NONCODE: an integrated knowledge database of non-coding RNAs

NONCODE is an integrated knowledge database dedicated to non-coding RNAs (ncRNAs), that is to say, RNAs that function without being translated into proteins. All ncRNAs in NONCODE were filtered automatically from literature and GenBank, and were later manually curated. The distinctive features of NONCODE are as follows: (i) the ncRNAs in NONCODE include almost all the types of ncRNAs, except transfer RNAs and ribosomal RNAs. (ii) All ncRNA sequences and their related information (e.g. function, cellular role, cellular location, chromosomal information, etc.) in NONCODE have been confirmed manually by consulting relevant literature: more than 80% of the entries are based on experimental data. (iii) Based on the cellular process and function, which a given ncRNA is involved in, we introduced a novel classification system, labeled process function class, to integrate existing classification systems. (iv) In addition, some 1100 ncRNAs have been grouped into nine other classes according to whether they are specific to gender or tissue or associated with tumors and diseases, etc. (v) NONCODE provides a user-friendly interface, a visualization platform and a convenient search option, allowing efficient recovery of sequence, regulatory elements in the flanking sequences, secondary structure, related publications and other information. The first release of NONCODE (v1.0) contains 5339 non-redundant sequences from 861 organisms, including eukaryotes, eubacteria, archaebacteria, virus and viroids. Access is free for all users through a web interface at http://noncode.bioinfo.org.cn

Proteasome Activity Influences UV-Mediated Subnuclear Localization Changes of NPM

Peer reviewe

The proapoptotic gene interferon regulatory factor-1 mediates the antiproliferative outcome of paired box 2 gene and tamoxifen

Funder: Norges Forskningsråd (Research Council of Norway); doi: https://doi.org/10.13039/501100005416Funder: Kreftforeningen (Norwegian Cancer Society); doi: https://doi.org/10.13039/100008730Abstract: Tamoxifen is the most prescribed selective estrogen receptor (ER) modulator in patients with ER-positive breast cancers. Tamoxifen requires the transcription factor paired box 2 protein (PAX2) to repress the transcription of ERBB2/HER2. Now, we identified that PAX2 inhibits cell growth of ER+/HER2− tumor cells in a dose-dependent manner. Moreover, we have identified that cell growth inhibition can be achieved by expressing moderate levels of PAX2 in combination with tamoxifen treatment. Global run-on sequencing of cells overexpressing PAX2, when coupled with PAX2 ChIP-seq, identified common targets regulated by both PAX2 and tamoxifen. The data revealed that PAX2 can inhibit estrogen-induced gene transcription and this effect is enhanced by tamoxifen, suggesting that they converge on repression of the same targets. Moreover, PAX2 and tamoxifen have an additive effect and both induce coding genes and enhancer RNAs (eRNAs). PAX2–tamoxifen upregulated genes are also enriched with PAX2 eRNAs. The enrichment of eRNAs is associated with the highest expression of genes that positivity regulate apoptotic processes. In luminal tumors, the expression of a subset of these proapoptotic genes predicts good outcome and their expression are significantly reduced in tumors of patients with relapse to tamoxifen treatment. Mechanistically, PAX2 and tamoxifen coexert an antitumoral effect by maintaining high levels of transcription of tumor suppressors that promote cell death. The apoptotic effect is mediated in large part by the gene interferon regulatory factor 1. Altogether, we conclude that PAX2 contributes to better clinical outcome in tamoxifen treated ER-positive breast cancer patients by repressing estrogen signaling and inducing cell death related pathways

Mutational dynamics and immune evasion in diffuse large B-cell lymphoma explored in a relapse-enriched patient series

Peer reviewe

RNA-Seq of the Nucleolus Reveals Abundant SNORD44-Derived Small RNAs

<div><p>Small non-coding RNAs represent RNA species that are not translated to proteins, but which have diverse and broad functional activities in physiological and pathophysiological states. The knowledge of these small RNAs is rapidly expanding in part through the use of massive parallel (deep) sequencing efforts. We present here the first deep sequencing of small RNomes in subcellular compartments with particular emphasis on small RNAs (sRNA) associated with the nucleolus. The vast majority of the cellular, cytoplasmic and nuclear sRNAs were identified as miRNAs. In contrast, the nucleolar sRNAs had a unique size distribution consisting of 19–20 and 25 nt RNAs, which were predominantly composed of small snoRNA-derived box C/D RNAs (termed as sdRNA). Sequences from 47 sdRNAs were identified, which mapped to both 5′ and 3′ ends of the snoRNAs, and retained conserved box C or D motifs. SdRNA reads mapping to SNORD44 comprised 74% of all nucleolar sdRNAs, and were confirmed by Northern blotting as comprising both 20 and 25 nt RNAs. A novel 120 nt SNORD44 form was also identified. The expression of the SNORD44 sdRNA and 120 nt form was independent of Dicer/Drosha–mediated processing pathways but was dependent on the box C/D snoRNP proteins/sno-ribonucleoproteins fibrillarin and NOP58. The 120 nt SNORD44-derived RNA bound to fibrillarin suggesting that C/D sno-ribonucleoproteins are involved in regulating the stability or processing of SNORD44. This study reveals sRNA cell-compartment specific expression and the distinctive unique composition of the nucleolar sRNAs.</p></div

Long noncoding RNA SMRG regulates Drosophila macrochaetes by antagonizing scute through E(spl)m

It is obvious that the majority of cellular transcripts are long noncoding RNAs (lncRNAs). Although studies suggested that lncRNAs participate in many biological processes through diverse mechanisms, however, little is known about their effects on epidermal mechanoreceptors. Here, we identified one novel Drosophila lncRNA, Scutellar Macrochaetes Regulatory Gene (SMRG), which regulates scutellar macrochaetes that act as mechanoreceptors by antagonizing the proneural gene scute (sc), through the repressor Enhancer-of-split m (E(spl)m). SMRG deficiency induced supernumerary scutellar macrochaetes and simultaneously a high sc RNA level in the adult thorax. Genetically, sc overexpression enhanced this supernumerary phenotype, while heterozygous sc mutant rescued this phenotype, both of which were mediated by E(spl)m. At the molecular level, SMRG recruited E(spl)m to the sc promoter region, which in turn suppressed sc expression. Our work presents a novel function of lncRNA and offers insights into the molecular mechanism underlying mechanoreceptor development.</p

Small RNA read distribution.

<p>sRNAs: miRNAs, snoRNAs, snRNAs.</p><p>misc RNAs: Y RNAs, vault RNAs, lincRNAs.</p><p>Small RNA read distribution.</p

The canonical siRNA-processing pathway is not involved in the regulation of SNORD44 sdRNAs.

<p><i>A–D</i> HeLa cells were transfected with control or Drosha-targeting siRNA and incubated for 48 hours. Cells were fixed and stained for Drosha (<i>A</i>) or DGCR8 (<i>B</i>), and counterstained for DNA. Merged images are shown. Scale bar, 10 µm. (<i>C, D</i>) Image quantifications for (<i>C</i>) Drosha and (<i>D</i>) DCGR8. Mean normalized fold intensity is shown. Error bars, SD. <i>E</i> Nuclear (containing nucleoli) and cytoplasmic fractions were prepared of the cells described in A, and RNA was isolated. Northern hybridization was conducted using the SNORD44 5′ probe. Signal intensities for 120 nt and sdRNAs were quantified and normalized against the mature SNORD44. <i>F</i> HCT116 and HCT116 Dicer −/− cells were subjected to subcellular fractionation, RNA was isolated and Northern hybridization was conducted using the SNORD44 5′ probe. Signal intensities for sdRNAs normalized to mature SNORD44 are provided below. hY1 probe was used as control.</p

Size-distribution of the annotated small RNA sequence reads in the subcellular compartments.

<p><i>A</i> Cellular RNA reads. <i>B</i> Cytoplasmic RNA reads. <i>C</i> Nuclear RNA reads. <i>D</i> Nucleolar RNA reads.</p

RNA-seq read alignment.

<p>sRNA: miRNA, snoRNA, snRNA, Y RNA, Vault RNA, LincRNA.</p><p>RNA-seq read alignment.</p