ASTRO: Automated Spatial-Transcriptome whole RNA Output

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Spatial transcriptomics analysis of formalin-fixed paraffin-embedded (FFPE) tissues is challenging.
• Existing methods struggle to capture both coding and non-coding RNAs spatially.
• Patho-DBiT technology requires specialized computational tools for FFPE samples.

Purpose of the Study:

• To develop an automated computational pipeline for spatial transcriptomics data analysis.
• To enable comprehensive whole-transcriptome analysis of FFPE samples.
• To detect various RNA species, including non-coding RNAs, in a spatial context.

Main Methods:

• Developed ASTRO, an automated pipeline for spatial transcriptomics data processing.
• Optimized ASTRO for whole-transcriptome analysis of FFPE samples.
• Incorporated specialized filtering and optimized spatial barcode calling to enhance mapping rates for degraded RNA.

Main Results:

• ASTRO supports standard spatial transcriptomics datasets and is optimized for FFPE samples.
• The pipeline enables detection of diverse RNA species, including non-coding RNAs like miRNAs.
• Optimizations in ASTRO improve mapping rates and allow robust spatial quantification of coding and non-coding RNAs in FFPE tissues.

Conclusions:

• ASTRO provides a specialized computational solution for spatial transcriptomics of FFPE samples.
• The pipeline facilitates comprehensive analysis of both coding and non-coding RNAs.
• ASTRO enhances the utility of FFPE tissues for spatial transcriptomics research.