Genome-wide DNA methylation mapping uncovers epigenetic changes associated with animal development, environmental adaptation, and species evolution. To address the lack of high-throughput methods for DNA methylation analysis in non-model organisms, we developed an integrated approach for studying DNA methylation differences independent of a reference genome. Experimentally, our method relies on an optimized 96-well protocol for reduced representation bisulfite sequencing (RRBS), which we have validated in nine species (human, mouse, rat, cow, dog, chicken, carp, sea bass, and zebrafish). Bioinformatically, we developed the RefFreeDMA software to deduce ad hoc genomes directly from RRBS reads and to pinpoint differentially methylated regions between samples or groups of individuals (http://RefFreeDMA.computational-epigenetics.org). The identified regions are interpreted using motif enrichment analysis and/or cross-mapping to annotated genomes. We validated our method by reference-free analysis of cell-type-specific DNA methylation in the blood of human, cow, and carp. In summary, we present a cost-effective method for epigenome analysis in ecology and evolution, which enables epigenome-wide association studies in natural populations and species without a reference genome.

The marsupial Tasmanian devil (Sarcophilus harrisii) faces extinction due to transmissible devil facial tumor disease (DFTD). To unveil the molecular underpinnings of this transmissible cancer, we combined pharmacological screens with an integrated systems-biology characterization. Sensitivity to inhibitors of ERBB tyrosine kinases correlated with their overexpression. Proteomic and DNA methylation analyses revealed tumor-specific signatures linked to the evolutionary conserved oncogenic STAT3. ERBB inhibition blocked phosphorylation of STAT3 and arrested cancer cells. Pharmacological blockade of ERBB or STAT3 prevented tumor growth in xenograft models and restored MHC class I expression. This link between the hyperactive ERBB-STAT3 axis and major histocompatibility complex class I-mediated tumor immunosurveillance provides mechanistic insights into horizontal transmissibility and puts forward a dual chemo-immunotherapeutic strategy to save Tasmanian devils from DFTD. VIDEO ABSTRACT.

The loss of forkhead box protein O1 (FoxO1) signaling in response to metabolic stress contributes to the etiology of type II diabetes, causing the dedifferentiation of pancreatic beta cells to a cell type reminiscent of endocrine progenitors. Lack of methods to easily model this process in vitro, however, have hindered progress into the identification of key downstream targets and potential inhibitors. We therefore aimed to establish such an in vitro cellular dedifferentiation model and apply it to identify novel agents involved in the maintenance of beta-cell identity.

Inflammatory bowel disease (IBD) arises by unknown environmental triggers in genetically susceptible individuals. Epigenetic regulation of gene expression may integrate internal and external influences and may thereby modulate disease susceptibility. Epigenetic modification may also affect the germ-line and in certain contexts can be inherited to offspring. This study investigates epigenetic alterations consequent to experimental murine colitis induced by dextran sodium sulphate (DSS), and their paternal transmission to offspring. Genome-wide methylome- and transcriptome-profiling of intestinal epithelial cells (IECs) and sperm cells of males of the F0 generation, which received either DSS and consequently developed colitis (F0(DSS)), or non-supplemented tap water (F0(Ctrl)) and hence remained healthy, and of their F1 offspring was performed using reduced representation bisulfite sequencing (RRBS) and RNA-sequencing (RNA-Seq), respectively. Offspring of F0(DSS) males exhibited aberrant methylation and expression patterns of multiple genes, including Igf1r and Nr4a2, which are involved in energy metabolism. Importantly, DSS colitis in F0(DSS) mice was associated with decreased body weight at baseline of their F1 offspring, and these F1 mice exhibited increased susceptibility to DSS-induced colitis compared to offspring from F0(Ctrl) males. This study hence demonstrates epigenetic transmissibility of metabolic and inflammatory traits resulting from experimental colitis.

Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping in very small cell populations (μWGBS) and single cells (scWGBS). Our assay is optimized for profiling many samples at low coverage, and we describe a bioinformatic method that analyzes collections of single-cell methylomes to infer cell-state dynamics. Using these technological advances, we studied epigenomic cell-state dynamics in three in vitro models of cellular differentiation and pluripotency, where we observed characteristic patterns of epigenome remodeling and cell-to-cell heterogeneity. The described method enables single-cell analysis of DNA methylation in a broad range of biological systems, including embryonic development, stem cell differentiation, and cancer. It can also be used to establish composite methylomes that account for cell-to-cell heterogeneity in complex tissue samples.

Type 1 diabetes is characterized by the destruction of pancreatic β cells, and generating new insulin-producing cells from other cell types is a major aim of regenerative medicine. One promising approach is transdifferentiation of developmentally related pancreatic cell types, including glucagon-producing α cells. In a genetic model, loss of the master regulatory transcription factor Arx is sufficient to induce the conversion of α cells to functional β-like cells. Here, we identify artemisinins as small molecules that functionally repress Arx by causing its translocation to the cytoplasm. We show that the protein gephyrin is the mammalian target of these antimalarial drugs and that the mechanism of action of these molecules depends on the enhancement of GABAA receptor signaling. Our results in zebrafish, rodents, and primary human pancreatic islets identify gephyrin as a druggable target for the regeneration of pancreatic β cell mass from α cells.

Pancreatic islets of Langerhans contain several specialized endocrine cell types, which are commonly identified by the expression of single marker genes. However, the established marker genes cannot capture the complete spectrum of cellular heterogeneity in human pancreatic islets, and existing bulk transcriptome datasets provide averages across several cell populations. To dissect the cellular composition of the human pancreatic islet and to establish transcriptomes for all major cell types, we performed single-cell RNA sequencing on 70 cells sorted from human primary tissue. We used this dataset to validate previously described marker genes at the single-cell level and to identify specifically expressed transcription factors for all islet cell subtypes. All data are available for browsing and download, thus establishing a useful resource of single-cell expression profiles for endocrine cells in human pancreatic islets.

Chronic inflammation impairs insulin secretion and sensitivity. β-cell dedifferentiation has recently been proposed as a mechanism underlying β-cell failure in T2D. Yet the effect of inflammation on β-cell identity in T2D has not been studied. Therefore, we investigated whether pro-inflammatory cytokines induce β-cell dedifferentiation and whether anti-inflammatory treatments improve insulin secretion via β-cell redifferentiation. We observed that IL-1β, IL-6 and TNFα promote β-cell dedifferentiation in cultured human and mouse islets, with IL-1β being the most potent one of them. In particular, β-cell identity maintaining transcription factor Foxo1 was downregulated upon IL-1β exposure. In vivo, anti-IL-1β, anti-TNFα or NF-kB inhibiting sodium salicylate treatment improved insulin secretion of isolated islets. However, only TNFα antagonism partially prevented the loss of β-cell identity gene expression. Finally, the combination of IL-1β and TNFα antagonism improved insulin secretion of ex vivo isolated islets in a synergistic manner. Thus, while inflammation triggered β-cell dedifferentiation and dysfunction in vitro, this mechanism seems to be only partly responsible for the observed in vivo improvements in insulin secretion.

Methylation of cytosines is a prototypic epigenetic modification of the DNA. It has been implicated in various regulatory mechanisms across the animal kingdom and particularly in vertebrates. We mapped DNA methylation in 580 animal species (535 vertebrates, 45 invertebrates), resulting in 2443 genome-scale DNA methylation profiles of multiple organs. Bioinformatic analysis of this large dataset quantified the association of DNA methylation with the underlying genomic DNA sequence throughout vertebrate evolution. We observed a broadly conserved link with two major transitions-once in the first vertebrates and again with the emergence of reptiles. Cross-species comparisons focusing on individual organs supported a deeply conserved association of DNA methylation with tissue type, and cross-mapping analysis of DNA methylation at gene promoters revealed evolutionary changes for orthologous genes. In summary, this study establishes a large resource of vertebrate and invertebrate DNA methylomes, it showcases the power of reference-free epigenome analysis in species for which no reference genomes are available, and it contributes an epigenetic perspective to the study of vertebrate evolution.

Spatial and molecular characteristics determine tissue function, yet high-resolution methods to capture both concurrently are lacking. Here, we developed high-definition spatial transcriptomics, which captures RNA from histological tissue sections on a dense, spatially barcoded bead array. Each experiment recovers several hundred thousand transcript-coupled spatial barcodes at 2-μm resolution, as demonstrated in mouse brain and primary breast cancer. This opens the way to high-resolution spatial analysis of cells and tissues.

Some members of the physiological human microbiome occasionally cause life-threatening disease even in immunocompetent individuals. A prime example of such a commensal pathogen is Neisseria meningitidis, which normally resides in the human nasopharynx but is also a leading cause of sepsis and epidemic meningitis. Using N. meningitidis as model organism, we tested the hypothesis that virulence of commensal pathogens is a consequence of within host evolution and selection of invasive variants due to mutations at contingency genes, a mechanism called phase variation. In line with the hypothesis that phase variation evolved as an adaptation to colonize diverse hosts, computational comparisons of all 27 to date completely sequenced and annotated meningococcal genomes retrieved from public databases showed that contingency genes are indeed enriched for genes involved in host interactions. To assess within-host genetic changes in meningococci, we further used ultra-deep whole-genome sequencing of throat-blood strain pairs isolated from four patients suffering from invasive meningococcal disease. We detected up to three mutations per strain pair, affecting predominantly contingency genes involved in type IV pilus biogenesis. However, there was not a single (set) of mutation(s) that could invariably be found in all four pairs of strains. Phenotypic assays further showed that these genetic changes were generally not associated with increased serum resistance, higher fitness in human blood ex vivo or differences in the interaction with human epithelial and endothelial cells in vitro. In conclusion, we hypothesize that virulence of meningococci results from accidental emergence of invasive variants during carriage and without within host evolution of invasive phenotypes during disease progression in vivo.

Genetic control of male or female gonad development displays between different groups of organisms a remarkable diversity of "master sex-determining genes" at the top of the genetic hierarchies, whereas downstream components surprisingly appear to be evolutionarily more conserved. Without much further studies, conservation of sequence has been equalized to conservation of function. We have used the medaka fish to investigate the generality of this paradigm. In medaka, the master male sex-determining gene is dmrt1bY, a highly conserved downstream regulator of sex determination in vertebrates. To understand its function in orchestrating the complex gene regulatory network, we have identified targets genes and regulated pathways of Dmrt1bY. Monitoring gene expression and interactions by transgenic fluorescent reporter fish lines, in vivo tissue-chromatin immunoprecipitation and in vitro gene regulation assays revealed concordance but also major discrepancies between mammals and medaka, notably amongst spatial, temporal expression patterns and regulations of the canonical Hedgehog and R-spondin/Wnt/Follistatin signaling pathways. Examination of Foxl2 protein distribution in the medaka ovary defined a new subpopulation of theca cells, where ovarian-type aromatase transcriptional regulation appears to be independent of Foxl2. In summary, these data show that the regulation of the downstream regulatory network of sex determination is less conserved than previously thought.

CRISPR-based genetic screens are accelerating biological discovery, but current methods have inherent limitations. Widely used pooled screens are restricted to simple readouts including cell proliferation and sortable marker proteins. Arrayed screens allow for comprehensive molecular readouts such as transcriptome profiling, but at much lower throughput. Here we combine pooled CRISPR screening with single-cell RNA sequencing into a broadly applicable workflow, directly linking guide RNA expression to transcriptome responses in thousands of individual cells. Our method for CRISPR droplet sequencing (CROP-seq) enables pooled CRISPR screens with single-cell transcriptome resolution, which will facilitate high-throughput functional dissection of complex regulatory mechanisms and heterogeneous cell populations.

Hematopoietic stem cells give rise to all blood cells in a differentiation process that involves widespread epigenome remodeling. Here we present genome-wide reference maps of the associated DNA methylation dynamics. We used a meta-epigenomic approach that combines DNA methylation profiles across many small pools of cells and performed single-cell methylome sequencing to assess cell-to-cell heterogeneity. The resulting dataset identified characteristic differences between HSCs derived from fetal liver, cord blood, bone marrow, and peripheral blood. We also observed lineage-specific DNA methylation between myeloid and lymphoid progenitors, characterized immature multi-lymphoid progenitors, and detected progressive DNA methylation differences in maturing megakaryocytes. We linked these patterns to gene expression, histone modifications, and chromatin accessibility, and we used machine learning to derive a model of human hematopoietic differentiation directly from DNA methylation data. Our results contribute to a better understanding of human hematopoietic stem cell differentiation and provide a framework for studying blood-linked diseases.

Micronutrient status of parents can affect long term health of their progeny. Around 2 billion humans are affected by chronic micronutrient deficiency. In this study we use zebrafish as a model system to examine morphological, molecular and epigenetic changes in mature offspring of parents that experienced a one-carbon (1-C) micronutrient deficiency. Zebrafish were fed a diet sufficient, or marginally deficient in 1-C nutrients (folate, vitamin B12, vitamin B6, methionine, choline), and then mated. Offspring livers underwent histological examination, RNA sequencing and genome-wide DNA methylation analysis. Parental 1-C micronutrient deficiency resulted in increased lipid inclusion and we identified 686 differentially expressed genes in offspring liver, the majority of which were downregulated. Downregulated genes were enriched for functional categories related to sterol, steroid and lipid biosynthesis, as well as mitochondrial protein synthesis. Differential DNA methylation was found at 2869 CpG sites, enriched in promoter regions and permutation analyses confirmed the association with parental feed. Our data indicate that parental 1-C nutrient status can persist as locus specific DNA methylation marks in descendants and suggest an effect on lipid utilization and mitochondrial protein translation in F1 livers. This points toward parental micronutrients status as an important factor for offspring health and welfare.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

Methods for highly multiplexed RNA imaging are limited in spatial resolution and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to the mouse brain, which yielded the readout of thousands of genes, including splice variants. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in the neurons of the mouse hippocampus, revealing patterns across multiple cell types, layer-specific cell types across the mouse visual cortex, and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus, ExSeq enables highly multiplexed mapping of RNAs from nanoscale to system scale.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

Transferring annotations of single-cell-, spatial- and multi-omics data is often challenging owing both to technical limitations, such as low spatial resolution or high dropout fraction, and to biological variations, such as continuous spectra of cell states. Based on the concept that these data are often best described as continuous mixtures of cells or molecules, we present a computational framework for the transfer of annotations to cells and their combinations (TACCO), which consists of an optimal transport model extended with different wrappers to annotate a wide variety of data. We apply TACCO to identify cell types and states, decipher spatiomolecular tissue structure at the cell and molecular level and resolve differentiation trajectories using synthetic and biological datasets. While matching or exceeding the accuracy of specialized tools for the individual tasks, TACCO reduces the computational requirements by up to an order of magnitude and scales to larger datasets (for example, considering the runtime of annotation transfer for 1 M simulated dropout observations).