Multi-sample non-negative spatial factorization.

It is important to model biological variation when analyzing spatial transcriptomics data from multiple samples. One approach to multi-sample analysis is to spatially align samples, but this is a challenging problem. Here, we provide an alignment-free framework for generalizing a one-sample spatial factorization model to multi-sample data. Using this framework, we develop a method, called multi-sample non-negative spatial factorization (mNSF) that extends the one-sample non-negative spatial factorization (NSF) framework to a multi-sample dataset. Our model allows for a sample-specific model for the spatial correlation structure and extracts a low-dimensional representation of the data. We illustrate the performance of mNSF by simulation studies and real data. mNSF identifies true factors in simulated data, identifies shared anatomical regions across samples in real data and reveals region-specific biological functions. mNSFs performance is similar to alignment based methods when alignment is possible, but extends analysis to situations where spatial alignment is impossible. We expect multi-sample factorization methods to be a powerful class of methods for analyzing spatially resolved transcriptomics data.

Growth deficiency in a mouse model of Kabuki syndrome 2 bears mechanistic similarities to Kabuki syndrome 1.

Growth deficiency is a characteristic feature of both Kabuki syndrome 1 (KS1) and Kabuki syndrome 2 (KS2), Mendelian disorders of the epigenetic machinery with similar phenotypes but distinct genetic etiologies. We previously described skeletal growth deficiency in a mouse model of KS1 and further established that a Kmt2d-/- chondrocyte model of KS1 exhibits precocious differentiation. Here we characterized growth deficiency in a mouse model of KS2, Kdm6atm1d/+. We show that Kdm6atm1d/+ mice have decreased femur and tibia length compared to controls and exhibit abnormalities in cortical and trabecular bone structure. Kdm6atm1d/+ growth plates are also shorter, due to decreases in hypertrophic chondrocyte size and hypertrophic zone height. Given these disturbances in the growth plate, we generated Kdm6a-/- chondrogenic cell lines. Similar to our prior in vitro model of KS1, we found that Kdm6a-/- cells undergo premature, enhanced differentiation towards chondrocytes compared to Kdm6a+/+ controls. RNA-seq showed that Kdm6a-/- cells have a distinct transcriptomic profile that indicates dysregulation of cartilage development. Finally, we performed RNA-seq simultaneously on Kmt2d-/-, Kdm6a-/-, and control lines at Days 7 and 14 of differentiation. This revealed surprising resemblance in gene expression between Kmt2d-/- and Kdm6a-/- at both time points and indicates that the similarity in phenotype between KS1 and KS2 also exists at the transcriptional level.

CO2 supply is a powerful tool to control homoacetogenesis, chain elongation and solventogenesis in ethanol and carboxylate fed reactor microbiomes.

Anaerobic fermentation technology enables the production of medium chain carboxylates and alcohols through microbial chain elongation. This involves steering reactor microbiomes to yield desired products, with CO2 supply playing a crucial role in controlling ethanol-based chain elongation and facilitating various bioprocesses simultaneously. In the absence of CO2 supply (Phase I), chain elongation predominantly led to n-caproate with a high selectivity of 96 Cmol%, albeit leaving approximately 80% of ethanol unconverted. During this phase, C. kluyveri and Proteiniphilum-related species dominated the reactors. In Phase II, with low CO2 input (2.0 NmL L-1 min-1), formation of n-butyrate, butanol, and hexanol was stimulated. Increasing CO2 doses in Phase III (6 NmL L-1 min-1) led to CO2 utilization via homoacetogenesis, coinciding with the enrichment of Clostridium luticellarii, a bacterium that can use CO2 as an electron acceptor. Lowering CO2 dose to 0.5 NmL L-1 min-1 led to a shift in microbiome composition, diminishing the dominance of C. luticellarii while increasing C. kluyveri abundance. Additionally, other Clostridia, Proteiniphilum, and Lactobacillus sakei-related species became prevalent. This decrease in CO2 load from 6 to 0.5 NmL L-1 min-1 minimized excessive ethanol oxidation from 30%-50% to 0%-3%, restoring a microbiome favoring net n-butyrate consumption and n-caproate production. The decreased ethanol oxidation coincided with the resurgence of hydrogen formation at partial pressures above 1%. High concentrations of butyrate, caproate, and ethanol in the reactor, along with low acetate concentration, promoted the formation of butanol and hexanol. It is evident that CO2 supply is indispensable for controlling chain elongation in an open culture and it can be harnessed to stimulate higher alcohol formation or induce CO2 utilization as an electron acceptor.

Neuron-specific chromatin disruption at CpG islands and aging-related regions in Kabuki syndrome mice.

Many Mendelian developmental disorders caused by coding variants in epigenetic regulators have now been discovered. Epigenetic regulators are broadly expressed, and each of these disorders typically shows phenotypic manifestations from many different organ systems. An open question is whether the chromatin disruption-the root of the pathogenesis-is similar in the different disease-relevant cell types. This is possible in principle, because all these cell types are subject to effects from the same causative gene, which has the same kind of function (e.g., methylates histones) and is disrupted by the same germline variant. We focus on mouse models for Kabuki syndrome types 1 and 2 and find that the chromatin accessibility changes in neurons are mostly distinct from changes in B or T cells. This is not because the neuronal accessibility changes occur at regulatory elements that are only active in neurons. Neurons, but not B or T cells, show preferential chromatin disruption at CpG islands and at regulatory elements linked to aging. A sensitive analysis reveals that regulatory elements disrupted in B/T cells do show chromatin accessibility changes in neurons, but these are very subtle and of uncertain functional significance. Finally, we are able to identify a small set of regulatory elements disrupted in all three cell types. Our findings reveal the cellular-context-specific effect of variants in epigenetic regulators and suggest that blood-derived episignatures, although useful diagnostically, may not be well suited for understanding the mechanistic basis of neurodevelopment in Mendelian disorders of the epigenetic machinery.

Removing unwanted variation between samples in Hi-C experiments.

Hi-C data are commonly normalized using single sample processing methods, with focus on comparisons between regions within a given contact map. Here, we aim to compare contact maps across different samples. We demonstrate that unwanted variation, of likely technical origin, is present in Hi-C data with replicates from different individuals, and that properties of this unwanted variation change across the contact map. We present band-wise normalization and batch correction, a method for normalization and batch correction of Hi-C data and show that it substantially improves comparisons across samples, including in a quantitative trait loci analysis as well as differential enrichment across cell types.

Genotype prediction of 336,463 samples from public expression data.

Tens of thousands of RNA-sequencing experiments comprising hundreds of thousands of individual samples have now been performed. These data represent a broad range of experimental conditions, sequencing technologies, and hypotheses under study. The Recount project has aggregated and uniformly processed hundreds of thousands of publicly available RNA-seq samples. Most of these samples only include RNA expression measurements; genotype data for these same samples would enable a wide range of analyses including variant prioritization, eQTL analysis, and studies of allele specific expression. Here, we developed a statistical model based on the existing reference and alternative read counts from the RNA-seq experiments available through Recount3 to predict genotypes at autosomal biallelic loci in coding regions. We demonstrate the accuracy of our model using large-scale studies that measured both gene expression and genotype genome-wide. We show that our predictive model is highly accurate with 99.5% overall accuracy, 99.6% major allele accuracy, and 90.4% minor allele accuracy. Our model is robust to tissue and study effects, provided the coverage is high enough. We applied this model to genotype all the samples in Recount 3 and provide the largest ready-to-use expression repository containing genotype information. We illustrate that the predicted genotype from RNA-seq data is sufficient to unravel the underlying population structure of samples in Recount3 using Principal Component Analysis.

Epitope Mapping of Human Polyclonal Antibodies to the fHbp Antigen of a Neisseria Meningitidis Vaccine by Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS).

Antigen-antibody interactions play a key role in the immune response post vaccination and the mechanism of action of antibody-based biopharmaceuticals. 4CMenB is a multicomponent vaccine against Neisseria meningitidis serogroup B in which factor H binding protein (fHbp) is one of the key antigens. In this study, we use hydrogen/deuterium exchange mass spectrometry (HDX-MS) to identify epitopes in fHbp recognized by polyclonal antibodies (pAb) from two human donors (HDs) vaccinated with 4CMenB. Our HDX-MS data reveal several epitopes recognized by the complex mixture of human pAb. Furthermore, we show that the pAb from the two HDs recognize the same epitope regions. Epitope mapping of total pAb and purified fHbp-specific pAb from the same HD reveals that the two antibody samples recognize the same main epitopes, showing that HDX-MS based epitope mapping can, in this case at least, be performed directly using total IgG pAb samples that have not undergone Ab-selective purification. Two monoclonal antibodies (mAb) were previously produced from B-cell repertoire sequences from one of the HDs and used for epitope mapping of fHbp with HDX-MS. The epitopes identified for the pAb from the same HD in this study, overlap with the epitopes recognized by the two individual mAbs. Overall, HDX-MS epitope mapping appears highly suitable for simultaneous identification of epitopes recognized by pAb from human donors and to thus both guide vaccine development and study basic human immunity to pathogens, including viruses.

A mouse model of Weaver syndrome displays overgrowth and excess osteogenesis reversible with KDM6A/6B inhibition.

Weaver syndrome is a Mendelian disorder of the epigenetic machinery (MDEM) caused by germline pathogenic variants in EZH2, which encodes the predominant H3K27 methyltransferase and key enzymatic component of Polycomb repressive complex 2 (PRC2). Weaver syndrome is characterized by striking overgrowth and advanced bone age, intellectual disability, and distinctive facies. We generated a mouse model for the most common Weaver syndrome missense variant, EZH2 p.R684C. Ezh2R684C/R684C mouse embryonic fibroblasts (MEFs) showed global depletion of H3K27me3. Ezh2R684C/+ mice had abnormal bone parameters, indicative of skeletal overgrowth, and Ezh2R684C/+ osteoblasts showed increased osteogenic activity. RNA-Seq comparing osteoblasts differentiated from Ezh2R684C/+, and Ezh2+/+ BM-mesenchymal stem cells (BM-MSCs) indicated collective dysregulation of the BMP pathway and osteoblast differentiation. Inhibition of the opposing H3K27 demethylases KDM6A and KDM6B substantially reversed the excessive osteogenesis in Ezh2R684C/+ cells both at the transcriptional and phenotypic levels. This supports both the ideas that writers and erasers of histone marks exist in a fine balance to maintain epigenome state and that epigenetic modulating agents have therapeutic potential for the treatment of MDEMs.

Conformationally Restricted Glycopeptide Backbone Inhibits Gas-Phase H/D Scrambling between Glycan and Peptide Moieties.

Protein glycosylation is a common post-translational modification on extracellular proteins. The conformational dynamics of several glycoproteins have been characterized by hydrogen/deuterium exchange mass spectrometry (HDX-MS). However, it is, in most cases, not possible to extract information about glycan conformation and dynamics due to the general difficulty of separating the deuterium content of the glycan from that of the peptide (in particular, for O-linked glycans). Here, we investigate whether the fragmentation of protonated glycopeptides by collision-induced dissociation (CID) can be used to determine the solution-specific deuterium content of the glycan. Central to this concept is that glycopeptides can undergo a facile loss of glycans upon CID, thereby allowing for the determination of their masses. However, an essential prerequisite is that hydrogen and deuterium (H/D) scrambling can be kept in check. Therefore, we have measured the degree of scrambling upon glycosidic bond cleavage in glycopeptides that differ in the conformational flexibility of their backbone and glycosylation pattern. Our results show that complete scrambling precedes the glycosidic bond cleavage in normal glycopeptides derived from a glycoprotein; i.e., all labile hydrogens have undergone positional randomization prior to loss of the glycan. In contrast, the glycosidic bond cleavage occurs without any scrambling in the glycopeptide antibiotic vancomycin, reflecting that the glycan cannot interact with the peptide moiety due to a conformationally restricted backbone as revealed by molecular dynamics simulations. Scrambling is also inhibited, albeit to a lesser degree, in the conformationally restricted glycopeptides ristocetin and its pseudoaglycone, demonstrating that scrambling depends on an intricate interplay between the flexibility and proximity of the glycan and the peptide backbone.

Pumping the brakes on RNA velocity by understanding and interpreting RNA velocity estimates.

BACKGROUND: RNA velocity analysis of single cells offers the potential to predict temporal dynamics from gene expression. In many systems, RNA velocity has been observed to produce a vector field that qualitatively reflects known features of the system. However, the limitations of RNA velocity estimates are still not well understood. RESULTS: We analyze the impact of different steps in the RNA velocity workflow on direction and speed. We consider both high-dimensional velocity estimates and low-dimensional velocity vector fields mapped onto an embedding. We conclude the transition probability method for mapping velocity estimates onto an embedding is effectively interpolating in the embedding space. Our findings reveal a significant dependence of the RNA velocity workflow on smoothing via the k-nearest-neighbors (k-NN) graph of the observed data. This reliance results in considerable estimation errors for both direction and speed in both high- and low-dimensional settings when the k-NN graph fails to accurately represent the true data structure; this is an unknown feature of real data. RNA velocity performs poorly at estimating speed in both low- and high-dimensional spaces, except in very low noise settings. We introduce a novel quality measure that can identify when RNA velocity should not be used. CONCLUSIONS: Our findings emphasize the importance of choices in the RNA velocity workflow and highlight critical limitations of data analysis. We advise against over-interpreting expression dynamics using RNA velocity, particularly in terms of speed. Finally, we emphasize that the use of RNA velocity in assessing the correctness of a low-dimensional embedding is circular.

Precision pharmacological reversal of strain-specific diet-induced metabolic syndrome in mice informed by epigenetic and transcriptional regulation.

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat, high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genome-wide DNA methylation analyses for each strain and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects revealed a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by epigenetic and transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the farnesoid X receptor pathway, and found that GW4064 exerts strain-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis. Furthermore, GW4064 treatment induced inflammatory-related gene expression changes in NOD, indicating a strain-specific effect in its associated toxicities as well as its therapeutic efficacy. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention and a mouse platform for guiding this approach.

Development of a PNGase Rc Column for Online Deglycosylation of Complex Glycoproteins during HDX-MS.

Protein glycosylation is one of the most common PTMs and many cell surface receptors, extracellular proteins, and biopharmaceuticals are glycosylated. However, HDX-MS analysis of such important glycoproteins has so far been limited by difficulties in determining the HDX of the protein segments that contain glycans. We have developed a column containing immobilized PNGase Rc (from Rudaea cellulosilytica) that can readily be implemented into a conventional HDX-MS setup to allow improved analysis of glycoproteins. We show that HDX-MS with the PNGase Rc column enables efficient online removal of N-linked glycans and the determination of the HDX of glycosylated regions in several complex glycoproteins. Additionally, we use the PNGase Rc column to perform a comprehensive HDX-MS mapping of the binding epitope of a mAb to c-Met, a complex glycoprotein drug target. Importantly, the column retains high activity in the presence of common quench-buffer additives like TCEP and urea and performed consistent across 114 days of extensive use. Overall, our work shows that HDX-MS with the integrated PNGase Rc column can enable fast and efficient online deglycosylation at harsh quench conditions to provide comprehensive analysis of complex glycoproteins.

Neuron-specific chromatin disruption at CpG islands and aging-related regions in Kabuki syndrome mice.

Many Mendelian developmental disorders caused by coding variants in epigenetic regulators have now been discovered. Epigenetic regulators are broadly expressed, and each of these disorders typically exhibits phenotypic manifestations from many different organ systems. An open question is whether the chromatin disruption - the root of the pathogenesis - is similar in the different disease-relevant cell types. This is possible in principle, since all these cell-types are subject to effects from the same causative gene, that has the same kind of function (e.g. methylates histones) and is disrupted by the same germline variant. We focus on mouse models for Kabuki syndrome types 1 and 2, and find that the chromatin accessibility abnormalities in neurons are mostly distinct from those in B or T cells. This is not because the neuronal abnormalities occur at regulatory elements that are only active in neurons. Neurons, but not B or T cells, show preferential chromatin disruption at CpG islands and at regulatory elements linked to aging. A sensitive analysis reveals that the regions disrupted in B/T cells do exhibit chromatin accessibility changes in neurons, but these are very subtle and of uncertain functional significance. Finally, we are able to identify a small set of regulatory elements disrupted in all three cell types. Our findings reveal the cellular-context-specific effect of variants in epigenetic regulators, and suggest that blood-derived "episignatures" may not be well-suited for understanding the mechanistic basis of neurodevelopment in Mendelian disorders of the epigenetic machinery.

Novel mouse model of Weaver syndrome displays overgrowth and excess osteogenesis reversible with KDM6A/6B inhibition.

Weaver syndrome is a Mendelian disorder of the epigenetic machinery (MDEM) caused by germline pathogenic variants in EZH2, which encodes the predominant H3K27 methyltransferase and key enzymatic component of Polycomb repressive complex 2 (PRC2). Weaver syndrome is characterized by striking overgrowth and advanced bone age, intellectual disability, and distinctive facies. We generated a mouse model for the most common Weaver syndrome missense variant, EZH2 p.R684C. Ezh2R684C/R684C mouse embryonic fibroblasts (MEFs) showed global depletion of H3K27me3. Ezh2R684C/+ mice had abnormal bone parameters indicative of skeletal overgrowth, and Ezh2R684C/+ osteoblasts showed increased osteogenic activity. RNA-seq comparing osteoblasts differentiated from Ezh2R684C/+ and Ezh2+/+ bone marrow mesenchymal stem cells (BM-MSCs) indicated collective dysregulation of the BMP pathway and osteoblast differentiation. Inhibition of the opposing H3K27 demethylases Kdm6a/6b substantially reversed the excessive osteogenesis in Ezh2R684C/+ cells both at the transcriptional and phenotypic levels. This supports both the ideas that writers and erasers of histone marks exist in a fine balance to maintain epigenome state, and that epigenetic modulating agents have therapeutic potential for the treatment of MDEMs.

nnSVG for the scalable identification of spatially variable genes using nearest-neighbor Gaussian processes.

Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose nnSVG, a scalable approach to identify spatially variable genes based on nearest-neighbor Gaussian processes. Our method (i) identifies genes that vary in expression continuously across the entire tissue or within a priori defined spatial domains, (ii) uses gene-specific estimates of length scale parameters within the Gaussian process models, and (iii) scales linearly with the number of spatial locations. We demonstrate the performance of our method using experimental data from several technological platforms and simulations. A software implementation is available at https://bioconductor.org/packages/nnSVG .

Precision pharmacological reversal of genotype-specific diet-induced metabolic syndrome in mice informed by transcriptional regulation.

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genomic DNA methylation analyses and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects reveals a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the Farnesoid X receptor pathway, and found that GW4064 exerts genotype-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis, as well as increased inflammatory-related gene expression changes in NOD. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention, and a mouse platform for guiding this approach.

Quantification and statistical modeling of droplet-based single-nucleus RNA-sequencing data.

In complex tissues containing cells that are difficult to dissociate, single-nucleus RNA-sequencing (snRNA-seq) has become the preferred experimental technology over single-cell RNA-sequencing (scRNA-seq) to measure gene expression. To accurately model these data in downstream analyses, previous work has shown that droplet-based scRNA-seq data are not zero-inflated, but whether droplet-based snRNA-seq data follow the same probability distributions has not been systematically evaluated. Using pseudonegative control data from nuclei in mouse cortex sequenced with the 10x Genomics Chromium system and mouse kidney sequenced with the DropSeq system, we found that droplet-based snRNA-seq data follow a negative binomial distribution, suggesting that parametric statistical models applied to scRNA-seq are transferable to snRNA-seq. Furthermore, we found that the quantification choices in adapting quantification mapping strategies from scRNA-seq to snRNA-seq can play a significant role in downstream analyses and biological interpretation. In particular, reference transcriptomes that do not include intronic regions result in significantly smaller library sizes and incongruous cell type classifications. We also confirmed the presence of a gene length bias in snRNA-seq data, which we show is present in both exonic and intronic reads, and investigate potential causes for the bias.

Microbial Recycling of Bioplastics via Mixed-Culture Fermentation of Hydrolyzed Polyhydroxyalkanoates into Carboxylates.

Polyhydroxyalkanoates (PHA) polymers are emerging within biobased biodegradable plastic products. To build a circular economy, effective recycling routes should be established for these and other end-of-life bioplastics. This study presents the first steps of a potential PHA recycling route by fermenting hydrolyzed PHA-based bioplastics (Tianan ENMATTM Y1000P; PHBV (poly(3-hydroxybutyrate-co-3-hydroxyvalerate)) into carboxylates acetate and butyrate. First, three different hydrolysis pretreatment methods under acid, base, and neutral pH conditions were tested. The highest 10% (from 158.8 g COD/L to 16.3 g COD/L) of hydrolysate yield was obtained with the alkaline pretreatment. After filtration to remove the remaining solid materials, 4 g COD/L of the hydrolyzed PHA was used as the substrate with the addition of microbial nutrients for mixed culture fermentation. Due to microbial conversion, 1.71 g/L acetate and 1.20 g/L butyrate were produced. An apparent complete bioconversion from intermediates such as 3-hydroxybutyrate (3-HB) and/or crotonate into carboxylates was found. The overall yields of the combined processes were calculated as 0.07 g acetate/g PHA and 0.049 g butyrate/g PHA. These produced carboxylates can theoretically be used to reproduce PHA or serve many other applications as part of the so-called carboxylate platform.

Comprehensive DNA Methylation Analysis Indicates That Pancreatic Intraepithelial Neoplasia Lesions Are Acinar-Derived and Epigenetically Primed for Carcinogenesis.

Pancreatic ductal adenocarcinoma (PDAC) is believed to arise from the accumulation of a series of somatic mutations and is also frequently associated with pancreatic intraepithelial neoplasia (PanIN) lesions. However, there is still debate as to whether the cell type-of-origin of PanINs and PDACs in humans is acinar or ductal. As cell type identity is maintained epigenetically, DNA methylation changes during pancreatic neoplasia can provide a compelling perspective to examine this question. Here, we performed laser-capture microdissection on surgically resected specimens from 18 patients to isolate, with high purity, DNA for whole-genome bisulfite sequencing from four relevant cell types: acini, nonneoplastic ducts, PanIN lesions, and PDAC lesions. Differentially methylated regions (DMR) were identified using two complementary analytical approaches: bsseq, which identifies any DMRs but is particularly useful for large block-like DMRs, and informME, which profiles the potential energy landscape across the genome and is particularly useful for identifying differential methylation entropy. Both global methylation profiles and block DMRs clearly implicated an acinar origin for PanINs. At the gene level, PanIN lesions exhibited an intermediate acinar-ductal phenotype resembling acinar-to-ductal metaplasia. In 97.6% of PanIN-specific DMRs, PanIN lesions had an intermediate methylation level between normal and PDAC, which suggests from an information theory perspective that PanIN lesions are epigenetically primed to progress to PDAC. Thus, epigenomic analysis complements histopathology to define molecular progression toward PDAC. The shared epigenetic lineage between PanIN and PDAC lesions could provide an opportunity for prevention by targeting aberrantly methylated progression-related genes. SIGNIFICANCE: Analysis of DNA methylation landscapes provides insights into the cell-of-origin of PanIN lesions, clarifies the role of PanIN lesions as metaplastic precursors to human PDAC, and suggests potential targets for chemoprevention.

recountmethylation enables flexible analysis of public blood DNA methylation array data.

Summary: Thousands of DNA methylation (DNAm) array samples from human blood are publicly available on the Gene Expression Omnibus (GEO), but they remain underutilized for experiment planning, replication and cross-study and cross-platform analyses. To facilitate these tasks, we augmented our recountmethylation R/Bioconductor package with 12 537 uniformly processed EPIC and HM450K blood samples on GEO as well as several new features. We subsequently used our updated package in several illustrative analyses, finding (i) study ID bias adjustment increased variation explained by biological and demographic variables, (ii) most variation in autosomal DNAm was explained by genetic ancestry and CD4+ T-cell fractions and (iii) the dependence of power to detect differential methylation on sample size was similar for each of peripheral blood mononuclear cells (PBMC), whole blood and umbilical cord blood. Finally, we used PBMC and whole blood to perform independent validations, and we recovered 38-46% of differentially methylated probes between sexes from two previously published epigenome-wide association studies. Availability and implementation: Source code to reproduce the main results are available on GitHub (repo: recountmethylation_flexible-blood-analysis_manuscript; url: https://github.com/metamaden/recountmethylation_flexible-blood-analysis_manuscript). All data was publicly available and downloaded from the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/). Compilations of the analyzed public data can be accessed from the website recount.bio/data (preprocessed HM450K array data: https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/; preprocessed EPIC array data: https://recount.bio/data/remethdb_h5se-gm_epic_0-0-2_1589820348/). Supplementary information: Supplementary data are available at Bioinformatics Advances online.