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

PLoS Comput Biol. 2020 Nov 12;16(11):e1008354. doi: 10.1371/journal.pcbi.1008354. eCollection 2020 Nov.


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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Animals
  • Behavior, Animal
  • Computational Biology
  • Extremities / anatomy & histology
  • Female
  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / statistics & numerical data
  • Gene Knockout Techniques*
  • Genetic Association Studies / methods*
  • Genetic Association Studies / statistics & numerical data
  • Male
  • Mice
  • Mice, Inbred C57BL
  • Mice, Knockout
  • Models, Genetic
  • Phenotype
  • Proof of Concept Study
  • RNA-Seq / statistics & numerical data
  • Transcriptome

Grants and funding

This work was supported by a European Research Council advanced grant ( to DT (NewGenes - 322564). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.