{"doi":"10.1101/2022.04.26.489601","title":"Optimized Repli-seq: Improved DNA Replication Timing Analysis by Next-Generation Sequencing","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>The human genome is divided into functional units that replicate at specific times during S-phase. This temporal program is known as replication timing (RT) and is coordinated with the spatial organization of the genome and transcriptional activity. RT is also cell type-specific, dynamically regulated during development, and alterations in RT are observed in multiple diseases. Thus, precise measure of RT is critical to understand the role of RT in gene function regulation. Distinct methods for assaying the RT program exist; however, conventional methods require thousands of cells as input, prohibiting its applicability to samples with limited cell numbers such as those from disease patients or from early developing embryos. Although single-cell analysis of RT has been developed as an alternative, these methods are low throughput and produce low resolution data. Here, we developed an improved method to measure RT genome-wide that enables high resolution analysis of low input samples. This method incorporates direct cell sorting into lysis buffer, as well as DNA fragmentation and library preparation in a single tube, resulting in higher yields, increased quality, and reproducibility with decreased costs. We also performed a systematic data processing analysis to provide standardized parameters for RT measurement. This optimized method facilitates RT analysis and will enable its application to a broad range of studies investigating the role of RT in gene expression, nuclear architecture, and disease.</jats:p>","journal":null,"year":null,"id":612641,"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":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":1577525,"name":"Claudia Trevilla-Garcia","orcid":null,"position":1,"is_corresponding":false},{"id":949877,"name":"Santiago Martinez-Cifuentes","orcid":null,"position":2,"is_corresponding":false},{"id":43143,"name":"Juan Carlos Rivera-Mulia","orcid":"0000-0002-7566-3875","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Optimized Repli-seq: Improved DNA Replication Timing Analysis by Next-Generation Sequencing","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>The human genome is divided into functional units that replicate at specific times during S-phase. This temporal program is known as replication timing (RT) and is coordinated with the spatial organization of the genome and transcriptional activity. RT is also cell type-specific, dynamically regulated during development, and alterations in RT are observed in multiple diseases. Thus, precise measure of RT is critical to understand the role of RT in gene function regulation. Distinct methods for assaying the RT program exist; however, conventional methods require thousands of cells as input, prohibiting its applicability to samples with limited cell numbers such as those from disease patients or from early developing embryos. Although single-cell analysis of RT has been developed as an alternative, these methods are low throughput and produce low resolution data. Here, we developed an improved method to measure RT genome-wide that enables high resolution analysis of low input samples. This method incorporates direct cell sorting into lysis buffer, as well as DNA fragmentation and library preparation in a single tube, resulting in higher yields, increased quality, and reproducibility with decreased costs. We also performed a systematic data processing analysis to provide standardized parameters for RT measurement. This optimized method facilitates RT analysis and will enable its application to a broad range of studies investigating the role of RT in gene expression, nuclear architecture, and disease.</jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21097893","pmcid":null,"openalex_id":"https://openalex.org/W4225141089","authors":[],"funders":[{"funder_name":"National Institutes of Health","grant_id":"3R35GM137950-04S1","title":"Regulatory elements of replication timing and 3D genome organization"},{"funder_name":"National Institutes of Health","grant_id":"1U54AG076041-01","title":"Minnesota Tissue Mapping Center for Senescent Cells"}],"total_grants":2,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"green","license":"cc-by-nc-nd","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2022/04/27/2022.04.26.489601.full.pdf","host_type":"repository"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2022/04/27/2022.04.26.489601.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2022.04.26.489601","host_type":"publisher"},{"url":"https://doi.org/10.1101/2022.04.26.489601","host_type":"repository"},{"url":"https://doi.org/10.1007/s10577-022-09703-7","host_type":""},{"url":"https://pubmed.ncbi.nlm.nih.gov/35781769","host_type":""}],"fields_of_study":["Cancer Genomics and Diagnostics","Genomics and Chromatin Dynamics","Single-cell and spatial transcriptomics","0301 basic medicine","0303 health sciences","03 medical and health sciences"],"mesh_terms":[],"keywords":["Computational biology","Genome","Replicate","Biology","Computer science","Replication (statistics)","Gene","Genetics","Mathematics","DNA Replication","DNA Replication Timing","Genome, Human","Humans","Reproducibility of Results","High-Throughput Nucleotide Sequencing","Gene Library"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-02T04:22:19.320450Z","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":[]}