Evidence map›Paper›PMID 31962234›Full record

ArticleiScience2020

Defining lncRNAs Correlated with CHO Cell Growth and IgG Productivity by RNA-Seq.

Davide Vito, Jens Christian Eriksen, Christian Skjødt, Dietmar Weilguny, Søren K Rasmussen, C Mark Smales

Open access · goldAbstract read
In one paragraph

Article in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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 at 3 institutions in 3 countries.

Davide VitoIndustrial Biotechnology Centre and School of Biosciences, University of Kent, Canterbury, Kent CT2 7NJ, UK.
Jens Christian EriksenSymphogen A/S, Pederstrupvej 93, DK-2750 Ballerup, Denmark; AGC Biologics, Vandtårnsvej 83, DK-2860 Søborg, Denmark.
Christian SkjødtSymphogen A/S, Pederstrupvej 93, DK-2750 Ballerup, Denmark.
Dietmar WeilgunySymphogen A/S, Pederstrupvej 93, DK-2750 Ballerup, Denmark; Alligator Bioscience AB, Medicon Village, Scheelevägen 2, 223 63 Lund, Sweden.
Søren K RasmussenSymphogen A/S, Pederstrupvej 93, DK-2750 Ballerup, Denmark.
C Mark SmalesIndustrial Biotechnology Centre and School of Biosciences, University of Kent, Canterbury, Kent CT2 7NJ, UK. Electronic address: c.m.smales@kent.ac.uk.
Symphogen (Denmark) · DKUniversity of Kent · GBMedicon Village · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

How the long non-coding RNA (lncRNA) genome in recombinant protein producing Chinese hamster ovary (CHO) cell lines relates to phenotype is not well described. We therefore defined the CHO cell lncRNA transcriptome from cells grown in controlled miniature bioreactors under fed-batch conditions using RNA-Seq to identify lncRNAs and how the expression of these changes throughout growth and between IgG producers. We identify lncRNAs including Adapt15, linked to ER stress, GAS5, linked to mTOR signaling/growth arrest, and PVT1, linked to Myc expression, which are differentially regulated during fed-batch culture and whose expression correlates to productivity and growth. Changes in (non)-coding RNA expression between the seed train and the equivalent day of fed-batch culture are also reported and compared with existing datasets. Collectively, we present a comprehensive lncRNA CHO cell profiling and identify targets for engineering growth and productivity characteristics of CHO cells.

Indexed as

Biological SciencesBiotechnologyTranscriptomics

Identifiers

PMID31962234
PMCPMC6971398
OpenAlexW2996223224

What OpenQuestion holds

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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.