A strategy to apply quantitative epistasis analysis on developmental traits

dc.citation.articleNumber42en_US
dc.citation.issueNumber1en_US
dc.citation.journalTitleBMC Geneticsen_US
dc.citation.volumeNumber18en_US
dc.contributor.authorLabocha, Marta K.en_US
dc.contributor.authorYuan, Wangen_US
dc.contributor.authorAleman-Meza, Boanergesen_US
dc.contributor.authorZhong, Weiweien_US
dc.date.accessioned2017-05-21T03:32:11Zen_US
dc.date.available2017-05-21T03:32:11Zen_US
dc.date.issued2017en_US
dc.date.updated2017-05-21T03:32:11Zen_US
dc.description.abstractAbstract Background Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. Methods In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Results Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. Conclusions We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.en_US
dc.identifier.citationLabocha, Marta K., Yuan, Wang, Aleman-Meza, Boanerges, et al.. "A strategy to apply quantitative epistasis analysis on developmental traits." <i>BMC Genetics,</i> 18, no. 1 (2017) BioMed Central: http://dx.doi.org/10.1186/s12863-017-0508-4.en_US
dc.identifier.doihttp://dx.doi.org/10.1186/s12863-017-0508-4en_US
dc.identifier.urihttps://hdl.handle.net/1911/94312en_US
dc.language.isoengen_US
dc.publisherBioMed Centralen_US
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en_US
dc.rights.holderThe Author(s).en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleA strategy to apply quantitative epistasis analysis on developmental traitsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
local.sword.agentBioMed Centralen_US
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