[New-generation high-throughput technologies based 'omics' research strategy in human disease]

Area of Science:

• Biotechnology and Bioinformatics
• Genomics, Transcriptomics, and Proteomics
• Translational Medicine

Background:

• High-throughput technologies (e.g., next-generation sequencing, mass spectrometry) are increasingly vital in human disease research.
• A data-driven, large-scale research model allows multi-level studies of diseases from genomic, transcriptomic, and proteomic perspectives.
• These technologies facilitate omnidirectional and multi-level investigations into complex biological problems.

Purpose of the Study:

• To review the latest developments in high-throughput technologies applied to DNA, RNA, epigenomics, metagenomics, and proteomics.
• To explore the applications of these technologies in translational medicine.
• To highlight the potential of integrated multi-omics data analysis for understanding disease mechanisms, diagnosis, and therapy.

Main Methods:

• Review of recent advancements in high-throughput sequencing (whole genome, exome, small RNA) and mass spectrometry.
• Analysis of applications in genomics, transcriptomics, proteomics, epigenomics, and metagenomics.
• Integration of bioinformatics for multi-omics data analysis.

Main Results:

• Whole genome resequencing excels at detecting large structural variants, enabling personalized genome-based medicine.
• Small RNA sequencing identifies potential biomarkers for disease diagnosis, prognosis, and treatment.
• Target proteomics aids in identifying disease-related proteins/peptides for clinical staging and typing.

Conclusions:

• High-throughput technologies provide powerful tools for comprehensive human disease research.
• Trans-omics studies, integrating multi-omics data via bioinformatics, offer systemic explanations for disease mechanisms, diagnosis, and therapy.
• These advancements are crucial for developing effective disease diagnosis and therapeutic strategies.