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ENC RNA Binding SUNY RIP-seq Track Settings
 
RIP-seq from ENCODE/SUNY Albany

Track collection: ENCODE RNA Binding Proteins

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 All Target Protein ELAVL1  PABPC1  RIP-Input  T7Tag 
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 GM12878  ELAVL1  Peaks  Pooled  GM12878 ELAVL1 RIP-seq Analysis from ENCODE/SUNY    Data format   2011-10-18 
 
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 GM12878  PABPC1  Peaks  Pooled  GM12878 PABPC1 RIP-seq Analysis from ENCODE/SUNY    Data format   2011-10-18 
 
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 K562  ELAVL1  Peaks  Pooled  K562 ELAVL1 RIP-seq Analysis from ENCODE/SUNY    Data format   2011-10-18 
 
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 K562  PABPC1  Peaks  Pooled  K562 PABPC1 RIP-seq Analysis from ENCODE/SUNY    Data format   2011-10-18 
     Restriction Policy
Assembly: Human Feb. 2009 (GRCh37/hg19)

Description

The RNA binding protein (RBP) associated mRNA sequencing track (RIP-Seq) is produced as part of the Encyclopedia of DNA Elements (ENCODE) Project. This track displays transcriptional fragments associated with RBP in cell lines K562 and GM12878, using Ribonomic profiling via Illumina SBS.

In eukaryotic organisms gene regulatory networks require an additional level of coordination that links transcriptional and post-transcriptional processes. Messenger RNAs have traditionally been viewed as passive molecules in the pathway from transcription to translation. However, it is now clear that RNA-binding proteins play a major role in regulating multiple mRNAs in order to facilitate gene expression patterns. These tracks show the associated mRNAs that co-precipitate with the targeted RNA-binding proteins using RIP-Seq profiling.

Display Conventions and Configuration

This track is a multi-view composite track. For each view there are multiple subtracks that display individually in the browser. The subtracks within this track correspond to different antibodies/target proteins tested in different cell lines.

Peaks
The Peaks view shows the genomic extent of the sequencing read peaks.

Signal
Density graph of signal enrichment based on a normalized aligned read density (Read Per Million, RPM). RPM is reported in the score field and is equal to the number of reads at that position divided by the total number of reads divided by one million. The Signal view is unflitered and displays dense, continuous data as a graph and the RPM measure assists in visualizing the relative amount of a given transcript across multiple samples.

Alignments
The Alignments view shows reads mapped to the genome. The alignment file follows the standard SAM format of Bowtie output. See the Bowtie Manual for more information about the SAM Bowtie output and the SAM Format Specification for more information on the SAM/BAM file format.
Instructions for configuring multi-view tracks are here.

Methods

RBP-mRNA complexes were purified from cells grown according to the approved ENCODE cell culture protocols . RNA samples were amplified and converted to cDNA with the Nugen Ovation© RNA-Seq System and prepped for sequencing with the Illumina mRNA-Seq protocol. Approximately 30 million single end sequencing reads were obtained for each K562 and GM12878. RIP samples were analyzed for signal that was at or above the 60th percentile and statistically enriched compared to the negative control. Sequences were analyzed using TopHat (Trapnell et al., 2009) with Bowtie (Langmead et al., 2009).

Peaks were called from the top 40% of TopHat normalized reads, with a max gap, min run of (24:48). Unions of overlapping peak regions from total RNA replicates (RIP-Input) are presented with p-value from a one tailed t-test for average signal from replicates versus 0 (no cut-off was used for totals). Replicate overlap for positive RIP treatment peaks (ELAVL1 and PABPC1) are presented with a p-value from one tailed t-test versus signal for same the region in negative control replicates (T7-tag). RIP peaks were from sequences longer than 120 bp and p-value < .05. For both totals (RIP-input) and RIPs, the peak scores are scaled relative p-values between treatment and control.

Credits

These data were produced and analyzed by a collaboration between the Tenenbaum lab at the University at Albany-SUNY, College of Nanoscale Science and Engineering,the Luiz Penalva group at the Greehey Children's Cancer Research Institute, University of Texas Health Science Center and the Microarray Core Facility at the Center for Functional Genomics, Rensselaer, NY.

Contact: Scott Tenenbaum

References

Baroni TE, Chittur SV, George AD, Tenenbaum SA. Advances in RIP-chip analysis : RNA-binding protein immunoprecipitation-microarray profiling . Methods Mol Biol. 2008;419:93-108.

George AD, Tenenbaum SA. MicroRNA modulation of RNA-binding protein regulatory elements . RNA Biol. 2006;3(2):57-9. Epub 2006 Apr 1.

Keene JD, Tenenbaum SA. Eukaryotic mRNPs may represent posttranscriptional operons . Mol Cell. 2002;9(6):1161-7.

Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome . Genome Biology. 2009 Mar; 10:R25.

Penalva LO, Tenenbaum SA, Keene JD. Gene expression analysis of messenger RNP complexes . Methods Mol Biol. 2004;257:125-34.

Tenenbaum SA, Lager PJ, Carson CC, Keene JD. Ribonomics: identifying mRNA subsets in mRNP complexes using antibodies to RNA-binding proteins and genomic arrays . Methods. 2002 Feb;26(2):191-8.

Data Release Policy

Data users may freely use ENCODE data, but may not, without prior consent, submit publications that use an unpublished ENCODE dataset until nine months following the release of the dataset. This date is listed in the Restricted Until column, above. The full data release policy for ENCODE is available here.