<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Gorjifard S</submitter><funding>United States Department of Agriculture | National Institute of Food and Agriculture (NIFA)</funding><funding>NHGRI NIH HHS</funding><funding>National Science Foundation (NSF)</funding><funding>U.S. Department of Health &amp; Human Services | National Institutes of Health (NIH)</funding><funding>U.S. Department of Health &amp;amp; Human Services | National Institutes of Health</funding><funding>United States Department of Agriculture | National Institute of Food and Agriculture</funding><funding>NIGMS NIH HHS</funding><funding>National Science Foundation</funding><pagination>5868</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11245536</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>15(1)</volume><pubmed_abstract>The 3' end of a gene, often called a terminator, modulates mRNA stability, localization, translation, and polyadenylation. Here, we adapted Plant STARR-seq, a massively parallel reporter assay, to measure the activity of over 50,000 terminators from the plants Arabidopsis thaliana and Zea mays. We characterize thousands of plant terminators, including many that outperform bacterial terminators commonly used in plants. Terminator activity is species-specific, differing in tobacco leaf and maize protoplast assays. While recapitulating known biology, our results reveal the relative contributions of polyadenylation motifs to terminator strength. We built a computational model to predict terminator strength and used it to conduct in silico evolution that generated optimized synthetic terminator</pubmed_abstract><journal>Nature communications</journal><pubmed_title>Arabidopsis and maize terminator strength is determined by GC content, polyadenylation motifs and cleavage probability.</pubmed_title><pmcid>PMC11245536</pmcid><funding_grant_id>2023-67012-39445</funding_grant_id><funding_grant_id>2240888</funding_grant_id><funding_grant_id>HG000035</funding_grant_id><funding_grant_id>R01-GM079712</funding_grant_id><funding_grant_id>R01 GM079712</funding_grant_id><funding_grant_id>T32 HG000035</funding_grant_id><funding_grant_id>R35 GM139532</funding_grant_id><funding_grant_id>1R35GM139532</funding_grant_id><pubmed_authors>Bubb K</pubmed_authors><pubmed_authors>Jores T</pubmed_authors><pubmed_authors>Queitsch C</pubmed_authors><pubmed_authors>Buckler ES</pubmed_authors><pubmed_authors>Tonnies J</pubmed_authors><pubmed_authors>Wrightsman T</pubmed_authors><pubmed_authors>Fields S</pubmed_authors><pubmed_authors>Cuperus JT</pubmed_authors><pubmed_authors>Gorjifard S</pubmed_authors><pubmed_authors>Mueth NA</pubmed_authors></additional><is_claimable>false</is_claimable><name>Arabidopsis and maize terminator strength is determined by GC content, polyadenylation motifs and cleavage probability.</name><description>The 3' end of a gene, often called a terminator, modulates mRNA stability, localization, translation, and polyadenylation. Here, we adapted Plant STARR-seq, a massively parallel reporter assay, to measure the activity of over 50,000 terminators from the plants Arabidopsis thaliana and Zea mays. We characterize thousands of plant terminators, including many that outperform bacterial terminators commonly used in plants. Terminator activity is species-specific, differing in tobacco leaf and maize protoplast assays. While recapitulating known biology, our results reveal the relative contributions of polyadenylation motifs to terminator strength. We built a computational model to predict terminator strength and used it to conduct in silico evolution that generated optimized synthetic terminator</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Jul</publication><modification>2025-04-18T21:43:03.887Z</modification><creation>2025-02-19T02:34:39.171Z</creation></dates><accession>S-EPMC11245536</accession><cross_references><pubmed>38997252</pubmed><doi>10.1038/s41467-024-50174-7</doi></cross_references></HashMap>