Insights into cancer-related phenotypes from gene-trait coevolution and gene copy number variation within and between species

Copy number variants (CNVs) are a significant source of genomic variation, often encompassing whole genes and thereby, potentially, altering gene dosage between individuals. These changes can influence disease susceptibility, with some variants conferring risk while others may have protective effects. Over evolutionary timescales, variation in gene copy number has long been studied as a source of phenotypic novelty and has also been proposed to contribute to inter-specific variation in disease risk. In mammals, for example, an increased copy number of tumour suppressor genes is hypothesised to mitigate cancer risk for large and long-lived species. In this thesis, we investigated the impact of changes in gene copy number at both scales: within human populations, to assess direct functional associations with disease, and across the mammalian phylogeny, to explore association with cancer-related phenotypes. Building on this work, we further investigated how molecular evolutionary rates coevolve with lifespan and body size, offering a complementary perspective on the genomic basis of cancer susceptibility and trait evolution. In Chapter 2, we examined the relationship between gene copy number variation and disease risk in humans. Motivated by the two-hit model of cancer causation, we hypothesised that copy number variants that increase the number of intact copies of tumour suppressor genes could reduce cancer susceptibility. We found suggestive evidence that supports this hypothesis, demonstrating that the presence of at least one duplication of a tumour suppressor gene harbouring a driver mutation is associated with reduced cancer incidence. We also identified association between gene deletions and cancer incidence. Additional genome-wide analyses revealed further associations between gene copy number and other disease phenotypes, highlighting the impact of gene copy number on human disease. In Chapter 3, we expanded this investigation across species, taking a comparative approach to assess the relationships between gene copy number and cancer risk, lifespan, or body size across mammals. While we did not find examples of genes for which the copy number was associated with lifespan or body size, we identified several genes for which copy number was associated with cancer prevalence across species. We also found several gene sets where aggregate copy number was linked to malignancy rate, with the strongest association identified for gene sets related to transforming growth factor-beta (TGF-β), a key regulator of cancer progression. These findings suggest that variation in gene copy number may help explain interspecies differences in cancer prevalence among mammals. In Chapter 4, we shifted our focus from gene copy number to sequence evolution, investigating how molecular evolutionary rates coevolve with life-history traits such as lifespan and body size. We examined the methodological challenges involved in detecting gene–trait coevolution, comparing standard linear regression with phylogenetic approaches including RERconverge and Coevol. In addition, we developed a novel coevolutionary modelling approach which effectively controlled false positives in simulated datasets, but failed to do so in real sequence data, potentially due to incomplete correction for heterotachy. As an alternative, we developed and applied a phylogenetic generalized least squares (PGLS) approach to identify genes for which the non-synonymous substitution rate was accelerated or decelerated relative to the genomic background in a way that is correlated with life-history traits. Together, this thesis integrates different facets of gene evolution to advance our understanding of how genomic changes may influence cancer susceptibility and life-history traits across recent and evolutionary timescales.

Publisher

University of Galway

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CC BY-NC-ND

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University of Galway Theses (PhD Theses)