Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue

Abstract

Single-nuclei RNA sequencing characterizes cell types at the gene level. However, compared to single-cell approaches, many single-nuclei cDNAs are purely intronic, lack barcodes and hinder the study of isoforms. Here we present single-nuclei isoform RNA sequencing (SnISOr-Seq). Using microfluidics, PCR-based artifact removal, target enrichment and long-read sequencing, SnISOr-Seq increased barcoded, exon-spanning long reads 7.5-fold compared to naive long-read single-nuclei sequencing. We applied SnISOr-Seq to adult human frontal cortex and found that exons associated with autism exhibit coordinated and highly cell-type-specific inclusion. We found two distinct combination patterns: those distinguishing neural cell types, enriched in TSS-exon, exon-polyadenylation-site and non-adjacent exon pairs, and those with multiple configurations within one cell type, enriched in adjacent exon pairs. Finally, we observed that human-specific exons are almost as tightly coordinated as conserved exons, implying that coordination can be rapidly established during evolution. SnISOr-Seq enables cell-type-specific long-read isoform analysis in human brain and in any frozen or hard-to-dissociate sample.

In-Depth Temporal Transcriptome Profiling of an Alphaherpesvirus Using Nanopore Sequencing

“…Besides Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) platforms, Loop Genomics has recently developed an LRS approach based on single molecule synthetic long-read sequencing (LoopSeq) [6]. In recent times, single cell [21] and single nuclei methods [22] have been developed for more refined transcriptomic characterizations.…”

ScisorWiz: visualizing differential isoform expression in single-cell long-read data

“…For a user-specified gene, reads for any number of cell types can be visualized and are clustered by chain of introns (the ordered list of a read’s introns), TSS and/or PolyA site for each cell type. We have used such plots in our long-read ( Sharon et al , 2013 ; Tilgner et al , 2014 , 2015 ) and single-cell long-read publications ( Gupta et al , 2018 ; Hardwick et al , 2022 ; Joglekar et al , 2021 ). However, customizing such a plot for publication standards includes read mapping, shrinking of introns and recalculation of coordinates, calculation of alternative exons, adjusting plot area depending on number of reads and cell types, as well as plotting single-nucleotide variants (SNVs), insertions and deletions.…”

“…Differential isoform expression between cell types and across conditions plays a major role in the diversification of the proteome ( Nilsen and Graveley, 2010 ) and functionality of transcripts in the cell ( Yang et al , 2016 ). Long-read sequencing has become widely used to address this problem ( Au et al , 2013 ; Bolisetty et al , 2015 ; Koren et al , 2012 ; Leung et al , 2021 ; Oikonomopoulos et al , 2016 ; Ruiz-Reche et al , 2019 ; Schulz et al , 2021 ; Sharon et al , 2013 ; Tilgner et al , 2015 ), and with applications to single-cell isoform sequencing studies ( Arzalluz-Luque et al , 2022 ; Gupta et al , 2018 ; Hardwick et al , 2022 ; Joglekar et al , 2021 ; Volden and Vollmers, 2022 ). These approaches have been reviewed in Hardwick et al (2019) .…”

ScisorWiz: Visualizing Differential Isoform Expression in Single-Cell Long-Read Data

“…For a user-specified gene, reads for any number of cell types can be visualized and are clustered by chain of introns (the ordered list of a read’s introns), TSS, and/or PolyA site for each cell type. We have used such plots in our long-read (4, 6, 19) and single-cell long-read publications (12–14). However, customizing such a plot for publication standards includes read mapping, shrinking of introns and recalculation of coordinates, calculation of alternative exons, adjusting plot area depending on number of reads and cell types, as well as plotting Single-Nucleotide Variants (SNVs), insertions, and deletions.…”