This track is produced as part of the ENCODE Project.
This track displays transcriptional fragments associated with RNA binding proteins in different
using RIP-Chip (Ribonomic) profiling on Affymetrix GeneChip® Human Gene 1.0 ST Arrays.
These sutracks show the genomic location of transcripts associated with the array probes.
Data for this track was produced as part of the
Encyclopedia of DNA Elements (ENCODE) Project.
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-Chip profiling.
Display Conventions and Configuration
This track has multiple subtracks that display individually in the browser.
The subtracks within this track correspond to different antibodies/target
proteins tested in different cell lines.
These subtracks show the genomic location of the mRNA transcripts associated with RNA Binding
Proteins as determined by the Affymetrix GeneChip® Human Gene 1.0 ST Array probes.
Items are shaded by p-value using the formula (maxPossibleScore-((maxPossibleScore/cutOffValue)*pValue))
so that items with more significant expression levels are shaded darker. The p-values are
displayed in the browser convention as -log10(pValue).
RBP-mRNA complexes were purified from cells grown according to the approved
ENCODE cell culture protocols.
Antibodies specific to the RNA Binding Protein (RBP) in question were first coated onto protein A/G containing
magnetic beads and then used to immunoprecipitate the targeted, endogenously-formed mRNP complexes. Antibody-coated
beads were incubated/tumbled with cell lysate overnight in the cold followed by extensive rinsing and subsequent
purification of associated RNA using Phenol/Chloroform extraction and ethanol precipitation.
The associated transcripts were identified using GeneChip® Human Gene 1.0 ST Arrays.
Arrays were analyzed using Agilent's GeneSpringGX software (version 11.0).
Arrays were analyzed a group at a time by applying the Iterative PLIER16 algorithm using quantile normalization.
Probesets whose normalized expression levels (signal value) fell within the 18 to 98 percentile in at least two of the three replicates
were retained for further analysis. A TTest (T7-Tag and RIP-Input) or a one-way ANOVA (samples and controls)
was applied to these probesets and a p-value cutoff of .05 was applied. The Benjamini-Hochberg false discovery rate
algorithm was then applied to generate corrected p-values, also known as q-values.
The RIP-Input was summarized first and selected probesets were retained for further analysis.
Next, the arrays for T7Tag (background/negative control) RIPs were summarized with those retained RIP-input probesets.
Probesets that fit the above criteria for either group (RIP-Input or T7Tag)
were then filtered for those that showed a minimum 2 fold increase of expression in T7Tag versus RIP-Input.
arrays for treatment RIP samples were summarized together with those for RIP-inputs and T7Tag RIPs. Probesets that fit the above
criteria for any group (RIP-Input or T7Tag or samples) were
then filtered for probesets that showed a minimum 2 fold increase of expression in treatment over total.
A similar list was produced for probesets showing the same enrichment in the T7Tag RIP set. Probesets which appeared in both
treatment and negative control at these cutoff stringencies were subtracted from the treatment results as background noise, yielding the final data track.
All experiments (including controls) were performed in and analyzed as triplicates.
Release 2 (September 2011) of this track corrects the scores and the calculated P and Q values.
In this release, the calculated P and Q values are -log10(P) and -log10(Q), and the scores,
and therefore the shading of items, reflect the p-values as described in the Display Conventions
and Configuration section above.
These data were produced and analyzed by a collaboration between the
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 .
Baroni TE, Chittur SV, George AD, Tenenbaum SA.
Advances in RIP-chip analysis : RNA-binding protein
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.
Jain R, Devine T, George AD, Chittur SV, Baroni TE, Penalva LO, Tenenbaum SA.
RNA-Binding Protein Immunoprecipitation-Microarray (Chip) Profiling.
Methods Mol Biol. 2011;703:247-63
Jayaseelan S, Doyle F, Currenti S, Tenenbaum SA.
RIP: An mRNA Localization Technique.
Methods Mol Biol. 2011;714:407-422.
Keene JD, Tenenbaum SA.
Eukaryotic mRNPs may represent posttranscriptional operons.
Mol Cell. 2002;9(6):1161-7.
Penalva LO, Tenenbaum SA, Keene JD.
Gene expression analysis of messenger RNP complexes.
Methods Mol Biol. 2004;257:125-34.
Tenenbaum SA, Carson CC, Lager PJ, Keene JD.
Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays.
Proc Natl Acad Sci U S A. 2000 Dec 19;97(26):14085-90.
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.
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