skip to main content

Explore Research Products in the NSF-PAR

Title: tRFtarget: a database for transfer RNA-derived fragment targets
Abstract Transfer RNA-derived fragments (tRFs) are a new class of small non-coding RNAs and play important roles in biological and physiological processes. Prediction of tRF target genes and binding sites is crucial in understanding the biological functions of tRFs in the molecular mechanisms of human diseases. We developed a publicly accessible web-based database, tRFtarget (http://trftarget.net), for tRF target prediction. It contains the computationally predicted interactions between tRFs and mRNA transcripts using the two state-of-the-art prediction tools RNAhybrid and IntaRNA, including location of the binding sites on the target, the binding region, and free energy of the binding stability with graphic illustration. tRFtarget covers 936 tRFs and 135 thousand predicted targets in eight species. It allows researchers to search either target genes by tRF IDs or tRFs by gene symbols/transcript names. We also integrated the manually curated experimental evidence of the predicted interactions into the database. Furthermore, we provided a convenient link to the DAVID® web server to perform downstream functional pathway analysis and gene ontology annotation on the predicted target genes. This database provides useful information for the scientific community to experimentally validate tRF target genes and facilitate the investigation of the molecular functions and mechanisms of tRFs.  more » « less
Award ID(s):
1916246
NSF-PAR ID:
10274599
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Nucleic Acids Research
Volume:
49
Issue:
D1
ISSN:
0305-1048
Page Range / eLocation ID:
D254 to D260
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ( , Nucleic Acids Research)
    Abstract

    tRNA-derived fragments (tRFs) are a class of emerging post-transcriptional regulators of gene expression likely binding to the transcripts of target genes. However, only a few tRFs targets have been experimentally validated, making it hard to extrapolate the functions or binding mechanisms of tRFs. The paucity of resources supporting the identification of the targets of tRFs creates a bottleneck in the fast-developing field. We have previously analyzed chimeric reads in crosslinked Argonaute1-RNA complexes to help infer the guide-target pairs and binding mechanisms of multiple tRFs based on experimental data in human HEK293 cells. To efficiently disseminate these results to the research community, we designed a web-based database tatDB (targets of tRFs DataBase) populated with close to 250 000 experimentally determined guide-target pairs with ∼23 000 tRF isoforms. tatDB has a user-friendly interface with flexible query options/filters allowing one to obtain comprehensive information on given tRFs (or targets). Modes of interactions are supported by secondary structures of potential guide-target hybrids and binding motifs, essential for understanding the targeting mechanisms of tRFs. Further, we illustrate the value of the database on an example of hypothesis-building for a tRFs potentially involved in the lifecycle of the SARS-CoV-2 virus. tatDB is freely accessible at https://grigoriev-lab.camden.rutgers.edu/tatdb.

     
    more » « less
  2. ; ; ; ; ( , Nucleic Acids Research)
    Abstract

    tRFtarget 1.0 (http://trftarget.net/) is a platform consolidating both computationally predicted and experimentally validated binding sites between transfer RNA-derived fragments (tRFs) and target genes (or transcripts) across multiple organisms. Here, we introduce a newly released version of tRFtarget 2.0, in which we integrated 6 additional tRF sources, resulting in a comprehensive collection of 2614 high-quality tRF sequences spanning across 9 species, including 1944 Homo sapiens tRFs and one newly incorporated species Rattus norvegicus. We also expanded target genes by including ribosomal RNAs, long non-coding RNAs, and coding genes >50 kb in length. The predicted binding sites have surged up to approximately 6 billion, a 20.5-fold increase than that in tRFtarget 1.0. The manually curated publications relevant to tRF targets have increased to 400 and the gene-level experimental evidence has risen to 232. tRFtarget 2.0 introduces several new features, including a web-based tool that identifies potential binding sites of tRFs in user's own datasets, integration of standardized tRF IDs, and inclusion of external links to contents within the database. Additionally, we enhanced website framework and user interface. With these improvements, tRFtarget 2.0 is more user-friendly, providing researchers a streamlined and comprehensive platform to accelerate their research progress.

     
    more » « less
  3. ; ; ; ( , mSphere)
    Bradford, Patricia A. (Ed.)
    ABSTRACT

    Efflux and motility are two key biological functions in bacteria. Recent findings have shown that efflux impacts flagellum biosynthesis and motility inEscherichia coliand other bacteria. AcrR is known to be the major transcriptional repressor of AcrAB-TolC, the main multidrug efflux pump inE. coliand otherEnterobacteriaceae. However, the underlying molecular mechanisms of how efflux and motility are co-regulated remain poorly understood. Here, we have studied the role of AcrR in direct regulation of motility inE. coli. By combining bioinformatics, electrophoretic mobility shift assays (EMSAs), gene expression, and motility experiments, we have found that AcrR represses motility inE. coliby directly repressing transcription of theflhDCoperon, but not the other flagellum genes/operons tested.flhDCencodes the master regulator of flagellum biosynthesis and motility genes. We found that such regulation primarily occurs by direct binding of AcrR to theflhDCpromoter region containing the first of the two predicted AcrR-binding sites identified in this promoter. This is the first report of direct regulation by AcrR of genes unrelated to efflux or detoxification. Moreover, we report that overexpression of AcrR restores to parental levels the increased swimming motility previously observed inE. colistrains without a functional AcrAB-TolC pump, and that such effect by AcrR is prevented by the AcrR ligand and AcrAB-TolC substrate ethidium bromide. Based on these and prior findings, we provide a novel model in which AcrR senses efflux and then co-regulates efflux and motility inE. colito maintain homeostasis and escape hazards.

    IMPORTANCE

    Efflux and motility play a major role in bacterial growth, colonization, and survival. InEscherichia coli, the transcriptional repressor AcrR is known to directly repress efflux and was later found to also repress flagellum biosynthesis and motility by Kim et al. (J Microbiol Biotechnol 26:1824–1828, 2016, doi: 10.4014/jmb.1607.07058). However, it remained unknown whether AcrR represses flagellum biosynthesis and motility directly and through which target genes, or indirectly because of altering the amount of efflux. This study reveals that AcrR represses flagellum biosynthesis and motility by directly repressing the expression of theflhDCmaster regulator of flagellum biosynthesis and motility genes, but not the other flagellum genes tested. We also show that the antimicrobial, efflux pump substrate, and AcrR ligand ethidium bromide regulates motility via AcrR. Overall, these findings support a novel model of direct co-regulation of efflux and motility mediated by AcrR in response to stress inE. coli.

     
    more » « less
  4. ; ; ; ; ; ; ; ; ; ( , Plant Physiology)
    null (Ed.)
    Abstract Deciphering gene regulatory networks (GRNs) is both a promise and challenge of systems biology. The promise lies in identifying key transcription factors (TFs) that enable an organism to react to changes in its environment. The challenge lies in validating GRNs that involve hundreds of TFs with hundreds of thousands of interactions with their genome-wide targets experimentally determined by high-throughput sequencing. To address this challenge, we developed ConnecTF, a species-independent, web-based platform that integrates genome-wide studies of TF–target binding, TF–target regulation, and other TF-centric omic datasets and uses these to build and refine validated or inferred GRNs. We demonstrate the functionality of ConnecTF by showing how integration within and across TF–target datasets uncovers biological insights. Case study 1 uses integration of TF–target gene regulation and binding datasets to uncover TF mode-of-action and identify potential TF partners for 14 TFs in abscisic acid signaling. Case study 2 demonstrates how genome-wide TF–target data and automated functions in ConnecTF are used in precision/recall analysis and pruning of an inferred GRN for nitrogen signaling. Case study 3 uses ConnecTF to chart a network path from NLP7, a master TF in nitrogen signaling, to direct secondary TF2s and to its indirect targets in a Network Walking approach. The public version of ConnecTF (https://ConnecTF.org) contains 3,738,278 TF–target interactions for 423 TFs in Arabidopsis, 839,210 TF–target interactions for 139 TFs in maize (Zea mays), and 293,094 TF–target interactions for 26 TFs in rice (Oryza sativa). The database and tools in ConnecTF will advance the exploration of GRNs in plant systems biology applications for model and crop species. 
    more » « less
  5. ; ; ; ( , Plant Physiology)
    Abstract

    Despite the known critical regulatory functions of microRNAs, histone modifications, and DNA methylation in reprograming plant epigenomes in response to pathogen infection, the molecular mechanisms underlying the tight coordination of these components remain poorly understood. Here, we show how Arabidopsis (Arabidopsis thaliana) miR778 coordinately modulates the root transcriptome, histone methylation, and DNA methylation via post-transcriptional regulation of the H3K9 methyltransferases SU(var)3-9 homolog 5 (SUVH5) and SUVH6 upon infection by the beet cyst nematode Heterodera schachtii. miR778 post-transcriptionally silences SUVH5 and SUVH6 upon nematode infection. Manipulation of the expression of miR778 and its two target genes significantly altered plant susceptibility to H. schachtii. RNA-seq analysis revealed a key role of SUVH5 and SUVH6 in reprograming the transcriptome of Arabidopsis roots upon H. schachtii infection. In addition, chromatin immunoprecipitation (ChIP)-seq analysis established SUVH5 and SUVH6 as the main enzymes mediating H3K9me2 deposition in Arabidopsis roots in response to nematode infection. ChIP-seq analysis also showed that these methyltransferases possess distinct DNA binding preferences in that they are targeting transposable elements under noninfected conditions and protein-coding genes in infected plants. Further analyses indicated that H3K9me2 deposition directed by SUVH5 and SUVH6 contributes to gene expression changes both in roots and in nematode feeding sites and preferentially associates with CG DNA methylation. Together, our results uncovered multi-layered epigenetic regulatory mechanisms coordinated by miR778 during Arabidopsis–H. schachtii interactions.

     
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email