Dataset Information

LincSNP: a database of linking disease-associated SNPs to human large intergenic non-coding RNAs.

ABSTRACT: BACKGROUND: Genome-wide association studies (GWAS) have successfully identified a large number of single nucleotide polymorphisms (SNPs) that are associated with a wide range of human diseases. However, many of these disease-associated SNPs are located in non-coding regions and have remained largely unexplained. Recent findings indicate that disease-associated SNPs in human large intergenic non-coding RNA (lincRNA) may lead to susceptibility to diseases through their effects on lincRNA expression. There is, therefore, a need to specifically record these SNPs and annotate them as potential candidates for disease. DESCRIPTION: We have built LincSNP, an integrated database, to identify and annotate disease-associated SNPs in human lincRNAs. The current release of LincSNP contains approximately 140,000 disease-associated SNPs (or linkage disequilibrium SNPs), which can be mapped to around 5,000 human lincRNAs, together with their comprehensive functional annotations. The database also contains annotated, experimentally supported SNP-lincRNA-disease associations and disease-associated lincRNAs. It provides flexible search options for data extraction and searches can be performed by disease/phenotype name, SNP ID, lincRNA name and chromosome region. In addition, we provide users with a link to download all the data from LincSNP and have developed a web interface for the submission of novel identified SNP-lincRNA-disease associations. CONCLUSIONS: The LincSNP database aims to integrate disease-associated SNPs and human lincRNAs, which will be an important resource for the investigation of the functions and mechanisms of lincRNAs in human disease. The database is available at http://bioinfo.hrbmu.edu.cn/LincSNP.

SUBMITTER: Ning S

PROVIDER: S-EPMC4038069 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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LincSNP: a database of linking disease-associated SNPs to human large intergenic non-coding RNAs.

Ning Shangwei S Zhao Zuxianglan Z Ye Jingrun J Wang Peng P Zhi Hui H Li Ronghong R Wang Tingting T Li Xia X

BMC bioinformatics 20140520

<h4>Background</h4>Genome-wide association studies (GWAS) have successfully identified a large number of single nucleotide polymorphisms (SNPs) that are associated with a wide range of human diseases. However, many of these disease-associated SNPs are located in non-coding regions and have remained largely unexplained. Recent findings indicate that disease-associated SNPs in human large intergenic non-coding RNA (lincRNA) may lead to susceptibility to diseases through their effects on lincRNA ex ...[more]

PMID: 24885522

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Project description:BACKGROUND: The advent of large-scale gene expression technologies has helped to reveal in eukaryotic cells, the existence of thousands of non-coding transcripts, whose function and significance remain mostly poorly understood. Among these non-coding transcripts, long non-coding RNAs (lncRNAs) are the least well-studied but are emerging as key regulators of diverse cellular processes. In the present study, we performed a survey in bovine Longissimus thoraci of lincRNAs (long intergenic non-coding RNAs not overlapping protein-coding transcripts). To our knowledge, this represents the first such study in bovine muscle. RESULTS: To identify lincRNAs, we used paired-end RNA sequencing (RNA-Seq) to explore the transcriptomes of Longissimus thoraci from nine Limousin bull calves. Approximately 14-45 million paired-end reads were obtained per library. A total of 30,548 different transcripts were identified. Using a computational pipeline, we defined a stringent set of 584 different lincRNAs with 418 lincRNAs found in all nine muscle samples. Bovine lincRNAs share characteristics seen in their mammalian counterparts: relatively short transcript and gene lengths, low exon number and significantly lower expression, compared to protein-encoding genes. As for the first time, our study identified lincRNAs from nine different samples from the same tissue, it is possible to analyse the inter-individual variability of the gene expression level of the identified lincRNAs. Interestingly, there was a significant difference when we compared the expression variation of the 418 lincRNAs with the 10,775 known selected protein-encoding genes found in all muscle samples. In addition, we found 2,083 pairs of lincRNA/protein-encoding genes showing a highly significant correlated expression. Fourteen lincRNAs were selected and 13 were validated by RT-PCR. Some of the lincRNAs expressed in muscle are located within quantitative trait loci for meat quality traits. CONCLUSIONS: Our study provides a glimpse into the lincRNA content of bovine muscle and will facilitate future experimental studies to unravel the function of these molecules. It may prove useful to elucidate their effect on mechanisms underlying the genetic variability of meat quality traits. This catalog will complement the list of lincRNAs already discovered in cattle and therefore will help to better annotate the bovine genome.

Dataset Information

LincSNP: a database of linking disease-associated SNPs to human large intergenic non-coding RNAs.

Publications

LincSNP: a database of linking disease-associated SNPs to human large intergenic non-coding RNAs.

Similar Datasets

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