Back

Parallel Activation and Interference CRISPR (PAIR) with Sequencing Uncovers DNA Repair Networks Guiding Precision Cell Engineering

Chang, C.; Gan, D.; Diao, L.; Wang, L.; Lacelle, C.; Li, J.; Hon, G. C.; Zhao, M.; Zhang, S.

2026-05-08 bioengineering
10.64898/2026.05.08.722799 bioRxiv
Show abstract

The dynamic balance of cellular homeostasis is often maintained by opposing regulatory pathways, yet most genetic screens interrogate them in one direction and therefore miss the bidirectional gene-gene interactions that shape complex phenotypes such as DNA damage response (DDR). Here, we present PAIR (Parallel Activation and Interference CRISPR), a bidirectional perturbation platform that enables simultaneous activation and suppression of distinct genes within the same cell using CRISPR activation (CRISPRa) and Cas13d RNA knockdown. Applying PAIR to the CRISPR/Cas9 induced DSB repair screen, we mapped gene-gene interactions across competing repair branches and identify synergistic perturbations, including NBN activation combined with suppression of end-joining factors, that shift repair outcomes toward homology-directed repair (HDR) and improve the precision of CRISPR-based gene editing. Using coupled PAIR with single-cell transcriptomic, we further demonstrated that NBN activation induces inflammatory and interferon programs, whereas co-suppression of end-joining factors buffers this response, revealing transcriptional states missed by conventional unidirectional perturbations. To translate these findings into non-viral chimeric antigen receptor (CAR) T cell engineering, we developed an mRNA-based strategy for parallel overexpression and knockdown of NBN-anchored DDR effectors in primary T cells, priming the T cells into a transient HDR-favored state that enhances the efficiency of CAR knock-in on the TRAC locus. Together, the PAIR system provides a general framework for studying opposing regulatory networks, uncovering hidden cell states, and guiding cell-state engineering through bidirectional perturbation.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.