promoter-capture-hi-c-high-resolution-genome-wide-profiling-promoter

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the ...

Babraham Research Campus

Long-distance chromosomal interactions are emerging as a potential mechanism of gene expression control. In this issue, Apostolou and Thanos (2008) describe how viral infection elicits interchromosomal associations between the interferon-beta (IFN-beta) gene enhancer and DNA binding sites of the transcription factor NF-kappaB, resulting in the initiation of transcription and an antiviral response.

Interchromosomal huddle kickstarts antiviral defense.

Interchromosomal &#x76F8;&#x4E92;&#x4F5C;&#x7528;&#x5728;&#x9AD8;&#x7B49;&#x771F;&#x6838;&#x751F;&#x7269;&#x4E2D;&#x53D1;&#x73B0;&#x6307;&#x5411;&#x529F;&#x80FD;&#x57FA;&#x56E0;&#x7EC4;&#x7ED3;&#x6784;&#x53CA;&#x57FA;&#x56E0;&#x8868;&#x8FBE;&#xFF0C;&#x5177;&#x6709;&#x6311;&#x6218;&#x6027;&#x7684;&#x8F6C;&#x5F55;&#x4E3A;&#x4E00;&#x4E2A;&#x4E00;&#x7EF4;&#x7684;&#x8FDB;&#x7A0B;&#x89C6;&#x56FE;&#x4E4B;&#x95F4;&#x7684;&#x76F8;&#x4E92;&#x4F5C;&#x7528;&#x3002;&#x7136;&#x800C;&#xFF0C;interchromosomal &#x76F8;&#x4E92;&#x4F5C;&#x7528;&#x7684;&#x7A0B;&#x5EA6;&#x548C;&#x5176;&#x80CC;&#x540E;&#x7684;&#x673A;&#x5236;&#x662F;&#x672A;&#x77E5;&#x7684;&#x3002;&#x5728;&#x8FD9;&#x91CC;&#x6211;&#x4EEC;&#x4ECB;&#x7ECD;&#x7CFB;&#x7956;&#x7EC4;&#x7EC7;&#x4F7F;&#x7528;&#x9F20;&#x6807;&#x73E0;&#x86CB;&#x767D;&#x57FA;&#x56E0;&#x7684;&#x8F6C;&#x5F55;&#x4EA4;&#x4E92;&#x7684;&#x7B2C;&#x4E00;&#x4E2A;&#x5168;&#x57FA;&#x56E0;&#x7EC4;&#x5206;&#x6790;&#x3002;&#x6211;&#x4EEC;&#x7684;&#x7814;&#x7A76;&#x7ED3;&#x679C;&#x663E;&#x793A;&#x6D3B;&#x52A8;&#x73E0;&#x86CB;&#x767D;&#x57FA;&#x56E0;&#x5173;&#x8054;&#x6570;&#x767E;&#x4E2A;&#x5176;&#x4ED6;&#x8F6C;&#x5F55;&#x57FA;&#x56E0;&#xFF0C;&#x63ED;&#x793A;&#x5E7F;&#x6CDB;&#x548C;&#x4F18;&#x60E0;&#x5185;&#x548C; interchromosomal &#x8F6C;&#x5F55; interactomes&#x3002;&#x6211;&#x4EEC;&#x663E;&#x793A;&#x8F6C;&#x5F55;&#x56E0;&#x5B50; Klf1 &#x4ECB;&#x5BFC;&#x7684; Klf1 &#x57FA;&#x56E0;&#x5728;&#x4E3A;&#x6570;&#x6709;&#x9650;&#x7684;&#x4E13;&#x95E8;&#x7684;&#x8F6C;&#x5F55;&#x5DE5;&#x5382;&#x4F18;&#x60E0; co-associations&#x3002;&#x6211;&#x4EEC;&#x7684;&#x7ED3;&#x679C;&#x5EFA;&#x7ACB;&#x65B0;&#x57FA;&#x56E0;&#x8868;&#x8FBE;&#x8303;&#x5F0F;&#xFF0C;&#x8FD9;&#x610F;&#x5473;&#x7740;&#x5408;&#x4F5C;&#x521B;&#x5EFA;&#x4E13;&#x95E8;&#x4F18;&#x5316;&#x7684;&#x6709;&#x6548;&#x548C;&#x534F;&#x8C03;&#x7684;&#x8F6C;&#x5F55;&#x8C03;&#x63A7;&#x7684;&#x6838;&#x70ED;&#x70B9;&#x6D3B;&#x52A8;&#x5171;&#x7684;&#x57FA;&#x56E0;&#x548C;&#x5176;&#x76D1;&#x7BA1;&#x7684;&#x56E0;&#x7D20;&#x3002;

&#x4F18;&#x60E0;&#x534F;&#x4F1A;&#x4E4B;&#x95F4;&#x5171;&#x57FA;&#x56E0;&#x63ED;&#x793A;&#x7CFB;&#x7956;&#x7EC6;&#x80DE;&#x7684;&#x8F6C;&#x5F55; interactome&#x3002;

The discovery of interchromosomal interactions in higher eukaryotes points to a functional interplay between genome architecture and gene expression, challenging the view of transcription as a one-dimensional process. However, the extent of interchromosomal interactions and the underlying mechanisms are unknown. Here we present the first genome-wide analysis of transcriptional interactions using the mouse globin genes in erythroid tissues. Our results show that the active globin genes associate with hundreds of other transcribed genes, revealing extensive and preferential intra- and interchromosomal transcription interactomes. We show that the transcription factor Klf1 mediates preferential co-associations of Klf1-regulated genes at a limited number of specialized transcription factories. Our results establish a new gene expression paradigm, implying that active co-regulated genes and their regulatory factors cooperate to create specialized nuclear hot spots optimized for efficient and coordinated transcriptional control.

Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells.

La d&#xE9;couverte des interactions interchromosomiques des points eucaryotes sup&#xE9;rieurs &#xE0; une interaction fonctionnelle entre l&#x26;#39;architecture du g&#xE9;nome et l&#x26;#39;expression des g&#xE8;nes, contestant le point de vue de la transcription comme un processus unidimensionnel. Toutefois, l&#x26;#39;&#xE9;tendue des interactions interchromosomiques et les m&#xE9;canismes sous-jacents sont inconnus. Nous pr&#xE9;sentons ici le premier g&#xE9;nome &#xE0; l&#x26;#39;&#xE9;chelle d&#x26;#39;analyse des interactions transcriptionnelles en utilisant les g&#xE8;nes de globine de souris dans les tissus &#xE9;rythro&#xEF;des. Nos r&#xE9;sultats montrent que les g&#xE8;nes de globine actifs associer &#xE0; des centaines d&#x26;#39;autres g&#xE8;nes transcrits, r&#xE9;v&#xE9;lant de vastes et pr&#xE9;f&#xE9;rentiel interactomes transcription intra et interchromosomique. Nous montrons que le facteur de transcription Klf1 m&#xE9;diateur privil&#xE9;gi&#xE9; des associations de co-Klf1 g&#xE8;nes r&#xE9;gul&#xE9;s &#xE0; un nombre limit&#xE9; d&#x26;#39;usines de transcription sp&#xE9;cialis&#xE9;s. Nos r&#xE9;sultats &#xE9;tablissent un paradigme d&#x26;#39;expression du nouveau g&#xE8;ne, ce qui implique que actives g&#xE8;nes co-r&#xE9;gul&#xE9;s et leurs facteurs de r&#xE9;gulation coop&#xE8;rent pour cr&#xE9;er sp&#xE9;cialis&#xE9;s nucl&#xE9;aires points chauds optimis&#xE9;s pour le contr&#xF4;le transcriptionnel efficace et coordonn&#xE9;e.

Associations pr&#xE9;f&#xE9;rentiels entre g&#xE8;nes co-r&#xE9;gul&#xE9;s R&#xE9;v&#xE9;ler une Interactome transcriptionnelle dans les cellules &#xE9;rythro&#xEF;des

Die Entdeckung der interchromosomal Interaktionen in den h&ouml;heren Eukaryotes verweist auf eine funktionale Zusammenspiel zwischen Genom Architektur und Gen-Ausdruck, an die Ansicht der Transkription als eindimensionale Prozess. Das Ausma&szlig; der interchromosomal Interaktionen und die zugrunde liegenden Mechanismen sind jedoch unbekannt. Hier pr&auml;sentieren wir die erste genomweiten Analyse transkriptionelle Aktivit&auml;ten, die mit der Maus-Globin-Gene in Erythroid Geweben. Unsere Ergebnisse zeigen, dass die aktive Globin-Gene mit Hunderten anderer transkribierten Gene, aufschlussreich, umfangreiche und bevorzugte Intra- und interchromosomal Transkription Interactomes zuordnen. Wir zeigen, dass der Transkriptionsfaktor Klf1 bevorzugte Co-associations Klf1 regulierte Gene bei einer begrenzten Anzahl von spezialisierten Transkription Fabriken vermittelt. Unsere Ergebnisse schaffen ein neues Gen-Ausdruck-Paradigma, was bedeutet, dass aktive co-regulated Gene und ihrer regulatorischen Faktoren arbeiten zusammen, um spezialisierte nukleare Hotspots optimiert f&uuml;r effiziente und koordinierte transkriptionelle Steuerelement zu erstellen.

Bevorzugte Zuordnungen zwischen co-regulated Gene zeigen eine transkriptionelle Interaktom in Erythroid Zellen.

La scoperta delle interazioni interchromosomal negli eucarioti superiori punti ad un&#39;interazione funzionale tra espressione genica e architettura del genoma, sfidando la vista della trascrizione come un processo unidimensionale. Tuttavia, la misura delle interazioni interchromosomal e i meccanismi sottostanti sono sconosciuti. Qui vi presentiamo la prima analisi genome-wide di transcriptional interazioni utilizzando i geni della globina del mouse nei tessuti eritroidi. I nostri risultati mostrano che i geni della globina attivo associano con centinaia di altri geni trascritti, rivelando ampie e preferenziale intra - e trascrizione interchromosomal interactomes. Dimostriamo che il fattore di trascrizione Klf1 Media co-associations preferenziale dei geni regolati Klf1 presso un numero limitato di fabbriche specializzate trascrizione. I nostri risultati stabiliscono un nuovo paradigma di espressione genica, implicando che geni attivi co e loro regolamentazione fattori collaborano per creare specializzato nucleare hot spot ottimizzato per il controllo di transcriptional efficiente e coordinato.

Associazioni preferenziali tra geni co rivelano un interactome trascrizionale in cellule eritroidi.

&#x9AD8;&#x7B49;&#x771F;&#x6838;&#x751F;&#x7269;&#x306E;&#x67D3;&#x8272;&#x4F53;&#x9593;&#x76F8;&#x4E92;&#x4F5C;&#x7528;&#x306E;&#x767A;&#x898B;&#x306F;&#x3001;&#x4E00;&#x6B21;&#x5143;&#x306E;&#x30D7;&#x30ED;&#x30BB;&#x30B9;&#x3068;&#x3057;&#x3066;&#x8EE2;&#x5199;&#x306E;&#x30D3;&#x30E5;&#x30FC;&#x306B;&#x6311;&#x6226;&#x3057;&#x3001;&#x30B2;&#x30CE;&#x30E0;&#x306E;&#x30A2;&#x30FC;&#x30AD;&#x30C6;&#x30AF;&#x30C1;&#x30E3;&#x3068;&#x907A;&#x4F1D;&#x5B50;&#x767A;&#x73FE;&#x3068;&#x306E;&#x9593;&#x306E;&#x6A5F;&#x80FD;&#x7684;&#x76F8;&#x4E92;&#x4F5C;&#x7528;&#x3092;&#x6307;&#x3057;&#x3066;&#x3044;&#x307E;&#x3059;&#x3002;&#x3057;&#x304B;&#x3057;&#x3001;&#x67D3;&#x8272;&#x4F53;&#x9593;&#x76F8;&#x4E92;&#x4F5C;&#x7528;&#x306E;&#x57FA;&#x790E;&#x3068;&#x306A;&#x308B;&#x30E1;&#x30AB;&#x30CB;&#x30BA;&#x30E0;&#x306E;&#x7A0B;&#x5EA6;&#x306F;&#x4E0D;&#x660E;&#x3067;&#x3042;&#x308B;&#x3002;&#x3053;&#x3053;&#x3067;&#x306F;&#x3001;&#x8D64;&#x8840;&#x7403;&#x306E;&#x7D44;&#x7E54;&#x3067;&#x3001;&#x30DE;&#x30A6;&#x30B9;&#x306E;&#x30B0;&#x30ED;&#x30D3;&#x30F3;&#x907A;&#x4F1D;&#x5B50;&#x3092;&#x7528;&#x3044;&#x3066;&#x8EE2;&#x5199;&#x306E;&#x76F8;&#x4E92;&#x4F5C;&#x7528;&#x306E;&#x6700;&#x521D;&#x306E;&#x30B2;&#x30CE;&#x30E0;&#x30EF;&#x30A4;&#x30C9;&#x306A;&#x89E3;&#x6790;&#x3092;&#x63D0;&#x793A;&#x3057;&#x307E;&#x3059;&#x3002;&#x6211;&#x3005;&#x306E;&#x7D50;&#x679C;&#x306F;&#x3001;&#x30A2;&#x30AF;&#x30C6;&#x30A3;&#x30D6;&#x306A;&#x30B0;&#x30ED;&#x30D3;&#x30F3;&#x907A;&#x4F1D;&#x5B50;&#x304C;&#x5E83;&#x7BC4;&#x304B;&#x3064;&#x512A;&#x5148;&#x7684;&#x306A;&#x30A4;&#x30F3;&#x30C8;&#x30E9;&#x3068;&#x67D3;&#x8272;&#x4F53;&#x9593;&#x306E;&#x8EE2;&#x5199;interactomes&#x3092;&#x660E;&#x3089;&#x304B;&#x306B;&#x3057;&#x3001;&#x4ED6;&#x306E;&#x8EE2;&#x5199;&#x3055;&#x308C;&#x305F;&#x907A;&#x4F1D;&#x5B50;&#x306E;&#x6570;&#x767E;&#x306B;&#x95A2;&#x9023;&#x4ED8;&#x3051;&#x3089;&#x308C;&#x3066;&#x3044;&#x308B;&#x3053;&#x3068;&#x3092;&#x793A;&#x3057;&#x3066;&#x3044;&#x307E;&#x3059;&#x3002;&#x6211;&#x3005;&#x306F;&#x3001;&#x8EE2;&#x5199;&#x56E0;&#x5B50;&#x306E;&#x512A;&#x9047;Klf1&#x4EF2;&#x4ECB;&#x5C02;&#x9580;&#x306E;&#x8EE2;&#x5199;&#x5DE5;&#x5834;&#x306E;&#x9650;&#x3089;&#x308C;&#x305F;&#x6570;&#x3067;Klf1&#x8ABF;&#x7BC0;&#x907A;&#x4F1D;&#x5B50;&#x306E;&#x5171;&#x540C;&#x7D44;&#x5408;&#x3092;&#x793A;&#x3057;&#x3066;&#x3044;&#x307E;&#x3059;&#x3002;&#x65B0;&#x3057;&#x3044;&#x907A;&#x4F1D;&#x5B50;&#x767A;&#x73FE;&#x306E;&#x30D1;&#x30E9;&#x30C0;&#x30A4;&#x30E0;&#x3092;&#x78BA;&#x7ACB;&#x3059;&#x308B;&#x6211;&#x3005;&#x306E;&#x7D50;&#x679C;&#x306F;&#x3001;&#x305D;&#x306E;&#x30A2;&#x30AF;&#x30C6;&#x30A3;&#x30D6;&#x306A;&#x5171;&#x540C;&#x8ABF;&#x7BC0;&#x907A;&#x4F1D;&#x5B50;&#x3092;&#x610F;&#x5473;&#x3059;&#x308B;&#x3068;&#x305D;&#x306E;&#x8ABF;&#x7BC0;&#x56E0;&#x5B50;&#x306F;&#x3001;&#x52B9;&#x7387;&#x7684;&#x304B;&#x3064;&#x5354;&#x8ABF;&#x7684;&#x8EE2;&#x5199;&#x5236;&#x5FA1;&#x306E;&#x305F;&#x3081;&#x306B;&#x6700;&#x9069;&#x5316;&#x3055;&#x308C;&#x305F;&#x7279;&#x6B8A;&#x306A;&#x6838;&#x306E;&#x30DB;&#x30C3;&#x30C8;&#x30B9;&#x30DD;&#x30C3;&#x30C8;&#x3092;&#x4F5C;&#x6210;&#x3059;&#x308B;&#x305F;&#x3081;&#x306B;&#x5354;&#x529B;&#x3057;&#x3066;&#x3044;&#x307E;&#x3059;&#x3002;

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&#xB192;&#xC740; &#xC9C4;&#xD575;&#xC0DD;&#xBB3C;&#xC5D0;&#xC11C; interchromosomal &#xC0C1;&#xD638; &#xC791;&#xC6A9;&#xC758; &#xBC1C;&#xACAC; 1 &#xCC28;&#xC6D0; &#xACFC;&#xC815;&#xC73C;&#xB85C; &#xD544; &#xC0AC; &#xBCF4;&#xAE30; &#xB3C4;&#xC804; &#xAC8C;&#xB188; &#xAC74;&#xCD95;&#xACFC; &#xC9C4; &#xC2DD; &#xC0AC;&#xC774;&#xC758; &#xAE30;&#xB2A5;&#xC801; &#xC791;&#xC6A9;&#xC744; &#xAC00;&#xB9AC;&#xD0B5;&#xB2C8;&#xB2E4;. &#xADF8;&#xB7EC;&#xB098;, interchromosomal &#xC0C1;&#xD638; &#xC791;&#xC6A9;&#xC758; &#xC815;&#xB3C4; &#xBC0F; &#xAE30;&#xBCF8; &#xBA54;&#xCEE4;&#xB2C8;&#xC998;&#xC744; &#xC54C; &#xC218; &#xC788;&#xC2B5;&#xB2C8;&#xB2E4;. &#xC5EC;&#xAE30;&#xC5D0; &#xC6B0;&#xB9AC;&#xAC00; &#xD604;&#xC7AC; &#xB9C8;&#xC6B0;&#xC2A4; globin &#xC720;&#xC804;&#xC790; erythroid&#xC758; &#xC870;&#xC9C1;&#xC5D0;&#xC11C; &#xC0AC;&#xC6A9; &#xD558;&#xB294; transcriptional &#xC0C1;&#xD638; &#xC791;&#xC6A9;&#xC758; &#xCCAB; &#xBC88;&#xC9F8; &#xAC8C;&#xB188; &#xB113;&#xC740; &#xBD84;&#xC11D;. &#xC6B0;&#xB9AC;&#xC758; &#xACB0;&#xACFC; &#xD65C;&#xC131; globin &#xC720;&#xC804;&#xC790; &#xC218;&#xBC31; &#xAD11;&#xBC94;&#xC704; &#xD558; &#xACE0; &#xC6B0;&#xC120; &#xB0B4;&#xBD80;-&#xBC0F; interchromosomal &#xC804;&#xC0AC; interactomes &#xACF5;&#xAC1C; &#xBCA0;&#xB080;&#xB41C; &#xB2E4;&#xB978; &#xC720;&#xC804;&#xC790;&#xC640; &#xC5F0;&#xACB0;&#xC744; &#xBCF4;&#xC5EC; &#xC90D;&#xB2C8;&#xB2E4;. &#xC6B0;&#xB9AC;&#xB294; &#xC804;&#xC0AC; &#xC778;&#xC790; Klf1 Klf1 &#xADDC;&#xC81C; &#xC81C;&#xD55C; &#xB41C; &#xD2B9;&#xC218; &#xC804;&#xC0AC; &#xACF5;&#xC7A5;&#xC5D0;&#xC11C; &#xC720;&#xC804;&#xC790;&#xC758; &#xD2B9;&#xD61C; co-associations &#xC911;&#xC7AC;&#xB97C; &#xBCF4;&#xC5EC;&#xC90D;&#xB2C8;&#xB2E4;. &#xC6B0;&#xB9AC;&#xC758; &#xACB0;&#xACFC; &#xD65C;&#xC131; co-regulated &#xC720;&#xC804;&#xC790;&#xC640; &#xADF8;&#xB4E4;&#xC758; &#xADDC;&#xC81C; &#xC694;&#xC778; &#xB9CC;&#xB4DC;&#xB294; &#xD2B9;&#xC218; &#xD575; &#xD56B;&#xC2A4;&#xD31F; &#xD6A8;&#xC728;&#xC801;&#xC774; &#xACE0; &#xC870;&#xC815; transcriptional &#xCEE8;&#xD2B8;&#xB864;&#xC5D0; &#xCD5C;&#xC801;&#xD654; &#xB41C; &#xD611;&#xB825;&#xC744; &#xC554;&#xC2DC; &#xD558; &#xACE0; &#xC0C8;&#xB85C;&#xC6B4; &#xC720;&#xC804;&#xC790; &#xC2DD; &#xD328;&#xB7EC;&#xB2E4;&#xC784;&#xC744; &#xC124;&#xC815; &#xD569;&#xB2C8;&#xB2E4;.

Co-regulated &#xC720;&#xC804;&#xC790; &#xAC04;&#xC758; &#xD2B9;&#xD61C; &#xC5F0;&#xACB0; erythroid &#xC140;&#xC758; transcriptional &#xC704;&#xD558;&#xC5EC; &#xACF5;&#xAC1C;.

El descubrimiento de las interacciones interchromosomal en eucariotas superiores puntos a una interacci&#xF3;n funcional entre la arquitectura del genoma y la expresi&#xF3;n g&#xE9;nica, desafiando la vista de la transcripci&#xF3;n como un proceso unidimensional. Sin embargo, el alcance de las interacciones interchromosomal y los mecanismos subyacentes son desconocidos. Aqu&#xED; les presentamos el primer genoma completo an&#xE1;lisis de las interacciones con la transcripci&#xF3;n de los genes de globina de rat&#xF3;n en los tejidos eritroides. Nuestros resultados muestran que los genes de globina activos asociarse con cientos de otros genes transcritos, dejando al descubierto extensas y preferencial interactomes transcripci&#xF3;n intra e interchromosomal. Se demuestra que el factor de transcripci&#xF3;n Klf1 media preferencial compa&#xF1;eros de las asociaciones de Klf1 genes regulados en un n&#xFA;mero limitado de f&#xE1;bricas de transcripci&#xF3;n especializados. Nuestros resultados establecen un paradigma de la expresi&#xF3;n de genes nuevos, lo que implica que la cooperaci&#xF3;n activa de los genes regulados y sus factores reguladores cooperen para crear puntos nucleares calientes especializados optimizados para control de la transcripci&#xF3;n eficiente y coordinada.

Asociaciones preferenciales entre genes co-regulados descubre un interactoma transcripcional en c&#xE9;lulas eritroides

In addition to protein coding genes a substantial proportion of mammalian genomes are transcribed. However, most transcriptome studies investigate steady-state mRNA levels, ignoring a considerable fraction of the transcribed genome. In addition, steady-state mRNA levels are influenced by both transcriptional and posttranscriptional mechanisms, and thus do not provide a clear picture of transcriptional output. Here, using deep sequencing of nuclear RNAs (nucRNA-Seq) in parallel with chromatin immunoprecipitation sequencing (ChIP-Seq) of active RNA polymerase II, we compared the nuclear transcriptome of mouse anemic spleen erythroid cells with polymerase occupancy on a genome-wide scale. We demonstrate that unspliced transcripts quantified by nucRNA-seq correlate with primary transcript frequencies measured by RNA FISH, but differ from steady-state mRNA levels measured by poly(A)-enriched RNA-seq. Highly expressed protein coding genes showed good correlation between RNAPII occupancy and transcriptional output; however, genome-wide we observed a poor correlation between transcriptional output and RNAPII association. This poor correlation is due to intergenic regions associated with RNAPII which correspond with transcription factor bound regulatory regions and a group of stable, nuclear-retained long non-coding transcripts. In conclusion, sequencing the nuclear transcriptome provides an opportunity to investigate the transcriptional landscape in a given cell type through quantification of unspliced primary transcripts and the identification of nuclear-retained long non-coding RNAs.

Nuclear RNA sequencing of the mouse erythroid cell transcriptome.

The mammalian genome harbors up to one million regulatory elements often located at great distances from their target genes. Long-range elements control genes through physical contact with promoters and can be recognized by the presence of specific histone modifications and transcription factor binding. Linking regulatory elements to specific promoters genome-wide is currently impeded by the limited resolution of high-throughput chromatin interaction assays. Here we apply a sequence capture approach to enrich Hi-C libraries for >22,000 annotated mouse promoters to identify statistically significant, long-range interactions at restriction fragment resolution, assigning long-range interacting elements to their target genes genome-wide in embryonic stem cells and fetal liver cells. The distal sites contacting active genes are enriched in active histone modifications and transcription factor occupancy, whereas inactive genes contact distal sites with repressive histone marks, demonstrating the regulatory potential of the distal elements identified. Furthermore, we find that coregulated genes cluster nonrandomly in spatial interaction networks correlated with their biological function and expression level. Interestingly, we find the strongest gene clustering in ES cells between transcription factor genes that control key developmental processes in embryogenesis. The results provide the first genome-wide catalog linking gene promoters to their long-range interacting elements and highlight the complex spatial regulatory circuitry controlling mammalian gene expression.

The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements.

Chromosome conformation capture and various derivative methods such as 4C, 5C and Hi-C have emerged as standard tools to analyze the three-dimensional organization of the genome in the nucleus. These methods employ ligation of diluted cross-linked chromatin complexes, intended to favor proximity-dependent, intra-complex ligation. During development of single-cell Hi-C, we devised an alternative Hi-C protocol with ligation in preserved nuclei rather than in solution. Here we directly compare Hi-C methods employing in-nucleus ligation with the standard in-solution ligation.

Comparison of Hi-C results using in-solution versus in-nucleus ligation.

Comprehensive study of transcriptional control processes will be required to enhance our understanding of both normal and malignant hematopoiesis. Modern sequencing technologies have revolutionized our ability to generate genome-scale expression and histone modification profiles, transcription factor (TF)-binding maps, and also comprehensive chromatin-looping information. Many of these technologies, however, require large numbers of cells, and therefore cannot be applied to rare hematopoietic stem/progenitor cell (HSPC) populations. The stem cell factor-dependent multipotent progenitor cell line HPC-7 represents a well-recognized cell line model for HSPCs. Here we report genome-wide maps for 17 TFs, 3 histone modifications, DNase I hypersensitive sites, and high-resolution promoter-enhancer interactomes in HPC-7 cells. Integrated analysis of these complementary data sets revealed TF occupancy patterns of genomic regions involved in promoter-anchored loops. Moreover, preferential associations between pairs of TFs bound at either ends of chromatin loops led to the identification of 4 previously unrecognized protein-protein interactions between key blood stem cell regulators. All HPC-7 data sets are freely available both through standard repositories and a user-friendly Web interface. Together with previously generated genome-wide data sets, this study integrates HPC-7 data into a genomic resource on par with ENCODE tier 1 cell lines and, importantly, is the only current model with comprehensive genome-scale data that is relevant to HSPC biology. 

Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model.

Mammalian genomes are spatially organized into compartments, topologically associating domains (TADs), and loops to facilitate gene regulation and other chromosomal functions. How compartments, TADs, and loops are generated is unknown. It has been proposed that cohesin forms TADs and loops by extruding chromatin loops until it encounters CTCF, but direct evidence for this hypothesis is missing. Here, we show that cohesin suppresses compartments but is required for TADs and loops, that CTCF defines their boundaries, and that the cohesin unloading factor WAPL and its PDS5 binding partners control the length of loops. In the absence of WAPL and PDS5 proteins, cohesin forms extended loops, presumably by passing CTCF sites, accumulates in axial chromosomal positions (vermicelli), and condenses chromosomes. Unexpectedly, PDS5 proteins are also required for boundary function. These results show that cohesin has an essential genome-wide function in mediating long-range chromatin interactions and support the hypothesis that cohesin creates these by loop extrusion, until it is delayed by CTCF in a manner dependent on PDS5 proteins, or until it is released from DNA by WAPL.

Article	Year
Interchromosomal huddle kickstarts antiviral defense. Cell\| PubMed ID: 18614003	2008
Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells. Nature genetics\| PubMed ID: 20010836	2010
Nuclear RNA sequencing of the mouse erythroid cell transcriptome. PloS one\| PubMed ID: 23209567	2012
The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements. Genome research\| PubMed ID: 25752748	2015
Comparison of Hi-C results using in-solution versus in-nucleus ligation. Genome biology\| PubMed ID: 26306623	2015
Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model. Blood\| PubMed ID: 26809507	2016
Topologically associating domains and chromatin loops depend on cohesin and are regulated by CTCF, WAPL, and PDS5 proteins. The EMBO journal\| PubMed ID: 29217591	2017

Stefan Schoenfelder

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