Evidence map›Paper›PMID 22951037›Full record

ArticleGenome biology2012

The GENCODE pseudogene resource.

Baikang Pei, Cristina Sisu, Adam Frankish, Cédric Howald, Lukas Habegger, Xinmeng Jasmine Mu, Rachel Harte, Suganthi Balasubramanian, Andrea Tanzer, Mark Diekhans and 4 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 203 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
203citing papers in PubMed, 1 pooled it
16.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

203 citing papers in PubMed, 1 synthesis or guideline pooled it, 347 citations in OpenAlex.

  1. Pooled it
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  7. Article
  8. Article
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143 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 6 institutions in 4 countries.

Baikang PeiProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
Cristina Sisu
Adam Frankish
Cédric Howald
Lukas Habegger
Xinmeng Jasmine Mu
Rachel Harte
Suganthi Balasubramanian
Andrea Tanzer
Mark Diekhans
Alexandre Reymond
Tim J Hubbard
Jennifer Harrow
Mark B Gerstein
Yale University · USWellcome Sanger Institute · GBUniversity of California, Santa Cruz · USUniversity of Lausanne · CHWhitney Museum of American Art · USCentre for Genomic Regulation · ES

Funding

GENCODE Resource ProjectU41HG007234 · NHGRI · SANGER INSTITUTE · PI FLICEK, PAUL · 2013 to 2020
$20.3M
Integrated human genome annotation: generation of a reference gene setU54HG004555 · NHGRI · SANGER INSTITUTE · PI HUBBARD, TIMOTHY JOHN · 2007 to 2012
$11.2M
NHGRI NIH HHS U41 HG007234NHGRI NIH HHS U54 HG004555Wellcome Trust 77198/Z/05/Z
6 · The paper itself

Abstract

backgroundPseudogenes have long been considered as nonfunctional genomic sequences. However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data.

resultsAs part of the GENCODE annotation of the human genome, we present the first genome-wide pseudogene assignment for protein-coding genes, based on both large-scale manual annotation and in silico pipelines. A key aspect of this coupled approach is that it allows us to identify pseudogenes in an unbiased fashion as well as untangle complex events through manual evaluation. We integrate the pseudogene annotations with the extensive ENCODE functional genomics information. In particular, we determine the expression level, transcription-factor and RNA polymerase II binding, and chromatin marks associated with each pseudogene. Based on their distribution, we develop simple statistical models for each type of activity, which we validate with large-scale RT-PCR-Seq experiments. Finally, we compare our pseudogenes with conservation and variation data from primate alignments and the 1000 Genomes project, producing lists of pseudogenes potentially under selection.

conclusionsAt one extreme, some pseudogenes possess conventional characteristics of functionality; these may represent genes that have recently died. On the other hand, we find interesting patterns of partial activity, which may suggest that dead genes are being resurrected as functioning non-coding RNAs. The activity data of each pseudogene are stored in an associated resource, psiDR, which will be useful for the initial identification of potentially functional pseudogenes.

Indexed as

Genome, HumanPseudogenesTranscription, GeneticAnimalsBinding SitesChromatinHumansModels, GeneticModels, StatisticalMolecular Sequence AnnotationPhylogenyPrimatesRegulatory Sequences, Nucleic AcidRNA Polymerase IISelection, GeneticSequence Analysis, DNAChromatinRNA Polymerase IITranscription Factors

Identifiers

PMID22951037
PMCPMC3491395
OpenAlexW1974352732

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.