Deep learning identifies and quantifies recombination hotspot determinants.

Journal: Bioinformatics (Oxford, England)
PMID: 35561158

Abstract

MOTIVATION: Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we propose a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes and species.

Authors

  • Yu Li
    Department of Public Health, Shihezi University School of Medicine, 832000, China.
  • Siyuan Chen
    First author: Department of Computer Science, Columbia University in the City of New York, 10027; second, fourth, and sixth authors: Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853; third author: Department of Mechanical Engineering, Columbia University; fifth author: Uber AI Labs, San Francisco 94103; seventh author: Plant Pathology and Plant-Microbe Biology Section, School of Integrative Plant Science, Cornell University; and eighth author: Department of Mechanical Engineering and Institute of Data Science, Columbia University.
  • Trisevgeni Rapakoulia
    Max Planck Institute for Molecular Genetics, Berlin 14195, Germany.
  • Hiroyuki Kuwahara
    Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
  • Kevin Y Yip
    Department of Computer Science and Engineering (CSE), The Chinese University of Hong Kong (CUHK), 999077, Hong Kong SAR, China.
  • Xin Gao
    Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA.

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