Automatic identification of informative regions with epigenomic changes associated to hematopoiesis

Hematopoiesis is one of the best characterized biological systems but the connection between chromatin changes and lineage differentiation is not yet well understood. We have developed a bioinformatic workflow to generate a chromatin space that allows to classify 42 human healthy blood epigenomes from the BLUEPRINT, NIH ROADMAP and ENCODE consortia by their cell type. This approach let us to distinguish different cells types based on their epigenomic profiles, thus recapitulating important aspects of human hematopoiesis. The analysis of the orthogonal dimension of the chromatin space identify 32,662 chromatin determinant regions (CDRs), genomic regions with different epigenetic characteristics between the cell types. Functional analysis revealed that these regions are linked with cell identities. The inclusion of leukemia epigenomes in the healthy hematological chromatin sample space gives us insights on the healthy cell types that are more epigenetically similar to the disease samples. Further analysis of tumoral epigenetic alterations in hematopoietic CDRs points to sets of genes that are tightly regulated in leukemic transformations and commonly mutated in other tumors. Our method provides an analytical approach to study the relationship between epigenomic changes and cell lineage differentiation. Method availability: https://github.com/david-juan/ChromDet.European Union’s Seventh Framework Programme [FP7/2007–2013, 282510 (BLUEPRINT)]; Spanish Ministry of Economy, Industry and Competitiveness and European Regional Development Fund [Project Retos BFU2015–71241-R]. Funding for open access charge: Project Retos BFU2015–71241-R (to A.V.).Peer ReviewedPostprint (published version

RAS-pathway mutation patterns define epigenetic subclasses in juvenile myelomonocytic leukemia

Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative disorder of early childhood characterized by mutations activating RAS signaling. Established clinical and genetic markers fail to fully recapitulate the clinical and biological heterogeneity of this disease. Here we report DNA methylome analysis and mutation profiling of 167 JMML samples. We identify three JMML subgroups with unique molecular and clinical characteristics. The high methylation group (HM) is characterized by somatic PTPN11 mutations and poor clinical outcome. The low methylation group is enriched for somatic NRAS and CBL mutations, as well as for Noonan patients, and has a good prognosis. The intermediate methylation group (IM) shows enrichment for monosomy 7 and somatic KRAS mutations. Hypermethylation is associated with repressed chromatin, genes regulated by RAS signaling, frequent co-occurrence of RAS pathway mutations and upregulation of DNMT1 and DNMT3B, suggesting a link between activation of the DNA methylation machinery and mutational patterns in JMML

Joint single-cell DNA accessibility and protein epitope profiling reveals environmental regulation of epigenomic heterogeneity.

Here we introduce Protein-indexed Assay of Transposase Accessible Chromatin with sequencing (Pi-ATAC) that combines single-cell chromatin and proteomic profiling. In conjunction with DNA transposition, the levels of multiple cell surface or intracellular protein epitopes are recorded by index flow cytometry and positions in arrayed microwells, and then subject to molecular barcoding for subsequent pooled analysis. Pi-ATAC simultaneously identifies the epigenomic and proteomic heterogeneity in individual cells. Pi-ATAC reveals a casual link between transcription factor abundance and DNA motif access, and deconvolute cell types and states in the tumor microenvironment in vivo. We identify a dominant role for hypoxia, marked by HIF1α protein, in the tumor microvenvironment for shaping the regulome in a subset of epithelial tumor cells

RAS-pathway mutation patterns define epigenetic subclasses in juvenile myelomonocytic leukemia

Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative disorder of early childhood characterized by mutations activating RAS signaling. Established clinical and genetic markers fail to fully recapitulate the clinical and biological heterogeneity of this disease. Here we report DNA methylome analysis and mutation profiling of 167 JMML samples. We identify three JMML subgroups with unique molecular and clinical characteristics. The high methylation group (HM) is characterized by somatic PTPN11 mutations and poor clinical outcome. The low methylation group is enriched for somatic NRAS and CBL mutations, as well as for Noonan patients, and has a good prognosis. The intermediate methylation group (IM) shows enrichment for monosomy 7 and somatic KRAS mutations. Hypermethylation is associated with repressed chromatin, genes regulated by RAS signaling, frequent co-occurrence of RAS pathway mutations and upregulation of DNMT1 and DNMT3B, suggesting a link between activation of the DNA methylation machinery and mutational patterns in JMML

Multi-omics analysis of DNMT3A- and NPM1-mutated acute myeloid leukemia

Acute myeloid leukemia (AML) represents a genetically heterogeneous group of aggressive myeloid malignancies arising from clonal expansion of aberrant, myeloid-primed hematopoietic stem or progenitor cells. Intensive chemotherapy efficiently targets proliferating blasts and achieves remission in the majority of patients. However, most patients relapse, likely due to persisting, slowly proliferating leukemic stem cells (LSCs). A novel flow cytometry sorting strategy was recently developed in-house to enrich five different leukemic populations, two of them enriched for LSCs (GPR56+NKG2DL-). This strategy was applied to a genetically harmonized DNMT3A and NPM1 double-mutant AML cohort. Despite identical driver mutations, one group presented with early relapse (ER) while the other achieved long-term remission (LTR). Multi-omics profiling (RNA-seq, DNA methylation, and genetic information) allowed me to deeply characterize these sorted leukemic populations and identify biological processes associated with ER. This analysis confirmed xenotransplantation experiments and demonstrated that the LSC-enriched populations exhibited indeed more stem-like characteristics. Still, LSC-enriched populations showed a higher cell cycle activity compared to non-engrafting, more differentiated AML populations. The LSC-enriched populations were transcriptionally similar, but the CD34+ population retained also healthy hematopoietic stem cells (HSCs) while the CD34- population contained exclusively leukemic (stem) cells. This was particularly reflected by the distinct mutant allele frequencies of the DNMT3A- and NPM1-mutations. By analyzing the LSC-enriched populations, I demonstrated a higher transcriptomic instability in ER LSCs compared to LTR LSCs that may be initiated by increasing hypomethylation associated with an earlier onset of the DNMT3A mutation. Moreover, ER LSCs exhibited a more stem-like phenotype, characterized by higher activity of mitochondrial oxidative phosphorylation compared to LTR LSCs, which presented enhanced glycolytic activity instead. The difference in energy metabolism was partially confirmed by untargeted metabolomics analyses. In a technical development project, I also implemented an interactive R shiny app (MetaboExtract) and an R package (MetAlyzer) to infer suitable extraction protocols for metabolomics studies. In addition, I trained an outcome prediction expression signature to stratify patients based on their risk of relapse and hence long-term chemotherapy sensitivity. This signature was highly predictive in different AML cohorts and was able to stratify AML patients with poor and more favorable overall survival. In summary, my work revealed biological mechanisms associated with an early relapse in LSC-enriched AML populations and generated a novel outcome prediction signature to stratify patients

The non-coding RNA landscape of human hematopoiesis and leukemia

© The Author(s) 2017. Non-coding RNAs have emerged as crucial regulators of gene expression and cell fate decisions. However, their expression patterns and regulatory functions during normal and malignant human hematopoiesis are incompletely understood. Here we present a comprehensive resource defining the non-coding RNA landscape of the human hematopoietic system. Based on highly specific non-coding RNA expression portraits per blood cell population, we identify unique fingerprint non-coding RNAs-such as LINC00173 in granulocytes-and assign these to critical regulatory circuits involved in blood homeostasis. Following the incorporation of acute myeloid leukemia samples into the landscape, we further uncover prognostically relevant non-coding RNA stem cell signatures shared between acute myeloid leukemia blasts and healthy hematopoietic stem cells. Our findings highlight the importance of the non-coding transcriptome in the formation and maintenance of the human blood hierarchy

Depletion of RUNX1/ETO in t(8;21) AML cells leads to genome-wide changes in chromatin structure and transcription factor binding

The t(8;21) translocation fuses the DNA-binding domain of the hematopoietic master regulator RUNX1 to the ETO protein. The resultant RUNX1/ETO fusion protein is a leukemia-initiating transcription factor that interferes with RUNX1 function. The result of this interference is a block in differentiation and, finally, the development of acute myeloid leukemia (AML). To obtain insights into RUNX1/ETO-dependant alterations of the epigenetic landscape, we measured genome-wide RUNX1- and RUNX1/ETO-bound regions in t(8;21) cells and assessed to what extent the effects of RUNX1/ETO on the epigenome depend on its continued expression in established leukemic cells. To this end, we determined dynamic alterations of histone acetylation, RNA Polymerase II binding and RUNX1 occupancy in the presence or absence of RUNX1/ETO using a knockdown approach. Combined global assessments of chromatin accessibility and kinetic gene expression data show that RUNX1/ETO controls the expression of important regulators of hematopoietic differentiation and self-renewal. We show that selective removal of RUNX1/ETO leads to a widespread reversal of epigenetic reprogramming and a genome-wide redistribution of RUNX1 binding, resulting in the inhibition of leukemic proliferation and self-renewal, and the induction of differentiation. This demonstrates that RUNX1/ETO represents a pivotal therapeutic target in AML

Resource:A Cellular Developmental Taxonomy of the Bone Marrow Mesenchymal Stem Cell Population in Mice

Mesenchymal stem cells (MSCs) play pivotal roles in tissue (re)generation. In the murine bone marrow, they are thought to reside within the Sca-1(+) CD51(+) bone marrow stromal cell population. Here, using scRNAseq, we aimed to delineate the cellularheterogeneity of this MSC-enriched population throughout development. At the fetal stage, the MSC population is relatively homogeneous with subsets predicted to contain stem/progenitor cells, based on transcriptional modeling and marker expression. These subsets decline in relative size throughout life, with postnatal emergence of specialized clusters, including hematopoietic stem/progenitor cell (HSPC) niches. In fetal development, these stromal HSPC niches are lacking, but subsets of endothelial cells express HSPC factors, suggesting that they may provide initial niches for emerging hematopoiesis. This cellular taxonomy of the MSC population upon development is anticipated to provide a resource aiding the prospective identification of cellular subsets and molecular mechanisms driving bone marrow (re)generation

Mapping the transcriptional landscape of haematopoietic stem and progenitor cells

Maintenance of the blood system requires balanced cell-fate decisions of haematopoietic stem and progenitor cells (HSPCs). Individual haematopoietic stem cells (HSCs) decide between self-renewal and differentiation and can generate all mature cell types. Cell-fate decisions are made at the single-cell level and are governed by regulatory networks. Dysregulation in this balanced process could lead to serious blood disorders such as leukaemia; therefore, it is important to understand how individual cells make these cell-fate decisions. To investigate HSPC populations, 1,654 cells were profiled by single-cell RNA-sequencing. Index sorting made it possible to sort HSPCs using broad sorting gates and retrospectively assign them to common HSPC populations, retaining all information about specific functionally pure populations while also capturing any intermediate cells normally excluded by conventional gating. Reconstruction of differentiation trajectories revealed dynamic expression changes associated with early lineage differentiation from HSCs. This transcriptional atlas of HSPC differentiation was further used to identify candidate genes for a CRISPR screen investigating genes implicated in HSC biology. These candidate gene perturbations were interrogated for changes in the expression of the HSC marker EPCR, as well as changes in apoptosis and lineage output. Transcription factors play a key role in regulating cell-fate decisions and operate within organized regulatory programs. To study relationships between transcription factors in HSPC populations, qRT-PCR was used to profile the expression of 41 genes, including 31 transcription factors, in HSPCs at the single-cell level. This approach confirmed known aspects of haematopoiesis and made deeper investigation of HSPC heterogeneity possible. Regulatory networks were reconstructed using Boolean network inference models and recapitulated differentiation of HSCs towards megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, a rule specific to the megakaryocyte-erythrocyte progenitor network was identified, in which GATA2 positively regulated Nfe2 and Cbfa2t3h. This was subsequently validated using transcription factor binding profiles and in vitro luciferase assays using a model cell line. Overall, the work presented in this thesis confirmed known aspects of HSPC biology using single-cell gene expression analysis and demonstrated how in silico approaches can be used to guide in vitro and in vivo investigations. In addition, the single-cell RNA-sequencing data was developed into an intuitive web interface that can be used to visualise the gene expression for any gene of choice at single-cell resolution across the HSPC atlas, providing a powerful resource for the haematopoietic community.My funding for the CIMR 4 year programme was provided by the Medical Research Council (MRC)