AbstractThe systematic determination of protein function is a key goal of modern biology, but remains challenging with current approaches. Here we present ORFtag, a versatile, cost-effective and highly efficient method for the massively parallel tagging and functional interrogation of proteins at the proteome scale.

。在这里，我们介绍了ORFtag，这是一种多功能，经济高效的方法，用于在蛋白质组规模上对蛋白质进行大规模并行标记和功能询问。

ORFtag uses retroviral vectors bearing a promoter, peptide tag and splice donor to generate fusions between the tag and endogenous open reading frames (ORFs). We demonstrate the utility of ORFtag through functional screens for transcriptional activators, repressors and posttranscriptional regulators in mouse embryonic stem cells.

。我们通过功能筛选小鼠胚胎干细胞中的转录激活因子，阻遏因子和转录后调节因子来证明ORFtag的实用性。

Each screen recovers known and identifies new regulators, including long ORFs inaccessible by other methods. Among other hits, we find that Zfp574 is a highly selective transcriptional activator and that oncogenic fusions often function as transactivators..

每个屏幕恢复已知的并识别新的监管机构，包括其他方法无法访问的长ORF。。。

MainProteins are central to almost all cellular processes, but their biochemical diversity often hinders systematic studies of protein function. Genetic loss-of-function screens—such as CRISPR–Cas9 and CRISPRi screens—are powerful methods for identifying genes involved in specific cellular processes, but typically do not provide direct insight into protein function1.

主要蛋白质是几乎所有细胞过程的核心，但它们的生化多样性往往阻碍蛋白质功能的系统研究。遗传功能丧失筛选（例如CRISPR-Cas9和CRISPRi筛选）是鉴定参与特定细胞过程的基因的有力方法，但通常不能直接了解蛋白质功能1。

They are also often hampered by functional redundancy and the essentiality of many genes. Conversely, sufficiency-based assays allow the direct determination of protein function2,3. However, current systematic methods rely on the delivery and expression of open reading frame (ORF) libraries (ORFeomes)4,5, which are not only costly and difficult to maintain, but also tend to favor shorter ORFs (<5 kb) due to limitations in DNA synthesis, cloning, viral packaging and delivery into cells2.

它们还经常受到功能冗余和许多基因的重要性的阻碍。相反，基于充分性的测定可以直接测定蛋白质功能2,3。然而，目前的系统方法依赖于开放阅读框（ORF）文库（ORFeomes）4,5的传递和表达，这不仅昂贵且难以维护，而且由于DNA合成，克隆，病毒包装和递送到细胞中的限制，倾向于支持较短的ORF（<5kb）。

Engineering of native gene locations can overcome these limitations6 and recent CRISPR–Cas9 techniques for systematic gene tagging have scaled to as many as 1,300 genes7,8,9,10,11,12,13, but achieving genome-wide coverage remains challenging. Here we present ORFtag, a versatile approach that allows for the massive, parallel and proteome-scale tagging and overexpression of endogenous genomically encoded ORFs.ResultsORFtag overviewORFtag is based on insertional elements such as retroviral vectors containing a constitutively active promoter, a selection gene and a functional tag of interest followed by a splice donor sequence (Fig.

天然基因位置的工程化可以克服这些限制6，最近用于系统基因标记的CRISPR-Cas9技术已经扩展到多达1300个基因7,8,9,10,11,12,13，但实现全基因组覆盖仍然具有挑战性。在这里，我们介绍了ORFtag，这是一种多功能方法，可以对内源性基因组编码的ORF进行大规模，平行和蛋白质组规模的标记和过表达。结果ORFTAG概述ORFTAG基于插入元件，例如含有组成型活性启动子，选择基因和感兴趣的功能标签的逆转录病毒载体，然后是剪接供体序列（图）。

1a and Extended Data Fig. 1). Upon large-scale transduction of cultured cells, ORFtag cassettes randomly integrate into the genome and drive the transcription of nearby endogenous gene loci by splicing of the functional tag to splice-acceptor sites downstream of the integration site, creating near N-.

1a和扩展数据图1）。在大规模转导培养细胞后，ORFtag盒随机整合到基因组中，并通过将功能标签剪接到整合位点下游的剪接受体位点来驱动附近内源基因位点的转录，从而产生近N-。

Data availability

数据可用性

The raw sequencing data generated in this study are available from the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE225972. These data were aligned to the mouse reference genome (mm10) available at https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001635.20/.

这项研究中产生的原始测序数据可从Gene Expression Omnibus（GEO）获得(https://www.ncbi.nlm.nih.gov/geo/)登记号为GSE225972。这些数据与小鼠参考基因组（mm10）进行了比对https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001635.20/.

The annotations for the mouse genome were sourced from GENCODE (v.M25, https://www.gencodegenes.org/mouse/release_M25.html) and Ensembl (v.100, https://nov2020.archive.ensembl.org/Mus_musculus/Info/Annotation). Previously published datasets referenced and used in this study are detailed in the Methods section and are available as follows: GEO accession number GSE99971 (RNA-seq)23; list of transcription factor genes24; list of genes containing activation or repressive domains2; list of hits in the ORFeome activator screen25; list of genes containing RNA-binding domains26; list of fusion oncoproteins27; human–mouse orthologs28 and manually curated Pfam-A domains.

小鼠基因组的注释来自GENCODE（v.M25，https://www.gencodegenes.org/mouse/release_M25.html)和Ensembl（v.100，https://nov2020.archive.ensembl.org/Mus_musculus/Info/Annotation)。本研究中引用和使用的先前发布的数据集在方法部分有详细说明，可获得如下：GEO登录号GSE99971（RNA-seq）23；转录因子基因列表24；包含激活或抑制域2的基因列表；ORFeome activator屏幕中的点击列表25；含有RNA结合域的基因列表26；融合癌蛋白列表27；人-小鼠直系同源物28和手动策划的Pfam-A域。

No restrictions on data availability apply. Source data are provided with this paper..

数据可用性不受限制。本文提供了源数据。。

Code availability

代码可用性

All custom scripts that were generated for this study were made publicly available at https://github.com/vloubiere/ORFtag_2024.

为这项研究生成的所有自定义脚本都可以在https://github.com/vloubiere/ORFtag_2024.

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Download referencesAcknowledgementsWe thank the IMP/IMBA/GMI and the Max Perutz Laboratories core facilities, especially flow cytometry teams, for providing outstanding support. F.N. was supported by a Boehringer Ingelheim Fonds PhD fellowship. V.L. was supported by Human Frontier Science Program (grant no.

下载参考文献致谢我们感谢IMP/IMBA/GMI和Max Perutz实验室核心设施，特别是流式细胞仪团队提供的出色支持。F、 。五、 L.得到了人类前沿科学计划（批准号：。

LT000926/2020) and European Molecular Biology Organisation (grant no. 790-2019) postdoctoral fellowships. Research in the Ameres group is supported by the European Union/European Research Council (ERC) (RiboTrace, grant no. CoG-866166) and the Austrian Science Fund (FWF, grant no. 10.55776/F80). Research in the Stark group is supported by the Austrian Science Fund (FWF, grant nos.

LT000926/2020）和欧洲分子生物学组织（批准号790-2019）博士后奖学金。Ameres小组的研究得到了欧盟/欧洲研究理事会（ERC）（RiboTrace，批准号CoG-866166）和奥地利科学基金（FWF，批准号10.55776/F80）的支持。斯塔克小组的研究得到了奥地利科学基金（FWF）的支持。

10.55776/P29613, 10.55776/P33157, 10.55776/P36971 and 10.55776/PAT3564423). Basic research at the IMP is supported by Boehringer Ingelheim GmbH and the Austrian Research Promotion Agency (FFG, grant no. FO999902549). Research in Brennecke group is funded by the Austrian Academy of Sciences and the European Community (grant no.

。IMP的基础研究得到了勃林格殷格翰有限公司和奥地利研究促进局（FFG，批准号FO99902549）的支持。布伦内克集团的研究由奥地利科学院和欧洲共同体资助（批准号：。

ERC-2015-CoG-682181). NGS was done at the Vienna Biocenter Core Facilities GmbH Next-Generation Sequencing Unit. For the purpose of Open Access, we have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.Author informationAuthor notesRamesh YelagandulaPresent address: Laboratory of Epigenetics, Cell Fate and Disease, Centre for DNA Fingerprinting and Diagnostics, Hyderabad, IndiaNina FaschingPresent address: QUANTRO Therapeutics GmbH, Vienna, AustriaThese authors contributed equally: Filip Nemčko, Moritz Himmelsbach.Authors and AffiliationsResearch Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, AustriaFilip Nemčko, Vincent Loubiere, Michaela Pagani & Alexander StarkVi.

ERC-2015-CoG-682181）。NGS是在维也纳生物中心核心设施有限公司下一代测序单元完成的。出于开放获取的目的，我们已将CC公共版权许可证应用于本次提交产生的任何作者接受的手稿版本。作者信息作者注释Ramesh YelagandulaPresent地址：表观遗传学，细胞命运和疾病实验室，DNA指纹和诊断中心，印度海得拉巴FaschingPresent地址：QUANTRO Therapeutics GmbH，Vienna，Australia这些作者做出了同样的贡献：Filip Nemčko，Moritz Himmelsbach。作者和附属机构分子病理学研究所（IMP），维也纳生物中心（VBC），维也纳，AustriaFilip Nemčko，Vincent Loubiere，Michaela Pagani＆Alexander StarkVi。

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PubMed Google ScholarUlrich EllingView作者出版物您也可以在

PubMed Google ScholarAlexander StarkView author publicationsYou can also search for this author in

PubMed Google ScholarAlexander StarkView作者出版物您也可以在

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PubMed Google ScholarStefan L.AmeresView作者出版物您也可以在

PubMed Google ScholarContributionsF.N. and M.H. implemented the ORFtag method and protocols. F.N. performed the activator screen, M.H. the PTGR screen and R.Y. and V.L. the repressor screen. F.N., M.H. and R.Y. performed candidate validation experiments. F.N. performed all Zfp574 follow-up experiments.

PubMed谷歌学术贡献。N、 和M.H.实施了ORFtag方法和协议。F、 N.进行了激活剂筛选，M.H.进行了PTGR筛选，R.Y.和V.L.进行了阻遏物筛选。F、 N.，M.H.和R.Y.进行了候选验证实验。F、 N.进行了所有Zfp574后续实验。

V.L., F.N. and A.S. developed the bioinformatic pipeline. V.L. and F.N. performed NGS data and downstream analyses. N.F. and M.P. helped with the experiments. U.E. and S.L.A conceptualized the ORFtag approach. S.L.A., A.S., U.E. and J.B. coordinated and supervised the work. All authors wrote the paper.Corresponding authorsCorrespondence to.

五、 L.，F.N.和A.S.开发了生物信息学管道。五、 L.和F.N.进行了NGS数据和下游分析。N、 F.和M.P.帮助进行了实验。U、 E.和S.L.A将ORFtag方法概念化。S、 洛杉矶、美国、阿联酋和J.B.协调并监督了这项工作。所有作者都写了这篇论文。通讯作者通讯。

Julius Brennecke, Ulrich Elling, Alexander Stark or Stefan L. Ameres.Ethics declarations

朱利叶斯·布伦内克（Julius Brennecke）、乌尔里希·埃林（Ulrich Elling）、亚历山大·斯塔克（Alexander Stark）或斯特凡·L·阿米尔斯（Stefan L.Ameres）。道德宣言

Competing interests

相互竞争的利益

S.L.A. is cofounder, advisor and member of the board of QUANTRO Therapeutics GmbH. U.E. is cofounder of JLP Health and VIVERITA Therapeutics, Managing Director of VIVERITA Discovery and advisor to TANGO Therapeutics. N.F. is employed by QUANTRO Therapeutics GmbH. The other authors declare no competing interests..

S、 L.A.是QUANTRO Therapeutics GmbH的联合创始人、顾问和董事会成员。U.E.是JLP Health和VIVERITA Therapeutics的联合创始人，VIVERITA Discovery的常务董事和TANGO Therapeutics的顾问。N、 F.受雇于QUANTRO Therapeutics GmbH。其他作者声明没有利益冲突。。

Peer review

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Peer review information

同行评审信息

Nature Methods thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Lei Tang, in collaboration with the Nature Methods team.

Nature Methods感谢匿名审稿人对这项工作的同行评审做出的贡献。主要处理编辑：Lei Tang，与Nature Methods团队合作。

Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Extended dataExtended Data Fig. 1 Overview of the ORFtag screening method.a, Detailed schematic illustrating Activator and Repressor ORFtag screens (top) and PTGR ORFtag screen (bottom).

Additional informationPublisher的注释Springer Nature在已发布的地图和机构隶属关系中的管辖权主张方面保持中立。扩展数据扩展数据图1 ORFtag筛选方法概述。a，详细示意图，说明激活剂和阻遏物ORFtag筛选（顶部）和PTGR ORFtag筛选（底部）。

b, Graphical depiction of the ORFtag screening protocol. c, Visual representation of the inverse PCR followed by next-generation sequencing (iPCR-NGS) protocol.Extended Data Fig. 2 Validation of the ORFtag approach.a, Percentage of in-frame products for both background and selected samples across three reading frames based on ORFtag Activator screens performed with each of the three viruses separately.

b、 ORFtag筛选协议的图形描述。c、 反向PCR的视觉表示，然后是下一代测序（iPCR NGS）方案。。

b, Distribution of sequences right downstream of the ORFtag cassette for background (left) and selected samples (right) based on ORFtag-targeted RNA-seq. Identity of spliced exons is shown below. c, Proportion of in-frame products for exon-spliced products from (b). d, Schematic of in-frame splicing events as determined by Sanger sequencing of five clones expressing ORFtag cassettes encoding Frame1 (red) or Frame2 (green).

b、 基于ORFtag靶向RNA-seq的背景（左）和选定样品（右）的ORFtag盒右下游序列的分布。剪接外显子的身份如下所示。c、 来自（b）的外显子剪接产物的框内产物比例。d、 通过Sanger测序五个表达编码Frame1（红色）或Frame2（绿色）的ORFtag盒的克隆确定的框内剪接事件的示意图。

e, GFP expression and the proportion of GFP-positive cells are compared between the Activator reporter cell line alone and in cases of ORFtag screening with TetR (with recruitment) or λN (with no recruitment) functional tags. f, Density plots represent GFP levels in pre-sorted GFP positive cells, derived from an Activator ORFtag screen, over a 5-day period in the presence (red) or absence (blue) of Doxycycline.

e、 比较单独的激活剂报告细胞系和使用TetR（有募集）或λN（无募集）功能标签进行ORFtag筛选的情况下，GFP表达和GFP阳性细胞的比例。f、 密度图表示在存在（红色）或不存在（蓝色）强力霉素的情况下，在5天的时间内，来自激活剂ORFtag筛选的预先分选的GFP阳性细胞中的GFP水平。

Parental non-activated reporter cell line is shown as control (grey).Extended Data Fig. 3 Analysis of ORFtag hits.a, STRING protein-protein interaction networks between activator/ repressor/ PTGR hits. Node c.

亲本未激活的报告细胞系显示为对照（灰色）。扩展数据图3 ORFtag命中的分析。a，激活剂/阻遏物/PTGR命中之间的STRING蛋白质-蛋白质相互作用网络。节点c。

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Reprints and permissionsAbout this articleCite this articleNemčko, F., Himmelsbach, M., Loubiere, V. et al. Proteome-scale tagging and functional screening in mammalian cells by ORFtag.

转载和许可本文引用本文Nemčko，F.，Himmelsbach，M.，Loubiere，V。等人。通过ORFtag在哺乳动物细胞中进行蛋白质组规模标记和功能筛选。

Nat Methods (2024). https://doi.org/10.1038/s41592-024-02339-xDownload citationReceived: 25 September 2023Accepted: 10 June 2024Published: 05 July 2024DOI: https://doi.org/10.1038/s41592-024-02339-xShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

Nat方法（2024）。https://doi.org/10.1038/s41592-024-02339-xDownload引文接收日期：2023年9月25日接收日期：2024年6月10日发布日期：2024年7月5日OI：https://doi.org/10.1038/s41592-024-02339-xShare本文与您共享以下链接的任何人都可以阅读此内容：获取可共享链接对不起，本文目前没有可共享的链接。。

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Genetic mappingHigh-throughput screeningMolecular engineeringSynthetic biology

遗传作图高通量筛选分子工程合成生物学