Key Points Mutations in a conserved intronic enhancer element lead to GATA2 haploinsufficiency. Mutations in GATA2, regardless of mutation type, lead to decreased GATA2 transcript levels and a common global transcriptional profile.

Non-coding DNA elements differentially control stem and progenitor cell transitions required for development.

Developmental and homeostatic remodeling of cellular organelles is mediated by a complex process termed autophagy. The cohort of proteins that constitute the autophagy machinery functions in a multistep biochemical pathway. Though components of the autophagy machinery are broadly expressed, autophagy can occur in specialized cellular contexts, and mechanisms underlying cell-type-specific autophagy are poorly understood. We demonstrate that the master regulator of hematopoiesis, GATA-1, directly activates transcription of genes encoding the essential autophagy component microtubule-associated protein 1 light chain 3B (LC3B) and its homologs (MAP1LC3A, GABARAP, GABARAPL1, and GATE-16). In addition, GATA-1 directly activates genes involved in the biogenesis/function of lysosomes, which mediate autophagic protein turnover. We demonstrate that GATA-1 utilizes the forkhead protein FoxO3 to activate select autophagy genes. GATA-1-dependent LC3B induction is tightly coupled to accumulation of the active form of LC3B and autophagosomes, which mediate mitochondrial clearance as a critical step in erythropoiesis. These results illustrate a novel mechanism by which a master regulator of development establishes a genetic network to instigate cell-type-specific autophagy.C ellular differentiation requires massive remodeling of subcellular structures to accommodate specialized functions of cell progeny. For example, the differentiation of committed hematopoietic progenitors into erythrocytes requires disposal of mitochondria (mitophagy) and nuclei (enucleation), which are not required for erythrocyte function. The process whereby cells consume organelles is termed autophagy (29). Autophagy mediates morphological remodeling in developmental and pathophysiological contexts. A cohort of autophagy proteins functions in a multistep reaction to generate an autophagosome that engulfs damaged organelles (53). The subsequent fusion of the loaded autophagosome with the lysosome results in proteolysis of the engulfed proteins.Core components of the autophagy machinery are broadly expressed, and therefore diverse cell types are competent to execute autophagy. A recent proteomics analysis expanded the repertoire of proteins linked to autophagy and illustrated their complex interaction networks (2). Many questions remain unanswered regarding how this complex network of apparently ubiquitous autophagy components is established and what role cell-type-specific factors have in instigating and regulating autophagy.Since autophagy is a critical step in erythrocyte development (19,39,41,57), it is particularly instructive to analyze cell-typespecific autophagy in this context. Targeted deletion of the BCL-2 family member NIX yields anemia, impaired erythroid maturation, and impaired mitophagy during terminal erythroid differentiation (39, 41). Furthermore, a conditional knockout in hematopoietic cells of Atg7, which encodes a protein resembling a ubiquitin-activating enzyme, yields severe anemia, defective erythropoiesis, and lethality shortly af...

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip) as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads). This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads). Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.