{"id":7681,"date":"2022-10-21T09:13:58","date_gmt":"2022-10-21T00:13:58","guid":{"rendered":"https:\/\/www.med.osaka-u.ac.jp\/eng\/?page_id=7681"},"modified":"2022-10-21T09:34:33","modified_gmt":"2022-10-21T00:34:33","slug":"kato2022-10-17","status":"publish","type":"page","link":"https:\/\/www.med.osaka-u.ac.jp\/eng\/activities\/results\/2022year\/kato2022-10-17","title":{"rendered":"Reiichi Sugihara, Yuki Kato \u226aRNA Biology and Neuroscience\u226b <span>CAPITAL: a major advance in single-cell RNA data analysis<\/span>"},"content":{"rendered":"<ul class=\"linkBar clearfix\">\n<li><a href=\"https:\/\/www.med.osaka-u.ac.jp\/activities\/results\/2022year\/kato2022-10-17\">Text in Japanese<\/a><\/li>\n<\/ul>\n<p><em>Nature Communications<\/em><\/p>\n<p><em>Researchers from Osaka University have developed a computational tool called CAPITAL that can carry out accurate comparative analysis of complex single-cell sequencing datasets<\/em><\/p>\n<p class=\"figure\"><a href=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig1.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-7682 size-medium\" src=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig1-400x299.jpg?_t=1665708989\" alt=\"\" width=\"400\" height=\"299\" srcset=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig1-400x299.jpg 400w, https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig1-768x573.jpg 768w, https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig1.jpg 900w\" sizes=\"(max-width: 400px) 100vw, 400px\" \/><\/a><br \/>Figure 1. Overview of CAPITAL: an algorithm for comparing pseudotime trajectories with branches<\/p>\n<p>New developments in high-throughput biological studies mean that the genes that are active in just a single cell can now be determined. However, analyzing the complex datasets that result can be challenging. Now, a team at Osaka University has developed CAPITAL, a new computational tool for comparing complex datasets from single cells.<\/p>\n<p>RNA sequencing provides information on the subset of the entire population of genes that are actively being expressed, or are \u201cswitched on\u201d. As technology has advanced, it has become possible to sequence the RNA population of just a single cell. This can provide a great deal of information on the specific changes in gene expression involved when a large population of mixed cells undergoes dynamic, transitional processes, such as differentiation or cell death, because each individual cell can be specifically analyzed rather than all the different cell types being pooled.<\/p>\n<p>CAPITAL is specifically designed to compare complex datasets from single cells undergoing transitional processes. These analyses are carried out by defining a \u201cpseudotime trajectory\u201d, which places the cells along a hypothetical path that reflects their progress through the transitional process. These trajectories are not always straightforward and linear; they can become very complex and branching. In the past, only linear trajectories could be aligned for comparison, but the team\u2019s innovation means that complex branching trajectories can now be accurately and automatically aligned and compared.<\/p>\n<p>After developing the algorithm used for CAPITAL, which implements a method known as tree alignment, they tested it on both synthetic datasets and authentic datasets from bone marrow cells. The results demonstrated that CAPITAL is statistically more accurate and robust than the computational algorithms that existed previously, showing major advances over these methods.<\/p>\n<p>Trajectory comparison is a powerful analysis that can, as an example, identify the gene expression dynamics between different species to provide information on evolutionary processes. \u201cWe showed in this study that CAPITAL can reveal the existence of different molecular patterns between humans and mice even when the expression patterns are similar and appear to be conserved,\u201d says lead author Reiichi Sugihara. \u201cThis will allow the identification of novel regulators that determine cell fates.\u201d This technology is not limited to just this type of data, as senior author Yuki Kato explains: \u201cOur novel computational tool can be applied to a wide range of high-throughput datasets, including pseudotemporal, spatial, and epigenetic data.\u201d<\/p>\n<p>This powerful new technique will allow the global comparison of single-cell trajectories, which may lead to the identification of novel disease-associated genes that could not be identified by earlier comparative methods. Thus, CAPITAL represents a significant advance in the field of single-cell biology.<\/p>\n<p>###<\/p>\n<p>The article, \u201cAlignment of single-cell trajectory trees with CAPITAL\u201d, was published in <em>Nature Communications<\/em> at DOI: <a href=\"https:\/\/doi.org\/10.1038\/s41467-022-33681-3\">https:\/\/doi.org\/10.1038\/s41467-022-33681-3<\/a>.<\/p>\n<p><strong>Summary:<\/strong> Researchers from Osaka University have developed a computational analysis tool called CAPITAL for comparative analysis of single-cell RNA sequencing data with complicated branching trajectories. As cells undergo a dynamic process, they can be placed on a \u201cpseudotime trajectory\u201d to analyze the gene expression changes throughout the process. While previously only straightforward linear trajectories could be compared, CAPITAL is proven to be able to accurately compare branching trajectories, significantly advancing the field of high-throughput single-cell sequencing.<\/p>\n<p><strong>Tweet :<\/strong> \u00a0Accurate comparative analysis of high-throughput single-cell RNA-seq data enabled by CAPITAL, a novel computational tool.<\/p>\n<p><strong>Primary Keyword:<\/strong> Life sciences<br \/><strong>Additional Keywords: <\/strong>Computational biology, Comparative analysis, Data analysis, Omics, Single cells, Single cell profiling, Single cell sequencing, Transcriptomics<\/p>\n<p><strong>Method of Research:<\/strong> Computational simulating\/modeling<\/p>\n<p><strong>Subject of Research:<\/strong>Cells<\/p>\n<p class=\"figure\"><a href=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig2.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-7686 size-medium\" src=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig2-400x309.jpg?_t=1665709569\" alt=\"\" width=\"400\" height=\"309\" srcset=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig2-400x309.jpg 400w, https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig2-768x593.jpg 768w, https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig2.jpg 900w\" sizes=\"(max-width: 400px) 100vw, 400px\" \/><\/a><br \/>Figure 2. Alignment of single-cell trajectory trees with CAPITAL<\/p>\n<p class=\"figure\"><a href=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig3.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-7690 size-medium\" src=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig3-400x252.jpg?_t=1665709769\" alt=\"\" width=\"400\" height=\"252\" srcset=\"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig3-400x252.jpg 400w, https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig3-768x483.jpg 768w, https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-content\/uploads\/2022\/10\/kato_efig3.jpg 900w\" sizes=\"(max-width: 400px) 100vw, 400px\" \/><\/a><br \/>Figure 3. Expression dynamics of gene CSF1 along pseudotime from hematopoietic stem cell to erythrocyte between human and mouse from bone marrow cells data<\/p>\n<p>Title: \u201cAlignment of single-cell trajectory trees with CAPITAL\u201d<br \/>Journal: <em>Nature Communications<\/em><em><br \/><\/em>Authors: Reiichi Sugihara, Yuki Kato, Tomoya Mori and Yukio Kawahara<br \/>DOI: <a href=\"https:\/\/doi.org\/10.1038\/s41467-022-33681-3\">10.1038\/s41467-022-33681-3<\/a><\/p>\n<p>Funded by: Japan Society for the Promotion of Science<\/p>\n<p>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Text in Japanese Nature Communications Researchers from Osaka University have developed a computational tool c [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":7682,"parent":6951,"menu_order":150,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/pages\/7681"}],"collection":[{"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/comments?post=7681"}],"version-history":[{"count":8,"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/pages\/7681\/revisions"}],"predecessor-version":[{"id":7693,"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/pages\/7681\/revisions\/7693"}],"up":[{"embeddable":true,"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/pages\/6951"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/media\/7682"}],"wp:attachment":[{"href":"https:\/\/www.med.osaka-u.ac.jp\/eng\/wp-json\/wp\/v2\/media?parent=7681"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}