Co-assembly of stranded and unstranded RNA-seq data improves coding and noncoding transcriptome maps
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE84946 | GEO | 2016/07/29
SECONDARY ACCESSION(S): PRJNA335726
REPOSITORIES: GEO
Similar Datasets
Project description:We want to develop transcriptome assembly pipeline that significantly improves the quality of the assemblies constructed using stranded and/or unstranded RNA-seq data. Transcriptome of mouse embryonic stem cells (mESC) were assembled using stranded and unstranded library generated by Illumina HiSeq 2000
2016-07-29 | E-GEOD-84946 | biostudies-arrayexpress
Project description:The advent of high-throughput RNA sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their orientations (known as unstranded reads) and certain boundary information. Methods to expand the usability of unstranded RNA-seq data by predetermining the orientation of the reads and precisely determining the boundaries of assembled transcripts could significantly benefit the quality of the resulting transcriptome maps. Here, we present a high-performing transcriptome assembly pipeline, called CAFE, that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites. Applying large-scale transcriptomic data comprising 230 billion RNA-seq reads from the ENCODE, Human BodyMap Projects, The Cancer Genome Atlas, and GTEx, CAFE enabled us to predict the directions of about 220 billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map, and a comprehensive lncRNA catalogue that includes thousands of novel lncRNAs. Our pipeline should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of non-coding genomes.
2017-04-01 | GSE97211 | GEO
Project description:The advent of high-throughput RNA sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their orientations (known as unstranded reads) and certain boundary information. Methods to expand the usability of unstranded RNA-seq data by predetermining the orientation of the reads and precisely determining the boundaries of assembled transcripts could significantly benefit the quality of the resulting transcriptome maps. Here, we present a high-performing transcriptome assembly pipeline, called CAFE, that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites. Applying large-scale transcriptomic data comprising 230 billion RNA-seq reads from the ENCODE, Human BodyMap Projects, The Cancer Genome Atlas, and GTEx, CAFE enabled us to predict the directions of about 220 billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map, and a comprehensive lncRNA catalogue that includes thousands of novel lncRNAs. Our pipeline should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of non-coding genomes. This SuperSeries is composed of the SubSeries listed below.
2017-04-01 | GSE97212 | GEO
Project description:New tools for improved long-read transcript assembly and coalescence with its short-read counterpart are required. Using our short- and long-read measurements from different cell lines with spiked-in standards, we systematically compared key parameters and biases in the read alignment and assembly of transcripts. We report a cDNA synthesis artifact in long-read datasets that impacts the identity and quantitation of assembled transcripts. We developed a computational pipeline to strand long-read cDNA libraries that markedly improves assembly of transcripts from long-reads. Incorporating stranded long-reads in a new hybrid assembly approach, we demonstrate its efficacy for improved characterization of challenging lncRNA transcripts. Our workflow can be applied to a wide range of transcriptomics datasets for superior demarcation of transcript ends and refined isoform structure, which can enable better differential gene expression analyses and molecular manipulations of transcripts.
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Project description:New tools for improved long-read transcript assembly and coalescence with its short-read counterpart are required. Using our short- and long-read measurements from different cell lines with spiked-in standards, we systematically compared key parameters and biases in the read alignment and assembly of transcripts. We report a cDNA synthesis artifact in long-read datasets that impacts the identity and quantitation of assembled transcripts. We developed a computational pipeline to strand long-read cDNA libraries that markedly improves assembly of transcripts from long-reads. Incorporating stranded long-reads in a new hybrid assembly approach, we demonstrate its efficacy for improved characterization of challenging lncRNA transcripts. Our workflow can be applied to a wide range of transcriptomics datasets for superior demarcation of transcript ends and refined isoform structure, which can enable better differential gene expression analyses and molecular manipulations of transcripts.
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Project description:DATA FILES FOR MULLIGHAN MEF2D RNASEQ UNSTRANDED
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Project description:A single hematopoietic stem cell can give rise to all blood cells with remarkable fidelity. Here, we define the chromatin accessibility and transcriptional landscape controlling this process in thirteen primary cell types that traverse the hematopoietic hierarchy. Exploiting the finding that enhancer landscapes better reflect cell identity than mRNA levels, we enable "enhancer cytometry" for accurate enumeration of pure cell types from complex populations. We further reveal the lineage ontogeny of genetic elements linked to diverse human diseases. In acute myeloid leukemia, chromatin accessibility reveals distinctive regulatory evolution in pre-leukemic HSCs (pHSCs), leukemia stem cells, and leukemic blasts. These leukemic cells demonstrate unique lineage infidelity, confirmed by single cell regulomes. We further show that pHSCs have a competitive advantage that is conferred by reduced chromatin accessibility at HOXA9 targets and is associated with adverse patient outcomes. Thus, regulome dynamics can provide diverse insights into human hematopoietic development and disease. Transcription profiles of hematopoietic and leukemic cell types, assayed using unstranded RNA-seq, across 13 normal hematopoietic cell types and 3 acute myeloid leukemia cell types. The complete data set contains a total of 81 samples.
2016-06-01 | E-GEOD-74246 | biostudies-arrayexpress
Project description:Constructing high-quality haplotype-resolved genome assemblies has substantially improved the ability to detect and characterize genetic variants. A targeted approach providing readily access to the rich information from haplotype-resolved genome assemblies will be appealing to groups of basic researchers and medical scientists focused on specific genomic regions. Here, using the 4.5 megabase, notoriously difficult-to-assemble major histocompatibility complex (MHC) region as an example, we demonstrated an approach to construct haplotype-resolved assembly of the targeted genomic region with the CRISPR-based enrichment. Compared to the results from haplotype-resolved genome assembly, our targeted approach achieved comparable completeness and accuracy with reduced computing complexity, sequencing cost, as well as the amount of starting materials. Moreover, using the targeted assembled personal MHC haplotypes as the reference both improves the quantification accuracy for sequencing data and enables allele-specific functional genomics analyses of the MHC region. Given its highly efficient use of resources, our approach can greatly facilitate population genetic studies of targeted regions, and may pave a new way to elucidate the molecular mechanisms in disease etiology.
2022-11-15 | GSE192501 | GEO
Project description:Constructing high-quality haplotype-resolved genome assemblies has substantially improved the ability to detect and characterize genetic variants. A targeted approach providing readily access to the rich information from haplotype-resolved genome assemblies will be appealing to groups of basic researchers and medical scientists focused on specific genomic regions. Here, using the 4.5 megabase, notoriously difficult-to-assemble major histocompatibility complex (MHC) region as an example, we demonstrated an approach to construct haplotype-resolved assembly of the targeted genomic region with the CRISPR-based enrichment. Compared to the results from haplotype-resolved genome assembly, our targeted approach achieved comparable completeness and accuracy with reduced computing complexity, sequencing cost, as well as the amount of starting materials. Moreover, using the targeted assembled personal MHC haplotypes as the reference both improves the quantification accuracy for sequencing data and enables allele-specific functional genomics analyses of the MHC region. Given its highly efficient use of resources, our approach can greatly facilitate population genetic studies of targeted regions, and may pave a new way to elucidate the molecular mechanisms in disease etiology.
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