Journal Article

Intron Evolution in Saccharomycetaceae

Katarzyna B. Hooks, Daniela Delneri and Sam Griffiths-Jones

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 6, issue 9, pages 2543-2556

Published online September 2014 | e-ISSN: 1759-6653 | DOI:

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Introns in protein-coding genes are very rare in hemiascomycetous yeast genomes. It has been suggested that these species have experienced extensive intron loss during their evolution from the postulated intron-rich fungal ancestor. However, no intron-devoid yeast species have been identified and some of the introns remaining within the genomes of intron-poor species, such as Saccharomyces cerevisiae, appear to be beneficial during growth under stress conditions. In order to reveal the pattern of intron retention within intron-poor yeast species and better understand the mechanisms of intron evolution, we generated a comprehensive set of 250 orthologous introns in the 20 species that comprise the Saccharomycetaceae, by analyzing RNA deep-sequencing data and alignments of intron-containing genes. Analysis of these intron sets shows that intron loss is at least two orders of magnitude more frequent than intron gain. Fine mapping of intron positions shows that intron sliding is rare, and that introns are almost always removed without changing the primary sequence of the encoded protein. The latter finding is consistent with the prevailing view that homologous recombination between reverse-transcribed mature mRNAs and the corresponding genomic locus is the primary mechanism of intron loss. However, we also find evidence that loss of a small number of introns is mediated by micro-homology, and that the number of intron losses is diminished in yeast species that have lost the microhomology end joining and nonhomologous end joining machinery.

Keywords: intron loss; yeast; fungi

Journal Article.  6830 words.  Illustrated.

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

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