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DC Field | Value | Language |
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dc.contributor.author | Xu, Yaobo | - |
dc.date.accessioned | 2016-09-05T13:13:18Z | - |
dc.date.available | 2016-09-05T13:13:18Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | http://hdl.handle.net/10443/3085 | - |
dc.description | PhD Thesis | en_US |
dc.description.abstract | Osteoarthritis (OA) is the most prevalent type of joint diseases. It is associated with the progressive degradation of articular cartilage and disease progression can lead to total destruction. In order to study the molecular changes in OA cartilage, I compared the transcriptome of OA and healthy cartilage using two technologies, expression microarrays and the recently introduced RNA sequencing (RNAseq) technology. RNAseq is based on the next-generation sequencing, enabling the investigation of the transcriptome in single nucleotide resolution. In this PhD project, I optimized the cartilage RNA extraction protocol first and then used the optimized protocol to extract RNAs from both OA and healthy cartilages samples. Before the RNAseq experiment, the quality of the RNA samples was checked with real-time PCR and gene expression microarray experiments. Using microarray and RNAseq data, I found novel OA associated genes and canonical pathways. With the RNAseq data, the knowledge of the OA transcriptome was further extended, including differentially expressed transcripts, novel transcripts in cartilage, alternative splicing events and differential allelic expressions. The performance of the RNAseq was also compared with the microarray technology, revealed both advantages and the limitations of the technology. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Newcastle University | en_US |
dc.title | Transcriptome analysis of cartilage in homoeostasis and osteoarthritis using deep sequencing technology | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Institute of Cellular Medicine |
Files in This Item:
File | Description | Size | Format | |
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Xu, Yaobo 2015.pdf | Thesis | 16.41 MB | Adobe PDF | View/Open |
dspacelicence.pdf | Licence | 43.82 kB | Adobe PDF | View/Open |
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