Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences.

Journal: Genome biology
Published Date: Aug 16, 2021

Abstract

Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limited. We develop a computational method, chromatin interaction neural network (ChINN), to predict chromatin interactions between open chromatin regions using only DNA sequences. ChINN predicts CTCF- and RNA polymerase II-associated and Hi-C chromatin interactions. ChINN shows good across-sample performances and captures various sequence features for chromatin interaction prediction. We apply ChINN to 6 chronic lymphocytic leukemia (CLL) patient samples and a published cohort of 84 CLL open chromatin samples. Our results demonstrate extensive heterogeneity in chromatin interactions among CLL patient samples.

Authors

  • Fan Cao
    Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Dr, Singapore, 117599, Singapore.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Yichao Cai
    Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Dr, Singapore, 117599, Singapore.
  • Sambhavi Animesh
    Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Dr, Singapore, 117599, Singapore.
  • Ying Zhang
    Department of Nephrology, Nanchong Central Hospital Affiliated to North Sichuan Medical College, Nanchong, China.
  • Semih Can Akincilar
    Institute of Molecular and Cell Biology, Agency for Science (IMCB), A*STAR (Agency for Science, Technology and Research,, Singapore, 138673, Singapore.
  • Yan Ping Loh
    Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Dr, Singapore, 117599, Singapore.
  • Xinya Li
    School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore.
  • Wee Joo Chng
    Department of Haematology and Oncology, National University Cancer Institute, National University Health System, Singapore; Cancer Science Institute of Singapore, National University of Singapore, Singapore.
  • Vinay Tergaonkar
    Institute of Molecular and Cell Biology, Agency for Science (IMCB), A*STAR (Agency for Science, Technology and Research,, Singapore, 138673, Singapore.
  • Chee Keong Kwoh
    School of Computer Science and Engineering,  Nanyang  Technological  University,  50  Nanyang  Avenue,  639798, Singapore.
  • Melissa J Fullwood
    Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Dr, Singapore, 117599, Singapore. mfullwood@ntu.edu.sg.

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