CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells.
Ontology highlight
ABSTRACT:
SUBMITTER: Liu SJ
PROVIDER: S-EPMC5394926 | biostudies-literature | 2017 Jan
REPOSITORIES: biostudies-literature
Publications
CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells.
Liu S John SJ Horlbeck Max A MA Cho Seung Woo SW Birk Harjus S HS Malatesta Martina M He Daniel D Attenello Frank J FJ Villalta Jacqueline E JE Cho Min Y MY Chen Yuwen Y Mandegar Mohammad A MA Olvera Michael P MP Gilbert Luke A LA Conklin Bruce R BR Chang Howard Y HY Weissman Jonathan S JS Lim Daniel A DA
Science (New York, N.Y.) 20161215 6320
The human genome produces thousands of long noncoding RNAs (lncRNAs)-transcripts >200 nucleotides long that do not encode proteins. Although critical roles in normal biology and disease have been revealed for a subset of lncRNAs, the function of the vast majority remains untested. We developed a CRISPR interference (CRISPRi) platform targeting 16,401 lncRNA loci in seven diverse cell lines, including six transformed cell lines and human induced pluripotent stem cells (iPSCs). Large-scale screeni ...[more]
Similar Datasets
Project description:The human genome produces thousands of long non-coding RNAs (lncRNAs) – transcripts >200 nucleotides long that do not encode proteins. While critical roles in normal biology and disease have been revealed for a subset of lncRNAs, the function of the vast majority remains untested. Here, we developed a CRISPR interference (CRISPRi) platform targeting 16,401 lncRNA loci in 7 diverse cell lines including 6 transformed cell lines and human induced pluripotent stem cells (iPSCs). Large-scale screening identified 499 lncRNA loci required for robust cellular growth, of which 89% showed growth modifying function exclusively in one cell type. We further found that lncRNA knockdown can perturb complex transcriptional networks in a cell type-specific manner. These data underscore the functional importance and cell type-specificity of many lncRNAs.
2016-12-01 | GSE85011 | GEO
Project description:BACKGROUND:Differential gene expression analysis using RNA-seq data is a popular approach for discovering specific regulation mechanisms under certain environmental settings. Both gene ontology (GO) and KEGG pathway enrichment analysis are major processes for investigating gene groups that participate in common biological responses or possess related functions. However, traditional approaches based on differentially expressed genes only detect a few significant GO terms and pathways, which are frequently insufficient to explain all-inclusive gene regulation mechanisms. METHODS:Transcriptomes of survivin (birc5) gene knock-down experimental and wild-type control zebrafish embryos were sequenced and assembled, and a differential expression (DE) gene list was obtained for traditional functional enrichment analysis. In addition to including DE genes with significant fold-change levels, we considered additional associated genes near or overlapped with differentially expressed long noncoding RNAs (DE lncRNAs), which may directly or indirectly activate or inhibit target genes and play important roles in regulation networks. Both the original DE gene list and the additional DE lncRNA-associated genes were combined to perform a comprehensive overrepresentation analysis. RESULTS:In this study, a total of 638 DE genes and 616 DE lncRNA-associated genes (lncGenes) were leveraged simultaneously in searching for significant GO terms and KEGG pathways. Compared to the traditional approach of only using a differential expression gene list, the proposed method of employing DE lncRNA-associated genes identified several additional important GO terms and KEGG pathways. In GO enrichment analysis, 60% more GO terms were obtained, and several neuron development functional terms were retrieved as complete annotations. We also observed that additional important pathways such as the FoxO and MAPK signaling pathways were retrieved, which were shown in previous reports to play important roles in apoptosis and neuron development functions regulated by the survivin gene. CONCLUSIONS:We demonstrated that incorporating genes near or overlapped with DE lncRNAs into the DE gene list outperformed the traditional enrichment analysis method for effective biological functional interpretations. These hidden interactions between lncRNAs and target genes could facilitate more comprehensive analyses.
| S-EPMC5998891 | biostudies-literature
Project description:Genome-wide association studies indicate that many disease susceptibility regions reside in non-protein-coding regions of the genome. Long noncoding RNAs (lncRNAs) are a major component of the noncoding genome, but their biological impacts are not fully understood. Here, we performed a CRISPR interference (CRISPRi) screen on 2263 epidermis-expressed lncRNAs and identified nine novel candidate lncRNAs regulating keratinocyte proliferation. We further characterized a top hit from the screen, progenitor renewal associated non-coding RNA (PRANCR), using RNA interference-mediated knockdown and phenotypic analysis in organotypic human tissue. PRANCR regulates keratinocyte proliferation, cell cycle progression, and clonogenicity. PRANCR-deficient epidermis displayed impaired stratification with reduced expression of differentiation genes that are altered in human skin diseases, including keratins 1 and 10, filaggrin, and loricrin. Transcriptome analysis showed that PRANCR controls the expression of 1136 genes, with strong enrichment for late cell cycle genes containing a CHR promoter element. In addition, PRANCR depletion led to increased levels of both total and nuclear CDKN1A (also known as p21), which is known to govern both keratinocyte proliferation and differentiation. Collectively, these data show that PRANCR is a novel lncRNA regulating epidermal homeostasis and identify other lncRNA candidates that may have roles in this process as well.
| S-EPMC6961571 | biostudies-literature
Project description:In this study, we aimed to explore the long noncoding RNA expression pattern in squamous cell lung cancer (SQCC) on a genome-wide scale. Total RNAs were extracted from 16 lung SQCC patients' normal and matched lung cancer tissues by Trizol reagent. The expression level of genome-wide scale lncRNA and mRNA was determined by microarray. qRT-PCR was used to validate the lncRNA expression level in 47 patients. Data analyses were performed using R and Bioconductor. A total of 2,748 up and 852 down regulated probes were identified to be significantly and differentially expressed in tumor tissues. The annotation result of their co-expressed mRNAs showed that the most significantly related category of GO analysis was development and differentiation, while the most significantly related pathway was cell cycle. Subgroup analysis identified that 46 and 18 probes were specifically differentially expressed in smoking and moderately differentiated tumors, respectively. Our study indicated that clusters of lncRNAs were significantly and differentially expressed in SQCC compared with normal tissues in the same subject. They may exert a significant role in lung cancer development and could be potential targets for future treatment of SQCC.
| S-EPMC4498179 | biostudies-literature
Project description:Long noncoding RNAs (lncRNAs) are one of the most intensively studied groups of noncoding elements. Debate continues over what proportion of lncRNAs are functional or merely represent transcriptional noise. Although characterization of individual lncRNAs has identified approximately 200 functional loci across the Eukarya, general surveys have found only modest or no evidence of long-term evolutionary conservation. Although this lack of conservation suggests that most lncRNAs are nonfunctional, the possibility remains that some represent recent evolutionary innovations. We examine recent selection pressures acting on lncRNAs in mouse populations. We compare patterns of within-species nucleotide variation at approximately 10,000 lncRNA loci in a cohort of the wild house mouse, Mus musculus castaneus, with between-species nucleotide divergence from the rat (Rattus norvegicus). Loci under selective constraint are expected to show reduced nucleotide diversity and divergence. We find limited evidence of sequence conservation compared with putatively neutrally evolving ancestral repeats (ARs). Comparisons of sequence diversity and divergence between ARs, protein-coding (PC) exons and lncRNAs, and the associated flanking regions, show weak, but significantly lower levels of sequence diversity and divergence at lncRNAs compared with ARs. lncRNAs conserved deep in the vertebrate phylogeny show lower within-species sequence diversity than lncRNAs in general. A set of 74 functionally characterized lncRNAs show levels of diversity and divergence comparable to PC exons, suggesting that these lncRNAs are under substantial selective constraints. Our results suggest that, in mouse populations, most lncRNA loci evolve at rates similar to ARs, whereas older lncRNAs tend to show signals of selection similar to PC genes.
| S-EPMC4558870 | biostudies-literature
Project description:BACKGROUND:The technological advances of RNA-seq and de novo transcriptome assembly have enabled genome annotation and transcriptome profiling in highly heterozygous species such as grapevine (Vitis vinifera L.). This work is an attempt to utilize a de novo-assembled transcriptome of the V. vinifera cultivar 'Riesling' to improve annotation of the grapevine reference genome sequence. RESULTS:Here we show that the transcriptome assembly of a single V. vinifera cultivar is insufficient for a complete genome annotation of the grapevine reference genome constructed from V. vinifera PN40024. Further, we provide evidence that the gene models we identified cannot be completely anchored to the previously published V. vinifera PN40024 gene models. In addition to these findings, we present a computational pipeline for the de novo identification of lncRNAs. Our results demonstrate that, in grapevine, lncRNAs are significantly different from protein coding transcripts in such metrics as length, GC-content, minimum free energy, and length-corrected minimum free energy. CONCLUSIONS:In grapevine, high-level heterozygosity necessitates that transcriptome characterization be based on cultivar-specific reference genome sequences. Our results strengthen the hypothesis that lncRNAs have thermodynamically different properties than protein-coding RNAs. The analyses of both coding and non-coding RNAs will be instrumental in uncovering inter-cultivar variation in wild and cultivated grapevine species.
| S-EPMC5712117 | biostudies-literature
Project description:BackgroundComputational analysis of cDNA sequences from multiple organisms suggests that a large portion of transcribed DNA does not code for a functional protein. In mammals, noncoding transcription is abundant, and often results in functional RNA molecules that do not appear to encode proteins. Many long noncoding RNAs (lncRNAs) appear to have epigenetic regulatory function in humans, including HOTAIR and XIST. While epigenetic gene regulation is clearly an essential mechanism in plants, relatively little is known about the presence or function of lncRNAs in plants.Methodology/principal findingsTo explore the connection between lncRNA and epigenetic regulation of gene expression in plants, a computational pipeline using the programming language Python has been developed and applied to maize full length cDNA sequences to identify, classify, and localize potential lncRNAs. The pipeline was used in parallel with an SVM tool for identifying ncRNAs to identify the maximal number of ncRNAs in the dataset. Although the available library of sequences was small and potentially biased toward protein coding transcripts, 15% of the sequences were predicted to be noncoding. Approximately 60% of these sequences appear to act as precursors for small RNA molecules and may function to regulate gene expression via a small RNA dependent mechanism. ncRNAs were predicted to originate from both genic and intergenic loci. Of the lncRNAs that originated from genic loci, ?20% were antisense to the host gene loci.Conclusions/significanceConsistent with similar studies in other organisms, noncoding transcription appears to be widespread in the maize genome. Computational predictions indicate that maize lncRNAs may function to regulate expression of other genes through multiple RNA mediated mechanisms.
| S-EPMC3420876 | biostudies-literature
Project description:OBJECTIVE:Long noncoding RNAs (lncRNAs) represent a rapidly growing class of RNA genes with functions related primarily to transcriptional and post-transcriptional control of gene expression. There is a paucity of information about lncRNA expression and function in human vascular cells. Thus, we set out to identify novel lncRNA genes in human vascular smooth muscle cells and to gain insight into their role in the control of smooth muscle cell phenotypes. APPROACH AND RESULTS:RNA sequencing (RNA-seq) of human coronary artery smooth muscle cells revealed 31 unannotated lncRNAs, including a vascular cell-enriched lncRNA (Smooth muscle and Endothelial cell-enriched migration/differentiation-associated long NonCoding RNA [SENCR]). Strand-specific reverse transcription polymerase chain reaction (PCR) and rapid amplification of cDNA ends indicate that SENCR is transcribed antisense from the 5' end of the FLI1 gene and exists as 2 splice variants. RNA fluorescence in situ hybridization and biochemical fractionation studies demonstrate SENCR is a cytoplasmic lncRNA. Consistent with this observation, knockdown studies reveal little to no cis-acting effect of SENCR on FLI1 or neighboring gene expression. RNA-seq experiments in smooth muscle cells after SENCR knockdown disclose decreased expression of Myocardin and numerous smooth muscle contractile genes, whereas several promigratory genes are increased. Reverse transcription PCR and Western blotting experiments validate several differentially expressed genes after SENCR knockdown. Loss-of-function studies in scratch wound and Boyden chamber assays support SENCR as an inhibitor of smooth muscle cell migration. CONCLUSIONS:SENCR is a new vascular cell-enriched, cytoplasmic lncRNA that seems to stabilize the smooth muscle cell contractile phenotype.
| S-EPMC4024079 | biostudies-literature
Project description:1. Evaluate the diagnostic value of long noncoding RNA (CCAT1) expression by RT-PCR in peripheral blood in colorectal cancer patients versus normal healthy control personal.
2. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in diagnosis of colorectal cancer patients & its relation to tumor staging.
3. Evaluate the clinical utility of detecting long noncoding RNA (CCAT1) expression in precancerous colorectal diseases.
4. Compare long noncoding RNA (CCAT1) expression with traditional marker; carcinoembryonic antigen (CEA) and Carbohydrate antigen 19-9 (CA19-9) in diagnosis of colorectal cancer.
| 2330122 | ecrin-mdr-crc
Project description:The RFAM database defines families of ncRNAs by means of sequence similarities that are sufficient to establish homology. In some cases, such as microRNAs and box H/ACA snoRNAs, functional commonalities define classes of RNAs that are characterized by structural similarities, and typically consist of multiple RNA families. Recent advances in high-throughput transcriptomics and comparative genomics have produced very large sets of putative noncoding RNAs and regulatory RNA signals. For many of them, evidence for stabilizing selection acting on their secondary structures has been derived, and at least approximate models of their structures have been computed. The overwhelming majority of these hypothetical RNAs cannot be assigned to established families or classes. We present here a structure-based clustering approach that is capable of extracting putative RNA classes from genome-wide surveys for structured RNAs. The LocARNA (local alignment of RNA) tool implements a novel variant of the Sankoff algorithm that is sufficiently fast to deal with several thousand candidate sequences. The method is also robust against false positive predictions, i.e., a contamination of the input data with unstructured or nonconserved sequences. We have successfully tested the LocARNA-based clustering approach on the sequences of the RFAM-seed alignments. Furthermore, we have applied it to a previously published set of 3,332 predicted structured elements in the Ciona intestinalis genome (Missal K, Rose D, Stadler PF (2005) Noncoding RNAs in Ciona intestinalis. Bioinformatics 21 (Supplement 2): i77-i78). In addition to recovering, e.g., tRNAs as a structure-based class, the method identifies several RNA families, including microRNA and snoRNA candidates, and suggests several novel classes of ncRNAs for which to date no representative has been experimentally characterized.
| S-EPMC1851984 | biostudies-literature