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DNA variants affecting the expression of numerous genes in trans have diverse mechanisms of action and evolutionary histories

ABSTRACT: DNA variants that alter gene expression contribute to variation in many phenotypic traits. In particular, trans-acting variants, which are often located on different chromosomes from the genes they affect, are an important source of heritable gene expression variation. However, our knowledge about the identity and mechanism of causal trans-acting variants remains limited. Here, we developed a fine-mapping strategy called CRISPR-Swap and dissected three expression quantitative trait locus (eQTL) hotspots known to alter the expression of multiple genes in trans in the yeast Saccharomyces cerevisiae. Causal variants were identified by engineering recombinant alleles and quantifying the effects of these alleles on the expression of a green fluorescent protein-tagged gene affected by the given locus in trans. We validated the effect of each variant on the expression of multiple genes by RNA-sequencing. The three variants were strikingly different in their molecular mechanism, the type of genes they reside in, and their distribution in natural populations. While a missense leucine-to-serine variant at position 63 in the transcription factor Oaf1 (L63S) was almost exclusively present in the reference laboratory strain, the two other variants were frequent among S. cerevisiae isolates. A causal missense variant in the glucose receptor Rgt2 (V539I) occurred at a poorly conserved amino acid residue and its effect was strongly dependent on the concentration of glucose in the culture medium. A noncoding variant in the conserved fatty acid regulated (FAR) element of the OLE1 promoter influenced the expression of the fatty acid desaturase Ole1 in cis and, by modulating the level of this essential enzyme, other genes in trans. The OAF1 and OLE1 variants showed a non-additive genetic interaction, and affected cellular lipid metabolism. These results revealed remarkable diversity in the molecular basis of trans-regulatory variation, highlighting the challenges in predicting which natural genetic variants affect gene expression.

ORGANISM(S): Saccharomyces cerevisiae

PROVIDER: GSE134169 | GEO | 2019/08/12

REPOSITORIES: GEO

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Project description:Despite widespread advances in DNA sequencing in the past decade, the functional consequences of most rare genetic variants remain poorly understood, severely limiting our ability to connect variants to their consequences on protein function, identify biochemical mechanisms by which variation causes disease, and interpret variant pathogenicity. Multiplexed Assays of Variant Effect (MAVEs), which can measure the function of tens of thousands variants, are beginning to address this problem. However, existing MAVEs cannot be applied to the approximately 10% of human genes encoding secreted proteins, about a quarter of which are associated with disease. We developed a flexible and scalable human cell surface display method, Multiplexed Surface Tethering of Extracellular Proteins (MultiSTEP), that can simultaneously measure the functional effects of tens of thousands of variants in secreted proteins. We used MultiSTEP to study the consequences of missense variation in coagulation factor IX (FIX), a vitamin K-dependent plasma serine protease where variation can cause FIX deficiency and the bleeding disorder hemophilia B. We used a panel of antibodies to detect FIX secretion or FIX post-translational modification, measuring a total of 45,024 effects for 9,007 variants. 43.8% of all possible F9 missense variants impact FIX secretion, post-translational modification or both. We also identify new signals of functional constraint on secretion including within the signal peptide, folded domains, and for nearly all variants that caused gain or loss of cysteine. FIX secretion scores correlate strongly with FIX levels in patient plasma and also reveal that most F9 missense variants causing severe hemophilia do so by profoundly impacting secretion. We integrate the secretion and post-translational modification data to develop a F9 variant classifier that can identify loss of function variants with high specificity. We use the resulting classifications to reinterpret and upgrade 62 of 97 F9 variants of uncertain significance (VUS) in the MyLifeOurFuture hemophilia genotyping project to likely pathogenic. Lastly, we show that MultiSTEP can be applied to a wide variety of secreted proteins, ranging from small signaling proteins like insulin to large proteins like factor VIII. Thus, we establish a multiplexed, multimodal, and generalizable method for systematically assessing variant effects for secreted proteins at scale, paving the way for improved understanding of biochemical mechanisms of disease and clinical variant interpretation.