1887

Abstract

Accurate annotation to single-nucleotide resolution of the transcribed regions in genomes is key to optimally analyse RNA-seq data, understand regulatory events and for the design of experiments. However, currently most genome annotations provided by GenBank generally lack information about untranslated regions. Additionally, information regarding genomic locations of non-coding RNAs, such as sRNAs, or anti-sense RNAs is frequently missing. To provide such information, diverse RNA-seq technologies, such as Rend-seq, have been developed and applied to many bacterial species. However, incorporating this vast amount of information into annotation files has been limited and is bioinformatically challenging, resulting in UTRs and other non-coding elements being overlooked or misrepresented. To overcome this problem, we present pyRAP (python Rend-seq Annotation Pipeline), a software package that analyses Rend-seq datasets to accurately resolve transcript boundaries genome-wide. We report the use of pyRAP to find novel transcripts, transcript isoforms, and RNase-dependent sRNA processing events. In we uncovered 63 novel transcripts and provide genomic coordinates with single-nucleotide resolution for 2218 5′UTRs, 1864 3′UTRs and 161 non-coding RNAs. In we report 117 novel transcripts, 2429 5′UTRs, 1619 3′UTRs and 91 non-coding RNAs, and in 16 novel transcripts, 664 5′UTRs, 696 3′UTRs, and 81 non-coding RNAs. Finally, we use pyRAP to produce updated annotation files for , , and for use in the wider microbial genomics research community.

Funding
This study was supported by the:
  • University of Bath
    • Principle Award Recipient: AndreasC Lawaetz
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2024-04-26
2024-05-07
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References

  1. Lawaetz AC, Cowley LA, Denham EL. Genome-wide annotation of transcript boundaries using bacterial rend-Seq Datasets Microbiology Society 2024 [View Article]
    [Google Scholar]
  2. Haldenwang WG. The sigma factors of Bacillus subtilis. Microbiol Rev 1995; 59:1–30 [View Article] [PubMed]
    [Google Scholar]
  3. Waters LS, Storz G. Regulatory RNAs in bacteria. Cell 2009; 136:615–628 [View Article] [PubMed]
    [Google Scholar]
  4. Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Nawrocki EP et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res 2016; 44:6614–6624 [View Article] [PubMed]
    [Google Scholar]
  5. Denham EL. The Sponge RNAs of bacteria - how to find them and their role in regulating the post-transcriptional network. Biochim Biophys Acta Gene Regul Mech 2020; 1863:194565 [View Article] [PubMed]
    [Google Scholar]
  6. Mars RAT, Nicolas P, Denham EL, van Dijl JM. Regulatory RNAs in Bacillus subtilis: a Gram-positive perspective on bacterial RNA-mediated regulation of gene expression. Microbiol Mol Biol Rev 2016; 80:1029–1057 [View Article] [PubMed]
    [Google Scholar]
  7. Brantl S, Müller P. Cis- and trans-encoded small regulatory RNAs in Bacillus subtilis. Microorganisms 2021; 9:1865 [View Article]
    [Google Scholar]
  8. Beisel CL, Storz G. Base pairing small RNAs and their roles in global regulatory networks. FEMS Microbiol Rev 2010; 34:866–882 [View Article] [PubMed]
    [Google Scholar]
  9. Brantl S. Regulatory mechanisms employed by cis-encoded antisense RNAs. Curr Opin Microbiol 2007; 10:102–109 [View Article] [PubMed]
    [Google Scholar]
  10. Wagner EGH, Romby P. Small RNAs in bacteria and archaea. In Advances in Genetics Academic Press; 2015 pp 133–208
    [Google Scholar]
  11. Barquist L, Vogel J. Accelerating discovery and functional analysis of small RNAs with new technologies. Annu Rev Genet 2015; 49:367–394 [View Article] [PubMed]
    [Google Scholar]
  12. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
    [Google Scholar]
  13. Kalvari I, Nawrocki EP, Argasinska J, Quinones-Olvera N, Finn RD et al. Non-coding RNA analysis using the Rfam database. Curr Protoc Bioinform 2018; 62:e51 [View Article] [PubMed]
    [Google Scholar]
  14. Livny J, Waldor MK. Identification of small RNAs in diverse bacterial species. Curr Opin Microbiol 2007; 10:96–101 [View Article] [PubMed]
    [Google Scholar]
  15. Nicolas P, Mäder U, Dervyn E, Rochat T, Leduc A et al. Condition-dependent transcriptome reveals high-level regulatory architecture in Bacillus subtilis. Science 2012; 335:1103–1106 [View Article] [PubMed]
    [Google Scholar]
  16. Rasmussen S, Nielsen HB, Jarmer H. The transcriptionally active regions in the genome of Bacillus subtilis. Mol Microbiol 2009; 73:1043–1057 [View Article] [PubMed]
    [Google Scholar]
  17. Wassarman KM, Repoila F, Rosenow C, Storz G, Gottesman S. Identification of novel small RNAs using comparative genomics and microarrays. Genes Dev 2001; 15:1637–1651 [View Article] [PubMed]
    [Google Scholar]
  18. Mäder U, Nicolas P, Depke M, Pané-Farré J, Debarbouille M et al. Staphylococcus aureus transcriptome architecture: from laboratory to infection-mimicking conditions. PLoS Genet 2016; 12:e1005962 [View Article] [PubMed]
    [Google Scholar]
  19. Tjaden B, Saxena RM, Stolyar S, Haynor DR, Kolker E et al. Transcriptome analysis of Escherichia coli using high-density oligonucleotide probe arrays. Nucleic Acids Res 2002; 30:3732–3738 [View Article] [PubMed]
    [Google Scholar]
  20. Raghavan R, Groisman EA, Ochman H. Genome-wide detection of novel regulatory RNAs in E. coli. Genome Res 2011; 21:1487–1497 [View Article] [PubMed]
    [Google Scholar]
  21. Shinhara A, Matsui M, Hiraoka K, Nomura W, Hirano R et al. Deep sequencing reveals as-yet-undiscovered small RNAs in Escherichia coli. BMC Genom 2011; 12:428 [View Article] [PubMed]
    [Google Scholar]
  22. Croucher NJ, Thomson NR. Studying bacterial transcriptomes using RNA-seq. Curr Opin Microbiol 2010; 13:619–624 [View Article] [PubMed]
    [Google Scholar]
  23. Ettwiller L, Buswell J, Yigit E, Schildkraut I. A novel enrichment strategy reveals unprecedented number of novel transcription start sites at single base resolution in a model prokaryote and the gut microbiome. BMC Genom 2016; 17:199 [View Article] [PubMed]
    [Google Scholar]
  24. Salgado H, Peralta-Gil M, Gama-Castro S, Santos-Zavaleta A, Muñiz-Rascado L et al. RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more. Nucleic Acids Res 2013; 41:D203–D213 [View Article] [PubMed]
    [Google Scholar]
  25. Mendoza-Vargas A, Olvera L, Olvera M, Grande R, Vega-Alvarado L et al. Genome-wide identification of transcription start sites, promoters and transcription factor binding sites in E. coli. PLoS One 2009; 4:e7526 [View Article] [PubMed]
    [Google Scholar]
  26. Warman EA, Forrest D, Guest T, Haycocks JJRJ, Wade JT et al. Widespread divergent transcription from bacterial and archaeal promoters is a consequence of DNA-sequence symmetry. Nat Microbiol 2021; 6:746–756 [View Article] [PubMed]
    [Google Scholar]
  27. Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B et al. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet 2010; 11:733–739 [View Article] [PubMed]
    [Google Scholar]
  28. Sharma CM, Vogel J. Differential RNA-seq: the approach behind and the biological insight gained. Curr Opin Microbiol 2014; 19:97–105 [View Article] [PubMed]
    [Google Scholar]
  29. Sharma CM, Hoffmann S, Darfeuille F, Reignier J, Findeiss S et al. The primary transcriptome of the major human pathogen Helicobacter pylori. Nature 2010; 464:250–255 [View Article] [PubMed]
    [Google Scholar]
  30. Dar D, Shamir M, Mellin JR, Koutero M, Stern-Ginossar N et al. Term-seq reveals abundant ribo-regulation of antibiotics resistance in bacteria. Science 2016; 352:aad9822 [View Article] [PubMed]
    [Google Scholar]
  31. Lalanne J-B, Taggart JC, Guo MS, Herzel L, Schieler A et al. Evolutionary convergence of pathway-specific enzyme expression stoichiometry. Cell 2018; 173:749–761 [View Article] [PubMed]
    [Google Scholar]
  32. Karp PD, Billington R, Caspi R, Fulcher CA, Latendresse M et al. The BioCyc collection of microbial genomes and metabolic pathways. Brief Bioinform 2019; 20:1085–1093 [View Article] [PubMed]
    [Google Scholar]
  33. Pedreira T, Elfmann C, Stülke J. The current state of SubtiWiki, the database for the model organism Bacillus subtilis. Nucleic Acids Res 2022; 50:D875–D882 [View Article] [PubMed]
    [Google Scholar]
  34. Fuchs S, Mehlan H, Bernhardt J, Hennig A, Michalik S et al. AureoWiki ̵ the repository of the Staphylococcus aureus research and annotation community. Int J Med Microbiol 2018; 308:558–568 [View Article] [PubMed]
    [Google Scholar]
  35. Keseler IM, Gama-Castro S, Mackie A, Billington R, Bonavides-Martínez C et al. The EcoCyc database in 2021. Front Microbiol 2021; 12:711077 [View Article] [PubMed]
    [Google Scholar]
  36. Geissler AS, Anthon C, Alkan F, González-Tortuero E, Poulsen LD et al. BSGatlas: a unified Bacillus subtilis genome and transcriptome annotation atlas with enhanced information access. Microb Genom 2021; 7:000524 [View Article] [PubMed]
    [Google Scholar]
  37. Durand S, Tomasini A, Braun F, Condon C, Romby P. sRNA and mRNA turnover in Gram-positive bacteria. FEMS Microbiol Rev 2015; 39:316–330 [View Article] [PubMed]
    [Google Scholar]
  38. Miyakoshi M, Chao Y, Vogel J. Cross talk between ABC transporter mRNAs via a target mRNA-derived sponge of the GcvB small RNA. EMBO J 2015; 34:1478–1492 [View Article] [PubMed]
    [Google Scholar]
  39. DeLoughery A, Lalanne JB, Losick R, Li GW. Maturation of polycistronic mRNAs by the endoribonuclease RNase Y and its associated Y-complex in Bacillus subtilis. Proc Natl Acad Sci U S A 2018; 115:E5585–E5594 [View Article] [PubMed]
    [Google Scholar]
  40. Liu B, Deikus G, Bree A, Durand S, Kearns DB et al. Global analysis of mRNA decay intermediates in Bacillus subtilis wild-type and polynucleotide phosphorylase-deletion strains. Mol Microbiol 2014; 94:41–55 [View Article] [PubMed]
    [Google Scholar]
  41. Durand S, Gilet L, Bessières P, Nicolas P, Condon C. Three essential ribonucleases-RNase Y, J1, and III-control the abundance of a majority of Bacillus subtilis mRNAs. PLoS Genet 2012; 8:e1002520 [View Article] [PubMed]
    [Google Scholar]
  42. Broglia L, Le Rhun A, Charpentier E. Methodologies for bacterial ribonuclease characterization using RNA-seq. FEMS Microbiol Rev 2023; 47:fuad049 [View Article] [PubMed]
    [Google Scholar]
  43. Sittka A, Lucchini S, Papenfort K, Sharma CM, Rolle K et al. Deep sequencing analysis of small noncoding RNA and mRNA targets of the global post-transcriptional regulator, Hfq. PLoS Genet 2008; 4:e1000163 [View Article] [PubMed]
    [Google Scholar]
  44. Helwak A, Tollervey D. Mapping the miRNA interactome by cross-linking ligation and sequencing of hybrids (CLASH). Nat Protoc 2014; 9:711–728 [View Article] [PubMed]
    [Google Scholar]
  45. Arnvig KB, Comas I, Thomson NR, Houghton J, Boshoff HI et al. Sequence-based analysis uncovers an abundance of non-coding RNA in the total transcriptome of Mycobacterium tuberculosis. PLoS Pathog 2011; 7:e1002342 [View Article] [PubMed]
    [Google Scholar]
  46. Durand S, Callan-Sidat A, McKeown J, Li S, Kostova G et al. Identification of an RNA sponge that controls the RoxS riboregulator of central metabolism in Bacillus subtilis. Nucleic Acids Res 2021; 49:6399–6419 [View Article] [PubMed]
    [Google Scholar]
  47. Mandell ZF, Vishwakarma RK, Yakhnin H, Murakami KS, Kashlev M et al. Comprehensive transcription terminator atlas for Bacillus subtilis. Nat Microbiol 2022; 7:1918–1931 [View Article] [PubMed]
    [Google Scholar]
  48. Adams PP, Baniulyte G, Esnault C, Chegireddy K, Singh N et al. Regulatory roles of Escherichia coli 5’ UTR and ORF-internal RNAs detected by 3’ end mapping. Elife 2021; 10:1–33 [View Article] [PubMed]
    [Google Scholar]
  49. Mäder U, Nicolas P, Depke M, Pané-Farré J, Debarbouille M et al. Staphylococcus aureus transcriptome architecture: from laboratory to infection-mimicking conditions. PLoS Genet 2016; 12:e1005962 [View Article] [PubMed]
    [Google Scholar]
  50. Irnov I, Sharma CM, Vogel J, Winkler WC. Identification of regulatory RNAs in Bacillus subtilis. Nucleic Acids Res 2010; 38:6637–6651 [View Article] [PubMed]
    [Google Scholar]
  51. Diesh C, Stevens GJ, Xie P, De Jesus Martinez T, Hershberg EA et al. JBrowse 2: a modular genome browser with views of synteny and structural variation. Genome Biol 2023; 24:74 [View Article] [PubMed]
    [Google Scholar]
  52. Naville M, Ghuillot-Gaudeffroy A, Marchais A, Gautheret D. ARNold: a web tool for the prediction of Rho-independent transcription terminators. RNA Biol 2011; 8:11–13 [View Article] [PubMed]
    [Google Scholar]
  53. Raina M, King A, Bianco C, Vanderpool CK. Dual-function RNAs. Microbiol Spectr 2018; 6:471–485 [View Article] [PubMed]
    [Google Scholar]
  54. Christopoulou N, Granneman S. The role of RNA-binding proteins in mediating adaptive responses in Gram-positive bacteria. FEBS J 2022; 289:1746–1764 [View Article] [PubMed]
    [Google Scholar]
  55. Gamba P, Jonker MJ, Hamoen LW. A novel feedback loop that controls bimodal expression of genetic competence. PLoS Genet 2015; 11:e1005047 [View Article] [PubMed]
    [Google Scholar]
  56. Lamm-Schmidt V, Fuchs M, Sulzer J, Gerovac M, Hör J et al. Grad-seq identifies KhpB as a global RNA-binding protein in Clostridioides difficile that regulates toxin production. Microlife 2021; 2:uqab004 [View Article] [PubMed]
    [Google Scholar]
  57. Kudla G, Granneman S, Hahn D, Beggs JD, Tollervey D. Cross-linking, ligation, and sequencing of hybrids reveals RNA-RNA interactions in yeast. Proc Natl Acad Sci U S A 2011; 108:10010–10015 [View Article] [PubMed]
    [Google Scholar]
  58. Granneman S, Kudla G, Petfalski E, Tollervey D. Identification of protein binding sites on U3 snoRNA and pre-rRNA by UV cross-linking and high-throughput analysis of cDNAs. Proc Natl Acad Sci U S A 2009; 106:9613–9618 [View Article] [PubMed]
    [Google Scholar]
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