{"doi":"10.1101/2020.08.27.266627","title":"Efficient generation of endogenous protein reporters for mouse preimplantation embryos","abstract":"Summary Fluorescent proteins and epitope tags can reveal protein localization in cells and animals. However, the large size of many tags hinders efficient genome targeting. Accordingly, many studies have relied on characterizing overexpressed proteins, which might not recapitulate endogenous protein activities. We present two approaches for higher throughput production of endogenous protein reporters. Our first approach makes use of a split fluorescent protein mNeonGreen2 (mNG2). Knock-in of a small portion of the mNG2 gene, in frame with gene coding regions of interest was highly efficient in embryos, eliminating the need to establish mouse lines. When complemented by the larger portion of the mNG2 gene, fluorescence was reconstituted and endogenous protein localization faithfully reported in living embryos. However, we report a threshold of detection using this approach. By contrast, the V5 epitope enabled high efficiency and higher sensitivity protein reporting. We describe complementary advantages and prospective applications of these two approaches. Highlights Split fluorescent protein for in vivo protein localization in living embryos V5 tagging for in vivo localization of low abundance proteins Bypassing the need for founder mouse lines for preimplantation studies Guidelines and strategies for implementation and prospective applications","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":130823,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9493,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":516219,"name":"Amy Ralston","orcid":"0000-0003-3755-8262","position":1,"is_corresponding":false},{"id":584051,"name":"Dan O’Hagan","orcid":null,"position":0,"is_corresponding":true}],"reference_count":43,"raw_metadata":null,"created_at":"2026-07-18T23:15:56.698770Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}