{"doi":"10.1093/narmme/ugag006","title":"Systematic evaluation of long- and short-read RNA-seq for human peripheral blood","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>RNA sequencing (RNA-seq) technologies enable comprehensive transcriptomic profiling, yet systematic comparisons using identical biological samples remain limited. Here, we performed a multi-faceted comparison of long-read (PacBio) and short-read (Illumina) RNA-seq using the same RNA from peripheral blood cells of four healthy donors. Unlike prior studies that aggregate datasets from different sources, this study evaluates platform-dependent performance across gene expression, transcript variants, fusion genes, primary microRNAs (pri-miRNAs), and immune receptor complementarity-determining region 3 (CDR3) regions using widely available software, highlighting both reproducibility and accessibility. Long-read sequencing outperformed short-read sequencing in detecting complex alternative splicing events, novel transcript isoforms, and full-length immune receptor sequences, particularly immunoglobulin heavy chains, enhancing clonotype resolution. Both platforms captured largely overlapping pri-miRNAs and CDR3 sequences, but each also detected unique elements, demonstrating that total RNA can serve as a proxy for these specialized features when dedicated kits are not used. Short-read sequencing retained superior quantification accuracy for highly expressed genes and stronger concordance with microarray data. Collectively, our findings reveal the complementary strengths of long- and short-read RNA-seq and provide a practical framework for systematic, side-by-side comparison of transcriptomic features, emphasizing the benefits of using the same input material and standard analysis pipelines.</jats:p>","journal":"NAR Molecular Medicine","year":2026,"id":609085,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1565170,"name":"Alessandro Nasti","orcid":"0000-0003-2550-2317","position":1,"is_corresponding":false},{"id":920615,"name":"Hikari Okada","orcid":"0009-0009-7218-9619","position":2,"is_corresponding":false},{"id":1565171,"name":"Yumie Takeshita","orcid":"0000-0002-0475-1931","position":3,"is_corresponding":false},{"id":1565172,"name":"Taka-Aki Sato","orcid":null,"position":4,"is_corresponding":false},{"id":1565173,"name":"Takeshi Urabe","orcid":null,"position":5,"is_corresponding":false},{"id":461654,"name":"Toshinari Takamura","orcid":"0000-0002-4393-3244","position":6,"is_corresponding":false},{"id":1565174,"name":"Takuro Tamura","orcid":null,"position":7,"is_corresponding":false},{"id":1394996,"name":"Atsushi Tajima","orcid":"0000-0001-6808-5491","position":8,"is_corresponding":false},{"id":1565175,"name":"Kenichi Matsubara","orcid":null,"position":9,"is_corresponding":false},{"id":597157,"name":"Shuichi Kaneko","orcid":"0000-0001-7113-3319","position":10,"is_corresponding":false},{"id":920617,"name":"Sadahiro Iwabuchi","orcid":"0000-0003-0434-3054","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Systematic evaluation of long- and short-read RNA-seq for human peripheral blood","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>RNA sequencing (RNA-seq) technologies enable comprehensive transcriptomic profiling, yet systematic comparisons using identical biological samples remain limited. Here, we performed a multi-faceted comparison of long-read (PacBio) and short-read (Illumina) RNA-seq using the same RNA from peripheral blood cells of four healthy donors. Unlike prior studies that aggregate datasets from different sources, this study evaluates platform-dependent performance across gene expression, transcript variants, fusion genes, primary microRNAs (pri-miRNAs), and immune receptor complementarity-determining region 3 (CDR3) regions using widely available software, highlighting both reproducibility and accessibility. Long-read sequencing outperformed short-read sequencing in detecting complex alternative splicing events, novel transcript isoforms, and full-length immune receptor sequences, particularly immunoglobulin heavy chains, enhancing clonotype resolution. Both platforms captured largely overlapping pri-miRNAs and CDR3 sequences, but each also detected unique elements, demonstrating that total RNA can serve as a proxy for these specialized features when dedicated kits are not used. Short-read sequencing retained superior quantification accuracy for highly expressed genes and stronger concordance with microarray data. Collectively, our findings reveal the complementary strengths of long- and short-read RNA-seq and provide a practical framework for systematic, side-by-side comparison of transcriptomic features, emphasizing the benefits of using the same input material and standard analysis pipelines.</jats:p>","is_dataset_classified":null,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"41635783","pmcid":"PMC12862385","openalex_id":"https://openalex.org/W7125224777","authors":[],"funders":[{"funder_name":"Kanazawa University","grant_id":"","title":null}],"total_grants":1,"fwci":10.441,"citation_percentile":0.9711078,"influential_citations":0,"citation_trend":[{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.1093/narmme/ugag006","host_type":"journal"},{"url":"https://doi.org/10.1093/narmme/ugag006","host_type":"publisher"},{"url":"https://academic.oup.com/narmolmed/advance-article-pdf/doi/10.1093/narmme/ugag006/66473862/ugag006.pdf","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/41635783","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12862385","host_type":"repository"},{"url":"https://kanazawa-u.repo.nii.ac.jp/records/2004011","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC12862385","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC12862385?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Cancer-related molecular mechanisms research","MicroRNA in disease regulation","Single-cell and spatial transcriptomics"],"mesh_terms":[],"keywords":["Transcriptome","microRNA","Alternative splicing","RNA","Peripheral blood","splice","Immune system","Gene"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-31T03:01:44.151966Z","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":[]}