Comparative analysis of synonymous codon usage bias in human monocytes, B and T lymphocytes based on transcriptome data / Muhammad Adib Ruzman
Human immune system comprises of many important biological components. Reduction in protein production such as hormones due to changes in codon distribution can lead to immune system disorder. In this study, the balance between mutational bias and translational selection in shaping codon usage bias...
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| Format: | Thesis |
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2018
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| Online Access: | http://studentsrepo.um.edu.my/13312/2/Muhammad_Adib.pdf http://studentsrepo.um.edu.my/13312/1/Muhammad_Adib.pdf http://studentsrepo.um.edu.my/13312/ |
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| Summary: | Human immune system comprises of many important biological components. Reduction in protein production such as hormones due to changes in codon distribution can lead to immune system disorder. In this study, the balance between mutational bias and translational selection in shaping codon usage bias in protein-coding genes in monocytes, B and T lymphocytes were examined. The protein-coding genes for monocytes, B and T lymphocytes as well as human reference protein-coding genes were obtained from RNA-Seq data from NCBI databases. This study was conducted by computing several codon usage indices and applying multivariate statistical methods. Nucleotide composition analysis showed that the protein-coding genes have GC-rich content and predicted to prefer GC-ended codons to code for the respective amino acids. Relative Synonymous Codon Usage (RSCU) analysis confirms the earlier prediction that GC-rich protein-coding genes will always prefer to use GC-ended codons except for monocytes protein-coding genes which prefer AT-ended codons. The overall codon usage bias was low in all of the cells including human reference protein-coding genes. Multivariate analysis used in this study suggested that codon usage bias is influenced by both mutational bias and translational selection. Moreover, translational selection was identified to be the dominant factor in all the immune cells studied except for monocytes in which it was heavily influenced by mutational bias. This research also provides new insights into human cells biology and contributes new information on advantages of RNA-Seq data in genomic study.
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