Functional analysis of regulatory single-nucleotide polymorphisms

Variants in ANRIL gene correlated with its expression contribute to myocardial infarction risk

ANRIL (antisense non-coding RNA in the INK4 locus), located at the 9p21.3 locus, has been known to be closely associated with the risk of coronary artery disease (CAD). To date, studies of the 9p21.3 variants on CAD risk mainly focus on the non-coding region of ANRIL. However, the biological significance of the variants on ANRIL promoter and exons is still unknown. Here we investigate whether the variants on ANRIL promoter and exons have an effect on myocardial infarction (MI) risk, and further analyze the association of these variants with the expression of ANRIL transcript. We did not find any common variants with minor allele frequencies (MAF) larger than 5% in ANRIL promoter by sequencing 1.6kb upstream of the start codon. Unconditional logistic regression analysis revealed that two SNPs in ANRIL exons, rs10965215 and rs10738605, were significantly associated with MI risk. Further studies revealed that ANRIL transcript EU741058.1 expression levels of rs10965215 and rs10738605 risk genotypes were borderline lower than those of protective genotypes. Our data provide the evidence that the variants rs10965215 and rs10738605 in ANRIL exons contribute to MI risk in the Chinese Han population which might be correlated with the expression of its transcript EU741058.1.

Regulatory Single-Nucleotide Variant Predictor Increases Predictive Performance of Functional Regulatory Variants

In silico methods for detecting functionally relevant genetic variants are important for identifying genetic markers of human inherited disease. Much research has focused on protein-coding variants since coding regions have well-defined physicochemical and functional properties. However, many bioinformatics tools are not applicable to variants outside coding regions. Here, we increase the classification performance of our regulatory single-nucleotide variant predictor (RSVP) for variants that cause regulatory abnormalities from an AUC of 0.90-0.97 by incorporating genomic regions identified by the ENCODE project into RSVP. RSVP is comparable to a recently published tool, Genome-Wide Annotation of Variants (GWAVA); both RSVP and GWAVA perform better on regulatory variants than a traditional variant predictor, combined annotation-dependent depletion (CADD). However, our method outperforms GWAVA on variants located at similar distances to the transcription start site as the positive set (AUC: 0.96) as compared with GWAVA (AUC: 0.71). Much of this disparity is due to RSVP's incorporation of features pertaining to the nearest gene (expression, GO terms, etc.), which are not included in GWAVA. Our findings hold out the promise of a framework for the assessment of all functional regulatory variants, providing a means to predict which rare or de novo variants are of pathogenic significance.

A genetic variant in the LDLR promoter is responsible for part of the LDL-cholesterol variability in primary hypercholesterolemia

BACKGROUND

GWAS have consistently revealed that LDLR locus variability influences LDL-cholesterol in general population. Severe LDLR mutations are responsible for familial hypercholesterolemia (FH). However, most primary hypercholesterolemias are polygenic diseases. Although Cis-regulatory regions might be the cause of LDL-cholesterol variability; an extensive analysis of the LDLR distal promoter has not yet been performed. We hypothesized that genetic variants in this region are responsible for the LDLR association with LDL-cholesterol found in GWAS.

METHODS

Four-hundred seventy-seven unrelated subjects with polygenic hypercholesterolemia (PH) and without causative FH-mutations and 525 normolipemic subjects were selected. A 3103 pb from LDLR (-625 to +2468) was sequenced in 125 subjects with PH. All subjects were genotyped for 4 SNPs (rs17242346, rs17242739, rs17248720 and rs17249120) predicted to be potentially involved in transcription regulation by in silico analysis. EMSA and luciferase assays were carried out for the rs17248720 variant. Multivariable linear regression analysis using LDL-cholesterol levels as the dependent variable were done in order to find out the variables that were independently associated with LDL-cholesterol.

RESULTS

The sequencing of the 125 PH subjects did not show variants with minor allele frequency ≥ 10%. The T-allele from g.3131C > T (rs17248720) had frequencies of 9% (PH) and 16.4% (normolipemic), p < 0.00001. Studies of this variant with EMSA and luciferase assays showed a higher affinity for transcription factors and an increase of 2.5 times in LDLR transcriptional activity (T-allele vs C-allele). At multivariate analysis, this polymorphism with the lipoprotein(a) and age explained ≈ 10% of LDL-cholesterol variability.

CONCLUSION

Our results suggest that the T-allele at the g.3131 T > C SNP is associated with LDL-cholesterol levels, and explains part of the LDL-cholesterol variability. As a plausible cause, the T-allele produces an increase in LDLR transcriptional activity and lower LDL-cholesterol levels.

Topics in transcriptional control of lipid metabolism: from transcription factors to gene-promoter polymorphisms

The central dogma of biology (DNA>>RNA>>Protein) has remained as an extremely useful scaffold to guide the study of molecular regulation of cellular metabolism. Molecular regulation of cellular metabolism has been pursued from an individual enzyme to a global assessment of protein function at the genomic (DNA), transcriptomic (RNA) and translation (Protein) levels. Details of a key role by inhibitory small RNAs and post-translational processing of cellular proteins on a whole cell/global basis are now just emerging. Below we emphasize the role of transcription factors (TF) in regulation of adipogenesis and lipogenesis. Additionally we have also focused on emerging additional TF that may also have hitherto unrecognized roles in adipogenesis and lipogenesis as compared to our present understanding. It is generally recognized that SNPs in structural genes can affect the final structure/function of a given protein. The implications of SNPs located in the non-transcribed promoter region on transcription have not been examined as extensively at this time. Here we have also summarized some emerging results on promoter SNPs for lipid metabolism and related cellular processes.

Prediction of functional regulatory SNPs in monogenic and complex disease

Next-generation sequencing (NGS) technologies are yielding ever higher volumes of human genome sequence data. Given this large amount of data, it has become both a possibility and a priority to determine how disease-causing single nucleotide polymorphisms (SNPs) detected within gene regulatory regions (rSNPs) exert their effects on gene expression. Recently, several studies have explored whether disease-causing polymorphisms have attributes that can distinguish them from those that are neutral, attaining moderate success at discriminating between functional and putatively neutral regulatory SNPs. Here, we have extended this work by assessing the utility of both SNP-based features (those associated only with the polymorphism site and the surrounding DNA) and gene-based features (those derived from the associated gene in whose regulatory region the SNP lies) in the identification of functional regulatory polymorphisms involved in either monogenic or complex disease. Gene-based features were found to be capable of both augmenting and enhancing the utility of SNP-based features in the prediction of known regulatory mutations. Adopting this approach, we achieved an AUC of 0.903 for predicting regulatory SNPs. Finally, our tool predicted 225 new regulatory SNPs with a high degree of confidence, with 105 of the 225 falling into linkage disequilibrium blocks of reported disease-associated genome-wide association studies SNPs.

Identifying functional single nucleotide polymorphisms in the human CArGome

Regulatory SNPs (rSNPs) reside primarily within the nonprotein coding genome and are thought to disturb normal patterns of gene expression by altering DNA binding of transcription factors. Nevertheless, despite the explosive rise in SNP association studies, there is little information as to the function of rSNPs in human disease. Serum response factor (SRF) is a widely expressed DNA-binding transcription factor that has variable affinity to at least 1,216 permutations of a 10 bp transcription factor binding site (TFBS) known as the CArG box. We developed a robust in silico bioinformatics screening method to evaluate sequences around RefSeq genes for conserved CArG boxes. Utilizing a predetermined phastCons threshold score, we identified 8,252 strand-specific CArGs within an 8 kb window around the transcription start site of 5,213 genes, including all previously defined SRF target genes. We then interrogated this CArG dataset for the presence of previously annotated common polymorphisms. We found a total of 118 unique CArG boxes harboring a SNP within the 10 bp CArG sequence and 1,130 CArG boxes with SNPs located just outside the CArG element. Gel shift and luciferase reporter assays validated SRF binding and functional activity of several new CArG boxes. Importantly, SNPs within or just outside the CArG box often resulted in altered SRF binding and activity. Collectively, these findings demonstrate a powerful approach to computationally define rSNPs in the human CArGome and provide a foundation for similar analyses of other TFBS. Such information may find utility in genetic association studies of human disease where little insight is known regarding the functionality of rSNPs.

Single-molecule analysis of chromatin: changing the view of genomes one molecule at a time

Wrapping DNA into chromatin provides a wealth of regulatory mechanisms that ensure normal growth and development in eukaryotes. Our understanding of chromatin structure, including nucleosomes and non-histone protein-DNA interactions, has benefited immensely from nuclease and chemical digestion techniques. DNA-bound proteins, such as histones or site-specific factors, protect DNA against nuclease cleavage and generate large nucleosomal or small regulatory factor footprints. Chromatin subject to distinct modes of regulation often coincides with sites of nuclease hypersensitivity or nucleosome positioning. An inherent limitation of cleavage-based analyses has been the inability to reliably analyze regions of interest when levels of digestion depart from single-hit kinetics. Moreover, cleavage-based techniques provide views that are averaged over all the molecules in a sample population. Therefore, in cases of occupancy of multiple regulatory elements by factors, one cannot define whether the factors are bound to the same or different molecules in the population. The recent development of DNA methyltransferase-based, single-molecule MAP-IT technology overcomes limitations of ensemble approaches and has opened numerous new avenues in chromatin research. Here, we review the strengths, limitations, applications and future prospects of MAP-IT ranging from structural issues to mechanistic questions in eukaryotic chromatin regulation.

The g.763G>C SNP of the bovineFASNgene affects its promoter activity via Sp-mediated regulation: implications for the bovine lactating mammary gland

Fatty acid synthase (FASN) is an enzyme that catalyzes de novo synthesis of fatty acids in cells. The bovine FASN gene maps to BTA 19, where several quantitative trait loci for fat-related traits have been described. Our group recently reported the identification of a single nucleotide polymorphism (SNP), g.763G>C, in the bovine FASN 5′ flanking region that was significantly associated with milk fat content in dairy cattle. The g.763G>C SNP was part of a GC-rich region that may constitute a cis element for members of the Sp transcription factor family. Thus the SNP could alter the transcription factor binding ability of the FASN promoter and consequently affect the promoter activity of the gene. However, the functional consequences of the SNP on FASN gene expression are unknown. The present study was therefore directed at elucidating the underlying molecular mechanism that could explain the association of the SNP with milk fat content. Three cellular lines (3T3L1, HepG2, and MCF-7) were used to test the promoter and the transcription factor binding activities by luciferase reporter assays and electrophoretic mobility shift assays, respectively. Band shift assays were also carried out with nuclear extracts from lactating mammary gland (LMG) to further investigate the role of the SNP in this tissue. Our results demonstrate that the SNP alters the bovine FASN promoter activity in vitro and the Sp1/Sp3 binding ability of the sequence. In bovine LMG, the specific binding of Sp3 may account for the association with milk fat content.