SNPs affecting functional elements with <i>cis</i>-regulatory effects on miRNA regulation.

<p>The first column gives the rs-number of the SNPs, in the second column the HGNC symbol of the affected genes are listed and the third column describes the functional mechanisms which could be assigned to the SNPs. The last column contains all traits associated with the respective SNP.</p

Impact of the SNP <i>rs10923</i> on miRNA-mediated repression of <i>SMC4</i>.

<p>Shown is the mRNA:miRNA duplex for the reference allele of <i>rs10923</i> (lower part). The minor allele of the SNP (position adumbrated by the light red box) disrupts the seed complementary region. In the upper part of the figure, the expression pattern of <i>SMC4</i> in lymphoblastoid cells is illustrated. The minor G allele of the polymorphism is significantly () linked to an increased abundance of <i>SMC4</i> transcript. For the illustration of expression values Genevar output was adapted <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036694#pone.0036694-Yang3" target="_blank">[89]</a>.</p

Mechanisms mediated by 3′-UTR SNPs affecting miRNA targeting.

<p><b>A:</b> Regular binding of the RISC to the target mRNA. <b>B:</b> Binding of the RISC and, thus, miRNA-mediated silencing is inhibited by a change in RNA secondary structure. <b>C:</b> A mutation within the MRE seed site disrupts the ability of a certain miRNA to target a transcript. Here, the opposite effect also applies, i.e. a new MRE seed site is formed by a polymorphism which enables targeting by a miRNA usually not controlling the respective transcript. <b>D:</b> Altered splicing by acceptor or donor splice site gain. The existing splice variants (I and II, grayed) are extended by mutationally introduced additional splice variants: (III) A present acceptor site (A₁) is substituted by a new acceptor site (A<i>_mut</i>), and (IV) a naturally occurring donor site (D₂) is replaced by a new donor site (D<i>_mut</i>). Both effects may lead to a considerable loss of exon sequence (displayed in red) and, thus, RISC binding sites. <b>E:</b> The percentages of classified SNPs mediating the single mechanisms. The greatest amount of functionally annotated 3′-UTR SNPs directly affect MRE sequences, followed by SNPs changing the RNA secondary structure and SNPs with an predicted effect on 3′-UTR splicing.</p

Statistical analysis of 3′-UTR enrichment values and determination of the folding correlation coefficient threshold.

<p><b>A:</b> SNP enrichment in the 3′-UTR in dependency of different LD thresholds. Displayed are the ORs and confidence intervals for five cut-offs. Accumulative 3′-UTR SNP sets were calculated. The fitted distribution (dashed line) points out the stabilization of the OR around a threshold of 0.8. <b>B:</b> SNP enrichment in the 3′-UTR in dependency of the minor allele frequency. Displayed are the ORs and confidence intervals for the 5 different MAF bins. SNP counts were compared within the respective bins. <b>C:</b> Probability distribution of correlation coefficients (<i>p</i>) between wild-type and mutated structures of RBP-binding regions. Below a cut-off for the correlation coefficient of 0.55 (displayed in gray) the probability to observe a change of RNA secondary structure of this scale by chance amounts to less than 5%.</p

Impact model of mutated SMC4 in primary biliary cirrhosis.

<p>Inflammation follows the autoimmune response leading to the activation of the <i>MAPK</i>-pathway via signal molecules as e.g. <i>TNF-alpha</i>. Transcription factors activated as downstream effect of <i>MAPK</i> activation lead to over-expression of DNA repair genes. The in PBC over-expressed <i>hsa-mir-299-5p</i> is hypothesized to target <i>SMC4</i> at the seed complementary region where <i>rs10923</i> is located. With the major allele, <i>SMC4</i> is silenced, whereas the mutated <i>SMC4</i>-G cannot be bound by <i>hsa-mir-299-5p</i> and therefore is translated without interference. This results in the more frequent association of the <i>Condensin I-PARP1-XRCC1</i> complex contributing to disturbed DNA repair in cirrhosis tissue.</p

The number of commercial SNPs necessary to describe all SNPs in different populations

<p><b>Copyright information:</b></p><p>Taken from "Evaluating the performance of commercial whole-genome marker sets for capturing common genetic variation"</p><p>http://www.biomedcentral.com/1471-2164/8/159</p><p>BMC Genomics 2007;8():159-159.</p><p>Published online 11 Jun 2007</p><p>PMCID:PMC1914356.</p><p></p> For each SNP in the commercial panels, we determined whether it was a tagSNP (the SNP with highest r) for any marker in the selected population samples. For example, among the 296 SNP in HumanHap 300 with MAF 1% there were 231 (78%) SNPs that described SNP from all populations in these regions. Only 20 out of 296 (6.8%) were the best for describing the CEPH population and 2 (0.7%) were the best for describing only the Yoruban population. The analysis is based only on the two ENCODE regions in which the Estonian markers were genotyped

Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10−204) and 10 loci for sphingolipids (smallest P-value = 3.10×10−57). After a correction for multiple comparisons (P-value<2.2×10−9), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits

Summary of Metabochip SNPs by trait: Fine-mapping and replication.

<p> <i>SNP counts are numbers of SNPs successfully manufactured on the Metabochip array.</i></p>*<p> <i>Waist-to-hip ratio and waist circumference were adjusted for body mass index.</i></p

Coverage of 257 Metabochip fine-mapping regions.

<p>Fraction of 1000 Genomes Project SNPs in strong linkage disequilibrium (r²≥.8) with HapMap 3 (green squares) or Metabochip (blue dots) SNPs as a function of minor allele frequencies: (A) 1000 Genomes Pilot 1 SNPs, (B) 1000 Genomes Phase 1 SNPs (May 2011 release).</p

Summary of Metabochip SNPs by SNP category.

<p> <i>Numbers in parenthesis represents the proportion of the SNPs in the previous column. A SNP may fall into multiple categories.</i></p