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A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome.
Riba, Andrea; Fumagalli, Maria Rita; Caselle, Michele; Osella, Matteo.
Affiliation
  • Fumagalli MR; Institute of Biophysics - CNR, National Research Council, Genova, Italy.
  • Caselle M; Department of Environmental Science and Policy, Center for Complexity and Biosystems, University of Milan, Milano, Italy.
  • Osella M; Department of Physics and INFN, University of Torino, Torino, Italy.
Genome Biol Evol ; 12(11): 2045-2059, 2020 11 03.
Article in En | MEDLINE | ID: mdl-32986810
ABSTRACT
Retrotransposons, DNA sequences capable of creating copies of themselves, compose about half of the human genome and played a central role in the evolution of mammals. Their current position in the host genome is the result of the retrotranscription process and of the following host genome evolution. We apply a model from statistical physics to show that the genomic distribution of the two most populated classes of retrotransposons in human deviates from random placement, and that this deviation increases with time. The time dependence suggests a major role of the host genome dynamics in shaping the current retrotransposon distributions. Focusing on a neutral scenario, we show that a simple model based on random placement followed by genome expansion and sequence duplications can reproduce the empirical retrotransposon distributions, even though more complex and possibly selective mechanisms can have contributed. Besides the inherent interest in understanding the origin of current retrotransposon distributions, this work sets a general analytical framework to analyze quantitatively the effects of genome evolutionary dynamics on the distribution of genomic elements.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Human / Long Interspersed Nucleotide Elements / Alu Elements / Biological Evolution / Models, Genetic Limits: Humans Language: En Journal: Genome Biol Evol Journal subject: BIOLOGIA / BIOLOGIA MOLECULAR Year: 2020 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome, Human / Long Interspersed Nucleotide Elements / Alu Elements / Biological Evolution / Models, Genetic Limits: Humans Language: En Journal: Genome Biol Evol Journal subject: BIOLOGIA / BIOLOGIA MOLECULAR Year: 2020 Document type: Article