Structure-based screening for functional non-coding RNAs in fission yeast identifies a factor repressing untimely initiation of sexual differentiation

Non-coding RNAs (ncRNAs) ubiquitously exist in normal and cancer cells. Despite their prevalent distribution, the functions of most long ncRNAs remain uncharacterized. The fission yeast Schizosaccharomyces pombe expresses >1800 ncRNAs annotated to date, but most unconventional ncRNAs (excluding tRNA, rRNA, snRNA and snoRNA) remain uncharacterized. To discover the functional ncRNAs, here we performed a combinatory screening of computational and biological tests. First, all S. pombe ncRNAs were screened in silico for those showing conservation in sequence as well as in secondary structure with ncRNAs in closely related species. Almost a half of the 151 selected conserved ncRNA genes were uncharacterized. Twelve ncRNA genes that did not overlap with protein-coding sequences were next chosen for biological screening that examines defects in growth or sexual differentiation, as well as sensitivities to drugs and stresses. Finally, we highlighted an ncRNA transcribed from SPNCRNA.1669, which inhibited untimely initiation of sexual differentiation. A domain that was predicted as conserved secondary structure by the computational operations was essential for the ncRNA to function. Thus, this study demonstrates that in silico selection focusing on conservation of the secondary structure over species is a powerful method to pinpoint novel functional ncRNAs.     

Sequence complementarity between human noncoding RNAs and SARS-CoV-2 genes: What are the implications for human health?

ObjectivesTo investigate in silico the presence of nucleotide sequence complementarity between the RNA genome of Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) and human non-coding (nc)RNA genes.MethodsThe FASTA sequence (NC_045512.2) of each of the 11 SARS-CoV-2 isolate Wuhan-Hu-1 genes was retrieved from NCBI.nlm.nih.gov/gene and the Ensembl.org library interrogated for any base-pair match with human ncRNA genes. SARS-CoV-2 gene-matched human ncRNAs were screened for functional activity using bioinformatic analysis. Finally, associations between identified ncRNAs and human diseases were searched in GWAS databases.ResultsA total of 252 matches were found between the nucleotide sequence of SARS-CoV-2 genes and human ncRNAs. With the exception of two small nuclear RNAs, all of them were long non-coding (lnc)RNAs expressed mainly in testis and central nervous system under physiological conditions. The percentage of alignment ranged from 91.30% to 100% with a mean nucleotide alignment length of 17.5 ± 2.4. Thirty-three (13.09%) of them contained predicted R-loop forming sequences, but none of these intersected the complementary sequences of SARS-CoV-2. However, in 31 cases matches fell on ncRNA regulatory sites, whose adjacent coding genes are mostly involved in cancer, immunological and neurological pathways. Similarly, several polymorphic variants of detected non-coding genes have been associated with neuropsychiatric and proliferative disorders.ConclusionThis pivotal in silico study shows that SARS-CoV-2 genes have Watson-Crick nucleotide complementarity to human ncRNA sequences, potentially disrupting ncRNA epigenetic control of target genes. It remains to be elucidated whether this could result in the development of human disease in the long term.     

Identification and annotation of noncoding RNAs in Saccharomycotina

The importance of ncRNAs in biological processes makes their annotation an essential component of any genome-sequencing project. The identification of ncRNAs in genomes requires specific expertise and tools that are distinct from the traditional protein gene annotation tools. Here, we describe the assembly of two automatic annotation pipelines, integrating publicly available tools, for homology and de novo ncRNA search in genomes. We applied both pipelines to 10 Saccharomycotina genomes and were able to find and annotate 693 ncRNA genes, corresponding to 81% of the ncRNAs expected for those genomes assuming the number of ncRNAs in Saccharomyces cerevisiae (86) as a reference. Several new ncRNAs, not yet known in the Saccharomycotina clade, were also detected. The results show the feasibility of automatic search for ncRNAs in full genomes and the utility of such approaches in large multi-genome sequencing and annotation projects.     

Identification of non-coding RNAs with a new composite feature in the Hybrid Random Forest Ensemble algorithm

To identify non-coding RNA (ncRNA) signals within genomic regions, a classification tool was developed based on a hybrid random forest (RF) with a logistic regression model to efficiently discriminate short ncRNA sequences as well as long complex ncRNA sequences. This RF-based classifier was trained on a well-balanced dataset with a discriminative set of features and achieved an accuracy, sensitivity and specificity of 92.11%, 90.7% and 93.5%, respectively. The selected feature set includes a new proposed feature, SCORE. This feature is generated based on a logistic regression function that combines five significant features—structure, sequence, modularity, structural robustness and coding potential—to enable improved characterization of long ncRNA (lncRNA) elements. The use of SCORE improved the performance of the RF-based classifier in the identification of Rfam lncRNA families. A genome-wide ncRNA classification framework was applied to a wide variety of organisms, with an emphasis on those of economic, social, public health, environmental and agricultural significance, such as various bacteria genomes, the Arthrospira (Spirulina) genome, and rice and human genomic regions. Our framework was able to identify known ncRNAs with sensitivities of greater than 90% and 77.7% for prokaryotic and eukaryotic sequences, respectively. Our classifier is available at http://ncrna-pred.com/HLRF.htm.     

Development and characterization of non-coding RNA based simple sequence repeat markers in Capsicum species

Plant growth and development are largely regulated by non-coding RNAs (ncRNA); thus ncRNA based markers would be rewarding in molecular breeding. In the present study, for the first time we developed total 623 ncRNA based SSRs including 119 microRNASSRs (miRNASSRs) and 504 long non-coding RNASSRs (lncRNASSRs) distributed across 12 Capsicum chromosomes. Out of 623 ncRNASSRs, 120 (including 60 each miRNASSRs and lncRNASSRs) were used for genotyping of 96 Capsicum accessions belonging to C. annuum, C. chinense and C. frutescens; and 75% SSRs were polymorphic. Model-based and distance-based cluster analyses identified three species specific clusters, i.e. cluster-I (C. annuum), cluster-II (C. frutescens) and cluster-III (C. chinense); therefore, these SSRs may have a potential role to play in interspecific Capsicum breeding. Tissue specific expression of SSR containing ncRNAs and versatile functions of their targets suggested the usefulness of SSRs for mapping of genes/QTLs and breeding of wide range of traits in Capsicum.