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RNA Capture-Seq resolves the deep complexity of the human transcriptome (Illumina)

ABSTRACT: Transcriptomic analyses have revealed an unexpected complexity of the human transcriptome, whose breadth and depth exceeds current RNA sequencing capacity 1-3. Here we combine tiling arrays and RNA sequencing technologies, in an approach we term RNA Capture-Seq, to enable the assembly and characterisation of transcripts whose expression level is below the detection limits of conventional sequencing approaches. By this technique we identify novel exons and splicing patterns to even well-studied genes, such as the p53 and Hox loci, and expose widespread, regulated and remarkably complex noncoding transcription in intergenic gene deserts. We show that unassigned tags observed in conventional RNA sequencing datasets are not noise but can derive from rare transcripts fully assembled by RNA Capture-Seq. We expect RNA Capture-Seq to prove an invaluable technique for future research into gene expression and its relationship to phenotypic variation.

ORGANISM(S): Homo sapiens

PROVIDER: GSE29038 | GEO | 2011/09/12

SECONDARY ACCESSION(S): PRJNA142903

REPOSITORIES: GEO

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RNA Capture-Seq resolves the deep complexity of the human transcriptome (Illumina)

Project description:Transcriptomic analyses have revealed an unexpected complexity of the human transcriptome, whose breadth and depth exceeds current RNA sequencing capacity 1-3. Here we combine tiling arrays and RNA sequencing technologies, in an approach we term RNA Capture-Seq, to enable the assembly and characterisation of transcripts whose expression level is below the detection limits of conventional sequencing approaches. By this technique we identify novel exons and splicing patterns to even well-studied genes, such as the p53 and Hox loci, and expose widespread, regulated and remarkably complex noncoding transcription in intergenic gene deserts. We show that unassigned tags observed in conventional RNA sequencing datasets are not noise but can derive from rare transcripts fully assembled by RNA Capture-Seq. We expect RNA Capture-Seq to prove an invaluable technique for future research into gene expression and its relationship to phenotypic variation. Application of RNA Capture sequencing from human fibroblasts for identifying rare novel transcripts. Hybridization enhancing oligos are designed to cover the full sequencing adaptor and MID sequences during hybridisation. Enhancing Oligo A 5 CCATCTCATCCCTGCGTGTCTCCGACTCAG/3ddc/ Enhancing Oligo B 5' CCTATCCCCTGTGTGCCTTGGCAGTCTCAG/3ddc/

2011-09-12 | E-GEOD-29038 | biostudies-arrayexpress

RNA Capture-Seq resolves the deep complexity of the human transcriptome (454)

Project description:Transcriptomic analyses have revealed an unexpected complexity of the human transcriptome, whose breadth and depth exceeds current RNA sequencing capacity 1-3. Here we combine tiling arrays and RNA sequencing technologies, in an approach we term RNA Capture-Seq, to enable the assembly and characterisation of transcripts whose expression level is below the detection limits of conventional sequencing approaches. By this technique we identify novel exons and splicing patterns to even well-studied genes, such as the p53 and Hox loci, and expose widespread, regulated and remarkably complex noncoding transcription in intergenic regions. We show that unassigned tags observed in conventional RNA sequencing datasets are not noise but can derive from rare transcripts fully assembled by RNA Capture-Seq. We expect RNA Capture-Seq to prove an invaluable technique for future research into gene expression and its relationship to phenotypic variation. Application of RNA Capture sequencing from human fibroblasts for identifying rare novel transcripts. Hybridization enhancing oligos are designed to cover the full sequencing adaptor and MID sequences during hybridisation. Enhancing Oligo A 5 CCATCTCATCCCTGCGTGTCTCCGACTCAG/3ddc/ Enhancing Oligo B 5' CCTATCCCCTGTGTGCCTTGGCAGTCTCAG/3ddc/

2011-09-12 | E-GEOD-29040 | biostudies-arrayexpress

RNA Capture-Seq resolves the deep complexity of the human transcriptome (454)

Project description:Transcriptomic analyses have revealed an unexpected complexity of the human transcriptome, whose breadth and depth exceeds current RNA sequencing capacity 1-3. Here we combine tiling arrays and RNA sequencing technologies, in an approach we term RNA Capture-Seq, to enable the assembly and characterisation of transcripts whose expression level is below the detection limits of conventional sequencing approaches. By this technique we identify novel exons and splicing patterns to even well-studied genes, such as the p53 and Hox loci, and expose widespread, regulated and remarkably complex noncoding transcription in intergenic regions. We show that unassigned tags observed in conventional RNA sequencing datasets are not noise but can derive from rare transcripts fully assembled by RNA Capture-Seq. We expect RNA Capture-Seq to prove an invaluable technique for future research into gene expression and its relationship to phenotypic variation.

2011-09-12 | GSE29040 | GEO

Unbiased Capture Hi-C reveals the potential targets of breast cancer susceptibility loci

Project description:Genome-wide association studies have identified over 70 common variants that are associated with breast cancer risk. Most of these variants map to non-protein-coding regions; several map to gene deserts, regions of several hundred kb lacking protein-coding genes. We hypothesized that gene deserts harbour long-range regulatory elements that can physically interact with target genes to influence their expression. To test this, we developed Capture Hi-C (CHi-C), which by incorporating a sequence capture step into a Hi-C protocol, allows high-resolution analysis of targeted regions of the genome. We used CHi-C to investigate long-range interactions at three breast cancer gene deserts mapping to 2q35, 8q24.21 and 9q31.2. We identified interaction peaks between putative regulatory elements ("bait fragments") within the captured regions and "targets" that included both protein-coding genes and long non-coding (lnc)RNAs, over distances of 6.6 kb to 2.6 Mb. Target protein-coding genes were IGFBP5, KLF4, NSMCE2 and MYC; target lncRNAs included DIRC3, PVT1 and CCDC26. For two gene deserts we were able to define a set of SNPs that were correlated with the published risk variant and that clustered within the bait end of an interaction peak. Preliminary functional analyses implicate one SNP (rs12613955; 2q35) as a potentially functional variant. Capture Hi-C was carried out in BT483, SUM44, and GM06990 cell lines to investigate breast cancer risk loci 2q35, 8q24.21 and 9q31.2.

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RNA Capture-Seq resolves the deep complexity of the human transcriptome

Project description:This SuperSeries is composed of the SubSeries listed below.

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