English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

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

MPS-Authors
/persons/resource/persons211439

Xie,  Chen
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons140421

Bekpen,  Cemalettin
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons56786

Künzel,  Sven
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons221670

Keshavarz,  Maryam
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons182509

Krebs-Wheaton,  Rebecca
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons221488

Skrabar,  Neva
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons201528

Ullrich,  Kristian K.
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons211441

Zhang,  Wenyu
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons56962

Tautz,  Diethard
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

External Ressource

Link
(Any fulltext)

Fulltext (public)

journal.pcbi.1008354.pdf
(Publisher version), 3MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Xie, C., Bekpen, C., Künzel, S., Keshavarz, M., Krebs-Wheaton, R., Skrabar, N., et al. (2020). Dedicated transcriptomics combined with power analysis lead to functional understanding of genes with weak phenotypic changes in knockout lines. PLoS Computational Biology, 16(11): e1008354. doi:10.1371/journal.pcbi.1008354.


Cite as: http://hdl.handle.net/21.11116/0000-0007-7777-E
Abstract
Author summary Knockout mice benefit the understanding of gene functions in mammals. However, it has proven difficult for many genes to identify clear phenotypes, related due to lack of sufficient assays. As Lewis Wolpert put it in a famous quote “But did you take them to the opera?”, thus metaphorically alluding to the need to extend phenotyping efforts. This insight led to the establishment of phenotyping pipelines that are nowadays routinely used to characterize knock-out lines. However, transcriptomic approaches based on RNA-Seq have been much less explored for such deep-level studies. We conducted here both, a theoretical power analysis and practical RNA-Seq experiments on two knockout lines with small phenotypic effects to investigate the parameters including sample size, sequencing depth, fold change, and dispersion. Our dedicated RNA-Seq studies discovered thousands of genes with small transcriptional changes and enriched in specific functions in both knockout lines. We find that it is more important to increase the number of samples than to increase the sequencing depth. Our work shows that a deep RNA-Seq study on knockouts is powerful for understanding gene functions in cases of weak phenotypic effects, and provides a guideline for the experimental design of such studies.