Serohijos, A. W. | Search bioRxiv

bioRxiv2025

A strategy for genome-wide seamless tagging of human protein-coding genes

Comprehensive and systematic proteome-wide experiments require financial and technical resources unavailable to most researchers. Here we describe a scalable CRISPR/Cas9-non-homologous end joining (NHEJ) based method for Pooled Recombinant Integration of Seamless Markers (PRISM) into protein coding genes. We created two gRNA libraries for 5- and 3-tagging of 18,804 human protein-coding genes. Selection for in-frame integration of the donor cassette can be guaranteed by fusing it to an antibiotic resistance enzyme (ARE) and P2A self-cleaving peptide, resulting in tagged proteins and free ARE to select for clones with inserted donor cassettes. We achieved a library integration rate of 19.75% and tagging of [~]80% for genes expressed in Hek293T cells and notably, 89.7% of essential genes, with donor DNA. Our strategy is scalable, specific, and selective, paving the way for genome-scale construction of human cell lines tagged with different types of reporter genes for protein functional characterization. Significance statementHere we report the first practical method to achieve near complete 5- or 3-end integration of reporter protein-coding sequences to express seamless fusions of human protein and reporter proteins that we call Pooled Recombinant Integration of Seamless Markers (PRISM). PRISM is independent of homology templates, yet it works with high efficiency and precision. Using gRNA-directed CRISPR/Cas9 genome editing and mini-plasmid donor cassettes we were able to tag about 80% of the protein-coding sequences of human genes with a green florescent protein at an integration efficiency of about 20% and most notably, of 90% of essential genes in the human cell line HEK 293T. This is important because the characterization of gene functions in a particular cell type usually begins with essential genes.

systems biology↗

bioRxiv2024

Protein-protein interaction is a major source of epistasis in genetic interaction networks

Genetic interaction (GI) and protein-protein interaction (PPI) networks have proved among the most important tools for inference of gene function and genotype-phenotype relationship1-6. It remains unclear, however, how these two networks are related to each other. Here we demonstrate that the strengths of epistatic genetic interactions between two genes strongly correlate with the binding free energies of interactions between their cognate proteins, for both yeast and human genomes. Consequently, we show that GI and PPI networks can reciprocally predict each other. Further, we observe that functional divergence and redundancy in duplicated genes (paralogs) are reflected in the binding affinity of their interactions with other proteins and in their genetic interaction strengths. Finally, we demonstrate that the overall topologies of GI and PPI networks significantly overlap in two topological features: Modules, in which genes/proteins are organized by common function, and connectors, which link modules to each other. This opens avenues for new integrated network approaches in understanding cellular processes and flow of genomic information.

systems biology↗