The technological landscape and applications of single-cell multi-omics

Area of Science:

• Molecular Cell Biology
• Genomics
• Systems Biology

Background:

• Single-cell multi-omics technologies integrate diverse omics data (transcriptome, genome, epigenome, proteome, etc.) to characterize cellular states and activities.
• These integrated approaches are transforming molecular cell biology research by providing a more holistic view of cellular processes.

Purpose of the Study:

• To provide a comprehensive review of established and cutting-edge single-cell multi-omics technologies.
• To discuss advancements in throughput, resolution, modality integration, uniqueness, and accuracy over the past decade.
• To highlight the impact and limitations of these technologies in various research areas.

Main Methods:

• Review of established and state-of-the-art single-cell multi-omics technologies.
• Analysis of technological adaptations focusing on throughput, resolution, integration, and accuracy.
• Discussion of bioinformatics tools for multi-modal data integration and functional elucidation.

Main Results:

• Single-cell multi-omics has significantly advanced cell lineage tracing, atlas production, tumor immunology, cancer genetics, and spatial biology.
• Improvements in technology have focused on optimizing key performance characteristics and addressing inherent limitations.
• Development of sophisticated bioinformatics tools is crucial for linking different omics modalities and interpreting complex biological data.

Conclusions:

• Single-cell multi-omics technologies are powerful tools revolutionizing molecular and cellular biology research.
• Continued technological development and advanced computational methods are essential for maximizing the potential of multi-omics data.
• These integrated approaches are critical for fundamental discoveries and translational applications in health and disease.