Abstract
Transcription start site (TSS) usage is a critical factor in the regulation of gene expression. A number of methods for global TSS mapping have been developed, but barriers of expense, technical difficulty, time, and/or cost have limited their broader adoption. To address these issues, we developed Survey of TRanscription Initiation at Promoter Elements with high-throughput sequencing (STRIPE-seq). Requiring only three enzymatic steps with intervening bead cleanups, a STRIPE-seq library can be prepared from as little as 50 ng total RNA in ~5 h at a cost of ~$12 (US). In addition to profiling TSS usage, STRIPE-seq provides information on transcript levels that can be used for differential expression analysis. Thanks to its simplicity and low cost, we envision that STRIPE-seq could be employed by any molecular biology laboratory interested in profiling transcription initiation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Calvo SE, Pagliarini DJ, Mootha VK (2009) Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans. Proc Natl Acad Sci 106:7507–7512. https://doi.org/10.1073/pnas.0810916106
Malabat C, Feuerbach F, Ma L, Saveanu C, Jacquier A (2015) Quality control of transcription start site selection by nonsense-mediated-mRNA decay. eLife 4:e06722. https://doi.org/10.7554/eLife.06722
Kurihara Y, Makita Y, Kawashima M, Fujita T, Iwasaki S, Matsui M (2018) Transcripts from downstream alternative transcription start sites evade uORF-mediated inhibition of gene expression in Arabidopsis. Proc Natl Acad Sci 115:7831–7836. https://doi.org/10.1073/pnas.1804971115
Mejía-Guerra MK, Li W, Galeano NF, Vidal M, Gray J, Doseff AI, Grotewold E (2015) Core promoter plasticity between maize tissues and genotypes contrasts with predominance of sharp transcription initiation sites. Plant Cell 27:3309–3320. https://doi.org/10.1105/tpc.15.00630
Ushijima T, Hanada K, Gotoh E, Yamori W, Kodama Y, Tanaka H, Kusano M, Fukushima A, Tokizawa M, Yamamoto YY, Tada Y, Suzuki Y, Matsushita T (2017) Light controls protein localization through Phytochrome-mediated alternative promoter selection. Cell 171:1316–1325.e12. https://doi.org/10.1016/j.cell.2017.10.018
Reyes A, Huber W (2018) Alternative start and termination sites of transcription drive most transcript isoform differences across human tissues. Nucleic Acids Res 46:582–592. https://doi.org/10.1093/nar/gkx1165
Pal S, Gupta R, Kim H, Wickramasinghe P, Baubet V, Showe LC, Dahmane N, Davuluri RV (2011) Alternative transcription exceeds alternative splicing in generating the transcriptome diversity of cerebellar development. Genome Res 21:1260–1272. https://doi.org/10.1101/gr.120535.111
Haberle V, Li N, Hadzhiev Y, Plessy C, Previti C, Nepal C, Gehrig J, Dong X, Akalin A, Suzuki AM, van Ijcken WFJ, Armant O, Ferg M, Strahle U, Carninci P, Muller F, Lenhard B (2014) Two independent transcription initiation codes overlap on vertebrate core promoters. Nature 507:381–385. https://doi.org/10.1038/nature12974
Boyd M, Thodberg M, Vitezic M, Bornholdt J, Vitting-Seerup K, Chen Y, Coskun M, Li Y, Lo BZS, Klausen P, Jan Schweiger P, Pedersen AG, Rapin N, Skovgaard K, Dahlgaard K, Andersson R, Terkelsen TB, Lilje B, Troelsen JT, Petersen AM, Jensen KB, Gögenur I, Thielsen P, Seidelin JB, Nielsen OH, Bjerrum JT, Sandelin A (2018) Characterization of the enhancer and promoter landscape of inflammatory bowel disease from human colon biopsies. Nat Commun 9:1661. https://doi.org/10.1038/s41467-018-03766-z
Demircioğlu D, Cukuroglu E, Kindermans M, Nandi T, Calabrese C, Fonseca NA, Kahles A, Lehmann K-V, Stegle O, Brazma A, Brooks AN, Rätsch G, Tan P, Göke J (2019) A pan-cancer transcriptome analysis reveals pervasive regulation through alternative promoters. Cell 178:1465–1477.e17. https://doi.org/10.1016/j.cell.2019.08.018
Murata M, Nishiyori-Sueki H, Kojima-Ishiyama M, Carninci P, Hayashizaki Y, Itoh M (2014) Detecting expressed genes using CAGE. In: Miyamoto-Sato E, Ohashi H, Sasaki H, Nishikawa J, Yanagawa H (eds) Transcription factor regulatory networks: methods and protocols. Springer, New York, NY, pp 67–85
Bhardwaj V, Semplicio G, Erdogdu NU, Manke T, Akhtar A (2019) MAPCap allows high-resolution detection and differential expression analysis of transcription start sites. Nat Commun 10:3219. https://doi.org/10.1038/s41467-019-11115-x
Wakaguri H, Yamashita R, Suzuki Y, Sugano S, Nakai K (2007) DBTSS: database of transcription start sites, progress report 2008. Nucleic Acids Res 36:D97–D101. https://doi.org/10.1093/nar/gkm901
Ni T, Corcoran DL, Rach EA, Song S, Spana EP, Gao Y, Ohler U, Zhu J (2010) A paired-end sequencing strategy to map the complex landscape of transcription initiation. Nat Methods 7:521–527. https://doi.org/10.1038/nmeth.1464
Arribere JA, Gilbert WV (2013) Roles for transcript leaders in translation and mRNA decay revealed by transcript leader sequencing. Genome Res 23:977–987. https://doi.org/10.1101/gr.150342.112
Pelechano V, Wei W, Steinmetz LM (2013) Extensive transcriptional heterogeneity revealed by isoform profiling. Nature 497:127. https://doi.org/10.1038/nature12121
Gu W, Lee H-C, Chaves D, Youngman EM, Pazour GJ, Conte D, Mello CC (2012) CapSeq and CIP-TAP identify pol II start sites and reveal capped small RNAs as C. elegans piRNA precursors. Cell 151:1488–1500. https://doi.org/10.1016/j.cell.2012.11.023
Park D, Morris AR, Battenhouse A, Iyer VR (2014) Simultaneous mapping of transcript ends at single-nucleotide resolution and identification of widespread promoter-associated non-coding RNA governed by TATA elements. Nucleic Acids Res 42:3736–3749. https://doi.org/10.1093/nar/gkt1366
Core LJ, Martins AL, Danko CG, Waters C, Siepel A, Lis JT (2014) Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers. Nat Genet 46:1311–1320. https://doi.org/10.1038/ng.3142
Kazuo M, Sumio S (1994) Oligo-capping: a simple method to replace the cap structure of eukaryotic mRNAs with oligoribonucleotides. Gene 138:171–174. https://doi.org/10.1016/0378-1119(94)90802-8
Negroni M, Buc H (2001) Retroviral recombination: what drives the switch? Nat Rev Mol Cell Biol 2:151–155. https://doi.org/10.1038/35052098
Zhu Y, Machleder E, Chenchik A, Li R, Siebert P (2001) Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction. BioTechniques 30:892–897
Wulf MG, Maguire S, Humbert P, Dai N, Bei Y, Nichols NM, Corrêa IR, Guan S (2019) Non-templated addition and template switching by Moloney murine leukemia virus (MMLV)-based reverse transcriptases co-occur and compete with each other. J Biol Chem 294:18220–18231. https://doi.org/10.1074/jbc.RA119.010676
Zhang Z, Dietrich FS (2005) Mapping of transcription start sites in Saccharomyces cerevisiae using 5′ SAGE. Nucleic Acids Res 33:2838–2851. https://doi.org/10.1093/nar/gki583
Batut P, Dobin A, Plessy C, Carninci P, Gingeras TR (2013) High-fidelity promoter profiling reveals widespread alternative promoter usage and transposon-driven developmental gene expression. Genome Res 23:169–180. https://doi.org/10.1101/gr.139618.112
Cumbie JS, Ivanchenko MG, Megraw M (2015) NanoCAGE-XL and CapFilter: an approach to genome wide identification of high confidence transcription start sites. BMC Genomics 16:597. https://doi.org/10.1186/s12864-015-1670-6
Poulain S, Kato S, Arnaud O, Morlighem J-É, Suzuki M, Plessy C, Harbers M (2017) NanoCAGE: a method for the analysis of coding and noncoding 5′-capped transcriptomes. In: Napoli S (ed) Promoter associated RNA: methods and protocols. Springer, New York, NY, pp 57–109
Cole C, Byrne A, Beaudin AE, Forsberg EC, Vollmers C (2018) Tn5Prime, a Tn5 based 5′ capture method for single cell RNA-seq. Nucleic Acids Res 46:e62–e62. https://doi.org/10.1093/nar/gky182
Schon MA, Kellner MJ, Plotnikova A, Hofmann F, Nodine MD (2018) NanoPARE: parallel analysis of RNA 5′ ends from low-input RNA. Genome Res. https://doi.org/10.1101/gr.239202.118
Islam S, Kjällquist U, Moliner A, Zajac P, Fan J-B, Lönnerberg P, Linnarsson S (2011) Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res 21:1160–1167. https://doi.org/10.1101/gr.110882.110
Picelli S, Björklund ÅK, Faridani OR, Sagasser S, Winberg G, Sandberg R (2013) Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096. https://doi.org/10.1038/nmeth.2639
Hagemann-Jensen M, Ziegenhain C, Chen P, Ramsköld D, Hendriks G-J, Larsson AJM, Faridani OR, Sandberg R (2020) Single-cell RNA counting at allele and isoform resolution using smart-seq3. Nat Biotechnol 38:708–714. https://doi.org/10.1038/s41587-020-0497-0
Bagnoli JW, Ziegenhain C, Janjic A, Wange LE, Vieth B, Parekh S, Geuder J, Hellmann I, Enard W (2018) Sensitive and powerful single-cell RNA sequencing using mcSCRB-seq. Nat Commun 9:2937. https://doi.org/10.1038/s41467-018-05347-6
Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM, Trombetta JJ, Weitz DA, Sanes JR, Shalek AK, Regev A, McCarroll SA (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161(5):1202–1214. https://doi.org/10.1016/j.cell.2015.05.002
Zheng GXY, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R, Ziraldo SB, Wheeler TD, McDermott GP, Zhu J, Gregory MT, Shuga J, Montesclaros L, Underwood JG, Masquelier DA, Nishimura SY, Schnall-Levin M, Wyatt PW, Hindson CM, Bharadwaj R, Wong A, Ness KD, Beppu LW, Deeg HJ, McFarland C, Loeb KR, Valente WJ, Ericson NG, Stevens EA, Radich JP, Mikkelsen TS, Hindson BJ, Bielas JH (2017) Massively parallel digital transcriptional profiling of single cells. Nature Communications 8(1) https://doi.org/10.1038/ncomms14049
Policastro RA, Raborn RT, Brendel VP, Zentner GE (2020) Simple and efficient profiling of transcription initiation and transcript levels with STRIPE-seq. Genome Res 30:910–923. https://doi.org/10.1101/gr.261545.120
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Genome Project Data Processing S (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079. https://doi.org/10.1093/bioinformatics/btp352
Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
Smith TS, Heger A, Sudbery I (2017) UMI-tools: modelling sequencing errors in unique molecular identifiers to improve quantification accuracy. Genome Res 27(3):491–499. https://doi.org/10.1101/gr.209601.116
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17(3). https://doi.org/10.14806/ej.17.1.200
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21. https://doi.org/10.1093/bioinformatics/bts635
Policastro RA, McDonald DJ, Brendel VP, Zentner GE (2021) Flexible analysis of TSS mapping data and detection of TSS shifts with TSRexploreR. NAR Genom and Bioinforma 3:lqab051. https://doi.org/10.1093/nargab/lqab051
Carninci P, Sandelin A, Lenhard B, Katayama S, Shimokawa K, Ponjavic J, Semple CA, Taylor MS, Engstrom PG, Frith MC (2006) Genome-wide analysis of mammalian promoter architecture and evolution. Nat Genet 38:626–635. https://doi.org/10.1038/ng1789
Zajac P, Islam S, Hochgerner H, Lönnerberg P, Linnarsson S (2014) Base preferences in non-templated nucleotide incorporation by MMLV-derived reverse Transcriptases. PLoS One 8:e85270. https://doi.org/10.1371/journal.pone.0085270
Policastro RA, McDonald DJ, Brendel VP, Zentner GE, (2021) Flexible analysis of TSS mapping data and detection of TSS shifts with TSRexploreR. NAR Genomics and Bioinformatics 3(2) https://doi.org/10.1093/nargab/lqab051
Rohland N, Reich D (2012) Cost-effective, high-throughput DNA sequencing libraries for multiplexed target capture. Genome Res 22:939–946. https://doi.org/10.1101/gr.128124.111
Krueger F, Andrews SR, Osborne CS (2011) Large scale loss of data in low-diversity Illumina sequencing libraries can be recovered by deferred cluster calling. PLoS One 6:e16607. https://doi.org/10.1371/journal.pone.0016607
Mitra A, Skrzypczak M, Ginalski K, Rowicka M (2015) Strategies for achieving high sequencing accuracy for low diversity samples and avoiding sample bleeding using illumina platform. PLoS One 10:e0120520–e0120520. https://doi.org/10.1371/journal.pone.0120520
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Policastro, R.A., Zentner, G.E. (2022). Genome-Wide Profiling of Transcription Initiation with STRIPE-seq. In: Devaux, F. (eds) Yeast Functional Genomics. Methods in Molecular Biology, vol 2477. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2257-5_2
Download citation
DOI: https://doi.org/10.1007/978-1-0716-2257-5_2
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-2256-8
Online ISBN: 978-1-0716-2257-5
eBook Packages: Springer Protocols