a120735fd0e3914968ffd26170946de5ab960135 gperez2 Sat Mar 7 16:28:02 2026 -0800 Reorganizing trackDb, updating name for files, updating shortLabels, updating the Human Methylation Atlas Summary and Human Methylation Atlas Signals track description pages, refs #36826 diff --git src/hg/makeDb/trackDb/human/methylationAtlas.html src/hg/makeDb/trackDb/human/methylationAtlas.html new file mode 100755 index 00000000000..de38a0ac535 --- /dev/null +++ src/hg/makeDb/trackDb/human/methylationAtlas.html @@ -0,0 +1,175 @@ +<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> + <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> +</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> + +<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> +