Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: current and developing technologies

Abstract

The most common form of genetic variation, single nucleotide polymorphisms or SNPs, can affect the way an individual responds to the environment and modify disease risk. Although most of the millions of SNPs have little or no effect on gene regulation and protein activity, there are many circumstances where base changes can have deleterious effects. Non-synonymous SNPs that result in amino acid changes in proteins have been studied because of their obvious impact on protein activity. It is well known that SNPs within regulatory regions of the genome can result in disregulation of gene transcription. However, the impact of SNPs located in putative regulatory regions, or rSNPs, is harder to predict for two primary reasons. First, the mechanistic roles of non-coding genomic sequence remain poorly defined. Second, experimental validation of the functional consequences of rSNPs is often slow and laborious. In this review, we summarize traditional and novel methodologies for candidate rSNPs selection, in particular in silico techniques that aid in candidate rSNP selection. Additionally we will discuss molecular biological techniques that assess the impact of rSNPs on binding of regulatory machinery, as well as functional consequences on transcription. Standard techniques such as EMSA and luciferase reporter constructs are still widely used to assess effects of rSNPs on binding and gene transcription; however, these protocols are often bottlenecks in the discovery process. Therefore, we highlight novel and developing high-throughput protocols that promise to aid in shortening the process of rSNP validation. Given the large amount of genomic information generated from a multitude of re-sequencing and genome-wide SNP array efforts, future focus should be to develop validation techniques that will allow greater understanding of the impact these polymorphisms have on human health and disease.

Figure 1

The impact of a SNP in a transcription factor binding site (TFBS). In many cases, the SNP will not change TF binding activity or target gene expression because the TF, in general, allows variation in the consensus sequence of the binding site. In some cases, a SNP may increase or decrease the binding, leading to allelic-specific gene expression. In rare cases, a SNP may eliminate the natural binding site or generate a novel binding site, and consequently the gene is no longer controlled by the original TF.

Figure 2

Flowchart of identification and experimental validation of candidate regulatory SNPs (rSNPs). Briefly, candidate gene selection involves one or more association and predictive processes that incorporate genomic, gene expression, and phenotypic information. An initial candidate gene list can benefit from bioinformatic analysis of this information, and vice versa. Once a list of candidate genes has been generated, polymorphisms in the regulatory region of these genes are selected by informed analysis of the region of interest, available genotyping data, and/or representative SNPs of haplotype regions. Then, experimental validation assessing polymorphic effects on binding affinity and transcriptional regulation can be performed using methodology outlined in this review. Following characterization, rSNPs can then be tested in populations to determine if they are predictive of disease or environmental response.

Figure 3

Outline of Microsphere Binding Assay. a) First, anneal oligonucleotides containing test sequences to tagged microspheres. b) Microspheres are uniquely dyed to allow identification of tagged oligonucleotides and multiplexing. This example shows four different microspheres and binding sequences. c) This assay allows for binding of pure TF or cellular extract containing activated TF. Cell cultures with and without activated TF are used and nuclear extracts are then mixed with the multiplexed microsphere-oligonucleotides to allow binding of TF. d) After washing, primary antibody specific for the TF of interest is added and detection is achieved with a phycoerythrin-conjugated antibody. A Bioplex flow cytometric device equipped with two excitation lasers and absorption optics is used for detection. The first laser identifies the microsphere (binding sequence) and the second laser identifies the quantitative signal from the TF. e) Signals are averaged for each microsphere type and plotted as signal intensity. Here, signal intensity for each condition is shown as a percentage of the perfect binding sequence. The core binding sequence generated the most signal when TF is added, while non-specific sequence generates only background noise. Our experimental sequence generates signal when TF is added, however the polymorphism modulates signal, and therefore binding potential of the TF.

Figure 4

An example of allelic imbalance measured by the use of quantitative allele discrimination assay for SNPs in coding regions performed on cDNA samples. A 5’ nuclease-based assay for rs1537236 was applied to homozygote and heterozygote cell lines to demonstrate the low level of expression of the C allele in GSTM3 gene [90].