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dc.contributor.authorLabocha, Marta K
Yuan, Wang
Aleman-Meza, Boanerges
Zhong, Weiwei
dc.date.accessioned 2017-05-21T03:32:11Z
dc.date.available 2017-05-21T03:32:11Z
dc.date.issued 2017
dc.identifier.citation Labocha, Marta K, Yuan, Wang, Aleman-Meza, Boanerges, et al.. "A strategy to apply quantitative epistasis analysis on developmental traits." BMC Genetics, 18, no. 1 (2017) http://dx.doi.org/10.1186/s12863-017-0508-4.
dc.identifier.urihttps://hdl.handle.net/1911/94312
dc.description.abstract Abstract 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.
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.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.title A strategy to apply quantitative epistasis analysis on developmental traits
dc.type Journal article
dc.citation.journalTitle BMC Genetics
dc.citation.volumeNumber 18
dc.citation.issueNumber 1
dc.contributor.publisher BioMed Central
dc.date.updated 2017-05-21T03:32:11Z
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1186/s12863-017-0508-4
dc.language.rfc3066 en
dc.type.publication publisher version
dcterms.bibliographicCitation BMC Genetics. 2017 May 15;18(1):42
dc.rights.holder The Author(s).
local.sword.agent BioMed Central
dc.citation.articleNumber 42


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This 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.
Except where otherwise noted, this item's license is described as This 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.