Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine ...

Weill Cornell Medical College

We have developed an enhanced form of reduced representation bisulfite sequencing with extended genomic coverage, which resulted in greater capture of DNA methylation information of regions lying outside of traditional CpG islands. Applying this method to primary human bone marrow specimens from patients with Acute Myelogeneous Leukemia (AML), we demonstrated that genetically distinct AML subtypes display diametrically opposed DNA methylation patterns. As compared to normal controls, we observed widespread hypermethylation in IDH mutant AMLs, preferentially targeting promoter regions and CpG islands neighboring the transcription start sites of genes. In contrast, AMLs harboring translocations affecting the MLL gene displayed extensive loss of methylation of an almost mutually exclusive set of CpGs, which instead affected introns and distal intergenic CpG islands and shores. When analyzed in conjunction with gene expression profiles, it became apparent that these specific patterns of DNA methylation result in differing roles in gene expression regulation. However, despite this subtype-specific DNA methylation patterning, a much smaller set of CpG sites are consistently affected in both AML subtypes. Most CpG sites in this common core of aberrantly methylated CpGs were hypermethylated in both AML subtypes. Therefore, aberrant DNA methylation patterns in AML do not occur in a stereotypical manner but rather are highly specific and associated with specific driving genetic lesions.

Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia.

Zusammenfassung: DNA-Methylierung ist eine chemische Modifikation von Cytosin-Basen, die zentrale f&uuml;r die Genregulation, zellul&auml;re Spezifikation und Entwicklung von Krebs ist. Hier beschreiben wir ein R Paket, MethylKit, die rasch genomweiten Cytosin epigenetischen Profilen von Hochdurchsatz-Methylierung und Hydroxymethylation Sequenzierung Experimente analysiert. MethylKit umfasst Funktionen f&uuml;r clustering, Probe-Qualit&auml;t-Visualisierung, differenzielle Methylierung Analyse- und Anmerkung Features, damit automatisiert und vereinfacht viele der Schritte f&uuml;r anspruchsvolle statistisch signifikante Basen oder Regionen der DNA-Methylierung. Schlie&szlig;lich zeigen wir MethylKit auf Brust Krebs Daten, in denen wir statistisch signifikante Regionen der differenziellen Methylierung zu finden und Schichtung Tumor Untertypen. MethylKit ist unter http://code.google.com/p/methylkit verf&uuml;gbar.

MethylKit: ein umfassendes R-Paket f&uuml;r die Analyse von genomweiten DNA-Methylierungs-Profilen.

ABSTRACT: Metilazione del DNA &egrave; una modificazione chimica delle basi citosina che &egrave; cruciale per la regolazione dei geni, cellulare specifica e lo sviluppo del cancro. Qui, descriviamo un pacchetto R, methylKit, che analizza rapidamente profili epigenetici citosina genome-wide da esperimenti di sequenziamento hydroxymethylation e metilazione di alto-rendimento. methylKit include le funzioni di clustering, campione qualit&agrave; visualizzazione, differenziali di metilazione analisi e annotazione caratteristiche, cos&igrave; automatizzare e semplificare molti dei passaggi per elevate basi statisticamente significative o regioni di metilazione del DNA. Infine, noi dimostrare methylKit sui dati di cancro al seno, in cui troviamo regioni statisticamente significativi dei differenziali di metilazione e stratificare i sottotipi di tumore. methylKit &egrave; disponibile presso http://code.google.com/p/methylkit.

methylKit: un pacchetto completo di R per l&#39;analisi dei profili di metilazione del DNA genome-wide.

&#x6458;&#x8981;&#xFF1A; DNA &#x7532;&#x57FA;&#x5316;&#x662F;&#x57FA;&#x56E0;&#x8C03;&#x63A7;&#x3001; &#x8702;&#x7A9D;&#x89C4;&#x683C;&#x548C;&#x764C;&#x75C7;&#x53D1;&#x5C55;&#x7684;&#x5173;&#x952E;&#x662F;&#x5316;&#x5B66;&#x6539;&#x6027;&#x7684;&#x80DE;&#x5627;&#x5576;&#x57FA;&#x5730;&#x3002;&#x5728;&#x8FD9;&#x91CC;&#xFF0C;&#x6211;&#x4EEC;&#x63CF;&#x8FF0;&#x4E86;&#x4E00;&#x4E2A; R &#x5305;&#x4E2D;&#xFF0C;methylKit&#xFF0C;&#x5B83;&#x8FC5;&#x901F;&#x5206;&#x6790;&#x5168;&#x57FA;&#x56E0;&#x7EC4;&#x80DE;&#x5627;&#x5576;&#x540E;&#x751F;&#x914D;&#x7F6E;&#x6587;&#x4EF6;&#x4ECE;&#x9AD8;&#x541E;&#x5410;&#x91CF;&#x7532;&#x57FA;&#x5316;&#x548C;&#x7F9F;&#x7532;&#x57FA;&#x5316;&#x6D4B;&#x5E8F;&#x5B9E;&#x9A8C;&#x3002;methylKit &#x5305;&#x62EC;&#x805A;&#x7C7B;&#x3001; &#x6837;&#x54C1;&#x8D28;&#x91CF;&#x53EF;&#x89C6;&#x5316;&#x3001; &#x5DEE;&#x5F02;&#x7532;&#x57FA;&#x5316;&#x5206;&#x6790;&#x548C;&#x6CE8;&#x91CA;&#x7684;&#x529F;&#x80FD;&#xFF0C;&#x56E0;&#x6B64;&#x81EA;&#x52A8;&#x5316;&#x548C;&#x7B80;&#x5316;&#x8FA8;&#x8BC6;&#x7EDF;&#x8BA1;&#x5B66;&#x57FA;&#x5730;&#x6216;&#x533A;&#x57DF;&#x7684; DNA &#x7532;&#x57FA;&#x5316;&#x6B65;&#x9AA4;&#x4E2D;&#x7684;&#x8BB8;&#x591A;&#x529F;&#x80FD;&#x3002;&#x6700;&#x540E;&#xFF0C;&#x6211;&#x4EEC;&#x8BC1;&#x660E; methylKit &#x5173;&#x4E8E;&#x4E73;&#x817A;&#x764C;&#x7684;&#x6570;&#x636E;&#xFF0C;&#x6211;&#x4EEC;&#x53D1;&#x73B0;&#x7EDF;&#x8BA1;&#x4E0A;&#x7684;&#x663E;&#x8457;&#x5DEE;&#x5F02;&#x7532;&#x57FA;&#x5316;&#x7684;&#x533A;&#x57DF;&#x548C;&#x8D22;&#x6743;&#x80BF;&#x7624;&#x4E9A;&#x578B;&#x3002;&#x53EF;&#x5728; http://code.google.com/p/methylkit methylKit&#x3002;

methylKit&#xFF1A; &#x7814;&#x53D1;&#x4E00;&#x5957;&#x5168;&#x9762;&#x7684;&#x5168;&#x57FA;&#x56E0;&#x7EC4; DNA &#x7532;&#x57FA;&#x5316;&#x56FE;&#x8C31;&#x5206;&#x6790;&#x3002;

ABSTRACT: DNA methylation is a chemical modification of cytosine bases that is pivotal for gene regulation, cellular specification and cancer development. Here, we describe an R package, methylKit, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments. methylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statistically significant regions of differential methylation and stratify tumor subtypes. methylKit is available at http://code.google.com/p/methylkit.

methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles.

R&eacute;sum&eacute; : La m&eacute;thylation de l&#39;ADN est une modification chimique des bases cytosine qui est essentielle pour la r&eacute;gulation des g&egrave;nes, sp&eacute;cification cellulaire et le d&eacute;veloppement du cancer. Nous d&eacute;crivons ici un paquet de R, methylKit, qui analyse rapidement les profils &eacute;pig&eacute;n&eacute;tiques pang&eacute;nomique cytosine de m&eacute;thylation du haut d&eacute;bit et des exp&eacute;riences de s&eacute;quen&ccedil;age hydroxymethylation. methylKit inclut des fonctions pour la gestion de clusters, visualisation de qualit&eacute; d&#39;&eacute;chantillon, caract&eacute;ristiques analyse et l&#39;annotation de m&eacute;thylation diff&eacute;rentielle, ainsi automatiser et simplifier beaucoup des &eacute;tapes pour discerner les bases statistiquement significatives ou des r&eacute;gions de m&eacute;thylation de l&#39;ADN. Finalement, nous d&eacute;montrons methylKit sur les donn&eacute;es sur le cancer du sein, dans lequel nous trouvons des r&eacute;gions statistiquement significatives de la m&eacute;thylation diff&eacute;rentielle et stratifier des sous-types de la tumeur. methylKit est disponible &agrave; http://code.google.com/p/methylkit.

methylKit : un ensemble complet de R pour l&#39;analyse des profils de m&eacute;thylation de l&#39;ADN genome-wide.

&#x8981;&#x7D04;: DNA &#x306E;&#x30E1;&#x30C1;&#x30EB;&#x5316;&#x907A;&#x4F1D;&#x5B50;&#x8ABF;&#x7BC0;&#x3001;&#x7D30;&#x80DE;&#x4ED5;&#x69D8;&#x3068;&#x764C;&#x306E;&#x958B;&#x767A;&#x306E;&#x305F;&#x3081;&#x306B;&#x6975;&#x3081;&#x3066;&#x91CD;&#x8981;&#x3067;&#x3042;&#x308B;&#x3001;&#x30B7;&#x30C8;&#x30B7;&#x30F3;&#x5869;&#x57FA;&#x306E;&#x5316;&#x5B66;&#x4FEE;&#x98FE;&#x3067;&#x3059;&#x3002;&#x3053;&#x3053;&#x3067;&#x306F;&#x3001;R &#x30D1;&#x30C3;&#x30B1;&#x30FC;&#x30B8;&#x3092;&#x6025;&#x901F;&#x306B;&#x9AD8;&#x30B9;&#x30EB;&#x30FC;&#x30D7;&#x30C3;&#x30C8;&#x306E;&#x30E1;&#x30C1;&#x30EB;&#x5316;&#x3068; hydroxymethylation &#x30B7;&#x30FC;&#x30B1;&#x30F3;&#x30B9;&#x5B9F;&#x9A13;&#x304B;&#x3089;&#x30B2;&#x30CE;&#x30E0; &#x30B7;&#x30C8;&#x30B7;&#x30F3; &#x30A8;&#x30D4;&#x30B8;&#x30A7;&#x30CD;&#x30C6;&#x30A3;&#x30C3;&#x30AF;&#x306A;&#x30D7;&#x30ED;&#x30D5;&#x30A1;&#x30A4;&#x30EB;&#x3092;&#x5206;&#x6790;&#x3059;&#x308B; methylKit&#x3001;&#x306B;&#x3064;&#x3044;&#x3066;&#x8AAC;&#x660E;&#x3057;&#x307E;&#x3059;&#x3002;methylKit &#x306B;&#x306F;&#x30AF;&#x30E9;&#x30B9;&#x30BF; &#x30EA;&#x30F3;&#x30B0;&#x3001;&#x30B5;&#x30F3;&#x30D7;&#x30EB;&#x54C1;&#x8CEA;&#x53EF;&#x8996;&#x5316;&#x3001;&#x5DEE;&#x52D5;&#x30E1;&#x30C1;&#x30EB;&#x5316;&#x5206;&#x6790;&#x3068;&#x6CE8;&#x91C8;&#x6A5F;&#x80FD;&#x3001;&#x3057;&#x305F;&#x304C;&#x3063;&#x3066;&#x3092;&#x81EA;&#x52D5;&#x5316;&#x3057;&#x3001;&#x7D71;&#x8A08;&#x7684;&#x306B;&#x6709;&#x610F;&#x306A;&#x62E0;&#x70B9;&#x3084;&#x5730;&#x57DF;&#x306E; DNA &#x30E1;&#x30C1;&#x30EB;&#x5316;&#x306E;&#x80A5;&#x3048;&#x305F;&#x624B;&#x9806;&#x306E;&#x591A;&#x304F;&#x3092;&#x7C21;&#x7D20;&#x5316;&#x3059;&#x308B;&#x305F;&#x3081;&#x306E;&#x6A5F;&#x80FD;&#x304C;&#x542B;&#x307E;&#x308C;&#x3066;&#x3044;&#x307E;&#x3059;&#x3002;&#x6700;&#x5F8C;&#x306B;&#x3001;&#x6211;&#x3005; &#x306E;&#x5DEE;&#x52D5;&#x306E;&#x30E1;&#x30C1;&#x30EB;&#x5316;&#x306E;&#x7D71;&#x8A08;&#x7684;&#x306B;&#x6709;&#x610F;&#x306A;&#x9818;&#x57DF;&#x3092;&#x898B;&#x3064;&#x3051;&#x3001;&#x816B;&#x760D;&#x306E;&#x30B5;&#x30D6;&#x30BF;&#x30A4;&#x30D7;&#x3092;&#x5206;&#x985E;&#x306E;&#x4E73;&#x623F;&#x304C;&#x3093;&#x30C7;&#x30FC;&#x30BF;&#x306E; methylKit &#x3092;&#x793A;&#x3057;&#x3066;&#x3044;&#x307E;&#x3059;&#x3002;methylKit &#x306F;&#x3001;http://code.google.com/p/methylkit &#x3067;&#x5229;&#x7528;&#x53EF;&#x80FD;&#x3067;&#x3059;&#x3002;

methylKit: &#x30B2;&#x30CE;&#x30E0; DNA &#x30E1;&#x30C1;&#x30EB;&#x5316;&#x30D7;&#x30ED;&#x30D5;&#x30A1;&#x30A4;&#x30EB;&#x306E;&#x89E3;&#x6790;&#x306E;&#x305F;&#x3081;&#x306E;&#x5305;&#x62EC;&#x7684;&#x306A; R &#x30D1;&#x30C3;&#x30B1;&#x30FC;&#x30B8;&#x3002;

&#xAC1C;&#xC694;: DNA &#xBA54; &#xD2F8; &#xD654;&#xB294; &#xC720;&#xC804;&#xC790; &#xC870;&#xC808;, &#xC138;&#xD3EC; &#xC0AC;&#xC591; &#xBC0F; &#xC554; &#xAC1C;&#xBC1C;&#xC5D0; &#xB300; &#xD55C; &#xC911;&#xCD94;&#xC801;&#xC778; &#xC2DC; &#xAE30;&#xC9C0;&#xC758; &#xD654;&#xD559; &#xC218;&#xC815; &#xC774;&#xB2E4;. &#xC5EC;&#xAE30;, &#xC6B0;&#xB9AC;&#xB294; &#xAE09;&#xC18D; &#xD558; &#xAC8C; &#xB192;&#xC740; &#xCC98;&#xB9AC;&#xB7C9; &#xBA54; &#xD2F8; &#xD654;&#xC640; hydroxymethylation &#xC2DC;&#xD000;&#xC2F1; &#xC2E4;&#xD5D8;&#xC5D0;&#xC11C; &#xAC8C;&#xB188; &#xB113;&#xC740; &#xC2DC; epigenetic &#xD504;&#xB85C; &#xD30C;&#xC77C;&#xC744; &#xBD84;&#xC11D; &#xD558;&#xB294; methylKit R &#xD328;&#xD0A4;&#xC9C0;&#xB97C; &#xC124;&#xBA85; &#xD569;&#xB2C8;&#xB2E4;. methylKit &#xD074;&#xB7EC;&#xC2A4;&#xD130;&#xB9C1;, &#xC0D8;&#xD50C; &#xD488;&#xC9C8; &#xC2DC;&#xAC01;&#xD654;, &#xCC28;&#xB3D9; &#xBA54; &#xD2F8; &#xD654; &#xBD84;&#xC11D; &#xBC0F; &#xC8FC;&#xC11D; &#xAE30;&#xB2A5;, &#xB530;&#xB77C;&#xC11C; &#xC790;&#xB3D9;&#xD654; &#xD558; &#xACE0; &#xB9CE;&#xC740; &#xD1B5;&#xACC4;&#xC801;&#xC73C;&#xB85C; &#xC911;&#xC694; &#xD55C; &#xAE30;&#xC9C0; &#xB610;&#xB294; DNA &#xBA54; &#xD2F8; &#xD654;&#xC758; &#xC601;&#xC5ED;&#xC744; &#xBD84;&#xBCC4; &#xD558;&#xB294; &#xB2E8;&#xACC4;&#xB97C; &#xB2E8;&#xC21C;&#xD654; &#xD558;&#xB294; &#xAE30;&#xB2A5;&#xC744; &#xD3EC;&#xD568; &#xD569;&#xB2C8;&#xB2E4;. &#xB9C8;&#xC9C0;&#xB9C9;&#xC73C;&#xB85C;, &#xC6B0;&#xB9AC;&#xB294; &#xC6B0;&#xB9AC;&#xAC00; &#xCC28;&#xB3D9; &#xBA54; &#xD2F8;&#xC758; &#xD1B5;&#xACC4;&#xC801;&#xC73C;&#xB85C; &#xC911;&#xC694; &#xD55C; &#xC601;&#xC5ED;&#xC744; &#xBC1C;&#xACAC; &#xBC0F; &#xC885;&#xC591; &#xD558;&#xC704; &#xCDA9; &#xC720; &#xBC29; &#xC554; &#xB370;&#xC774;&#xD130;&#xC5D0; Methylkit&#xC744; &#xBCF4;&#xC5EC; &#xC90D;&#xB2C8;&#xB2E4;. Methylkit&#xC740; http://code.google.com/p/methylkit&#xC5D0;&#xC11C; &#xAC00;&#xB2A5; &#xD569;&#xB2C8;&#xB2E4;.

methylKit: &#xAC8C;&#xB188; &#xC804;&#xCCB4; DNA &#xBA54; &#xD2F8; &#xD654; &#xD504;&#xB85C;&#xD544; &#xBD84;&#xC11D;&#xC5D0; &#xB300; &#xD55C; &#xD3EC;&#xAD04;&#xC801;&#xC778; R &#xD328;&#xD0A4;&#xC9C0;.

Resumen: La metilaci&oacute;n del ADN es una modificaci&oacute;n qu&iacute;mica de bases citosina que es fundamental para la regulaci&oacute;n g&eacute;nica, la especificaci&oacute;n celular y el desarrollo de c&aacute;ncer. Aqu&iacute;, describimos un paquete R, methylKit, que r&aacute;pidamente analiza perfiles epigen&eacute;ticos genoma citosina de metilaci&oacute;n de alto rendimiento y experimentos de la secuencia de hydroxymethylation. methylKit incluye funciones para clustering, visualizaci&oacute;n de calidad de muestra, caracter&iacute;sticas an&aacute;lisis y anotaci&oacute;n de metilaci&oacute;n diferencial, as&iacute; automatizar y simplificar muchas de las medidas para los m&aacute;s exigentes bases estad&iacute;sticamente significativas o regiones de metilaci&oacute;n del ADN. Finalmente, demostramos methylKit en datos de c&aacute;ncer de mama, en el cual encontramos regiones estad&iacute;sticamente significativas de la metilaci&oacute;n diferencial y estratificar subtipos del tumor. methylKit est&aacute; disponible en http://code.google.com/p/methylkit.

methylKit: un paquete integral de R para el an&aacute;lisis de perfiles de metilaci&oacute;n de ADN gen&oacute;mico.

Recently discovered recurrent somatic mutations in the key metabolic enzymes IDH1 and IDH2 produce the aberrant oncometabolite 2-HG and contribute to malignant transformation of hematopoietic and glial cells. Two recent reports in Science describe the first IDH1 and IDH2 mutant-specific small-molecule inhibitors, which induce cell differentiation of myeloid leukemias and malignant gliomas.

Differentiation therapy for IDH1/2 mutant malignancies.

DNA methylation profiling reveals important differentially methylated regions (DMRs) of the genome that are altered during development or that are perturbed by disease. To date, few programs exist for regional analysis of enriched or whole-genome bisulfate conversion sequencing data, even though such data are increasingly common. Here, we describe an open-source, optimized method for determining empirically based DMRs (eDMR) from high-throughput sequence data that is applicable to enriched whole-genome methylation profiling datasets, as well as other globally enriched epigenetic modification data.

Francine E. Garrett-Bakelman

Department of Medicine

Weill Cornell Medical College

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Francine E. Garrett-Bakelman

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Medicine

Weill Cornell Medical College

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Department of Medicine