<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Vallejo J</submitter><funding>NCATS NIH HHS</funding><funding>National Institutes of Health Grant</funding><funding>NIAID NIH HHS</funding><funding>NHLBI NIH HHS</funding><funding>Cancer Research Institute</funding><funding>Swedish Society for Medical Research</funding><pagination>193</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9434837</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>20(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Cryopreserved peripheral blood mononuclear cells (PBMCs) are frequently collected and provide disease- and treatment-relevant data in clinical studies. Here, we developed combined protein (40 antibodies) and transcript single-cell (sc)RNA sequencing (scRNA-seq) in PBMCs.&lt;h4>Results&lt;/h4>Among 31 participants in the Women's Interagency HIV Study (WIHS), we sequenced 41,611 cells. Using Boolean gating followed by Seurat UMAPs (tool for visualizing high-dimensional data) and Louvain clustering, we identified 50 subsets among CD4+ T, CD8+ T, B, NK cells, and monocytes. This resolution was superior to flow cytometry, mass cytometry, or scRNA-seq without antibodies. Combined protein and transcript scRNA-seq allowed for the assessment of disease-related changes in transcriptomes</pubmed_abstract><journal>BMC biology</journal><pubmed_title>Combined protein and transcript single-cell RNA sequencing in human peripheral blood mononuclear cells.</pubmed_title><pmcid>PMC9434837</pmcid><funding_grant_id>R01 HL148094</funding_grant_id><funding_grant_id>P30 AI050410</funding_grant_id><funding_grant_id>U01-AI-103390</funding_grant_id><funding_grant_id>K01 HL137557</funding_grant_id><funding_grant_id>U01-AI-034989</funding_grant_id><funding_grant_id>U01 HL146204</funding_grant_id><funding_grant_id>U01 HL146202</funding_grant_id><funding_grant_id>R35 HL145241</funding_grant_id><funding_grant_id>R01 HL140976</funding_grant_id><funding_grant_id>P01 HL136275</funding_grant_id><funding_grant_id>R01 HL126543</funding_grant_id><funding_grant_id>U01 AI103408</funding_grant_id><funding_grant_id>R01 HL121697</funding_grant_id><funding_grant_id>P30 AI027767</funding_grant_id><funding_grant_id>R01 HL134236</funding_grant_id><funding_grant_id>U01 AI034989</funding_grant_id><funding_grant_id>U01 AI031834</funding_grant_id><funding_grant_id>R35-HL-145241, R01-HL-121697, R01-HL-148094</funding_grant_id><funding_grant_id>UL1 TR000004</funding_grant_id><funding_grant_id>P30 AI050409</funding_grant_id><funding_grant_id>U01 AI103390</funding_grant_id><funding_grant_id>U01-AI-103408</funding_grant_id><funding_grant_id>R01-HL-126543, 5R01-HL-126543-05, 5R01-HL-140976-02, R01-HL-148094-01, R01-HL-148094</funding_grant_id><funding_grant_id>K01-HL-137557</funding_grant_id><funding_grant_id>P01-KL-136275, R01-HL-134236</funding_grant_id><pubmed_authors>Durant CP</pubmed_authors><pubmed_authors>Lanier LL</pubmed_authors><pubmed_authors>Hedrick CC</pubmed_authors><pubmed_authors>Alimadadi A</pubmed_authors><pubmed_authors>Ghosheh Y</pubmed_authors><pubmed_authors>Ofotokun I</pubmed_authors><pubmed_authors>Vallejo J</pubmed_authors><pubmed_authors>Pattarabanjird T</pubmed_authors><pubmed_authors>Shemesh A</pubmed_authors><pubmed_authors>Roy P</pubmed_authors><pubmed_authors>Weber KM</pubmed_authors><pubmed_authors>Tracy RP</pubmed_authors><pubmed_authors>Armstrong Suthahar SS</pubmed_authors><pubmed_authors>Heath SL</pubmed_authors><pubmed_authors>Adimora AA</pubmed_authors><pubmed_authors>Landay AL</pubmed_authors><pubmed_authors>McNamara CA</pubmed_authors><pubmed_authors>Gulati R</pubmed_authors><pubmed_authors>Tien PC</pubmed_authors><pubmed_authors>Saigusa R</pubmed_authors><pubmed_authors>Suryawanshi V</pubmed_authors><pubmed_authors>Ley K</pubmed_authors><pubmed_authors>Hanna DB</pubmed_authors><pubmed_authors>Hodis HN</pubmed_authors><pubmed_authors>Ehinger E</pubmed_authors><pubmed_authors>Lazar JM</pubmed_authors><pubmed_authors>Mack WJ</pubmed_authors><pubmed_authors>Kaplan RC</pubmed_authors></additional><is_claimable>false</is_claimable><name>Combined protein and transcript single-cell RNA sequencing in human peripheral blood mononuclear cells.</name><description>&lt;h4>Background&lt;/h4>Cryopreserved peripheral blood mononuclear cells (PBMCs) are frequently collected and provide disease- and treatment-relevant data in clinical studies. Here, we developed combined protein (40 antibodies) and transcript single-cell (sc)RNA sequencing (scRNA-seq) in PBMCs.&lt;h4>Results&lt;/h4>Among 31 participants in the Women's Interagency HIV Study (WIHS), we sequenced 41,611 cells. Using Boolean gating followed by Seurat UMAPs (tool for visualizing high-dimensional data) and Louvain clustering, we identified 50 subsets among CD4+ T, CD8+ T, B, NK cells, and monocytes. This resolution was superior to flow cytometry, mass cytometry, or scRNA-seq without antibodies. Combined protein and transcript scRNA-seq allowed for the assessment of disease-related changes in transcriptomes</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Sep</publication><modification>2025-04-19T18:51:36.958Z</modification><creation>2025-04-19T18:51:36.958Z</creation></dates><accession>S-EPMC9434837</accession><cross_references><pubmed>36045343</pubmed><doi>10.1186/s12915-022-01382-4</doi></cross_references></HashMap>