Evidence map›Paper›PMID 27232982›Full record

ArticleeLife2016

Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling.

Anil Raj, Sidney H Wang, Heejung Shim, Arbel Harpak, Yang I Li, Brett Engelmann, Matthew Stephens, Yoav Gilad, Jonathan K Pritchard

Abstract read
In one paragraph

Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed
–field-weighted citation impact
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

98 citing papers in PubMed.

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  10. Proteogenomics Reveals Microproteins in Activated T Cells.Molecular & cellular proteomics : MCP · 2025
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38 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

9 authors.

Anil RajDepartment of Genetics, Stanford University, Stanford, United States.ORCID 0000-0003-4412-0883
Sidney H WangDepartment of Human Genetics, University of Chicago, Chicago, United States.
Heejung ShimDepartment of Human Genetics, University of Chicago, Chicago, United States.
Arbel HarpakDepartment of Biology, Stanford University, Stanford, United States.
Yang I LiDepartment of Genetics, Stanford University, Stanford, United States.ORCID 0000-0002-0736-251X
Brett EngelmannDepartment of Human Genetics, University of Chicago, Chicago, United States.ORCID 0000-0002-9845-6668
Matthew StephensDepartment of Human Genetics, University of Chicago, Chicago, United States.
Yoav GiladDepartment of Human Genetics, University of Chicago, Chicago, United States.
Jonathan K PritchardDepartment of Genetics, Stanford University, Stanford, United States.

Funding

Genome analysis: statistical methods and applicationsR01HG002585 · NHGRI · UNIVERSITY OF WASHINGTON · PI MATTHEW STEPHENS · 2002 to 2026
$8.4M
Analysis and interpretation of noncoding regulatory variationR01MH084703 · NIMH · UNIVERSITY OF CHICAGO · PI GILAD, YOAV, PRITCHARD, JONATHAN K · 2008 to 2015
$3.4M
Genetic and epigenetic controls of gene regulationU01HG007036 · NHGRI · UNIVERSITY OF CHICAGO · PI PRITCHARD, JONATHAN K · 2012 to 2015
$1.4M
NHGRI NIH HHS R01 HG002585NHGRI NIH HHS U01 HG007036NIMH NIH HHS R01 MH084703
6 · The paper itself

Abstract

Accurate annotation of protein coding regions is essential for understanding how genetic information is translated into function. We describe riboHMM, a new method that uses ribosome footprint data to accurately infer translated sequences. Applying riboHMM to human lymphoblastoid cell lines, we identified 7273 novel coding sequences, including 2442 translated upstream open reading frames. We observed an enrichment of footprints at inferred initiation sites after drug-induced arrest of translation initiation, validating many of the novel coding sequences. The novel proteins exhibit significant selective constraint in the inferred reading frames, suggesting that many are functional. Moreover, ~40% of bicistronic transcripts showed negative correlation in the translation levels of their two coding sequences, suggesting a potential regulatory role for these novel regions. Despite known limitations of mass spectrometry to detect protein expressed at low level, we estimated a 14% validation rate. Our work significantly expands the set of known coding regions in humans.

Indexed as

Open Reading FramesProtein BiosynthesisCell LineHumansLymphocytesMolecular BiologyRibosomescomputational biologyevolutionary biologygenomicshidden Markov modelshumannoncoding RNAribosome profilingsystems biologytranslationupstream ORF

Identifiers

PMID27232982
PMCPMC4940163

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Registered trials

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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.