2024.01.26
Identification of region-specific gene isoforms in the human brain using long-read transcriptome sequencing
Sci Adv. 2024 Jan 26;10(4):eadj5279. doi: 10.1126/sciadv.adj5279. Epub 2024 Jan 24.
Shimada M1,2,3, Omae Y1, Kakita A4, Gabdulkhaev R4, Hitomi Y5, Miyagawa T3, Honda M3,6, Fujimoto A7, Tokunaga K1.
1Genome Medical Science Project (Toyama), National Center for Global Health and Medicine (NCGM).
2Center for Clinical Sciences, National Center for Global Health and Medicine (NCGM).
3Sleep Disorders Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science.
4Department of Pathology, Brain Research Institute, Niigata University.
5Department of Human Genetics, Research Institute, National Center for Global Health and Medicine (NCGM).
6Japan Somnology Center and Seiwa Hospital, Institute of Neuropsychiatry.
7Department of Human Genetics, Graduate School of Medicine, the University of Tokyo.
Abstract
In neurological and neuropsychiatric diseases, different brain regions are affected, and differences in gene expression patterns could potentially explain this mechanism. However, limited studies have precisely explored gene expression in different regions of the human brain. In this study, we performed long-read RNA sequencing on three different brain regions of the same individuals: the cerebellum, hypothalamus, and temporal cortex. Despite stringent filtering criteria excluding isoforms predicted to be artifacts, over half of the isoforms expressed in multiple samples across multiple regions were found to be unregistered in the GENCODE reference. We then especially focused on genes with different major isoforms in each brain region, even with similar overall expression levels, and identified that many of such genes including GAS7 might have distinct roles in dendritic spine and neuronal formation in each region. We also found that DNA methylation might, in part, drive different isoform expressions in different regions. These findings highlight the significance of analyzing isoforms expressed in disease-relevant sites.
*Reprinted under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).
