{"doi":"10.17504/protocols.io.kqdg3k6xpv25/v2","title":"TIRTL-seq 96-well v2","abstract":"TIRTL-seq is a method to obtain paired TCR-sequencing information from millions of human T cells. It is based on splitting cells into 96-384 wells, preparing and sequencing TCRalpha and TCRbeta libraries from each well in miniaturized reactions, and then pairing alpha and beta chains based on co-occurrence patterns or relative frequency variations between wells. For more details about the method, please see our paper (https://www.nature.com/articles/s41592-025-02907-9). The 384-well protocol requires some automation: a non-contact liquid dispenser (we have tested Dispendix I.Dot mini/S/L and Formulatrix Mantis) and a device to transfer 1 uL between 384-well plates (we use Integra Viaflo, but many other solutions should work equally well). We have also designed a 96-well protocol with increased volumes, which does not require any automation but has lower resolution. Schematic of TIRTL-seq protocol. Briefly, a cell suspension is distributed into 384-well plates containing RT/lysis mastermix under a hydrophobic overlay using non-contact liquid dispensers. After the RT reaction, PCR I mastermix with V-segment and C-segment primers is dispensed into the same plate. The PCR I product is then diluted and transferred to the PCR II plate for indexing PCR with well-specific unique dual indices. The PCR II products are pooled by centrifugation, purified, size-selected using magnetic beads, and sequenced on an Illumina platform. Total library preparation cost is listed for one 384-well plate.","journal":null,"year":2025,"id":583012,"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":0.8545,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":618935,"name":"Allison M. Kirk","orcid":"0000-0002-4286-3678","position":1,"is_corresponding":false},{"id":1373476,"name":"Samir Adhikari","orcid":"0000-0003-0406-2498","position":2,"is_corresponding":false},{"id":43173,"name":"Balaji Sundararaman","orcid":"0000-0001-8559-1660","position":3,"is_corresponding":false},{"id":482919,"name":"Paul Thomas","orcid":"0000-0002-2420-0950","position":4,"is_corresponding":false},{"id":618933,"name":"Mikhail V. Pogorelyy","orcid":"0000-0003-0773-1204","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:58:59.653747Z","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":[]}