Dataset Information

Integrative genomic analyses for identification and prioritization of long non-coding RNAs associated with autism.

ABSTRACT: Genetic studies have identified many risk loci for autism spectrum disorder (ASD) although causal factors in the majority of cases are still unknown. Currently, known ASD risk genes are all protein-coding genes; however, the vast majority of transcripts in humans are non-coding RNAs (ncRNAs) which do not encode proteins. Recently, long non-coding RNAs (lncRNAs) were shown to be highly expressed in the human brain and crucial for normal brain development. We have constructed a computational pipeline for the integration of various genomic datasets to identify lncRNAs associated with ASD. This pipeline utilizes differential gene expression patterns in affected tissues in conjunction with gene co-expression networks in tissue-matched non-affected samples. We analyzed RNA-seq data from the cortical brain tissues from ASD cases and controls to identify lncRNAs differentially expressed in ASD. We derived a gene co-expression network from an independent human brain developmental transcriptome and detected a convergence of the differentially expressed lncRNAs and known ASD risk genes into specific co-expression modules. Co-expression network analysis facilitates the discovery of associations between previously uncharacterized lncRNAs with known ASD risk genes, affected molecular pathways and at-risk developmental time points. In addition, we show that some of these lncRNAs have a high degree of overlap with major CNVs detected in ASD genetic studies. By utilizing this integrative approach comprised of differential expression analysis in affected tissues and connectivity metrics from a developmental co-expression network, we have prioritized a set of candidate ASD-associated lncRNAs. The identification of lncRNAs as novel ASD susceptibility genes could help explain the genetic pathogenesis of ASD.

SUBMITTER: Gudenas BL

PROVIDER: S-EPMC5451068 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrative genomic analyses for identification and prioritization of long non-coding RNAs associated with autism.

Gudenas Brian L BL Srivastava Anand K AK Wang Liangjiang L

PloS one 20170531 5

Genetic studies have identified many risk loci for autism spectrum disorder (ASD) although causal factors in the majority of cases are still unknown. Currently, known ASD risk genes are all protein-coding genes; however, the vast majority of transcripts in humans are non-coding RNAs (ncRNAs) which do not encode proteins. Recently, long non-coding RNAs (lncRNAs) were shown to be highly expressed in the human brain and crucial for normal brain development. We have constructed a computational pipel ...[more]

PMID: 28562671

Similar Datasets

Project description:Genetic and environmental factors, alone or in combination, contribute to the pathogenesis of autism spectrum disorder (ASD). Although many protein-coding genes have now been identified as disease risk genes for ASD, a detailed illustration of long non-coding RNAs (lncRNAs) associated with ASD remains elusive. In this study, we first identified ASD-related lncRNAs based on genomic variant data of individuals with ASD from a twin study. In total, 532 ASD-related lncRNAs were identified, and 86.7% of these ASD-related lncRNAs were further validated by an independent copy number variant (CNV) dataset. Then, the functions and associated biological pathways of ASD-related lncRNAs were explored by enrichment analysis of their three different types of functional neighbor genes (i.e., genomic neighbors, competing endogenous RNA (ceRNA) neighbors, and gene co-expression neighbors in the cortex). The results have shown that most of the functional neighbor genes of ASD-related lncRNAs were enriched in nervous system development, inflammatory responses, and transcriptional regulation. Moreover, we explored the differential functions of ASD-related lncRNAs in distinct brain regions by using gene co-expression network analysis based on tissue-specific gene expression profiles. As a set, ASD-related lncRNAs were mainly associated with nervous system development and dopaminergic synapse in the cortex, but associated with transcriptional regulation in the cerebellum. In addition, a functional network analysis was conducted for the highly reliable functional neighbor genes of ASD-related lncRNAs. We found that all the highly reliable functional neighbor genes were connected in a single functional network, which provided additional clues for the action mechanisms of ASD-related lncRNAs. Finally, we predicted several potential drugs based on the enrichment of drug-induced pathway sets in the ASD-altered biological pathway list. Among these drugs, several (e.g., amoxapine, piperine, and diflunisal) were partly supported by the previous reports. In conclusion, ASD-related lncRNAs participated in the pathogenesis of ASD through various known biological pathways, which may be differential in distinct brain regions. Detailed investigation into ASD-related lncRNAs can provide clues for developing potential ASD diagnosis biomarkers and therapy.

Project description:Recently, large numbers of normal human tissues have been profiled for non-coding RNAs and more than fourteen thousand long intergenic non-coding RNAs (lincRNAs) are found expressed in normal human tissues. The functional roles of these normal lincRNAs (nlincRNAs) in the regulation of protein coding genes in normal and disease biology are yet to be established. Here, we have profiled two RNA-seq datasets including cancer and matched non-neoplastic tissues from 12 individuals from diverse demography for both coding genes and nlincRNAs. We find 130 nlincRNAs significantly regulated in cancer, with 127 regulated in the same direction in the two datasets. Interestingly, according to Illumina Body Map, significant numbers of these nlincRNAs display baseline null expression in normal prostate tissues but are specific to other tissues such as thyroid, kidney, liver and testis. A number of the regulated nlincRNAs share loci with coding genes, which are either co-regulated or oppositely regulated in all cancer samples studied here. For example, in all cancer samples i) the nlincRNA, TCONS_00029157, and a neighboring tumor suppressor factor, SIK1, are both down regulated; ii) several thyroid-specific nlincRNAs in the neighborhood of the thyroid-specific gene TPO, are both up-regulated; and iii) the TCONS_00010581, an isoform of HEIH, is down-regulated while the neighboring EZH2 gene is up-regulated in cancer. Several nlincRNAs from a prostate cancer associated chromosomal locus, 8q24, are up-regulated in cancer along with other known prostate cancer associated genes including PCAT-1, PVT1, and PCAT-92. We observe that there is significant bias towards up-regulation of nlincRNAs with as high as 118 out of 127 up-regulated in cancer, even though regulation of coding genes is skewed towards down-regulation. Considering that all reported cancer associated lincRNAs (clincRNAs) are biased towards up-regulation, we conclude that this bias may be functionally relevant.

Dataset Information

Integrative genomic analyses for identification and prioritization of long non-coding RNAs associated with autism.

Publications

Integrative genomic analyses for identification and prioritization of long non-coding RNAs associated with autism.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets