Chromatin state dynamics during blood formation

Abstract

Chromatin modifications are crucial for development, yet little is known about their dynamics during differentiation. Hematopoiesis provides a well-defined model to study chromatin state dynamics, however technical limitations impede profiling of homogeneous differentiation intermediates. We developed a high sensitivity indexing-first chromatin immunoprecipitation approach (iChIP) to profile the dynamics of four chromatin modifications across 16 stages of hematopoietic differentiation. We identify 48,415 enhancer regions and characterize their dynamics. We find that lineage commitment involves de novo establishment of 17,035 lineage-specific enhancers. These enhancer repertoire expansions foreshadow transcriptional programs in differentiated cells. Combining our enhancer catalog with gene expression profiles, we elucidate the transcription factor network controlling chromatin dynamics and lineage specification in hematopoiesis. Together, our results provide a comprehensive model of chromatin dynamics during development.

Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation

“…This field has been propelled by remarkable technological advances for efficiently isolating single cells 28, 29, and the reduction of the detection levels of protocols for profiling gene expression 30, 31, histone marks 25, 26, or chromatin accessibility 32, 33 in individual cells. These techniques allow researchers to overcome the limitations of population studies, in which averaging the measurements over a heterogeneous population of cells masks the variability at the epigenetics and transcriptional levels among cells within a culture or tissue 26, 34, 35.…”

“…Profiling of the epigenetics landscape of individual cells has shown that lineage‐specific master regulators are associated with single‐cell epigenomic variability across several cell types, suggesting that control of single‐cell variance is a fundamental characteristic of different biological states 32. Moreover, another study compiled a comprehensive catalog of enhancer histone marks at the single‐cell level, and unveiled that there exists significant de novo establishment of lineage‐specific enhancers during hematopoiesis 25. Similarly, based on single‐cell profiling of histone modifications dynamics in different tissue‐resident macrophages populations, the same group showed that a combination of tissue‐ and lineage‐specific transcription factors form the regulatory networks controlling chromatin specification in tissue‐resident macrophages 26.…”

“…This study shows that among the variable genes in mESCs are included pluripotency factors previously reported to fluctuate in pluripotent cells ( Nanog , Rex1/Zfp42 , Dppa5a , Sox2 , Esrrb ), and more strikingly, the most highly variable genes included known markers of Primitive Endoderm fate ( Col4a1/2 , Lama1/b1 , Sox17 , Sparc ), markers of Epiblast fate ( Krt8 , Krt18 , S100a6 ), and key epigenetic regulators of the ESC state ( Dnmt3b ) 42. The high variability in the epigenetic landscape has recently been studied at the single‐cell level in HSCs 25, in which significant chromatin reorganization in different subpopulations plays a key role during cell‐fate commitment. Similar observations have been made in human ESCs, where the dynamics of histone chromatin marks and DNA methylation is strongly associated to the binding of specific TFs, such as Sox17 , Otx2 , and Gata6 , which defines and stabilizes the phenotypes corresponding to different germ layers 13.…”

“…In contrast to previous computational methods for analyzing single cell data for identifying lineage specifiers 80, 81, 82, which rely on the identification of trends in the expression of individual genes in different subpopulations, in this study we have demonstrated that information of the interactions among genes in the subpopulation‐specific GRNs, is key for predicting the genes triggering differentiation reported experimentally 74. These network models 73, 74, 102, 103 relying solely on transcriptomics data could be significantly improved by overlaying epigenetics data 25, 32, 33, for contextualizing regulatory interactions at the transcriptional level depending on the chromatin state – e.g. open/close chromatin regions, and activating/inhibitory chromatin marks patterns 25, 26, 32, 33.…”

“…Since the characterization of the initial PGRNs, more complex regulatory networks have been described including many other transcription factors (TFs) ( Sall4 , Zscan10 , and Dax1 ) as key regulators of self‐renewal and differentiation of ESCs into different cell‐fates 4, 24. The chromatin landscape and signaling pathways also play a key role in regulating pluripotency and differentiation, although the cross talk between these regulatory levels during lineage specification has been much less studied 5, 25, 26.…”