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After obtaining the raw measurements as gene copies per litre using RT-qPCR, a normalisation process is required prior to reporting the data as RNA copies per person. This is because the concentration of viral RNA in wastewater is affected by both the population of the catchment area at each waterworks, as well as the amount of flow into the works. For example, an area with heavy rainfall will have high volumes of fluid flow, which will dilute RNA values. Therefore, parameters such as the flow volume of wastewater and population size are used to overcome this bias. Unfortunately, the flow data are not always accessible for all sites. Three methods were developed by Biomathematics and Statistics Scotland (BioSS) to estimate the flow for the normalization process, depending on data availability: 1. Normalisation using ammonia concentration to estimate flow; 2. Normalisation using flow historical average (when data for method 1 are not available); 3. Normalisation using predicted ammonia to estimate flow (when data for methods 1 and 2 are not available). For all methods, the normalised outputs were reported as a daily value of RNA copies per person. These methods are described separately in this protocol. For other methodologies involving SARS-CoV-2 quantification in wastewater, such as viral RNA isolation and RT-qPCR, please refer to: dx.doi.org/10.17504/protocols.io.bzv5p686 (RNA extraction from wastewater for detection of SARS-CoV-2) dx.doi.org/10.17504/protocols.io.bzwap7ae (RT-qPCR for detection of SARS-CoV-2 in wastewater)

Background The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants. Results A high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts – BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al. Nature; 544: 427–433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20–28, 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5′ and 3′ UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage. Conclusion A high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.

A high-quality, barley gene reference transcript dataset (BaRTv1.0), was used to quantify gene and transcript abundances from 22 RNA-seq experiments, covering 843 separate samples. Using the abundance data we developed a Barley Expression Database (EORNA*) to underpin a visualisation tool that displays comparative gene and transcript abundance data on demand as transcripts per million (TPM) across all samples and all the genes. EORNA provides gene and transcript models for all of the transcripts contained in BaRTV1.0, and these can be conveniently identified through either BaRT or HORVU gene names, or by direct BLAST of query sequences. Browsing the quantification data reveals cultivar, tissue and condition specific gene expression and shows changes in the proportions of individual transcripts that have arisen via alternative splicing. TPM values can be easily extracted to allow users to determine the statistical significance of observed transcript abundance variation among samples or perform meta analyses on multiple RNA-seq experiments. * Eòrna is the Scottish Gaelic word for Barley., Measurement(s) gene expression Technology Type(s) transcription profiling assay Factor Type(s) Genotype • Abiotic Stress • Developmental stage • Tissue • Biotic stress Sample Characteristic - Organism Hordeum vulgare Sample Characteristic - Environment sodium chloride salt • drought • increased temperature • decreased temperature Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13643387

A high-quality, barley gene reference transcript dataset (BaRTv1.0), was used to quantify gene and transcript abundances from 22 RNA-seq experiments, covering 843 separate samples. Using the abundance data we developed a Barley Expression Database (EoRNA* – Expression of RNA) to underpin a visualisation tool that displays comparative gene and transcript abundance data on demand as transcripts per million (TPM) across all samples and all the genes. EoRNA provides gene and transcript models for all of the transcripts contained in BaRTV1.0, and these can be conveniently identified through either BaRT or HORVU gene names, or by direct BLAST of query sequences. Browsing the quantification data reveals cultivar, tissue and condition specific gene expression and shows changes in the proportions of individual transcripts that have arisen via alternative splicing. TPM values can be easily extracted to allow users to determine the statistical significance of observed transcript abundance variation among samples or perform meta analyses on multiple RNA-seq experiments. * Eòrna is the Scottish Gaelic word for Barley

Background Prolonged over-consumption of a high-fat diet (HFD) commonly leads to obesity and insulin resistance. However, even 3 days of HFD consumption has been linked to inflammation within the key homeostatic brain region, the hypothalamus. Methods Mice were fed either a low-fat diet (LFD) or HFD containing 10% or 60% (Kcal) respectively from fat for 3 days. Mice were weighed, food intake measured and glucose tolerance calculated using intraperitoneal glucose tolerance tests (IPGTT). Proteomic analysis was carried out to determine if hypothalamic proteins were changed by a HFD. The direct effects of dietary fatty acids on mitochondrial morphology and on one of the proteins most changed by a HFD, dihydropyrimidinase-related protein 2 (DRP-2) a microtubule-associated protein which regulates microtubule dynamics, were also tested in mHypoE-N42 (N42) neuronal cells challenged with palmitic acid (PA) and oleic acid (OA). Results Mice on the HFD, as expected, showed increased adiposity and glucose intolerance. Hypothalamic proteomic analysis revealed changes in 104 spots after 3 days on HFD, which, when identified by LC/MS/MS, were found to represent 78 proteins mainly associated with cytoskeleton and synaptic plasticity, stress response, glucose metabolism and mitochondrial function. Over half of the changed proteins have also been reported to be changed in neurodegenerative conditions such as Alzheimer’s disease. Also,in N42 neurons mitochondrial morphology and DRP-2 levels were altered by PA but not by OA. Conclusion These results demonstrate that within 3 days, there is a relatively large effect of HFD on the hypothalamic proteome indicative of cellular stress, altered synaptic plasticity and mitochondrial function, but not inflammation. Changes in N42 cells show an effect of PA but not OA on DRP-2 and on mitochondrial morphology indicating that long-chain saturated fatty acids damage neuronal function. Electronic supplementary material The online version of this article (10.1186/s12986-019-0352-9) contains supplementary material, which is available to authorized users.

Additional file 2: Figure S1. 3 Pass Star alignment details. Figure S2. GMAP parameter options to align the 22,651 Haruna Nijo full-length cDNAs to the barley genome. Figure S3. Optimal StringTie assembly. Figure S4. Transdecoder annotation and filtering short transcripts. Figure S5. Examples of significant alternative transcript switches between developing inflorescence (INF1) and leaf (LEA) samples. Figure S6. Pipeline describing the algorithm to compare HR-RT-PCR and RNA-seq alternatively spliced transcript proportions and correlations.

Assembly of the barley genome and extensive use of RNA-seq has resulted in an abundance of gene expression data and the recognition of wide-scale production of alternatively spliced transcripts. Here, we describe in detail a high-resolution reverse transcription-PCR based panel (HR RT-PCR) that confirms the accuracy of alternatively spliced transcripts from RNA-seq and allows quantification of changes in the proportion of splice isoforms between different experimental conditions, time points, tissues, genotypes, ecotypes, and treatments. By validating a selection of barley genes, use of the panel gives confidence or otherwise to the genome-wide global changes in alternatively spliced transcripts reported by RNA-seq. This simple assay can readily be applied to perform detailed transcript isoform analysis for any gene in any species.

Assembly of the barley genome and extensive use of RNA-seq has resulted in an abundance of gene expression data and the recognition of wide-scale production of alternatively spliced transcripts. Here, we describe in detail a high-resolution reverse transcription-PCR based panel (HR RT-PCR) that confirms the accuracy of alternatively spliced transcripts from RNA-seq and allows quantification of changes in the proportion of splice isoforms between different experimental conditions, time points, tissues, genotypes, ecotypes, and treatments. By validating a selection of barley genes, use of the panel gives confidence or otherwise to the genome-wide global changes in alternatively spliced transcripts reported by RNA-seq. This simple assay can readily be applied to perform detailed transcript isoform analysis for any gene in any species.

Dietary fibers (DF) can prevent obesity in rodents fed a high-fat diet (HFD). Their mode of action is not fully elucidated, but the gut microbiota have been implicated. This study aimed to identify the effects of seven dietary fibers (barley beta-glucan, apple pectin, inulin, inulin acetate ester, inulin propionate ester, inulin butyrate ester or a combination of inulin propionate ester and inulin butyrate ester) effective in preventing diet-induced obesity and links to differences in cecal bacteria and host gene expression. Mice (n = 12) were fed either a low-fat diet (LFD), HFD or a HFD supplemented with the DFs, barley beta-glucan, apple pectin, inulin, inulin acetate ester, inulin propionate ester, inulin butyrate ester or a combination of inulin propionate ester and inulin butyrate ester for 8 weeks. Cecal bacteria were determined by Illumina MiSeq sequencing of 16S rRNA gene amplicons. Host responses, body composition, metabolic markers and gene transcription (cecum and liver) were assessed post intervention. HFD mice showed increased adiposity, while all of the DFs prevented weight gain. DF specific differences in cecal bacteria were observed. Results indicate that diverse DFs prevent weight gain on a HFD, despite giving rise to different cecal bacteria profiles. Conversely, common host responses to dietary fiber observed are predicted to be important in improving barrier function and genome stability in the gut, maintaining energy homeostasis and reducing HFD induced inflammatory responses in the liver.

Background Energy homeostasis is regulated by the hypothalamus but fails when animals are fed a high-fat diet (HFD), and leptin insensitivity and obesity develops. To elucidate the possible mechanisms underlying these effects, a microarray-based transcriptomics approach was used to identify novel genes regulated by HFD and leptin in the mouse hypothalamus. Results Mouse global array data identified serpinA3N as a novel gene highly upregulated by both a HFD and leptin challenge. In situ hybridisation showed serpinA3N expression upregulation by HFD and leptin in all major hypothalamic nuclei in agreement with transcriptomic gene expression data. Immunohistochemistry and studies in the hypothalamic clonal neuronal cell line, mHypoE-N42 (N42), confirmed that alpha 1-antichymotrypsin (α1AC), the protein encoded by serpinA3, is localised to neurons and revealed that it is secreted into the media. SerpinA3N expression in N42 neurons is upregulated by palmitic acid and by leptin, together with IL-6 and TNFα, and all three genes are downregulated by the anti-inflammatory monounsaturated fat, oleic acid. Additionally, palmitate upregulation of serpinA3 in N42 neurons is blocked by the NFκB inhibitor, BAY11, and the upregulation of serpinA3N expression in the hypothalamus by HFD is blunted in IL-1 receptor 1 knockout (IL-1R1−/−) mice. Conclusions These data demonstrate that serpinA3 expression is implicated in nutritionally mediated hypothalamic inflammation LMW, CG, ACM, EB, AM, BdR, MVB, MM and C-DM were supported by a project grant from NuGO; LMW, AM and FHM were supported by a project support grant from the British Society for Neuroendocrinology; DS was supported by a SULSA studentship; FHM was supported by a EASTBIO DTP BBSRC studentship; LMW, CG, ACM, EB, BdR, C-DM, FMC, PN, JED and NH were funded by the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS). AT and KC were funded by the German Ministry of Research and Education (Ref. No: 0315087). HMR was supported by the Irish Department of Agriculture, Food and Marine ImmunoMet Programme (14/F/828). FCM and HMR were supported by Science Foundation Ireland Principal Investigator Programme (11/PI/1119). RN and CD were supported by grants from Ministerio de Economia y Competitividad (CD: BFU2011-29102; RN: BFU2012-35255), Xunta de Galicia (RN: EM 2012/039 and 2012-CP069). Centro de Investigación Biomédica en Red (CIBER) de Fisiopatología de la Obesidad y Nutrición (CIBERobn). CIBERobn is an initiative of the Instituto de Salud Carlos III (ISCIII) of Spain which is supported by FEDER funds. The research leading to these results has also received funding from the European Community’s Seventh Framework Programme under the following grants: no 245009: NeuroFAST to CD and ERC StG-2011-OBESITY53-281408 to RN SI

In biomedical research, weighted logrank tests are frequently applied to compare two samples of randomly right censored survival times. We address the question how to combine a number of weighted logrank statistics to achieve good power of the corresponding survival test for a whole linear space or cone of alternatives, which are given by hazard rates. This leads to a new class of semiparametric projection tests that are motivated by likelihood ratio tests for an asymptotic model. We show that these tests can be carried out as permutation tests and discuss their asymptotic properties. A simulation study together with the analysis of a classical data set illustrates the advantages.

Colon cancers are characterized by aberrant gene expression signatures associated with disease initiation and progression. Identification of aberrant gene expression associated with colon carcinogenesis has increased significantly with application of gene array technologies. Downstream processing of these data has been hindered by the lack of robust multiplexed gene quantitative technologies facilitating study of the identified multiple gene targets. The GenomeLab Genetic Analysis System presents a novel technology platform for quantitative multiplexed gene expression analysis. This report describes the custom design of a GeXP multiplexed assay used to assess expression profiles of 14 inflammatory gene targets in normal, polyp, and tumor tissue. Characteristic normal, polyp, and tumor tissue gene expression profiles were obtained. Statistical analysis confirmed comparable relative quantitation of gene expression using the GeXP, macroarray, and single-plex real-time polymerase chain reaction assays. GeXP assays may be usefully applied in clinical and regulatory studies of multiple gene targets. This system permits custom-design options for relative quantification of multiple gene target expression, simultaneously in a single reaction, using nanogram quantities of total RNA template. The system provides an approach to advance the study of multiple targets identified from gene array analysis with potential for characterizing gene expression signatures in clinical diagnostics.

“ Roseburia inulinivorans ” is an anaerobic polysaccharide-utilizing firmicute bacterium from the human colon that was identified as a producer of butyric acid during growth on glucose, starch, or inulin. R. inulinivorans A2-194 is also able to grow on the host-derived sugar fucose, following a lag period, producing propionate and propanol as additional fermentation products. A shotgun genomic microarray was constructed and used to investigate the switch in gene expression that is involved in changing from glucose to fucose utilization. This revealed a set of genes coding for fucose utilization, propanediol utilization, and the formation of propionate and propanol that are up-regulated during growth on fucose. These include homologues of genes that are implicated in polyhedral body formation in Salmonella enterica . Dehydration of the intermediate 1,2-propanediol involves an enzyme belonging to the new B 12 -independent glycerol dehydratase family, in contrast to S. enterica , which relies on a B 12 -dependent enzyme. A typical gram-positive agr -type quorum-sensing system was also up-regulated in R. inulinivorans during growth on fucose. Despite the lack of genome sequence information for this commensal bacterium, microarray analysis has provided a powerful tool for obtaining new information on its metabolic capabilities.

There is growing interest in the potential health benefits of diets that involve regular periods of fasting. While animal studies have provided compelling evidence that feeding patterns such as alternate-day fasting can increase longevity and reduce incidence of many chronic diseases, the evidence from human studies is much more limited and equivocal. Additionally, although several candidate processes have been proposed to contribute to the health benefits observed in animals, the precise molecular mechanisms responsible remain to be elucidated. The study described here examined the effects of an extended fast on gene transcript profiles in peripheral blood mononuclear cells from ten apparently healthy subjects, comparing transcript profiles after an overnight fast, sampled on four occasions at weekly intervals, with those observed on a single occasion after a further 24 h of fasting. Analysis of the overnight fasted data revealed marked inter-individual differences, some of which were associated with parameters such as gender and subject body mass. For example, a striking positive association between body mass index and the expression of genes regulated by type 1 interferon was observed. Relatively subtle changes were observed following the extended fast. Nonetheless, the pattern of changes was consistent with stimulation of fatty acid oxidation, alterations in cell cycling and apoptosis and decreased expression of key pro-inflammatory genes. Stimulation of fatty acid oxidation is an expected response, most likely in all tissues, to fasting. The other processes highlighted provide indications of potential mechanisms that could contribute to the putative beneficial effects of intermittent fasting in humans.

SUMMARY Many small mammals respond to seasonal changes in photoperiod by altering body mass and adiposity. These animals may provide valuable models for understanding the regulation of energy balance. Here, we present data on the field vole (Microtus agrestis) – a previously uncharacterised example of photoperiod-induced changes in body mass. We examined the effect of increased day length on body mass, food intake, apparent digestive efficiency,body composition, de novo lipogenesis and fatty acid composition of adipose tissue in cold-acclimated (8°C) male field voles by transferring them from a short (SD, 8 h:16 h L:D) to long day photoperiod (LD, 16 h:8 h L:D). During the first 4 weeks of exposure to LD, voles underwent a substantial increase in body mass, after which the average difference between body masses of LD and SD voles stabilized at 7.5 g. This 24.8% increase in body mass reflected significant increases in absolute amounts of all body components, including dry fat mass, dry lean mass and body water mass. After correcting body composition and organ morphology data for the differences in body mass, only gonads (testes and seminal vesicles) were enlarged due to photoperiod treatment. To meet energetic demands of deposition and maintenance of extra tissue, voles adjusted their food intake to an increasing body mass and improved their apparent digestive efficiency. Consequently, although mass-corrected food intake did not differ between the photoperiod groups, the LD voles undergoing body mass increase assimilated on average 8.4 kJ day-1 more than animals maintained in SD. The majority(73–77%) of the fat accumulated as adipose tissue had dietary origin. The rate of de novo lipogenesis and fatty acid composition of adipose tissue were not affected by photoperiod. The most important characteristics of the photoperiodic regulation of energy balance in the field vole are the clear delineation between phases where animals regulate body mass at two different levels and the rate at which animals are able to switch between different levels of energy homeostasis. Our data indicate that the field vole may provide an attractive novel animal model for investigation of the regulation of body mass and energy homeostasis at both organism and molecular levels.

Background: The thyroid hormone triiodothyronine (T3) is known to affect energy balance. Recent evidence points to an action of T3 in the hypothalamus, a key area of the brain involved in energy homeostasis, but the components and mechanisms are far from understood. The aim of this study was to identify components in the hypothalamus that may be involved in the action of T3 on energy balance regulatory mechanisms. Methods: Sprague Dawley rats were made hypothyroid by giving 0.025% methimazole (MMI) in their drinking water for 22 days. On day 21, half the MMI-treated rats received a saline injection, whereas the others were injected with T3. Food intake and body weight measurements were taken daily. Body composition was determined by magnetic resonance imaging, gene expression was analyzed by in situ hybridization, and T3-induced gene expression was determined by microarray analysis of MMI-treated compared to MMI-T3-injected hypothalamic RNA. Results: Post mortem serum thyroid hormone levels showed that MMI treatment decreased circulating thyroid hormones and increased thyrotropin (TSH). MMI treatment decreased food intake and body weight. Body composition analysis revealed reduced lean and fat mass in thyroidectomized rats from day 14 of the experiment. MMI treatment caused a decrease in circulating triglyceride concentrations, an increase in nonesterified fatty acids, and decreased insulin levels. A glucose tolerance test showed impaired glucose clearance in the thyroidectomized animals. In the brain, in situ hybridization revealed marked changes in gene expression, including genes such as Mct8, a thyroid hormone transporter, and Agrp, a key component in energy balance regulation. Microarray analysis revealed 110 genes to be up- or downregulated with T3 treatment (±1.3-fold change, p

It is shown that in the case of heterogenous censoring distributions Studentized survival tests can be carried out as conditional permutation tests given the order statistics and their censoring status. The result is based on a conditional central limit theorem for permutation statistics. It holds for linear test statistics as well as for sup-statistics. The procedure works under one of the following general circumstances for the two-sample problem: the unbalanced sample size case, highly censored data, certain non-convergent weight functions or under alternatives. For instance, the two-sample log rank test can be carried out asymptotically as a conditional test if the relative amount of uncensored observations vanishes asymptotically as long as the number of uncensored observations becomes infinite. Similar results hold whenever the sample sizes n 1 and n 2 are unbalanced in the sense that n 1 /n 2 → 0 and n 1 → ∞ hold.

Mild dietary zinc deprivation in humans and rodents has little effect on blood plasma zinc levels, and yet cellular consequences of zinc depletion can be detected in vascular and other tissues. We proposed that a zinc-regulated humoral factor might mediate the effects of zinc deprivation. Using a novel approach, primary rat vascular smooth muscle cells (VSMCs) were treated with plasma from zinc-deficient (1 mg Zn/kg) or zinc-adequate (35 mg Zn/kg, pair-fed) adult male rats, and zinc levels were manipulated to distinguish direct and indirect effects of plasma zinc. Gene expression changes were analyzed by microarray and qPCR, and incubation of VSMCs with blood plasma from zinc-deficient rats strongly changed the expression of2500 genes, compared to incubation of cells with zinc-adequate rat plasma. We demonstrated that this effect was caused by a low-molecular-weight (∼2-kDa) zinc-regulated humoral factor but that changes in gene expression were mostly reversed by adding zinc back to zinc-deficient plasma. Strongly regulated genes were overrepresented in pathways associated with immune function and development. We conclude that zinc deficiency induces the production of a low-molecular-weight humoral factor whose influence on VSMC gene expression is blocked by plasma zinc. This factor is therefore under dual control by zinc.

Inflammatory disorders of the bowel and colon cancer are associated with elevated indices of oxidative stress. Analogous elevations in markers of oxidative stress and loss of cell-membrane integrity are also observed in the colons of rats deficient in vitamin E (D-α-tocopherol), the major lipid-soluble antioxidant in biological systems. The causal relationship between colon pathologies associated with oxidative stress and dietary deficiency in antioxidant vitamins such as vitamin E is still uncertain. Investigation of potential mechanisms by which lack of dietary vitamin E may lead to clinically relevant pathological changes in colon tissue was conducted using gene expression profiling strategies on vitamin E-sufficient and -deficient rats. Morphological changes and increased indices of lipid peroxidation were linked to vitamin E deficiency. These changes in colon tissue are potentially important in disease pathogenesis of the colon linked with oxidative stress or other direct consequences of inadequate levels of vitamin E.

The objective of this study was to characterize differences in the secretome of human omental compared with subcutaneous adipose tissue using global gene expression profiling. Gene expression was measured using Affymetrix microarrays (Affymetrix, Santa Clara, CA) in subcutaneous and omental adipose tissue in two independent experiments (n = 5 and n = 3 independent subjects; n = 16 arrays in total, 2 for each subject). Predictive bioinformatic algorithms were employed to identify secreted proteins. Microarray analysis identified 22 gene probe sets whose expression was significantly different with a fold change (FC) greater than 5 in expression in both experiments between omental and subcutaneous adipose tissue. Using bioinformatic predictive programs 11 of these 22 probe sets potentially coded for secreted proteins. Pathway network analysis of the secreted proteins showed that three of the proteins are part of a common pathway network. These proteins gremlin 1 (GREM1), pleiotrophin (PTN), and secretory leukocyte peptidase inhibitor (SLPI) are expressed respectively 43×, 23×, and 5× in omental adipose tissue relative to subcutaneous adipose tissue as determined by real-time PCR. The presence of GREM1, PTN, and SLPI protein in human adipose tissue was confirmed by western blotting. All three proteins are expressed in the human Simpson-Golabi-Behmel syndrome (SGBS) preadipocyte cell line. The expression of GREM1, PTN, and SLPI changed with the differentiation of the preadipocytes into mature adipocytes. Gene expression coupled with predictive bioinformatic algorithms have identified several genes coding for secreted proteins which are expressed differently in omental adipose tissue compared to subcutaneous adipose tissue proving a valid alternative approach to help further define the adipocyte secretome.

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially.

Despite the economic importance of grasses as food, feed, and energy crops, little is known about the genes that control their cell wall synthesis, assembly, and remodelling. Here a detailed transcriptome analysis that allowed the identification of genes involved in grass cell wall biogenesis is provided. Differential gene expression profiling, using maize oligonucleotide arrays, was used to identify genes differentially expressed between an elongating internode, containing cells exhibiting primary cell wall synthesis, and an internode that had just ceased elongation and in which many cells were depositing secondary cell wall material. This is one of only a few studies specifically aimed at the identification of cell wall-related genes in grasses. Analysis identified new candidate genes for a role in primary and secondary cell wall biogenesis in grasses. The results suggest that many proteins involved in cell wall processes during normal development are also recruited during defence-related cell wall remodelling events. This work provides a platform for studies in which candidate genes will be functionally tested for involvement in cell wall-related processes, increasing our knowledge of cell wall biogenesis and its regulation in grasses. Since several grasses are currently being developed as lignocellulosic feedstocks for biofuel production, this improved understanding of grass cell wall biogenesis is timely, as it will facilitate the manipulation of traits favourable for sustainable food and biofuel production.

The integration of multiple high-dimensional data sets (omics data) has been a very active but challenging area of bioinformatics research in recent years. Various adaptations of non-standard multivariate statistical tools have been suggested that allow to analyze and visualize such data sets simultaneously. However, these methods typically can deal with two data sets only, whereas systems biology experiments often generate larger numbers of high-dimensional data sets. For this reason, we suggest an explorative analysis of similarity between data sets as an initial analysis steps. This analysis is based on the RV coefficient, a matrix correlation, that can be interpreted as a generalization of the squared correlation from two single variables to two sets of variables. It has been shown before however that the high-dimensionality of the data introduces substantial bias to the RV.We therefore introduce an alternative version, the adjusted RV, which is unbiased in the case of independent data sets. We can also show that in many situations, particularly for very high-dimensional data sets, the adjusted RV is a better estimator than previously RV versions in terms of the mean square error and the power of the independence test based on it.We demonstrate the usefulness of the adjusted RV by applying it to data set of 19 different multivariate data sets from a systems biology experiment. The pairwise RV values between the data sets define a similarity matrix that we can use as an input to a hierarchical clustering or a multi-dimensional scaling. We show that this reveals biological meaningful subgroups of data sets in our study.

Roseburia inulinivorans is a recently identified motile representative of the Firmicutes that contributes to butyrate formation from a variety of dietary polysaccharide substrates in the human large intestine. Microarray analysis was used here to investigate substrate-driven gene-expression changes in R. inulinivorans A2-194. A cluster of fructo-oligosaccharide/inulin utilization genes induced during growth on inulin included one encoding a β-fructofuranosidase protein that was prominent in the proteome of inulin-grown cells. This cluster also included a 6-phosphofructokinase and an ABC transport system, whereas a distinct inulin-induced 1-phosphofructokinase was linked to a fructose-specific phosphoenolpyruvate-dependent sugar phosphotransferase system (PTS II transport enzyme). Real-time PCR analysis showed that the β-fructofuranosidase and adjacent ABC transport protein showed greatest induction during growth on inulin, whereas the 1-phosphofructokinase enzyme and linked sugar phosphotransferase transport system were most strongly up-regulated during growth on fructose, indicating that these two clusters play distinct roles in the use of inulin. The R. inulinivorans β-fructofuranosidase was overexpressed in Escherichia coli and shown to hydrolyze fructans ranging from inulin down to sucrose, with greatest activity on fructo-oligosaccharides. Genes induced on starch included the major extracellular α-amylase and two distinct α-glucanotransferases together with a gene encoding a flagellin protein. The latter response may be concerned with improving bacterial access to insoluble starch particles.

MOTIVATION Transcriptomic studies using microarray technology have become a standard tool in life sciences in the last decade. Nevertheless the cost of these experiments remains high and forces scientists to work with small sample sizes at the expense of statistical power. In many cases, little or no prior knowledge on the underlying variability is available, which would allow an accurate estimation of the number of samples (microarrays) required to answer a particular biological question of interest. We investigate sequential methods, also called group sequential or adaptive designs in the context of clinical trials, for microarray analysis. Through interim analyses at different stages of the experiment and application of a stopping rule a decision can be made as to whether more samples should be studied or whether the experiment has yielded enough information already. RESULTS The high dimensionality of microarray data facilitates the sequential approach. Since thousands of genes simultaneously contribute to the stopping decision, the marginal distribution of any single gene is nearly independent of the global stopping rule. For this reason, the interim analysis does not seriously bias the final p-values. We propose a meta-analysis approach to combining the results of the interim analyses at different stages. We consider stopping rules that are either based on the estimated number of true positives or on a sensitivity estimate and particularly discuss the difficulty of estimating the latter. We study this sequential method in an extensive simulation study and also apply it to several real data sets. The results show that applying sequential methods can reduce the number of microarrays without substantial loss of power. An R-package SequentialMA implementing the approach is available from the authors.

Background Early microbial colonization of the gut reduces the incidence of infectious, inflammatory and autoimmune diseases. Recent population studies reveal that childhood hygiene is a significant risk factor for development of inflammatory bowel disease, thereby reinforcing the hygiene hypothesis and the potential importance of microbial colonization during early life. The extent to which early-life environment impacts on microbial diversity of the adult gut and subsequent immune processes has not been comprehensively investigated thus far. We addressed this important question using the pig as a model to evaluate the impact of early-life environment on microbe/host gut interactions during development. Results Genetically-related piglets were housed in either indoor or outdoor environments or in experimental isolators. Analysis of over 3,000 16S rRNA sequences revealed major differences in mucosa-adherent microbial diversity in the ileum of adult pigs attributable to differences in early-life environment. Pigs housed in a natural outdoor environment showed a dominance of Firmicutes, in particular Lactobacillus, whereas animals housed in a hygienic indoor environment had reduced Lactobacillus and higher numbers of potentially pathogenic phylotypes. Our analysis revealed a strong negative correlation between the abundance of Firmicutes and pathogenic bacterial populations in the gut. These differences were exaggerated in animals housed in experimental isolators. Affymetrix microarray technology and Real-time Polymerase Chain Reaction revealed significant gut-specific gene responses also related to early-life environment. Significantly, indoor-housed pigs displayed increased expression of Type 1 interferon genes, Major Histocompatibility Complex class I and several chemokines. Gene Ontology and pathway analysis further confirmed these results. Conclusion Early-life environment significantly affects both microbial composition of the adult gut and mucosal innate immune function. We observed that a microbiota dominated by lactobacilli may function to maintain mucosal immune homeostasis and limit pathogen colonization.

Motivation: With the proliferation of microarray experiments and their availability in the public domain, the use of meta-analysis methods to combine results from different studies increases. In microarray experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably increase the statistical power and give more accurate results. Results: A moderated effect size combination method was proposed and compared with other meta-analysis approaches. All methods were applied to real publicly available datasets on prostate cancer, and were compared in an extensive simulation study for various amounts of inter-study variability. Although the proposed moderated effect size combination improved already existing effect size approaches, the P-value combination was found to provide a better sensitivity and a better gene ranking than the other meta-analysis methods, while effect size methods were more conservative. Availability: An R package metaMA is available on the CRAN. Contact: guillemette.marot@jouy.inra.fr

The mechanism(s) involved in the regulation of the seasonal-appropriate body weight of the Siberian hamster are currently unknown. We have identified photoperiodically regulated genes including VGF in a sub-region of the arcuate nucleus termed the dorsomedial posterior arcuate (dmpARC). Gene expression changes in this nucleus so far account for a significant number of those reported as photoperiodically regulated and are therefore likely to contribute to seasonal physiological responses of the hamsters. The present study aimed to identify additional genes expressed in the dmpARC regulated by photoperiod that could be involved in regulating the activity of this nucleus with respect to seasonal physiology of the Siberian hamster. Using laser capture microdissection coupled with a microarray analysis and a candidate gene approach, we have identified several photoperiodically regulated genes in the dmpARC that are known to have roles in secretory and intracellular signalling pathways. These include secretogranin (sg) III and SgVI (secretory pathway), melanocortin 3 receptor (MC3-R) and serotonin (5-HT) receptors 2A and 7 (signalling pathway), all of which increase in expression under a short photoperiod. The spatial relationship between receptor signalling and potential secretory pathways was investigated by dual in situ hybridisation, which revealed that 5-HT2A and 5-HT7 receptors are expressed in neurones expressing VGF mRNA and that a sub-population (approximately 40%) of these neurones express MC3-R. These gene expression changes in dmpARC neurones may reflect the functional requirement of these neurones for seasonal physiological responses of the hamster.

NuGO, the European Nutrigenomics Organization, utilizes 31 powerful computers for, e.g., data storage and analysis. These so-called black boxes (NBXses) are located at the sites of different partners. NuGO decided to use GenePattern as the preferred genomic analysis tool on each NBX. To handle the custom made Affymetrix NuGO arrays, new NuGO modules are added to GenePattern. These NuGO modules execute the latest Bioconductor version ensuring up-to-date annotations and access to the latest scientific developments. The following GenePattern modules are provided by NuGO: NuGOArrayQualityAnalysis for comprehensive quality control, NuGOExpressionFileCreator for import and normalization of data, LimmaAnalysis for identification of differentially expressed genes, TopGoAnalysis for calculation of GO enrichment, and GetResultForGo for retrieval of information on genes associated with specific GO terms. All together, these NuGO modules allow comprehensive, up-to-date, and user friendly analysis of Affymetrix data. A special feature of the NuGO modules is that for analysis they allow the use of either the standard Affymetrix or the MBNI custom CDF-files, which remap probes based on current knowledge. In both cases a .chip-file is created to enable GSEA analysis. The NuGO GenePattern installations are distributed as binary Ubuntu (.deb) packages via the NuGO repository.

We have previously shown that cold-acclimated (8 degrees C) male field voles (Microtus agrestis) transferred from short day (SD, 8 h light) to long day (LD, 16 h light) photoperiod exhibit an increase in body mass lasting 4 weeks, after which they stabilise at a new plateau approximately 7.5 g (24.8%) higher than animals maintained in SD. By infusing voles with exogenous leptin, we have also demonstrated that SD voles respond to the hormone by reducing body mass and food intake, whereas LD animals increasing body mass are resistant to leptin treatment. In the present study, we investigated whether seasonal changes in body mass could be linked to modulation of the leptin signal by suppressor of cytokine signalling-3 (SOCS3). We used in situ hybridisation to examine hypothalamic arcuate nucleus (ARC) expression of SOCS3, neuropeptide Y (NPY), agouti-related peptide (AgRP), pro-opiomelanocortin (POMC) and cocaine- and amphetamine-regulated transcript (CART) genes in 90 voles exposed to either SD or LD for up to 11 weeks. LD voles increasing body mass had significantly higher levels of SOCS3 mRNA than SD or LD voles with a stable body mass. There were no associated changes in expression of NPY, AgRP, POMC and CART genes. These results suggest that voles that regulate body mass at either the lower (SD) or upper (LD) plateau remain sensitive to leptin action, whereas SOCS3-mediated leptin resistance is a short-term mechanism that enables animals to move between the stable body mass plateaus. Our data provide evidence that expression of SOCS3 in the ARC is involved in the modulation of the strength of the leptin signal to facilitate seasonal cycles in body mass and adiposity.

Cancers exhibit abnormal molecular signatures associated with disease initiation and progression. Molecular signatures could improve cancer screening, detection, drug development and selection of appropriate drug therapies for individual patients. Typically only very small amounts of tissue are available from patients for analysis and biopsy samples exhibit broad heterogeneity that cannot be captured using a single marker. This report details application of an in-house custom designed GenomeLab System multiplex gene expression assay, the hCellMarkerPlex, to assess predictive gene signatures of normal, adenomatous polyp and carcinoma colon tissue using archived tissue bank material. The hCellMarkerPlex incorporates twenty-one gene markers: epithelial (EZR, KRT18, NOX1, SLC9A2), proliferation (PCNA, CCND1, MS4A12), differentiation (B4GANLT2, CDX1, CDX2), apoptotic (CASP3, NOX1, NTN1), fibroblast (FSP1, COL1A1), structural (ACTG2, CNN1, DES), gene transcription (HDAC1), stem cell (LGR5), endothelial (VWF) and mucin production (MUC2). Gene signatures distinguished normal, adenomatous polyp and carcinoma. Individual gene targets significantly contributing to molecular tissue types, classifier genes, were further characterised using real-time PCR, in-situ hybridisation and immunohistochemistry revealing aberrant epithelial expression of MS4A12, LGR5 CDX2, NOX1 and SLC9A2 prior to development of carcinoma. Identified gene signatures identify aberrant epithelial expression of genes prior to cancer development using in-house custom designed gene expression multiplex assays. This approach may be used to assist in objective classification of disease initiation, staging, progression and therapeutic responses using biopsy material.

Microarrays allow the simultaneous measurement of the expression levels of thousands of genes. This unique data structure has inspired a completely new area of research in statistics and bioinformatics. The objective of the present chapter is to review some of the main statistical tools used in this context. We will mainly focus on low-level preprocessing steps: image analysis, data transformation, normalization, and multiple testing for differential expression. The high-level inference of genetic regulatory interactions from preprocessed microarray data will be covered in Chapters 8 and 9.

We consider a semiparametric competing risk model given by k independent survival times. The paper offers an asymptotic treatment of tests for the semiparametric null hypothesis of equality of the underlying risks. It turns out that modified rank tests are asymptotically efficient for certain semiparametric submodels, where the baseline hazard is a nuisance parameter. In addition, the asymptotic relative efficiency of the present tests is derived. A comparison of asymptotic power functions can then be used to classify various tests proposed earlier in the literature. For instance a chi-square type test is efficient for proportional hazards. Data driven tests of likelihood ratio type are proposed for cones of alternatives. We will consider certain stochastically increasing alternatives as a special example. The paper shows how the concept of local asymptotic normality of Le Cam works for hazard oriented models.

BackgroundAcquisition of the intestinal microbiota in early life corresponds with the development of the mucosal immune system. Recent work on caesarean-delivered infants revealed that early microbial composition is influenced by birthing method and environment. Furthermore, we have confirmed that early-life environment strongly influences both the adult gut microbiota and development of the gut immune system. Here, we address the impact of limiting microbial exposure after initial colonization on the development of adult gut immunity.Methodology/principal findingsPiglets were born in indoor or outdoor rearing units, allowing natural colonization in the immediate period after birth, prior to transfer to high-health status isolators. Strikingly, gut closure and morphological development were strongly affected by isolator-rearing, independent of indoor or outdoor origins of piglets. Isolator-reared animals showed extensive vacuolation and disorganization of the gut epithelium, inferring that normal gut closure requires maturation factors present in maternal milk. Although morphological maturation and gut closure were delayed in isolator-reared animals, these hard-wired events occurred later in development. Type I IFN, IL-22, IL-23 and Th17 pathways were increased in indoor-isolator compared to outdoor-isolator animals during early life, indicating greater immune activation in pigs originating from indoor environments reflecting differences in the early microbiota. This difference was less apparent later in development due to enhanced immune activation and convergence of the microbiota in all isolator-reared animals. This correlated with elevation of Type I IFN pathways in both groups, although T cell pathways were still more affected in indoor-reared animals.Conclusions/significanceEnvironmental factors, in particular microbial exposure, influence expression of a large number of immune-related genes. However, the homeostatic effects of microbial colonization in outdoor environments require sustained microbial exposure throughout development. Gut development in high-hygiene environments negatively impacts on normal succession of the gut microbiota and promotes innate immune activation which may impair immune homeostasis.