{"id":2685,"date":"2020-05-20T10:52:31","date_gmt":"2020-05-20T14:52:31","guid":{"rendered":"https:\/\/www.med.unc.edu\/genomics\/?page_id=2685"},"modified":"2023-01-27T19:08:40","modified_gmt":"2023-01-28T00:08:40","slug":"rna-sequencing","status":"publish","type":"page","link":"https:\/\/www.med.unc.edu\/genomics\/overview-of-services\/rna-sequencing\/","title":{"rendered":"RNA Library Preparation and Sequencing"},"content":{"rendered":"<h2 class=\"section-som\"><span>Total RNA-seq<\/span><\/h2>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignleft\" src=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/08\/lib-staff_1_Yan.jpg\" alt=\"Yan\" width=\"200\" height=\"1001\" \/>Whole-transcriptome analysis with total RNA sequencing (RNA-Seq) detects coding plus multiple forms of noncoding RNA. Total RNA-Seq can accurately measure gene and transcript abundance and identify known and novel features of the transcriptome.<\/p>\n<p>For library preparation recommendations based on species, please see the below chart for details.<\/p>\n<table style=\"width: 100%;border-collapse: collapse;border-style: solid;border-color: #007FAE\" border=\"3\">\n<tbody>\n<tr>\n<td style=\"width: 50%;text-align: center\"><strong style=\"color: #007fae\">Species<\/strong><\/td>\n<td style=\"width: 50%;text-align: center\"><strong style=\"color: #007fae\">Library Preparation<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 50%;text-align: center\"><strong>Human\/Mouse\/Rat<\/strong><\/td>\n<td style=\"width: 50%;text-align: center\">TruSeq Ribo-Zero-Gold and Kapa Ribo-Erase<\/td>\n<\/tr>\n<tr>\n<td style=\"width: 50%;text-align: center\"><strong>Individual species depletions<\/strong><\/td>\n<td style=\"width: 50%;text-align: center\">\n<ul>\n<li>Tecan Genomics Ovation Universal RNAseq with any deplete<\/li>\n<li>Nugen Solo<\/li>\n<li>Nugen Trio<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>For low input material, the HTSF typically recommends Tecan Genomics SOLO or Trio, which can be done with any depletion for ribosomal depletion.<\/p>\n<p>General sequencing platform and pooling recommendations can be found below:<\/p>\n<table style=\"width: 100%;border-collapse: collapse;border-style: solid;border-color: #007FAE;height: 186px\" border=\"3\">\n<tbody>\n<tr style=\"height: 24px\">\n<td style=\"width: 25%;height: 24px;text-align: center\"><strong style=\"color: #007fae\">Service<\/strong><\/td>\n<td style=\"width: 25%;height: 24px;text-align: center\"><strong style=\"color: #007fae\">Samples per Pool<\/strong><\/td>\n<td style=\"width: 25%;height: 24px;text-align: center\"><strong style=\"color: #007fae\">Platform<\/strong><\/td>\n<td style=\"width: 25%;height: 24px;text-align: center\"><strong style=\"color: #007fae\">Cycles<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 162px;text-align: center\" rowspan=\"7\"><strong>Total RNAseq<\/strong><\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">24<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\" rowspan=\"2\">NovaSeq S4<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">2&#215;150<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">96<\/td>\n<td style=\"width: 25%;height: 139px;text-align: center\" rowspan=\"6\">2&#215;50<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">38<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">NovaSeq S2<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">16<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">NovaSeq S1<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">8<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">NovaSeq SP<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">3<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\" rowspan=\"2\">HiSeq 4000<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 25%;height: 24px;text-align: center\">2<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div style=\"font-size: 14px\">*NOTE: Anticipated yield of 100 million clusters (200 million reads) per library<\/div>\n<h2 class=\"section-som\"><span>mRNA-Seq<\/span><\/h2>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignright\" src=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/08\/lib-staff_1_Page_09.jpg\" alt=\"Library Staff\" width=\"200\" height=\"670\" \/>mRNA sequencing (mRNA-Seq) has rapidly become the method of choice for analyzing the transcriptomes of disease states, of biological processes, and across a wide range of study designs. mRNA-Seq can identify both known and novel transcript isoforms, gene fusions, and other features as well as allele-specific expression. mRNA-Seq delivers a complete view of the coding transcriptome that is not restricted by the filter of prior knowledge.<\/p>\n<p>There are a variety of approaches to mRNA sequencing. Therefore, the best approach will depend on your needs.<br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignleft\" style=\"padding-right: 16px\" src=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/08\/working_Sciclone2.jpg\" alt=\"Sciclone\" width=\"200\" height=\"1029\" \/>Typically, the HTSF recommends the following library preparation methods:<\/p>\n<ul>\n<li>Kapa mRNA stranded<\/li>\n<li>Takara Smarter + Nextera XT for low input material<\/li>\n<li>Nugen mRNA can also be done by request.<\/li>\n<\/ul>\n<p>Sequencing and pooling recommendations can be found in the table below:<\/p>\n<table style=\"height: 148px;width: 100%;border-collapse: collapse;border-style: solid;border-color: #007fae\" border=\"3\">\n<tbody>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\"><strong style=\"color: #007fae\">Services<\/strong><\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\"><strong style=\"color: #007fae\">Samples per Pool<\/strong><\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\"><strong style=\"color: #007fae\">Platform<\/strong><\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\"><strong style=\"color: #007fae\">Cycles<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 125px;text-align: center\" rowspan=\"6\"><strong>mRNA-Seq<\/strong><\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">198<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">NovaSeq S4<\/td>\n<td style=\"width: 25%;height: 125px;text-align: center\" rowspan=\"6\">2&#215;50<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">76<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">NovaSeq S2<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">32<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">NovaSeq S1<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">16<\/td>\n<td style=\"width: 25%;height: 23px;text-align: center\">NovaSeq SP<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 10px;text-align: center\">6<\/td>\n<td style=\"width: 25%;height: 33px;text-align: center\" rowspan=\"2\">HiSeq 4000<\/td>\n<\/tr>\n<tr style=\"height: 23px\">\n<td style=\"width: 25%;height: 23px;text-align: center\">4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div style=\"font-size: 14px\">*NOTE: Anticipated yield of 50 million clusters (100 million reads) per library<\/div>\n<h2 class=\"section-som\"><span>Small RNA sequencing<\/span><\/h2>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignright\" src=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/08\/bioinformatics_Hongwei.jpg\" alt=\"Hongwei\" width=\"200\" height=\"480\" \/>MicroRNA sequencing (miRNA-seq), a type of RNA-Seq, is the use of next-generation sequencing to sequence microRNAs, also called miRNAs. miRNA-seq differs from other forms of RNA-seq in that input material is typically enriched for small RNAs. miRNA-seq allows researchers to examine tissue-specific expression patterns, disease associations, and isoforms of miRNAs, and to discover previously uncharacterized miRNAs.<\/p>\n<p>Like other miRNA profiling technologies, miRNA-Seq has both advantages (sequence-independence, coverage) and disadvantages (high cost, infrastructure requirements, run length, and potential artifacts).<\/p>\n<p>Preferred library preparation kits for this service include:<\/p>\n<ul>\n<li>BioO NextFlex<\/li>\n<\/ul>\n<p>Sequencing and pooling recommendations can be found in the table below:<\/p>\n<table style=\"width: 100%;border-collapse: collapse;border-style: solid;border-color: #007FAE\" border=\"3\">\n<tbody>\n<tr>\n<td style=\"width: 25%;text-align: center\"><strong style=\"color: #007fae\">Service<\/strong><\/td>\n<td style=\"width: 25%;text-align: center\"><strong style=\"color: #007fae\">Samples per Pool<\/strong><\/td>\n<td style=\"width: 25%;text-align: center\"><strong style=\"color: #007fae\">Platform<\/strong><\/td>\n<td style=\"width: 25%;text-align: center\"><strong style=\"color: #007fae\">Cycle<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"width: 25%;text-align: center\"><strong>Small RNA-seq<\/strong><\/td>\n<td style=\"width: 25%;text-align: center\">48<\/td>\n<td style=\"width: 25%;text-align: center\">NextSeq 2000<\/td>\n<td style=\"width: 25%;text-align: center\">Single End\/50x<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div style=\"font-size: 14px\">*NOTE: Anticipated yield of 20 million reads\/clusters per library<\/div>\n<h2 class=\"section-som\"><span>Relevant RNA Services Forms and Guides <\/span><\/h2>\n<a href=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/07\/HTSF-DNA-and-RNA-Sample-Preparation-Requirement-Guide_V6_12-2021_FINAL-1.pdf\">HTSF Sample Preparation Requirement Guide <\/a><br \/>\n<a href=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/07\/HTSF-Illumina_Sequencing_Platform_Comparison_Chart_v7_12-2021_FINAL.pdf\">Illumina Platform Comparison and Specification Table<\/a><br \/>\n<a href=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/07\/HTSF-NovaSeq-Requirements-and-Pooling-Suggestions_v3_7-2020_FINAL.pdf\">NovaSeq Requirements<\/a><br \/>\n<a href=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/07\/HTSF-Novaseq-Whitepaper_v45_7-2020_FINAL.pdf\">NovaSeq White Paper<\/a><br \/>\n<a href=\"https:\/\/www.med.unc.edu\/genomics\/wp-content\/uploads\/sites\/708\/2020\/07\/HTSF-Approved-Container-Requirements_v5_7-2020_FINAL.pdf\">Approved Containers Information <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Whole-transcriptome analysis with total RNA sequencing (RNA-Seq) detects coding plus multiple forms of noncoding RNA. Total RNA-Seq can accurately measure gene and transcript abundance and identify known and novel features of the transcriptome. For library preparation recommendations based on species, please see the below chart for details. Species Library Preparation Human\/Mouse\/Rat TruSeq Ribo-Zero-Gold and Kapa &hellip; <a href=\"https:\/\/www.med.unc.edu\/genomics\/overview-of-services\/rna-sequencing\/\" aria-label=\"Read more about RNA Library Preparation and Sequencing\">Read more<\/a><\/p>\n","protected":false},"author":64010,"featured_media":0,"parent":2650,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"layout":"","cellInformation":"","apiCallInformation":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-2685","page","type-page","status-publish","hentry","odd"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>RNA Library Preparation and Sequencing - High-Throughput Sequencing Facility (HTSF)<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.med.unc.edu\/genomics\/overview-of-services\/rna-sequencing\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"RNA Library Preparation and Sequencing - High-Throughput Sequencing Facility (HTSF)\" \/>\n<meta property=\"og:description\" content=\"Whole-transcriptome analysis with total RNA sequencing (RNA-Seq) detects coding plus multiple forms of noncoding RNA. 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