Advances in alternative splicing identification: deep learning and pantranscriptome

Frontiers in Plant Science

Plant Science

Hao He¹  Xin Huang¹  Fei Shen¹  Xiaozeng Yang¹  Deng Yang¹  Chenyang Hu²  Jirong Zhao³ 

[1] Institute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China;Institute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China;Shanxi Key Lab of Chinese Jujube, College of Life Science, Yan’an University, Yan’an, Shanxi, China;Shanxi Key Lab of Chinese Jujube, College of Life Science, Yan’an University, Yan’an, Shanxi, China;

关键词: alternative splicing;    RNA-seq;    Iso-seq;    detection algorithm;    deep learning;    pantranscriptome;   

DOI  :  10.3389/fpls.2023.1232466

 received in 2023-05-31, accepted in 2023-08-28,  发布年份 2023

来源: Frontiers

【 摘 要 】

In plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate identification of splicing events is a vital step in studying alternative splicing. This article presents the application of alternative splicing algorithms with or without reference genomes in plants, as well as the integration of advanced deep learning techniques for improved detection accuracy. In addition, we also discuss alternative splicing studies in the pan-genomic background and the usefulness of integrated strategies for fully profiling alternative splicing.

【 授权许可】

Unknown   
Copyright © 2023 Shen, Hu, Huang, He, Yang, Zhao and Yang