{"id":1025,"date":"2026-04-19T15:17:37","date_gmt":"2026-04-19T15:17:37","guid":{"rendered":"https:\/\/www.embl.org\/groups\/genomics\/?page_id=1025"},"modified":"2026-06-16T07:41:48","modified_gmt":"2026-06-16T07:41:48","slug":"single-cell-genomic-applications","status":"publish","type":"page","link":"https:\/\/www.embl.org\/groups\/genomics\/single-cell-genomic-applications\/","title":{"rendered":"Single-cell genomic applications"},"content":{"rendered":"\n<div class=\"vf-grid | vf-grid__col-1\"><div><!--[vf\/content]-->\n<div class=\"vf-content\">\n\n<p>Single-cell sequencing measures molecular profiles in individual cells, revealing cell-to-cell differences that bulk assays average out. Across laboratories, the main applications of scRNA-seq and scDNA-seq are broadly similar, since they are determined by what is being measured (RNA versus DNA). Practical differences usually come from sample preparation, platform and protocol choices, sequencing depth, and data analysis, which mainly influence sensitivity and resolution.<\/p>\n\n\n\n<div class=\"vf-grid | vf-grid__col-2\"><div><!--[vf\/content]-->\n<div class=\"vf-content\">\n\n<h2 class=\"wp-block-heading\">scRNA-seq<\/h2>\n\n\n\n<div class=\"vf-tabs\"><ul class=\"vf-tabs__list\" data-vf-js-tabs=\"true\"><li class=\"vf-tabs__item\"><a class=\"vf-tabs__link\" href=\"#vf-tabs__section-bd-rhapsody\" data-vf-js-location-nearest-activation-target=\"\">BD Rhapsody<\/a><\/li><li class=\"vf-tabs__item\"><a class=\"vf-tabs__link\" href=\"#vf-tabs__section-10x-genomics-chromium\" data-vf-js-location-nearest-activation-target=\"\">10x Genomics Chromium<\/a><\/li><li class=\"vf-tabs__item\"><a class=\"vf-tabs__link\" href=\"#vf-tabs__section-smart-seq\" data-vf-js-location-nearest-activation-target=\"\">Smart-seq<\/a><\/li><\/ul><div class=\"vf-tabs-content\" data-vf-js-tabs-content=\"true\">\n<section class=\"vf-tabs__section\" id=\"vf-tabs__section-bd-rhapsody\"><h2 class=\"vf-u-sr-only\">BD Rhapsody<\/h2>\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      Becton Dickinson Rhapsody    <\/h3>\n                <p class=\"vf-card__text\"><strong>BD Rhapsody (Becton Dickinson)<\/strong>\u00a0is a single-cell platform that captures\u00a0<strong>individual cells in microwells<\/strong>\u00a0and labels their RNA with\u00a0<strong>cell-specific barcodes<\/strong>, enabling high-throughput gene expression (and compatible multiomic) profiling while linking sequencing reads back to each cell of origin.<\/p>\n      <\/div>\n<\/article>\n\n\n\n\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      Key References    <\/h3>\n                <p class=\"vf-card__text\"><ul>\r\n \t<li>&#8220;<em><a class=\"vf-card_link\" href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-981-13-6037-4_5\">Quantitation of mRNA Transcripts and Proteins Using the BD Rhapsody\u2122 Single-Cell Analysis System<\/a><\/em>&#8220;<\/li>\r\n \t<li><strong>&#8220;<\/strong><em><a class=\"vf-card_link\" href=\"https:\/\/link.springer.com\/protocol\/10.1007\/978-1-0716-2756-3_2\">BD Rhapsody\u2122 Single-Cell Analysis System Workflow: From Sample to Multimodal Single-Cell Sequencing Data<\/a><\/em>&#8220;<\/li>\r\n<\/ul><\/p>\n      <\/div>\n<\/article>\n\n<\/section>\n\n\n\n<section class=\"vf-tabs__section\" id=\"vf-tabs__section-10x-genomics-chromium\"><h2 class=\"vf-u-sr-only\">10x Genomics Chromium<\/h2>\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      10x Genomics Chromium    <\/h3>\n                <p class=\"vf-card__text\"><strong>10x Genomics Chromium<\/strong>\u00a0is a droplet microfluidics platform that partitions single cells (or nuclei) into\u00a0<strong>barcoded Gel-beads-in-emulsion (GEMs)<\/strong>, enabling high-throughput single-cell sequencing by assigning sequencing reads back to their cell of origin via\u00a0<strong>cell barcodes<\/strong>.<\/p>\n      <\/div>\n<\/article>\n\n\n\n\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      Key References    <\/h3>\n                <p class=\"vf-card__text\"><ul>\r\n \t<li>&#8220;<a class=\"vf-card_link\" href=\"https:\/\/link.springer.com\/protocol\/10.1007\/978-1-0716-4901-5_35\"><em>Single-Cell 3\u2032 mRNA Sequencing with 10\u00d7 Chromium Gel Beads-in-Emulsion (GEM) Kits<\/em><\/a>&#8220;<\/li>\r\n \t<li>&#8220;<a class=\"vf-card_link\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/38907921\/\"><em>Sequencing: 10X Genomics 3&#8242; HT Assay for Gene Expression<\/em><\/a>&#8220;<\/li>\r\n<\/ul><\/p>\n      <\/div>\n<\/article>\n\n<\/section>\n\n\n\n<section class=\"vf-tabs__section\" id=\"vf-tabs__section-smart-seq\"><h2 class=\"vf-u-sr-only\">Smart-seq<\/h2>\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      Smart-seq    <\/h3>\n                <p class=\"vf-card__text\"><strong>Smart-seq (e.g., Smart-seq2\/3)<\/strong>\u00a0is a plate-based single-cell RNA-seq method that generates\u00a0<strong>full-length transcript<\/strong>\u00a0libraries from individual cells, providing high per-cell sensitivity (useful for isoforms and allele-specific expression) but typically at\u00a0<strong>lower throughput<\/strong>\u00a0than droplet-based platforms.<\/p>\n      <\/div>\n<\/article>\n\n\n\n\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      Key References    <\/h3>\n                <p class=\"vf-card__text\"><ul>\r\n \t<li>&#8220;<em><a class=\"vf-card_link\" href=\"https:\/\/www.nature.com\/articles\/nprot.2014.006\">Full-length RNA-seq from single cells using Smart-seq2<\/a>&#8220;<\/em><\/li>\r\n \t<li>&#8220;<a class=\"vf-card_link\" href=\"https:\/\/www.nature.com\/articles\/s41587-020-0497-0\"><em>Single-cell RNA counting at allele and isoform resolution using Smart-seq3<\/em><\/a>&#8220;<\/li>\r\n<\/ul><\/p>\n      <\/div>\n<\/article>\n\n<\/section>\n<\/div><\/div>\n\n<\/div>\n<\/div>\n\n\n<div><!--[vf\/content]-->\n<div class=\"vf-content\">\n\n<h2 class=\"wp-block-heading\">scDNA-seq<\/h2>\n\n\n\n<div class=\"vf-tabs\"><ul class=\"vf-tabs__list\" data-vf-js-tabs=\"true\"><li class=\"vf-tabs__item\"><a class=\"vf-tabs__link\" href=\"#vf-tabs__section-multiple-displacement-amplifications\" data-vf-js-location-nearest-activation-target=\"\">Multiple Displacement Amplifications<\/a><\/li><\/ul><div class=\"vf-tabs-content\" data-vf-js-tabs-content=\"true\">\n<section class=\"vf-tabs__section\" id=\"vf-tabs__section-multiple-displacement-amplifications\"><h2 class=\"vf-u-sr-only\">Multiple Displacement Amplifications<\/h2>\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      Multiple Displacement Amplifications    <\/h3>\n                <p class=\"vf-card__text\"><strong>Multiple Displacement Amplifications (MDA)<\/strong> is a single-cell DNA method that uses <strong>phi29 DNA polymerase<\/strong>\u00a0to\u00a0<strong>amplify the entire genome<\/strong>\u00a0from a single cell before sequencing, enabling whole\u2011genome or exome analysis but often introducing\u00a0<strong>coverage bias and allele dropout<\/strong>, which can affect variant calling.<\/p>\n      <\/div>\n<\/article>\n\n\n\n\n<article class=\"vf-card vf-card--brand vf-card--bordered vf-u-margin__bottom--800\" default>\n  <div class=\"vf-card__content | vf-stack vf-stack--400\">\n      <h3 class=\"vf-card__heading\">\n      Key References    <\/h3>\n                <p class=\"vf-card__text\"><ul>\r\n \t<li>&#8220;<em><a class=\"vf-card_link\" href=\"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC419624\/\">Genome coverage and sequence fidelity of phi29 polymerase-based multiple strand displacement whole genome amplification<\/a>&#8220;<\/em><\/li>\r\n \t<li><em>&#8220;<\/em><a class=\"vf-card_link\" href=\"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC7663899\/\"><em>SCELLECTOR: ranking amplification bias in single cells using shallow sequencing<\/em><\/a>&#8220;<\/li>\r\n<\/ul><\/p>\n      <\/div>\n<\/article>\n\n<\/section>\n<\/div><\/div>\n\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"vf-divider\">\n\n\n\n<div class=\"vf-grid | vf-grid__col-2\"><div><!--[vf\/content]-->\n<div class=\"vf-content\">\n\n<a href=\"https:\/\/www.embl.org\/groups\/genomics\/#Applications\" target=\"_blank\">\n<button class=\"vf-button vf-button--primary\">More applications<\/button>\n<\/a>\n<!--\/vf-button-->\n\n\n<\/div>\n<\/div>\n\n\n<div><!--[vf\/content]-->\n<div class=\"vf-content\">\n\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":19,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"template-title-left-aligned.php","meta":{"_acf_changed":false,"footnotes":""},"embl_taxonomy":[],"class_list":["post-1025","page","type-page","status-publish","hentry"],"acf":[],"embl_taxonomy_terms":[],"_links":{"self":[{"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/pages\/1025","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/comments?post=1025"}],"version-history":[{"count":26,"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/pages\/1025\/revisions"}],"predecessor-version":[{"id":1818,"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/pages\/1025\/revisions\/1818"}],"wp:attachment":[{"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/media?parent=1025"}],"wp:term":[{"taxonomy":"embl_taxonomy","embeddable":true,"href":"https:\/\/www.embl.org\/groups\/genomics\/wp-json\/wp\/v2\/embl_taxonomy?post=1025"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}