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      DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse

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          SUMMARY

          We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.

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          In brief

          Infinium arrays are a cost-effective high-throughput DNA methylation profiling tool for human samples. Zhou et al. have developed an equivalent array for the mouse and used it to generate a DNA methylome atlas representing the diversity of DNA methylation biology in development, aging, and disease in this important model organism.

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            BEDTools: a flexible suite of utilities for comparing genomic features

            Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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              Regularization Paths for Generalized Linear Models via Coordinate Descent

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                Author and article information

                Journal
                9918284260106676
                51106
                Cell Genom
                Cell Genom
                Cell genomics
                2666-979X
                16 July 2022
                13 July 2022
                22 July 2022
                : 2
                : 7
                : 100144
                Affiliations
                [1 ]Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
                [2 ]Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [3 ]Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
                [4 ]Illumina, Inc., Bioinformatics and Instrument Software Department, San Diego, CA 92122, USA
                [5 ]Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI 49503, USA
                [6 ]Genomics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
                [7 ]Vivarium and Transgenics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
                [8 ]Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
                [9 ]FOXO Technologies Inc., Minneapolis, MN 55402, USA
                [10 ]Present address: Department of Biological Sciences, Olivet Nazarene University, Bourbonnais, IL 60914, USA
                [11 ]Lead contact
                Author notes

                AUTHOR CONTRIBUTIONS

                Conceptualization, W.Z., T.H., B.B., R.P., B.H.C., H.S., and P.W.L.; data curation, W.Z., T.H., B.B., K.K.F., J.A.P., P.E.S., M.S.B., H.S., and P.W.L.; formal analysis, W.Z., T.H., B.B., W.I., S.M.L., E.J.M., W.D., H.S., and P.W.L.; funding acquisition, W.Z., B.B., R.P., B.H.C., H.S., and P.W.L.; investigation, O.M., K.K.F., A.V., J.M.K., L.K., A.K.W., P.A.J., C.M.K., and M.A.; methodology, W.Z., T.H., B.B., P.A.J., C.M.K., M.A., H.S., and P.W.L.; project administration, W.Z., B.B., K.K.F., C.M.K., M.A., R.P., B.H.C., H.S., and P.W.L.; resources, K.-H.L., M.K., N.J.S., B.E., and N.A.V.S.; software, W.Z., T.H., B.B., W.I., S.M.L., E.J.M., W.D., and H.S.; visualization, W.Z., T.H., W.I., S.M.L., H.S., and P.W.L.; writing – original draft, W.Z., T.H., H.S., and P.W.L.; writing - review & editing, W.Z., T.H., M.K., J.A.P., M.S.B., A.K.W., P.A.J., C.M.K., R.P., B.H.C., H.S., and P.W.L.; supervision, W.Z., H.S., and P.W.L.

                Article
                NIHMS1823589
                10.1016/j.xgen.2022.100144
                9306256
                35873672
                a15082dc-4cda-4d8a-ad40-8132418ed468

                This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/).

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