Journal Article

Polygenic Molecular Architecture Underlying Non-Sexual Cell Aggregation in Budding Yeast

Jiarui Li, Lin Wang, Xiaoping Wu, Ou Fang, Luwen Wang, Chenqi Lu, Shengjie Yang, Xiaohua Hu and Zewei Luo

in DNA Research

Published on behalf of Kazusa DNA Research Institute

Volume 20, issue 1, pages 55-66
Published in print February 2013 | ISSN: 1340-2838
Published online January 2013 | e-ISSN: 1756-1663 | DOI: http://dx.doi.org/10.1093/dnares/dss033

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Cell aggregation in unicellular organisms, induced by either cell non-sexual adhesion to yield flocs and biofilm, or pheromone-driving sexual conjugation is of great significance in cellular stress response, medicine, and brewing industries. Most current literatures have focused on one form of cell aggregation termed flocculation and its major molecular determinants, the flocculation (FLO) family genes. Here, we implemented a map-based approach for dissecting the molecular basis of non-sexual cell aggregation in Saccharomyces cerevisiae. Genome-wide mapping has identified four major quantitative trait loci (QTL) underlying nature variation in the cell aggregation phenotype. High-resolution mapping following up with knockout and allele replacement experiments resolved the QTL into the underlying genes (AMN1, RGA1, FLO1, and FLO8) or even into the causative nucleotide. Genetic variation in the QTL genes can explain up to 46% of phenotypic variation of this trait. Of these genes, AMN1 plays the leading role, differing from the FLO family members, in regulating expression of cell clumping phenotype through inducing cell segregation defect. These findings provide novel insights into the molecular mechanism of how cell aggregation is regulated in budding yeast, and the data will be directly implicated to understand the molecular basis and evolutionary implications of cell aggregation in other fungus species.

Keywords: cell aggregation; map-based cloning; QTL analysis; Saccharomyces cerevisiae

Journal Article.  6413 words.  Illustrated.

Subjects: Genetics and Genomics

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