{"doi":"10.1101/2021.01.25.427807","title":"Seq-Scope: Submicrometer-resolution spatial transcriptomics for single cell and subcellular studies","abstract":"Abstract Spatial barcoding technologies have the potential to reveal histological details of transcriptomic profiles; however, they are currently limited by their low resolution. Here we report Seq-Scope, a spatial barcoding technology with a resolution almost comparable to an optical microscope. Seq-Scope is based on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides using an Illumina sequencing-by-synthesis platform. The resulting clusters annotated with spatial coordinates are processed to expose RNA-capture moiety. These RNA-capturing barcoded clusters define the pixels of Seq-Scope that are approximately 0.5-1 μm apart from each other. From tissue sections, Seq-Scope visualizes spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon) and inflammation-fibrosis (injured liver) axes, cellular components including single cell types and subtypes, and subcellular architectures of nucleus, cytoplasm and mitochondria. Seq-scope is quick, straightforward and easy-to-implement, and makes spatial single cell analysis accessible to a wide group of biomedical researchers.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2021,"id":213825,"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":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9608,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":562749,"name":"Jingyue Xi","orcid":null,"position":1,"is_corresponding":false},{"id":318828,"name":"Sung-Rye Park","orcid":null,"position":2,"is_corresponding":false},{"id":615670,"name":"Jer-En Hsu","orcid":"0000-0002-2968-1853","position":3,"is_corresponding":false},{"id":273632,"name":"Myungjin Kim","orcid":"0000-0002-3144-5235","position":4,"is_corresponding":false},{"id":12925,"name":"Goo Jun","orcid":"0000-0003-0891-0204","position":5,"is_corresponding":false},{"id":24782,"name":"Hyun Min Kang","orcid":"0000-0002-3631-3979","position":6,"is_corresponding":false},{"id":240235,"name":"Jun Hee Lee","orcid":"0000-0002-2200-6011","position":7,"is_corresponding":false},{"id":273638,"name":"Chun‐Seok Cho","orcid":"0000-0002-9589-5745","position":0,"is_corresponding":true}],"reference_count":65,"raw_metadata":null,"created_at":"2026-07-18T23:52:41.672172Z","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":[]}