Comparative analyses suggest a link between mRNA splicing, stability, and RNA covalent modifications in flowering plants.
Angiosperms
Comparative transcriptomics
RNA
RNA covalent modifications
RNA decay
Journal
BMC plant biology
ISSN: 1471-2229
Titre abrégé: BMC Plant Biol
Pays: England
ID NLM: 100967807
Informations de publication
Date de publication:
12 Aug 2024
12 Aug 2024
Historique:
received:
23
05
2024
accepted:
05
08
2024
medline:
13
8
2024
pubmed:
13
8
2024
entrez:
12
8
2024
Statut:
epublish
Résumé
In recent years, covalent modifications on RNA nucleotides have emerged as pivotal moieties influencing the structure, function, and regulatory processes of RNA Polymerase II transcripts such as mRNAs and lncRNAs. However, our understanding of their biological roles and whether these roles are conserved across eukaryotes remains limited. In this study, we leveraged standard polyadenylation-enriched RNA-sequencing data to identify and characterize RNA modifications that introduce base-pairing errors into cDNA reads. Our investigation incorporated data from three Poaceae (Zea mays, Sorghum bicolor, and Setaria italica), as well as publicly available data from a range of stress and genetic contexts in Sorghum and Arabidopsis thaliana. We uncovered a strong enrichment of RNA covalent modifications (RCMs) deposited on a conserved core set of nuclear mRNAs involved in photosynthesis and translation across these species. However, the cohort of modified transcripts changed based on environmental context and developmental program, a pattern that was also conserved across flowering plants. We determined that RCMs can partly explain accession-level differences in drought tolerance in Sorghum, with stress-associated genes receiving a higher level of RCMs in a drought tolerant accession. To address function, we determined that RCMs are significantly enriched near exon junctions within coding regions, suggesting an association with splicing. Intriguingly, we found that these base-pair disrupting RCMs are associated with stable mRNAs, are highly correlated with protein abundance, and thus likely associated with facilitating translation. Our data point to a conserved role for RCMs in mRNA stability and translation across the flowering plant lineage.
Sections du résumé
BACKGROUND
BACKGROUND
In recent years, covalent modifications on RNA nucleotides have emerged as pivotal moieties influencing the structure, function, and regulatory processes of RNA Polymerase II transcripts such as mRNAs and lncRNAs. However, our understanding of their biological roles and whether these roles are conserved across eukaryotes remains limited.
RESULTS
RESULTS
In this study, we leveraged standard polyadenylation-enriched RNA-sequencing data to identify and characterize RNA modifications that introduce base-pairing errors into cDNA reads. Our investigation incorporated data from three Poaceae (Zea mays, Sorghum bicolor, and Setaria italica), as well as publicly available data from a range of stress and genetic contexts in Sorghum and Arabidopsis thaliana. We uncovered a strong enrichment of RNA covalent modifications (RCMs) deposited on a conserved core set of nuclear mRNAs involved in photosynthesis and translation across these species. However, the cohort of modified transcripts changed based on environmental context and developmental program, a pattern that was also conserved across flowering plants. We determined that RCMs can partly explain accession-level differences in drought tolerance in Sorghum, with stress-associated genes receiving a higher level of RCMs in a drought tolerant accession. To address function, we determined that RCMs are significantly enriched near exon junctions within coding regions, suggesting an association with splicing. Intriguingly, we found that these base-pair disrupting RCMs are associated with stable mRNAs, are highly correlated with protein abundance, and thus likely associated with facilitating translation.
CONCLUSIONS
CONCLUSIONS
Our data point to a conserved role for RCMs in mRNA stability and translation across the flowering plant lineage.
Identifiants
pubmed: 39134938
doi: 10.1186/s12870-024-05486-7
pii: 10.1186/s12870-024-05486-7
doi:
Substances chimiques
RNA, Messenger
0
RNA, Plant
0
Types de publication
Journal Article
Comparative Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
768Subventions
Organisme : Division of Biological Infrastructure
ID : 1743442
Organisme : Division of Integrative Organismal Systems
ID : 2023310
Organisme : Division of Integrative Organismal Systems
ID : 2023310
Organisme : Division of Molecular and Cellular Biosciences
ID : 2120131
Informations de copyright
© 2024. The Author(s).
Références
Cappannini A, Ray A, Purta E, Mukherjee S, Boccaletto P, Moafinejad SN, et al. MODOMICS: a database of RNA modifications and related information. 2023 update. Nucleic Acids Res. 2024;52:D239–44.
pubmed: 38015436
doi: 10.1093/nar/gkad1083
Baumer ZT, Erber L, Jolley E, Lawrence S, Lin C, Murakami S, et al. Defining the commonalities between post-transcriptional and post-translational modification communities. Trends Biochem Sci. 2024;49:185–8.
pubmed: 37884411
doi: 10.1016/j.tibs.2023.09.011
Saletore Y, Meyer K, Korlach J, Vilfan ID, Jaffrey S, Mason CE. The birth of the Epitranscriptome: deciphering the function of RNA modifications. Genome Biol. 2012;13:175.
pubmed: 23113984
pmcid: 3491402
doi: 10.1186/gb-2012-13-10-175
Gilbert WV, Nachtergaele S. mRNA regulation by RNA modifications. Annu Rev Biochem. 2023;92:175–98.
pubmed: 37018844
pmcid: 11192554
doi: 10.1146/annurev-biochem-052521-035949
Lewis CJT, Pan T, Kalsotra A. RNA modifications and structures cooperate to guide RNA-protein interactions. Nat Rev Mol Cell Biol. 2017;18:202–10.
pubmed: 28144031
pmcid: 5542016
doi: 10.1038/nrm.2016.163
Roy B. Effects of mRNA modifications on translation: an overview. In: McMahon M, editor. RNA modifications: methods and protocols. New York, NY: Springer US; 2021. pp. 327–56.
doi: 10.1007/978-1-0716-1374-0_20
Prall W, Ganguly DR, Gregory BD. The covalent nucleotide modifications within plant mRNAs: what we know, how we find them, and what should be done in the future. Plant Cell. 2023;35:1801–16.
pubmed: 36794718
pmcid: 10226571
doi: 10.1093/plcell/koad044
Sharma B, Prall W, Bhatia G, Gregory BD. The diversity and functions of plant RNA modifications: what we know and where we go from Here. Annu Rev Plant Biol. 2023;74:53–85.
pubmed: 36917824
doi: 10.1146/annurev-arplant-071122-085813
Kramer MC, Janssen KA, Palos K, Nelson ADL, Vandivier LE, Garcia BA, et al. N6-methyladenosine and RNA secondary structure affect transcript stability and protein abundance during systemic salt stress in Arabidopsis. Plant Direct. 2020;4:e00239.
pubmed: 32724893
pmcid: 7379018
doi: 10.1002/pld3.239
Sun H, Li K, Liu C, Yi C. Regulation and functions of non-m6A mRNA modifications. Nat Rev Mol Cell Biol. 2023;24:714–31.
pubmed: 37369853
doi: 10.1038/s41580-023-00622-x
Luo G-Z, MacQueen A, Zheng G, Duan H, Dore LC, Lu Z, et al. Unique features of the m6A methylome in Arabidopsis thaliana. Nat Commun. 2014;5:5630.
pubmed: 25430002
doi: 10.1038/ncomms6630
Perry RP, Kelley DE, Friderici K, Rottman F. The methylated constituents of L cell messenger RNA: evidence for an unusual cluster at the 5’ terminus. Cell. 1975;4:387–94.
pubmed: 1168101
doi: 10.1016/0092-8674(75)90159-2
Wiener D, Schwartz S. The epitranscriptome beyond m6A. Nat Rev Genet. 2021;22:119–31.
pubmed: 33188361
doi: 10.1038/s41576-020-00295-8
Vandivier LE, Campos R, Kuksa PP, Silverman IM, Wang L-S, Gregory BD. Chemical modifications mark alternatively spliced and uncapped Messenger RNAs in Arabidopsis. Plant Cell. 2015;27:3024–37.
pubmed: 26561561
pmcid: 4682304
doi: 10.1105/tpc.15.00591
Tan K-T, Ding L-W, Wu C-S, Tenen DG, Yang H. Repurposing RNA sequencing for discovery of RNA modifications in clinical cohorts. Sci Adv. 2021;7.
Kannan K, Nelson ADL, Shippen DE. Dyskerin is a component of the Arabidopsis telomerase RNP required for telomere maintenance. Mol Cell Biol. 2008;28:2332–41.
pubmed: 18212040
pmcid: 2268427
doi: 10.1128/MCB.01490-07
Sun L, Xu Y, Bai S, Bai X, Zhu H, Dong H, et al. Transcriptome-wide analysis of pseudouridylation of mRNA and non-coding RNAs in Arabidopsis. J Exp Bot. 2019;70:5089–600.
pubmed: 31173101
pmcid: 6793436
doi: 10.1093/jxb/erz273
Rintala-Dempsey AC, Kothe U. Eukaryotic stand-alone pseudouridine synthases - RNA modifying enzymes and emerging regulators of gene expression? RNA Biol. 2017;14:1185–96.
pubmed: 28045575
pmcid: 5699540
doi: 10.1080/15476286.2016.1276150
Zhang M, Zhang X, Ma Y, Yi C. New directions for Ψ and m1A decoding in mRNA: deciphering the stoichiometry and function. RNA. 2024;30:537–47.
pubmed: 38531648
pmcid: 11019747
doi: 10.1261/rna.079950.124
Yang Y, Hsu PJ, Chen Y-S, Yang Y-G. Dynamic transcriptomic m6A decoration: writers, erasers, readers and functions in RNA metabolism. Cell Res. 2018;28:616–24.
pubmed: 29789545
pmcid: 5993786
doi: 10.1038/s41422-018-0040-8
Flamand MN, Tegowski M, Meyer KD. The proteins of mRNA modification: writers, readers, and Erasers. Annu Rev Biochem. 2023;92:145–73.
pubmed: 37068770
pmcid: 10443600
doi: 10.1146/annurev-biochem-052521-035330
Wilkinson E, Cui Y-H, He Y-Y. Roles of RNA modifications in Diverse Cellular functions. Front Cell Dev Biol. 2022;10:828683.
pubmed: 35350378
pmcid: 8957929
doi: 10.3389/fcell.2022.828683
Dominissini D, Moshitch-Moshkovitz S, Schwartz S, Salmon-Divon M, Ungar L, Osenberg S, et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature. 2012;485:201–6.
pubmed: 22575960
doi: 10.1038/nature11112
Li M, Tao Z, Zhao Y, Li L, Zheng J, Li Z, et al. 5-methylcytosine RNA methyltransferases and their potential roles in cancer. J Transl Med. 2022;20:214.
pubmed: 35562754
pmcid: 9102922
doi: 10.1186/s12967-022-03427-2
Chen X, Li A, Sun B-F, Yang Y, Han Y-N, Yuan X, et al. 5-methylcytosine promotes pathogenesis of bladder cancer through stabilizing mRNAs. Nat Cell Biol. 2019;21:978–90.
pubmed: 31358969
doi: 10.1038/s41556-019-0361-y
Barbieri I, Kouzarides T. Role of RNA modifications in cancer. Nat Rev Cancer. 2020;20:303–22.
pubmed: 32300195
doi: 10.1038/s41568-020-0253-2
Zhong S, Li H, Bodi Z, Button J, Vespa L, Herzog M, et al. MTA is an Arabidopsis messenger RNA adenosine methylase and interacts with a homolog of a sex-specific splicing factor. Plant Cell. 2008;20:1278–88.
pubmed: 18505803
pmcid: 2438467
doi: 10.1105/tpc.108.058883
Yang W, Meng J, Liu J, Ding B, Tan T, Wei Q, et al. The N1-Methyladenosine methylome of Petunia mRNA. Plant Physiol. 2020;183:1710–24.
pubmed: 32461301
pmcid: 7401140
doi: 10.1104/pp.20.00382
Cui X, Liang Z, Shen L, Zhang Q, Bao S, Geng Y, et al. 5-Methylcytosine RNA methylation in Arabidopsis Thaliana. Mol Plant. 2017;10:1387–99.
pubmed: 28965832
doi: 10.1016/j.molp.2017.09.013
David R, Burgess A, Parker B, Li J, Pulsford K, Sibbritt T, et al. Transcriptome-wide mapping of RNA 5-Methylcytosine in Arabidopsis mRNAs and noncoding RNAs. Plant Cell. 2017;29:445–60.
pubmed: 28062751
pmcid: 5385953
doi: 10.1105/tpc.16.00751
Decatur WA, Fournier MJ. rRNA modifications and ribosome function. Trends Biochem Sci. 2002;27:344–51.
pubmed: 12114023
doi: 10.1016/S0968-0004(02)02109-6
Zhou KI, Shi H, Lyu R, Wylder AC, Matuszek Ż, Pan JN, et al. Regulation of co-transcriptional Pre-mRNA splicing by m6A through the low-complexity protein hnRNPG. Mol Cell. 2019;76:70–e819.
pubmed: 31445886
pmcid: 6778029
doi: 10.1016/j.molcel.2019.07.005
Uzonyi A, Dierks D, Nir R, Kwon OS, Toth U, Barbosa I, et al. Exclusion of m6A from splice-site proximal regions by the exon junction complex dictates m6A topologies and mRNA stability. Mol Cell. 2023;83:237–e517.
pubmed: 36599352
doi: 10.1016/j.molcel.2022.12.026
Yang X, Triboulet R, Liu Q, Sendinc E, Gregory RI. Exon junction complex shapes the m6A epitranscriptome. Nat Commun. 2022;13:7904.
pubmed: 36550132
pmcid: 9780246
doi: 10.1038/s41467-022-35643-1
Karikó K, Muramatsu H, Welsh FA, Ludwig J, Kato H, Akira S, et al. Incorporation of pseudouridine into mRNA yields superior nonimmunogenic vector with increased translational capacity and biological stability. Mol Ther. 2008;16:1833–40.
pubmed: 18797453
doi: 10.1038/mt.2008.200
Eyler DE, Franco MK, Batool Z, Wu MZ, Dubuke ML, Dobosz-Bartoszek M, et al. Pseudouridinylation of mRNA coding sequences alters translation. Proc Natl Acad Sci U S A. 2019;116:23068–74.
pubmed: 31672910
pmcid: 6859337
doi: 10.1073/pnas.1821754116
Zhang Q, Kim N-K, Feigon J. Architecture of human telomerase RNA. Proc Natl Acad Sci U S A. 2011;108:20325–32.
pubmed: 21844345
pmcid: 3251123
doi: 10.1073/pnas.1100279108
Kim N-K, Theimer CA, Mitchell JR, Collins K, Feigon J. Effect of pseudouridylation on the structure and activity of the catalytically essential P6.1 hairpin in human telomerase RNA. Nucleic Acids Res. 2010;38:6746–56.
pubmed: 20554853
pmcid: 2965242
doi: 10.1093/nar/gkq525
Anderson BR, Muramatsu H, Jha BK, Silverman RH, Weissman D, Karikó K. Nucleoside modifications in RNA limit activation of 2’-5’-oligoadenylate synthetase and increase resistance to cleavage by RNase L. Nucleic Acids Res. 2011;39:9329–38.
pubmed: 21813458
pmcid: 3241635
doi: 10.1093/nar/gkr586
Yang Y, Wang L, Han X, Yang W-L, Zhang M, Ma H-L, et al. RNA 5-Methylcytosine facilitates the maternal-to-zygotic transition by preventing maternal mRNA decay. Mol Cell. 2019;75:1188–e20211.
pubmed: 31399345
doi: 10.1016/j.molcel.2019.06.033
Zhang Y, Lu L, Li X. Detection technologies for RNA modifications. Exp Mol Med. 2022;54:1601–16.
pubmed: 36266445
pmcid: 9636272
doi: 10.1038/s12276-022-00821-0
Schaefer M, Pollex T, Hanna K, Lyko F. RNA cytosine methylation analysis by bisulfite sequencing. Nucleic Acids Res. 2009;37:e12.
pubmed: 19059995
doi: 10.1093/nar/gkn954
Woodson SA, Muller JG, Burrows CJ, Rokita SE. A primer extension assay for modification of guanine by Ni(II) complexes. Nucleic Acids Res. 1993;21:5524–5.
pubmed: 8265373
pmcid: 310599
doi: 10.1093/nar/21.23.5524
Ryvkin P, Leung YY, Silverman IM, Childress M, Valladares O, Dragomir I, et al. HAMR: high-throughput annotation of modified ribonucleotides. RNA. 2013;19:1684–92.
pubmed: 24149843
pmcid: 3884653
doi: 10.1261/rna.036806.112
Ebhardt HA, Tsang HH, Dai DC, Liu Y, Bostan B, Fahlman RP. Meta-analysis of small RNA-sequencing errors reveals ubiquitous post-transcriptional RNA modifications. Nucleic Acids Res. 2009;37:2461–70.
pubmed: 19255090
pmcid: 2677864
doi: 10.1093/nar/gkp093
Findeiss S, Langenberger D, Stadler PF, Hoffmann S. Traces of post-transcriptional RNA modifications in deep sequencing data. Biol Chem. 2011;392:305–13.
pubmed: 21345160
doi: 10.1515/bc.2011.043
Motorin Y, Muller S, Behm-Ansmant I, Branlant C. Identification of modified residues in RNAs by reverse transcription-based methods. Methods Enzymol. 2007;425:21–53.
pubmed: 17673078
doi: 10.1016/S0076-6879(07)25002-5
Todkari IA, Chandrasekaran AR, Punnoose JA, Mao S, Haruehanroengra P, Beckles C, et al. Resolving altered base-pairing of RNA modifications with DNA nanoswitches. Nucleic Acids Res. 2023;51:11291–7.
pubmed: 37811879
pmcid: 10639047
doi: 10.1093/nar/gkad802
Chiu NHL, Simpson JH, Wang H, Tannous BA. A theoretical perspective of the physical properties of different RNA modifications with respect to RNA duplexes. BBA Adv. 2021;1:100025.
pubmed: 37082016
pmcid: 10074902
doi: 10.1016/j.bbadva.2021.100025
Katz K, Shutov O, Lapoint R, Kimelman M, Brister JR, O’Sullivan C. The sequence read Archive: a decade more of explosive growth. Nucleic Acids Res. 2022;50:D387–90.
pubmed: 34850094
doi: 10.1093/nar/gkab1053
Helm M, Motorin Y. Detecting RNA modifications in the epitranscriptome: predict and validate. Nat Rev Genet. 2017;18:275–91.
pubmed: 28216634
doi: 10.1038/nrg.2016.169
Hauenschild R, Tserovski L, Schmid K, Thüring K, Winz M-L, Sharma S, et al. The reverse transcription signature of N-1-methyladenosine in RNA-Seq is sequence dependent. Nucleic Acids Res. 2015;43:9950–64.
pubmed: 26365242
pmcid: 4787781
Wang Y, Li S, Zhao Y, You C, Le B, Gong Z, et al. NAD
pubmed: 31142655
pmcid: 6575598
doi: 10.1073/pnas.1903682116
Mergner J, Frejno M, List M, Papacek M, Chen X, Chaudhary A, et al. Mass-spectrometry-based draft of the Arabidopsis proteome. Nature. 2020;579:409–14.
pubmed: 32188942
doi: 10.1038/s41586-020-2094-2
McCormick RF, Truong SK, Sreedasyam A, Jenkins J, Shu S, Sims D, et al. The Sorghum bicolor reference genome: improved assembly, gene annotations, a transcriptome atlas, and signatures of genome organization. Plant J. 2018;93:338–54.
pubmed: 29161754
doi: 10.1111/tpj.13781
Klepikova AV, Kasianov AS, Gerasimov ES, Logacheva MD, Penin AA. A high resolution map of the Arabidopsis thaliana developmental transcriptome based on RNA-seq profiling. Plant J. 2016;88:1058–70.
pubmed: 27549386
doi: 10.1111/tpj.13312
Kryuchkova-Mostacci N, Robinson-Rechavi M. A benchmark of gene expression tissue-specificity metrics. Brief Bioinform. 2017;18:205–14.
pubmed: 26891983
Matilla MA, Espinosa-Urgel M, Rodríguez-Herva JJ, Ramos JL, Ramos-González MI. Genomic analysis reveals the major driving forces of bacterial life in the rhizosphere. Genome Biol. 2007;8:R179.
pubmed: 17784941
pmcid: 2375017
doi: 10.1186/gb-2007-8-9-r179
Sullivan A, Purohit PK, Freese NH, Pasha A, Esteban E, Waese J, et al. An eFP-Seq browser for visualizing and exploring RNA sequencing data. Plant J. 2019;100:641–54.
pubmed: 31350781
pmcid: 6899666
doi: 10.1111/tpj.14468
Murat F, Armero A, Pont C, Klopp C, Salse J. Reconstructing the genome of the most recent common ancestor of flowering plants. Nat Genet. 2017;49:490–6.
pubmed: 28288112
doi: 10.1038/ng.3813
Sharma B, Govindan G, Li Y, Sunkar R, Gregory BD. RNA N6-Methyladenosine affects Copper-Induced oxidative stress response in Arabidopsis thaliana. Noncoding RNA. 2024;10.
Prall W, Sheikh AH, Bazin J, Bigeard J, Almeida-Trapp M, Crespi M, et al. Pathogen-induced m6A dynamics affect plant immunity. Plant Cell. 2023;35:4155–72.
pubmed: 37610247
doi: 10.1093/plcell/koad224
Govindan G, Sharma B, Li Y-F, Armstrong CD, Merum P, Rohila JS, et al. mRNA N6 -methyladenosine is critical for cold tolerance in Arabidopsis. Plant J. 2022;111:1052–68.
pubmed: 35710867
pmcid: 9543165
doi: 10.1111/tpj.15872
Cheng Q, Wang P, Wu G, Wang Y, Tan J, Li C, et al. Coordination of m6A mRNA methylation and gene transcriptome in rice response to cadmium stress. Rice. 2021;14:62.
pubmed: 34224034
pmcid: 8257850
doi: 10.1186/s12284-021-00502-y
Hu J, Cai J, Park SJ, Lee K, Li Y, Chen Y, et al. N6 -Methyladenosine mRNA methylation is important for salt stress tolerance in Arabidopsis. Plant J. 2021;106:1759–75.
pubmed: 33843075
doi: 10.1111/tpj.15270
Varoquaux N, Cole B, Gao C, Pierroz G, Baker CR, Patel D, et al. Transcriptomic analysis of field-droughted sorghum from seedling to maturity reveals biotic and metabolic responses. Proc Natl Acad Sci U S A. 2019;116:27124–32.
pubmed: 31806758
pmcid: 6936495
doi: 10.1073/pnas.1907500116
Sorenson RS, Deshotel MJ, Johnson K, Adler FR, Sieburth LE. Arabidopsis mRNA decay landscape arises from specialized RNA decay substrates, decapping-mediated feedback, and redundancy. Proc Natl Acad Sci U S A. 2018;115:E1485–94.
pubmed: 29386391
pmcid: 5816150
doi: 10.1073/pnas.1712312115
Deyholos MK, Cavaness GF, Hall B, King E, Punwani J, Van Norman J, et al. VARICOSE, a WD-domain protein, is required for leaf blade development. Development. 2003;130:6577–88.
pubmed: 14660546
doi: 10.1242/dev.00909
Zhang W, Murphy C, Sieburth LE. Conserved RNaseII domain protein functions in cytoplasmic mRNA decay and suppresses Arabidopsis decapping mutant phenotypes. Proc Natl Acad Sci U S A. 2010;107:15981–5.
pubmed: 20798041
pmcid: 2936607
doi: 10.1073/pnas.1007060107
Lubas M, Damgaard CK, Tomecki R, Cysewski D, Jensen TH, Dziembowski A. Exonuclease hDIS3L2 specifies an exosome-independent 3’-5’ degradation pathway of human cytoplasmic mRNA. EMBO J. 2013;32:1855–68.
pubmed: 23756462
pmcid: 3981170
doi: 10.1038/emboj.2013.135
Malecki M, Viegas SC, Carneiro T, Golik P, Dressaire C, Ferreira MG, et al. The exoribonuclease Dis3L2 defines a novel eukaryotic RNA degradation pathway. EMBO J. 2013;32:1842–54.
pubmed: 23503588
pmcid: 3981172
doi: 10.1038/emboj.2013.63
Hug N, Longman D, Cáceres JF. Mechanism and regulation of the nonsense-mediated decay pathway. Nucleic Acids Res. 2016;44:1483–95.
pubmed: 26773057
pmcid: 4770240
doi: 10.1093/nar/gkw010
Lee W-C, Hou B-H, Hou C-Y, Tsao S-M, Kao P, Chen H-M. Widespread exon Junction Complex footprints in the RNA degradome Mark mRNA degradation before steady state translation. Plant Cell. 2020;32:904–22.
pubmed: 31988264
pmcid: 7145476
doi: 10.1105/tpc.19.00666
Unterholzner L, Izaurralde E. SMG7 acts as a molecular link between mRNA surveillance and mRNA decay. Mol Cell. 2004;16:587–96.
pubmed: 15546618
doi: 10.1016/j.molcel.2004.10.013
Gloggnitzer J, Akimcheva S, Srinivasan A, Kusenda B, Riehs N, Stampfl H, et al. Nonsense-mediated mRNA decay modulates immune receptor levels to regulate plant antibacterial defense. Cell Host Microbe. 2014;16:376–90.
pubmed: 25211079
doi: 10.1016/j.chom.2014.08.010
Cheng JX, Chen L, Li Y, Cloe A, Yue M, Wei J, et al. RNA cytosine methylation and methyltransferases mediate chromatin organization and 5-azacytidine response and resistance in leukaemia. Nat Commun. 2018;9:1163.
pubmed: 29563491
pmcid: 5862959
doi: 10.1038/s41467-018-03513-4
Li Y, Yi Y, Lv J, Gao X, Yu Y, Babu SS, et al. Low RNA stability signifies increased post-transcriptional regulation of cell identity genes. Nucleic Acids Res. 2023;51:6020–38.
pubmed: 37125636
pmcid: 10325912
doi: 10.1093/nar/gkad300
Chen S, Zhou Y, Chen Y, Gu J. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–90.
pubmed: 30423086
pmcid: 6129281
doi: 10.1093/bioinformatics/bty560
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.
pubmed: 22388286
pmcid: 3322381
doi: 10.1038/nmeth.1923
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21.
pubmed: 23104886
doi: 10.1093/bioinformatics/bts635
Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417–9.
pubmed: 28263959
pmcid: 5600148
doi: 10.1038/nmeth.4197
Soneson C, Love MI, Robinson MD. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res. 2015;4:1521.
pubmed: 26925227
doi: 10.12688/f1000research.7563.1
Ferrer-Bonsoms JA, Gimeno M, Olaverri D, Sacristan P, Lobato C, Castilla C, et al. EventPointer 3.0: flexible and accurate splicing analysis that includes studying the differential usage of protein-domains. NAR Genom Bioinform. 2022;4:lqac067.
pubmed: 36128425
pmcid: 9477077
doi: 10.1093/nargab/lqac067
Yu G, Wang L-G, Han Y, He Q-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–7.
pubmed: 22455463
pmcid: 3339379
doi: 10.1089/omi.2011.0118
Team RC. Others. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www R-project org/. 2016.
Wickham H. ggplot2: elegant graphics for data analysis. Springer; 2016.
Yan L, ggvenn. Draw Venn Diagram by ggplot2. R Package Version. 2021;19.
Yu G. Enrichplot: visualization of functional enrichment result. R package version. 2021;1.
Krassowski M. ComplexUpset. ComplexUpset. 2020.
Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847–9.
pubmed: 27207943
doi: 10.1093/bioinformatics/btw313
Yu G. Using ggtree to visualize data on Tree-Like structures. Curr Protoc Bioinf. 2020;69:e96.
doi: 10.1002/cpbi.96