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Next-generation sequencing analyses in human disease and population genomics

Next-generation sequencing analyses in human disease and population genomics
Next-generation sequencing analyses in human disease and population genomics
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.
University of Southampton
Forooshani, Mohammad Reza Jabal Ameli
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Forooshani, Mohammad Reza Jabal Ameli
d533e702-7a6b-4f2d-8947-352ea1dd769b
Ennis, Sarah
7b57f188-9d91-4beb-b217-09856146f1e9
Collins, Andrew
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Tapper, William
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Forooshani, Mohammad Reza Jabal Ameli (2018) Next-generation sequencing analyses in human disease and population genomics. University of Southampton, Doctoral Thesis, 302pp.

Record type: Thesis (Doctoral)

Abstract

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.

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Published date: October 2018

Identifiers

Local EPrints ID: 430688
URI: http://eprints.soton.ac.uk/id/eprint/430688
PURE UUID: ac1bc631-c08e-448e-9e18-fd29136e5c24
ORCID for Mohammad Reza Jabal Ameli Forooshani: ORCID iD orcid.org/0000-0002-7762-0529
ORCID for Sarah Ennis: ORCID iD orcid.org/0000-0003-2648-0869
ORCID for Andrew Collins: ORCID iD orcid.org/0000-0001-7108-0771
ORCID for William Tapper: ORCID iD orcid.org/0000-0002-5896-1889

Catalogue record

Date deposited: 08 May 2019 16:30
Last modified: 18 Feb 2021 16:53

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Contributors

Author: Mohammad Reza Jabal Ameli Forooshani ORCID iD
Thesis advisor: Sarah Ennis ORCID iD
Thesis advisor: Andrew Collins ORCID iD
Thesis advisor: William Tapper ORCID iD

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