<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Wang X</submitter><funding>Pharmaceutical Research and Manufacturers of America Foundation (PhRMA Foundation)</funding><funding>U.S. Department of Health &amp; Human Services | NIH | National Institute of General Medical Sciences (NIGMS)</funding><funding>U.S. Department of Health &amp; Human Services | NIH | NIH Office of the Director (OD)</funding><pagination>4198</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12056006</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>16(1)</volume><pubmed_abstract>Nearly 10,000 plant species are represented by RNA-seq datasets in the NCBI sequence read archive, which are difficult to search in unassembled format due to database size. Here, we optimize RNA-seq assembly to transform most of this public RNA-seq data to a searchable database for biosynthetic gene discovery. We test our transcriptome mining pipeline towards the diversification of moroidins, which are plant ribosomally-synthesized and posttranslationally-modified peptides (RiPPs) biosynthesized from copper-dependent peptide cyclases. Moroidins are bicyclic compounds with a conserved stephanotic acid scaffold, which becomes cytotoxic to non-small cell lung adenocarcinoma cells with an additional C-terminal macrocycle. We discover moroidin analogs with second ring structures diversified at </pubmed_abstract><journal>Nature communications</journal><pubmed_title>Large-scale transcriptome mining enables macrocyclic diversification and improved bioactivity of the stephanotic acid scaffold.</pubmed_title><pmcid>PMC12056006</pmcid><funding_grant_id>T32GM140223</funding_grant_id><funding_grant_id>S10OD034245</funding_grant_id><funding_grant_id>R35GM146934</funding_grant_id><funding_grant_id>R01GM152417</funding_grant_id><funding_grant_id>F32GM146395</funding_grant_id><funding_grant_id>Predoctoral Fellowship</funding_grant_id><funding_grant_id>F31GM155959</funding_grant_id><pubmed_authors>Sexton JZ</pubmed_authors><pubmed_authors>Shafiq K</pubmed_authors><pubmed_authors>Mydy LS</pubmed_authors><pubmed_authors>Chigumba DN</pubmed_authors><pubmed_authors>Davis D</pubmed_authors><pubmed_authors>Kersten RD</pubmed_authors><pubmed_authors>Wang X</pubmed_authors><pubmed_authors>McDonough KM</pubmed_authors><pubmed_authors>Ousley DA</pubmed_authors></additional><is_claimable>false</is_claimable><name>Large-scale transcriptome mining enables macrocyclic diversification and improved bioactivity of the stephanotic acid scaffold.</name><description>Nearly 10,000 plant species are represented by RNA-seq datasets in the NCBI sequence read archive, which are difficult to search in unassembled format due to database size. Here, we optimize RNA-seq assembly to transform most of this public RNA-seq data to a searchable database for biosynthetic gene discovery. We test our transcriptome mining pipeline towards the diversification of moroidins, which are plant ribosomally-synthesized and posttranslationally-modified peptides (RiPPs) biosynthesized from copper-dependent peptide cyclases. Moroidins are bicyclic compounds with a conserved stephanotic acid scaffold, which becomes cytotoxic to non-small cell lung adenocarcinoma cells with an additional C-terminal macrocycle. We discover moroidin analogs with second ring structures diversified at </description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 May</publication><modification>2026-06-02T21:00:24.378Z</modification><creation>2026-04-20T03:14:34.821Z</creation></dates><accession>S-EPMC12056006</accession><cross_references><pubmed>40328797</pubmed><doi>10.1038/s41467-025-59428-4</doi></cross_references></HashMap>