Prime editor-based high-throughput screening reveals functional synonymous mutations in the human genome DOI Open Access
Xuran Niu, Wei Tang, Yongshuo Liu

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июнь 17, 2024

Abstract Synonymous mutations are generally considered neutral, while their roles in the human genome remain largely unexplored. Herein, we employed PEmax system to create a library of 297,900 epegRNAs and performed extensive screening identify synonymous that impact cell fitness. While most found some can elicit phenotypic effects. By developing specialized machine learning tool, uncovered on various biological processes such as mRNA splicing transcription, supported by multifaceted experimental evidence. Notably, alter RNA folding affect translation, demonstrated PLK1_S2. integrating data with our model, successfully predicted clinically deleterious mutations. This research deepens understanding provides insights for clinical disease studies.

Язык: Английский

Spatially Resolved Panoramic in vivo CRISPR Screen via Perturb-DBiT DOI
Rong Fan, Alev Baysoy, Xiaolong Tian

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 8, 2025

​Spatially resolved in vivo CRISPR screening integrates gene editing with spatial transcriptomics to examine how genetic perturbations alter expression within native tissue environments. However, current methods are limited small perturbation panels and the detection of a narrow subset protein-coding RNAs. We present Perturb-DBiT, distinct versatile approach for simultaneous co-sequencing total RNA whole-transcriptome single-guide RNAs (sgRNAs), base-by-base, on same section. This method enables unbiased discovery influence regulation, cellular dynamics, architecture situ. Applying Perturb-DBiT human cancer metastatic colonization model, we mapped large sgRNAs across tumor colonies consecutive sections alongside their corresponding transcriptomes. revealed novel insights into affect long non-coding (lncRNA) co-variation, microRNA-mRNA interactions, global tRNA alterations amino acid metabolism linked migration growth. By integrating transcriptional pseudotime trajectories, further uncovered impact clonal dynamics cooperation. In an immune-competent syngeneic mouse enabled investigation immune microenvironment, revealing synergistic effects infiltration suppression. provides spatially comprehensive view knockouts diverse molecular responses including proliferation, migration, metastasis, offering panoramic perspective complex tissues.

Язык: Английский

Процитировано

0
Biosafety considerations triggered by genome-editing technologies DOI Creative Commons
Xinxin Li,

Yuanjiao Gao,

Ziyu Zhang

и другие.

Biosafety and Health, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
Prime editor with rational design and AI-driven optimization for reverse editing window and enhanced fidelity DOI Creative Commons
Chao Yang,

Qingxiao Fang,

Mengyu Li

и другие.

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Июнь 3, 2025

Prime editing (PE) is a precise tool for introducing genetic mutations in eukaryotes. Extending the efficient scope and mitigating undesired byproducts are possible. We introduce reverse PE (rPE), SpCas9-directed variant that enabled DNA at 3' direction of HNH-mediated nick site. The rPE leveraging nCas9-D10A gRNA targeting 5' site inscribes alterations, achieving window potentially high fidelity. HNH transcriptase engineered using protein language models conjunction with La facilitate circular erPEmax erPE7max, efficiency up to 44.41% without or positive selection. Furthermore, our findings underscore capability inserting functionally enhanced (PIK3CDE527G) cell therapy. By expanding enhancing genomic manipulability, represents meaningful advancement prime editing, improving its utility research therapeutic applications.

Язык: Английский

Процитировано

0
A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening DOI Creative Commons
Ann Cirincione, Danny Simpson, Purnima Ravisankar

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Март 27, 2024

Prime editing installs precise edits into the genome with minimal unwanted byproducts, but low and variable efficiencies have complicated application of approach to high-throughput functional genomics. Leveraging several recent advances, we assembled a prime platform capable high-efficiency substitution across set engineered guide RNAs (epegRNAs) corresponding target sequences (80% median intended editing). Then, using custom library 240,000 epegRNAs targeting >17,000 codons 175 different types, benchmarked our for interrogation small variants (1-3 nucleotides) targeted essential genes. Resulting data identified negative growth phenotypes nonsense mutations ~8,000 codons, comparing those results from controls demonstrated high specificity. We also observed synonymous that disrupted splice site motifs at 3' exon boundaries. Altogether, establish benchmark characterization genetic simple readouts multiplexed experiments.

Язык: Английский

Процитировано

2
Prime editor-based high-throughput screening reveals functional synonymous mutations in the human genome DOI Open Access
Xuran Niu, Wei Tang, Yongshuo Liu

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июнь 17, 2024

Abstract Synonymous mutations are generally considered neutral, while their roles in the human genome remain largely unexplored. Herein, we employed PEmax system to create a library of 297,900 epegRNAs and performed extensive screening identify synonymous that impact cell fitness. While most found some can elicit phenotypic effects. By developing specialized machine learning tool, uncovered on various biological processes such as mRNA splicing transcription, supported by multifaceted experimental evidence. Notably, alter RNA folding affect translation, demonstrated PLK1_S2. integrating data with our model, successfully predicted clinically deleterious mutations. This research deepens understanding provides insights for clinical disease studies.

Язык: Английский

Процитировано

2