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Satellitome Analysis on Talpa aquitania Genome and Inferences about the satDNAs Evolution on Some Talpidae.

Juana GutiérrezGaël Aleix-MataEugenia E MontielDiogo C Cabral-de-MelloJuan Alberto Marchal OrtegaAntonio Sánchez Baca
Published in: Genes (2022)
In the genus Talpa a new species, named Talpa aquitania , has been recently described. Only cytogenetic data are available for the nuclear genome of this species. In this work, we characterize the satellitome of the T. aquitania genome that presents 16 different families, including telomeric sequences, and they represent 1.24% of the genome. The first satellite DNA family (TaquSat1-183) represents 0.558%, and six more abundant families, including TaquSat1-183, comprise 1.13%, while the remaining 11 sat-DNAs represent only 0.11%. The average A + T content of the SatDNA families was 50.43% and the median monomer length was 289.24 bp. The analysis of these SatDNAs indicated that they have different grades of clusterization, homogenization, and degeneration. Most of the satDNA families are present in the genomes of the other Talpa species analyzed, while in the genomes of other more distant species of Talpidae, only some of them are present, in accordance with the library hypothesis. Moreover, chromosomal localization by FISH revealed that some satDNAs are localized preferentially on centromeric and non-centromeric heterochromatin in T. aquitania and also in the sister species T. occidentalis karyotype. The differences observed between T. aquitania and the close relative T. occidentalis and T. europaea suggested that the satellitome is a very dynamic component of the genomes and that the satDNAs could be responsible for chromosomal differences between the species. Finally, in a broad context, these data contribute to the understanding of the evolution of satellitomes on mammals.
Keyphrases
  • genome wide
  • genetic diversity
  • electronic health record
  • big data
  • lymph node
  • machine learning
  • dna methylation
  • mass spectrometry
  • single cell
  • artificial intelligence
  • deep learning
  • circulating tumor