计算机科学
计算生物学
仿形(计算机编程)
人工智能
生物
操作系统
作者
Halima Hannah Schede,Christian G. Schneider,Johanna Stergiadou,Lars E. Borm,Anurag Ranjak,Tracy Yamawaki,Fabrice P.A. David,Peter Lönnerberg,Gilles Laurent,Maria Antonietta Tosches,Simone Codeluppi,Gioele La Manno
标识
DOI:10.1101/2020.08.04.235655
摘要
Genomics techniques are currently being adapted to provide spatially resolved omics profiling. However, the adaptation of each new method typically requires the setup of specific detection strategies or specialized instrumentation. A generic approach to spatially resolve different types of high throughput data is missing. Here, we describe an imaging-free framework to localize high throughput readouts within a tissue by combining compressive sampling and image reconstruction. We implemented this framework to transform a low-input RNA sequencing protocol into an imaging-free spatial transcriptomics technique (STRP-seq) and validated this method with a transcriptome profiling of the murine brain. To verify the broad applicability of STRP-seq, we applied the technique on the brain of the Australian bearded dragon Pogona vitticeps . Our results reveal the molecular anatomy of the telencephalon of this lizard, providing evidence for a marked regionalization of the reptilian pallium and subpallium. Overall, the proposed framework constitutes a new approach that allows upgrading in a generic fashion conventional genomic assays to spatially resolved techniques.
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