A panel of induced pluripotent stem cells from chimpanzees: A resource for comparative functional genomics

Comparative genomics studies in primates are restricted due to our limited access to samples. In order to gain better insight into the genetic processes that underlie variation in complex phenotypes in primates, we must have access to faithful model systems for a wide range of cell types. To facilitate this, we generated a panel of 7 fully characterized chimpanzee induced pluripotent stem cell (iPSC) lines derived from healthy donors. To demonstrate the utility of comparative iPSC panels, we collected RNA-sequencing and DNA methylation data from the chimpanzee iPSCs and the corresponding fibroblast lines, as well as from 7 human iPSCs and their source lines, which encompass multiple populations and cell types. We observe much less withinspecies variation in iPSCs than in somatic cells, indicating the reprogramming process erases many inter-individual differences. The low within-species regulatory variation in iPSCs allowed us to identify many novel inter-species regulatory differences of small magnitude

Immunochemical faecal occult blood test: number of samples and positivity cutoff. What is the best strategy for colorectal cancer screening?

Immunochemical faecal occult blood tests have shown a greater sensitivity than guaiac test in colorectal cancer screening, but optimal number of samples and cutoff have still to be defined. The aim of this multicentric study was to evaluate the performance of immunochemical-based screening strategies according to different positivity thresholds (80, 100, 120 ng ml−1) and single vs double sampling (one, at least one, or both positive samples) using 1-day sample with cutoff at 100 ng ml−1 as the reference strategy. A total of 20 596 subjects aged 50–69 years were enrolled from Italian population-based screening programmes. Positivity rate was 4.5% for reference strategy and 8.0 and 2.0% for the most sensitive and the most specific strategy, respectively. Cancer detection rate of reference strategy was 2.8‰, and ranged between 2.1 and 3.4‰ in other strategies; reference strategy detected 15.6‰ advanced adenomas (range=10.0–22.5‰). The number needed to scope to find a cancer or an advanced adenoma was lower than 2 (1.5–1.7) for the most specific strategies, whereas it was 2.4–2.7, according to different thresholds, for the most sensitive ones. Different strategies seem to have a greater impact on adenomas rather than on cancer detection rate. The study provides information when deciding screening protocols and to adapt them to local resources

Identification of 55,000 Replicated DNA Methylation QTL

DNA methylation plays an important role in the regulation of transcription. Genetic control of DNA methylation is a potential candidate for explaining the many identified SNP associations with disease that are not found in coding regions. We replicated 52,916 cis and 2,025 trans DNA methylation quantitative trait loci (mQTL) using methylation from whole blood measured on Illumina HumanMethylation450 arrays in the Brisbane Systems Genetics Study (n = 614 from 177 families) and the Lothian Birth Cohorts of 1921 and 1936 (combined n = 1366). The trans mQTL SNPs were found to be over-represented in 1 Mbp subtelomeric regions, and on chromosomes 16 and 19. There was a significant increase in trans mQTL DNA methylation sites in upstream and 5' UTR regions. The genetic heritability of a number of complex traits and diseases was partitioned into components due to mQTL and the remainder of the genome. Significant enrichment was observed for height (p = 2.1 × 10), ulcerative colitis (p = 2 × 10), Crohn's disease (p = 6 × 10) and coronary artery disease (p = 5.5 × 10) when compared to a random sample of SNPs with matched minor allele frequency, although this enrichment is explained by the genomic location of the mQTL SNPs

Statistical and integrative system-level analysis of DNA methylation data

Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This Review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information

Methylation QTLs Are Associated with Coordinated Changes in Transcription Factor Binding, Histone Modifications, and Gene Expression Levels

DNA methylation is an important epigenetic regulator of gene expression. Recent studies have revealed widespread associations between genetic variation and methylation levels. However, the mechanistic links between genetic variation and methylation remain unclear. To begin addressing this gap, we collected methylation data at ∼300,000 loci in lymphoblastoid cell lines (LCLs) from 64 HapMap Yoruba individuals, and genome-wide bisulfite sequence data in ten of these individuals. We identified (at an FDR of 10%) 13,915 cis methylation QTLs (meQTLs)—i.e., CpG sites in which changes in DNA methylation are associated with genetic variation at proximal loci. We found that meQTLs are frequently associated with changes in methylation at multiple CpGs across regions of up to 3 kb. Interestingly, meQTLs are also frequently associated with variation in other properties of gene regulation, including histone modifications, DNase I accessibility, chromatin accessibility, and expression levels of nearby genes. These observations suggest that genetic variants may lead to coordinated molecular changes in all of these regulatory phenotypes. One plausible driver of coordinated changes in different regulatory mechanisms is variation in transcription factor (TF) binding. Indeed, we found that SNPs that change predicted TF binding affinities are significantly enriched for associations with DNA methylation at nearby CpGs.</p

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DAVID analysis of meQTLs implicated in GWAS.

<p>The results from a DAVID analysis <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004663#pgen.1004663-Huangda1" target="_blank">[66]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004663#pgen.1004663-Huangda2" target="_blank">[67]</a> of genes near a SNP whose genotype is associated with DNA methylation levels and complex disease. These data include GO terms, KEGG pathways, and up-regulated tissues.</p><p>DAVID analysis of meQTLs implicated in GWAS.</p