bioRxivBioinformaticsPreprint
Charting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPR
Lin WangiD, Wenjuan DongiD, Zheng YiniD, Jianting ShengiD, Chika F. EzeanaiD, Yang LiiD, Xiaohui YuiD, Solomon S. Y. Wong, Zhihao Wan, Rebecca L. Danforth, Han Kun, Dingcheng GaoiD, Stephen T.C. WongiD
Abstract
Single cell lineage tracing, essential for unraveling cellular dynamics in disease evolution is critical for developing targeted therapies. CRISPR-Cas9, known for inducing permanent and cumulative mutations, is a cornerstone in lineage tracing. The novel homing guide RNA (hgRNA) technology enhances this by enabling dynamic retargeting and facilitating ongoing genetic modifications. Charting these mutations, especially through successive hgRNA edits, poses a significant challenge. Our solution, LINEMAP, is a computational framework designed to trace and map these mutations with precision. LINEMAP meticulously discerns mutation alleles at single-cell resolution and maps their complex interrelationships through a mutation evolution network. By utilizing a Markov Process model, we can predict mutation transition probabilities, revealing potential mutational routes and pathways. Our reconstruction algorithm, anchored in the Markov models attributes, reconstructs cellular lineage pathways, shedding light on the cells evolutionary journey to the minutiae of single-cell division. Our findings reveal an intricate network of mutation evolution paired with a predictive Markov model, advancing our capability to reconstruct single-cell lineage via hgRNA. This has substantial implications for advancing our understanding of biological mechanisms and propelling medical research forward.
- assay: CRISPR screen
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: variant calling
- approach: statistical model
- Citations
- 1
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