A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological Information

Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific gene IDs that cannot handle genomics data from other species. We developed a species-independent method to search pathways databases to analyse microarray data. Three PERL scripts were developed that use the names of the genes on the microarray. (1) Add synonyms of gene names by searching the Gene Ontology (GO) database. (2) Search the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database for pathway information using this GO-enriched gene list. (3) Combine the pathway data with the microarray data and visualize the results using color codes indicating regulation. To demonstrate the power of the method, we used a previously reported chicken microarray experiment investigating line-specific reactions to Salmonella infection as an example

Genomic prediction of dry matter intake in dairy cattle from an international data set consisting of research herds in Europe, North America, and Australasia

peer-reviewedFinancial support for gDMI from CRV (Arnhem, the Netherlands), ICBF (Cork, Ireland), CONAFE (Madrid, Spain), DairyCo (Warwickshire, UK) directly to the gDMI consortium, and The Natural Science and Engineering Research Council of Canada and DairyGen Council of Canadian Dairy Network (Guelph, ON, Canada) is gratefully appreciated, as well as the EU FP7 IRSES SEQSEL (Grant no. 317697).With the aim of increasing the accuracy of genomic estimated breeding values for dry matter intake (DMI) in Holstein-Friesian dairy cattle, data from 10 research herds in Europe, North America, and Australasia were combined. The DMI records were available on 10,701 parity 1 to 5 records from 6,953 cows, as well as on 1,784 growing heifers. Predicted DMI at 70 d in milk was used as the phenotype for the lactating animals, and the average DMI measured during a 60- to 70-d test period at approximately 200 d of age was used as the phenotype for the growing heifers. After editing, there were 583,375 genetic markers obtained from either actual high-density single nucleotide polymorphism (SNP) genotypes or imputed from 54,001 marker SNP genotypes. Genetic correlations between the populations were estimated using genomic REML. The accuracy of genomic prediction was evaluated for the following scenarios: (1) within-country only, by fixing the correlations among populations to zero, (2) using near-unity correlations among populations and assuming the same trait in each population, and (3) a sharing data scenario using estimated genetic correlations among populations. For these 3 scenarios, the data set was divided into 10 sub-populations stratified by progeny group of sires; 9 of these sub-populations were used (in turn) for the genomic prediction and the tenth was used for calculation of the accuracy (correlation adjusted for heritability). A fourth scenario to quantify the benefit for countries that do not record DMI was investigated (i.e., having an entire country as the validation population and excluding this country in the development of the genomic predictions). The optimal scenario, which was sharing data, resulted in a mean prediction accuracy of 0.44, ranging from 0.37 (Denmark) to 0.54 (the Netherlands). Assuming near-unity among-country genetic correlations, the mean accuracy of prediction dropped to 0.40, and the mean within-country accuracy was 0.30. If no records were available in a country, the accuracy based on the other populations ranged from 0.23 to 0.53 for the milking cows, but were only 0.03 and 0.19 for Australian and New Zealand heifers, respectively; the overall mean prediction accuracy was 0.37. Therefore, there is a benefit in collaboration, because phenotypic information for DMI from other countries can be used to augment the accuracy of genomic evaluations of individual countries.financial support for gDMI from CRV (Arnhem, the Netherlands), ICBF (Cork, Ireland), CONAFE (Madrid, Spain), DairyCo (Warwickshire, UK) directly to the gDMI consortium, and The Natural Science and Engineering Research Council of Canada and DairyGen Council of Canadian Dairy Network (Guelph, ON, Canada) is gratefully appreciated, as well as the EU FP7 IRSES SEQSEL (Grant no. 317697).financial support for gDMI from CRV (Arnhem, the Netherlands), ICBF (Cork, Ireland), CONAFE (Madrid, Spain), DairyCo (Warwickshire, UK) directly to the gDMI consortium, and The Natural Science and Engineering Research Council of Canada and DairyGen Council of Canadian Dairy Network (Guelph, ON, Canada) is gratefully appreciated, as well as the EU FP7 IRSES SEQSEL (Grant no. 317697)

Methods for interpreting lists of affected genes obstained in a DNA microarray experiment

Background - The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. Results - Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. Conclusion - It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experimen

Content and Quality of Motor Initiatives in the Support of People With Profound Intellectual and Multiple Disabilities

Motor activation is rarely integrated into the support of people with profound intellectual and multiple disabilities (PIMD), which might be the result of the limited evidence‐based knowledge in this field. Practitioners have recently been developing several motor initiatives for people with PIMD, but it remains unclear about what core elements the motor initiatives actually consist of and to what level of quality it is implemented in practice. This study aims to offer an overview and analysis of the content and quality of motor initiatives actually in use for people with PIMD. Motor initiatives were explored by asking practitioners to complete an online inventory form. Documents, expert knowledge, and observations were used to collect data about the characteristics of the motor initiatives. The quality of the motor initiatives which met our eligibility criteria, was analyzed on the basis of the level of evidence for their effectiveness. The inventory yielded 118 motor initiatives of which 17 met the eligibility criteria. We identified four motor initiatives reflecting an approach to motorically activate people with PIMD within various activities, three including power‐assisted exercises, three with aquatic exercises, two frameworks which integrated motor activities into their daily programs, two methods which included small‐scale activities, two rhythmic movement therapies, and one program including gross motor activities. We found limited indications for descriptive evidence from 17 initiatives, limited or no indications for theoretical evidence from 12 and five initiatives respectively, and none of the initiatives provided a causal level of evidence for effectiveness. A wide variety of motor initiatives is used in current practice to activate persons with PIMD, although their effectiveness is actually unproven. Science and practice should cooperate to develop an evidence‐based understanding to ensure more evidence‐based support for the motor activation of people with PIMD in the future

The potential of using hair cortisol to measure chronic stress in occupational healthcare; a scoping review

OBJECTIVES: Workplace-based selective prevention of mental health problems currently relies on subjective evaluation of stress complaints. Hair cortisol captures chronic stress responses and could be a promising biomarker for the early identification of mental health problems. The objective was to provide an overview of the state-of-the-art knowledge on the practical value of hair cortisol in the occupational setting. METHODS: We performed a scoping review of cross-sectional and longitudinal studies in PubMed, Embase, and PsycINFO up to November 2019 assessing the relations of hair cortisol with work-related stressors, perceived stress, and mental health outcomes in healthy workers. RESULTS: We found five longitudinal studies, of which two observed an increase in work-related stressors to be associated with higher hair cortisol, one found a relation with lower hair cortisol and one did not find a relationship. Findings of cross-sectional studies were also mixed. The one available longitudinal study regarding mental health showed that hair cortisol was not related to depressive symptoms. CONCLUSIONS: Hair cortisol measurement within occupational health research is still in its early stage and more longitudinal studies are urgently needed to clarify its relationship with work-related stressors and perceived stress before hair cortisol can be used to identify workers at risk for mental health problems

Trajectories of metabolic risk factors and biochemical markers prior to the onset of type 2 diabetes:The population-based longitudinal Doetinchem study

BACKGROUND: Risk factors often develop at young age and are maintained over time, but it is not fully understood how risk factors develop over time preceding type 2 diabetes. We examined how levels and trajectories of metabolic risk factors and biochemical markers prior to diagnosis differ between persons with and without type 2 diabetes over 15-20 years. METHODS: A total of 355 incident type 2 diabetes cases (285 self-reported, 70 with random glucose >= 11.1 mmol l(-1)) and 2130 controls were identified in a prospective cohort between 1987-2012. Risk factors were measured at 5-year intervals. Trajectories preceding case ascertainment were analysed using generalised estimating equations. RESULTS: Among participants with a 21-year follow-up period, those with type 2 diabetes had higher levels of metabolic risk factors and biochemical markers 15-20 years before case ascertainment. Subsequent trajectories were more unfavourable in participants with type 2 diabetes for body mass index (BMI), HDL cholesterol and glucose (P <0.01), and to a lesser extent for waist circumference, diastolic and systolic blood pressure, triglycerides, alanine aminotransferase, gamma glutamyltransferase, C-reactive protein, uric acid and estimated glomerular filtration rate compared with participants without type 2 diabetes. Among persons with type 2 diabetes, BMI increased by 5-8% over 15 years, whereas the increase among persons without type 2 diabetes was 0-2% (P <0.01). The observed differences in trajectories of metabolic risk factors and biochemical markers were largely attenuated after inclusion of BMI in the models. Results were similar for men and women. CONCLUSIONS: Participants with diabetes had more unfavourable levels of metabolic risk factors and biochemical markers already 15-20 years before diagnosis and worse subsequent trajectories than others. Our results highlight the need, in particular, for maintenance of a healthy weight from young adulthood onwards for diabetes prevention

Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies

Comparative Transcriptomes Profiling of Photoperiod-sensitive Male Sterile Rice Nongken 58S During the Male Sterility Transition between Short-day and Long-day

<p>Abstract</p> <p>Background</p> <p>Photoperiod-sensitive genic male sterile (PGMS) rice, Nongken 58S, was discovered in 1973. It has been widely used for the production of hybrid rice, and great achievements have been made in improving rice yields. However, the mechanism of the male sterility transition in PGMS rice remains to be determined.</p> <p>Results</p> <p>To investigate the transcriptome during the male sterility transition in PGMS rice, the transcriptome of Nongken 58S under short-day (SD) and long-day (LD) at the glume primordium differentiation and pistil/stamen primordium forming stages was compared. Seventy-three and 128 differentially expressed genes (DEGs) were identified at the glume primordium differentiation and pistil/stamen primordium forming stages, respectively. Five and 22 genes were markedly up-regulated (≥ 5-fold), and two and five genes were considerably down-regulated (≥ 5-fold) under SD during the male sterility transition. Gene ontology annotation and pathway analysis revealed that four biological processes and the circadian rhythms and the flowering pathways coordinately regulated the male sterility transition. Further quantitative PCR analysis demonstrated that the circadian rhythms of <it>OsPRR1, OsPRR37, OsGI, Hd1, OsLHY </it>and <it>OsDof </it>in leaves were obviously different between Nongken 58S and Nongken 58 under LD conditions. Moreover, both <it>OsPRR37 </it>and <it>Hd1 </it>in the inflorescence displayed differences between Nongken 58S and Nongken 58 under both LD and SD conditions.</p> <p>Conclusion</p> <p>The results presented here indicate that the transcriptome in Nongken 58S was significantly suppressed under LD conditions. Among these DEGs, the circadian rhythm and the flowering pathway were involved in the male sterility transition. Furthermore, these pathways were coordinately involved in the male sterility transition in PGMS rice.</p