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Resources » Paper

Labocha MK et al. (2017) BMC Genet "A strategy to apply quantitative epistasis analysis on developmental traits."

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    PMID:
    28506208
    DOI:
    10.1186/s12863-017-0508-4
    Status:
    Publication type:
    Journal_article
    WormBase ID:
    WBPaper00051250

    Labocha MK, Yuan W, Aleman-Meza B, & Zhong W (2017). A strategy to apply quantitative epistasis analysis on developmental traits. BMC Genet, 18, 42. doi:10.1186/s12863-017-0508-4

    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.


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