Decoding telomere gene variation through saturation genome editing: from functional genomics to clinical interpretation

Doctoral Thesis

This thesis investigates how saturation genome editing (SGE) can improve the interpretation of genetic variants in telomere biology genes, focusing on POT1 and TINF2, which are increasingly included on hereditary cancer testing panels. Many variants identified clinically remain classified as variants of uncertain significance, limiting diagnosis, risk assessment and patient management.

Using SGE in haploid HAP1-A5 cells, the thesis develops and applies high-throughput functional assays to generate dense variant effect maps at endogenous genomic loci. For POT1, approximately 97% of all possible coding single nucleotide variants were assessed, revealing a continuum of functional effects and identifying key loss-of-function regions within DNA-binding domains. Functional scores were validated through telomere length and DNA damage phenotyping and linked to cancer risk in population and clinical cohorts. The approach was extended to TINF2, identifying deleterious variants...Show moreThis thesis investigates how saturation genome editing (SGE) can improve the interpretation of genetic variants in telomere biology genes, focusing on POT1 and TINF2, which are increasingly included on hereditary cancer testing panels. Many variants identified clinically remain classified as variants of uncertain significance, limiting diagnosis, risk assessment and patient management.

Using SGE in haploid HAP1-A5 cells, the thesis develops and applies high-throughput functional assays to generate dense variant effect maps at endogenous genomic loci. For POT1, approximately 97% of all possible coding single nucleotide variants were assessed, revealing a continuum of functional effects and identifying key loss-of-function regions within DNA-binding domains. Functional scores were validated through telomere length and DNA damage phenotyping and linked to cancer risk in population and clinical cohorts. The approach was extended to TINF2, identifying deleterious variants affecting critical TRF1, TRF2 and TPP1 interaction surfaces and supporting a broader tumour spectrum.

The thesis further demonstrates how SGE data can support interpretation of rare variants in melanoma cohorts and hereditary cancer families. Overall, it establishes SGE as a clinically relevant framework for reducing variants of uncertain significance and linking functional effects to telomere dysfunction, cancer predisposition and improved genetic interpretation.
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Telomeres

MAVEs

Saturation Genome Editing

Cancer predisposition

Variants