Meta-analysis Followed by Replication Identifies Loci in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as Associated with Systemic Lupus Erythematosus in Asians

Systemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic involvement and ethnic differences. Susceptibility genes identified so far only explain a small portion of the genetic heritability of SLE, suggesting that many more loci are yet to be uncovered for this disease. In this study, we performed a meta-analysis of genome-wide association studies on SLE in Chinese Han populations and followed up the findings by replication in four additional Asian cohorts with a total of 5,365 cases and 10,054 corresponding controls. We identified genetic variants in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as associated with the disease. These findings point to potential roles of cell-cycle regulation, autophagy, and DNA demethylation in SLE pathogenesis. For the region involving TET3 and that involving CDKN1B, multiple independent SNPs were identified, highlighting a phenomenon that might partially explain the missing heritability of complex diseases

Research on Continuous Injection Direct Rolling Process for PMMA Optical Plate

Continuous injection direct rolling (CIDR) combined intermittent injection and rolling process is a new technology for molding optical polymer plates with microstructured patterns; research on forming PMMA optical plates is an aspect of it in this paper. The equipment of CIDR process consists of plastic injection module, precision rolling module, and automatic coiling module. Based on the establishing mathematical CIDR models, numerical analysis was used to explode the distribution of velocity, temperature, and pressure in injection-rolling zone. The simulation results show that it is feasible to control the temperature, velocity, and injection-rolling force, so it can form polymer plate under certain process condition. CIDR experiment equipment has been designed and produced. PMMA optical plate was obtained by CIDR experiments, longitudinal thickness difference is 0.005 mm/200 mm, horizontal thickness difference is 0.02/200 mm, transmittance is 86.3%, Haze is 0.61%, and the difference is little compared with optical glasses. So it can be confirmed that CIDR process is practical to produce PMMA optical plates

Effects of Thermal Reflowing Stress on Mechanical Properties of Novel SMT-SREKs

A novel silicone rubber elastic key (SREK) is proposed in this paper for surface mounting technology (SMT) applications. Effects of thermal reflowing stress on the mechanical properties of SMT-SREKs are investigated. The manufactured SMT-SREKs, which underwent various reflowing conditions in advance, are subjected to pressing force and fatigue pressing tests. Fatigue lifetime projection model and its predicted error are then assessed systematically. The thermal degradation of silicone rubber materials is illustrated through the dynamic mechanical analysis and the Fourier transform infrared spectroscopy experiments. The mechanical finite element modeling is also conducted to simulate the pressing process. The results show that the pressing force and tactility of the SMT-SREKs are strongly affected by the reflowing condition, which contributes to the degradation of the silicone rubber materials. During the fatigue pressing test, the change rate of tactility increases with the reflowing peak temperature ( T-{p} ) and is accelerated by the repeated reflowing process. Moreover, a linear model can precisely project the tactility before the fatigue pressing number of 2.0E+6 times, and the impact rate of T-{p} on tactility with the increasing fatigue pressing number can be predicted effectively by using a logarithm model.Electronic Components, Technology and Material

Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array

Abstract Background Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle. Results Using the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle. Conclusions We identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle

Fast genomic prediction of breeding values using parallel Markov chain Monte Carlo with convergence diagnosis

Abstract Background Running multiple-chain Markov Chain Monte Carlo (MCMC) provides an efficient parallel computing method for complex Bayesian models, although the efficiency of the approach critically depends on the length of the non-parallelizable burn-in period, for which all simulated data are discarded. In practice, this burn-in period is set arbitrarily and often leads to the performance of far more iterations than required. In addition, the accuracy of genomic predictions does not improve after the MCMC reaches equilibrium. Results Automatic tuning of the burn-in length for running multiple-chain MCMC was proposed in the context of genomic predictions using BayesA and BayesCπ models. The performance of parallel computing versus sequential computing and tunable burn-in MCMC versus fixed burn-in MCMC was assessed using simulation data sets as well by applying these methods to genomic predictions of a Chinese Simmental beef cattle population. The results showed that tunable burn-in parallel MCMC had greater speedups than fixed burn-in parallel MCMC, and both had greater speedups relative to sequential (single-chain) MCMC. Nevertheless, genomic estimated breeding values (GEBVs) and genomic prediction accuracies were highly comparable between the various computing approaches. When applied to the genomic predictions of four quantitative traits in a Chinese Simmental population of 1217 beef cattle genotyped by an Illumina Bovine 770 K SNP BeadChip, tunable burn-in multiple-chain BayesCπ (TBM-BayesCπ) outperformed tunable burn-in multiple-chain BayesCπ (TBM-BayesA) and Genomic Best Linear Unbiased Prediction (GBLUP) in terms of the prediction accuracy, although the differences were not necessarily caused by computational factors and could have been intrinsic to the statistical models per se. Conclusions Automatically tunable burn-in multiple-chain MCMC provides an accurate and cost-effective tool for high-performance computing of Bayesian genomic prediction models, and this algorithm is generally applicable to high-performance computing of any complex Bayesian statistical model