Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum

Yang Huang, Geoffrey Siwo, Stefan Wuchty, Michael T. Ferdig, Teresa M. Przytycka

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

It is being increasingly recognized that many important phenotypic traits, including various diseases, are governed by a combination of weak genetic effects and their interactions. While the detection of epistatic interactions that involve a non-additive effect of two loci on a quantitative trait is particularly challenging, this interaction type is fundamental for the understanding of genome organization and gene regulation. However, current methods that detect epistatic interactions typically rely on the existence of a strong primary effect, considerably limiting the sensitivity of the search. To fill this gap, we developed a new method, SEE (Symmetric Epistasis Estimation), allowing the genome-wide detection of epistatic interactions without the need for a strong primary effect. We applied our approach to progeny crosses of the human malaria parasite P. falciparum and S. cerevisiae. We found an abundance of epistatic interactions in the parasite and a much smaller number of such interactions in yeast. The genome of P. falciparum also harboured several epistatic interaction hotspots that putatively play a role in drug resistance mechanisms. The abundance of observed epistatic interactions might suggest a mechanism of compensation for the extremely limited repertoire of transcription factors. Interestingly, epistatic interaction hotspots were associated with elevated levels of linkage disequilibrium, an observation that suggests selection pressure acting on P. falciparum, potentially reflecting host-pathogen interactions or drug-induced selection.

Original languageEnglish (US)
Pages (from-to)1544-1552
Number of pages9
JournalMolecular BioSystems
Volume8
Issue number5
DOIs
StatePublished - May 2012

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Biology

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