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Title: Next-generation sequencing analyses in human disease and population genomics
Author: Forooshani, Mohammad Reza Jabal Ameli
ISNI:       0000 0004 7960 7584
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2018
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Application of next-generation sequencing (NGS) in clinical diagnosis has enabled the efficient analysis of diverse genetic disorders. Rapid growth in the number of human genomes sequenced, underpinning a developing understanding of the disease-gene relationship. The high-throughput nature of NGS technology necessitates the need for a robust analytical framework for efficient and accurate genetic diagnosis. The higher degree of genetic variation identified in NGS applications often confounds the molecular diagnosis, and requires an enhanced strategy for the identification of causal variants. This thesis explores diverse applications of whole-exome and whole-genome sequencing at both the individual and population level for delineation of the human disease genome. Design, implementation and benchmarking of efficient pipelines for analysing whole-exome and whole-genome sequencing data is first explored. Next, the diagnostic utility of the pipelines is examined in a range of rare disorders. This includes whole exome analysis of patients with hereditary nephrolithiasis, whole-exome and whole-genome analysis of a patient with severe skeletal dysplasia and targeted gene panel sequencing in a cohort of patients with syndromic cleft lip/palate (CLP). Through analyses of these cases, advantages and limitations of NGS analysis for establishing the molecular diagnosis in rare disorders are demonstrated. A novel method for ranking variants in the presence of phenotypic and genetic heterogeneity is introduced, and its diagnostic utility explored across syndromic CLP patients. While the application of variant-level attributes such as pathogenicity and conservation scores greatly facilitate molecular diagnosis, full resolution of the genetic architecture underlying disease genome depends on identification of factors that dictate the spatial distribution of pathogenic mutations across the genome. The nonrandom distribution of variants across the genome is the outcome of the complex interplay between selection, recombination and mutation which is reflected in genome-wide linkage disequilibrium (LD) patterns. The final section of the thesis explores the possibility of delineating human disease genome from fine-scale LD maps in Sub-Saharan African populations (SSA). Extended population history in the SSA populations enables an unprecedented resolution for characterisation of LD patterns at sub-genic levels. LD maps constructed according to the Mal´ecot-Morton model from the whole-genome sequence data of 295 individuals from major SSA populations correlates closely with the proposed models of Bantu expansion across Africa. Furthermore, the relationship between gene-ontology groups, gene essentiality and gene-age with the extent of LD is investigated, and a model for identification of the association between the LD extent and gene-group assignment is proposed. Overall, this thesis demonstrates many applications of NGS technology and highlights the common limitations involved in the analysis and interpretation of variants revealed from high throughput NGS analysis.
Supervisor: Ennis, Sarah ; Collins, Andrew ; Tapper, William Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available