Lineage-specific and single cell chromatin accessibility charts human hematopoiesis and leukemia evolution

By M. Corces, Jason D. Buenrostro, Beijing Wu, Peyton Greenside, Steven M. Chan, J. Koenig, Michael Snyder, Jonathan K. Pritchard, Anshul B Kundaje, W.J. Greenleaf and 2 more. Nature Genetics, 2016

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We define the chromatin accessibility and transcriptional landscapes in 13 human primary blood cell types that span the hematopoietic hierarchy. Exploiting the finding that the enhancer landscape better reflects cell identity than mRNA levels, we enable 'enhancer cytometry' for enumeration of pure cell types from complex populations. We identify regulators governing hematopoietic differentiation and further show the lineage ontogeny of genetic elements linked to diverse human diseases. In acute myeloid leukemia (AML), chromatin accessibility uncovers unique regulatory evolution in cancer cells with a progressively increasing mutation burden. Single AML cells exhibit distinctive mixed regulome profiles corresponding to disparate developmental stages. A method to account for this regulatory heterogeneity identified cancer-specific deviations and implicated HOX factors as key regulators of preleukemic hematopoietic stem cell characteristics. Thus, regulome dynamics can provide diverse insights into hematopoietic development and disease.

Subfields: Cancer Research, Hematology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2896ef1bd1415717e465f5520e7cd21af0b569de

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Citations in the corpus

Comprehensive integration of single-cell data (2018, methodology): “As bulk ATAC-seq data are available for ﬂuorescence-activated cell sorting (FACS)-sorted populations of human immune cell subsets (Corces et al., 2016), we experimentally validated our predictions by comparing FACS-sorted ATAC-seq proﬁles with pseudo-bulk proﬁles obtained from our classiﬁed…”
Targeted in situ genome-wide profiling with high efficiency for low cell numbers (2018, neutral): “But ATAC-seq is limited to nonspecific identification of TFs that are in accessible regions of chromatin and is unable to distinguish chromatin states demarcated by histone PTMs. Problems of epitope masking in cross-linking ChIP, leading to low efficiency, can be mitigated by using a native ChIP str”
cisTopic: cis-Regulatory topic modelling on single-cell ATAC-seq data (2019, neutral): “This work (GSE114557) + H3K27Ac profiles of 3 melanoma cell lines: A375, MM029 and MM032 + Omni-ATAC during an EMT-like transition in melanoma (8 samples): Two cell lines (MM057 and MM087) under SOX10KD and sampling on different time points (0h, 24h, 48h, 72h) + scATAC-seq during an EMT-like transit”
The Human Cell Atlas (2017, background): “The optimal amount and type of information to collect will emerge based on a balance of technological feasibility and the biological insight provided by each layer (Corces et al., 2016; Lorthongpanich et al., 2013; Paul et al., 2015).”
Profiling tumor infiltrating immune cells with CIBERSORT (2018, methodology): “In the original description of CIBERSORT, the support vectors were genes selected from a signature matrix, however the CIBERSORT algorithm is completely generalizable and can be applied to various genomic features [19].”
Separable Fully Connected Layers Improve Deep Learning Models For Genomics (2017, methodology): “For the in vivo accessibility dataset, we use a hematopoiesis dataset measuring accessibility in 16 cell types from Corces et al. [2016], and train on 837,977 examples.”
Characterization of cell fate probabilities in single-cell data with Palantir (2019, positive): “…measurements such as DNase-seq and ATAC-seq suggest potential mechanisms for a continuous process by indicating that progressive enhancer restriction, coupled with pre-establishment of lineage-specifying enhancers in precursor cells, can serve as a vehicle for driving differentiation 5, 9, 10 .”