Noncoding RNA Genes Transcribed by RNA Polymerase III in Yarrowia lipolytica

  • Cécile NeuvégliseEmail author
  • Claude Gaillardin
  • Christian Marck
Part of the Microbiology Monographs book series (MICROMONO, volume 24)


In the hemiascomycetous yeast Yarrowia lipolytica, the Pol III-transcribed ncRNAs display a number of unusual and remarkable features with respect to other Hemiascomycetes. With 510 bona fide genes, the genome of this organism contains the largest number of tRNA genes among yeasts. Unlike all other Hemiascomycetes which unconventionally decode the Leu CUN and Arg CGN codons like bacteria, Y. lipolytica follows the regular eukaryotic rule. Full genome sequencing of the first Hemiascomycetes revealed many cases of tandem tRNA genes. Such genes are present in Y. lipolytica, together with other unexpected cases of Pol III hybrid genes. In Y. lipolytica, contrary to most Hemiascomycetes and similarly to Schizosaccharomyces pombe, the 5S rRNA genes (transcribed by Pol III) are not embedded into the multiple rDNA units. Y. lipolytica appears unique with the presence of ~50 copies of hybrid dicistronic tRNA-5S rRNA genes coexisting with ~60 copies of more conventional, isolated 5S rRNA genes. These hybrid genes were shown experimentally to be actively co-transcribed in vitro and in vivo from the leader tRNA genes rendering the specific transcription factor of 5S rRNA genes, TFIIIA, dispensable. Y. lipolytica also contains a novel ncRNA, RUF70, expressed from multiple genes located 3′ to each of the 13 copies of the tRNA-Trp gene. Such a complex assembly of Pol III genes is not found outside the Yarrowia clade. Many Pol III-related features differentiate Y. lipolytica from other Hemiascomycetes, rendering it closer to Schizosaccharomyces pombe, to other ascomycetes, and to the rest of eukaryotes.


tRNA Gene Yarrowia Lipolytica Signal Recognition Particle rDNA Unit Spliceosomal Intron 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We wish to thank Joël Acker for helpful discussions, Carl Mann for correcting the manuscript, and all our colleagues from the Génolevures consortium. This work was supported by the GDR CNRS 2354 “Génolevures-3,” the ANR grant “Genarise” (ANR-05-BLAN-0331), and the ANR grant “RegPolStress” (ANR-07-BLAN-0039).


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Cécile Neuvéglise
    • 1
    Email author
  • Claude Gaillardin
    • 1
  • Christian Marck
    • 2
  1. 1.INRA UMR1319AgroParisTech, Micalis, Centre de Biotechnologie Agro-IndustrielleThiverval-GrignonFrance
  2. 2.Institut de Biologie et Technologies de Saclay (iBiTec-S)Gif-sur-Yvette CedexFrance

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