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Gene Coexpression Networks in Human Brain Developmental Transcriptomes Implicate the Association of Long Noncoding RNAs with Intellectual Disability
Author(s) -
Brian Gudenas,
Liangjiang Wang
Publication year - 2015
Publication title -
bioinformatics and biology insights
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 23
ISSN - 1177-9322
DOI - 10.4137/bbi.s29435
Subject(s) - biology , gene , genetics , long non coding rna , computational biology , proband , human genetics , phenotype , copy number variation , rna , genome , mutation
The advent of next-generation sequencing for genetic diagnoses of complex developmental disorders, such as intellectual disability (ID), has facilitated the identification of hundreds of predisposing genetic variants. However, there still exists a vast gap in our knowledge of causal genetic factors for ID as evidenced by low diagnostic yield of genetic screening, in which identifiable genetic causes are not found for the majority of ID cases. Most methods of genetic screening focus on protein-coding genes; however, noncoding RNAs may outnumber protein-coding genes and play important roles in brain development. Long noncoding RNAs (lncRNAs) specifically have been shown to be enriched in the brain and have diverse roles in gene regulation at the transcriptional and posttranscriptional levels. LncRNAs are a vastly uncharacterized group of noncoding genes, which could function in brain development and harbor ID-predisposing genetic variants. We analyzed lncRNAs for coexpression with known ID genes and affected biological pathways within a weighted gene coexpression network derived from RNA-sequencing data spanning human brain development. Several ID-associated gene modules were found to be enriched for lncRNAs, known ID genes, and affected biological pathways. Utilizing a list of de novo and pathogenic copy number variants detected in ID probands, we identified lncRNAs overlapping these genetic structural variants. By integrating our results, we have made a prioritized list of potential ID-associated lncRNAs based on the developing brain gene coexpression network and genetic structural variants found in ID probands.

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