Genome-wide identification of the essential protein-coding genes and long non-coding RNAs for human pan-cancer

2019 ◽  
Vol 35 (21) ◽  
pp. 4344-4349 ◽  
Author(s):  
Yuwei Zhang ◽  
Yang Tao ◽  
Huihui Ji ◽  
Wei Li ◽  
Xingli Guo ◽  
...  
Keyword(s):  
Network Analysis ◽  
Regulatory Network ◽  
Essential Genes ◽  
Supplementary Information ◽  
Published Data ◽  
Biological Processes ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Non Coding Rnas ◽  
Pan Cancer

Abstract Motivation Genome-scale CRISPR/Cas9 system has been a democratized gene editing technique and widely used to investigate gene functions in some biological processes and diseases especially cancers. Aiming to characterize gene aberrations and assess their effects on cancer, we designed a pipeline to identify the essential genes for pan-cancer. Methods CRISPR screening data were used to identify the essential genes that were collected from published data and integrated by Robust Rank Aggregation algorithm. Then, hypergeometrics test and random walks with restart (RWR) were used to predict additional essential genes on broader scale. Finally, the expression status and potential roles of these genes were explored based on TCGA portal and regulatory network analysis. Results We collected 926 samples from 10 CRISPR-based screening studies involving 33 different types of cancer to identify cancer-essential genes, which consists of 799 protein-coding genes (PCGs) and 97 long non-coding RNAs (lncRNAs). Then, we constructed a ‘bi-colored’ network with both PCGs and lncRNAs and applied it to predict additional essential genes including 495 PCGs and 280 lncRNAs on a broader scale using hypergeometrics test and RWR. After obtaining all essential genes, we further investigated their potential roles in cancer and found that essential genes have higher and more stable expression levels, and are associated with multiple cancer-associated biological processes and survival time. The regulatory network analysis detected two intriguing modules of essential genes participating in the regulation of cell cycle and ribosome biogenesis in cancer. Availability and implementation   Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals An integrative atlas of chicken long non-coding genes and their annotations across 25 tissues

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Frédéric Jehl ◽  
Kévin Muret ◽  
Maria Bernard ◽  
Morgane Boutin ◽  
Laetitia Lagoutte ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Biological Processes ◽  
Rna Seq ◽  
Protein Coding ◽  
Tissue Specific ◽  
Protein Coding Genes ◽  
Intergenic Regions ◽  
Immune Tissues ◽  
Non Coding Rnas

AbstractLong non-coding RNAs (LNC) regulate numerous biological processes. In contrast to human, the identification of LNC in farm species, like chicken, is still lacunar. We propose a catalogue of 52,075 chicken genes enriched in LNC (http://www.fragencode.org/), built from the Ensembl reference extended using novel LNC modelled here from 364 RNA-seq and LNC from four public databases. The Ensembl reference grew from 4,643 to 30,084 LNC, of which 59% and 41% with expression ≥ 0.5 and ≥ 1 TPM respectively. Characterization of these LNC relatively to the closest protein coding genes (PCG) revealed that 79% of LNC are in intergenic regions, as in other species. Expression analysis across 25 tissues revealed an enrichment of co-expressed LNC:PCG pairs, suggesting co-regulation and/or co-function. As expected LNC were more tissue-specific than PCG (25% vs. 10%). Similarly to human, 16% of chicken LNC hosted one or more miRNA. We highlighted a new chicken LNC, hosting miR155, conserved in human, highly expressed in immune tissues like miR155, and correlated with immunity-related PCG in both species. Among LNC:PCG pairs tissue-specific in the same tissue, we revealed an enrichment of divergent pairs with the PCG coding transcription factors, as for example LHX5, HXD3 and TBX4, in both human and chicken.

scholarly journals Regulatory Potential of Long Non-Coding RNAs (lncRNAs) in Boar Spermatozoa with Good and Poor Freezability

Life ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 300
Author(s):  
Leyland Fraser ◽  
Łukasz Paukszto ◽  
Anna Mańkowska ◽  
Paweł Brym ◽  
Przemysław Gilun ◽  
...  
Keyword(s):  
Target Genes ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Biological Processes ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Potential Target ◽  
Non Coding Rnas

Long non-coding RNAs (lncRNAs) are suggested to play an important role in the sperm biological processes. We performed de novo transcriptome assembly to characterize lncRNAs in spermatozoa, and to investigate the role of the potential target genes of the differentially expressed lncRNAs (DElncRNAs) in sperm freezability. We detected approximately 4007 DElncRNAs, which were differentially expressed in spermatozoa from boars classified as having good and poor semen freezability (GSF and PSF, respectively). Most of the DElncRNAs were upregulated in boars of the PSF group and appeared to significantly affect the sperm’s response to the cryopreservation conditions. Furthermore, we predicted that the potential target genes were regulated by DElncRNAs in cis or trans. It was found that DElncRNAs of both freezability groups had potential cis- and trans-regulatory effects on different protein-coding genes, such as COX7A2L, TXNDC8 and SOX-7. Gene Ontology (GO) enrichment revealed that the DElncRNA target genes are associated with numerous biological processes, including signal transduction, response to stress, cell death (apoptosis), motility and embryo development. Significant differences in the de novo assembled transcriptome expression profiles of the DElncRNAs between the freezability groups were confirmed by quantitative real-time PCR analysis. This study reveals the potential effects of protein-coding genes of DElncRNAs on sperm functions, which could contribute to further research on their relevance in semen freezability.

scholarly journals Pan-Cancer Analysis Reveals Common and Specific Relationships between Intragenic miRNAs and Their Host Genes

Biomedicines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1263
Author(s):  
Baohong Liu ◽  
Yu Shyr ◽  
Qi Liu
Keyword(s):  
Mirna Biogenesis ◽  
Comprehensive Investigation ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Specific Cancer ◽  
Precursor Mirnas ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
Pan Cancer ◽  
Host Genes

MicroRNAs (miRNAs) are small endogenous non-coding RNAs that play important roles in regulating gene expression. Most miRNAs are located within or close to genes (host). miRNAs and their host genes have either coordinated or independent transcription. We performed a comprehensive investigation on co-transcriptional patterns of miRNAs and host genes based on 4707 patients across 21 cancer types. We found that only 11.6% of miRNA-host pairs were co-transcribed consistently and strongly across cancer types. Most miRNA-host pairs showed a strong coexpression only in some specific cancer types, demonstrating a high heterogenous pattern. For two particular types of intergenic miRNAs, readthrough and divergent miRNAs, readthrough miRNAs showed higher coexpression with their host genes than divergent ones. miRNAs located within non-coding genes had tighter co-transcription with their hosts than those located within protein-coding genes, especially exonic and junction miRNAs. A few precursor miRNAs changed their dominate form between 5′ and 3′ strands in different cancer types, including miR-486, miR-99b, let-7e, miR-125a, let-7g, miR-339, miR-26a, miR-16, and miR-218, whereas only two miRNAs with multiple host genes switched their co-transcriptional partner in different cancer types (miR-219a-1 with SLC39A7/HSD17B8 and miR-3615 with RAB37/SLC9A3R1). miRNAs generated from distinct precursors (such as miR-125b from miR-125b-1 or miR-125b-2) were more likely to have cancer-dependent main contributors. miRNAs and hosts were less co-expressed in KIRC than other cancer types, possibly due to its frequent VHL mutations. Our findings shed new light on miRNA biogenesis and cancer diagnosis and treatments.

scholarly journals Predicting the Functions of Long Noncoding RNAs Using RNA-Seq Based on Bayesian Network

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Yun Xiao ◽  
Yanling Lv ◽  
Hongying Zhao ◽  
Yonghui Gong ◽  
Jing Hu ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Regulatory Network ◽  
Noncoding Rnas ◽  
Nervous System Development ◽  
Long Noncoding Rnas ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Rna Seq ◽  
Protein Coding ◽  
Protein Coding Genes

Long noncoding RNAs (lncRNAs) have been shown to play key roles in various biological processes. However, functions of most lncRNAs are poorly characterized. Here, we represent a framework to predict functions of lncRNAs through construction of a regulatory network between lncRNAs and protein-coding genes. Using RNA-seq data, the transcript profiles of lncRNAs and protein-coding genes are constructed. Using the Bayesian network method, a regulatory network, which implies dependency relations between lncRNAs and protein-coding genes, was built. In combining protein interaction network, highly connected coding genes linked by a given lncRNA were subsequently used to predict functions of the lncRNA through functional enrichment. Application of our method to prostate RNA-seq data showed that 762 lncRNAs in the constructed regulatory network were assigned functions. We found that lncRNAs are involved in diverse biological processes, such as tissue development or embryo development (e.g., nervous system development and mesoderm development). By comparison with functions inferred using the neighboring gene-based method and functions determined using lncRNA knockdown experiments, our method can provide comparable predicted functions of lncRNAs. Overall, our method can be applied to emerging RNA-seq data, which will help researchers identify complex relations between lncRNAs and coding genes and reveal important functions of lncRNAs.

scholarly journals Co‐regulation of long non‐coding RNAs and protein‐coding genes during cell quiescence

2021 ◽  
Vol 35 (S1) ◽  
Author(s):  
Hilary Coller ◽  
Huiling Huang ◽  
Mithun Mitra ◽  
Kaiser Atai ◽  
Kirthana Sarathy
Keyword(s):  
Protein Coding ◽  
Protein Coding Genes ◽  
Cell Quiescence ◽  
Non Coding Rnas

scholarly journals Promising Advances in LINC01116 Related to Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Yating Xu ◽  
Xiao Yu ◽  
Menggang Zhang ◽  
Qingyuan Zheng ◽  
Zongzong Sun ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gastric Cancer ◽  
Lung Cancer ◽  
Cancer Colorectal ◽  
Malignant Tumors ◽  
Biological Processes ◽  
Aberrant Expression ◽  
Protein Coding ◽  
Future Studies ◽  
Non Coding Rnas

Long non-coding RNAs (lncRNAs) are RNAs with a length of no less than 200 nucleotides that are not translated into proteins. Accumulating evidence indicates that lncRNAs are pivotal regulators of biological processes in several diseases, particularly in several malignant tumors. Long intergenic non-protein coding RNA 1116 (LINC01116) is a lncRNA, whose aberrant expression is correlated with a variety of cancers, including lung cancer, gastric cancer, colorectal cancer, glioma, and osteosarcoma. LINC01116 plays a crucial role in facilitating cell proliferation, invasion, migration, and apoptosis. In addition, numerous studies have recently suggested that LINC01116 has emerged as a novel biomarker for prognosis and therapy in malignant tumors. Consequently, we summarize the clinical significance of LINC01116 associated with biological processes in various tumors and provide a hopeful orientation to guide clinical treatment of various cancers in future studies.

scholarly journals DNA methylation patterns of protein-coding genes and long non-coding RNAs in males with schizophrenia

2015 ◽  
Vol 12 (5) ◽  
pp. 6568-6576 ◽  
Author(s):  
QI LIAO ◽  
YUNLIANG WANG ◽  
JIA CHENG ◽  
DONGJUN DAI ◽  
XINGYU ZHOU ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Non Coding Rnas ◽  
Methylation Patterns

FindNonCoding: rapid and simple detection of non-coding RNAs in genomes

2021 ◽  
Author(s):  
Erik S Wright
Keyword(s):  
Pattern Mining ◽  
Ease Of Use ◽  
Supplementary Information ◽  
Sequence Motifs ◽  
Protein Coding ◽  
False Discovery ◽  
Non Coding Rna ◽  
Hairpin Loops ◽  
Simple Detection ◽  
Non Coding Rnas

Abstract Summary Non-coding RNAs are often neglected during genome annotation due to their difficulty of detection relative to protein coding genes. FindNonCoding takes a pattern mining approach to capture the essential sequence motifs and hairpin loops representing a non-coding RNA family and quickly identify matches in genomes. FindNonCoding was designed for ease of use and accurately finds non-coding RNAs with a low false discovery rate. Availability FindNonCoding is implemented within the DECIPHER package (v2.19.3) for R (v4.1) available from Bioconductor. Pre-trained models of common non-coding RNA families are included for bacteria, archaea, and eukarya. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Involvement of Long Non-Coding RNAs (lncRNAs) in Tumor Angiogenesis

2020 ◽  
Vol 6 (4) ◽  
pp. 42 ◽  
Author(s):  
Julia Teppan ◽  
Dominik A. Barth ◽  
Felix Prinz ◽  
Katharina Jonas ◽  
Martin Pichler ◽  
...  
Keyword(s):  
Tumor Angiogenesis ◽  
Biological Processes ◽  
Protein Coding ◽  
Diagnostic Biomarkers ◽  
Oncogenic Pathways ◽  
Therapeutic Molecules ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
Effective Use ◽  
To Receive

Long non-coding RNAs (lncRNAs) are defined as non-protein coding transcripts with a minimal length of 200 nucleotides. They are involved in various biological processes such as cell differentiation, apoptosis, as well as in pathophysiological processes. Numerous studies considered that frequently deregulated lncRNAs contribute to all hallmarks of cancer including metastasis, drug resistance, and angiogenesis. Angiogenesis, the formation of new blood vessels, is crucial for a tumor to receive sufficient amounts of nutrients and oxygen and therefore, to grow and exceed in its size over the diameter of 2 mm. In this review, the regulatory mechanisms of lncRNAs are described, which influence tumor angiogenesis by directly or indirectly regulating oncogenic pathways, interacting with other transcripts such as microRNAs (miRNAs) or modulating the tumor microenvironment. Further, angiogenic lncRNAs occurring in several cancer types such as liver, gastrointestinal cancer, or brain tumors are summarized. Growing evidence on the influence of lncRNAs on tumor angiogenesis verified these transcripts as potential predictive or diagnostic biomarkers or therapeutic targets of anti-angiogenesis treatment. However, there are many unsolved questions left which are pointed out in this review, hence driving comprehensive research in this area is necessary to enable an effective use of lncRNAs as either therapeutic molecules or diagnostic targets in cancer.

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