The spatiotemporal dynamics of spatially variable genes in developing mouse brain revealed by a novel computational scheme

• DOI: 10.1038/s41420-023-01569-w
• Publication Date: 2023-07-27T07:03:55Z
• Authors: Yingzhou Hong; Kai Song; Zongbo Zhang; Yuxia Deng; Xue Zhang; Jinqian Zhao; Jun Jiang; Qing Zhang; Chunming Guo; Cheng Peng
• Keywords: QH573-671; Neoplasms. Tumors. Oncology. Including cancer and carcinogens; Cytology; RC254-282; Article

To understand how brain regions form and work, it is important to explore the spatially variable genes (SVGs) enriched in specific during development. Spatial transcriptomics techniques provide opportunity select SVGs high-throughput way. However, previous methods neglected ranking order combinatorial effect of SVGs, making them difficult automatically high-priority from spatial data. Here, we proposed a novel computational pipeline, called SVGbit, rank individual for marker selection various regions, which was tested different kinds public datasets both human mouse brains. We then generated immunohistochemistry data at critical embryonic neonatal stages. The results show that our clustering scheme captures key coincide with known anatomic developing brain. More importantly, SVGbit can facilitate identification multiple gene combination sets regions. identified three dynamical sub-regions be segregated by staining Sox2 Calb2 thalamus, also found Nr4a2 expression gradually segregates neocortex hippocampus In summary, work not only reveals spatiotemporal dynamics brain, but provides pipeline