The repertoire of candidate archaeal noncoding RNAs and their association with temperature adaptation

  • 1Instituto Universitario de Investigación y Desarrollo Tecnológico (IDT), Universidad Tecnológica Metropolitana, Santiago, 8940577, Chile. Electronic address: raul.arias@utem.cl.
  • 2Centro de Genómica y Bioinformática, Facultad de Ciencias, Ingeniería y Tecnología, Universidad Mayor, Santiago, Chile.
  • 3GEMA Center for Genomics, Ecology & Environment, Facultad de Ciencias, Universidad Mayor, Santiago, 8580745, Chile.
  • 4Unidad de Genómica Avanzada - UGA, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, 8380494, Chile; Centro de Modelamiento Molecular, Biofísica y Bioinformática - CM2B2, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, 8380494, Chile. Electronic address: vinicius.maracaja@uchile.cl.

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Abstract

Noncoding RNAs (ncRNAs) play a crucial role in the fine-tuning regulation of cells in all domains of life. In archaea, ncRNAs remain poorly studied, with only a few ncRNA classes well characterised. Archaea are renowned for their ability to survive in harsh environments, though they have been discovered in a variety of other habitats as well. We have determined the ncRNA candidate repertoire across 270 archaeal genomes using secondary structure inferences and sequence similarity searches. Here, 33 non-coding RNA classes were identified in these genomes. The correlation between all ncRNA classes and optimal growth temperature (OGT) was R2 0.65. Phylogenetic analysis based on multiple alignments of a set of highly conserved proteins revealed preferences for ncRNA classes at the phylum and genus levels. All of the ncRNA data generated by this study reveals a correlation between the genomic abundance of specific ncRNA classes and the optimal growth temperature, especially for the sRNA C/D box type. All the genomic and ncRNA archaeal data generated is a valuable resource that will stimulate experimentalists to investigate whether or not their predicted ncRNAs are correct and biologically meaningful, boosting further associative studies using the unique features of this domain.

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