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Noncoding DNA is central to our understanding of human gene regulation and complex diseases1,2, and measuring the evolutionary sequence constraint can establish the functional relevance of putative regulatory elements in the human genome3–9. Identifying the genomic elements that have become constrained specifically in primates has been hampered by the faster evolution of noncoding DNA compared to protein-coding DNA10, the relatively short timescales separating primate species11, and the previously limited availability of whole-genome sequences12. Here we construct a whole-genome alignment of 239 species, representing nearly half of all extant species in the primate order. Using this resource, we identified human regulatory elements that are under selective constraint across primates and other mammals at a 5% false discovery rate. We detected 111,318 DNase I hypersensitivity sites and 267,410 transcription factor binding sites that are constrained specifically in primates but not across other placental mammals and validate their cis-regulatory effects on gene expression. These regulatory elements are enriched for human genetic variants that affect gene expression and complex traits and diseases. Our results highlight the important role of recent evolution in regulatory sequence elements differentiating primates, including humans, from other placental mammals.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. [ABSTRACT FROM AUTHOR]

Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context1–5. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we 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 (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.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. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is a multifocal and progressive inflammatory disease of the central nervous system (CNS). However, the compartmentalized pathology of the disease affecting various anatomical regions including gray and white matter and lack of appropriate disease models impede understanding of the disease. Utilizing single-nucleus RNA-sequencing and multiplex spatial RNA mapping, we generated an integrated transcriptomic map comprising leukocortical, cerebellar and spinal cord areas in normal and MS tissues that captures regional subtype diversity of various cell types with an emphasis on astrocytes and oligodendrocytes. While we found strong cross-regional diversity among glial subtypes in control tissue, regional signatures become more obscure in MS. This suggests that patterns of transcriptomic changes in MS are shared across regions and converge on specific pathways, especially those regulating cellular stress and immune activation. In addition, we found evidence that a subtype of white matter oligodendrocytes appearing across all three CNS regions adopt pro-remyelinating gene signatures in MS. In summary, our data suggest that cross-regional transcriptomic glial signatures overlap in MS, with different reactive glial cell types capable of either exacerbating or ameliorating pathology. [ABSTRACT FROM AUTHOR]

Cortical organoids are self-organizing three-dimensional cultures that model features of the developing human cerebral cortex1,2. However, the fidelity of organoid models remains unclear3–5. Here we analyse the transcriptomes of individual primary human cortical cells from different developmental periods and cortical areas. We find that cortical development is characterized by progenitor maturation trajectories, the emergence of diverse cell subtypes and areal specification of newborn neurons. By contrast, organoids contain broad cell classes, but do not recapitulate distinct cellular subtype identities and appropriate progenitor maturation. Although the molecular signatures of cortical areas emerge in organoid neurons, they are not spatially segregated. Organoids also ectopically activate cellular stress pathways, which impairs cell-type specification. However, organoid stress and subtype defects are alleviated by transplantation into the mouse cortex. Together, these datasets and analytical tools provide a framework for evaluating and improving the accuracy of cortical organoids as models of human brain development. 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. [ABSTRACT FROM AUTHOR]

In the CRISPR system, a short RNA guide sequence and a variant of the Cas9 protein are introduced into cells. The RNA will bind to an identical sequence in the genome, as long as it is followed by the PAM sequence (usually GG), and mark it for subsequent cutting or modification by the Cas9 protein. As most biologists know, genes have complex similarity relationships, a few groups have many, almost identical copies in the genome, like zinc fingers or olfactory receptors, and many others appear in the genome only once. When it comes to human applications, the context that matters is even more important, from the specific guide, to the Cas9 used and its concentration, to the particular cell type and ultimately the medical gain from the genome modification relative to the potential risks and their likelihood. [Extracted from the article]

Multiple sclerosis (MS) is a neuroinflammatory disease with a relapsing–remitting disease course at early stages, distinct lesion characteristics in cortical grey versus subcortical white matter and neurodegeneration at chronic stages. Here we used single-nucleus RNA sequencing to assess changes in expression in multiple cell lineages in MS lesions and validated the results using multiplex in situ hybridization. We found selective vulnerability and loss of excitatory CUX2-expressing projection neurons in upper-cortical layers underlying meningeal inflammation; such MS neuron populations exhibited upregulation of stress pathway genes and long non-coding RNAs. Signatures of stressed oligodendrocytes, reactive astrocytes and activated microglia mapped most strongly to the rim of MS plaques. Notably, single-nucleus RNA sequencing identified phagocytosing microglia and/or macrophages by their ingestion and perinuclear import of myelin transcripts, confirmed by functional mouse and human culture assays. Our findings indicate lineage- and region-specific transcriptomic changes associated with selective cortical neuron damage and glial activation contributing to progression of MS lesions. 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. [ABSTRACT FROM AUTHOR]

Throughout evolution primate genomes have been modified by waves of retrotransposon insertions. For each wave, the host eventually finds a way to repress retrotransposon transcription and prevent further insertions. In mouse embryonic stem cells, transcriptional silencing of retrotransposons requires KAP1 (also known as TRIM28) and its repressive complex, which can be recruited to target sites by KRAB zinc-finger (KZNF) proteins such as murine-specific ZFP809 which binds to integrated murine leukaemia virus DNA elements and recruits KAP1 to repress them. KZNF genes are one of the fastest growing gene families in primates and this expansion is hypothesized to enable primates to respond to newly emerged retrotransposons. However, the identity of KZNF genes battling retrotransposons currently active in the human genome, such as SINE-VNTR-Alu (SVA) and long interspersed nuclear element 1 (L1), is unknown. Here we show that two primate-specific KZNF genes rapidly evolved to repress these two distinct retrotransposon families shortly after they began to spread in our ancestral genome. ZNF91 underwent a series of structural changes 8-12 million years ago that enabled it to repress SVA elements. ZNF93 evolved earlier to repress the primate L1 lineage until ∼12.5 million years ago when the L1PA3-subfamily of retrotransposons escaped ZNF93's restriction through the removal of the ZNF93-binding site. Our data support a model where KZNF gene expansion limits the activity of newly emerged retrotransposon classes, and this is followed by mutations in these retrotransposons to evade repression, a cycle of events that could explain the rapid expansion of lineage-specific KZNF genes. [ABSTRACT FROM AUTHOR]

In the version of this article initially published, Lena Dolman's second affiliation was given as Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK. The correct second affiliation is Ontario Institute for Cancer Research, Toronto, Ontario, Canada. The error has been corrected in the HTML and PDF versions of the article. [ABSTRACT FROM AUTHOR]