Background While some non-coding RNAs (ncRNAs) are assigned critical regulatory roles, most remain functionally uncharacterized. This presents a challenge whenever an interesting set of ncRNAs needs to be analyzed in a functional context. Transcripts located close-by on the genome are often regulated together. This genomic proximity on the sequence can hint at a functional association. Results We present a tool, NoRCE, that performs cis enrichment analysis for a given set of ncRNAs. Enrichment is carried out using the functional annotations of the coding genes located proximal to the input ncRNAs. Other biologically relevant information such as topologically associating domain (TAD) boundaries, co-expression patterns, and miRNA target prediction information can be incorporated to conduct a richer enrichment analysis. To this end, NoRCE includes several relevant datasets as part of its data repository, including cell-line specific TAD boundaries, functional gene sets, and expression data for coding & ncRNAs specific to cancer. Additionally, the users can utilize custom data files in their investigation. Enrichment results can be retrieved in a tabular format or visualized in several different ways. NoRCE is currently available for the following species: human, mouse, rat, zebrafish, fruit fly, worm, and yeast. Conclusions NoRCE is a platform-independent, user-friendly, comprehensive R package that can be used to gain insight into the functional importance of a list of ncRNAs of any type. The tool offers flexibility to conduct the users’ preferred set of analyses by designing their own pipeline of analysis. NoRCE is available in Bioconductor and https://github.com/guldenolgun/NoRCE.

Motivation Recent experimental evidence has shown that some long noncoding RNAs (lncRNAs) contain small open reading frames (sORFs) that are translated into functional micropeptides, suggesting that these lncRNAs are misannotated as noncoding. Current methods to detect misannotated lncRNAs rely on ribosome-profiling (Ribo-Seq) and mass-spectrometry experiments, which are cell-type dependent and expensive. Results Here, we propose a computational method to identify possible misannotated lncRNAs from sequence information alone. Our approach first builds deep learning models to discriminate coding and non-coding transcripts and leverages these models’ training dynamics to identify misannotated lncRNAs—i.e. lncRNAs with coding potential. The set of misannotated lncRNAs we identified significantly overlap with experimentally validated ones and closely resemble coding protein sequences as evidenced by significant BLAST hits. Our analysis on a subset of misannotated lncRNA candidates also shows that some ORFs they contain yield high confidence folded structures as predicted by AlphaFold2. This methodology offers promising potential for assisting experimental efforts in characterizing the hidden proteome encoded by misannotated lncRNAs and for curating better datasets for building coding potential predictors. Availability Source code is available at https://github.com/nabiafshan/DetectingMisannotatedLncRNAs. Supplementary information Supplementary data are available at Bioinformatics online.

Human Angiotensin I Converting Enzyme 2 (ACE2) that acts as a receptor for SARS-CoV-2 entry is highly expressed in human type II pneumocytes and enterocytes and similarly in other mammals and zebrafish (Danio rerio). The zebrafish genome has a highly conserved, one-to-one ortholog of ACE2, i.e., ace2, whose expression profile however has not yet been studied during development or in pathologies relevant to COVID-19. Herein, we identified significant development-, tissue- and gender-specific modulations in ace2 expression based on meta-analysis of zebrafish Affymetrix transcriptomics datasets (ndatasets=107, GPL1319 in GEO database). Co-expression network analysis of ace2 revealed distinct positively correlated (carboxypeptidase activity and fibrin clot formation), and negatively correlated (cilia biogenesis/transport and chromatin modifications) STRING network modules. Using additional transcriptomics datasets, we showed zebrafish embryos before 3 days post fertilization (dpf) exhibited low levels of ace2 that increased significantly until 4 dpf implicating a role for ace2 in organogenesis. Re-analysis of RNA-seq datasets from zebrafish adult tissues demonstrated ace2 was expressed highly in intestines, variably in liver, and at lower levels in other organs. In addition, zebrafish females and males showed significant dimorphism in their age-dependent expression of ace2, and between ovary and testis where the latter had higher levels. Moreover, we demonstrated ace2 expression was significantly modulated under different physiological and pathological conditions associated with development, diet, infection, and inflammation. Our findings implicate a novel translational role for zebrafish ace2 in differentiation and pathologies predominantly found in intestines and liver, in which the effects of SARS-CoV-2 could be detrimental.

The original article [1] has been corrected.