High-throughput epistatic analysis is well developed for single cells, but it is still undeveloped for multicellular complex developmental traits. As epistasis analysis is one of the most effective methods of mapping genetic interactions, we developed quantitative epistasis analysis method for two developmental traits (sex ratio and body length) of 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. 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. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3, sdc-1, and set-2, validating the effectiveness of our method in detecting genetic interactions.

https://bmcgenet.biomedcentral.com/articles/10.1186/s12863-017-0508-4

High-throughput epistatic analysis is well developed for single cells, but it is still undeveloped for multicellular complex developmental traits. As epistasis analysis is one of the most effective methods of mapping genetic interactions, we developed quantitative epistasis analysis method for two developmental traits (sex ratio and body length) of 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. 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. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3, sdc-1, and set-2, validating the effectiveness of our method in detecting genetic interactions.

https://bmcgenet.biomedcentral.com/articles/10.1186/s12863-017-0508-4