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We also describe how to combine i-BLESS with our qDSB-Seq approach to enable the measurement of absolute DSB frequencies per cell and their precise genomic coordinates at the same time. Such normalization using qDSB-Seq is especially useful for the evaluation of spontaneous DSB levels and the estimation of DNA damage induced rather uniformly in the genome (e.g., by irradiation or radiomimetic chemotherapeutics).Human skin harbors various immune cells that are crucial for the control of injury and infection. However, the current understanding of immune cell function within viable human skin tissue is limited. We developed an ex vivo imaging approach in which fresh skin biopsies are mounted and then labeled with nanobodies or antibodies against cell surface markers on tissue-resident memory CD8+ T cells, other immune cells of interest, or extracellular tissue components. Subsequent longitudinal imaging allows one to describe the dynamic behavior of human skin-resident cells in situ. In addition, this strategy can be used to study immune cell function in murine skin. The ability to follow the spatiotemporal behavior of CD8+ T cells and other immune cells in skin, including their response to immune stimuli, provides a platform to investigate physiological immune cell behavior and immune cell behavior in skin diseases. The mounting, staining and imaging of skin samples requires ~1.5 d, and subsequent tracking analysis requires a minimum of 1 d. The optional production of fluorescently labeled nanobodies takes ~5 d.Base editors can achieve targeted genomic base conversion. However, the off-target issue is one of the major concerns in their application. Whole-genome sequencing (WGS) at the individual level can provide direct information on genome-wide specificity, but it is difficult to distinguish true off-target single-nucleotide variants (SNVs) induced by base editors from background variation. Here we describe an unbiased WGS method for evaluating the specificity of base editors in rice. In this protocol, we describe the experimental design and provide details of vector construction, rice transformation and tissue culture, as well as a comprehensive WGS data analysis pipeline for overcoming two related core problems in various plant species high background mutation rates and the heterogeneity of examined populations. Using this protocol, researchers can straightforwardly and accurately assess the genome-wide specificity of base editors and other genome editing tools in 12-15 weeks.DNA nanopores are bio-inspired nanostructures that control molecular transport across lipid bilayer membranes. Researchers can readily engineer the structure and function of DNA nanopores to synergistically combine the strengths of DNA nanotechnology and nanopores. The pores can be harnessed in a wide range of areas, including biosensing, single-molecule chemistry, and single-molecule biophysics, as well as in cell biology and synthetic biology. Here, we provide a protocol for the rational design of nanobarrel-like DNA pores and larger DNA origami nanopores for targeted applications. We discuss strategies for the pores' chemical modification with lipid anchors to enable them to be inserted into membranes such as small unilamellar vesicles (SUVs) and planar lipid bilayers. The procedure covers the self-assembly of DNA nanopores via thermal annealing, their characterization using gel electrophoresis, purification, and direct visualization with transmission electron microscopy and atomic force microscopy. We also describe a gel assay to determine pore-membrane binding and discuss how to use single-channel current recordings and dye flux assays to confirm transport through the pores. We expect this protocol to take approximately 1 week to complete for DNA nanobarrel pores and 2-3 weeks for DNA origami pores.Expression quantitative trait loci (eQTLs) studies provide associations of genetic variants with gene expression but fall short of pinpointing functionally important eQTLs. Here, using H3K27ac HiChIP assays, we mapped eQTLs overlapping active cis-regulatory elements that interact with their target gene promoters (promoter-interacting eQTLs, pieQTLs) in five common immune cell types (Database of Immune Cell Expression, Expression quantitative trait loci and Epigenomics (DICE) cis-interactome project). This approach allowed us to identify functionally important eQTLs and show mechanisms that explain their cell-type restriction. We also devised an approach to eQTL discovery that relies on HiChIP-based promoter interaction maps as a structural framework for deciding which SNPs to test for association with gene expression, and observe ultra-long-distance pieQTLs (>1 megabase away), including several disease-risk variants. We validated the functional role of pieQTLs using reporter assays, CRISPRi, dCas9-tiling guides and Cas9-mediated base-pair editing. Celastrol In this article we present a method for functional eQTL discovery and provide insights into relevance of noncoding variants for cell-specific gene regulation and for disease association beyond conventional eQTL mapping.Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by different technologies and in different laboratories remains a major challenge. Here we address the need for guidance in choosing algorithms leading to accurate biological interpretations of varied data types acquired with different platforms. Using two well-characterized cellular reference samples (breast cancer cells and B cells), captured either separately or in mixtures, we compared different scRNA-seq platforms and several preprocessing, normalization and batch-effect correction methods at multiple centers. Although preprocessing and normalization contributed to variability in gene detection and cell classification, batch-effect correction was by far the most important factor in correctly classifying the cells. Moreover, scRNA-seq dataset characteristics (for example, sample and cellular heterogeneity and platform used) were critical in determining the optimal bioinformatic method. However, reproducibility across centers and platforms was high when appropriate bioinformatic methods were applied.