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GeneticsG3 Genes Genomes Genetics
Peer-reviewed journal article

Variation in filamentous growth and response to quorum-sensing compounds in environmental isolates of Saccharomyces cerevisiae

Benedict Adam LenhartiD, Brianna MeeksiD, Helen A. MurphyiD

Abstract

In fungi, filamentous growth is a major developmental transition that occurs in response to environmental cues. In diploid Saccharomyces cerevisiae, it is known as pseudohyphal growth and presumed to be a foraging mechanism. Rather than normal unicellular growth, multicellular filaments composed of elongated, attached cells spread over and into surfaces. This morphogenetic switch can be induced through quorum sensing with the aromatic alcohols phenylethanol and tryptophol. Most research investigating pseudohyphal growth has been conducted in a single lab background, {Sigma}1278b. To investigate the natural variation in this phenotype and its induction, we assayed the diverse 100-genomes collection of environmental S. cerevisiae isolates. Using computational image analysis, we quantified the production of pseudohyphae and observed a large amount of variation. Unlike ecological niche, population membership was associated with pseudohyphal growth, with the West African population having the most. Surprisingly, most strains showed little or no response to exogenous phenylethanol or tryptophol. We also investigated the amount of natural genetic variation in pseudohyphal growth using a mapping population derived from a single, highly-heterozygous clinical isolate that contained as much phenotypic variation as the environmental panel. A bulk-segregant analysis uncovered five major peaks with candidate loci that have been implicated in the {Sigma}1278b background. Our results indicate that the filamentous growth response is a generalized, highly variable phenotype in natural populations, while response to quorum sensing molecules is surprisingly rare. These findings highlight the importance of coupling studies in tractable lab strains with natural isolates in order to understand the relevance and distribution of well-studied traits.

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