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DC Field | Value | Language |
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dc.contributor.author | Mastrorosa, Francesco Kumara | - |
dc.date.accessioned | 2022-06-15T08:56:11Z | - |
dc.date.available | 2022-06-15T08:56:11Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://hdl.handle.net/10443/5447 | - |
dc.description | PhD Thesis | en_US |
dc.description.abstract | Very few genetic variants are currently known to cause severe male infertility phenotypes in a dominant fashion. This is explained by an absence of cohorts of patient-parent trios, which impedes the study of this genetic inheritance model. It has been demonstrated that de novo copy number variants (CNVs) on chromosome Y cause severe male infertility, but up to now, such variants have not been identified on the autosomes. In this thesis, I used whole-exome sequencing (WES) in a large cohort of male infertility patient-parent trios to study the possible role of de novo and maternally inherited CNVs as causes of quantitative sperm defects. I also used the same method to identify likely pathogenic CNVs in two patients-only cohorts affected by quantitative as well as qualitative sperm defects. We identified several possibly causative de novo and maternally inherited CNVs, pointing us to novel candidate genes for male infertility. Moreover, my findings contributed to the identification of the first gene on chromosome X associated with a male infertility phenotype characterised by multiple morphological abnormalities of the sperm flagella. This study reveals unique insight into the genetic aetiology of severe male infertility. Also, it illustrates the value of WES as a tool for CNV detection and supports the increasing use of this genomic technique in the field of male infertility genetics. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Newcastle University | en_US |
dc.title | The Role of Copy Number Variants in Severe Idiopathic Male Infertility | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Biosciences Institute |
Files in This Item:
File | Description | Size | Format | |
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MastrorosaFK2021.pdf | Thesis | 14.65 MB | Adobe PDF | View/Open |
dspacelicence.pdf | Licence | 43.82 kB | Adobe PDF | View/Open |
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