7648a54276c90c08ff73dc555fe051f92dd4f57d gperez2 Sun Mar 8 18:20:00 2026 -0700 Updating the Methylation Atlas summary subtracks section and adding a Cell/Tissue Type section, #36826 diff --git src/hg/makeDb/trackDb/human/methylationAtlas.html src/hg/makeDb/trackDb/human/methylationAtlas.html index de38a0ac535..4f318dc08c4 100755 --- src/hg/makeDb/trackDb/human/methylationAtlas.html +++ src/hg/makeDb/trackDb/human/methylationAtlas.html @@ -1,175 +1,191 @@ <h2>Description</h2> <p> The <b>Human Methylation Atlas</b> tracks display genome-wide DNA methylation profiles from deep whole-genome bisulfite sequencing (WGBS) of <b>39 primary human cell types</b> sorted from 205 healthy tissue samples. This comprehensive resource enables fragment-level analysis across thousands of unique markers, providing a detailed reference for cell-type-specific methylation patterns. </p> <b>Human Methylation Atlas Summary</b> consists of the following subtracks: <ul> <li><b>All unmethylated regions</b> track displays a comprehensive catalogue of unmethylated genomic regions identified independently for each of the 39 cell types in the atlas using a fragment-level analysis, retaining regions where at least 85% of sequenced DNA fragments covering four or more CpGs are unmethylated.</li><br> <li><b>Putative enhancers from unmethylated regions</b> track displays a genome-wide catalogue of - putative transcriptional enhancers for each of the 39 cell types, derived from regions - where at least 85% of sequenced DNA fragments are unmethylated and that overlap H3K27ac - but not H3K4me3 ChIP-seq peaks, distinguishing distal enhancer elements from active - promoters.</li><br> + putative transcriptional enhancers derived from regions where at least 85% of sequenced + DNA fragments are unmethylated, and that overlap H3K27ac but not H3K4me3 ChIP-seq peaks, + distinguishing distal enhancer elements from active promoters. This track covers 32 of + the 39 cell types, as H3K27ac ChIP-seq data were unavailable for Adipocytes, Bone + Osteoblasts, Erythrocyte Progenitors, Fallopian Epithelium, Gallbladder, Ovary Epithelium, + and Smooth Muscle. </li><br> <li><b>Top 250 unmethylated regions specific to each cell type</b> track displays the top 250 genomic regions most specifically unmethylated in each of the 39 cell types, identified - using a one-versus-all comparison approach.</li> + using a one-versus-all comparison approach. Some regions are shared across closely related + cell types (for example, Neuron:Oligodend or Colon-Ep:Gastric-Ep:Small-Int-Ep), + indicating they are unmethylated across those cell types but methylated in all others in + the atlas.</li> </ul> <p> Unsupervised clustering of these methylomes recapitulates key elements of tissue ontogeny and developmental lineage relationships. </p> <h2>Display Conventions and Configuration</h2> <h3>Track Colors</h3> <p> Tracks are colored by tissue/cell type category as follows: </p> <table border="1" cellpadding="4" cellspacing="0"> <tr><th>Color</th><th>Cell Type(s)</th></tr> <tr><td style="background-color:rgb(138,43,226);width:30px;"> </td><td>Neurons</td></tr> <tr><td style="background-color:rgb(148,103,189);width:30px;"> </td><td>Oligodendrocytes</td></tr> <tr><td style="background-color:rgb(72,61,139);width:30px;"> </td><td>Thyroid Epithelium</td></tr> <tr><td style="background-color:rgb(153,50,204);width:30px;"> </td><td>Prostate Epithelium</td></tr> <tr><td style="background-color:rgb(186,85,211);width:30px;"> </td><td>Bladder Epithelium</td></tr> <tr><td style="background-color:rgb(220,20,60);width:30px;"> </td><td>Heart Cardiomyocytes</td></tr> <tr><td style="background-color:rgb(205,92,92);width:30px;"> </td><td>Smooth Muscle</td></tr> <tr><td style="background-color:rgb(178,34,34);width:30px;"> </td><td>Heart Fibroblasts</td></tr> <tr><td style="background-color:rgb(139,0,0);width:30px;"> </td><td>Skeletal Muscle</td></tr> <tr><td style="background-color:rgb(205,51,51);width:30px;"> </td><td>Erythrocyte Progenitors</td></tr> <tr><td style="background-color:rgb(255,99,71);width:30px;"> </td><td>Blood Granulocytes</td></tr> <tr><td style="background-color:rgb(244,164,96);width:30px;"> </td><td>Blood Monocytes/Macrophages</td></tr> <tr><td style="background-color:rgb(255,140,0);width:30px;"> </td><td>Blood T Cells</td></tr> <tr><td style="background-color:rgb(255,165,0);width:30px;"> </td><td>Blood B Cells</td></tr> <tr><td style="background-color:rgb(255,127,80);width:30px;"> </td><td>Blood NK Cells</td></tr> <tr><td style="background-color:rgb(255,215,0);width:30px;"> </td><td>Pancreas Beta Cells</td></tr> <tr><td style="background-color:rgb(218,165,32);width:30px;"> </td><td>Pancreas Alpha Cells</td></tr> <tr><td style="background-color:rgb(240,230,140);width:30px;"> </td><td>Pancreas Delta Cells</td></tr> <tr><td style="background-color:rgb(238,232,170);width:30px;"> </td><td>Pancreas Duct Cells</td></tr> <tr><td style="background-color:rgb(189,183,107);width:30px;"> </td><td>Pancreas Acinar Cells</td></tr> <tr><td style="background-color:rgb(34,139,34);width:30px;"> </td><td>Colon Epithelium</td></tr> <tr><td style="background-color:rgb(85,107,47);width:30px;"> </td><td>Colon Fibroblasts</td></tr> <tr><td style="background-color:rgb(46,139,87);width:30px;"> </td><td>Small Intestine Epithelium</td></tr> <tr><td style="background-color:rgb(60,179,113);width:30px;"> </td><td>Gastric Epithelium</td></tr> <tr><td style="background-color:rgb(107,142,35);width:30px;"> </td><td>Gallbladder</td></tr> <tr><td style="background-color:rgb(139,69,19);width:30px;"> </td><td>Liver Hepatocytes</td></tr> <tr><td style="background-color:rgb(100,149,237);width:30px;"> </td><td>Lung Bronchus Epithelium</td></tr> <tr><td style="background-color:rgb(135,206,250);width:30px;"> </td><td>Lung Alveolar Epithelium</td></tr> <tr><td style="background-color:rgb(255,140,105);width:30px;"> </td><td>Kidney Epithelium</td></tr> <tr><td style="background-color:rgb(255,105,180);width:30px;"> </td><td>Endothelial</td></tr> <tr><td style="background-color:rgb(219,112,147);width:30px;"> </td><td>Breast Basal Epithelium</td></tr> <tr><td style="background-color:rgb(255,182,193);width:30px;"> </td><td>Breast Luminal Epithelium</td></tr> <tr><td style="background-color:rgb(218,112,214);width:30px;"> </td><td>Fallopian Epithelium</td></tr> <tr><td style="background-color:rgb(221,160,221);width:30px;"> </td><td>Ovary Epithelium</td></tr> <tr><td style="background-color:rgb(210,180,140);width:30px;"> </td><td>Adipocytes</td></tr> <tr><td style="background-color:rgb(222,184,135);width:30px;"> </td><td>Epidermal Keratinocytes</td></tr> <tr><td style="background-color:rgb(245,222,179);width:30px;"> </td><td>Dermal Fibroblasts</td></tr> <tr><td style="background-color:rgb(188,143,143);width:30px;"> </td><td>Bone Osteoblasts</td></tr> <tr><td style="background-color:rgb(0,206,209);width:30px;"> </td><td>Head Neck Epithelium</td></tr> </table> +<p> +Items in these tracks can be filtered by: +</p> +<ul> + <li><b>Cell/Tissue Type</b> - The cell or tissue type associated with each region. + Filter values include the 39 cell types for the <b>All Unmethylated Regions</b> track, + 32 cell types for the <b>Putative Enhancers</b> track, and 39 cell types plus combined + cell type groups for the <b>Top 250 Unmethylated Regions</b> track. The default is no + filtering.</li> +</ul> + <h2>Methods</h2> <h3>Sample Collection and Sequencing</h3> <p> Primary human cells were isolated from freshly dissociated adult healthy tissues using fluorescence-activated cell sorting (FACS), yielding high-purity preparations across major cell lineages. A total of 205 samples representing 77 primary cell types were collected from 137 consenting donors and merged into 39 cell type groups based on methylation similarity. Average sample purity exceeded 90% as determined by flow cytometry, gene expression, and DNA methylation analysis. Some cell types showed lower purity, including colon fibroblasts (78%), smooth muscle cells (82%), endothelial cells (86%), and adipocytes (87%). </p> <p> Several cell types are absent from the atlas, typically due to limited availability of primary material. These include osteoblasts, cholangiocytes, cells of the adrenal gland, urethral epithelium, and haematopoietic stem cells. Subpopulations of interest, such as distinct neuronal or lymphocyte subtypes, were also not resolved separately. </p> <p> Whole-genome bisulfite sequencing was performed using 150 bp paired-end reads at an average sequencing depth of 30× (minimum 6.62×). Libraries were prepared using the Accel-NGS Methyl-Seq DNA library preparation kit and sequenced on the Illumina NovaSeq 6000 platform. </p> <h3>Processing and Analysis</h3> <p> Reads were mapped to the human genome (hg38) using bwa-meth, deduplicated with Sambamba, and processed into per-CpG methylation calls. The genome was segmented into 7.1 million non-overlapping methylation blocks using a multi-channel dynamic programming algorithm that identifies regions of homogeneous methylation across samples. </p> <p> Cell-type-specific differentially methylated regions were identified using a one-versus-all comparison approach. Regions uniquely unmethylated in specific cell types were found to be enriched for transcriptional enhancers and tissue-specific transcription factor binding motifs. </p> <p> Data processing was performed using <a href="https://github.com/nloyfer/wgbs_tools" target="_blank">wgbstools</a>, an open-source computational suite for DNA methylation sequencing data representation, visualization, and analysis. </p> <h2>Data Access</h2> <p> The raw data for these tracks can be explored interactively using the <a href="../cgi-bin/hgTables">Table Browser</a> or the <a href="../cgi-bin/hgIntegrator">Data Integrator</a>. For automated analysis, the data may also be queried from our <a href="../goldenPath/help/api.html">REST API</a>. </p> <p> The complete dataset, including all WGBS data files and processed methylation calls, is available from GEO accession <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE186458" target="_blank">GSE186458</a>. </p> <p> For questions regarding the data, please contact <a href="mailto:tommy.kaplan@mail.huji.ac.il">Prof. Tommy Kaplan</a> at the Hebrew University of Jerusalem. </p> <h2>Credits</h2> <p> Data generation and analysis were performed at the Hebrew University of Jerusalem by the Dor, Kaplan, and Glaser laboratories and collaborators. Sample collection involved collaboration with Hadassah Medical Center, Oregon Health & Science University, Karolinska Institute, and University of Alberta. </p> <h2>References</h2> <p> Loyfer N, Magenheim J, Peretz A, Cann G, Bredno J, Klochendler A, Fox-Fisher I, Shabi-Porat S, Hecht M, Pelet T <em>et al</em>. <a href="https://www.nature.com/articles/s41586-022-05580-6" target="_blank"> A DNA methylation atlas of normal human cell types</a>. <em>Nature</em>. 2023 Jan;613(7943):355-364. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36599988" target="_blank">36599988</a> </p> <p> Loyfer N, Rosenski J, Kaplan T. <a href="https://doi.org/10.26508/lsa.202503514" target="_blank"> wgbstools: a computational suite for DNA methylation sequencing data analysis</a>. <em>Life Sci Alliance</em>. 2026 Apr;9(4):e202503514. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/41611450" target="_blank">41611450</a> </p>