Repurposing RNA sequencing for discovery of RNA modifications in clinical cohorts

Tan, Kian-Lee; Ding, Ling-Wen; Wu, Chan-Shuo; Tenen, Daniel G.; Yang, Henry

doi:10.1126/sciadv.abd2605

Cited by 17 publications

(15 citation statements)

References 114 publications

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“…The U1248 position of 18S is known to be m 1 acp 3 Ψ modified and is located within the ribosome decoding region ( Meyer et al, 2011 ). The U4530 position of 28S is known to be m 3 U modified ( Tan et al, 2021 ). These three rRF modification sites were detected with high mismatch by TGIRT ( Figure 5 ).…”

Section: Discussionmentioning

confidence: 99%

“…These three rRF modification sites were detected with high mismatch by TGIRT ( Figure 5 ). Interestingly, 18S:1248 (m 1 acp 3 Ψ) was suggested to have a lower modification level based on mismatch pattern from long RNA-seq in TCGA tumors, especially READ, UCEC and COAD ( Tan et al, 2021 ). Surprisingly, although rRNA modifications on human ribosomes have very recently been visualized by Cryo-EM ( Natchiar et al, 2017 ), a lot of the rRNA modification enzymatic processes are not well elucidated in humans.…”

Section: Discussionmentioning

confidence: 99%

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Characterization of novel small non-coding RNAs and their modifications in bladder cancer using an updated small RNA-seq workflow

Monshaugen

Klungland

et al. 2022

Front. Mol. Biosci.

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Background: Bladder cancer (BLCA) is one of the most common cancer types worldwide. The disease is responsible for about 200,000 deaths annually, thus improved diagnostics and therapy is needed. A large body of evidence reveal that small RNAs of less than 40 nucleotides may act as tumor suppressors, oncogenes, and disease biomarkers, with a major focus on microRNAs. However, the role of other families of small RNAs is not yet deciphered. Recent results suggest that small RNAs and their modification status, play a role in BLCA development and are promising biomarkers due to their high abundance in the exomes and body fluids (including urine). Moreover, free modified nucleosides have been detected at elevated levels from the urine of BLCA patients. A genome-wide view of small RNAs, and their modifications, will help pinpoint the molecules that could be used as biomarker or has important biology in BLCA development.Methods: BLCA tumor tissue specimens were obtained from 12 patients undergoing transurethral resection of non-muscle invasive papillary urothelial carcinomas. Genome-wide profiling of small RNAs less than 40 bases long was performed by a modified protocol with TGIRT (thermostable group II reverse transcriptase) to identify novel small RNAs and their modification status.Results: Comprehensive analysis identified not only microRNAs. Intriguingly, 57 ± 15% (mean ± S.D.) of sequencing reads mapped to non-microRNA-small RNAs including tRNA-derived fragments (tRFs), ribosomal RNA-derived fragments (rRFs) and YRNA-derived fragments (YRFs). Misincorporation (mismatch) sites identified potential base modification positions on the small RNAs, especially on tRFs, corresponding to m1A (N1-methyladenosine), m1G (N1-methylguanosine) and m22G (N2, N2-dimethylguanosine). We also detected mismatch sites on rRFs corresponding to known modifications on 28 and 18S rRNA.Conclusion: We found abundant non-microRNA-small RNAs in BLCA tumor samples. Small RNAs, especially tRFs and rRFs, contain modifications that can be captured as mismatch by TGIRT sequencing. Both the modifications and the non-microRNA-small RNAs should be explored as a biomarker for BLCA detection or follow-up.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Characterization of novel small non-coding RNAs and their modifications in bladder cancer using an updated small RNA-seq workflow

Monshaugen

Klungland

et al. 2022

Front. Mol. Biosci.

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“…Researchers should apply various approaches to avoid making an incorrect assumption about a specific nucleotide and its potential modifications. Machine learning approaches have been developed to infer RNA modifications from RNA sequencing data, with varying success (Ryvkin et al 2013;Tan et al 2021;Werner et al 2020).…”

Section: Modification-induced Errorsmentioning

confidence: 99%

Artifacts and biases of the reverse transcription reaction in RNA sequencing

Verwilt

Mestdagh

Vandesompele

2023

RNA

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RNA sequencing has spurred a great number of research areas in recent years. Most protocols rely on converting RNA into a more stable complementary DNA copy during the reverse transcription reaction. The resulting cDNA pool is often wrongfully assumed to be quantitatively and molecularly similar to the original RN input. Sadly, biases and artifacts confound the resulting cDNA mixture. These issues are often overlooked or ignored in the literature by those that rely on the reverse transcription process. In this Review, we confront the reader with intra- and inter-sample biases, and artifacts caused by the reverse transcription reaction during RNA sequencing experiments. To fight the reader’s despair, we also provide solutions to most issues and inform on good RNA sequencing practices. We hope the reader can use this Review to his advantage, thereby contributing to scientifically sound RNA studies.

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“…However, it is well documented that people with cancer, obesity and diabetes are more vulnerable to COVID-19, [35][36][37][38][39] and these individuals have been reported to have elevated m 1 A modification and the modification has negative effects on prognosis of their clinical conditions. [40][41][42][43][44] Therefore, their transcriptomic machinery would be more likely to install m 1 A onto the SARS-CoV-2 genome and they would do better for COVID-19 than the general population without considering other factors such as induced immunity. One scenario that can overcome the contradiction could be that m 1 A modification in these individuals are highly dynamic, which is likely.…”

Section: In Comparison Of Figuresmentioning

confidence: 99%

Effects of Epitranscriptomic RNA Modifications on the Catalytic Activity of the SARS‐CoV‐2 Replication Complex**

et al. 2023

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SARS-CoV-2 causes individualized symptoms. Many reasons have been given. We propose that an individual's epitranscriptomic system could be responsible as well. The viral RNA genome can be subject to epitranscriptomic modifications, the modifications can be different for different individuals, and thus epitranscriptomics can affect many events including RNA replication differently. In this context, we studied the effects of modifications including pseudouridine (Ψ), 5methylcytosine (m 5 C), N 6 -methyladenosine (m 6 A), N 1 -methyladenosine (m 1 A) and N 3methylcytosine (m 3 C) on the activity of SARS-CoV-2 replication complex (SC2RC). We found that Ψ, m 5 C, m 6 A and m 3 C had little effects, while m 1 A inhibited the enzyme. Both m 1 A and m 3 C disrupt canonical base-pairing, but they had different effects. The fact that m 1 A inhibits SC2RC implies that the modification can be difficult to detect. The fact also implies that individuals with upregulated m 1 A including cancer, obesity and diabetes patients may have milder symptoms. However, this contradicts clinical observations. Relevant discussions are provided.

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Repurposing RNA sequencing for discovery of RNA modifications in clinical cohorts

Cited by 17 publications

References 114 publications

Characterization of novel small non-coding RNAs and their modifications in bladder cancer using an updated small RNA-seq workflow

Characterization of novel small non-coding RNAs and their modifications in bladder cancer using an updated small RNA-seq workflow

Artifacts and biases of the reverse transcription reaction in RNA sequencing

Effects of Epitranscriptomic RNA Modifications on the Catalytic Activity of the SARS‐CoV‐2 Replication Complex**

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