Developmental enhancers mediate on/off patterns of gene expression in specific cell types at particular stages during metazoan embryogenesis. They typically integrate multiple signals and regulatory determinants to achieve precise spatiotemporal expression. Such enhancers can map quite far--one megabase or more--from the genes they regulate. How remote enhancers relay regulatory information to their target promoters is one of the central mysteries of genome organization and function. A variety of contrasting mechanisms have been proposed over the years, including enhancer tracking, linking, looping, and mobilization to transcription factories.
We first generated a transgenic CRISPRa system using dCas9 fused to a transcriptional activator, VP64, to test whether it can rescue the obesity phenotype in a Sim1 haploinsufficient mouse model. CRISPRa targeting of the Sim1 promoter or its hypothalamus-specific enhancer, which is 270 kilobases away from the gene, in Sim1 haploinsufficient mice increased the expression of the normal copy of Sim1. This up-regulation was sufficient to rescue the obesity phenotype of Sim1 heterozygous mice and led to significantly reduced food intake and body fat content in these mice. We assessed the off-targeting effects of CRISPRa using both RNA sequencing (RNA-seq) and Cas9 chromatin immunoprecipitation sequencing (ChIP-seq) analyses. We found CRISPRa targeting to be highly specific and without any overt changes in the expression of other genes.
The brain is responsible for cognition, behavior, and much of what makes us uniquely human. The development of the brain is a highly complex process, and this process is reliant on precise regulation of molecular and cellular events grounded in the spatiotemporal regulation of the transcriptome. Disruption of this regulation can lead to neuropsychiatric disorders. The regulatory, epigenomic, and transcriptomic features of the human brain have not been comprehensively compiled across time, regions, or cell types. Understanding the etiology of neuropsychiatric disorders requires knowledge not just of endpoint differences between healthy and diseased brains but also of the developmental and cellular contexts in which these differences arise. Moreover, an emerging body of research indicates that many aspects of the development and physiology of the human brain are not well recapitulated in model organisms, and therefore it is necessary that neuropsychiatric disorders be understood in the broader context of the developing and adult human brain. Here we describe the generation and analysis of a variety of genomic data modalities at the tissue and single-cell levels, including transcriptome, DNA methylation, and histone modifications across multiple brain regions ranging in age from embryonic development through adulthood. We observed a widespread transcriptomic transition beginning during late fetal development and consisting of sharply decreased regional differences. This reduction coincided with increases in the transcriptional signatures of mature neurons and the expression of genes associated with dendrite development, synapse development, and neuronal activity, all of which were temporally synchronous across neocortical areas, as well as myelination and oligodendrocytes, which were asynchronous. Moreover, genes including MEF2C, SATB2, and TCF4, with genetic associations to multiple brain-related traits and disorders, converged in a small number of modules exhibiting spatial or spatiotemporal specificity. We generated and applied our dataset to document transcriptomic and epigenetic changes across human development and then related those changes to major neuropsychiatric disorders. These data allowed us to identify genes, cell types, gene coexpression modules, and spatiotemporal loci where disease risk might converge, demonstrating the utility of the dataset and providing new insights into human development and disease.
BELLEVUE, WA – September 17, 2019 -- Today, Skylum has announced two major new features coming to Luminar 4, set to be released this fall. AI Skin Enhancer and Portrait Enhancer will enable photographers to further develop and improve their portraits. These tools use machine learning to speed up the process, but contain detailed controls for even the most demanding photo editor. Previously, photographers would have to spend time selectively editing their photographs, manually adjusting various tools through selections and masking. With Luminar 4, these tedious tools are a thing of the past.