Analysis of chromosomal organisation and nuclear genome annotation in Eimeria tenella

Tay Yea Ling (P43771)

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DC Field	Value	Language
dc.contributor.advisor	Wan Kiew Lian, Prof. Dr.
dc.contributor.author	Tay Yea Ling (P43771)
dc.date.accessioned	2023-10-13T09:43:57Z	-
dc.date.available	2023-10-13T09:43:57Z	-
dc.date.issued	2012-03-22
dc.identifier.other	ukmvital:120734
dc.identifier.uri	https://ptsldigital.ukm.my/jspui/handle/123456789/500468	-
dc.description	Eimeria tenella, one of the seven coccidiosis-causing Eimeria species infecting chicken, contributes to massive economic losses to the poultry industry. Current control methods are relatively ineffective and expensive, as resistance to drugs arise rapidly and vaccine production involves high production costs. This study aims to analyse the E. tenella genome to understand its structure, to predict genes encoded by the genome and subsequently to analyse the structure and functions of these predicted genes. In order to analyse the structure of the E. tenella genome, sequences across chromosome 2 were chosen systematically to determine their copy-number using molecular copy-number counting. Results suggest that the unique segmental structure of the genome, consisting of feature poor (P) and feature rich (R) regions, could be a result of the two distinct sequence segments evolving separately. The random distribution of sequence copy-numbers across chromosome 2 also implies that the E. tenella genome is dynamic, which is believed to be a beneficial characteristic to the parasite and may indirectly be responsible for the rapid development of drug resistance. Manual curation of genes was subsequently carried out using RNA-Seq data in an effort to produce a set of highly accurate genes for training of the computational gene prediction software. These genes were later used to evaluate the accuracy of genes predicted using the iterative gene prediction approach adapted in this study, showing that the approach was able to produce high quality gene predictions. This gene prediction process, which involved repeated-steps of manual gene curation, training of gene prediction software with curated gene models and gene prediction, successfully predicted 6788 genes from the E. tenella genome sequence. Analysis of the structure of these genes showed that more E. tenella genes have introns than closely-related apicomplexans, suggesting that these introns were gained later in evolution since divergence from a common apicomplexan ancestor. The predicted genes were then subjected to automated functional annotation, which identified putative functions for 28.6% of the genes. These genes were subsequently found to be mapped to various expected biological pathways, such as the metabolic pathways, and several unexpected ones, such as drug metabolism and plant hormone biosynthesis pathways. Further analysis also revealed that nine out of the 1449 pathogen-specific genes predicted to be secreted or membrane-bound are expected to be expressed during the invasive stage. Thus, these nine genes are believed to be potential targets for the development of more effective detection and control methods for E. tenella.,Certification of Master's/ Doctorial Thesis" is not available
dc.language.iso	eng
dc.publisher	UKM, Bangi
dc.relation	Faculty of Science and Technology / Fakulti Sains dan Teknologi
dc.rights	UKM
dc.subject	Dissertations, Academic -- Malaysia
dc.subject	Eimeriidae
dc.subject	Eimeria
dc.subject	Coccidiosis
dc.subject	Genomes
dc.subject	Universiti Kebangsaan Malaysia -- Dissertations
dc.title	Analysis of chromosomal organisation and nuclear genome annotation in Eimeria tenella
dc.type	Theses
dc.format.pages	119
dc.identifier.callno	QL368.C59T348 2012 tesis
dc.identifier.barcode	002919 (2012)
Appears in Collections:	Faculty of Science and Technology / Fakulti Sains dan Teknologi

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