Dataset Information

Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq.

ABSTRACT: Genomic instability has profound effects on cellular phenotypes. Studies have shown that pluripotent cells with abnormal karyotypes may grow faster, differentiate less and become more resistance to apoptosis. Previously, we showed that microarray gene expression profiles can be utilized for the analysis of chromosomal aberrations by comparing gene expression levels between normal and aneuploid samples. Here we adopted this method for RNA-Seq data and present eSNP-Karyotyping for the detection of chromosomal aberrations, based on measuring the ratio of expression between the two alleles. We demonstrate its ability to detect chromosomal gains and losses in pluripotent cells and their derivatives, as well as meiotic recombination patterns. This method is advantageous since it does not require matched diploid samples for comparison, is less sensitive to global expression changes caused by the aberration and utilizes already available gene expression profiles to determine chromosomal aberrations.

SUBMITTER: Weissbein U

PROVIDER: S-EPMC4941052 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq.

Weissbein Uri U Schachter Maya M Egli Dieter D Benvenisty Nissim N

Nature communications 20160707

Genomic instability has profound effects on cellular phenotypes. Studies have shown that pluripotent cells with abnormal karyotypes may grow faster, differentiate less and become more resistance to apoptosis. Previously, we showed that microarray gene expression profiles can be utilized for the analysis of chromosomal aberrations by comparing gene expression levels between normal and aneuploid samples. Here we adopted this method for RNA-Seq data and present eSNP-Karyotyping for the detection of ...[more]

PMID: 27385103

Similar Datasets

Project description:Measuring allelic RNA expression ratios is a powerful approach for detecting cis-acting regulatory variants, RNA editing, loss of heterozygosity in cancer, copy number variation, and allele-specific epigenetic gene silencing. Whole transcriptome RNA sequencing (RNA-Seq) has emerged as a genome-wide tool for identifying allelic expression imbalance (AEI), but numerous factors bias allelic RNA ratio measurements. Here, we compare RNA-Seq allelic ratios measured in nine different human brain regions with a highly sensitive and accurate SNaPshot measure of allelic RNA ratios, identifying factors affecting reliable allelic ratio measurement. Accounting for these factors, we subsequently surveyed the variability of RNA editing across brain regions and across individuals.We find that RNA-Seq allelic ratios from standard alignment methods correlate poorly with SNaPshot, but applying alternative alignment strategies and correcting for observed biases significantly improves correlations. Deploying these methods on a transcriptome-wide basis in nine brain regions from a single individual, we identified genes with AEI across all regions (SLC1A3, NHP2L1) and many others with region-specific AEI. In dorsolateral prefrontal cortex (DLPFC) tissues from 14 individuals, we found evidence for frequent regulatory variants affecting RNA expression in tens to hundreds of genes, depending on stringency for assigning AEI. Further, we find that the extent and variability of RNA editing is similar across brain regions and across individuals.These results identify critical factors affecting allelic ratios measured by RNA-Seq and provide a foundation for using this technology to screen allelic RNA expression on a transcriptome-wide basis. Using this technology as a screening tool reveals tens to hundreds of genes harboring frequent functional variants affecting RNA expression in the human brain. With respect to RNA editing, the similarities within and between individuals leads us to conclude that this post-transcriptional process is under heavy regulatory influence to maintain an optimal degree of editing for normal biological function.

Dataset Information

Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq.

Publications

Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets