Deep learning-enhanced R-loop prediction provides mechanistic implications for repeat expansion diseases
Year: 2024
Type: article
Abstract: R-loops play diverse functional roles, but controversial genomic localization of R-loops have emerged from experimental approaches, posing significant challenges for R-loop research. The development and application of an accurate computational tool for studying human R-loops remains an unmet need. Here, we introduce DeepER, a deep learning-enhanced R-loop prediction tool. DeepER showcases outstanding performance compared to existing tools, facilitating accurate genome-wide annotation of R-loops and a deeper understanding of the position- and context-dependent effects of nucleotide composition on R-loop formation. DeepER also unveils a strong association between certain tandem repeats and R-loop formation, opening a new avenue for understanding the mechanisms underlying some repeat expansion diseases. To facilitate broader utilization, we have developed a user-friendly web server as an integral component of R-loopBase. We anticipate that DeepER will find extensive applications in the field of R-loop research.
Source: iScience
Authors: Jiyun Hu, Zetong Xing, Hongbing Yang, Yongli Zhou, Liufei Guo, Xianhong Zhang, Longsheng Xu, Qiong Liu, Jing Ye, Xiaoming Zhong, Jixin Wang, Ruoyao Lin, Erping Long, Jiewei Jiang, Liang Chen, Yongcheng Pan, Lang He, Jia-Yu Chen
Institutions: Nanjing Drum Tower Hospital, State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Xi’an University of Posts and Telecommunications, Wuhan University, Central South University, Xiangya Hospital Central South University, St. Jude Children's Research Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Institute of Basic Medical Sciences of the Chinese Academy of Medical Sciences
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,150
Funders: National Natural Science Foundation of China, Jiangsu Provincial Department of Education, Nanjing University, National University's Basic Research Foundation of China, Fundamental Research Funds for the Central Universities, Dream Project of Ministry of Science and Technology of the People's Republic of China
Awards: G134330249, G6121050021, G7586881478
OpenAlex ID: W4401001949