Journal Article

Zygomycetes, Microsporidia, and the Evolutionary Ancestry of Sex Determination

Tina Koestler and Ingo Ebersberger

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 186-194
Published in print January 2011 |
Published online February 2011 | e-ISSN: 1759-6653 | DOI:

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  • Bioinformatics and Computational Biology
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Zygomycetes and their alleged sister taxon, the microsporidia, exclusively share the presence of a cluster of three genes encoding a sugar transporter, a high mobility group (HMG)-type transcription factor, and an RNA helicase. In zygomycetes, the HMG-type transcription factor acts as the sole sex determinant. This intimately ties the evolutionary history of this gene cluster to the evolution of sex determination. Here, we have unraveled the relationships of the two gene clusters by vicariously analyzing the sugar transporters and the RNA helicases. We show that if the two gene clusters share a common ancestry, it dates back to the early days of eukaryotic evolution. As a consequence, the zygomycete MAT locus would be old enough to represent the archetype of fungal and animal sex determination. However, the evolutionary scenario that has to be invoked is complex. An independent assembly of the two clusters deserves therefore consideration. In either case, shared ancestry or convergent evolution, the presence of the gene cluster in microsporidia and in zygomycetes represents at best a plesiomorphy. Hence, it is not phylogenetically informative. A further genome-wide reanalysis of gene order conservation reveals that gene order is not significantly more similar between microsporidia and zygomycetes than between microsporidia and any other fungal taxon or even humans. Consequently, the phylogenetic placement of microsporidia as sister to the zygomycetes needs to be reconsidered.

Keywords: sex determination; gene cluster; HMG; plesiomorphy; MAT locus; shared synteny

Journal Article.  5325 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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