Single-nuclei isoform RNA sequencing reveals combination patterns of transcript elements across human brain cell types

Abstract

Single-nuclei RNA-Seq is being widely employed to investigate cell types, especially of human brain and other frozen samples. In contrast to single-cell approaches, however, the majority of single-nuclei RNA counts originate from partially processed RNA leading to intronic cDNAs, thus hindering the investigation of complete isoforms. Here, using microfluidics, PCR-based artifact removal, target enrichment, and long-read sequencing, we developed single-nuclei isoform RNA-sequencing ('SnISOr-Seq'), and applied it to the analysis of human adult frontal cortex samples. We found that exons associated with autism exhibit coordinated and more cell-type specific inclusion than exons associated with schizophrenia or ALS. We discovered two distinct modes of combination patterns: first, those distinguishing cell types in the human brain. These are enriched in combinations of TSS-exon, exon-polyA site, and distant (non-adjacent) exon pairs. Second, those with all isoform combinations found within one neural cell type, which are enriched in adjacent exon pairs. Furthermore, adjacent exon pairs are predominantly mutually associated, while distant pairs are frequently mutually exclusive. Finally, we observed that human-specific exons are as tightly coordinated as conserved exons, pointing to an efficient evolutionary mechanism underpinning coordination. SnISOr-Seq opens the door to single-nuclei long-read isoform analysis in the human brain, and in any frozen, archived or hard-to-dissociate sample.

Analyzing alternative splicing in Alzheimer’s disease postmortem brain: a cell-level perspective

“…Crosslinking and immunoprecipitation methods could also be employed to explore the interaction between splicing factors and ASEs (Sternburg and Karginov, 2020). The recently developed single-cell long-read method can provide more details of the final RNA sequence and may predict more translational regulation by the asset of the machine learning approach than the current studies (Hardwick et al, 2022;Joglekar et al, 2023). However, single-cell long read transcriptomics has been limited in capturing a wide range of isoform diversity due to the sequencing depth constraints inherent in its protocols.…”

Sequencing of individual barcoded cDNAs on Pacific Biosciences and Oxford Nanopore reveals platform-specific error patterns

“…Different long-read RNA approaches are increasingly used for isoform analysis (Koren et al 2012;Au et al 2013;Sharon et al 2013;Tilgner et al 2014Tilgner et al , 2015Oikonomopoulos et al 2016;Tilgner et al 2018;Garalde et al 2018;Gupta et al 2018;Depledge et al 2019;Wang et al 2019;Tardaguila et al 2018;Volden et al 2018;Tang et al 2020;Sun et al 2021;Joglekar et al 2021;Hardwick et al 2021).…”

RNA regulation in brain function and disease 2022 (NeuroRNA): A conference report

“…Tilgner lab is moving forward with single-nuclei RNA sequencing (snRNAseq) and isoform identification that enables analysis of frozen tissue material (i.e., the majority of clinical samples). The key methodological development in SnISOr-seq (single-nuclei isoform RNA sequencing) is the addition of two steps in cDNA library preparation: an asymmetric PCR to amplify barcoded cDNA and an enrichment step using exon-targeting probes to filter out purely intronic molecules (Hardwick et al, 2022). As alternative exon inclusion/skipping event is relatively common in the brain and cell type-specific phenomenon, more interestingly, there is cell typespecific coordination of exons, TSS, and poly(A) patterns that can be noticed from snRNA-seq datasets (Hardwick et al, 2022).…”