To circumvent these issues multiple approaches have been dev

To circumvent these issues, multiple approaches have been developed that target small fractions of the genome, thus reducing the sequencing burden (Dostie et al., 2006; Fullwood et al., 2009; Mumbach et al., 2016). Application of one such approach, chromosome conformation capture carbon copy (5C), which interrogates small contiguous genomic stretches, identified examples of short-range non-CTCF loops that change in differentiating mouse embryonic stem Oxamic acid at specific regulatory genes (Phillips-Cremins et al., 2013), and which to varying degrees are dynamically restored during somatic cell reprogramming (Beagan et al., 2016). Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET), which maps interactions between genomic regions bound by specific proteins, provides further examples of dynamic enhancer and promoter interactions between embryonic stem cells and differentiated B lymphocytes (Kieffer-Kwon et al., 2013). While useful for asking specific questions, such targeted approaches are unsuitable for identifying genome-wide intra-chromosomal interactions that are likely important for cellular differentiation. By interrogating only small, interspersed regions of the genome, approaches such as ChIA-PET, capture Hi-C, and HiChIP may not be able to distinguish differences in local chromatin compaction from true DNA loops (Rao et al., 2014). The introduction of a modified Hi-C protocol, in situ Hi-C, in combination with the continually decreasing cost of genomic sequencing has allowed for the unbiased genome-wide detection of DNA loops in human cells. Nuclear proximity ligation increases the efficiency of in situ Hi-C over existing protocols by reducing random ligation events, enabling higher-resolution and detailed mapping of DNA loops at currently achievable sequencing depths. Importantly, the comprehensive nature of in situ Hi-C allows comparison of interaction frequencies to local backgrounds, something not possible with targeted methods like ChIA-PET, capture Hi-C, and HiChIP, producing quantifiable improvements in accuracy of loop detection (Rao et al., 2014). While multi-cell comparison of high-resolution in situ Hi-C maps has identified thousands of DNA loops that are preserved across diverse cell types (Rao et al., 2014), examples of cell-type-specific looping events also support a role for dynamic genome architecture regulating specific genes. However, this method has not been broadly applied to study dynamic looping in the context of human development and cellular differentiation. Macrophages are phagocytic cells of the innate immune system that represent one of the body’s first defenses against invading pathogens. Macrophage-mediated inflammation has been identified as a key driver of multiple human disorders and diseases, including atherosclerosis, diabetes, and cancer (Chawla et al., 2011; Moore et al., 2013; Noy and Pollard, 2014; Ostuni et al., 2015). The differentiation of monocytic precursors into mature macrophages is well characterized, and key transcriptional regulators of this process have been identified, including SPI-1 proto-oncogene (SPI1), V-maf musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB), and activator protein 1 (AP-1) (FANTOM Consortium et al., 2009; Kelly et al., 2000; Rosa et al., 2007; Valledor et al., 1998). However, the role of DNA looping in this process remains largely unexplored. Treatment of the monocytic leukemia cell line THP-1 with phorbol myristate acetate (PMA) is a model widely used for studying monocyte-macrophage differentiation and provides an ideal system for studying the regulatory dynamics controlled via long-range interactions (Daigneault et al., 2010). First, THP-1 cells grow as a largely homogeneous cell population with a near-diploid genetic background lacking major cytogenetic rearrangements typical of most established cell lines (Odero et al., 2000). Second, they exhibit high functional similarity to in vivo monocytes, including the ability to differentiate into extremely pure populations of macrophages, with over 95% of cells transitioning to macrophages following PMA treatment (Kouno et al., 2013; Lund et al., 2016). Finally, because these cells renew indefinitely, unlimited experiments can be performed on the same cells, eliminating variability introduced by genetic differences.