Dissecting genotype-specific effects of disease-associated genetic variants

Area of Science:

• Genetics
• Neuroscience
• Stem Cell Biology

Background:

• Non-coding variants contribute to complex diseases by influencing gene regulatory networks.
• Parkinson's disease (PD) is linked to genetic variants, but their functional impact, especially non-coding ones, remains challenging to elucidate.
• Induced pluripotent stem cells (iPSCs) offer a powerful model for studying human genetic variation in a controlled cellular context.

Purpose of the Study:

• To investigate the functional consequences of the Parkinson's disease-associated non-coding variant rs11610045.
• To determine how this variant impacts gene regulation and protein binding in a human cellular model.
• To establish a framework for dissecting the role of non-coding disease-associated variants.

Main Methods:

• Utilized CRISPR-Cas9 gene editing in isogenic iPSCs to generate matched clones with specific genotypes (A|A vs. G|G) for rs11610045.
• Employed affinity purification followed by mass spectrometry (AP-MS) to identify allele-specific protein binding partners.
• Differentiated iPSCs into cortical neurons to assess context-dependent gene expression changes.

Main Results:

• Identified widespread genotype-dependent regulation of distal genes, including THBS1 and PDGFB.
• Discovered differential binding of regulatory proteins, such as transcription factor TCF7L1, to the G|G allele.
• Observed context-dependent effects upon neuronal differentiation, with significant differential expression of 24 genes and consistent alteration of PAX5 across developmental stages.

Conclusions:

• The Parkinson's disease-associated variant rs11610045 influences gene expression and protein binding in a genotype-dependent manner.
• These findings support trans-acting mechanisms as a key way non-coding variants contribute to regulatory variation in complex diseases.
• The study presents a generalizable framework for functionally characterizing disease-associated non-coding loci using human cellular models.