{"doi":"10.1101/2021.04.22.440869","title":"Synergistic effect of short- and long-read sequencing on functional meta-omics","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>\n                  Real-world evaluations of metagenomic reconstructions are challenged by distinguishing reconstruction artefacts from genes and proteins present\n                  <jats:italic>in situ</jats:italic>\n                  . Here, we evaluate short-read-only, long-read-only, and hybrid assembly approaches on four different metagenomic samples of varying complexity and demonstrate how they affect gene and protein inference which is particularly relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic, and metaproteomic data to evaluate the metagenomic data-based protein predictions. Our findings pave the way for critical assessments of metagenomic reconstructions and we propose a reference-independent solution based on the synergistic effects of multi-omic data integration for the\n                  <jats:italic>in situ</jats:italic>\n                  study of microbiomes using long-read sequencing data.\n                </jats:p>","journal":null,"year":null,"id":592027,"datarank":0.13581937997458388,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.03184730289059208,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.03184730289059208,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":1,"citers_with_citation_signal":1,"citers_with_endowment":1,"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":416403,"name":"Susheel Bhanu Busi","orcid":"0000-0001-7559-3400","position":1,"is_corresponding":false},{"id":631987,"name":"Benoît J. Kunath","orcid":"0000-0002-3356-8562","position":2,"is_corresponding":false},{"id":1363068,"name":"Laura de Nies","orcid":"0000-0002-6483-7489","position":3,"is_corresponding":false},{"id":1514827,"name":"Magdalena Calusinska","orcid":"0000-0003-2270-2217","position":4,"is_corresponding":false},{"id":240209,"name":"Rashi Halder","orcid":"0000-0002-1402-1254","position":5,"is_corresponding":false},{"id":297276,"name":"Patrick May","orcid":"0000-0001-8698-3770","position":6,"is_corresponding":false},{"id":36358,"name":"Paul Wilmes","orcid":"0000-0002-6478-2924","position":7,"is_corresponding":false},{"id":734781,"name":"Cédric C. Laczny","orcid":"0000-0002-1100-1282","position":8,"is_corresponding":false},{"id":1514826,"name":"Valentina Galata","orcid":"0000-0002-4541-427X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Synergistic effect of short- and long-read sequencing on functional meta-omics","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>\n                  Real-world evaluations of metagenomic reconstructions are challenged by distinguishing reconstruction artefacts from genes and proteins present\n                  <jats:italic>in situ</jats:italic>\n                  . Here, we evaluate short-read-only, long-read-only, and hybrid assembly approaches on four different metagenomic samples of varying complexity and demonstrate how they affect gene and protein inference which is particularly relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic, and metaproteomic data to evaluate the metagenomic data-based protein predictions. Our findings pave the way for critical assessments of metagenomic reconstructions and we propose a reference-independent solution based on the synergistic effects of multi-omic data integration for the\n                  <jats:italic>in situ</jats:italic>\n                  study of microbiomes using long-read sequencing data.\n                </jats:p>","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26657633","pmcid":null,"openalex_id":"https://openalex.org/W3158976456","authors":[],"funders":[{"funder_name":"Swiss National Science Foundation","grant_id":"180241","title":"Elucidating the success of microbial biofilms and their implications for habitability and ecosystem evolution in glacial floodplain streams (ENSEMBLE)"},{"funder_name":"European Commission","grant_id":"863664","title":"Deciphering the impact of exposures from the gut microbiome-derived molecular complex in  human health and disease"}],"total_grants":2,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2022,"count":1}],"oa_status":"green","license":"cc-by","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2021/04/23/2021.04.22.440869.full.pdf","host_type":"repository"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2021/04/23/2021.04.22.440869.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2021.04.22.440869","host_type":"publisher"},{"url":"https://doi.org/10.1101/2021.04.22.440869","host_type":"repository"},{"url":"https://dx.doi.org/10.1101/2021.04.22.440869","host_type":""},{"url":"http://dx.doi.org/10.1101/2021.04.22.440869","host_type":""}],"fields_of_study":["Genomics and Phylogenetic Studies","Gut microbiota and health","Bioinformatics and Genomic Networks","0301 basic medicine","03 medical and health sciences","0206 medical engineering","02 engineering and technology"],"mesh_terms":[],"keywords":["Metagenomics","Computational biology","Microbiome","Biology","Inference","Computer science","Gene","Bioinformatics","Artificial intelligence","Genetics"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-26T11:53:36.898029Z","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":[]}