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.

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.

Mutant TRP53 exerts a target gene-selective dominant-negative effect to drive tumor development.

Mutations in Trp53, prevalent in human cancer, are reported to drive tumorigenesis through dominant-negative effects (DNEs) over wild-type TRP53 function as well as neomorphic gain-of-function (GOF) activity. We show that five TRP53 mutants do not accelerate lymphomagenesis on a TRP53-deficient background but strongly synergize with c-MYC overexpression in a manner that distinguishes the hot spot Trp53 mutations. RNA sequencing revealed that the mutant TRP53 DNE does not globally repress wild-type TRP53 function but disproportionately impacts a subset of wild-type TRP53 target genes. Accordingly, TRP53 mutant proteins impair pathways for DNA repair, proliferation, and metabolism in premalignant cells. This reveals that, in our studies of lymphomagenesis, mutant TRP53 drives tumorigenesis primarily through the DNE, which modulates wild-type TRP53 function in a manner advantageous for neoplastic transformation.

A single-cell RNA expression atlas of normal, preneoplastic and tumorigenic states in the human breast.

To examine global changes in breast heterogeneity across different states, we determined the single-cell transcriptomes of > 340,000 cells encompassing normal breast, preneoplastic BRCA1+/- tissue, the major breast cancer subtypes, and pairs of tumors and involved lymph nodes. Elucidation of the normal breast microenvironment revealed striking changes in the stroma of post-menopausal women. Single-cell profiling of 34 treatment-naive primary tumors, including estrogen receptor (ER)+ , HER2+ , and triple-negative breast cancers, revealed comparable diversity among cancer cells and a discrete subset of cycling cells. The transcriptomes of preneoplastic BRCA1+/- tissue versus tumors highlighted global changes in the immune microenvironment. Within the tumor immune landscape, proliferative CD8+ T cells characterized triple-negative and HER2+ cancers but not ER+ tumors, while all subtypes comprised cycling tumor-associated macrophages, thus invoking potentially different immunotherapy targets. Copy number analysis of paired ER+ tumors and lymph nodes indicated seeding by genetically distinct clones or mass migration of primary tumor cells into axillary lymph nodes. This large-scale integration of patient samples provides a high-resolution map of cell diversity in normal and cancerous human breast.

Calling differentially methylated regions from whole genome bisulphite sequencing with DMRcate.

Whole genome bisulphite sequencing (WGBS) permits the genome-wide study of single molecule methylation patterns. One of the key goals of mammalian cell-type identity studies, in both normal differentiation and disease, is to locate differential methylation patterns across the genome. We discuss the most desirable characteristics for DML (differentially methylated locus) and DMR (differentially methylated region) detection tools in a genome-wide context and choose a set of statistical methods that fully or partially satisfy these considerations to compare for benchmarking. Our data simulation strategy is both biologically informed-employing distribution parameters derived from large-scale consortium datasets-and thorough. We report DML detection ability with respect to coverage, group methylation difference, sample size, variability and covariate size, both marginally and jointly, and exhaustively with respect to parameter combination. We also benchmark these methods on FDR control and computational time. We use this result to backend and introduce an expanded version of DMRcate: an existing DMR detection tool for microarray data that we have extended to now call DMRs from WGBS data. We compare DMRcate to a set of alternative DMR callers using a similarly realistic simulation strategy. We find DMRcate and RADmeth are the best predictors of DMRs, and conclusively find DMRcate the fastest.

Single cell transcriptome atlas of mouse mammary epithelial cells across development.

BACKGROUND: Heterogeneity within the mouse mammary epithelium and potential lineage relationships have been recently explored by single-cell RNA profiling. To further understand how cellular diversity changes during mammary ontogeny, we profiled single cells from nine different developmental stages spanning late embryogenesis, early postnatal, prepuberty, adult, mid-pregnancy, late-pregnancy, and post-involution, as well as the transcriptomes of micro-dissected terminal end buds (TEBs) and subtending ducts during puberty. METHODS: The single cell transcriptomes of 132,599 mammary epithelial cells from 9 different developmental stages were determined on the 10x Genomics Chromium platform, and integrative analyses were performed to compare specific time points. RESULTS: The mammary rudiment at E18.5 closely aligned with the basal lineage, while prepubertal epithelial cells exhibited lineage segregation but to a less differentiated state than their adult counterparts. Comparison of micro-dissected TEBs versus ducts showed that luminal cells within TEBs harbored intermediate expression profiles. Ductal basal cells exhibited increased chromatin accessibility of luminal genes compared to their TEB counterparts suggesting that lineage-specific chromatin is established within the subtending ducts during puberty. An integrative analysis of five stages spanning the pregnancy cycle revealed distinct stage-specific profiles and the presence of cycling basal, mixed-lineage, and 'late' alveolar intermediates in pregnancy. Moreover, a number of intermediates were uncovered along the basal-luminal progenitor cell axis, suggesting a continuum of alveolar-restricted progenitor states. CONCLUSIONS: This extended single cell transcriptome atlas of mouse mammary epithelial cells provides the most complete coverage for mammary epithelial cells during morphogenesis to date. Together with chromatin accessibility analysis of TEB structures, it represents a valuable framework for understanding developmental decisions within the mouse mammary gland.

Lung Basal Stem Cells Rapidly Repair DNA Damage Using the Error-Prone Nonhomologous End-Joining Pathway.

Lung squamous cell carcinoma (SqCC), the second most common subtype of lung cancer, is strongly associated with tobacco smoking and exhibits genomic instability. The cellular origins and molecular processes that contribute to SqCC formation are largely unexplored. Here we show that human basal stem cells (BSCs) isolated from heavy smokers proliferate extensively, whereas their alveolar progenitor cell counterparts have limited colony-forming capacity. We demonstrate that this difference arises in part because of the ability of BSCs to repair their DNA more efficiently than alveolar cells following ionizing radiation or chemical-induced DNA damage. Analysis of mice harbouring a mutation in the DNA-dependent protein kinase catalytic subunit (DNA-PKcs), a key enzyme in DNA damage repair by nonhomologous end joining (NHEJ), indicated that BSCs preferentially repair their DNA by this error-prone process. Interestingly, polyploidy, a phenomenon associated with genetically unstable cells, was only observed in the human BSC subset. Expression signature analysis indicated that BSCs are the likely cells of origin of human SqCC and that high levels of NHEJ genes in SqCC are correlated with increasing genomic instability. Hence, our results favour a model in which heavy smoking promotes proliferation of BSCs, and their predilection for error-prone NHEJ could lead to the high mutagenic burden that culminates in SqCC. Targeting DNA repair processes may therefore have a role in the prevention and therapy of SqCC.

Regulation of germinal center responses and B-cell memory by the chromatin modifier MOZ.

Memory B cells and long-lived bone marrow-resident plasma cells maintain humoral immunity. Little is known about the intrinsic mechanisms that are essential for forming memory B cells or endowing them with the ability to rapidly differentiate upon reexposure while maintaining the population over time. Histone modifications have been shown to regulate lymphocyte development, but their role in regulating differentiation and maintenance of B-cell subsets during an immune response is unclear. Using stage-specific deletion of monocytic leukemia zinc finger protein (MOZ), a histone acetyltransferase, we demonstrate that mutation of this chromatin modifier alters fate decisions in both primary and secondary responses. In the absence of MOZ, germinal center B cells were significantly impaired in their ability to generate dark zone centroblasts, with a concomitant decrease in both cell-cycle progression and BCL-6 expression. In contrast, there was increased differentiation to IgM and low-affinity IgG1(+) memory B cells. The lack of MOZ affected the functional outcome of humoral immune responses, with an increase in secondary germinal centers and a corresponding decrease in secondary high-affinity antibody-secreting cell formation. Therefore, these data provide strong evidence that manipulating epigenetic modifiers can regulate fate decisions during humoral responses, and thus could be targeted for therapeutic intervention.

Integration of microRNA signatures of distinct mammary epithelial cell types with their gene expression and epigenetic portraits.

INTRODUCTION: MicroRNAs (miRNAs) have been implicated in governing lineage specification and differentiation in multiple organs; however, little is known about their specific roles in mammopoiesis. We have determined the global miRNA expression profiles of functionally distinct epithelial subpopulations in mouse and human mammary tissue, and compared these to their cognate transcriptomes and epigenomes. Finally, the human miRNA signatures were used to interrogate the different subtypes of breast cancer, with a view to determining miRNA networks deregulated during oncogenesis. METHODS: RNA from sorted mouse and human mammary cell subpopulations was subjected to miRNA expression analysis using the TaqMan MicroRNA Array. Differentially expressed (DE) miRNAs were correlated with gene expression and histone methylation profiles. Analysis of miRNA signatures of the intrinsic subtypes of breast cancer in The Cancer Genome Atlas (TCGA) database versus those of normal human epithelial subpopulations was performed. RESULTS: Unique miRNA signatures characterized each subset (mammary stem cell (MaSC)/basal, luminal progenitor, mature luminal, stromal), with a high degree of conservation across species. Comparison of miRNA and transcriptome profiles for the epithelial subtypes revealed an inverse relationship and pinpointed key developmental genes. Interestingly, expression of the primate-specific miRNA cluster (19q13.4) was found to be restricted to the MaSC/basal subset. Comparative analysis of miRNA signatures with H3 lysine modification maps of the different epithelial subsets revealed a tight correlation between active or repressive marks for the top DE miRNAs, including derepression of miRNAs in Ezh2-deficient cellular subsets. Interrogation of TCGA-identified miRNA profiles with the miRNA signatures of different human subsets revealed specific relationships. CONCLUSIONS: The derivation of global miRNA expression profiles for the different mammary subpopulations provides a comprehensive resource for understanding the interplay between miRNA networks and target gene expression. These data have highlighted lineage-specific miRNAs and potential miRNA-mRNA networks, some of which are disrupted in neoplasia. Furthermore, our findings suggest that key developmental miRNAs are regulated by global changes in histone modification, thus linking the mammary epigenome with genome-wide changes in the expression of genes and miRNAs. Comparative miRNA signature analyses between normal breast epithelial cells and breast tumors confirmed an important linkage between luminal progenitor cells and basal-like tumors.

Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.

A flexible statistical framework is developed for the analysis of read counts from RNA-Seq gene expression studies. It provides the ability to analyse complex experiments involving multiple treatment conditions and blocking variables while still taking full account of biological variation. Biological variation between RNA samples is estimated separately from the technical variation associated with sequencing technologies. Novel empirical Bayes methods allow each gene to have its own specific variability, even when there are relatively few biological replicates from which to estimate such variability. The pipeline is implemented in the edgeR package of the Bioconductor project. A case study analysis of carcinoma data demonstrates the ability of generalized linear model methods (GLMs) to detect differential expression in a paired design, and even to detect tumour-specific expression changes. The case study demonstrates the need to allow for gene-specific variability, rather than assuming a common dispersion across genes or a fixed relationship between abundance and variability. Genewise dispersions de-prioritize genes with inconsistent results and allow the main analysis to focus on changes that are consistent between biological replicates. Parallel computational approaches are developed to make non-linear model fitting faster and more reliable, making the application of GLMs to genomic data more convenient and practical. Simulations demonstrate the ability of adjusted profile likelihood estimators to return accurate estimators of biological variability in complex situations. When variation is gene-specific, empirical Bayes estimators provide an advantageous compromise between the extremes of assuming common dispersion or separate genewise dispersion. The methods developed here can also be applied to count data arising from DNA-Seq applications, including ChIP-Seq for epigenetic marks and DNA methylation analyses.

Identification of aberrant luminal progenitors and mTORC1 as a potential breast cancer prevention target in BRCA2 mutation carriers.

Inheritance of a BRCA2 pathogenic variant conveys a substantial life-time risk of breast cancer. Identification of the cell(s)-of-origin of BRCA2-mutant breast cancer and targetable perturbations that contribute to transformation remains an unmet need for these individuals who frequently undergo prophylactic mastectomy. Using preneoplastic specimens from age-matched, premenopausal females, here we show broad dysregulation across the luminal compartment in BRCA2mut/+ tissue, including expansion of aberrant ERBB3lo luminal progenitor and mature cells, and the presence of atypical oestrogen receptor (ER)-positive lesions. Transcriptional profiling and functional assays revealed perturbed proteostasis and translation in ERBB3lo progenitors in BRCA2mut/+ breast tissue, independent of ageing. Similar molecular perturbations marked tumours bearing BRCA2-truncating mutations. ERBB3lo progenitors could generate both ER+ and ER- cells, potentially serving as cells-of-origin for ER-positive or triple-negative cancers. Short-term treatment with an mTORC1 inhibitor substantially curtailed tumorigenesis in a preclinical model of BRCA2-deficient breast cancer, thus uncovering a potential prevention strategy for BRCA2 mutation carriers.

Ehf controls mammary alveolar lineage differentiation and is a putative suppressor of breast tumorigenesis.

The transcription factor EHF is highly expressed in the lactating mammary gland, but its role in mammary development and tumorigenesis is not fully understood. Utilizing a mouse model of Ehf deletion, herein, we demonstrate that loss of Ehf impairs mammary lobuloalveolar differentiation at late pregnancy, indicated by significantly reduced levels of milk genes and milk lipids, fewer differentiated alveolar cells, and an accumulation of alveolar progenitor cells. Further, deletion of Ehf increased proliferative capacity and attenuated prolactin-induced alveolar differentiation in mammary organoids. Ehf deletion also increased tumor incidence in the MMTV-PyMT mammary tumor model and increased the proliferative capacity of mammary tumor organoids, while low EHF expression was associated with higher tumor grade and poorer outcome in luminal A and basal human breast cancers. Collectively, these findings establish EHF as a non-redundant regulator of mammary alveolar differentiation and a putative suppressor of mammary tumorigenesis.

Unraveling the timeline of gene expression: A pseudotemporal trajectory analysis of single-cell RNA sequencing data.

Background: Single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed in recent years. The droplet-based single cell platforms enable the profiling of gene expression in tens of thousands of cells per sample. The goal of a typical scRNA-seq analysis is to identify different cell subpopulations and their respective marker genes. Additionally, trajectory analysis can be used to infer the developmental or differentiation trajectories of cells. Methods: This article demonstrates a comprehensive workflow for performing trajectory inference and time course analysis on a multi-sample single-cell RNA-seq experiment of the mouse mammary gland. The workflow uses open-source R software packages and covers all steps of the analysis pipeline, including quality control, doublet prediction, normalization, integration, dimension reduction, cell clustering, trajectory inference, and pseudo-bulk time course analysis. Sample integration and cell clustering follows the Seurat pipeline while the trajectory inference is conducted using the monocle3 package. The pseudo-bulk time course analysis uses the quasi-likelihood framework of edgeR. Results: Cells are ordered and positioned along a pseudotime trajectory that represented a biological process of cell differentiation and development. The study successfully identified genes that were significantly associated with pseudotime in the mouse mammary gland. Conclusions: The demonstrated workflow provides a valuable resource for researchers conducting scRNA-seq analysis using open-source software packages. The study successfully demonstrated the usefulness of trajectory analysis for understanding the developmental or differentiation trajectories of cells. This analysis can be applied to various biological processes such as cell development or disease progression, and can help identify potential biomarkers or therapeutic targets.

Three-dimensional genome architecture coordinates key regulators of lineage specification in mammary epithelial cells.

Although lineage-specific genes have been identified in the mammary gland, little is known about the contribution of the 3D genome organization to gene regulation in the epithelium. Here, we describe the chromatin landscape of the three major epithelial subsets through integration of long- and short-range chromatin interactions, accessibility, histone modifications, and gene expression. While basal genes display exquisite lineage specificity via distal enhancers, luminal-specific genes show widespread promoter priming in basal cells. Cell specificity in luminal progenitors is largely mediated through extensive chromatin interactions with super-enhancers in gene-body regions in addition to interactions with polycomb silencer elements. Moreover, lineage-specific transcription factors appear to be controlled through cell-specific chromatin interactivity. Finally, chromatin accessibility rather than interactivity emerged as a defining feature of the activation of quiescent basal stem cells. This work provides a comprehensive resource for understanding the role of higher-order chromatin interactions in cell-fate specification and differentiation in the adult mouse mammary gland.

R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue.

Breast cancer is a common and highly heterogeneous disease. Understanding cellular diversity in the mammary gland and its surrounding micro-environment across different states can provide insight into cancer development in the human breast. Recently, we published a large-scale single-cell RNA expression atlas of the human breast spanning normal, preneoplastic and tumorigenic states. Single-cell expression profiles of nearly 430,000 cells were obtained from 69 distinct surgical tissue specimens from 55 patients. This article extends the study by providing quality filtering thresholds, downstream processed R data objects, complete cell annotation and R code to reproduce all the analyses. Data quality assessment measures are presented and details are provided for all the bioinformatic analyses that produced results described in the study.

Activation of stably silenced genes by recruitment of a synthetic de-methylating module.

Stably silenced genes that display a high level of CpG dinucleotide methylation are refractory to the current generation of dCas9-based activation systems. To counter this, we create an improved activation system by coupling the catalytic domain of DNA demethylating enzyme TET1 with transcriptional activators (TETact). We show that TETact demethylation-coupled activation is able to induce transcription of suppressed genes, both individually and simultaneously in cells, and has utility across a number of cell types. Furthermore, we show that TETact can effectively reactivate embryonic haemoglobin genes in non-erythroid cells. We anticipate that TETact will expand the existing CRISPR toolbox and be valuable for functional studies, genetic screens and potential therapeutics.

Loss of TAF8 causes TFIID dysfunction and p53-mediated apoptotic neuronal cell death.

Mutations in genes encoding general transcription factors cause neurological disorders. Despite clinical prominence, the consequences of defects in the basal transcription machinery during brain development are unclear. We found that loss of the TATA-box binding protein-associated factor TAF8, a component of the general transcription factor TFIID, in the developing central nervous system affected the expression of many, but notably not all genes. Taf8 deletion caused apoptosis, unexpectedly restricted to forebrain regions. Nuclear levels of the transcription factor p53 were elevated in the absence of TAF8, as were the mRNAs of the pro-apoptotic p53 target genes Noxa, Puma and Bax. The cell death in Taf8 forebrain regions was completely rescued by additional loss of p53, but Taf8 and p53 brains failed to initiate a neuronal expression program. Taf8 deletion caused aberrant transcription of promoter regions and splicing anomalies. We propose that TAF8 supports the directionality of transcription and co-transcriptional splicing, and that failure of these processes causes p53-induced apoptosis of neuronal cells in the developing mouse embryo.

In vivo genome-editing screen identifies tumor suppressor genes that cooperate with Trp53 loss during mammary tumorigenesis.

Breast cancer is a heterogeneous disease that comprises multiple histological and molecular subtypes. To gain insight into mutations that drive breast tumorigenesis, we describe a pipeline for the identification and validation of tumor suppressor genes. Based on an in vivo genome-wide CRISPR/Cas9 screen in Trp53+/- heterozygous mice, we identified tumor suppressor genes that included the scaffold protein Axin1, the protein kinase A regulatory subunit gene Prkar1a, as well as the proof-of-concept genes Pten, Nf1, and Trp53 itself. Ex vivo editing of primary mammary epithelial organoids was performed to further interrogate the roles of Axin1 and Prkar1a. Increased proliferation and profound changes in mammary organoid morphology were observed for Axin1/Trp53 and Prkar1a/Trp53 double mutants compared to Pten/Trp53 double mutants. Furthermore, direct in vivo genome editing via intraductal injection of lentiviruses engineered to express dual short-guide RNAs revealed that mutagenesis of Trp53 and either Prkar1a, Axin1, or Pten markedly accelerated tumor development compared to Trp53-only mutants. This proof-of-principle study highlights the application of in vivo CRISPR/Cas9 editing for uncovering cooperativity between defects in tumor suppressor genes that elicit mammary tumorigenesis.

Mammary tumour cells remodel the bone marrow vascular microenvironment to support metastasis.

Bone marrow is a preferred metastatic site for multiple solid tumours and is associated with poor prognosis and significant morbidity. Accumulating evidence indicates that cancer cells colonise specialised niches within the bone marrow to support their long-term propagation, but the precise location and mechanisms that mediate niche interactions are unknown. Using breast cancer as a model of solid tumour metastasis to the bone marrow, we applied large-scale quantitative three-dimensional imaging to characterise temporal changes in the bone marrow microenvironment during disease progression. We show that mouse mammary tumour cells preferentially home to a pre-existing metaphyseal domain enriched for type H vessels. Metastatic lesion outgrowth rapidly remodelled the local vasculature through extensive sprouting to establish a tumour-supportive microenvironment. The evolution of this tumour microenvironment reflects direct remodelling of the vascular endothelium through tumour-derived granulocyte-colony stimulating factor (G-CSF) in a hematopoietic cell-independent manner. Therapeutic targeting of the metastatic niche by blocking G-CSF receptor inhibited pathological blood vessel remodelling and reduced bone metastasis burden. These findings elucidate a mechanism of 'host' microenvironment hijacking by mammary tumour cells to subvert the local microvasculature to form a specialised, pro-tumorigenic niche.

Intraclonal Plasticity in Mammary Tumors Revealed through Large-Scale Single-Cell Resolution 3D Imaging.

Breast tumors are inherently heterogeneous, but the evolving cellular organization through neoplastic progression is poorly understood. Here we report a rapid, large-scale single-cell resolution 3D imaging protocol based on a one-step clearing agent that allows visualization of normal tissue architecture and entire tumors at cellular resolution. Imaging of multicolor lineage-tracing models of breast cancer targeted to either basal or luminal progenitor cells revealed profound clonal restriction during progression. Expression profiling of clones arising in Pten/Trp53-deficient tumors identified distinct molecular signatures. Strikingly, most clones harbored cells that had undergone an epithelial-to-mesenchymal transition, indicating widespread, inherent plasticity. Hence, an integrative pipeline that combines lineage tracing, 3D imaging, and clonal RNA sequencing technologies offers a comprehensive path for studying mechanisms underlying heterogeneity in whole tumors.