K562 polyA RNA-Seq
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE34740 | GEO | 2012/11/14
SECONDARY ACCESSION(S): PRJNA150405
REPOSITORIES: GEO
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Project description:RNA-Seq reads and TopHat (Trapnell et al. Bioinformatics 2009) alignments of K562 cell-line transcriptome. These were used to validate the expression of short peptides idenitified by Mass-Spectrometry in K562 cells. K562 polyA+ RNA (Batch 1) and total RNA (batch 2) was purchased from Ambion. We used oligo (dT)-selected polyA+ RNA to construct libraries for RNA-Seq.We then profiled the transcriptome of polyadenylated mRNA-Seq using Illumina sequencing platforms. We then used the sequenced reads to reconstruct the transcriptome using the Cufflinks de-novo assembler (Trapnell et al. Nat.Bio.Tech. 2010). Recent computational and ribosome profiling analyses suggest that many short open reading frames (sORFs) in eukaryotic genomes are translated. However, evidence that these sORFs produce stable polypeptides is lacking. Here we develop a strategy to discover and validate novel sORF-encoded polypeptides (SEPs) in human cells. In total, we detect 117 SEPs, 114 of which are novel, varying in length from 15 to 149 amino acids. Of these, 10 SEPs (0.5%) are derived from long intergenic non-coding RNAs (lincRNAs). We also observe the presence of polycistronic genes and the widespread use of non-AUG start codons, which is a phenomenon historically thought to be rare in the mammalian genome. Quantitative measurements reveal that SEPs can be found at concentrations between ~10-2000 copies per cell, which is within the range of typical cellular proteins. We confirm the translation of a number of these SEPs through heterologous expression of their encoding cDNAs. We also discover that several SEPs possess properties characteristic of functional proteins. These results demonstrate that human sORFs produce numerous stable polypeptides, revealing that the human proteome is larger and more diverse than previously appreciated.
2012-11-14 | E-GEOD-34740 | biostudies-arrayexpress
Project description:Using RNA-Seq (Mortazavi et al., 2008), high-resolution genome-wide maps of the mouse transcriptome across multiple mouse (C57Bl/6) tissues and primary cells were generated. Cells were grown according to the approved ENCODE cell culture protocols (http://genome.ucsc.edu/ENCODE/protocols/cell/mouse). RNA-Seq RNA samples from tissues and primary cells were extracted from Trizol® according to protocol (Invitrogen). PolyA+ RNA was purified with the Dynabeads mRNA purification kit (Invitrogen). The mRNA libraries were prepared for strand-specific sequencing as described previously (Parkhomchuk et al., 2009). Sequencing and Analysis Samples were sequenced on Illumina Genome Analyzer II, Genome Analyzer IIx and HiSeq 2000 platforms for 36 cycles. Image analysis, base calling and alignment to the mouse genome version mm9 were performed using Illumina's RTA. Alignment to the mouse genome was performed using TopHat (Trapnell et al., 2009). Wig files were generated by TopHat and expression levels were calculated with Cufflinks (Trapnell et al., 2010).
2012-05-09 | E-GEOD-36026 | biostudies-arrayexpress
Project description:Purpose: The goal of this study is to identify differentially expressed genes in SETDB2 deficient mouse primary hepatocytes (MPH) treated with dexamethasone when compared to control MPH Methods: Total RNA from MPH treated with either shControl or shSETDB2 adenovirus (pool of 3 mice per group) was isolated by the TRIzol method (Life Technologies) according to manufacturer’s instructions. Total RNA was DNase-treated and RNA integrity was evaluated by Biolanalyzer (Agilent). RNA sequencing was performed by the SBP Genomics Core Facility in Lake Nona (Orlando, FL) using the Illumina HiSeq platform and the following parameters: paired-end read length: 100 BP; number of output reads: 300m reads. The Tophat+Cufflinks pipeline was used for the RNA-seq analysis as described previously (Haas et al., 2013; Trapnell et al., 2012). Differentially expressed genes in shSETDB2 vs. shControl MPH were determined using a 2-fold cutoff, p-value of less than 0.05, and FPKM (fragments per kilobase of transcript per million mapped reads) cutoff of 1. The shSETDB2 and shControl RNA-seq reads were mapped to the mm10 genome using Tophat (Trapnell et al., 2009). The mapping results were further analyzed by Cufflinks, which outputs the final differential gene list.
2016-08-28 | GSE85278 | GEO
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2012-06-06 | E-GEOD-35585 | biostudies-arrayexpress
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Georgi K. Marinov mailto:georgi@caltech.edu (data coordination/informatics/experimental), Diane Trout mailto:diane@caltech.edu (informatics) Brian Williams mailto:bawilli_91125@yahoo.com (experimental)). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). RNA-seq is a method for mapping and quantifying the transcriptome of any organism that has a genomic DNA sequence assembly (Mortazavi et al., 2008). RNA-seq is performed by reverse-transcribing an RNA sample into cDNA, followed by high-throughput DNA sequencing, which was done here on the Illumina HiSeq sequencer. The transcriptome measurements shown on these tracks were performed on polyA selected RNA (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=longPolyA&type=rnaExtract) from total cellular RNA (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=cell&type=localization). PolyA-selected RNA was fragmented by magnesium-catalyzed hydrolysis and then converted into cDNA by random priming and amplified. Paired-end 2x100 bp reads were obtained from each end of a cDNA fragment. Reads were aligned to the mm9 human reference genome using TopHat (Trapnell et al., 2009), a program specifically designed to align RNA-seq reads and discover splice junctions de novo. All sequence and alignments files are available at http://hgwdev.cse.ucsc.edu/cgi-bin/hgFileUi?db=mm9&g=wgEncodeCaltechRnaSeq.
2012-05-10 | GSE37909 | GEO
Project description:RNA-seq is a method for mapping and quantifying the transcriptome of any organism that has a genomic DNA sequence assembly (Mortazavi et al., 2008). RNA-seq is performed by reverse-transcribing an RNA sample into cDNA, followed by high-throughput DNA sequencing, which was done here on the Illumina HiSeq sequencer. The transcriptome measurements shown on these tracks were performed on polyA selected RNA (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=longPolyA&type=rnaExtract) from total cellular RNA (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=cell&type=localization). PolyA-selected RNA was fragmented by magnesium-catalyzed hydrolysis and then converted into cDNA by random priming and amplified. Paired-end 2x100 bp reads were obtained from each end of a cDNA fragment. Reads were aligned to the mm9 human reference genome using TopHat (Trapnell et al., 2009), a program specifically designed to align RNA-seq reads and discover splice junctions de novo. All sequence and alignments files are available at http://hgwdev.cse.ucsc.edu/cgi-bin/hgFileUi?db=mm9&g=wgEncodeCaltechRnaSeq. Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Cells were lysed in RLT buffer (Qiagen RNEasy kit), and processed on RNEasy midi columns according to the manufacturer's protocol, with the inclusion of the "on-column" DNAse digestion step to remove residual genomic DNA. A quantity of 75 µgs of total RNA was selected twice with oligo-dT beads (Dynal) according to the manufacturer's protocol to isolate mRNA from each of the preparations. A quantity of 100 ngs of mRNA was then processed according to the protocol in Mortazavi et al. (2008), and prepared for sequencing on the Illumina GAIIx or HiSeq platforms according to the protocol for the ChIP-Seq DNA genomic DNA kit (Illumina). Paired-end libraries were size-selected around 200 bp (fragment length). Libraries were sequenced with the Illumina HiSeq according to the manufacturer's recommendations. Paired-end reads of 100 bp length were obtained. Reads were mapped to the reference mouse genome (version mm9 with or without the Y chromosome, depending on the sex of the cell line, and without the random chromosomes in all cases) using TopHat (version 1.3.1) (http://tophat.cbcb.umd.edu/). TopHat was used with default settings with the exception of specifying an empirically determined mean inner-mate distance and supplying known ENSEMBL version 63 splice junctions.
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Project description:PolyA Sequencing of K562 Cells
| PRJNA607080 | ENA
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