转录组
生物
基因
基因表达
精神分裂症(面向对象编程)
计算生物学
背外侧前额叶皮质
神经科学
前额叶皮质
基因组学
计算机科学
遗传学
基因组
认知
程序设计语言
作者
Kristen R. Maynard,Leonardo Collado‐Torres,Lukas M. Weber,Cedric Uytingco,Brianna K. Barry,Stephen R. Williams,Joseph L. Catallini,Matthew N. Tran,Zachary Besich,Madhavi Tippani,Jennifer Chew,Yifeng Yin,Joel E. Kleinman,Thomas M. Hyde,Nikhil Rao,Stephanie Hicks,Andrew E. Jaffe
标识
DOI:10.1101/2020.02.28.969931
摘要
Abstract We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex (DLPFC). We identified extensive layer-enriched expression signatures, and refined associations to previous laminar markers. We overlaid our laminar expression signatures onto large-scale single nuclei RNA sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially-defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions where morphological architecture is not as well-defined as cortical laminae. We lastly created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research ( http://research.libd.org/spatialLIBD ).
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