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This protocol describes how to set up arrayed and pooled CRISPR genome-editing experiments. It describes the design of sgRNAs using CRISPOR, the wet-lab implementations, and analysis of the generated results by CRISPResso.

Single-cell analysis of patient brains and cortical organoids links disrupted developmental metabolic reprogramming to postnatal synaptic dysfunction in dup15q syndrome, revealing shared neuronal changes with idiopathic autism.

Nano et al. introduce a pipeline to generate meta-atlases of the human brain from existing single-cell datasets and extract gene modules linked to cell fate specification. Perturbing these programs in human cortical chimeroids validated their roles in cell type specification.

Inclusion body myositis (IBM) is a progressive inflammatory muscle disease of unknown cause, prevalent in older adults. Through spatial and single nuclear profiling, the authors identify a selective type 2 myofiber pathology in IBM, linked to genomic stress and denervation.

Lerma-Martin et al. generated a paired single-nucleus RNA sequencing and spatial transcriptomics dataset from subcortical multiple sclerosis lesions, identifying spatial niches and key cell interactions driving inflammation and disease progression at the lesion rim.

Using a single-nucleus multi-omics approach, a study jointly profiles the reorganization of the epigenome and the three-dimensional chromatin conformation during the development of the human hippocampus and prefrontal cortex.

Whole-genome alignment of 239 primate species reveals noncoding regulatory elements that are under selective constraint in primates but not in other placental mammals, that are enriched for variants that affect human gene expression and complex traits in diseases.

The authors present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications and gene expression on the same tissue section at near-single-cell resolution.

Analysis of chromatin state at a single-cell level in samples of developing human forebrain demonstrate both cell-type-specific and region-specific changes during neurogenesis.

High-throughput experimental platforms have revolutionized the ability to profile biochemical and functional properties of biological sequences such as DNA, RNA and proteins. By collating several data modalities with customizable tracks rendered using intuitive visualizations, genome browsers enable an interactive and interpretable exploration of diverse types of genome profiling experiments and derived annotations. However, existing genome browser tracks are not well suited for intuitive visualization of high-resolution DNA sequence features such as transcription factor motifs. Typically, motif instances in regulatory DNA sequences are visualized as BED-based annotation tracks, which highlight the genomic coordinates of the motif instances but do not expose their specific sequences. Instead, a genome sequence track needs to be cross-referenced with the BED track to identify sequences of motif hits. Even so, quantitative information about the motif instances such as affinity or conservation as well as differences in base resolution from the consensus motif are not immediately apparent. This makes interpretation slow and challenging. This problem is compounded when analyzing several cellular states and/or molecular readouts (such as ATAC-seq and ChIP–seq) simultaneously, as coordinates of enriched regions (peaks) and the set of active transcription factor motifs vary across cell states.

Single-cell RNA sequencing was used to construct a map of gene expression in lesions from brains of patients with multiple sclerosis, revealing distinct lineage- and region-specific transcriptomic changes associated with selective cortical neuron damage and glial activation.

Single-cell RNA sequencing clarifies the development and specification of neurons in the human cortex and shows that cell stress impairs this process in cortical organoids.

Off-targets identified by whole-genome sequencing of CRISPR-treated mouse embryos and their genetic parents are compared to predictions from GUIDE-seq and computational methods.

Samples of different body regions from hundreds of human donors are used to study how genetic variation influences gene expression levels in 44 disease-relevant tissues.

Eze et al. use single-cell sequencing and immunohistochemical validation to create an atlas of early human brain development. In the telencephalon, they discover a diversity of progenitor subtypes, including two that are enriched in humans.

Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.

Using the GTEx data and others, a comprehensive analysis of adenosine-to-inosine RNA editing in mammals is presented; targets of the various ADAR enzymes are identified, as are several potential regulators of editing, such as AIMP2.

Multiple transcriptome approaches, including single-cell sequencing, demonstrate that escape from X chromosome inactivation is widespread and occasionally variable between cells, chromosomes, and tissues, resulting in sex-biased expression of at least 60 genes and potentially contributing to sex-specific differences in health and disease.

The authors show that rare genetic variants contribute to large gene expression changes across diverse human tissues and provide an integrative method for interpretation of rare variants in individual genomes.

The authors show that two primate-specific genes encoding KRAB domain containing zinc finger proteins, ZNF91 and ZNF93, have evolved during the last 25 million years to repress retrotransposon families that emerged during this time period; according to the new data KZNF gene expansion limits the activity of newly emerged retrotransposons, which subsequently mutate to evade repression.

The UCSC SARS-CoV-2 Genome Browser (https://genome.ucsc.edu/covid19.html) is an adaptation of our popular genome-browser visualization tool for this virus, containing many annotation tracks and new features, including conservation with similar viruses, immune epitopes, RT–PCR and sequencing primers and CRISPR guides. We invite all investigators to contribute to this resource to accelerate research and development activities globally.