Evidence map›Paper›PMID 33180766›Full record

ArticlePLoS computational biology2020

Dedicated transcriptomics combined with power analysis lead to functional understanding of genes with weak phenotypic changes in knockout lines.

Chen Xie, Cemalettin Bekpen, Sven Künzel, Maryam Keshavarz, Rebecca Krebs-Wheaton, Neva Skrabar, Kristian K Ullrich, Wenyu Zhang, Diethard Tautz

Open access · goldAbstract readValidation Study
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
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  4. De Novo Genes.Annual review of genetics · 2024
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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

9 authors at 1 institution in 1 country.

Chen XieDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.ORCID 0000-0002-6183-7301
Cemalettin BekpenDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.
Sven KünzelDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.
Maryam KeshavarzDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.ORCID 0000-0002-9029-4318
Rebecca Krebs-WheatonDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.ORCID 0000-0001-8954-1994
Neva SkrabarDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.
Kristian K UllrichDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.ORCID 0000-0003-4308-9626
Wenyu ZhangDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.ORCID 0000-0002-2507-3033
Diethard TautzDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön, Germany.ORCID 0000-0002-0460-5344
Max Planck Institute for Evolutionary Biology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systematic knockout studies in mice have shown that a large fraction of the gene replacements show no lethal or other overt phenotypes. This has led to the development of more refined analysis schemes, including physiological, behavioral, developmental and cytological tests. However, transcriptomic analyses have not yet been systematically evaluated for non-lethal knockouts. We conducted a power analysis to determine the experimental conditions under which even small changes in transcript levels can be reliably traced. We have applied this to two gene disruption lines of genes for which no function was known so far. Dedicated phenotyping tests informed by the tissues and stages of highest expression of the two genes show small effects on the tested phenotypes. For the transcriptome analysis of these stages and tissues, we used a prior power analysis to determine the number of biological replicates and the sequencing depth. We find that under these conditions, the knockouts have a significant impact on the transcriptional networks, with thousands of genes showing small transcriptional changes. GO analysis suggests that A930004D18Rik is involved in developmental processes through contributing to protein complexes, and A830005F24Rik in extracellular matrix functions. Subsampling analysis of the data reveals that the increase in the number of biological replicates was more important that increasing the sequencing depth to arrive at these results. Hence, our proof-of-principle experiment suggests that transcriptomic analysis is indeed an option to study gene functions of genes with weak or no traceable phenotypic effects and it provides the boundary conditions under which this is possible.

Indexed as

Gene Knockout TechniquesAnimalsBehavior, AnimalComputational BiologyExtremitiesFemaleGene Expression ProfilingGenetic Association StudiesMaleMiceMice, Inbred C57BLMice, KnockoutModels, GeneticPhenotypeProof of Concept StudyRNA-Seq

Identifiers

PMID33180766
PMCPMC7685438
OpenAlexW3104465474

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.