Splicing varies across brain regions, but the single-cell resolution of regional variation is unclear. We present a single-cell investigation of differential isoform expression (DIE) between brain regions using single-cell long-read sequencing in mouse hippocampus and prefrontal cortex in 45 cell types at postnatal day 7 (www.isoformAtlas.com). Isoform tests for DIE show better performance than exon tests. We detect hundreds of DIE events traceable to cell types, often corresponding to functionally distinct protein isoforms. Mostly, one cell type is responsible for brain-region specific DIE. However, for fewer genes, multiple cell types influence DIE. Thus, regional identity can, although rarely, override cell-type specificity. Cell types indigenous to one anatomic structure display distinctive DIE, e.g. the choroid plexus epithelium manifests distinct transcription-start-site usage. Spatial transcriptomics and long-read sequencing yield a spatially resolved splicing map. Our methods quantify isoform expression with cell-type and spatial resolution and it contributes to further our understanding of how the brain integrates molecular and cellular complexity.

Next-generation sequencing (NGS) provides a broad investigation of the genome, and it is being readily applied for the diagnosis of disease-associated genetic features. However, the interpretation of NGS data remains challenging owing to the size and complexity of the genome and the technical errors that are introduced during sample preparation, sequencing and analysis. These errors can be understood and mitigated through the use of reference standards - well-characterized genetic materials or synthetic spike-in controls that help to calibrate NGS measurements and to evaluate diagnostic performance. The informed use of reference standards, and associated statistical principles, ensures rigorous analysis of NGS data and is essential for its future clinical use.

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RNA sequencing (RNA-seq) can be used to assemble spliced isoforms, quantify expressed genes and provide a global profile of the transcriptome. However, the size and diversity of the transcriptome, the wide dynamic range in gene expression and inherent technical biases confound RNA-seq analysis. We have developed a set of spike-in RNA standards, termed 'sequins' (sequencing spike-ins), that represent full-length spliced mRNA isoforms. Sequins have an entirely artificial sequence with no homology to natural reference genomes, but they align to gene loci encoded on an artificial in silico chromosome. The combination of multiple sequins across a range of concentrations emulates alternative splicing and differential gene expression, and it provides scaling factors for normalization between samples. We demonstrate the use of sequins in RNA-seq experiments to measure sample-specific biases and determine the limits of reliable transcript assembly and quantification in accompanying human RNA samples. In addition, we have designed a complementary set of sequins that represent fusion genes arising from rearrangements of the in silico chromosome to aid in cancer diagnosis. RNA sequins provide a qualitative and quantitative reference with which to navigate the complexity of the human transcriptome.

The complexity of microbial communities, combined with technical biases in next-generation sequencing, pose a challenge to metagenomic analysis. Here, we develop a set of internal DNA standards, termed “sequins” (sequencing spike-ins), that together constitute a synthetic community of artificial microbial genomes. Sequins are added to environmental DNA samples prior to library preparation, and undergo concurrent sequencing with the accompanying sample. We validate the performance of sequins by comparison to mock microbial communities, and demonstrate their use in the analysis of real metagenome samples. We show how sequins can be used to measure fold change differences in the size and structure of accompanying microbial communities, and perform quantitative normalization between samples. We further illustrate how sequins can be used to benchmark and optimize new methods, including nanopore long-read sequencing technology. We provide metagenome sequins, along with associated data sets, protocols, and an accompanying software toolkit, as reference standards to aid in metagenomic studies.

DNA sequencing, phylogenetic and mapping studies suggest that the class 1 integron found in pathogens arose when one member of the diverse family of environmental class 1 integrons became embedded into a Tn402 transposon. However, the timing of this event and the selective forces that first fixed the newly formed element in a bacterial lineage are still unknown. Biocides have a longer use in clinical practice than antibiotics, and a qac (quaternary ammonium compound) resistance gene, or remnant thereof, is a normal feature of class 1 integrons recovered from clinical isolates. Consequently, it is possible that the initial selective advantage was conferred by resistance to biocides, mediated by qac. Here, we show that diverse qac gene cassettes are a dominant feature of cassette arrays from environmental class 1 integrons, and that they occur in the absence of any antibiotic resistance gene cassettes. They are present in arrays that are dynamic, acquiring and rearranging gene cassettes within the arrays. The abundance of qac gene cassettes makes them a likely candidate for participation in the original insertion into Tn402, and as a source of a readily selectable phenotype. More broadly, the increasing use of qac and other biocides at the present time seems likely to promote the fixation of further novel genetic elements, with unpredictable and potentially adverse consequences for human health and agriculture.

Integrons are bacterial genetic elements capable of capturing and expressing potentially adaptive genetic material. Class 1 integrons constitute the most intensely studied group of these elements to date, mainly due to their well-established role in the acquisition and dissemination of antibiotic resistance genes in clinical environments. However, virtually nothing is known about the distribution or abundance of class 1 integrons outside of the clinical context. Here we develop a SYBR Green-based real-time quantitative PCR assay capable of quantifying the abundance of class 1 integrons in environmental samples. It was shown that the abundance of the intI1 gene in creek sediment correlates with ecological condition, implying that class 1 integrons provide selective advantages relevant to environmental pressures other than the use of antibiotics. By comparing the quantities of intI1 and 16S rRNA gene in each sample, it was demonstrated that approximately 2.7% of cells potentially harbour a class 1 integron. These findings suggest that class 1 integrons are widespread in natural environments removed from clinical settings and occur in a broader range of host organisms than had previously been assumed on the basis of culture-dependent estimates.

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.