Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Allelome.PRO A pipeline to define allele-specific genome features

ABSTRACT: We used RNA-seq data from mouse embryonic fibroblasts from F1 reciprocal crosses to determine a biologically relevant allelic ratio cutoff, and define for the first time an entire allelome. Furthermore, we show that Allelome.PRO detects differential enrichment of H3K4me3 over promoters from ChIP-seq data validating the RNA-seq results. Defining allele-specific genome features from F1 E12.5 mouse embryonic fibroblasts

ORGANISM(S): Mus musculus

SUBMITTER: Daniel Andergassen

PROVIDER: E-GEOD-69168 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data.

Andergassen Daniel D Dotter Christoph P CP Kulinski Tomasz M TM Guenzl Philipp M PM Bammer Philipp C PC Barlow Denise P DP Pauler Florian M FM Hudson Quanah J QJ

Nucleic acids research 20150721 21

Detecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here, we present Allelome.PRO, an automated user-friendly bioinformatics pipeline, which uses high-throughput sequencing data from reciprocal crosses of two genetically distinct mouse strains to detect allele-specific expression and chromatin modifications. Allelome.PRO extends approaches used in previous studies that exclusively analyzed imprinted expre ...[more]

PMID: 26202974

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Project description:Background: Long non-coding RNAs (lncRNAs) are increasingly implicated as gene regulators and may ultimately be more numerous than protein-coding genes in the human genome. Despite large numbers of reported lncRNAs, reference annotations are likely incomplete due to their lower and tighter tissue-specific expression compared to mRNAs. An unexplored factor potentially confounding lncRNA identification is inter-individual expression variability. Here, we characterize lncRNA natural expression variability in human primary granulocytes. Results: We annotate granulocyte lncRNAs and mRNAs in RNA-seq data from ten healthy individuals, identifying multiple lncRNAs absent from reference annotations, and use this to investigate three known features (higher tissue-specificity, lower expression, and reduced splicing efficiency) of lncRNAs relative to mRNAs. Expression variability was examined in seven individuals sampled three times at one or more than one month intervals. We show that lncRNAs display significantly more inter-individual expression variability compared to mRNAs. We confirm this finding in 2 independent human datasets by analyzing multiple tissues from the GTEx project and lymphoblastoid cell lines from the GEUVADIS project. Using the latter dataset we also show that including more human donors into the transcriptome annotation pipeline allows identification of an increasing number of lncRNAs, but minimally affects mRNA gene number. Conclusions: A comprehensive annotation of lncRNAs is known to require an approach that is sensitive to low and tight tissue-specific expression. Here we show that increased inter-individual expression variability is an additional general lncRNA feature to consider when creating a comprehensive annotation of human lncRNAs or proposing their use as prognostic or disease markers. We used PolyA+ RNA-seq data from human primary granulocytes of 10 healthy individuals to de novo annotate lncRNAs and mRNAs in this cell type and ribosomal depleted (total) RNA-seq data from seven of these individuals sampled three times to analyze lncRNA amd mRNA expression variability

Project description:Many thousand long non-coding (lnc) RNAs are mapped in the human genome. Time consuming studies using reverse genetic approaches by post-transcriptional knock-down or genetic modification of the locus demonstrated diverse biological functions for a few of these transcripts. The Human Gene Trap Mutant Collection in haploid KBM7 cells is a ready-to-use tool for studying protein-coding gene function. As lncRNAs show remarkable differences in RNA biology compared to protein-coding genes, it is unclear if this gene trap collection is useful for functional analysis of lncRNAs. Here we use the uncharacterized LOC100288798 lncRNA as a model to answer this question. Using public RNA-seq data we show that LOC100288798 is ubiquitously expressed, but inefficiently spliced. The minor spliced LOC100288798 isoforms are exported to the cytoplasm, whereas the major unspliced isoform is nuclear localized. This shows that LOC100288798 RNA biology differs markedly from typical mRNAs. De novo assembly from RNA-seq data suggests that LOC100288798 extends 289kb beyond its annotated 3' end and overlaps the downstream SLC38A4 gene. Three cell lines with independent gene trap insertions in LOC100288798 were available from the KBM7 gene trap collection. RT-qPCR and RNA-seq confirmed successful lncRNA truncation and its extended length. Expression analysis from RNA-seq data shows significant deregulation of 41 protein-coding genes upon LOC100288798 truncation. Our data shows that gene trap collections in human haploid cell lines are useful tools to study lncRNAs, and identifies the previously uncharacterized LOC100288798 as a potential gene regulator. We cultured and processed 8 KBM7 cell lines in one batch. These cell lines were: two wild type KBM7 cells (WT2 and WT3), two monoclonal KBM7 cell lines with gene trap cassette insertions outside of the body of LOC100288798 (C1 and C2), two independently obtained KBM7 clones with gene trap cassette insertion 3kb downstream LOC100288798 transcriptional start site (TSS) (3kb1 and 3kb2), one independently obtained KBM7 clone with gene trap cassette insertion 100kb downstream LOC100288798 TSS replicated twice at the thawing step (100kb1 and 100kb2). We isolated total RNA from all th 8 cell lines, applied DNAseI treatment and ribosomal RNA depletion, and thhen prepared strand-specific RNA-seq libraries, which were pooled in equal molarities and sequenced using Illumina HiSeq 2000 (8 pooled samples were sequence on 2 lanes). We performed 50bp single-end RNA-seq. We used these 8 samples (4 untreated: WT2, WT3, C1, C2 and 4 treated:3kb1, 3kb2, 100kbk1, 100kb2) to analyze genome-wide gene deregulation associated with LOC100288798 lncRNA truncation

Dataset Information

Allelome.PRO A pipeline to define allele-specific genome features

Publications

Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data.

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