EHA Library - The official digital education library of European Hematology Association (EHA)

INTEGRATIVE ANALYSIS OF THE GENOME, EPIGENOME, TRANSCRIPTOME AND THREE-DIMENSIONAL CHROMATIN STRUCTURE IN CHRONIC LYMPHOCYTIC LEUKEMIA
Author(s): ,
Renée Beekman
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
,
Núria Russiñol
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
,
Vicente Chapaprieta
Affiliations:
Departamento de Fundamentos Clínicos,UB,Barcelona,Spain
,
Núria Verdaguer-Dot
Affiliations:
Departamento de Fundamentos Clínicos,UB,Barcelona,Spain
,
Roser Vilarrasa-Blasi
Affiliations:
Departamento de Fundamentos Clínicos,UB,Barcelona,Spain
,
Guillem Clot
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
,
Martí Duran-Ferrer
Affiliations:
Departamento de Fundamentos Clínicos,UB,Barcelona,Spain
,
Marta Kulis
Affiliations:
Departamento de Fundamentos Clínicos,UB,Barcelona,Spain
,
Giancarlo Castellano
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
,
Biola M. Javierre
Affiliations:
Nuclear Dynamics,Babraham Institute,Cambridge,United Kingdom
,
Steven W. Wingett
Affiliations:
Nuclear Dynamics,Babraham Institute,Cambridge,United Kingdom
,
Julie Blanc
Affiliations:
Sequencing Unit,CNAG-CRG, CRG, BIST and UPF,Barcelona,Spain
,
François Serra
Affiliations:
Structural Genomics,CNAG-CRG, CRG, BIST and UPF,Barcelona,Spain
,
Angelika Merkel
Affiliations:
Bioinformatics Development and Statistical Genomics,CNAG-CRG, CRG, BIST and UPF,Barcelona,Spain
,
Sebastian Ullrich
Affiliations:
Computational Biology of RNA Processing,CRG,Barcelona,Spain
,
Anna Vlasova
Affiliations:
Computational Biology of RNA Processing,CRG,Barcelona,Spain
,
Emilio Palumbo
Affiliations:
Computational Biology of RNA Processing,CRG,Barcelona,Spain
,
Magda Pinyol
Affiliations:
Unidad de Genómica,IDIBAPS,Barcelona,Spain
,
Sílvia Beà
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
,
Romina Royo
Affiliations:
Joint Program on Computational Biology,BSC,Barcelona,Spain
,
Montserrat Puiggros
Affiliations:
Joint Program on Computational Biology,BSC,Barcelona,Spain
,
Avik Datta
Affiliations:
EMBL-EBI,EMBL-EBI,Hinxton,United Kingdom
,
Paul Flicek
Affiliations:
EMBL-EBI,EMBL-EBI,Hinxton,United Kingdom
,
Ernesto Lowy
Affiliations:
EMBL-EBI,EMBL-EBI,Hinxton,United Kingdom
,
Myrto Kostadima
Affiliations:
EMBL-EBI,EMBL-EBI,Hinxton,United Kingdom
,
Laura Clarke
Affiliations:
EMBL-EBI,EMBL-EBI,Hinxton,United Kingdom
,
Julio Delgado
Affiliations:
Servicio de Hematología,IDIBAPS,Barcelona,Spain
,
Armando López-Guillermo
Affiliations:
Servicio de Hematología,IDIBAPS,Barcelona,Spain
,
Xose S. Puente
Affiliations:
Departamento de Bioquímica y Biología Molecular,IUOPA,Oviedo,Spain
,
Carlos López-Otin
Affiliations:
Departamento de Bioquímica y Biología Molecular,IUOPA,Oviedo,Spain
,
David Torrents
Affiliations:
Joint Program on Computational Biology,BSC,Barcelona,Spain
,
Marie-LAure Yaspo
Affiliations:
Gene Regulation and Systems Biology of Cancer,Max Planck Institut for Molecular Genetics,Berlin,Germany
,
Marta Aymerich
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
,
Simon Heath
Affiliations:
Bioinformatics Development and Statistical Genomics,CNAG-CRG, CRG, BIST and UPF,Barcelona,Spain
,
Roderic Guigó
Affiliations:
Computational Biology of RNA Processing,CRG,Barcelona,Spain
,
Marta Gut
Affiliations:
Sequencing Unit,CNAG-CRG, CRG, BIST and UPF,Barcelona,Spain
,
Peter Fraser
Affiliations:
Nuclear Dynamics,Babraham Institute,Cambridge,United Kingdom
,
Marc Martí-Renom
Affiliations:
Structural Genomics,CNAG-CRG, CRG, BIST, UPF and ICREA,Barcelona,Spain
,
Ivo Gut
Affiliations:
Applied Genomics,CNAG-CRG, CRG, BIST and UPF,Barcelona,Spain
,
Joost Martens
Affiliations:
Molecular Biology,NCMLS,Nijmegen,Netherlands
,
Henk Stunnenberg
Affiliations:
Molecular Biology,NCMLS,Nijmegen,Netherlands
,
Elias Campo
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
Iñaki Martin-Subero
Affiliations:
Hematology and Oncology,IDIBAPS,Barcelona,Spain
(Abstract release date: 05/18/17) EHA Library. Beekman R. 06/23/17; 181404; S117
Dr. Renée Beekman
Dr. Renée Beekman
Contributions
Abstract

Abstract: S117

Type: Oral Presentation

Presentation during EHA22: On Friday, June 23, 2017 from 12:15 - 12:30

Location: Hall D

Background

Different omics studies have focused on the analysis of individual layers of information in chronic lymphocytic leukemia (CLL), such as the genome, transcriptome and DNA methylome. However, besides the DNA methylome, other layers of the epigenome, like histone modifications, remain relatively unexplored and an integrative molecular portrait of CLL is not available yet.

Aims

The aim of this study was to extensively map and analyse the epigenome of CLL in relation to the mutational, transcriptional and three-dimensional (3D) chromatin landscape.

Methods

Seven CLL patients with distinct clinico-pathological features and five mature B-cell subpopulations were extensively analysed using (i) ChIP-seq of six different histone marks with non-overlapping features (H3K27ac, H3K4me1, H3K4me3, H3K9me3, H3K27me3 and H3K36me3); (ii) single stranded RNA-seq; iii) transposase-accessible chromatin assays (ATAC-seq) and iv) whole-genome bisulfite sequencing (WGBS), creating a unique reference epigenome for CLL. These data were complemented with the 3D chromatin landscape in one CLL case measured by high-throughput chromatin conformation capture (HiC-seq) and promoter capture Hi-C (PCHi-C). Furthermore, we mapped the active chromatin landscape of 100 CLL patients by H3K27ac ChIP-seq and ATAC-seq. Whole-genome sequencing data was available for 44 of these patients. We applied a broad range of bioinformatic tools to analyze the data in an integrative way.

Results

CLL is distinct from normal B cells for all layers of the reference epigenome (7 CLLs) and the active chromatin landscape (100 CLLs). CLL though is closer to naive and memory B cells than to germinal center B cells and plasma cells. Interestingly, in CLL we not only saw activation of regions that are active in naive and memory B cells, but also an unexpected activation of genomic regions that are specifically active in germinal center B cells and plasma cells. Changes in activation in these and other regions could furthermore distinguish the two major clinical subgroups of CLL with unmutated and mutated immunoglobulin heavy chains (IGVH).
CLLs did not only differ from normal B cells regarding the separate layers of information, but also using combined patterns of histone marks, which for example can define regulatory elements as active promoters (H3K4me3 and H3K27ac) or active enhancers (H3K27ac and H3K4me1). More specifically, we detected 534 genomic regions with de novo gain (n=498) or loss (n=36) of active regulatory regions in CLL. Large regions (>10kb) showing de novo gain of regulatory elements in CLL (n=51), were located into, close to, or interacted in 3D space with genes important for CLL pathogenesis, e.g., LEF1, BCL2 and FMOD. Interestingly, non-coding somatic mutations in IGVH mutated CLLs accumulate in these and other active regulatory regions, likely being off-target effects of the somatic hypermutation machinery.
Besides changes in regulatory elements, we observed that CLLs lose poised promoters, which are replaced by repressed/inactive regions. This change, mainly occurring in developmental genes, does not affect gene expression levels, as these genes are already silent in normal B cells. It may however represent loss of plasticity during CLL pathogenesis in which these genes become permanently inactive.

Conclusion

With this integrative study, we generated new conceptual avenues to understand the complex link among the epigenetic, mutational, transcriptional and 3D chromatin landscape in CLL. In addition we provide the community with an extensive resource of epigenetic information of this lymphoid neoplasm.

Session topic: 5. Chronic lymphocytic leukemia and related disorders - Biology

Keyword(s): Genomics, Epigenetic, Chronic Lymphocytic Leukemia, Chromatin

Abstract: S117

Type: Oral Presentation

Presentation during EHA22: On Friday, June 23, 2017 from 12:15 - 12:30

Location: Hall D

Background

Different omics studies have focused on the analysis of individual layers of information in chronic lymphocytic leukemia (CLL), such as the genome, transcriptome and DNA methylome. However, besides the DNA methylome, other layers of the epigenome, like histone modifications, remain relatively unexplored and an integrative molecular portrait of CLL is not available yet.

Aims

The aim of this study was to extensively map and analyse the epigenome of CLL in relation to the mutational, transcriptional and three-dimensional (3D) chromatin landscape.

Methods

Seven CLL patients with distinct clinico-pathological features and five mature B-cell subpopulations were extensively analysed using (i) ChIP-seq of six different histone marks with non-overlapping features (H3K27ac, H3K4me1, H3K4me3, H3K9me3, H3K27me3 and H3K36me3); (ii) single stranded RNA-seq; iii) transposase-accessible chromatin assays (ATAC-seq) and iv) whole-genome bisulfite sequencing (WGBS), creating a unique reference epigenome for CLL. These data were complemented with the 3D chromatin landscape in one CLL case measured by high-throughput chromatin conformation capture (HiC-seq) and promoter capture Hi-C (PCHi-C). Furthermore, we mapped the active chromatin landscape of 100 CLL patients by H3K27ac ChIP-seq and ATAC-seq. Whole-genome sequencing data was available for 44 of these patients. We applied a broad range of bioinformatic tools to analyze the data in an integrative way.

Results

CLL is distinct from normal B cells for all layers of the reference epigenome (7 CLLs) and the active chromatin landscape (100 CLLs). CLL though is closer to naive and memory B cells than to germinal center B cells and plasma cells. Interestingly, in CLL we not only saw activation of regions that are active in naive and memory B cells, but also an unexpected activation of genomic regions that are specifically active in germinal center B cells and plasma cells. Changes in activation in these and other regions could furthermore distinguish the two major clinical subgroups of CLL with unmutated and mutated immunoglobulin heavy chains (IGVH).
CLLs did not only differ from normal B cells regarding the separate layers of information, but also using combined patterns of histone marks, which for example can define regulatory elements as active promoters (H3K4me3 and H3K27ac) or active enhancers (H3K27ac and H3K4me1). More specifically, we detected 534 genomic regions with de novo gain (n=498) or loss (n=36) of active regulatory regions in CLL. Large regions (>10kb) showing de novo gain of regulatory elements in CLL (n=51), were located into, close to, or interacted in 3D space with genes important for CLL pathogenesis, e.g., LEF1, BCL2 and FMOD. Interestingly, non-coding somatic mutations in IGVH mutated CLLs accumulate in these and other active regulatory regions, likely being off-target effects of the somatic hypermutation machinery.
Besides changes in regulatory elements, we observed that CLLs lose poised promoters, which are replaced by repressed/inactive regions. This change, mainly occurring in developmental genes, does not affect gene expression levels, as these genes are already silent in normal B cells. It may however represent loss of plasticity during CLL pathogenesis in which these genes become permanently inactive.

Conclusion

With this integrative study, we generated new conceptual avenues to understand the complex link among the epigenetic, mutational, transcriptional and 3D chromatin landscape in CLL. In addition we provide the community with an extensive resource of epigenetic information of this lymphoid neoplasm.

Session topic: 5. Chronic lymphocytic leukemia and related disorders - Biology

Keyword(s): Genomics, Epigenetic, Chronic Lymphocytic Leukemia, Chromatin

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