High-throughput identification of human SNPs affecting regulatory element activity

Abstract

Most of the millions of single-nucleotide polymorphisms (SNPs) in the human genome are non-coding, and many overlap with putative regulatory elements. Genome-wide association studies (GWAS) have linked many of these SNPs to human traits or to gene expression levels, but rarely with sufficient resolution to identify the causal SNPs. Functional screens based on reporter assays have previously been of insufficient throughput to test the vast space of SNPs for possible effects on regulatory element activity. Here, we leveraged the throughput and resolution of the SuRE reporter technology to survey the effect of 5.9 million SNPs, including 57% of the known common SNPs, on enhancer and promoter activity. We identified more than 30,000 SNPs that alter the activity of putative regulatory elements, partially in a cell-type specific manner. Integration of this dataset with GWAS results may help pinpoint SNPs that underlie human traits.

Massively parallel discovery of human-specific substitutions that alter neurodevelopmental enhancer activity

“…A single MPRA experiment interrogates thousands of sequence changes at once, which provides the means to comprehensively analyze sequence variation within regulatory elements in a combinatorial manner. This technique has been used to quantify the effect of saturating mutations in single enhancers or to interrogate the functional effects of segregating human variants (van Arensbergen et al, 2019;Melnikov et al, 2012;Ulirsch et al, 2016).…”

Computational Assessment of the Regulation-Modulating Potential for Noncoding Variants

“…For example, the SIK2-correlated variant rs1784782 shows very weak regulatory potential (CARMEN score = 0.0004), while the linked variant rs59921976 presents rather high potential (CARMEN score = 0.6091). The independent MPRA assay confirmed that the CARMEN-predicted causal variant rs59921976 had significant expression changes, but the reported lead SNP rs1784782 did not 53 , and the validated expression-modulating variant rs59921976 was also missed by ExPecto as a nonsignificant variant.…”

A polyclonal allelic expression assay for detecting regulatory effects of transcript variants

“…We highlight that our approach maintains the genomic context of variants and native gene regulation. Thus, it does not suffer from the limitations of massively parallel approaches where discrepancies between eQTL and experimental data may be due to measuring genetic regulatory effects in artificial constructs (Tewhey et al, 2016;van Arensbergen et al, 2019). Altogether, more experimentation and further comparison of population and experimental results are required to fully understand differences between experimental and population data.…”

“…Methods such as massively parallel reporter assays (MPRAs) (Tewhey et al, 2016;van Arensbergen et al, 2019), which couple regulatory sequences with an expression-correlated reporter, are high-throughput approaches for finding active regulatory variants outside of the gene body, and analogous methods exist for variants affecting splicing (Ke et al, 2011;Wang et al, 2012). However, the results of the assays show low concordance with eQTL data (Tewhey et al, 2016;van Arensbergen et al, 2019), perhaps due to taking the variant out of its genomic context. Furthermore, MPRAs are not suited to testing variants within the transcript that can affect gene expression levels via post-transcriptional mechanisms, e.g.…”