{"id":940,"date":"2020-03-10T13:59:06","date_gmt":"2020-03-10T13:59:06","guid":{"rendered":"http:\/\/serranolab.crg.eu\/?p=940"},"modified":"2020-03-10T14:28:38","modified_gmt":"2020-03-10T14:28:38","slug":"translational_eff_tumor","status":"publish","type":"post","link":"http:\/\/serranolab.crg.eu\/index.php\/2020\/03\/10\/translational_eff_tumor\/","title":{"rendered":"Translational efficiency across healthy and tumor tissues is proliferation-related"},"content":{"rendered":"<p>Abstract:<\/p>\n<blockquote><p>Different tissues express genes with particular codon usage and anticodon tRNA repertoires. However, the codon\u2013anticodon co\u2010adaptation in humans is not completely understood, nor is its effect on tissue\u2010specific protein levels. Here, we first validated the accuracy of small RNA\u2010seq for tRNA quantification across five human cell lines. We then analyzed the tRNA abundance of more than 8,000 tumor samples from TCGA, together with their paired mRNA\u2010seq and proteomics data, to determine the Supply\u2010to\u2010Demand Adaptation. We thereby elucidate that the dynamic adaptation of the tRNA pool is largely related to the proliferative state across tissues. The distribution of such tRNA pools over the whole cellular translatome affects the subsequent translational efficiency, which functionally determines a condition\u2010specific expression program both in healthy and tumor states. Furthermore, the aberrant translational efficiency of some codons in cancer, exemplified by ProCCA and GlyGGT, is associated with poor patient survival. The regulation of these tRNA profiles is partly explained by the tRNA gene copy numbers and their promoter DNA methylation.<\/p><\/blockquote>\n<p>Read the <a href=\"https:\/\/www.embopress.org\/doi\/full\/10.15252\/msb.20199275\">full text<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Abstract: Different tissues express genes with particular codon usage and anticodon tRNA repertoires. However, the codon\u2013anticodon co\u2010adaptation in humans is not completely understood, nor is its effect on tissue\u2010specific protein levels. Here, we first validated the accuracy of small RNA\u2010seq for tRNA quantification across five human cell lines. We then &hellip;<\/p>\n","protected":false},"author":28,"featured_media":941,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false},"categories":[15],"tags":[28,38,39,40,37],"_links":{"self":[{"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/posts\/940"}],"collection":[{"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/users\/28"}],"replies":[{"embeddable":true,"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/comments?post=940"}],"version-history":[{"count":4,"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/posts\/940\/revisions"}],"predecessor-version":[{"id":947,"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/posts\/940\/revisions\/947"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/media\/941"}],"wp:attachment":[{"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/media?parent=940"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/categories?post=940"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/serranolab.crg.eu\/index.php\/wp-json\/wp\/v2\/tags?post=940"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}