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BACKGROUND: Computer use may have an adverse effect on musculoskeletal outcomes. This study assessed the risk of neck and shoulder pain associated with objectively recorded professional computer use. METHODS: A computer programme was used to collect data on mouse and keyboard usage and weekly reports of neck and shoulder pain among 2146 technical assistants. Questionnaires were also completed at baseline and at 12 months. The three outcome measures were: (1) acute pain (measured as weekly pain); (2) prolonged pain (no or minor pain in the neck and shoulder region over four consecutive weeks followed by three consecutive weeks with a high pain score); and (3) chronic pain (reported pain or discomfort lasting more than 30 days and 'quite a lot of trouble' during the past 12 months). RESULTS: Risk for acute neck pain and shoulder pain increased linearly by 4% and 10%, respectively, for each quartile increase in weekly mouse usage time. Mouse and keyboard usage time did not predict the onset of prolonged or chronic pain in the neck or shoulder. Women had higher risks for neck and shoulder pain. Number of keystrokes and mouse clicks, length of the average activity period, and micro-pauses did not influence reports of acute or prolonged pain. A few psychosocial factors predicted the risk of prolonged pain. CONCLUSIONS: Most computer workers have no or minor neck and shoulder pain, few experience prolonged pain, and even fewer, chronic neck and shoulder pain. Moreover, there seems to be no relationship between computer use and prolonged and chronic neck and shoulder pain. [ABSTRACT FROM AUTHOR]

BACKGROUND: It is well known that the time from conception to early childhood has importance for health conditions that reach into later stages of life. Recent research supports this view, and diseases such as cardiovascular morbidity, cancer, mental illnesses, asthma, and allergy may all have component causes that act early in life. Exposures in this period, which influence fetal growth, cell divisions, and organ functioning, may have long-lasting impact on health and disease susceptibility. METHODS: To investigate these issues the Danish National Birth Cohort (Better health for mother and child) was established. A large cohort of pregnant women with long-term follow-up of the offspring was the obvious choice because many of the exposures of interest cannot be reconstructed with sufficient validity back in time. The study needs to be large, and it is aimed to recruit 100,000 women early in pregnancy, and to continue follow-up for decades. The Nordic countries are better suited for this kind of research than most other countries because of their population-based registers on diseases, demography and social conditions, linkable at the individual level by means of the unique ID-number given to all citizens. Exposure information is mainly collected by computer-assisted telephone interviews with the women twice during pregnancy and when their children are six and 18 months old. Participants are also asked to fill in a self-administered food frequency questionnaire in mid-pregnancy. Furthermore, a biological bank has been set up with blood taken from the mother twice during pregnancy and blood from the umbilical cord taken shortly after birth. Data collection started in 1996 and the project covered all regions in Denmark in 1999. By August 2000. a total of 60,000 pregnant women had been recruited to the study. It is expected that a large number of gene-environmental hypotheses need to be based on case-control analyses within a cohort like this. [ABSTRACT FROM AUTHOR]

Analyzing multi-sample spatial transcriptomics data requires accounting for biological variation. We present multi-sample non-negative spatial factorization (mNSF), an alignment-free framework extending single-sample spatial factorization (NSF) to multi-sample datasets. mNSF incorporates sample-specific spatial correlation modeling and extracts low-dimensional data representations. Through simulations and real data analysis, we demonstrate mNSF's efficacy in identifying true factors, shared anatomical regions, and region-specific biological functions. mNSF's performance is comparable to alignment-based methods when alignment is feasible, while enabling analysis in scenarios where spatial alignment is unfeasible. mNSF shows promise as a robust method for analyzing spatially resolved transcriptomics data across multiple samples., Competing Interests: Conflicts of Interest None.

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., (© The Author(s) 2023. Published by Oxford University Press.)

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., (© 2024 Boukas et al.; Published by Cold Spring Harbor Laboratory Press.)

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., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests:HTB is a consultant for Mahzi therapeutics. The authors declare no other conflicts of interest relevant to this manuscript., (Copyright: © 2024 Gao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., (© The Author(s) 2024. Published by Oxford University Press.)

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., Competing Interests: Conflicts of Interest None.

Background: Current minimally invasive fat reduction modalities use equipment that can cost thousands of U.S. dollars. Electrochemical lipolysis (ECLL), using low-cost battery and electrodes (approximately $10), creates acid/base within fat (width, approximately 3 mm), damaging adipocytes. Longitudinal effects of ECLL have not been studied. In this pilot study, the authors hypothesize that in vivo ECLL induces fat necrosis, decreases adipocyte number/viability, and forms lipid droplets., Methods: Two female Yorkshire pigs (50 to 60 kg) received ECLL. In pig 1, 10 sites received ECLL, and 10 sites were untreated. In pig 2, 12 sites received ECLL and 12 sites were untreated. For ECLL, two electrodes were inserted into dorsal subcutaneous fat and direct current was applied for 5 minutes. Adverse effects of excessive pain, bleeding, infection, and agitation were monitored. Histology, live-dead (calcein, Hoechst, ethidium homodimer-1), and morphology (Bodipy and Hoechst) assays were performed on day 0 and postprocedure days 1, 2, 7, 14 (pig 1 and pig 2), and 28 (pig 2). Average particle area, fluorescence signal areas, and adipocytes and lipid droplet numbers were compared., Results: No adverse effects occurred. Live-dead assays showed adipocyte death on the anode on days 0 to 7 and the cathode on days 1 to 2 (not significant). Bodipy showed significant adipocyte loss at all sites ( P < 0.001) and lipid droplet formation at the cathode site on day 2 ( P = 0.0046). Histology revealed fat necrosis with significant increases in average particle area at the anode and cathode sites by day 14 (+277.3% change compared with untreated, P < 0.0001; +143.4%, P < 0.0001) and day 28 (+498.6%, P < 0.0001; +354.5%, P < 0.0001)., Conclusions: In vivo ECLL induces fat necrosis in pigs. Further studies are needed to evaluate volumetric fat reduction., Clinical Relevance Statement: In vivo ECLL induces adipocyte death and fat necrosis. ECLL has the potential to be utilized in body fat contouring., (Copyright © 2023 by the American Society of Plastic Surgeons.)

Background: Gene co-expression networks (GCNs) describe relationships among expressed genes key to maintaining cellular identity and homeostasis. However, the small sample size of typical RNA-seq experiments which is several orders of magnitude fewer than the number of genes is too low to infer GCNs reliably. recount3 , a publicly available dataset comprised of 316,443 uniformly processed human RNA-seq samples, provides an opportunity to improve power for accurate network reconstruction and obtain biological insight from the resulting networks., Results: We compared alternate aggregation strategies to identify an optimal workflow for GCN inference by data aggregation and inferred three consensus networks: a universal network, a non-cancer network, and a cancer network in addition to 27 tissue context-specific networks. Central network genes from our consensus networks were enriched for evolutionarily constrained genes and ubiquitous biological pathways, whereas central context-specific network genes included tissue-specific transcription factors and factorization based on the hubs led to clustering of related tissue contexts. We discovered that annotations corresponding to context-specific networks inferred from aggregated data were enriched for trait heritability beyond known functional genomic annotations and were significantly more enriched when we aggregated over a larger number of samples., Conclusion: This study outlines best practices for network GCN inference and evaluation by data aggregation. We recommend estimating and regressing confounders in each data set before aggregation and prioritizing large sample size studies for GCN reconstruction. Increased statistical power in inferring context-specific networks enabled the derivation of variant annotations that were enriched for concordant trait heritability independent of functional genomic annotations that are context-agnostic. While we observed strictly increasing held-out log-likelihood with data aggregation, we noted diminishing marginal improvements. Future directions aimed at alternate methods for estimating confounders and integrating orthogonal information from modalities such as Hi-C and ChIP-seq can further improve GCN inference., Competing Interests: Competing interests A.B. is a consultant for Third Rock Ventures, LLC, a shareholder in Alphabet, Inc, and a founder of CellCipher, Inc.

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.

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., (© 2023. The Author(s).)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Wulfridge et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., Competing Interests: Disclosure declaration HTB is a paid consultant for Mahzi therapeutics.

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 ., (© 2023. The Author(s).)

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. Ezh2 R684C/R684C mouse embryonic fibroblasts (MEFs) showed global depletion of H3K27me3. Ezh2 R684C/ + mice had abnormal bone parameters indicative of skeletal overgrowth, and Ezh2 R684C/ + osteoblasts showed increased osteogenic activity. RNA-seq comparing osteoblasts differentiated from Ezh2 R684C/ + 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 Ezh2 R684C/ + 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.

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., (©2023 American Association for Cancer Research.)

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.

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&#95;flexible-blood-analysis&#95;manuscript; url: https://github.com/metamaden/recountmethylation&#95;flexible-blood-analysis&#95;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&#95;h5se-gm&#95;epic&#95;0-0-2&#95;1589820348/; preprocessed EPIC array data: https://recount.bio/data/remethdb&#95;h5se-gm&#95;epic&#95;0-0-2&#95;1589820348/)., Supplementary Information: Supplementary data are available at Bioinformatics Advances online., (© The Author(s) 2023. Published by Oxford University Press.)

Estimates of correlation between pairs of genes in co-expression analysis are commonly used to construct networks among genes using gene expression data. As previously noted, the distribution of such correlations depends on the observed expression level of the involved genes, which we refer to this as a mean-correlation relationship in RNA-seq data, both bulk and single-cell. This dependence introduces an unwanted technical bias in co-expression analysis whereby highly expressed genes are more likely to be highly correlated. Such a relationship is not observed in protein-protein interaction data, suggesting that it is not reflecting biology. Ignoring this bias can lead to missing potentially biologically relevant pairs of genes that are lowly expressed, such as transcription factors. To address this problem, we introduce spatial quantile normalization (SpQN), a method for normalizing local distributions in a correlation matrix. We show that spatial quantile normalization removes the mean-correlation relationship and corrects the expression bias in network reconstruction., Competing Interests: The authors have declared that no competing interests exist.

Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures up to 36k CpGs per species that are well conserved across many mammalian species. We designed a set of probes that can tolerate specific cross-species mutations. We annotate the array in over 200 species and report CpG island status and chromatin states in select species. Calibration experiments demonstrate the high fidelity in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of conserved cytosines facilitating the development of epigenetic biomarkers, and it increases the probability that biological insights gained in one species will translate to others., (© 2022. The Author(s).)

Uremic symptoms are common in patients with advanced chronic kidney disease, but the toxins that cause these symptoms are unknown. To evaluate this, we performed a cross-sectional study of the 12 month post-randomization follow-up visit of Modification of Diet in Renal Disease (MDRD) participants reporting uremic symptoms who also had available stored serum. We quantified 1,163 metabolites by liquid chromatography-tandem mass spectrometry. For each uremic symptom, we calculated a score as the severity multiplied by the number of days the symptom was experienced. We analyzed the associations of the individual symptom scores with metabolites using linear models with empirical Bayesian inference, adjusted for multiple comparisons. Among 695 participants, the mean measured glomerular filtration rate (mGFR) was 28 mL/min/1.73 m 2 . Uremic symptoms were more common in the subgroup of 214 patients with an mGFR under 20 mL/min/1.73 m 2 (mGFR under 20 subgroup) than in the full group. For all metabolites with significant associations, the direction of the association was concordant in the full group and the subgroup. For gastrointestinal symptoms (bad taste, loss of appetite, nausea, and vomiting), eleven metabolites were associated with symptoms. For neurologic symptoms (decreased alertness, falling asleep during the day, forgetfulness, lack of pep and energy, and tiring easily/weakness), seven metabolites were associated with symptoms. Associations were consistent across sensitivity analyses. Thus, our proof-of-principle study demonstrates the potential for metabolomics to understand metabolic pathways associated with uremic symptoms. Larger, prospective studies with external validation are needed., (Copyright © 2021 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

Background: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data., Results: Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell-cycle embedding using a fixed reference dataset and project new data into this reference embedding, an approach that overcomes key limitations of learning a dataset-dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species, and even sequencing assays., Conclusions: Tricycle generalizes across datasets and is highly scalable and applicable to atlas-level single-cell RNA-seq data., (© 2021. The Author(s).)

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types.

We present recount3, a resource consisting of over 750,000 publicly available human and mouse RNA sequencing (RNA-seq) samples uniformly processed by our new Monorail analysis pipeline. To facilitate access to the data, we provide the recount3 and snapcount R/Bioconductor packages as well as complementary web resources. Using these tools, data can be downloaded as study-level summaries or queried for specific exon-exon junctions, genes, samples, or other features. Monorail can be used to process local and/or private data, allowing results to be directly compared to any study in recount3. Taken together, our tools help biologists maximize the utility of publicly available RNA-seq data, especially to improve their understanding of newly collected data. recount3 is available from http://rna.recount.bio ., (© 2021. The Author(s).)

Although each Mendelian Disorder of the Epigenetic Machinery (MDEM) has a different causative gene, there are shared disease manifestations. We hypothesize that this phenotypic convergence is a consequence of shared epigenetic alterations. To identify such shared alterations, we interrogate chromatin (ATAC-seq) and expression (RNA-seq) states in B cells from three MDEM mouse models (Kabuki [KS] type 1 and 2 and Rubinstein-Taybi type 1 [RT1] syndromes). We develop a new approach for the overlap analysis and find extensive overlap primarily localized in gene promoters. We show that disruption of chromatin accessibility at promoters often disrupts downstream gene expression, and identify 587 loci and 264 genes with shared disruption across all three MDEMs. Subtle expression alterations of multiple, IgA-relevant genes, collectively contribute to IgA deficiency in KS1 and RT1, but not in KS2. We propose that the joint study of MDEMs offers a principled approach for systematically mapping functional epigenetic variation in mammals., Competing Interests: TL, LB, GP, JJ, AK, KH, HB None, LZ none, (© 2021, Luperchio et al.)

While DNA methylation (DNAm) is the most-studied epigenetic mark, few recent studies probe the breadth of publicly available DNAm array samples. We collectively analyzed 35 360 Illumina Infinium HumanMethylation450K DNAm array samples published on the Gene Expression Omnibus. We learned a controlled vocabulary of sample labels by applying regular expressions to metadata and used existing models to predict various sample properties including epigenetic age. We found approximately two-thirds of samples were from blood, one-quarter were from brain and one-third were from cancer patients. About 19% of samples failed at least one of Illumina's 17 prescribed quality assessments; signal distributions across samples suggest modifying manufacturer-recommended thresholds for failure would make these assessments more informative. We further analyzed DNAm variances in seven tissues (adipose, nasal, blood, brain, buccal, sperm and liver) and characterized specific probes distinguishing them. Finally, we compiled DNAm array data and metadata, including our learned and predicted sample labels, into database files accessible via the recountmethylation R/Bioconductor companion package. Its vignettes walk the user through some analyses contained in this paper., (© The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Background: DNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions., Results: Using GTEx samples, we generate a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12 to 23 donors. We identify differentially methylated regions between brain regions among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pairwise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identify unique CpG differentially methylated regions, many associated with ion transport. We also identify 81,130 regions of variably CpG methylated regions, i.e., variable methylation among individuals in the same brain region, which are enriched in regulatory regions and in CpG differentially methylated regions. Many variably methylated regions are unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. Variably methylated regions identified in the amygdala, anterior cingulate cortex, and hippocampus are enriched for heritability of schizophrenia., Conclusions: These data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder.

Probing epigenetic features on DNA has tremendous potential to advance our understanding of the phased epigenome. In this study, we use nanopore sequencing to evaluate CpG methylation and chromatin accessibility simultaneously on long strands of DNA by applying GpC methyltransferase to exogenously label open chromatin. We performed nanopore sequencing of nucleosome occupancy and methylome (nanoNOMe) on four human cell lines (GM12878, MCF-10A, MCF-7 and MDA-MB-231). The single-molecule resolution allows footprinting of protein and nucleosome binding, and determination of the combinatorial promoter epigenetic signature on individual molecules. Long-read sequencing makes it possible to robustly assign reads to haplotypes, allowing us to generate a fully phased human epigenome, consisting of chromosome-level allele-specific profiles of CpG methylation and chromatin accessibility. We further apply this to a breast cancer model to evaluate differential methylation and accessibility between cancerous and noncancerous cells.

Body contouring achieved via subcutaneous adipose tissue reduction has notably advanced over the past century, from suction assisted lipectomy to techniques with reduced degrees of invasiveness including laser, radiofrequency, high frequency focused ultrasound, cryolipolysis, and drug-based injection approaches. These costly techniques have focused on damaging adipocyte cell membranes, hydrolyzing triglycerides (TGs), or inducing apoptosis. Here, we present a simple, low-cost technique, termed electrochemical lipolysis (ECLL). During ECLL, saline is injected into the subcutaneous adipose tissue, followed by insertion of needle electrodes and application of an electrical potential. Electrolysis of saline creates localized pH gradients that drive adipocyte death and saponification of TGs. Using pH mapping, various optical imaging techniques, and biochemical assays, we demonstrate the ability of ECLL to induce acid and base injury, cell death, and the saponification of triglycerides in ex vivo porcine adipose tissue. We define ECLL's potential role as a minimally-invasive, ultra-low-cost technology for reducing and contouring adipose tissue, and present ECLL as a potential new application of an emerging electrochemical redox based treatment modality.

Air pollution involving particulate matter smaller than 2.5 μm in size (PM2.5) is the world's leading environmental risk factor contributing to mortality through cardiometabolic pathways. In this study, we modeled early life exposure using chow-fed C57BL/6J male mice that were exposed to real-world inhaled, concentrated PM2.5 (~10 times ambient levels/~60-120 μg/m3) or filtered air over a 14-week period. We investigated the effects of PM2.5 on phenotype, the transcriptome, and chromatin accessibility and compared these with the effects of a prototypical high-fat diet (HFD) as well as cessation of exposure on phenotype reversibility. Exposure to PM2.5 impaired glucose and insulin tolerance and reduced energy expenditure and 18FDG-PET uptake in brown adipose tissue. Multiple differentially expressed gene clusters in pathways involving metabolism and circadian rhythm were noted in insulin-responsive tissues. Although the magnitude of transcriptional change detected with PM2.5 exposure was lower than that observed with a HFD, the degree of alteration in chromatin accessibility after PM2.5 exposure was significant. The novel chromatin remodeler SMARCA5 (SWI/SNF complex) was regulated in response to PM2.5 exposure, the cessation of which was associated with a reversal of insulin resistance and restoration of chromatin accessibility and nucleosome positioning near transcription start sites, as well as a reversal of exposure-induced changes in the transcriptome, including SMARCA5. These changes indicate pliable epigenetic control mechanisms following cessation of exposure.

The aggregation and joint analysis of large numbers of exome sequences has recently made it possible to derive estimates of intolerance to loss-of-function (LoF) variation for human genes. Here, we demonstrate strong and widespread coupling between genic LoF intolerance and promoter CpG density across the human genome. Genes downstream of the most CpG-rich promoters (top 10% CpG density) have a 67.2% probability of being highly LoF intolerant, using the LOEUF metric from gnomAD. This is in contrast to 7.4% of genes downstream of the most CpG-poor (bottom 10% CpG density) promoters. Combining promoter CpG density with exonic and promoter conservation explains 33.4% of the variation in LOEUF, and the contribution of CpG density exceeds the individual contributions of exonic and promoter conservation. We leverage this to train a simple and easily interpretable predictive model that outperforms other existing predictors and allows us to classify 1,760 genes-which are currently unascertained in gnomAD-as highly LoF intolerant or not. These predictions have the potential to aid in the interpretation of novel variants in the clinical setting. Moreover, our results reveal that high CpG density is not merely a generic feature of human promoters but is preferentially encountered at the promoters of the most selectively constrained genes, calling into question the prevailing view that CpG islands are not subject to selection., (Copyright © 2020. Published by Elsevier Inc.)

Recent genome-wide association studies (GWAS) identified numerous schizophrenia (SZ) and Alzheimer's disease (AD) associated loci, most outside protein-coding regions and hypothesized to affect gene transcription. We used a massively parallel reporter assay to screen, 1,049 SZ and 30 AD variants in 64 and nine loci, respectively for allele differences in driving reporter gene expression. A library of synthetic oligonucleotides assaying each allele five times was transfected into K562 chronic myelogenous leukemia lymphoblasts and SK-SY5Y human neuroblastoma cells. One hundred forty eight variants showed allelic differences in K562 and 53 in SK-SY5Y cells, on average 2.6 variants per locus. Nine showed significant differences in both lines, a modest overlap reflecting different regulatory landscapes of these lines that also differ significantly in chromatin marks. Eight of nine were in the same direction. We observe no preference for risk alleles to increase or decrease expression. We find a positive correlation between the number of SNPs in linkage disequilibrium and the proportion of functional SNPs supporting combinatorial effects that may lead to haplotype selection. Our results prioritize future functional follow up of disease associated SNPs to determine the driver GWAS variant(s), at each locus and enhance our understanding of gene regulation dynamics., (© 2019 Wiley Periodicals, Inc.)

Background: The 3-dimensional (3D) conformation of chromatin inside the nucleus is integral to a variety of nuclear processes including transcriptional regulation, DNA replication, and DNA damage repair. Aberrations in 3D chromatin conformation have been implicated in developmental abnormalities and cancer. Despite the importance of 3D chromatin conformation to cellular function and human health, little is known about how 3D chromatin conformation varies in the human population, or whether DNA sequence variation between individuals influences 3D chromatin conformation., Results: To address these questions, we perform Hi-C on lymphoblastoid cell lines from 20 individuals. We identify thousands of regions across the genome where 3D chromatin conformation varies between individuals and find that this variation is often accompanied by variation in gene expression, histone modifications, and transcription factor binding. Moreover, we find that DNA sequence variation influences several features of 3D chromatin conformation including loop strength, contact insulation, contact directionality, and density of local cis contacts. We map hundreds of quantitative trait loci associated with 3D chromatin features and find evidence that some of these same variants are associated at modest levels with other molecular phenotypes as well as complex disease risk., Conclusion: Our results demonstrate that common DNA sequence variants can influence 3D chromatin conformation, pointing to a more pervasive role for 3D chromatin conformation in human phenotypic variation than previously recognized.

In the study of DNA methylation, genetic variation between species, strains or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here, we use whole-genome bisulfite sequencing data on two highly divergent mouse strains to study this problem. We show that alignment to personal genomes is necessary for valid methylation quantification. We introduce a method for including strain-specific CpGs in differential analysis, and show that this increases power. We apply our method to a human normal-cancer dataset, and show this improves accuracy and power, illustrating the broad applicability of our approach. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, while accounting for differences in the spatial occurrences of CpGs. Our results have implications for joint analysis of genetic variation and DNA methylation using bisulfite-converted DNA, and unlocks the use of personal genomes for addressing this question., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Kabuki syndrome 1 (KS1) is a Mendelian disorder of the epigenetic machinery caused by mutations in the gene encoding KMT2D, which methylates lysine 4 on histone H3 (H3K4). KS1 is characterized by intellectual disability, postnatal growth retardation, and distinct craniofacial dysmorphisms. A mouse model (Kmt2d+/βGeo) exhibits features of the human disorder and has provided insight into other phenotypes; however, the mechanistic basis of skeletal abnormalities and growth retardation remains elusive. Using high-resolution micro-CT, we show that Kmt2d+/βGeo mice have shortened long bones and ventral bowing of skulls. In vivo expansion of growth plates within skulls and long bones suggests disrupted endochondral ossification as a common disease mechanism. Stable chondrocyte cell lines harboring inactivating mutations in Kmt2d exhibit precocious differentiation, further supporting this mechanism. A known inducer of chondrogenesis, SOX9, and its targets show markedly increased expression in Kmt2d-/- chondrocytes. By transcriptome profiling, we identify Shox2 as a putative KMT2D target. We propose that decreased KMT2D-mediated H3K4me3 at Shox2 releases Sox9 inhibition and thereby leads to enhanced chondrogenesis, providing a potentially novel and plausible explanation for precocious chondrocyte differentiation. Our findings provide insight into the pathogenesis of growth retardation in KS1 and suggest therapeutic approaches for this and related disorders.

Chromatin modifiers act to coordinate gene expression changes critical to neuronal differentiation from neural stem/progenitor cells (NSPCs). Lysine-specific methyltransferase 2D (KMT2D) encodes a histone methyltransferase that promotes transcriptional activation and is frequently mutated in cancers and in the majority (>70%) of patients diagnosed with the congenital, multisystem intellectual disability disorder Kabuki syndrome 1 (KS1). Critical roles for KMT2D are established in various non-neural tissues, but the effects of KMT2D loss in brain cell development have not been described. We conducted parallel studies of proliferation, differentiation, transcription, and chromatin profiling in KMT2D-deficient human and mouse models to define KMT2D-regulated functions in neurodevelopmental contexts, including adult-born hippocampal NSPCs in vivo and in vitro. We report cell-autonomous defects in proliferation, cell cycle, and survival, accompanied by early NSPC maturation in several KMT2D-deficient model systems. Transcriptional suppression in KMT2D-deficient cells indicated strong perturbation of hypoxia-responsive metabolism pathways. Functional experiments confirmed abnormalities of cellular hypoxia responses in KMT2D-deficient neural cells and accelerated NSPC maturation in vivo. Together, our findings support a model in which loss of KMT2D function suppresses expression of oxygen-responsive gene programs important to neural progenitor maintenance, resulting in precocious neuronal differentiation in a mouse model of KS1.

Coding variants in epigenetic regulators are emerging as causes of neurological dysfunction and cancer. However, a comprehensive effort to identify disease candidates within the human epigenetic machinery (EM) has not been performed; it is unclear whether features exist that distinguish between variation-intolerant and variation-tolerant EM genes, and between EM genes associated with neurological dysfunction versus cancer. Here, we rigorously define 295 genes with a direct role in epigenetic regulation (writers, erasers, remodelers, readers). Systematic exploration of these genes reveals that although individual enzymatic functions are always mutually exclusive, readers often also exhibit enzymatic activity (dual-function EM genes). We find that the majority of EM genes are very intolerant to loss-of-function variation, even when compared to the dosage sensitive transcription factors, and we identify 102 novel EM disease candidates. We show that this variation intolerance is driven by the protein domains encoding the epigenetic function, suggesting that disease is caused by a perturbed chromatin state. We then describe a large subset of EM genes that are coexpressed within multiple tissues. This subset is almost exclusively populated by extremely variation-intolerant genes and shows enrichment for dual-function EM genes. It is also highly enriched for genes associated with neurological dysfunction, even when accounting for dosage sensitivity, but not for cancer-associated EM genes. Finally, we show that regulatory regions near epigenetic regulators are genetically important for common neurological traits. These findings prioritize novel disease candidate EM genes and suggest that this coexpression plays a functional role in normal neurological homeostasis., (© 2019 Boukas et al.; Published by Cold Spring Harbor Laboratory Press.)

Background: Massively parallel reporter assays (MPRAs) have emerged as a popular means for understanding noncoding variation in a variety of conditions. While a large number of experiments have been described in the literature, analysis typically uses ad-hoc methods. There has been little attention to comparing performance of methods across datasets., Results: We present the mpralm method which we show is calibrated and powerful, by analyzing its performance on multiple MPRA datasets. We show that it outperforms existing statistical methods for analysis of this data type, in the first comprehensive evaluation of statistical methods on several datasets. We investigate theoretical and real-data properties of barcode summarization methods and show an unappreciated impact of summarization method for some datasets. Finally, we use our model to conduct a power analysis for this assay and show substantial improvements in power by performing up to 6 replicates per condition, whereas sequencing depth has smaller impact; we recommend to always use at least 4 replicates. An R package is available from the Bioconductor project., Conclusions: Together, these results inform recommendations for differential analysis, general group comparisons, and power analysis and will help improve design and analysis of MPRA experiments.

Epigenetic modifications confer stable transcriptional patterns in the brain, and both normal and abnormal brain function involve specialized brain regions. We examined DNA methylation by whole-genome bisulfite sequencing in neuronal and non-neuronal populations from four brain regions (anterior cingulate gyrus, hippocampus, prefrontal cortex, and nucleus accumbens) as well as chromatin accessibility in the latter two. We find pronounced differences in both CpG and non-CpG methylation (CG-DMRs and CH-DMRs) only in neuronal cells across brain regions. Neuronal CH-DMRs were highly associated with differential gene expression, whereas CG-DMRs were consistent with chromatin accessibility and enriched for regulatory regions. These CG-DMRs comprise ~12 Mb of the genome that is highly enriched for genomic regions associated with heritability of neuropsychiatric traits including addictive behavior, schizophrenia, and neuroticism, thus suggesting a mechanistic link between pathology and differential neuron-specific epigenetic regulation in distinct brain regions.

Background: Meiosis is a specialized germ cell cycle that generates haploid gametes. In the initial stage of meiosis, meiotic prophase I (MPI), homologous chromosomes pair and recombine. Extensive changes in chromatin in MPI raise an important question concerning the contribution of epigenetic mechanisms such as DNA methylation to meiosis. Interestingly, previous studies concluded that in male mice, genome-wide DNA methylation patters are set in place prior to meiosis and remain constant subsequently. However, no prior studies examined DNA methylation during MPI in a systematic manner necessitating its further investigation., Results: In this study, we used genome-wide bisulfite sequencing to determine DNA methylation of adult mouse spermatocytes at all MPI substages, spermatogonia and haploid sperm. This analysis uncovered transient reduction of DNA methylation (TRDM) of spermatocyte genomes. The genome-wide scope of TRDM, its onset in the meiotic S phase and presence of hemimethylated DNA in MPI are all consistent with a DNA replication-dependent DNA demethylation. Following DNA replication, spermatocytes regain DNA methylation gradually but unevenly, suggesting that key MPI events occur in the context of hemimethylated genome. TRDM also uncovers the prior deficit of DNA methylation of LINE-1 retrotransposons in spermatogonia resulting in their full demethylation during TRDM and likely contributing to the observed mRNA and protein expression of some LINE-1 elements in early MPI., Conclusions: Our results suggest that contrary to the prevailing view, chromosomes exhibit dynamic changes in DNA methylation in MPI. We propose that TRDM facilitates meiotic prophase processes and gamete quality control.

The incidence of diet-induced metabolic disease has soared over the last half-century, despite national efforts to improve health through universal dietary recommendations. Studies comparing dietary patterns of populations with health outcomes have historically provided the basis for healthy diet recommendations. However, evidence that population-level diet responses are reliable indicators of responses across individuals is lacking. This study investigated how genetic differences influence health responses to several popular diets in mice, which are similar to humans in genetic composition and the propensity to develop metabolic disease, but enable precise genetic and environmental control. We designed four human-comparable mouse diets that are representative of those eaten by historical human populations. Across four genetically distinct inbred mouse strains, we compared the American diet's impact on metabolic health to three alternative diets (Mediterranean, Japanese, and Maasai/ketogenic). Furthermore, we investigated metabolomic and epigenetic alterations associated with diet response. Health effects of the diets were highly dependent on genetic background, demonstrating that individualized diet strategies improve health outcomes in mice. If similar genetic-dependent diet responses exist in humans, then a personalized, or "precision dietetics," approach to dietary recommendations may yield better health outcomes than the traditional one-size-fits-all approach., (Copyright © 2018 by the Genetics Society of America.)

Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multiomics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide the unrestricted multiple 'omics data for each cancer tissue in The Cancer Genome Atlas as ready-to-analyze MultiAssayExperiment objects and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable, and reproducible statistical analysis of multiomics data and enhances data science applications of multiple omics datasets. Cancer Res; 77(21); e39-42. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Every institution that is involved in research with animals is expected to have in place policies and procedures for the management of allegations of noncompliance with the Animal Welfare Act and the U.S. Public Health Service Policy on the Humane Care and Use of Laboratory Animals. We present here a model set of recommendations for institutional animal care and use committees and institutional officials to ensure appropriate consideration of allegations of noncompliance with federal Animal Welfare Act regulations that carry a significant risk or specific threat to animal welfare. This guidance has 3 overarching aims: 1 ) protecting the welfare of research animals; 2 ) according fair treatment and due process to an individual accused of noncompliance; and 3 ) ensuring compliance with federal regulations. Through this guidance, the present work seeks to advance the cause of scientific integrity, animal welfare, and the public trust while recognizing and supporting the critical importance of animal research for the betterment of the health of both humans and animals.-Hansen, B. C., Gografe, S., Pritt, S., Jen, K.-L. C., McWhirter, C. A., Barman, S. M., Comuzzie, A., Greene, M., McNulty, J. A., Michele, D. E., Moaddab, N., Nelson, R. J., Norris, K., Uray, K. D., Banks, R., Westlund, K. N., Yates, B. J., Silverman, J., Hansen, K. D., Redman, B. Ensuring due process in the IACUC and animal welfare setting: considerations in developing noncompliance policies and procedures for institutional animal care and use committees and institutional officials., (© FASEB.)