MARS-seq2.0

MARS-seq2.0 integrates index sorting with massively parallel single-cell RNA sequencing (scRNA-seq) to profile and identify unique cell types and characterize cellular niches across human tissues, diseases, model organisms, and experimental conditions.

Key Features:

• Integrated Pipeline: Combines index sorting with massively parallel scRNA-seq to link FACS-derived phenotypes to transcriptomes.
• Sub-Microliter Reaction Volumes: Employs sub-microliter reaction volumes to reduce reagent consumption and minimize well-to-well contamination.
• Optimized Enzymatic Mixtures: Uses optimized enzymatic mixtures to improve reproducibility of library preparation.
• Enhanced Analytical Pipeline: Implements comprehensive quality assessment layers, error detection and correction mechanisms, and graphical reporting of library complexity, noise distribution, and sequencing saturation.
• Efficient Sampling via FACS: Integrates fluorescence-activated cell sorting (FACS) with scRNA-seq to enable depletion or enrichment of specific cell populations for targeted sampling.
• High-Throughput Capacity: Capable of processing over one million cells through the refined methodology.

Scientific Applications:

• Cellular Niche Characterization: Detailed mapping and characterization of cellular diversity and niches within human tissues.
• Rare Cell Discovery in Clinical Research: Identification and molecular characterization of rare cell types in clinical samples to inform disease mechanisms and therapeutic targets.
• Comparative High-Throughput Studies: Large-scale comparative profiling across tissues, diseases, model organisms, and experimental conditions.

Methodology:

Data are processed through an analytical pipeline that performs quality assessment, error detection and correction, and generates graphical summaries of library complexity, noise distribution, and sequencing saturation.