The intersectional genetics landscape for humans.

Area of Science:

• Genomics
• Systems Biology
• Synthetic Biology

Background:

• The human body comprises numerous cell types and states, many genetically inaccessible.
• Intersectional genetic methods offer enhanced cell targeting but require systematic safety and scope assessment.
• Current intersectional methods use "AND" logic gates to combine multiple regulatory elements (REs) for cell-specific output.

Purpose of the Study:

• To systematically assess the intersectional genetics landscape of the human genome.
• To develop and validate methods for identifying cell-type-specific regulatory element intersections.
• To explore the potential of these methods for gene delivery technologies.

Main Methods:

• Utilized a subset of cells from the Functional ANnoTation Of the Mammalian genome 5 (FANTOM5) atlas, generated by cap analysis of gene expression sequencing (CAGE-seq).
• Developed algorithms to retrieve and rank "AND" gate intersections of active REs.
• Defined and identified "versatile entry codes" (VEnCodes) as minimal RE intersections for cell-type diagnosis.

Main Results:

• Over 90% of 154 primary human cell types were distinguishable using 3-4 active REs, forming robust VEnCodes.
• 158 cancer cell types were distinguished from healthy primary cells using small, robust VEnCodes.
• Methods for cross-validation of CAGE-seq-derived VEnCodes and extraction from single-cell sequencing data were established.

Conclusions:

• The study provides a systematic view of human intersectional genetics.
• Demonstrated the potential of VEnCodes for precise genetic targeting and future gene delivery applications.