Dynamic co-expression network analysis of lncRNAs and mRNAs associated with venous congestion

Combined analyses of RNA-sequence and Hi-C along with GWAS loci—A novel approach to dissect keloid disorder genetic mechanism

Keloid disorder is a tumour-like disease with invasive growth and a high recurrence rate. Genetic contribution is well expected due to the presence of autosomal dominant inheritance and various genetic mutations in keloid lesions. However, GWAS failed to reveal functional variants in exon regions but single nucleotide polymorphisms in the non-coding regions, suggesting the necessity of innovative genetic investigation. This study employed combined GWAS, RNA-sequence and Hi-C analyses to dissect keloid disorder genetic mechanisms using paired keloid tissues and normal skins. Differentially expressed genes, miRNAs and lncRNAs mined by RNA-sequence were identified to construct a network. From which, 8 significant pathways involved in keloid disorder pathogenesis were enriched and 6 of them were verified. Furthermore, topologically associated domains at susceptible loci were located via the Hi-C database and ten differentially expressed RNAs were identified. Among them, the functions of six molecules for cell proliferation, cell cycle and apoptosis were particularly examined and confirmed by overexpressing and knocking-down assays. This study firstly revealed unknown key biomarkers and pathways in keloid lesions using RNA-sequence and previously reported mutation loci, indicating a feasible approach to reveal the genetic contribution to keloid disorder and possibly to other diseases that are failed by GWAS analysis alone.

Keloid disorder is a benign skin tumour characterized by uncontrolled fibroproliferative tissue growth, which only occurs in human beings with severe reoccurrence post-therapy. It affects several hundred million people with difficulty to control its growth and relapse. It has been long thought that exonic gene mutations must play an important role, but large-scaled GWAS analyses only revealed 3 single nucleotide polymorphisms in the non-coding regions as previously reported. For the first time, this study demonstrated that the true genetic mechanism is likely to be the dysfunctional epigenetic regulation caused by mutations in regulatory elements at the non-coding region as revealed by the combined analyses of GWAS, RNA-sequence and Hi-C data. This approach may lead to the breakthrough of keloid disorder genetic/epigenetic mechanism, if further large-scaled analyses are performed along with human keloid tissue Hi-C data.

Long Non-coding RNAs: Mechanisms, Experimental, and Computational Approaches in Identification, Characterization, and Their Biomarker Potential in Cancer

Long non-coding RNAs are diverse class of non-coding RNA molecules >200 base pairs of length having various functions like gene regulation, dosage compensation, epigenetic regulation. Dysregulation and genomic variations of several lncRNAs have been implicated in several diseases. Their tissue and developmental specific expression are contributing factors for them to be viable indicators of physiological states of the cells. Here we present an comprehensive review the molecular mechanisms and functions, state of the art experimental and computational pipelines and challenges involved in the identification and functional annotation of lncRNAs and their prospects as biomarkers. We also illustrate the application of co-expression networks on the TCGA-LIHC dataset for putative functional predictions of lncRNAs having a therapeutic potential in Hepatocellular carcinoma (HCC).

Comprehensive analysis of lncRNAs N6-methyladenosine modification in colorectal cancer

BACKGROUND

Long non-coding RNAs (lncRNAs) and their N6-methyladenosine (M6A) modifications are involved in cancer occurrence and development.

METHODS

lncRNA M6A modification in colorectal cancer (CRC) was comprehensively analyzed for the first time.

RESULTS

M6A levels of lnRNAs in CRC tissues were higher than those in tumor-adjacent normal tissues. A total of 8,332 M6A peaks were detected in 6,690 lncRNAs in CRC tissues. Approximately 91% of the modified lncRNAs had unique M6A modification peaks. A total of 383 lncRNAs were differentially methylated in CRC, of which 48.24% had a length of 1-1,000 bp. Most of these were located on chromosomes 1, 2, 7, 11, 16 and 19; 42.3% were within a sense-overlapping exon. RNA sequencing identified 163 differentially expressed lncRNAs in CRC. GO and KEGG analyses revealed that genes near differentially-methylated or -expressed lncRNAs were associated with CRC occurrence and development. Methylation was positively correlated with lncRNA expression levels in CRC and tumor-adjacent normal tissues. More unmethylated than M6A methylated lncRNA molecules were detected. A competing endogenous RNA (ceRNA) and lncRNA-mRNA expression-regulation network revealed a regulatory relationship between lncRNAs, microRNAs (miRNAs), and mRNAs.

CONCLUSIONS

The findings may help improve our understanding of lncRNA function in colorectal cancer.

Inferring and analyzing module-specific lncRNA-mRNA causal regulatory networks in human cancer

It is known that noncoding RNAs (ncRNAs) cover ∼98% of the transcriptome, but do not encode proteins. Among ncRNAs, long noncoding RNAs (lncRNAs) are a large and diverse class of RNA molecules, and are thought to be a gold mine of potential oncogenes, anti-oncogenes and new biomarkers. Although only a minority of lncRNAs is functionally characterized, it is clear that they are important regulators to modulate gene expression and involve in many biological functions. To reveal the functions and regulatory mechanisms of lncRNAs, it is vital to understand how lncRNAs regulate their target genes for implementing specific biological functions. In this article, we review the computational methods for inferring lncRNA-mRNA interactions and the third-party databases of storing lncRNA-mRNA regulatory relationships. We have found that the existing methods are based on statistical correlations between the gene expression levels of lncRNAs and mRNAs, and may not reveal gene regulatory relationships which are causal relationships. Moreover, these methods do not consider the modularity of lncRNA-mRNA regulatory networks, and thus, the networks identified are not module-specific. To address the above two issues, we propose a novel method, MSLCRN, to infer and analyze module-specific lncRNA-mRNA causal regulatory networks. We have applied it into glioblastoma multiforme, lung squamous cell carcinoma, ovarian cancer and prostate cancer, respectively. The experimental results show that MSLCRN, as an expression-based method, could be a useful complementary method to study lncRNA regulations.

Atlas of Schistosoma mansoni long non-coding RNAs and their expression correlation to protein-coding genes

Long non-coding RNAs (lncRNAs) have been widely discovered in several organisms with the help of high-throughput RNA sequencing. LncRNAs are over 200 nt-long transcripts that do not have protein-coding (PC) potential, having been reported in model organisms to act mainly on the overall control of PC gene expression. Little is known about the functionality of lncRNAs in evolutionarily ancient non-model metazoan organisms, like Schistosoma mansoni, the parasite that causes schistosomiasis, one of the most prevalent infectious-parasitic diseases worldwide. In a recent transcriptomics effort, we identified thousands of S. mansoni lncRNAs predicted to be functional along the course of parasite development. Here, we present an online catalog of each of the S. mansoni lncRNAs whose expression is correlated to PC genes along the parasite life-cycle, which can be conveniently browsed and downloaded through a new web resource http://verjolab.usp.br. We also provide access now to navigation on the co-expression networks disclosed in our previous publication, where we correlated mRNAs and lncRNAs transcriptional patterns across five life-cycle stages/forms, pinpointing biological processes where lncRNAs might act upon.

Database URL: http://verjolab.usp.br

Differently expressed long noncoding RNAs and mRNAs in TK6 cells exposed to low dose hydroquinone

Previous studies have shown that long noncoding RNAs (lncRNAs) were related to human carcinogenesis and might be designated as diagnosis and prognosis biomarkers. Hydroquinone (HQ), as one of the metabolites of benzene, was closely relevant to occupational benzene poisoning and occupational leukemia. Using high-throughput sequencing technology, we investigated differences in lncRNA and mRNA expression profiles between experimental group (HQ 20 μmol/L) and control group (PBS). Compared to control group, a total of 65 lncRNAs and 186 mRNAs were previously identified to be aberrantly expressed more than two fold change in experimental group. To validate the sequencing results, we selected 10 lncRNAs and 10 mRNAs for quantitative real-time PCR (qRT-PCR). Through GO annotation and KEGG pathway analysis, we obtained 3 mainly signaling pathways, including P53 signaling pathway, which plays an important role in tumorigenesis and progression. After that, 25 lncRNAs and 32 mRNAs formed the lncRNA-mRNA co-expression network were implemented to play biological functions of the dysregulated lncRNAs transcripts by regulating gene expression. The lncRNAs target genes prediction provided a new idea for the study of lncRNAs. Finally, we have another important discovery, which is screened out 11 new lncRNAs without annotated. All these results uncovered that lncRNA and mRNA expression profiles in TK6 cells exposed to low dose HQ were different from control group, helping to further study the toxicity mechanisms of HQ and providing a new direction for the therapy of leukemia.

The Schistosoma mansoni genome encodes thousands of long non-coding RNAs predicted to be functional at different parasite life-cycle stages

Next Generation Sequencing (NGS) strategies, like RNA-Seq, have revealed the transcription of a wide variety of long non-coding RNAs (lncRNAs) in the genomes of several organisms. In the present work we assessed the lncRNAs complement of Schistosoma mansoni, the blood fluke that causes schistosomiasis, ranked among the most prevalent parasitic diseases worldwide. We focused on the long intergenic/intervening ncRNAs (lincRNAs), hidden within the large amount of information obtained through RNA-Seq in S. mansoni (88 libraries). Our computational pipeline identified 7029 canonically-spliced putative lincRNA genes on 2596 genomic loci (at an average 2.7 isoforms per lincRNA locus), as well as 402 spliced lncRNAs that are antisense to protein-coding (PC) genes. Hundreds of lincRNAs showed traits for being functional, such as the presence of epigenetic marks at their transcription start sites, evolutionary conservation among other schistosome species and differential expression across five different life-cycle stages of the parasite. Real-time qPCR has confirmed the differential life-cycle stage expression of a set of selected lincRNAs. We have built PC gene and lincRNA co-expression networks, unraveling key biological processes where lincRNAs might be involved during parasite development. This is the first report of a large-scale identification and structural annotation of lncRNAs in the S. mansoni genome.