Alternative splicing of schizophrenia risk genes, such as DRD2, GRM3, and DISC1, has been extensively described. Nevertheless, the alternative splicing characteristics of the growing number of schizophrenia risk genes identified through genetic analyses remain relatively opaque. Recently, transcriptomic analyses in human brains based on short-read RNA-sequencing have discovered many “local splicing” events (e.g., exon skipping junctions) associated with genetic risk of schizophrenia, and further molecular characterizations have identified novel spliced isoforms, such as AS3MTd2d3 and ZNF804AE3E4. In addition, long-read sequencing analyses of schizophrenia risk genes (e.g., CACNA1C and NRXN1) have revealed multiple previously unannotated brain-abundant isoforms with therapeutic potentials, and functional analyses of KCNH2-3.1 and Ube3a1 have provided examples for investigating such spliced isoforms in vitro and in vivo. These findings suggest that alternative splicing may be an essential molecular mechanism underlying genetic risk of schizophrenia, however, the incomplete annotations of human brain transcriptomes might have limited our understanding of schizophrenia pathogenesis, and further efforts to elucidate these transcriptional characteristics are urgently needed to gain insights into the illness-correlated brain physiology and pathology as well as to translate genetic discoveries into novel therapeutic targets.
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This work was supported by grants from the National Natural Science Foundation of China (81722019 and 81971259 to ML, 31872778 to ZH). ZH was also supported by Xiangya Hospital Start-up Research Grants, The innovative team program 2019RS1010 from Department of Science & Technology of Hunan Province, The innovation-driven team project 2020CX016 from Central South University, 111 Grant (B13036), and Hunan 100 Talents Program.
Conflict of interest
The authors declare no competing interests.
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Zhang, CY., Xiao, X., Zhang, Z. et al. An alternative splicing hypothesis for neuropathology of schizophrenia: evidence from studies on historical candidate genes and multi-omics data. Mol Psychiatry 27, 95–112 (2022). https://doi.org/10.1038/s41380-021-01037-w
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