Poster Presentation 43rd Lorne Genome Conference 2022

Identification of novel isoforms in schizophrenia and depression risk genes in human brain (#144)

Ricardo De Paoli-Iseppi 1 , Rhea M Kujawa 1 , Yoonji Seo 1 , Shweta S Joshi 1 , Michael B Clark 1
  1. University of Melbourne, Parkville, VIC, Australia

Schizophrenia (SZ) and major depressive disorder (MDD) are debilitating conditions with a strong genetic component. Genome-wide association studies (GWAS) have identified hundreds of genomic risk loci for these neuropsychiatric disorders [1,2]. How risk loci and their associated genes contribute to disease risk through altered gene expression and RNA splicing is not well understood [3]. We amplified the entire coding sequences of risk gene isoforms and used nanopore long-read sequencing to better understand their expression, splicing and contribution to neuropsychiatric disease risk.

Gene selection was based upon accumulated ‘levels of evidence’ collated from multiple study types supporting involvement with risk for SZ or MDD including GWAS [4], transcriptome wide association studies (TWAS), mendelian randomisation and DNA methylation data. Thirty high-confidence risk genes were sequenced using long-reads from seven regions of post-mortem human brain from five healthy individuals. A custom informatics pipeline, DIscoAnt was used to identify, quantify, and annotate known and novel isoforms.

Hundreds of isoforms were identified across the sequenced risk genes with the majority of these being novel. Novel isoforms constituted a high proportion of expression for many risk genes including ATG13 (60%), PRMT7 (86%), MEF2C (22%) and AREL1 (42%) highlighting their potential functional importance. Abundant novel isoforms displayed both changes to UTR regions as well as the coding sequence. For example, in the SZ risk gene ATG13, the top expressed novel isoform (24%) differs from the canonical transcript with omission of exons 3, 14 and 15 possibly resulting in an altered protein.

This study expands the full splicing profile for neuropsychiatric risk genes and supports the use of long-read sequencing to identify novel isoforms in human brain. Changes to coding sequences, novel splice junctions and novel exon combinations in untranslated regions are attractive targets for further validation studies and assessment of isoform impact on neuropsychiatric disorder development.

  1. 1. Ripke, S., et al., Biological insights from 108 schizophrenia-associated genetic loci. Nature, 2014. 511(7510): p. 421.
  2. 2. Wang, Q., et al., A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data. Nature neuroscience, 2019. 22(5): p. 691.
  3. 3. Clark, M.B., et al., Long-read sequencing reveals the complex splicing profile of the psychiatric risk gene CACNA1C in human brain. Molecular psychiatry, 2019: p. 1-11.
  4. 4. Buniello, A., et al., The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic acids research, 2019. 47(D1): p. D1005-D1012.