Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue
RNA A-to-I editing; carried out by the family of adenosine deaminase acting on RNA (ADAR) proteins, is the most common type of RNA editing in vertebrates. It can lead to the disruption of protein synthesis or structure, as well as changes in both the coding and non-coding sequence of the RNA. This c...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2018
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| Online Access: | https://eprints.nottingham.ac.uk/50506/ |
| _version_ | 1848798268989898752 |
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| author | North, Francesca Louise |
| author_facet | North, Francesca Louise |
| author_sort | North, Francesca Louise |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | RNA A-to-I editing; carried out by the family of adenosine deaminase acting on RNA (ADAR) proteins, is the most common type of RNA editing in vertebrates. It can lead to the disruption of protein synthesis or structure, as well as changes in both the coding and non-coding sequence of the RNA. This can lead to the development of many diseases, and when present in the brain, contribute to the onset of conditions such as depression, epilepsy, schizophrenia, and amyotrophic lateral sclerosis (ALS) (Kwak and Kawahara, 2005, Maas et al., 2006). The aim of this project was to develop a bioinformatics pipeline to identify potential A-to-I RNA editing sites from RNA sequencing data. A number of identified sites were then verified using PCR and Sanger Sequencing to test the stringency of the pipeline. A site identified as likely to be a false positive due to sequencing error was confirmed as such. Two other sites that were likely to be false positive were also confirmed to be false positive and one true editing site was verified. This project shows that RNA-Sequencing (RNA-Seq) data provides a good basis for the prediction of potential editing sites from the transcriptome with a good bioinformatics pipeline. However, it seems using reference genomic sequence data lacks the specificity of using exome or whole genome data generated from the same samples as the RNA sequence, therefore leading to a number of false positives. |
| first_indexed | 2025-11-14T20:17:05Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-50506 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:17:05Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-505062025-02-28T14:03:01Z https://eprints.nottingham.ac.uk/50506/ Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue North, Francesca Louise RNA A-to-I editing; carried out by the family of adenosine deaminase acting on RNA (ADAR) proteins, is the most common type of RNA editing in vertebrates. It can lead to the disruption of protein synthesis or structure, as well as changes in both the coding and non-coding sequence of the RNA. This can lead to the development of many diseases, and when present in the brain, contribute to the onset of conditions such as depression, epilepsy, schizophrenia, and amyotrophic lateral sclerosis (ALS) (Kwak and Kawahara, 2005, Maas et al., 2006). The aim of this project was to develop a bioinformatics pipeline to identify potential A-to-I RNA editing sites from RNA sequencing data. A number of identified sites were then verified using PCR and Sanger Sequencing to test the stringency of the pipeline. A site identified as likely to be a false positive due to sequencing error was confirmed as such. Two other sites that were likely to be false positive were also confirmed to be false positive and one true editing site was verified. This project shows that RNA-Sequencing (RNA-Seq) data provides a good basis for the prediction of potential editing sites from the transcriptome with a good bioinformatics pipeline. However, it seems using reference genomic sequence data lacks the specificity of using exome or whole genome data generated from the same samples as the RNA sequence, therefore leading to a number of false positives. 2018-07-12 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/50506/3/4276108%20NORTH%20FL%20MRES%20THESIS%20MARCH%202018.pdf North, Francesca Louise (2018) Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue. MRes thesis, University of Nottingham. RNA RNA-Sequencing RNA Editing Human Brain. |
| spellingShingle | RNA RNA-Sequencing RNA Editing Human Brain. North, Francesca Louise Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue |
| title | Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue |
| title_full | Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue |
| title_fullStr | Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue |
| title_full_unstemmed | Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue |
| title_short | Identifying potential RNA editing sites from RNA-Sequencing data from human brain tissue |
| title_sort | identifying potential rna editing sites from rna-sequencing data from human brain tissue |
| topic | RNA RNA-Sequencing RNA Editing Human Brain. |
| url | https://eprints.nottingham.ac.uk/50506/ |