Methylation in the CHH Context Allows to Predict Recombination in Rice

Mauricio Peñuela, Jenny Johana Gallo-Franco, Jorge Finke, Camilo Rocha, Anestis Gkanogiannis, Thaura Ghneim-Herrera, Mathias Lorieux

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

DNA methylation is the most studied epigenetic trait. It is considered a key factor in regulating plant development and physiology, and has been associated with the regulation of several genomic features, including transposon silencing, regulation of gene expression, and recombination rates. Nonetheless, understanding the relation between DNA methylation and recombination rates remains a challenge. This work explores the association between recombination rates and DNA methylation for two commercial rice varieties. The results show negative correlations between recombination rates and methylated cytosine counts for all contexts tested at the same time, and for CG and CHG contexts independently. In contrast, a positive correlation between recombination rates and methylated cytosine count is reported in CHH contexts. Similar behavior is observed when considering only methylated cytosines within genes, transposons, and retrotransposons. Moreover, it is shown that the centromere region strongly affects the relationship between recombination rates and methylation. Finally, machine learning regression models are applied to predict recombination using the count of methylated cytosines in the CHH context as the entrance feature. These findings shed light on the understanding of the recombination landscape of rice and represent a reference framework for future studies in rice breeding, genetics, and epigenetics.

Original languageEnglish
Article number12505
JournalInternational Journal of Molecular Sciences
Volume23
Issue number20
DOIs
StatePublished - Oct 2022

Keywords

  • DNA methylation
  • bisulfite sequencing
  • epigenetic
  • machine learning
  • modeling

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