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Background and aims:Infliximab is an effective treatment for ulcerative colitis with over 60% of patients responding to treatment and up to 30% reaching remission. The mechanism of resistance to anti-tumour necrosis factor α (anti-TNFα) is unknown. This study used colonic mucosal gene expression to provide a predictive response signature for infliximab treatment in ulcerative colitis.Methods:Two cohorts of patients who received their first treatment with infliximab for refractory ulcerative colitis were studied. Response to infliximab was defined as endoscopic and histological healing. Total RNA from pre-treatment colonic mucosal biopsies was analysed with Affymetrix Human Genome U133 Plus 2.0 Arrays. Quantitative RT-PCR was used to confirm microarray data.Results:For predicting response to infliximab treatment, pre-treatment colonic mucosal expression profiles were compared for responders and non-responders. Comparative analysis identified 179 differentially expressed probe sets in cohort A and 361 in cohort B with an overlap of 74 probe sets, representing 53 known genes, between both analyses. Comparative analysis of both cohorts combined, yielded 212 differentially expressed probe sets. The top five differentially expressed genes in a combined analysis of both cohorts were osteoprotegerin, stanniocalcin-1, prostaglandin-endoperoxide synthase 2, interleukin 13 receptor alpha 2 and interleukin 11. All proteins encoded by these genes are involved in the adaptive immune response. These markers separated responders from non-responders with 95% sensitivity and 85% specificity.Conclusion:Gene array studies of ulcerative colitis mucosal biopsies identified predictive panels of genes for (non-)response to infliximab. Further study of the pathways involved should allow a better understanding of the mechanisms of resistance to infliximab therapy in ulcerative colitis.ClinicalTrials.gov number, NCT00639821.

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems.

Abstract Rationale Human rhinovirus infections cause colds and trigger exacerbations of lower airway diseases. Objectives To define changes in gene expression profiles during in vivo rhinovirus infections. Methods Nasal epithelial scrapings were obtained before and during experimental rhinovirus infection, and gene expression was evaluated by microarray. Naturally acquired rhinovirus infections, cultured human epithelial cells, and short interfering RNA knockdown were used to further evaluate the role of viperin in rhinovirus infections. Measurements and Main Results Symptom scores and viral titers were measured in subjects inoculated with rhinovirus or sham control, and changes in gene expression were assessed 8 and 48 hours after inoculation. Real-time reverse transcription-polymerase chain reaction for viperin and rhinoviruses was used in naturally acquired infections, and viperin mRNA levels and viral titers were measured in cultured cells. Rhinovirus-induced changes in gene expression were not observed 8 hours after viral infection, but 11,887 gene transcripts were significantly altered in scrapings obtained 2 days postinoculation. Major groups of up-regulated genes included chemokines, signaling molecules, interferon-responsive genes, and antivirals. Viperin expression was further examined and also was increased in naturally acquired rhinovirus infections, as well as in cultured human epithelial cells infected with intact, but not replication-deficient, rhinovirus. Knockdown of viperin with short interfering RNA increased rhinovirus replication in infected epithelial cells. Conclusions Rhinovirus infection significantly alters the expression of many genes associated with the immune response, including chemokines and antivirals. The data obtained provide insights into the host response to rhinovirus infection and identify potential novel targets for further evaluation.

Purpose: Hypertrophic cardiomyopathy (HCM) is caused primarily by pathogenic variants in genes encoding sarcomere proteins. We report genetic testing results for HCM in 2,912 unrelated individuals with nonsyndromic presentations from a broad referral population over 10 years. Methods: Genetic testing was performed by Sanger sequencing for 10 genes from 2004 to 2007, by HCM CardioChip for 11 genes from 2007 to 2011 and by next-generation sequencing for 18, 46, or 51 genes from 2011 onward. Results: The detection rate is ~32% among unselected probands, with inconclusive results in an additional 15%. Detection rates were not significantly different between adult and pediatric probands but were higher in females compared with males. An expanded gene panel encompassing more than 50 genes identified only a very small number of additional pathogenic variants beyond those identifiable in our original panels, which examined 11 genes. Familial genetic testing in at-risk family members eliminated the need for longitudinal cardiac evaluations in 691 individuals. Based on the projected costs derived from Medicare fee schedules for the recommended clinical evaluations of HCM family members by the American College of Cardiology Foundation/American Heart Association, our data indicate that genetic testing resulted in a minimum cost savings of about $0.7 million. Conclusion: Clinical HCM genetic testing provides a definitive molecular diagnosis for many patients and provides cost savings to families. Expanded gene panels have not substantively increased the clinical sensitivity of HCM testing, suggesting major additional causes of HCM still remain to be identified. Genet Med 17 11, 880–888.

Batch effects can lead to incorrect biological conclusions but are not widely considered. The authors show that batch effects are relevant to a range of high-throughput 'omics' data sets and are crucial to address. They also explain how batch effects can be mitigated. High-throughput technologies are widely used, for example to assay genetic variants, gene and protein expression, and epigenetic modifications. One often overlooked complication with such studies is batch effects, which occur because measurements are affected by laboratory conditions, reagent lots and personnel differences. This becomes a major problem when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. Using both published studies and our own analyses, we argue that batch effects (as well as other technical and biological artefacts) are widespread and critical to address. We review experimental and computational approaches for doing so.

Background China is the birthplace of the deer family and the country with the most abundant deer resources. However, at present, China’s deer industry faces the problem that pure sika deer and hybrid deer cannot be easily distinguished. Therefore, the development of a SNP identification chip is urgently required. Results In this study, 250 sika deer, 206 red deer, 23 first-generation hybrid deer (F1), 20 s-generation hybrid deer (F2), and 20 third-generation hybrid deer (F3) were resequenced. Using the chromosome-level sika deer genome as the reference sequence, mutation detection was performed on all individuals, and a total of 130,306,923 SNP loci were generated. After quality control filtering was performed, the remaining 31,140,900 loci were confirmed. From molecular-level and morphological analyses, the sika deer reference population and the red deer reference population were established. The Fst values of all SNPs in the two reference populations were calculated. According to customized algorithms and strict screening principles, 1000 red deer-specific SNP sites were finally selected for chip design, and 63 hybrid individuals were determined to contain red deer-specific SNP loci. The results showed that the gene content of red deer gradually decreased in subsequent hybrid generations, and this decrease roughly conformed to the law of statistical genetics. Reaction probes were designed according to the screening sites. All candidate sites met the requirements of the Illumina chip scoring system. The average score was 0.99, and the MAF was in the range of 0.3277 to 0.3621. Furthermore, 266 deer (125 sika deer, 39 red deer, 56 F1, 29 F2,17 F3) were randomly selected for 1 K SNP chip verification. The results showed that among the 1000 SNP sites, 995 probes were synthesized, 4 of which could not be typed, while 973 loci were polymorphic. PCA, random forest and ADMIXTURE results showed that the 1 K sika deer SNP chip was able to clearly distinguish sika deer, red deer, and hybrid deer and that this 1 K SNP chip technology may provide technical support for the protection and utilization of pure sika deer species resources. Conclusion We successfully developed a low-density identification chip that can quickly and accurately distinguish sika deer from their hybrid offspring, thereby providing technical support for the protection and utilization of pure sika deer germplasm resources.

Oligonucleotide synthesis is a fundamental technology in various fields of life science, including synthetic biology, molecular diagnostics, and biotechnology. In this study, we present OpenIDS2, an open-source, second-generation inkjet-based DNA synthesizer designed to enable flexible and low-cost synthesis in laboratory settings. Built upon the original OpenIDS platform, OpenIDS2 reduces the overall device volume to approximately one-third, integrates all control electronics through a custom-designed printed circuit board (PCB), and improves operational stability and fabrication accessibility via a peristaltic pump–based bulk solution delivery system. Notably, most mechanical components are designed for 3D printing, allowing users to fabricate and assemble the system at low cost using widely available tools. This design significantly enhances reproducibility and global accessibility as an open-source hardware platform. The system supports phosphoramidite chemistry and successfully synthesized 15-mer poly(dT) sequences on CPG-based substrates, which were subsequently analyzed by urea-PAGE and HPLC. OpenIDS2 not only demonstrates the practicality of a fully open, benchtop oligonucleotide synthesizer, but it also serves as a reproducible and extensible foundational platform that lowers the barrier to entry for laboratory automation through its nature as an open-source contribution.

Gene transcripts with invariant abundance during development and in the face of environmental stimuli are essential reference points for accurate gene expression analyses, such as RNA gel-blot analysis or quantitative reverse transcription-polymerase chain reaction (PCR). An exceptionally large set of data from Affymetrix ATH1 whole-genome GeneChip studies provided the means to identify a new generation of reference genes with very stable expression levels in the model plant species Arabidopsis (Arabidopsis thaliana). Hundreds of Arabidopsis genes were found that outperform traditional reference genes in terms of expression stability throughout development and under a range of environmental conditions. Most of these were expressed at much lower levels than traditional reference genes, making them very suitable for normalization of gene expression over a wide range of transcript levels. Specific and efficient primers were developed for 22 genes and tested on a diverse set of 20 cDNA samples. Quantitative reverse transcription-PCR confirmed superior expression stability and lower absolute expression levels for many of these genes, including genes encoding a protein phosphatase 2A subunit, a coatomer subunit, and an ubiquitin-conjugating enzyme. The developed PCR primers or hybridization probes for the novel reference genes will enable better normalization and quantification of transcript levels in Arabidopsis in the future.

Key Points Highly parallel genomic assays have two fundamental characteristics: a highly parallel array-based read-out and an intrinsically scalable, multiplexing sample preparation. The power of highly parallel genomic assays is that they tend to follow the principle behind Moore's law: the amount of information extracted from a sample increases linearly with the number of probes on the array, whereas the overall cost of the assay tends to increase at a much slower rate. These general concepts are being applied successfully to an increasing variety of assays, including gene-expression profiling, SNP genotyping, genomic copy-number analysis, measurement of allele-specific expression levels, and methylation status. Early genomic assays, such as gene-expression profiling, relied only on sequence-specific probe hybridization to confer specificity. The next generation of assays have made use of enzymatic discrimination in addition to hybridization to increase specificity and to enable assay designs that extract more information. Data quality, reproducibility and robustness of intrinsically parallel assays that use enzymatic discrimination have been shown to be high, defying the conventional wisdom that increasing sample complexity automatically results in lower data quality. The technology of highly parallel assays is enabling a revolution in genomics that has far-reaching implications for molecular biology and human health. Increasingly, ambitious projects that aim to be more comprehensive in their approach to genomic analysis, such as the International HapMap Project, the ENCODE Project, and the Cancer Genome Atlas, are reliant on new, highly parallel assay technologies. The orders of magnitude decrease in cost and increased speed and accuracy that are provided by highly parallel assays have brought us to the dawn of a potentially revolutionary new era of discovery in human genetics that will be based on comprehensive, high-resolution genetic mapping. Such studies might require about a billion or more genotypes, and were impractical prior to the advent of the assays that are described in this Review. A few years ago, the genotyping costs for such a study would have been in the hundreds of millions of dollars. Today, the costs would be a few million dollars, with far higher data quality and completeness, and genotyping can be carried out in a few weeks instead of many years. Parallel assay systems are assisting a similar revolution in the field of DNA sequencing, and will probably enable powerful new comprehensive studies that are prohibitively costly today. Fifteen years after the first generation of microarray platforms for highly parallel genomic analysis, intrinsically parallel whole-genome approaches to genotyping, epigenetic profiling and sequencing are being developed. What are the recent key developments that promise to transform the study of human health and disease? Recent developments in highly parallel genome-wide assays are transforming the study of human health and disease. High-resolution whole-genome association studies of complex diseases are finally being undertaken after much hypothesizing about their merit for finding disease loci. The availability of inexpensive high-density SNP-genotyping arrays has made this feasible. Cancer biology will also be transformed by high-resolution genomic and epigenomic analysis. In the future, most cancers might be staged by high-resolution molecular profiling rather than by gross cytological analysis. Here, we describe the key developments that enable highly parallel genomic assays.