AGTR2 gene polymorphism is associated with muscle fibre composition, athletic status and aerobic performance.

Muscle fibre type is a heritable trait and can partly predict athletic success. It has been proposed that polymorphisms of genes involved in the regulation of muscle fibre characteristics may predispose the muscle precursor cells of a given individual to be predominantly fast or slow. In the present study, we examined the association between 15 candidate gene polymorphisms and muscle fibre type composition of the vastus lateralis muscle in 55 physically active, healthy men. We found that rs11091046 C allele carriers of the angiotensin II type 2 receptor gene (AGTR2; involved in skeletal muscle development, metabolism and circulatory homeostasis) had a significantly higher percentage of slow-twitch fibres than A allele carriers [54.2 (11.1) versus 45.2 (10.2)%; P = 0.003]. These data indicate that 15.2% of the variation in muscle fibre composition of the vastus lateralis muscle can be explained by the AGTR2 genotype. Next, we investigated the frequencies of the AGTR2 alleles in 2178 Caucasian athletes and 1220 control subjects. The frequency of the AGTR2 C allele was significantly higher in male and female endurance athletes compared with power athletes (males, 62.7 versus 51.7%, P = 0.0038; females, 56.6 versus 48.1%, P = 0.0169) and control subjects (males, 62.7 versus 51.0%, P = 0.0006; elite female athletes, 65.1 versus 55.2%, P = 0.0488). Furthermore, the frequency of the AGTR2 A allele was significantly over-represented in female power athletes (51.9%) in comparison to control subjects (44.8%, P = 0.0069). We also found that relative maximal oxygen consumption was significantly greater in male endurance athletes with the AGTR2 C allele compared with AGTR2 A allele carriers [n = 28; 62.3 (4.4) versus 57.4 (6.0) ml min(-1) kg(-1); P = 0.0197]. Taken together, these results demonstrate that the AGTR2 gene C allele is associated with an increased proportion of slow-twitch muscle fibres, endurance athlete status and aerobic performance, while the A allele is associated with a higher percentage of fast-twitch fibres and power-oriented disciplines.

An integrative analysis of reprogramming in human isogenic system identified a clone selection criterion.

The pluripotency of newly developed human induced pluripotent stem cells (iPSCs) is usually characterized by physiological parameters; i.e., by their ability to maintain the undifferentiated state and to differentiate into derivatives of the 3 germ layers. Nevertheless, a molecular comparison of physiologically normal iPSCs to the "gold standard" of pluripotency, embryonic stem cells (ESCs), often reveals a set of genes with different expression and/or methylation patterns in iPSCs and ESCs. To evaluate the contribution of the reprogramming process, parental cell type, and fortuity in the signature of human iPSCs, we developed a complete isogenic reprogramming system. We performed a genome-wide comparison of the transcriptome and the methylome of human isogenic ESCs, 3 types of ESC-derived somatic cells (fibroblasts, retinal pigment epithelium and neural cells), and 3 pairs of iPSC lines derived from these somatic cells. Our analysis revealed a high input of stochasticity in the iPSC signature that does not retain specific traces of the parental cell type and reprogramming process. We showed that 5 iPSC clones are sufficient to find with 95% confidence at least one iPSC clone indistinguishable from their hypothetical isogenic ESC line. Additionally, on the basis of a small set of genes that are characteristic of all iPSC lines and isogenic ESCs, we formulated an approach of "the best iPSC line" selection and confirmed it on an independent dataset.

Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips.

Illumina's Infinium HumanMethylation450 BeadChip arrays were used to examine genome-wide DNA methylation profiles in 22 sample pairs from colorectal cancer (CRC) and adjacent tissues and 19 colon tissue samples from cancer-free donors. We show that the methylation profiles of tumors and healthy tissue samples can be clearly distinguished from one another and that the main source of methylation variability is associated with disease status. We used different statistical approaches to evaluate the methylation data. In general, at the CpG-site level, we found that common CRC-specific methylation patterns consist of at least 15,667 CpG sites that were significantly different from either adjacent healthy tissue or tissue from cancer-free subjects. Of these sites, 10,342 were hypermethylated in CRC, and 5,325 were hypomethylated. Hypermethylated sites were common in the maximum number of sample pairs and were mostly located in CpG islands, where they were significantly enriched for differentially methylated regions known to be cancer-specific. In contrast, hypomethylated sites were mostly located in CpG shores and were generally sample-specific. Despite the considerable variability in methylation data, we selected a panel of 14 highly robust candidates showing methylation marks in genes SND1, ADHFE1, OPLAH, TLX2, C1orf70, ZFP64, NR5A2, and COL4A. This set was successfully cross-validated using methylation data from 209 CRC samples and 38 healthy tissue samples from The Cancer Genome Atlas consortium (AUC = 0.981 [95% CI: 0.9677-0.9939], sensitivity = 100% and specificity = 82%). In summary, this study reports a large number of loci with novel differential methylation statuses, some of which may serve as candidate markers for diagnostic purposes.