Allele-specific quantitative proteomics unravels molecular mechanisms modulated by cis-regulatory PPARG locus variation

Abstract

Genome-wide association studies identified numerous disease risk loci. Delineating molecular mechanisms influenced by cis-regulatory variants is essential to understand gene regulation and ultimately disease pathophysiology. Combining bioinformatics and public domain chromatin information with quantitative proteomics supports prediction of cis-regulatory variants and enabled identification of allele-dependent binding of both, transcription factors and coregulators at the type 2 diabetes associated PPARG locus. We found rs7647481A nonrisk allele binding of Yin Yang 1 (YY1), confirmed by allele-specific chromatin immunoprecipitation in primary adipocytes. Quantitative proteomics also found the coregulator RING1 and YY1 binding protein (RYBP) whose mRNA levels correlate with improved insulin sensitivity in primary adipose cells carrying the rs7647481A nonrisk allele. Our findings support a concept with diverse cis-regulatory variants contributing to disease pathophysiology at one locus. Proteome-wide identification of both, transcription factors and coregulators, can profoundly improve understanding of mechanisms underlying genetic associations.

Two SNPs (rs1801282 and -1279G/A) of PPARγ are associated with Parkinson's disease in a northern Chinese population

“…-1279G/A is located in the promoter region of PPARγ and the polymorphism of the promoter region tends to affect gene expression and contribute to the occurrence of disease [30]. The ENCODE project and bioinfomatics approaches identified the − 1279G/A(rs7647481) as the cis-regulatory vabriant which exerts the effect of regulating transranscriptional activity, and ultimately contributes to different sensitivity of insulin in primary adipose cells [31]. In addition, Yin Yang 1(YY1) has been confirmed as an allele-specific transcription factor for − 1279G/A (rs7647481) A allele, which may affects the level of PPARγ [31].…”

“…The ENCODE project and bioinfomatics approaches identified the − 1279G/A(rs7647481) as the cis-regulatory vabriant which exerts the effect of regulating transranscriptional activity, and ultimately contributes to different sensitivity of insulin in primary adipose cells [31]. In addition, Yin Yang 1(YY1) has been confirmed as an allele-specific transcription factor for − 1279G/A (rs7647481) A allele, which may affects the level of PPARγ [31]. Taken together, the − 1279G/A polymorphism is a cis-regulatory vabrian [31], which may play a role in decreasing transcriptional activity of PPARγ, leading to the low expression level of PPARγ which confers to susceptibility for the development of PD.…”

“…In addition, Yin Yang 1(YY1) has been confirmed as an allele-specific transcription factor for − 1279G/A (rs7647481) A allele, which may affects the level of PPARγ [31]. Taken together, the − 1279G/A polymorphism is a cis-regulatory vabrian [31], which may play a role in decreasing transcriptional activity of PPARγ, leading to the low expression level of PPARγ which confers to susceptibility for the development of PD. In fact, the precise molecular mechanism is more complicated than we expect, and hence, further research is required to elucidate the underlying mechanism between variants and disease risk.…”

Determining Allele-Specific Protein Expression (ASPE) Using a QconCAT-Based Proteomics Method: a Novel Approach to Identify Cis-acting Genetic Variants

“…In principle, this type of variants cannot be identified by mRNA ASE-based studies, but will be readily detected by an ASPE assay. ASPE has been quantified in several proteomics studies, which revealed wide spread contributions of cis-regulatory factors to variability in protein expression 4,23,24 .…”

“…Therefore, measuring ASPE could be a powerful approach for the study of cis-regulatory variants because it is insusceptible to the confounding effects of transelements and environmental contributors. ASPE has been quantified in several proteomics studies, which revealed wide spread contributions of cis-regulatory factors to variability in protein expression (3,18,19). However, the data-dependent acquisition (DDA) or label-free proteomics techniques utilized in these studies exhibit intrinsic limitations in the accuracy, precision, and repeatability of protein quantification (20).…”