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Exploiting nanopore sequencing advances for tRNA sequencing of human cancer models

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Abstract Transfer RNAs (tRNAs) are essential regulators of protein synthesis, and dysregulation of their abundance and modification status is involved in many human diseases including cancer. Despite the rapid development of novel tRNA sequencing approaches, due to tRNAs’ stable secondary structure and abundant modification sites, the human tRNA landscape has remained mostly unexplored. Here, we evaluated the new RNA004 chemistry of Oxford Nanopore Technologies, that is integrated with updated Dorado base-caller models, for tRNA quantification and modification annotation in human cancer models. We demonstrated that this technology identifies variations in tRNA expression across cancer cell lines and in response to external stress conditions, with highly reproducible results. We also show that analysis of base-calling error rate can indicate the presence of known modifications, including the cancer-associated tRNAPhe-Wybutosine modification. Furthermore, implementing the updated Dorado modification-calling feature, we showed the potential of RNA004 tRNA-seq in predicting common tRNA modifications. We also pinpointed possible limitations and challenges associated with both modification calling methods. Overall, RNA004 tRNA-seq can potentially enhance our understanding of the human tRNAome by simultaneously analyzing both tRNA abundance and modifications.
Title: Exploiting nanopore sequencing advances for tRNA sequencing of human cancer models
Description:
Abstract Transfer RNAs (tRNAs) are essential regulators of protein synthesis, and dysregulation of their abundance and modification status is involved in many human diseases including cancer.
Despite the rapid development of novel tRNA sequencing approaches, due to tRNAs’ stable secondary structure and abundant modification sites, the human tRNA landscape has remained mostly unexplored.
Here, we evaluated the new RNA004 chemistry of Oxford Nanopore Technologies, that is integrated with updated Dorado base-caller models, for tRNA quantification and modification annotation in human cancer models.
We demonstrated that this technology identifies variations in tRNA expression across cancer cell lines and in response to external stress conditions, with highly reproducible results.
We also show that analysis of base-calling error rate can indicate the presence of known modifications, including the cancer-associated tRNAPhe-Wybutosine modification.
Furthermore, implementing the updated Dorado modification-calling feature, we showed the potential of RNA004 tRNA-seq in predicting common tRNA modifications.
We also pinpointed possible limitations and challenges associated with both modification calling methods.
Overall, RNA004 tRNA-seq can potentially enhance our understanding of the human tRNAome by simultaneously analyzing both tRNA abundance and modifications.

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