QC-Chain: Fast and Holistic Quality Control Method for Next-Generation Sequencing Data

Next-generation sequencing (NGS) technologies have been widely used in life sciences. However, several kinds of sequencing artifacts, including low-quality reads and contaminating reads, were found to be quite common in raw sequencing data, which compromise downstream analysis. Therefore, quality control (QC) is essential for raw NGS data. However, although a few NGS data quality control tools are publicly available, there are two limitations: First, the processing speed could not cope with the rapid increase of large data volume. Second, with respect to removing the contaminating reads, none of them could identify contaminating sources de novo, and they rely heavily on prior information of the contaminating species, which is usually not available in advance. Here we report QC-Chain, a fast, accurate and holistic NGS data quality-control method. The tool synergeticly comprised of user-friendly tools for (1) quality assessment and trimming of raw reads using Parallel-QC, a fast read processing tool; (2) identification, quantification and filtration of unknown contamination to get high-quality clean reads. It was optimized based on parallel computation, so the processing speed is significantly higher than other QC methods. Experiments on simulated and real NGS data have shown that reads with low sequencing quality could be identified and filtered. Possible contaminating sources could be identified and quantified de novo, accurately and quickly. Comparison between raw reads and processed reads also showed that subsequent analyses (genome assembly, gene prediction, gene annotation, etc.) results based on processed reads improved significantly in completeness and accuracy. As regard to processing speed, QC-Chain achieves 7–8 time speed-up based on parallel computation as compared to traditional methods. Therefore, QC-Chain is a fast and useful quality control tool for read quality process and de novo contamination filtration of NGS reads, which could significantly facilitate downstream analysis. QC-Chain is publicly available at: http://www.computationalbioenergy.org/qc-chain.html.     

Methionine Synthase A2756G Polymorphism and Risk of Colorectal Adenoma and Cancer: Evidence Based on 27 Studies

Methionine synthase (MTR), which plays a central role in maintaining adequate intracellular folate, methionine and normal homocysteine concentrations, was thought to be involved in the development of colorectal cancer (CRC) and colorectal adenoma (CRA) by affecting DNA methylation. However, studies on the association between MTR A2756G polymorphism and CRC/CRA remain conflicting. We conducted a meta-analysis of 27 studies, including 13465 cases and 20430 controls for CRC, and 4844 cases and 11743 controls for CRA. Potential sources of heterogeneity and publication bias were also systematically explored. Overall, the summary odds ratio of G variant for CRC was 1.03 (95% CI: 0.96–1.09) and 1.05 (95% CI: 0.99–1.12) for CRA. No significant results were observed in heterozygous and homozygous when compared with wild genotype for these polymorphisms. In the stratified analyses according to ethnicity, source of controls, sample size, sex, and tumor site, no evidence of any gene-disease association was obtained. Results from the meta-analysis of four studies on MTR stratified according to smoking and alcohol drinking status showed an increased CRC risk in heavy smokers (OR = 2.06, 95% CI: 1.32–3.20) and heavy drinkers (OR = 2.00, 95% CI: 1.28–3.09) for G allele carriers. This meta-analysis suggests that the MTR A2756G polymorphism is not associated with CRC/CRA susceptibility and that gene-environment interaction may exist.     

Increased Expression of IL-22 Is Associated with Disease Activity in Behcet’s Disease

Objective

Interleukin (IL)-22 has been reported to be involved in the development of autoimmune diseases. This study aimed to analyze the expression and potential role of IL-22 in the pathogenesis of Behcet’s disease (BD).

Methods

The levels of IL-22 in patient sera or supernatants of cultured peripheral blood mononuclear cells (PBMCs) and CD4⁺T cells were detected by enzyme-linked immunosorbent assay (ELISA). Flow cytometry was used to evaluate the frequency of IL-22–producing CD4⁺ T cells. IL-22 mRNA from erythema nodosum skin lesions was examined using real time quantitative RT-PCR.

Results

BD patients with active uveitis showed a significantly higher expression of IL-22 in the supernatants of stimulated PBMCs and CD4⁺T cells compared with BD patients without active uveitis and normal controls. An increased frequency of IL-22-producing CD4⁺T cells was also found in BD patients with active uveitis. IL-22 mRNA expression was elevated in erythema nodosum skin lesions. In BD patients, a high IL-22 level in the supernatant of stimulated PBMCs correlated with the presence of retinal vasculitis and erythema nodosum.

Conclusions

IL-22 was associated with disease activity in BD and correlated with the presence of small vessel inflammation, suggesting that it may be involved in its pathogenesis.     

TNFAIP3 Gene Polymorphisms in a Chinese Han Population with Vogt–Koyanagi–Harada Syndrome

Background

This study was performed to evaluate the potential association of TNFAIP3 polymorphisms with Vogt–Koyanagi–Harada (VKH) disease in a Chinese Han population.

Methodology/Principal Findings

Five single-nucleotide polymorphisms (SNPs), rs10499194, rs610604, rs7753873, rs5029928 and rs9494885 of TNFAIP3 were genotyped in 834 VKH disease patients and 1415 healthy controls using a PCR-restriction fragment length polymorphism assay. An increased frequency of the C allele and CT genotype for rs9494885 were found in VKH patients in the Guangzhou and Chongqing cohorts (pc = 0.015, OR = 1.6, pc = 0.036, OR = 1.7; pc = 2.36×10−4, OR = 1.5, pc = 0.012, OR = 1.5, respectively). Meanwhile, a decreased frequency of the TT genotype for rs9494885 was observed in VKH patients in the Guangzhou and Chongqing cohorts (pc = 0.026, OR = 0.6, pc = 0.0074, OR = 0.7, respectively). The combined analysis showed that a significantly increased prevalence of the rs9494885 TC genotype and C allele were found in VKH disease patients compared with controls (pc = 2.26×10−5, OR = 1.7; pc = 1.09× 10−5, OR = 1.6, respectively). The frequency of the TT genotype of rs9494885 was markedly lower in VKH disease patients as compared with that in controls (pc = 1.12×10−5, OR = 0.6; p_c = 1.09×10⁻⁵, OR = 0.6, respectively). No association was found between rs10499194, rs610604, rs7753873 and rs5029928 polymorphisms and VKH disease. To our knowledge this is the first report describing the association of a TNFAIP3 gene polymorphism with VKH disease in a Chinese Han population.

Conclusions/Significance

The results suggest that the rs9494885 TC genotype and C allele may be predisposing factors to VKH disease, whereas the rs9494885 TT genotype and T allele may provide protection against this disease.     

Allele-Specific Behavior of Molecular Networks: Understanding Small-Molecule Drug Response in Yeast

The study of systems genetics is changing the way the genetic and molecular basis of phenotypic variation, such as disease susceptibility and drug response, is being analyzed. Moreover, systems genetics aids in the translation of insights from systems biology into genetics. The use of systems genetics enables greater attention to be focused on the potential impact of genetic perturbations on the molecular states of networks that in turn affects complex traits. In this study, we developed models to detect allele-specific perturbations on interactions, in which a genetic locus with alternative alleles exerted a differing influence on an interaction. We utilized the models to investigate the dynamic behavior of an integrated molecular network undergoing genetic perturbations in yeast. Our results revealed the complexity of regulatory relationships between genetic loci and networks, in which different genetic loci perturb specific network modules. In addition, significant within-module functional coherence was found. We then used the network perturbation model to elucidate the underlying molecular mechanisms of individual differences in response to 100 diverse small molecule drugs. As a result, we identified sub-networks in the integrated network that responded to variations in DNA associated with response to diverse compounds and were significantly enriched for known drug targets. Literature mining results provided strong independent evidence for the effectiveness of these genetic perturbing networks in the elucidation of small-molecule responses in yeast.