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A modified Chromium 10x droplet-based protocol that subsamples cells for both short-read and long-read (nanopore) sequencing together with a new computational pipeline ( FLAMES ) is developed to enable isoform discovery, splicing analysis, and mutation detection in single cells. We identify thousands of unannotated isoforms and find conserved functional modules that are enriched for alternative transcript usage in different cell types and species, including ribosome biogenesis and mRNA splicing. Analysis at the transcript level allows data integration with scATAC-seq on individual promoters, improved correlation with protein expression data, and linked mutations known to confer drug resistance to transcriptome heterogeneity.

Abstract Glimma 1.0 introduced intuitive, point-and-click interactive graphics for differential gene expression analysis. Here, we present a major update to Glimma that brings improved interactivity and reproducibility using high-level visualization frameworks for R and JavaScript. Glimma 2.0 plots are now readily embeddable in R Markdown, thus allowing users to create reproducible reports containing interactive graphics. The revamped multidimensional scaling plot features dashboard-style controls allowing the user to dynamically change the colour, shape and size of sample points according to different experimental conditions. Interactivity was enhanced in the MA-style plot for comparing differences to average expression, which now supports selecting multiple genes, export options to PNG, SVG or CSV formats and includes a new volcano plot function. Feature-rich and user-friendly, Glimma makes exploring data for gene expression analysis more accessible and intuitive and is available on Bioconductor and GitHub.

scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify ‘true’ cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.

Long-read single-cell RNA-sequencing enables the profiling of RNA isoform expression and alternative splicing at the single cell level. However, diverse single-cell technologies and sparse isoform data demand flexible, accurate, processing and analysis tools. Here we introduce FLAMESv2, a highly modular and protocol-agnostic R/Bioconductor package for long-read singlecell RNA-seq data processing. FLAMESv2 supports a wide range of single-cell and spatial experimental protocols, is highly configurable and scalable, allowing seamless multi-sample analysis and provides versatile visualisation and analysis outputs. We demonstrate FLAMESv2 compatibility with both dropletbased and combinatorial barcoding single-cell methods, as well as spatial transcriptomics workflows. Applying FLAMESv2 to in vitro differentiation of stem cells into neurons, we identify celltypes, differentiation trajectories, expression of annotated and novel isoforms and isoform expression diversity and heterogeneity within individual cells. FLAMESv2 provides a comprehensive, flexible approach to analysing long-read single-cell RNA-sequencing, unlocking this powerful methodology for RNA isoform characterisation.

scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify “true” cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.

Glimma 1.0 introduced intuitive, point-and-click interactive graphics for differential gene expression analysis. Here, we present a major update to Glimma which brings improved interactivity and reproducibility using high-level visualisation frameworks for R and JavaScript. Glimma 2.0 plots are now readily embeddable in R Markdown, thus allowing users to create reproducible reports containing interactive graphics. The revamped multidimensional scaling plot features dashboard-style controls allowing the user to dynamically change the colour, shape and size of sample points according to different experimental conditions. Interactivity was enhanced in the MA-style plot for comparing differences to average expression, which now supports selecting multiple genes, export options to PNG, SVG or CSV formats and includes a new volcano plot function. Feature-rich and user-friendly, Glimma makes exploring data for gene expression analysis more accessible and intuitive and is available on Bioconductor and GitHub. Competing Interest Statement The authors have declared no competing interest.

The Indo-Pacific is the world’s largest marine biogeographic region, covering the tropical and subtropical waters from the Red Sea in the Western Indian Ocean to the Easter Islands in the Pacific. It is characterized by a vast degree of biogeographic connectivity in particular in its marine realm. So far, usage of molecular tools rejected the presence of cosmopolitan or very widespread sponge species in several cases, supporting hypotheses on a higher level of endemism among marine invertebrates than previously thought. We analysed the genetic diversity of Hyrtios erectus and Stylissa massa , two alleged widespread sponge species of the Indo-Pacific, from the Red Sea and Mayotte in the West Indian Ocean to Polynesia in the Central Pacific. In the region of its type locality, the Red Sea, Hyrtios erectus is genetically distinct, and the populations from the remaining Indo-Pacific are a potentially different species and paraphyletic in respect to H. altus . Stylissa massa falls into different, but widespread genetic clades, one of them ( Stylissa cf. massa ), with distinct potentially hairpin-forming elements in mitochondrial intergenic regions. The results also indicate that morphologically established demosponge species in the Indo-Pacific can be widespread, but simultaneously harbour cryptic, genetically distinct lineages.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Aim: The Indo-Pacific is the world's largest marine biogeographic region. It is characterised by different degrees of connectivity among its subregions, and harbours the majority of demosponge species currently known to science. Comparisons between several regional sponge faunas have been undertaken in the past, mostly based on identifying the sponge species morphologically. The Sponge Barcoding Project, in tandem with other regional DNA taxonomy campaigns, provides one of the largest DNA-based taxonomic data collections from sponges of the Indo-Pacific. Here, we utilise the sponge barcoding data in the largest molecular biodiversity study of sponges to date, which reveals patterns of shallow-water demosponge faunal connectivity, endemism, and distribution in the Indo-Pacific with a level of resolution unavailable in prior morphology-based studies. Location: Demosponge specimens in this study cover 13 marine provinces of the Indo-Pacific, from the Red Sea to South East Polynesia. Methods: We classified demosponge barcodes using the ribosomal subunit (28S rDNA) of 1,910 sponge samples into molecular operational taxonomic units (MOTUs). MOTU composition of the 13 marine provinces was compared based on Jaccard and Sorenson dissimilarities, and other biodiversity indices. Results: Our data corroborated high levels of endemism among demosponges. Faunal overlaps were revealed between the Red Sea and the Gulf, which displayed relatively small connectivity with other marine provinces of the Western Indian Ocean. In the Western Indian Ocean, we observed a strong faunistic boundary to the Central Indo-Pacific. The Polynesian sponge faunas were comparatively isolated marine provinces of the Central Indo-Pacific. Main conclusions: Our data corroborate case studies on sponges that generally reject the presence of cosmopolitan or otherwise widespread sponge species, instead revealing high levels of regional endemism. This is consistent with similar observations and hypotheses in other marine invertebrates. Connectivity among Indo-Pacific marine provinces differs for demosponges in many aspects from that of other marine taxa, such as corals and fishes, probably due to their shorter pelagic larval phase.Competing Interest StatementThe authors have declared no competing interest.