Evidence map›Paper›PMID 26253570›Full record

ArticleMolecular systems biology2015

Comprehensive assembly of novel transcripts from unmapped human RNA-Seq data and their association with cancer.

Majid Kazemian, Min Ren, Jian-Xin Lin, Wei Liao, Rosanne Spolski, Warren J Leonard

Abstract read
In one paragraph

Article in Molecular systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

6 authors.

Majid KazemianLaboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute National Institutes of Health, Bethesda, MD, USA.
Min RenLaboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute National Institutes of Health, Bethesda, MD, USA.
Jian-Xin LinLaboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute National Institutes of Health, Bethesda, MD, USA.
Wei LiaoLaboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute National Institutes of Health, Bethesda, MD, USA.
Rosanne SpolskiLaboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute National Institutes of Health, Bethesda, MD, USA.
Warren J LeonardLaboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute National Institutes of Health, Bethesda, MD, USA wjl@helix.nih.gov.

Funding

IL-2 Family Cytokines and their Receptors-- Molecular Regulation via STATsZIAHL005402 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI LEONARD, WARREN J · 2009 to 2025
$26.8M
DNA Sequencing Core (DSC)ZICHL006058 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI ZHU, JUN · 2010 to 2016
$16.6M
Expression, regulation, and role of enhancer RNAs in T helper cellsK22HL125593 · NHLBI · PURDUE UNIVERSITY · PI KAZEMIAN, MAJID · 2017 to 2019
$747k
Intramural NIH HHSNHLBI NIH HHS K22 HL125593PHS HHS K22- KHL125593A
6 · The paper itself

Abstract

Crucial parts of the genome including genes encoding microRNAs and noncoding RNAs went unnoticed for years, and even now, despite extensive annotation and assembly of the human genome, RNA-sequencing continues to yield millions of unmappable and thus uncharacterized reads. Here, we examined > 300 billion reads from 536 normal donors and 1,873 patients encompassing 21 cancer types, identified ~300 million such uncharacterized reads, and using a distinctive approach de novo assembled 2,550 novel human transcripts, which mainly represent long noncoding RNAs. Of these, 230 exhibited relatively specific expression or non-expression in certain cancer types, making them potential markers for those cancers, whereas 183 exhibited tissue specificity. Moreover, we used lentiviral-mediated expression of three selected transcripts that had higher expression in normal than in cancer patients and found that each inhibited the growth of HepG2 cells. Our analysis provides a comprehensive and unbiased resource of unmapped human transcripts and reveals their associations with specific cancers, providing potentially important new genes for therapeutic targeting.

Indexed as

AnimalsBase SequenceBiomarkers, TumorCell Line, TumorCell ProliferationChromosome MappingGene Expression ProfilingGenomeGorilla gorillaHEK293 CellsHep G2 CellsHigh-Throughput Nucleotide SequencingHistonesHumansMicroRNAsMolecular Sequence AnnotationBiomarkers, TumorHistonesMicroRNAsRNA, Long Noncodingcancer‐associated transcriptslong noncoding RNAsunmapped sequencing reads

Identifiers

PMID26253570
PMCPMC4562499

What OpenQuestion holds

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LicenceCC BY
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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.