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.

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.

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.

Single-cell multiomics reveal the scale of multilayered adaptations enabling CLL relapse during venetoclax therapy.

Venetoclax (VEN) inhibits the prosurvival protein BCL2 to induce apoptosis and is a standard therapy for chronic lymphocytic leukemia (CLL), delivering high complete remission rates and prolonged progression-free survival in relapsed CLL but with eventual loss of efficacy. A spectrum of subclonal genetic changes associated with VEN resistance has now been described. To fully understand clinical resistance to VEN, we combined single-cell short- and long-read RNA-sequencing to reveal the previously unappreciated scale of genetic and epigenetic changes underpinning acquired VEN resistance. These appear to be multilayered. One layer comprises changes in the BCL2 family of apoptosis regulators, especially the prosurvival family members. This includes previously described mutations in BCL2 and amplification of the MCL1 gene but is heterogeneous across and within individual patient leukemias. Changes in the proapoptotic genes are notably uncommon, except for single cases with subclonal losses of BAX or NOXA. Much more prominent was universal MCL1 gene upregulation. This was driven by an overlying layer of emergent NF-κB (nuclear factor kappa B) activation, which persisted in circulating cells during VEN therapy. We discovered that MCL1 could be a direct transcriptional target of NF-κB. Both the switch to alternative prosurvival factors and NF-κB activation largely dissipate following VEN discontinuation. Our studies reveal the extent of plasticity of CLL cells in their ability to evade VEN-induced apoptosis. Importantly, these findings pinpoint new approaches to circumvent VEN resistance and provide a specific biological justification for the strategy of VEN discontinuation once a maximal response is achieved rather than maintaining long-term selective pressure with the drug.

Genome assembly of the Australian black tiger shrimp (Penaeus monodon) reveals a novel fragmented IHHNV EVE sequence.

Shrimp are a valuable aquaculture species globally; however, disease remains a major hindrance to shrimp aquaculture sustainability and growth. Mechanisms mediated by endogenous viral elements have been proposed as a means by which shrimp that encounter a new virus start to accommodate rather than succumb to infection over time. However, evidence on the nature of such endogenous viral elements and how they mediate viral accommodation is limited. More extensive genomic data on Penaeid shrimp from different geographical locations should assist in exposing the diversity of endogenous viral elements. In this context, reported here is a PacBio Sequel-based draft genome assembly of an Australian black tiger shrimp (Penaeus monodon) inbred for 1 generation. The 1.89 Gbp draft genome is comprised of 31,922 scaffolds (N50: 496,398 bp) covering 85.9% of the projected genome size. The genome repeat content (61.8% with 30% representing simple sequence repeats) is almost the highest identified for any species. The functional annotation identified 35,517 gene models, of which 25,809 were protein-coding and 17,158 were annotated using interproscan. Scaffold scanning for specific endogenous viral elements identified an element comprised of a 9,045-bp stretch of repeated, inverted, and jumbled genome fragments of infectious hypodermal and hematopoietic necrosis virus bounded by a repeated 591/590 bp host sequence. As only near complete linear ∼4 kb infectious hypodermal and hematopoietic necrosis virus genomes have been found integrated in the genome of P. monodon previously, its discovery has implications regarding the validity of PCR tests designed to specifically detect such linear endogenous viral element types. The existence of joined inverted infectious hypodermal and hematopoietic necrosis virus genome fragments also provides a means by which hairpin double-stranded RNA could be expressed and processed by the shrimp RNA interference machinery.

Benchmarking UMI-based single-cell RNA-seq preprocessing workflows.

BACKGROUND: Single-cell RNA-sequencing (scRNA-seq) technologies and associated analysis methods have rapidly developed in recent years. This includes preprocessing methods, which assign sequencing reads to genes to create count matrices for downstream analysis. While several packaged preprocessing workflows have been developed to provide users with convenient tools for handling this process, how they compare to one another and how they influence downstream analysis have not been well studied. RESULTS: Here, we systematically benchmark the performance of 10 end-to-end preprocessing workflows (Cell Ranger, Optimus, salmon alevin, alevin-fry, kallisto bustools, dropSeqPipe, scPipe, zUMIs, celseq2, and scruff) using datasets yielding different biological complexity levels generated by CEL-Seq2 and 10x Chromium platforms. We compare these workflows in terms of their quantification properties directly and their impact on normalization and clustering by evaluating the performance of different method combinations. While the scRNA-seq preprocessing workflows compared vary in their detection and quantification of genes across datasets, after downstream analysis with performant normalization and clustering methods, almost all combinations produce clustering results that agree well with the known cell type labels that provided the ground truth in our analysis. CONCLUSIONS: In summary, the choice of preprocessing method was found to be less important than other steps in the scRNA-seq analysis process. Our study comprehensively compares common scRNA-seq preprocessing workflows and summarizes their characteristics to guide workflow users.

Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing.

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.

Targeting histone acetylation dynamics and oncogenic transcription by catalytic P300/CBP inhibition.

To separate causal effects of histone acetylation on chromatin accessibility and transcriptional output, we used integrated epigenomic and transcriptomic analyses following acute inhibition of major cellular lysine acetyltransferases P300 and CBP in hematological malignancies. We found that catalytic P300/CBP inhibition dynamically perturbs steady-state acetylation kinetics and suppresses oncogenic transcriptional networks in the absence of changes to chromatin accessibility. CRISPR-Cas9 screening identified NCOR1 and HDAC3 transcriptional co-repressors as the principal antagonists of P300/CBP by counteracting acetylation turnover kinetics. Finally, deacetylation of H3K27 provides nucleation sites for reciprocal methylation switching, a feature that can be exploited therapeutically by concomitant KDM6A and P300/CBP inhibition. Overall, this study indicates that the steady-state histone acetylation-methylation equilibrium functions as a molecular rheostat governing cellular transcription that is amenable to therapeutic exploitation as an anti-cancer regimen.

Fatal perinatal mitochondrial cardiac failure caused by recurrent de novo duplications in the ATAD3 locus.

BACKGROUND: In about half of all patients with a suspected monogenic disease, genomic investigations fail to identify the diagnosis. A contributing factor is the difficulty with repetitive regions of the genome, such as those generated by segmental duplications. The ATAD3 locus is one such region, in which recessive deletions and dominant duplications have recently been reported to cause lethal perinatal mitochondrial diseases characterized by pontocerebellar hypoplasia or cardiomyopathy, respectively. METHODS: Whole exome, whole genome and long-read DNA sequencing techniques combined with studies of RNA and quantitative proteomics were used to investigate 17 subjects from 16 unrelated families with suspected mitochondrial disease. FINDINGS: We report six different de novo duplications in the ATAD3 gene locus causing a distinctive presentation including lethal perinatal cardiomyopathy, persistent hyperlactacidemia, and frequently corneal clouding or cataracts and encephalopathy. The recurrent 68 Kb ATAD3 duplications are identifiable from genome and exome sequencing but usually missed by microarrays. The ATAD3 duplications result in the formation of identical chimeric ATAD3A/ATAD3C proteins, altered ATAD3 complexes and a striking reduction in mitochondrial oxidative phosphorylation complex I and its activity in heart tissue. CONCLUSIONS: ATAD3 duplications appear to act in a dominant-negative manner and the de novo inheritance infers a low recurrence risk for families, unlike most pediatric mitochondrial diseases. More than 350 genes underlie mitochondrial diseases. In our experience the ATAD3 locus is now one of the five most common causes of nuclear-encoded pediatric mitochondrial disease but the repetitive nature of the locus means ATAD3 diagnoses may be frequently missed by current genomic strategies. FUNDING: Australian NHMRC, US Department of Defense, Japanese AMED and JSPS agencies, Australian Genomics Health Alliance and Australian Mito Foundation.

The First Genetic Map for a Psoraleoid Legume (Bituminaria bituminosa) Reveals Highly Conserved Synteny with Phaseoloid Legumes.

We present the first genetic map of tedera (Bituminaria bituminosa (L.) C.H. Stirton), a drought-tolerant forage legume from the Canary Islands with useful pharmaceutical properties. It is also the first genetic map for any species in the tribe Psoraleeae (Fabaceae). The map comprises 2042 genotyping-by-sequencing (GBS) markers distributed across 10 linkage groups, consistent with the haploid chromosome count for this species (n = 10). Sequence tags from the markers were used to find homologous matches in the genome sequences of the closely related species in the Phaseoleae tribe: soybean, common bean, and cowpea. No tedera linkage groups align in their entirety to chromosomes in any of these phaseoloid species, but there are long stretches of collinearity that could be used in tedera research for gene discovery purposes using the better-resourced phaseoloid species. Using Ks analysis of a tedera transcriptome against five legume genomes provides an estimated divergence time of 17.4 million years between tedera and soybean. Genomic information and resources developed here will be invaluable for breeding tedera varieties for forage and pharmaceutical purposes.

A single-cell transcriptome atlas of the adult human retina.

The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, Müller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult Müller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.

Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments.

Single cell RNA-sequencing (scRNA-seq) technology has undergone rapid development in recent years, leading to an explosion in the number of tailored data analysis methods. However, the current lack of gold-standard benchmark datasets makes it difficult for researchers to systematically compare the performance of the many methods available. Here, we generated a realistic benchmark experiment that included single cells and admixtures of cells or RNA to create 'pseudo cells' from up to five distinct cancer cell lines. In total, 14 datasets were generated using both droplet and plate-based scRNA-seq protocols. We compared 3,913 combinations of data analysis methods for tasks ranging from normalization and imputation to clustering, trajectory analysis and data integration. Evaluation revealed pipelines suited to different types of data for different tasks. Our data and analysis provide a comprehensive framework for benchmarking most common scRNA-seq analysis steps.

Single cell RNA sequencing of stem cell-derived retinal ganglion cells.

We used single cell sequencing technology to characterize the transcriptomes of 1,174 human embryonic stem cell-derived retinal ganglion cells (RGCs) at the single cell level. The human embryonic stem cell line BRN3B-mCherry (A81-H7), was differentiated to RGCs using a guided differentiation approach. Cells were harvested at day 36 and prepared for single cell RNA sequencing. Our data indicates the presence of three distinct subpopulations of cells, with various degrees of maturity. One cluster of 288 cells showed increased expression of genes involved in axon guidance together with semaphorin interactions, cell-extracellular matrix interactions and ECM proteoglycans, suggestive of a more mature RGC phenotype.

High concordance between Illumina HiSeq2500 and NextSeq500 for reduced representation bisulfite sequencing (RRBS).

Reduced representation bisulfite sequencing (RRBS) provides an efficient method for measuring DNA methylation at single base resolution in regions of high CpG density. This technique has been extensively tested on the HiSeq2500, which uses a 4-colour detection method, however it is unclear if the method will also work on the NextSeq500 platform, which employs a 2-colour detection system. We created an RRBS library and sequenced it on both the HiSeq2500 and NextSeq500, and found no significant difference in the base composition of reads derived from either machine. Moreover, the methylation calls made from the data of each instrument were highly concordant, with methylation patterns across the genome appearing as expected. Therefore, RRBS can be sequenced on the Nextseq500 with comparable quality to that of the HiSeq2500. All sequencing data are deposited in the GEO database under accession number GSE87097.