{"doi":"10.1101/2020.03.12.989806","title":"Sensitive spatial genome wide expression profiling at cellular resolution","abstract":"Abstract The precise spatial localization of molecular signals within tissues richly informs the mechanisms of tissue formation and function. Previously, we developed Slide-seq, a technology which enables transcriptome-wide measurements with 10-micron spatial resolution. Here, we report new modifications to Slide-seq library generation, bead synthesis, and array indexing that markedly improve the mRNA capture sensitivity of the technology, approaching the efficiency of droplet-based single-cell RNAseq techniques. We demonstrate how this modified protocol, which we have termed Slide-seqV2, can be used effectively in biological contexts where high detection sensitivity is important. First, we deploy Slide-seqV2 to identify new dendritically localized mRNAs in the mouse hippocampus. Second, we integrate the spatial information of Slide-seq data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex. The combination of near-cellular resolution and high transcript detection will enable broad utility of Slide-seq across many experimental contexts.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":118673,"datarank":2.0597027277602904,"base_score":3.8918202981106265,"endowment":3.8918202981106265,"self_citation_contribution":0.5837730447165941,"citation_network_contribution":1.4759296830436963,"self_endowment_contribution":0.5837730447165941,"citer_contribution":1.4759296830436963,"corpus_percentile":null,"corpus_rank":null,"citation_count":48,"citer_count":43,"citers_with_citation_signal":40,"citers_with_endowment":40,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9494,"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":35220,"name":"Evan Murray","orcid":"0000-0002-9195-7478","position":1,"is_corresponding":false},{"id":551774,"name":"Pawan Kumar","orcid":"0000-0002-4539-9241","position":2,"is_corresponding":false},{"id":106181,"name":"Jilong Li","orcid":"0000-0002-0004-8464","position":3,"is_corresponding":false},{"id":2279,"name":"Jamie L. Marshall","orcid":"0000-0002-2364-391X","position":4,"is_corresponding":false},{"id":551775,"name":"Daniela Di Bella","orcid":"0000-0003-0912-5136","position":5,"is_corresponding":false},{"id":2734,"name":"Paola Arlotta","orcid":"0000-0003-2184-2277","position":6,"is_corresponding":false},{"id":3628,"name":"Evan Z. Macosko","orcid":"0000-0002-2794-5165","position":7,"is_corresponding":false},{"id":24055,"name":"Fei Chen","orcid":"0000-0003-2308-3649","position":8,"is_corresponding":false},{"id":24050,"name":"Robert R. Stickels","orcid":"0000-0003-4326-4084","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:14:03.409507Z","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":[]}