Dataset Information

Mining regulatory 5'UTRs from cDNA deep sequencing datasets.

ABSTRACT: Regulatory 5' untranslated regions (r5'UTRs) of mRNAs such as riboswitches modulate the expression of genes involved in varied biological processes in both bacteria and eukaryotes. New high-throughput sequencing technologies could provide powerful tools for discovery of novel r5'UTRs, but the size and complexity of the datasets generated by these technologies makes it difficult to differentiate r5'UTRs from the multitude of other types of RNAs detected. Here, we developed and implemented a bioinformatic approach to identify putative r5'UTRs from within large datasets of RNAs recently identified by pyrosequencing of the Vibrio cholerae small transcriptome. This screen yielded only approximately 1% of all non-overlapping RNAs along with 75% of previously annotated r5'UTRs and 69 candidate V. cholerae r5'UTRs. These candidates include several putative functional homologues of diverse r5'UTRs characterized in other species as well as numerous candidates upstream of genes involved in pathways not known to be regulated by r5'UTRs, such as fatty acid oxidation and peptidoglycan catabolism. Two of these novel r5'UTRs were experimentally validated using a GFP reporter-based approach. Our findings suggest that the number and diversity of pathways regulated by r5'UTRs has been underestimated and that deep sequencing-based transcriptomics will be extremely valuable in the search for novel r5'UTRs.

SUBMITTER: Livny J

PROVIDER: S-EPMC2836559 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

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Mining regulatory 5'UTRs from cDNA deep sequencing datasets.

Livny Jonathan J Waldor Matthew K MK

Nucleic acids research 20091207 5

Regulatory 5' untranslated regions (r5'UTRs) of mRNAs such as riboswitches modulate the expression of genes involved in varied biological processes in both bacteria and eukaryotes. New high-throughput sequencing technologies could provide powerful tools for discovery of novel r5'UTRs, but the size and complexity of the datasets generated by these technologies makes it difficult to differentiate r5'UTRs from the multitude of other types of RNAs detected. Here, we developed and implemented a bioin ...[more]

PMID: 19969537

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Project description:Although the bioactive sphingolipid ceramide is an important cell signaling molecule, relatively few direct ceramide-interacting proteins are known. We used an approach combining yeast surface cDNA display and deep sequencing technology to identify novel proteins binding directly to ceramide. We identified 234 candidate ceramide-binding protein fragments and validated binding for 20. Most (17) bound selectively to ceramide, although a few (3) bound to other lipids as well. Several novel ceramide-binding domains were discovered, including the EF-hand calcium-binding motif, the heat shock chaperonin-binding motif STI1, the SCP2 sterol-binding domain, and the tetratricopeptide repeat region motif. Interestingly, four of the verified ceramide-binding proteins (HPCA, HPCAL1, NCS1, and VSNL1) and an additional three candidate ceramide-binding proteins (NCALD, HPCAL4, and KCNIP3) belong to the neuronal calcium sensor family of EF hand-containing proteins. We used mutagenesis to map the ceramide-binding site in HPCA and to create a mutant HPCA that does not bind to ceramide. We demonstrated selective binding to ceramide by mammalian cell-produced wild type but not mutant HPCA. Intriguingly, we also identified a fragment from prostaglandin D2synthase that binds preferentially to ceramide 1-phosphate. The wide variety of proteins and domains capable of binding to ceramide suggests that many of the signaling functions of ceramide may be regulated by direct binding to these proteins. Based on the deep sequencing data, we estimate that our yeast surface cDNA display library covers ∼60% of the human proteome and our selection/deep sequencing protocol can identify target-interacting protein fragments that are present at extremely low frequency in the starting library. Thus, the yeast surface cDNA display/deep sequencing approach is a rapid, comprehensive, and flexible method for the analysis of protein-ligand interactions, particularly for the study of non-protein ligands.

Dataset Information

Mining regulatory 5'UTRs from cDNA deep sequencing datasets.

Publications

Mining regulatory 5'UTRs from cDNA deep sequencing datasets.

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