various approaches toward future improvements for a sustained eco-agriculture system. Full article

(This article belongs to the Special Issue Plant Non-coding RNAs in the Era of Biological Big Data 2.0)

► Show Figures