Doctoral thesis
Open access

Impact of genetic variation on gene expression and cellular phenotypes

ContributorsReal, Aline
Number of pages169
Imprimatur date2022-08-26
Defense date2022-08-26

Complex traits and diseases, such as cancer, are determined by a combination of genetic and environmental factors, which makes them difficult to study. While genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits and diseases, the causal genes, and therefore, the underlying diseases-driving processes remain mostly unknown. This thesis aims to contribute to close this gap by unravelling the effect of genetic variation on gene expression, as well as on cellular cancer-like phenotypes. In the first project, the effects of genetic variation on gene expression were addressed using direct long-read RNA sequencing. RNA alternative splicing (AS) regulates gene expression, and ultimately the proteome, by allowing the production of multiple mRNA molecules from a single gene. It was shown that many genome wide associations for common diseases are affecting splicing processes by mechanisms that are distinct from the ones affecting gene expression. However, technology limitations made it difficult to determine the genetic effects on AS events on a genome-wide scale. Direct RNA long-read sequencing of 60 Lymphoblastoid cell lines (LCLs) was used to detect annotated and novel transcripts and to identify genetic variants affecting transcript expression and structure. Previously identified expression quantitative trait loci (eQTL) effects, i.e. were characterized more closely by the identification of the transcripts affected by the eQTL among all the ones produced by the same gene. Moreover, we discovered novel transcripts QTLs (trQTL) not included in the eQTLs previously reported using short-read sequencing. In the second project, the effects of genetic variation on cancer-like phenotypes were studied by designing a population-level study. Historically cancer believed to be linked to somatic driver mutations but, in recent years, it has become increasingly clear from GWAS that non-coding regulatory drivers also play a critical role in cancer development and progression. Specifically, inherited genetic variants (germline variants) might increase the risk of developing cancer. To gain a deeper understanding of the regulatory germline contribution to cancer genetics and to identify which target genes are involved, 87 genetically different LCLs were tested to assess cells’ proliferation, apoptosis, and chemotaxis using functional in-vitro assays. The aim was to investigate whether specific variants and genes are associated with these three cancer-like phenotypes, i.e. whether they affected the cell line to proliferate, resist apoptosis, and migrate in response to chemical stimuli. Despite the relatively small sample size, we were able to identify a significant genetic variant associated with the replication index phenotype and multiple putative genes mediating this genetic effect. The evidence from GWAS that non-coding genetic variants are associated with splicing, and ultimately with cancer, underlines the need to focus on filling the gap still present between variation in the non-coding genome and downstream effects on gene expression. With this thesis, I attempted to obtain a deeper understanding of the genetic mechanisms linking genetic variants, splicing and complex traits such as cancer. Integrating genetic information with gene expression data, generated with the novel long-read sequencing technology, phenotype and functional data, might open new way of study complex diseases.

  • Genetic variation
  • Long-reads direct RNA-seq
  • Cancer-like phentoypes
  • Splicing
  • Complex traits
Citation (ISO format)
REAL, Aline. Impact of genetic variation on gene expression and cellular phenotypes. 2022. doi: 10.13097/archive-ouverte/unige:164744
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Technical informations

Creation11/07/2022 9:05:00 AM
First validation11/07/2022 9:05:00 AM
Update time03/16/2023 8:43:16 AM
Status update03/16/2023 8:43:14 AM
Last indexation02/01/2024 9:05:02 AM
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