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.

Human hepatoma HepG2 cells are used as an in vitro model of the human liver. High-throughput transcriptomic sequencing is an advanced approach for assessing the functional state of a tissue or cell type. However, the influence of experimental factors, such as the sample preparation method and inter-laboratory variation, on the transcriptomic profile has not been evaluated. The whole-transcriptome sequencing of HepG2 cells was performed using the SOLiD platform and validated using droplet digital PCR. The gene expression profile was compared to the results obtained with the same sequencing method in another laboratory and using another sample preparation method. We also compared the transcriptomic profile HepG2 cells with that of liver tissue. Comparison of the gene expression profiles between the HepG2 cell line and liver tissue revealed the highest variation, followed by HepG2 cells submitted to two different sample preparation protocols. The lowest variation was observed between HepG2 cells prepared by two different laboratories using the same protocol. The enrichment analysis of the genes that were differentially expressed between HepG2 cells and liver tissue mainly revealed the cancer-associated gene signature of HepG2 cells and the activation of the response to chemical stimuli in the liver tissue. The HepG2 transcriptome obtained with the SOLiD platform was highly correlated with the published transcriptome obtained with the Illumina and Helicos platforms, with moderate correspondence to microarrays. In the present study, we assessed the influence of experimental factors on the HepG2 transcriptome and identified differences in gene expression between the HepG2 cell line and liver cells. These findings will facilitate robust experimental design in the fields of pharmacology and toxicology. Our results were supported by a comparative analysis with previous HepG2 gene expression studies.

Purpose: Iron is an important component of the oxygen-binding proteins and may be critical to optimal athletic performance. Previous studies have suggested that the G allele of C/G rare variant (rs1799945), which causes H63D amino acid replacement, in the HFE is associated with elevated iron indexes and may give some advantage in endurance-oriented sports. The aim of the present study was to investigate the association between the HFE H63D polymorphism and elite endurance athlete status in Japanese and Russian populations, aerobic capacity and to perform a meta-analysis using current findings and three previous studies. Methods: The study involved 315 international-level endurance athletes (255 Russian and 60 Japanese) and 809 healthy controls (405 Russian and 404 Japanese). Genotyping was performed using micro-array analysis or by PCR. VO_2max in 46 male Russian endurance athletes was determined using gas analysis system. Results: The frequency of the iron-increasing CG/GG genotypes was significantly higher in Russian (38.0 vs 24.9%; OR 1.85, P = 0.0003) and Japanese (13.3 vs 5.0%; OR 2.95, P = 0.011) endurance athletes compared to ethnically matched controls. The meta-analysis using five cohorts (two French, Japanese, Spanish, and Russian; 586 athletes and 1416 controls) showed significant prevalence of the CG/GG genotypes in endurance athletes compared to controls (OR 1.96, 95% CI 1.58–2.45; P = 1.7 × 10^–9). Furthermore, the HFE G allele was associated with high V̇O_2max in male athletes [CC: 61.8 (6.1), CG/GG: 66.3 (7.8) ml/min/kg; P = 0.036]. Conclusions: We have shown that the HFE H63D polymorphism is strongly associated with elite endurance athlete status, regardless ethnicities and aerobic capacity in Russian athletes.

Escherichia coli (E. coli) has been increasingly implicated in the pathogenesis of Crohn’s disease (CD). The phylogeny of E. coli isolated from Crohn’s disease patients (CDEC) was controversial, and while genotyping results suggested heterogeneity, the sequenced strains of E. coli from CD patients were closely related. We performed the shotgun genome sequencing of 28 E. coli isolates from ten CD patients and compared genomes from these isolates with already published genomes of CD strains and other pathogenic and non-pathogenic strains. CDEC was shown to belong to A, B1, B2 and D phylogenetic groups. The plasmid and several operons from the reference CD-associated E. coli strain LF82 were demonstrated to be more often present in CDEC genomes belonging to different phylogenetic groups than in genomes of commensal strains. The operons include carbon-source induced invasion GimA island, prophage I, iron uptake operons I and II, capsular assembly pathogenetic island IV and propanediol and galactitol utilization operons. Our findings suggest that CDEC are phylogenetically diverse. However, some strains isolated from independent sources possess highly similar chromosome or plasmids. Though no CD-specific genes or functional domains were present in all CD-associated strains, some genes and operons are more often found in the genomes of CDEC than in commensal E. coli. They are principally linked to gut colonization and utilization of propanediol and other sugar alcohols.

Muscle fiber composition is associated with physical performance, with endurance athletes having a high proportion of slow-twitch muscle fibers compared to power athletes. Approximately 45% of muscle fiber composition is heritable, however, single nucleotide polymorphisms (SNP) underlying inter-individual differences in muscle fiber types remain largely unknown. Based on three whole genome SNP datasets, we have shown that the rs236448 A allele located near the cyclin-dependent kinase inhibitor 1A (CDKN1A) gene was associated with an increased proportion of slow-twitch muscle fibers in Russian (n = 151; p = 0.039), Finnish (n = 287; p = 0.03), and Japanese (n = 207; p = 0.008) cohorts (meta-analysis: p = 7.9 × 10⁻⁵. Furthermore, the frequency of the rs236448 A allele was significantly higher in Russian (p = 0.045) and Japanese (p = 0.038) elite endurance athletes compared to ethnically matched power athletes. On the contrary, the C allele was associated with a greater proportion of fast-twitch muscle fibers and a predisposition to power sports. CDKN1A participates in cell cycle regulation and is suppressed by the miR-208b, which has a prominent role in the activation of the slow myofiber gene program. Bioinformatic analysis revealed that the rs236448 C allele was associated with increased CDKN1A expression in whole blood (p = 8.5 × 10⁻¹⁵) and with greater appendicular lean mass (p = 1.2 × 10⁻⁵), whereas the A allele was associated with longer durations of exercise (p = 0.044) reported amongst the UK Biobank cohort. Furthermore, the expression of CDKN1A increased in response to strength (p < 0.0001) or sprint (p = 0.00035) training. Accordingly, we found that CDKN1A expression is significantly (p = 0.002) higher in the m. vastus lateralis of strength athletes compared to endurance athletes and is positively correlated with the percentage of fast-twitch muscle fibers (p = 0.018). In conclusion, our data suggest that the CDKN1A rs236448 SNP may be implicated in the determination of muscle fiber composition and may affect athletic performance.

Purpose: Circulating testosterone levels are a heritable trait with anabolic properties in various tissues, including skeletal muscle. So far, hundreds of single nucleotide polymorphisms (SNPs) associated with testosterone levels have been identified in nonathletic populations. The aim of the present study was to test the association of 822 testosterone-increasing SNPs with muscle-related traits (muscle fiber size, fat-free mass and handgrip strength) and to validate the identified SNPs in independent cohorts of strength and power athletes. Methods: One hundred and forty-eight physically active individuals (47 females, 101 males) were assessed for cross-sectional area (CSA) of fast-twitch muscle fibers. Significant SNPs were further assessed for fat-free mass and handgrip strength in > 354,000 participants from the UK Biobank cohort. The validation cohorts included Russian elite athletes. Results: From an initial panel of 822 SNPs, we identified five testosterone-increasing alleles (DOCK3 rs77031559 G, ESR1 rs190930099 G, GLIS3 rs34706136 TG, GRAMD1B rs850294 T, TRAIP rs62260729 C) nominally associated (P < 0.05) with CSA of fast-twitch muscle fibers, fat-free mass and handgrip strength. Based on these five SNPs, the number of testosterone-increasing alleles was positively associated with testosterone levels in male athletes (P = 0.048) and greater strength performance in weightlifters (P = 0.017). Moreover, the proportion of participants with ≥ 2 testosterone-increasing alleles was higher in power athletes compared to controls (68.9 vs. 55.6%; P = 0.012). Conclusion: Testosterone-related SNPs are associated with muscle fiber size, fat-free mass and strength, which combined can partially contribute to a greater predisposition to strength/power sports.