The Non-Coding RNA Ontology : a comprehensive resource for the unification of non-coding RNA biology

In recent years, sequencing technologies have enabled the identification of a wide range of non-coding RNAs (ncRNAs). Unfortunately, annotation and integration of ncRNA data has lagged behind their identification. Given the large quantity of information being obtained in this area, there emerges an urgent need to integrate what is being discovered by a broad range of relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a systematically structured and precisely defined controlled vocabulary for the domain of ncRNAs, thereby facilitating the discovery, curation, analysis, exchange, and reasoning of data about structures of ncRNAs, their molecular and cellular functions, and their impacts upon phenotypes. The goal of NCRO is to serve as a common resource for annotations of diverse research in a way that will significantly enhance integrative and comparative analysis of the myriad resources currently housed in disparate sources. It is our belief that the NCRO ontology can perform an important role in the comprehensive unification of ncRNA biology and, indeed, fill a critical gap in both the Open Biological and Biomedical Ontologies (OBO) Library and the National Center for Biomedical Ontology (NCBO) BioPortal. Our initial focus is on the ontological representation of small regulatory ncRNAs, which we see as the first step in providing a resource for the annotation of data about all forms of ncRNAs. The NCRO ontology is free and open to all users

The development of non-coding RNA ontology

Identification of non-coding RNAs (ncRNAs) has been significantly improved over the past decade. On the other hand, semantic annotation of ncRNA data is facing critical challenges due to the lack of a comprehensive ontology to serve as common data elements and data exchange standards in the field. We developed the Non-Coding RNA Ontology (NCRO) to handle this situation. By providing a formally defined ncRNA controlled vocabulary, the NCRO aims to fill a specific and highly needed niche in semantic annotation of large amounts of ncRNA biological and clinical data

PLIT: An alignment-free computational tool for identification of long non-coding RNAs in plant transcriptomic datasets

Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs which play a significant role in several biological processes. RNA-seq based transcriptome sequencing has been extensively used for identification of lncRNAs. However, accurate identification of lncRNAs in RNA-seq datasets is crucial for exploring their characteristic functions in the genome as most coding potential computation (CPC) tools fail to accurately identify them in transcriptomic data. Well-known CPC tools such as CPC2, lncScore, CPAT are primarily designed for prediction of lncRNAs based on the GENCODE, NONCODE and CANTATAdb databases. The prediction accuracy of these tools often drops when tested on transcriptomic datasets. This leads to higher false positive results and inaccuracy in the function annotation process. In this study, we present a novel tool, PLIT, for the identification of lncRNAs in plants RNA-seq datasets. PLIT implements a feature selection method based on L1 regularization and iterative Random Forests (iRF) classification for selection of optimal features. Based on sequence and codon-bias features, it classifies the RNA-seq derived FASTA sequences into coding or long non-coding transcripts. Using L1 regularization, 31 optimal features were obtained based on lncRNA and protein-coding transcripts from 8 plant species. The performance of the tool was evaluated on 7 plant RNA-seq datasets using 10-fold cross-validation. The analysis exhibited superior accuracy when evaluated against currently available state-of-the-art CPC tools

Lithium alters expression of RNAs in a type-specific manner in differentiated human neuroblastoma neuronal cultures, including specific genes involved in Alzheimer's disease.

Lithium (Li) is a medication long-used to treat bipolar disorder. It is currently under investigation for multiple nervous system disorders, including Alzheimer's disease (AD). While perturbation of RNA levels by Li has been previously reported, its effects on the whole transcriptome has been given little attention. We, therefore, sought to determine comprehensive effects of Li treatment on RNA levels. We cultured and differentiated human neuroblastoma (SK-N-SH) cells to neuronal cells with all-trans retinoic acid (ATRA). We exposed cultures for one week to lithium chloride or distilled water, extracted total RNA, depleted ribosomal RNA and performed whole-transcriptome RT-sequencing. We analyzed results by RNA length and type. We further analyzed expression and protein interaction networks between selected Li-altered protein-coding RNAs and common AD-associated gene products. Lithium changed expression of RNAs in both non-specific (inverse to sequence length) and specific (according to RNA type) fashions. The non-coding small nucleolar RNAs (snoRNAs) were subject to the greatest length-adjusted Li influence. When RNA length effects were taken into account, microRNAs as a group were significantly less likely to have had levels altered by Li treatment. Notably, several Li-influenced protein-coding RNAs were co-expressed or produced proteins that interacted with several common AD-associated genes and proteins. Lithium's modification of RNA levels depends on both RNA length and type. Li activity on snoRNA levels may pertain to bipolar disorders while Li modification of protein coding RNAs may be relevant to AD

Non-coding and Coding Transcriptional Profiles Are Significantly Altered in Pediatric Retinoblastoma Tumors.

Retinoblastoma is a rare pediatric tumor of the retina, caused by the homozygous loss of the Retinoblastoma 1 (RB1) tumor suppressor gene. Previous microarray studies have identified changes in the expression profiles of coding genes; however, our understanding of how non-coding genes change in this tumor is absent. This is an important area of research, as in many adult malignancies, non-coding genes including LNC-RNAs are used as biomarkers to predict outcome and/or relapse. To establish a complete and in-depth RNA profile, of both coding and non-coding genes, in Retinoblastoma tumors, we conducted RNA-seq from a cohort of tumors and normal retina controls. This analysis identified widespread transcriptional changes in the levels of both coding and non-coding genes. Unexpectedly, we also found rare RNA fusion products resulting from genomic alterations, specific to Retinoblastoma tumor samples. We then determined whether these gene expression changes, of both coding and non-coding genes, were also found in a completely independent Retinoblastoma cohort. Using our dataset, we then profiled the potential effects of deregulated LNC-RNAs on the expression of neighboring genes, the entire genome, and on mRNAs that contain a putative area of homology. This analysis showed that most deregulated LNC-RNAs do not act locally to change the transcriptional environment, but potentially function to modulate genes at distant sites. From this analysis, we selected a strongly down-regulated LNC-RNA in Retinoblastoma, DRAIC, and found that restoring DRAIC RNA levels significantly slowed the growth of the Y79 Retinoblastoma cell line. Collectively, our work has generated the first non-coding RNA profile of Retinoblastoma tumors and has found that these tumors show widespread transcriptional deregulation

The non-coding RNA landscape of plasma cell dyscrasias

Despite substantial advancements have been done in the understanding of the pathogenesis of plasma cell (PC) disorders, these malignancies remain hard-to-treat. The discovery and subsequent characterization of non-coding transcripts, which include several members with diverse length and mode of action, has unraveled novel mechanisms of gene expression regulation often malfunctioning in cancer. Increasing evidence indicates that such non-coding molecules also feature in the pathobiology of PC dyscrasias, where they are endowed with strong therapeutic and/or prognostic potential. In this review, we aim to summarize the most relevant findings on the biological and clinical features of the non-coding RNA landscape of malignant PCs, with major focus on multiple myeloma. The most relevant classes of non-coding RNAs will be examined, along with the mechanisms accounting for their dysregulation and the recent strategies used for their targeting in PC dyscrasias. It is hoped these insights may lead to clinical applications of non-coding RNA molecules as biomarkers or therapeutic targets/agents in the near future