Systematic comparison of sequencing-based spatial transcriptomic methods.

Recent developments of sequencing-based spatial transcriptomics (sST) have catalyzed important advancements by facilitating transcriptome-scale spatial gene expression measurement. Despite this progress, efforts to comprehensively benchmark different platforms are currently lacking. The extant variability across technologies and datasets poses challenges in formulating standardized evaluation metrics. In this study, we established a collection of reference tissues and regions characterized by well-defined histological architectures, and used them to generate data to compare 11 sST methods. We highlighted molecular diffusion as a variable parameter across different methods and tissues, significantly affecting the effective resolutions. Furthermore, we observed that spatial transcriptomic data demonstrate unique attributes beyond merely adding a spatial axis to single-cell data, including an enhanced ability to capture patterned rare cell states along with specific markers, albeit being influenced by multiple factors including sequencing depth and resolution. Our study assists biologists in sST platform selection, and helps foster a consensus on evaluation standards and establish a framework for future benchmarking efforts that can be used as a gold standard for the development and benchmarking of computational tools for spatial transcriptomic analysis.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

An immunohistochemical atlas of necroptotic pathway expression.

Necroptosis is a lytic form of regulated cell death reported to contribute to inflammatory diseases of the gut, skin and lung, as well as ischemic-reperfusion injuries of the kidney, heart and brain. However, precise identification of the cells and tissues that undergo necroptotic cell death in vivo has proven challenging in the absence of robust protocols for immunohistochemical detection. Here, we provide automated immunohistochemistry protocols to detect core necroptosis regulators - Caspase-8, RIPK1, RIPK3 and MLKL - in formalin-fixed mouse and human tissues. We observed surprising heterogeneity in protein expression within tissues, whereby short-lived immune barrier cells were replete with necroptotic effectors, whereas long-lived cells lacked RIPK3 or MLKL expression. Local changes in the expression of necroptotic effectors occurred in response to insults such as inflammation, dysbiosis or immune challenge, consistent with necroptosis being dysregulated in disease contexts. These methods will facilitate the precise localisation and evaluation of necroptotic signaling in vivo.

Flexiplex: a versatile demultiplexer and search tool for omics data.

MOTIVATION: The process of analyzing high throughput sequencing data often requires the identification and extraction of specific target sequences. This could include tasks, such as identifying cellular barcodes and UMIs in single-cell data, and specific genetic variants for genotyping. However, existing tools, which perform these functions are often task-specific, such as only demultiplexing barcodes for a dedicated type of experiment, or are not tolerant to noise in the sequencing data. RESULTS: To overcome these limitations, we developed Flexiplex, a versatile and fast sequence searching and demultiplexing tool for omics data, which is based on the Levenshtein distance and thus allows imperfect matches. We demonstrate Flexiplex's application on three use cases, identifying cell-line-specific sequences in Illumina short-read single-cell data, and discovering and demultiplexing cellular barcodes from noisy long-read single-cell RNA-seq data. We show that Flexiplex achieves an excellent balance of accuracy and computational efficiency compared to leading task-specific tools. AVAILABILITY AND IMPLEMENTATION: Flexiplex is available at https://davidsongroup.github.io/flexiplex/.

Dividing out quantification uncertainty allows efficient assessment of differential transcript expression with edgeR.

Differential expression analysis of RNA-seq is one of the most commonly performed bioinformatics analyses. Transcript-level quantifications are inherently more uncertain than gene-level read counts because of ambiguous assignment of sequence reads to transcripts. While sequence reads can usually be assigned unambiguously to a gene, reads are very often compatible with multiple transcripts for that gene, particularly for genes with many isoforms. Software tools designed for gene-level differential expression do not perform optimally on transcript counts because the read-to-transcript ambiguity (RTA) disrupts the mean-variance relationship normally observed for gene level RNA-seq data and interferes with the efficiency of the empirical Bayes dispersion estimation procedures. The pseudoaligners kallisto and Salmon provide bootstrap samples from which quantification uncertainty can be assessed. We show that the overdispersion arising from RTA can be elegantly estimated by fitting a quasi-Poisson model to the bootstrap counts for each transcript. The technical overdispersion arising from RTA can then be divided out of the transcript counts, leading to scaled counts that can be input for analysis by established gene-level software tools with full statistical efficiency. Comprehensive simulations and test data show that an edgeR analysis of the scaled counts is more powerful and efficient than previous differential transcript expression pipelines while providing correct control of the false discovery rate. Simulations explore a wide range of scenarios including the effects of paired vs single-end reads, different read lengths and different numbers of replicates.

scPipe: an extended preprocessing pipeline for comprehensive single-cell ATAC-Seq data integration in R/Bioconductor.

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.

Hookworms dynamically respond to loss of Type 2 immune pressure.

The impact of the host immune environment on parasite transcription and fitness is currently unknown. It is widely held that hookworm infections have an immunomodulatory impact on the host, but whether the converse is true remains unclear. Immunity against adult-stage hookworms is largely mediated by Type 2 immune responses driven by the transcription factor Signal Transducer and Activator of Transcription 6 (STAT6). This study investigated whether serial passage of the rodent hookworm Nippostrongylus brasiliensis in STAT6-deficient mice (STAT6 KO) caused changes in parasites over time. After adaptation to STAT6 KO hosts, N. brasiliensis increased their reproductive output, feeding capacity, energy content, and body size. Using an improved N. brasiliensis genome, we found that these physiological changes corresponded with a dramatic shift in the transcriptional landscape, including increased expression of gene pathways associated with egg production, but a decrease in genes encoding neuropeptides, proteases, SCP/TAPS proteins, and transthyretin-like proteins; the latter three categories have been repeatedly observed in hookworm excreted/secreted proteins (ESPs) implicated in immunosuppression. Although transcriptional changes started to appear in the first generation of passage in STAT6 KO hosts for both immature and mature adult stages, downregulation of the genes putatively involved in immunosuppression was only observed after multiple generations in this immunodeficient environment. When STAT6 KO-adapted N. brasiliensis were reintroduced to a naive WT host after up to 26 generations, this progressive change in host-adaptation corresponded to increased production of inflammatory cytokines by the WT host. Surprisingly, however, this single exposure of STAT6 KO-adapted N. brasiliensis to WT hosts resulted in worms that were morphologically and transcriptionally indistinguishable from WT-adapted parasites. This work uncovers remarkable plasticity in the ability of hookworms to adapt to their hosts, which may present a general feature of parasitic nematodes.

FGF-independent MEK1/2 signalling in the developing foetal testis is essential for male germline differentiation in mice.

BACKGROUND: Disrupted germline differentiation or compromised testis development can lead to subfertility or infertility and are strongly associated with testis cancer in humans. In mice, SRY and SOX9 induce expression of Fgf9, which promotes Sertoli cell differentiation and testis development. FGF9 is also thought to promote male germline differentiation but the mechanism is unknown. FGFs typically signal through mitogen-activated protein kinases (MAPKs) to phosphorylate ERK1/2 (pERK1/2). We explored whether FGF9 regulates male germline development through MAPK by inhibiting either FGF or MEK1/2 signalling in the foetal testis immediately after gonadal sex determination and testis cord formation, but prior to male germline commitment. RESULTS: pERK1/2 was detected in Sertoli cells and inhibition of MEK1/2 reduced Sertoli cell proliferation and organisation and resulted in some germ cells localised outside of the testis cords. While pERK1/2 was not detected in germ cells, inhibition of MEK1/2 after somatic sex determination profoundly disrupted germ cell mitotic arrest, dysregulated a broad range of male germline development genes and prevented the upregulation of key male germline markers, DPPA4 and DNMT3L. In contrast, while FGF inhibition reduced Sertoli cell proliferation, expression of male germline markers was unaffected and germ cells entered mitotic arrest normally. While male germline differentiation was not disrupted by FGF inhibition, a range of stem cell and cancer-associated genes were commonly altered after 24 h of FGF or MEK1/2 inhibition, including genes involved in the maintenance of germline stem cells, Nodal signalling, proliferation, and germline cancer. CONCLUSIONS: Together, these data demonstrate a novel role for MEK1/2 signalling during testis development that is essential for male germline differentiation, but indicate a more limited role for FGF signalling. Our data indicate that additional ligands are likely to act through MEK1/2 to promote male germline differentiation and highlight a need for further mechanistic understanding of male germline development.

Restrander: rapid orientation and artefact removal for long-read cDNA data.

In transcriptomic analyses, it is helpful to keep track of the strand of the RNA molecules. However, the Oxford Nanopore long-read cDNA sequencing protocols generate reads that correspond to either the first or second-strand cDNA, therefore the strandedness of the initial transcript has to be inferred bioinformatically. Reverse transcription and PCR can also introduce artefacts which should be flagged in data pre-processing. Here we introduce Restrander, a lightning-fast and highly accurate tool for restranding and removing artefacts in long-read cDNA sequencing data. Thanks to its C++ implementation, Restrander was faster than Oxford Nanopore Technologies' existing tool Pychopper, and correctly restranded more reads due to its strategy of searching for polyA/T tails in addition to primer sequences from the reverse transcription and template-switch steps. We found that restranding improved the process of visualising and exploring data, and increased the number of novel isoforms discovered by bambu, particularly in regions where sense and anti-sense transcripts co-occur. The artefact detection implemented in Restrander quantifies reads lacking the correct 5' and 3' ends, a useful feature in quality control for library preparation. Restrander is pre-configured for all major cDNA protocols, and can be customised with user-defined primers. Restrander is available at https://github.com/mritchielab/restrander.

Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures.

The lack of benchmark data sets with inbuilt ground-truth makes it challenging to compare the performance of existing long-read isoform detection and differential expression analysis workflows. Here, we present a benchmark experiment using two human lung adenocarcinoma cell lines that were each profiled in triplicate together with synthetic, spliced, spike-in RNAs (sequins). Samples were deeply sequenced on both Illumina short-read and Oxford Nanopore Technologies long-read platforms. Alongside the ground-truth available via the sequins, we created in silico mixture samples to allow performance assessment in the absence of true positives or true negatives. Our results show that StringTie2 and bambu outperformed other tools from the six isoform detection tools tested, DESeq2, edgeR and limma-voom were best among the five differential transcript expression tools tested and there was no clear front-runner for performing differential transcript usage analysis between the five tools compared, which suggests further methods development is needed for this application.

SMCHD1 has separable roles in chromatin architecture and gene silencing that could be targeted in disease.

The interplay between 3D chromatin architecture and gene silencing is incompletely understood. Here, we report a novel point mutation in the non-canonical SMC protein SMCHD1 that enhances its silencing capacity at endogenous developmental targets. Moreover, it also results in enhanced silencing at the facioscapulohumeral muscular dystrophy associated macrosatellite-array, D4Z4, resulting in enhanced repression of DUX4 encoded by this repeat. Heightened SMCHD1 silencing perturbs developmental Hox gene activation, causing a homeotic transformation in mice. Paradoxically, the mutant SMCHD1 appears to enhance insulation against other epigenetic regulators, including PRC2 and CTCF, while depleting long range chromatin interactions akin to what is observed in the absence of SMCHD1. These data suggest that SMCHD1's role in long range chromatin interactions is not directly linked to gene silencing or insulating the chromatin, refining the model for how the different levels of SMCHD1-mediated chromatin regulation interact to bring about gene silencing in normal development and disease.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Modeling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data.

Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and its presence can hamper the detection of differentially expressed genes. Since most bulk RNA-seq methods assume equal group variances, we introduce two new approaches that account for heteroscedastic groups, namely voomByGroup and voomWithQualityWeights using a blocked design (voomQWB). Compared to current gold-standard methods that do not account for group heteroscedasticity, we show results from simulations and various experiments that demonstrate the superior performance of voomByGroup and voomQWB in terms of error control and power when group variances in pseudo-bulk single-cell RNA-seq data are unequal.

Identification and control for the effects of bioinformatic globin depletion on human RNA-seq differential expression analysis.

When profiling blood samples by RNA-sequencing (RNA-seq), RNA from haemoglobin (Hgb) can account for up to 70% of the transcriptome. Due to considerations of sequencing depth and power to detect biological variation, Hgb RNA is typically depleted prior to sequencing by hybridisation-based methods; an alternative approach is to deplete reads arising from Hgb RNA bioinformatically. In the present study, we compared the impact of these two approaches on the outcome of differential gene expression analysis performed using RNA-seq data from 58 human tuberculosis (TB) patient or contact whole blood samples-29 globin kit-depleted and 29 matched non-depleted-a subset of which were taken at TB diagnosis and at six months post-TB treatment from the same patient. Bioinformatic depletion of Hgb genes from the non-depleted samples (bioinformatic-depleted) substantially reduced library sizes (median = 57.24%) and fewer long non-coding, micro, small nuclear and small nucleolar RNAs were captured in these libraries. Profiling published TB gene signatures across all samples revealed inferior correlation between kit-depleted and bioinformatic-depleted pairs when the proportion of reads mapping to Hgb genes was higher in the non-depleted sample, particularly at the TB diagnosis time point. A set of putative "globin-fingerprint" genes were identified by directly comparing kit-depleted and bioinformatic-depleted samples at each timepoint. Two TB treatment response signatures were also shown to have decreased differential performance when comparing samples at TB diagnosis to six months post-TB treatment when profiled on the bioinformatic-depleted samples compared with their kit-depleted counterparts. These results demonstrate that failure to deplete Hgb RNA prior to sequencing has a negative impact on the sensitivity to detect disease-relevant gene expression changes even when bioinformatic removal is performed.

Actinobacillus pleuropneumoniae encodes multiple phase-variable DNA methyltransferases that control distinct phasevarions.

Actinobacillus pleuropneumoniae is the cause of porcine pleuropneumonia, a severe respiratory tract infection that is responsible for major economic losses to the swine industry. Many host-adapted bacterial pathogens encode systems known as phasevarions (phase-variable regulons). Phasevarions result from variable expression of cytoplasmic DNA methyltransferases. Variable expression results in genome-wide methylation differences within a bacterial population, leading to altered expression of multiple genes via epigenetic mechanisms. Our examination of a diverse population of A. pleuropneumoniae strains determined that Type I and Type III DNA methyltransferases with the hallmarks of phase variation were present in this species. We demonstrate that phase variation is occurring in these methyltransferases, and show associations between particular Type III methyltransferase alleles and serovar. Using Pacific BioSciences Single-Molecule, Real-Time (SMRT) sequencing and Oxford Nanopore sequencing, we demonstrate the presence of the first ever characterised phase-variable, cytosine-specific Type III DNA methyltransferase. Phase variation of distinct Type III DNA methyltransferase in A. pleuropneumoniae results in the regulation of distinct phasevarions, and in multiple phenotypic differences relevant to pathobiology. Our characterisation of these newly described phasevarions in A. pleuropneumoniae will aid in the selection of stably expressed antigens, and direct and inform development of a rationally designed subunit vaccine against this major veterinary pathogen.

Venetoclax treatment in patients with cancer has limited impact on circulating T and NK cells.

Venetoclax is an effective treatment for certain blood cancers, such as chronic lymphocytic leukemia (CLL) and acute myeloid leukemia (AML). However, most patients relapse while on venetoclax and further treatment options are limited. Combining venetoclax with immunotherapies is an attractive approach; however, a detailed understanding of how venetoclax treatment impacts normal immune cells in patients is lacking. In this study, we performed deep profiling of peripheral blood (PB) cells from patients with CLL and AML before and after short-term treatment with venetoclax using mass cytometry (cytometry by time of flight) and found no impact on the concentrations of key T-cell subsets or their expression of checkpoint molecules. We also analyzed PB from patients with breast cancer receiving venetoclax long-term using a single-cell multiomics approach (cellular indexing of transcriptomes and epitopes by sequencing) and functional assays. We found significant depletion of B-cell populations with low expression of MCL-1 relative to other immune cells, attended by extensive transcriptomic changes. By contrast, there was less impact on circulating T cells and natural killer (NK) cells, with no changes in their subset composition, transcriptome, or function following venetoclax treatment. Our data indicate that venetoclax has minimal impact on circulating T or NK cells, supporting the rationale of combining this BH3 mimetic drug with cancer immunotherapies for more durable antitumor responses.

Arginine-rich C9ORF72 ALS proteins stall ribosomes in a manner distinct from a canonical ribosome-associated quality control substrate.

Hexanucleotide expansion mutations in C9ORF72 are a frequent cause of amyotrophic lateral sclerosis. We previously reported that long arginine-rich dipeptide repeats (DPRs), mimicking abnormal proteins expressed from the hexanucleotide expansion, caused translation stalling when expressed in cell culture models. Whether this stalling provides a mechanism of pathogenicity remains to be determined. Here, we explored the molecular features of DPR-induced stalling and examined whether known mechanisms such as ribosome quality control (RQC) regulate translation elongation on sequences that encode arginine-rich DPRs. We demonstrate that arginine-rich DPRs lead to stalling in a length-dependent manner, with lengths longer than 40 repeats invoking severe translation arrest. Mutational screening of 40×Gly-Xxx DPRs shows that stalling is most pronounced when Xxx is a charged amino acid (Arg, Lys, Glu, or Asp). Through a genome-wide knockout screen, we find that genes regulating stalling on polyadenosine mRNA coding for poly-Lys, a canonical RQC substrate, act differently in the case of arginine-rich DPRs. Indeed, these findings point to a limited scope for natural regulatory responses to resolve the arginine-rich DPR stalls, even though the stalls may be sensed, as evidenced by an upregulation of RQC gene expression. These findings therefore implicate arginine-rich DPR-mediated stalled ribosomes as a source of stress and toxicity and may be a crucial component in pathomechanisms.

A method for stabilising the XX karyotype in female mESC cultures.

Female mouse embryonic stem cells (mESCs) present differently from male mESCs in several fundamental ways; however, complications with their in vitro culture have resulted in an under-representation of female mESCs in the literature. Recent studies show that the second X chromosome in female, and more specifically the transcriptional activity from both of these chromosomes due to absent X chromosome inactivation, sets female and male mESCs apart. To avoid this undesirable state, female mESCs in culture preferentially adopt an XO karyotype, with this adaption leading to loss of their unique properties in favour of a state that is near indistinguishable from male mESCs. If female pluripotency is to be studied effectively in this system, it is crucial that high-quality cultures of XX mESCs are available. Here, we report a method for better maintaining XX female mESCs in culture that also stabilises the male karyotype and makes study of female-specific pluripotency more feasible.

A specialized tyrosine-based endocytosis signal in MR1 controls antigen presentation to MAIT cells.

MR1 is a highly conserved microbial immune-detection system in mammals. It captures vitamin B-related metabolite antigens from diverse microbes and presents them at the cell surface to stimulate MR1-restricted lymphocytes including mucosal-associated invariant T (MAIT) cells. MR1 presentation and MAIT cell recognition mediate homeostasis through host defense and tissue repair. The cellular mechanisms regulating MR1 cell surface expression are critical to its function and MAIT cell recognition, yet they are poorly defined. Here, we report that human MR1 is equipped with a tyrosine-based motif in its cytoplasmic domain that mediates low affinity binding with the endocytic adaptor protein 2 (AP2) complex. This interaction controls the kinetics of MR1 internalization from the cell surface and minimizes recycling. We propose MR1 uses AP2 endocytosis to define the duration of antigen presentation to MAIT cells and the detection of a microbial metabolic signature by the immune system.