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Genome-wide interrogation of gene functions through base editor screens empowered by barcoded sgRNAs

Nature Biotechnology volume 39, pages 1403–1413 (2021)Cite this article

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Abstract

Canonical CRISPR–knockout (KO) screens rely on Cas9-induced DNA double-strand breaks (DSBs) to generate targeted gene KOs. These methodologies may yield distorted results because DSB-associated effects are often falsely assumed to be consequences of gene perturbation itself, especially when high copy-number sites are targeted. In the present study, we report a DSB-independent, genome-wide CRISPR screening method, termed iBARed cytosine base editing-mediated gene KO (BARBEKO). This method leverages CRISPR cytosine base editors for genome-scale KO screens by perturbing gene start codons or splice sites, or by introducing premature termination codons. Furthermore, it is integrated with iBAR, a strategy we devised for improving screening quality and efficiency. By constructing such a cell library through lentiviral infection at a high multiplicity of infection (up to 10), we achieved efficient and accurate screening results with substantially reduced starting cells. More importantly, in comparison with Cas9-mediated fitness screens, BARBEKO screens are no longer affected by DNA cleavage-induced cytotoxicity in HeLa-, K562- or DSB-sensitive retinal pigmented epithelial 1 cells. We anticipate that BARBEKO offers a valuable tool to complement the current CRISPR–KO screens in various settings.

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Fig. 1: Design of CBE-based genome-scale sgRNA library for gene KO screens.
Fig. 2: BARBEKO achieves high-MOI fitness screens in HeLa cells.
Fig. 3: Copy-number effect could be diminished in BARBEKO screens.
Fig. 4: BARBEKO empowers fitness screen in K562 cells at extra-high MOIs.
Fig. 5: Comparing BARBEKO with CRISPR–KO screens in RPE1 cells.
Fig. 6: Comparisons of differently selected hits among fitness screens of RPE1.

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Data availability

The raw sequencing data of screens are available under NCBI BioProject accession no. PRJNA643641. Source data are available for this paper.

Code availability

The source code for sgRNA library design can be accessed from https://bitbucket.org/WeiLab/barbeko_sgrna_design/src/master. The ZFC algorithm has been implemented by Python 3 and can be downloaded from https://github.com/wolfsonliu/zfc.

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Acknowledgements

This work was supported by funds from the National Science Foundation of China (grant nos. NSFC31930016 to W.W. and NSFC31870893 to Z.Z.), Beijing Municipal Science & Technology Commission (grant no. Z181100001318009), and the Beijing Advanced Innovation Center for Genomics at Peking University, the Peking–Tsinghua Center for Life Sciences (to W.W.). We thank the staff of the BIOPIC High-throughput Sequencing Center (Peking University), H. Lyu, L. Du and H. Yang of the National Center for Protein Sciences (Beijing) at Peking University for technical assistance, and the High-Performance Computing Platform at Peking University for NGS data analysis. We thank Y. Sun and D. Xu (Peking University) for providing hTERT RPE1 and RPE1-TP53KO-Cas9 cell lines.

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Author notes

  1. These authors contributed equally: Ping Xu, Zhiheng Liu, Ying Liu, Huazheng Ma.

Authors and Affiliations

  1. Biomedical Pioneering Innovation Center, Beijing Advanced Innovation Center for Genomics, Peking–Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China

    Ping Xu, Zhiheng Liu, Ying Liu, Huazheng Ma, Yiyuan Xu, Ying Bao, Shiyou Zhu, Zhongzheng Cao, Zeguang Wu, Zhuo Zhou & Wensheng Wei

  2. Peking University–Tsinghua University–National Institute of Biological Sciences Joint Graduate Program, Peking University, Beijing, China

    Huazheng Ma

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Contributions

W.W. conceived and supervised the project. W.W., P.X. and Y.L. designed the experiments. P.X., H.M., Y.X., Y.B., S.Z. and Z.C. performed the experiments. P.X., Z.L. and Y.L. analyzed experimental data. P.X. wrote the manuscript and W.W., Z.Z., H.M., Y.L., Z.L. and Z.W. revised it.

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Correspondence to Wensheng Wei.

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Extended data

Extended Data Fig. 1 Effect of ANTXR1 deficiency by AncBE4max on PA/LFnDTA-triggered cytotoxicity in HeLa cells.

a, Schematic indicates sgRNA targeting sites at ANTXR1 genomic locus. b, Images of HeLa cells with or without PA/LFnDTA treatment for 48 hours after AncBE4max editing with indicated sgRNAs. The results shown are from one group of sgRNA transfected HeLa cells and conducted in triplicates with individual PA/LFnDTA toxin treatment. Scale bar: 100 μm. c, Sanger sequencing chromatograms of sgRNA-targeting ANTXR1 genomic fragments of PA/LFnDTA toxin resistant cells, black arrows indicate peaks of targeted cytosines and their editing results. d, C-to-T editing frequency of indicated sgRNAs targeting ANTXR1 in HeLa cells detected by sanger sequencing. Sorting of the sgRNA-expressing cells was conducted 2 days post-transduction (denoted as day 0), and cells were harvested on days 0, 3 and 6. The green lines indicated the editing frequency of targeted cytosine for gene knockouts, and the other blank lines indicated the editing frequency of cytosine locating in the activity windows of AncBE4max.

Extended Data Fig. 2 Comparing knockout efficiency between AncBE4max and Cas9 by targeting ribosomal genes on cell proliferation.

a, sgRNAStop targeting HBEGF, sgRNAStart targeting ANTXR1 and sgRNAAAVS1 served as negative controls. b, Effects of indicated sgRNAs targeting ribosomal gene RPL23A on cell proliferation in K562 cells by AncBE4max (left) and Cas9 (right). Data are presented as the mean ± s.d. of 3 independent experiments. P values represent comparisons with sgRNAAAVS1 at the endpoint (day 18) using a one-tailed Student’s t-test and adjusted using the Benjamini–Hochberg method. **p < 0.01; ***p < 0.001. c, Editing efficiency of AncBE4max with indicated sgRNAs targeting RPL23A detected by sanger sequencing. sgRNA-expressing cells were sorted on 2 days post transduction (denoted as day 0) and cells were harvested daily until day 6. The colored lines indicated the conversion efficiency of targeted cytosine for gene knockouts and the other blank lines indicated the conversion efficiency of cytosine locating in the activity windows of AncBE4max (the same with f). d, Editing efficiency of Cas9 with indicated sgRNAs targeting RPL23A were detected by sanger sequencing. e, Effects of indicated sgRNAs targeting ribosomal gene RPL11 on cell proliferation in K562 cells by AncBE4max (left) and Cas9 (right). f, Editing efficiency of AncBE4max with indicated sgRNAs targeting RPL11 detected by sanger sequencing. g, Editing efficiency of Cas9 with indicated sgRNAs targeting RPL11 were detected by sanger sequencing.

Extended Data Fig. 3 Information of sgRNAsiBAR and BARBEKO library.

a, Schematic shows the scaffold sequence of sgRNAiBAR, in which 4 iBARs employed in BARBEKO library are highlighted in red. b, Pie chart shows the composition of BARBEKO library that newly designed sgRNAStart and sgRNAs targeting splice sites (sgRNASD and sgRNASA) account for 2.5% and 39.3% respectively, and sgRNAStop introduced from Kuscu et al. account for 58.2%.

Extended Data Fig. 4 Comparisons of BARBEKO screening with CRISPR-KO results and comparisons of depleted hits of BARBEKO between timepoints in HeLa cells.

a-b, ROC analysis for screens in HeLa cells based on reference gene sets with 513 (a) and 662 (b) essential genes. c, Boxplots showing the distribution of gene FS of 349 essential, 703 non-essential and other genes in conventional CRISPR-KO, CRISPRiBAR and BARBEKO screening. Boxplots are represented as follows: center line indicating the median, box limits indicating the upper and lower quartiles, whiskers indicating the 1.5x interquartile range and all other observed points plotting as outliers. d, Scatter plot of sgRNAiBAR ZLFC of two biological replicates on day 15, Pearson correlation coefficient is indicated on the top. sgRNAsiBAR targeting AAVS1 locus and non-targeting sgRNAsiBAR as negative controls are labelled in purple and green. e, Scatter plot of gene Fitness Score (FS) on day 15 of two biological replicates, Pearson correlation coefficient is indicated on the top. f, Scatter plot of gene FS of day 15 and day 21, Pearson correlation coefficient is indicated on the top. g, Venn diagram shows the numbers of common and different depleted hits of day 15 and day 21. h, Gene Ontology (GO) analysis of common and day 21-only selected hits. GO terms are ranked from top to bottom based on P value of day 21 results using Metascape. Blue bars represent the numbers of commonly depleted hits and red bars represent the numbers of day 21-only selected hits in each GO terms.

Extended Data Fig. 5 Efficiency comparison among different types of sgRNAs.

a, Efficiency comparison across 3 types of sgRNAs, sgRNAStart targeting start codons, sgRNASD/SA targeting splice sites and sgRNAStop targeting codons of Gln (CAA, CAG), Arg (CGA) and Trp (TGG). b, Efficiency comparison between sgRNASA targeting splice acceptor sites and sgRNASD targeting splice donor sites. c, Editing efficiency comparison across 4 types (A, C, G, T) of 5’ context of sgRNA-targeted cytosine. d, Editing efficiency comparison across locations of sgRNA-targeted cytosine in AncBE4max editing window. e, Efficiency comparison across sgRNAStop targeting CAA, CAG, TGG and CGA. Boxplots are represented as follows: center line indicating the median, box limits indicating the upper and lower quartiles and whiskers indicating the 1.5x interquartile range. The numbers of sgRNAs in each category are indicated above the corresponding boxplots.

Extended Data Fig. 6 Editing kinetics and effect on cell proliferation by AncBE4max or Cas9 targeting high-copy loci in HeLa cells.

a and d, C-to-T editing frequency of sgRNAs targeting high-copy-number SDHA (a) and TRIP13 (d) loci in HeLa cells detected by sanger sequencing. Sorting of the sgRNA-expressing cells was conducted 2 days post-transduction (denoted as day 0), and cells were harvested on days 0, 3 and 6. The green lines indicated the editing frequency of targeted cytosine for gene knockouts, and the other blank lines indicated the editing frequency of cytosine locating in the activity windows of AncBE4max. b, Schematic showing the genomic region of a highly amplified gene TRIP13 and the targeting sites of sgRNAs selected from BARBEKO (sgRNAStop-1 and sgRNAStop-2) or TKO (sgRNA-7 and sgRNA-8) libraries. c, Effects of indicated sgRNAs targeting TRIP13 on cell proliferation in HeLa cells. 4 sgRNAs were individually delivered into AncBE4max- and Cas9-expressing cells for validation. Data are presented as the mean ± s.d. of 3 independent experiments. sgRNAAAVS1 served as negative control. P values represent comparisons with sgRNAAAVS1 at the end point (day 15), and was calculated using a one-tailed Student’s t-test and adjusted using the Benjamini–Hochberg method, ***p < 0.001.

Extended Data Fig. 7 Comparisons of BARBEKO screening in RPE1 cells with CRISPR-KO based on gold-standard reference gene sets and essential GO terms.

a-c, ROC analysis for screens based on reference gene sets with 349 (a), 513 (b) and 662 (c) essential genes. d, Boxplots showing the distribution of gene FS of 349 essential, 703 non-essential and other genes in conventional CRISPR-KO, high-MOI CRISPR-KO or BARBEKO screening in wild-type or TP53-/- RPE1 cells. Boxplots are represented as follows: center line indicating the median, box limits indicating the upper and lower quartiles, whiskers indicating the 1.5x interquartile range and all other observed points plotting as outliers. e, Gene lists were obtained from Gene Ontology, and the numbers of genes are indicated at the top left. Boxplots are represented the same as above. Screening data from publications was re-analyzed by ZFC algorithm for comparisons.

Extended Data Fig. 8 Fitness screen of TP53-/- RPE1 cells by BARBEKO at a high MOI.

a, Volcano plot showing the overall outcomes of BARBEKO screen in TP53-/- background at a MOI of ~ 3. The top 5 depleted and enriched genes together with top-ranking Hippo genes are labelled. b, Scatter plot showing the distribution of gene rankings of 4 categories. Gene rankings of BARBEKO screens are calculated according to the gene FS from small to large. Essential genes and ribosomal genes are extracted from reference gene sets, while non-targeting and AAVS1 controls are composed of 3 corresponding sgRNAs by randomly sampling. The results are presented as the mean ± s.d., and the mean value of gene rankings of each categories is highlighted in red.

Extended Data Fig. 9 Comparing the depleted hits of BARBEKO and CRISPR-KO screens in RPE1 cells.

a, Venn diagram showing the numbers of commonly and differently selected hits of BARBEKO and CRISPR-KO screens. b-d, GO enrichment analysis by Metascape of common essential hits in wild-type cells but not in TP53-/- cells (b), unique essential hits of BARBEKO screen in wild-type cells (c) and CRISPR-KO screen in wild-type cells (d). GO terms are ranked by the value of FDR from small to large. The size of circle represents the number of genes belonging to each term.

Extended Data Fig. 10 Perturbations on different sites of the CDKN1A locus caused variant phenotypes.

a, Schematic shows genomic region of CDKN1A and the targeting sites of sgRNAs selected from BARBEKO library (sgRNAStop-1) and newly designed sgRNAs (sgRNAStop2-4 and sgRNASD). b-c, Effects of indicated sgRNAs targeting CDKN1A on cell proliferation in AncBE4max- (b) and Cas9-expressing (c) RPE1 cells. sgRNAAAVS1 served as negative control. Data are presented as the mean ± s.d. of 3 independent experiments. P values represent comparisons with sgRNAAAVS1 at the end point (day 15), calculated using a one-tailed Student’s t-test and adjusted using the Benjamini–Hochberg method, **p < 0.01, ***p < 0.001.

Supplementary information

Supplementary Information

Supplementary Figs. 1–8.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–3. The sequences of sgRNAs, primers and nontargeting sgRNAs.

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Unprocessed western blots.

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Statistical source data.

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Statistical source data.

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Statistical source data.

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Xu, P., Liu, Z., Liu, Y. et al. Genome-wide interrogation of gene functions through base editor screens empowered by barcoded sgRNAs. Nat Biotechnol 39, 1403–1413 (2021). https://doi.org/10.1038/s41587-021-00944-1

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