An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Genome-Wide Identification of Expression Quantitative Trait Loci (eQTLs) in Human Heart.

In recent years genome-wide association studies (GWAS) have uncovered numerous chromosomal loci associated with various electrocardiographic traits and cardiac arrhythmia predisposition. A considerable fraction of these loci lie within inter-genic regions. The underlying trait-associated variants likely reside in regulatory regions and exert their effect by modulating gene expression. Hence, the key to unraveling the molecular mechanisms underlying these cardiac traits is to interrogate variants for association with differential transcript abundance by expression quantitative trait locus (eQTL) analysis. In this study we conducted an eQTL analysis of human heart. For a total of 129 left ventricular samples that were collected from non-diseased human donor hearts, genome-wide transcript abundance and genotyping was determined using microarrays. Each of the 18,402 transcripts and 897,683 SNP genotypes that remained after pre-processing and stringent quality control were tested for eQTL effects. We identified 771 eQTLs, regulating 429 unique transcripts. Overlaying these eQTLs with cardiac GWAS loci identified novel candidates for studies aimed at elucidating the functional and transcriptional impact of these loci. Thus, this work provides for the first time a comprehensive eQTL map of human heart: a powerful and unique resource that enables systems genetics approaches for the study of cardiac traits

Impact of in Utero Folate Exposure on Dna Methylation and Its Potential Relevance for Later‐Life Health – Evidence from Mouse Models Translated to Human Cohorts

Scope: Persistent DNA methylation changes may mediate the effects of early-life exposures on later-life health. However, the human lifespan is challenging for prospective studies, therefore data from longitudinal studies are limited. Projecting data from mouse models of early-life exposure to existing human studies offers a potential tool to address this challenge. Methods and Results: C57BL/6J mice were fed low or normal folate diets before and during pregnancy and lactation. Genome-wide promoter methylation was measured in male offspring livers at 17.5 days gestation and 28 weeks. Eight promoters were concurrently hypermethylated by folate depletion in fetuses and adults (>1.10 fold-change;p<0.05). Processes/pathways potentially influenced by global changes, and function of these 8 genes, suggest neurocognitive effects. Human observational and randomized controlled trial data were interrogated for translational findings. Methylation at birth was inversely associated with maternal plasma folate in 6 of the genes (-1.15% to-0.16%/nmol/l;p<0.05), whilst maternal folic acid supplementation was associated with differential methylation of 4 of these genes in adulthood. Three CpGs were persistently hypermethylated with lower maternal folate (p = 0.04). Conclusion: Some persistent folate-induced methylation changes observed in mice were mirrored in humans. This demonstrates utility of mouse data in identifying human loci for interrogation as biomarkers of later-life health

Beetlehangers.org: harmonizing host–parasite records of Harmonia axyridis and Hesperomyces harmoniae

Citizen science is an increasingly powerful tool to gather large quantities of biological data and to engage the public. The number of citizen science initiatives has rapidly increased in the last 15 years. Invasive alien species such as the harlequin ladybird, Harmonia axyridis (Coleoptera, Coccinellidae), provide a particularly good opportunity for broad-scale use of such initiatives. Harmonia axyridis is parasitized by a fungus, Hesperomyces harmoniae (Ascomycota, Laboulbeniales), that can be found throughout the range of its host. Here we present Beetlehangers.org, a website and data repository where we combine observations of He. harmoniae from literature, online databases, and citizen science initiatives, including new records of both Ha. axyridis and He. harmoniae. Whereas Ha. axyridis is now present in 86 countries across six continents (including seven new country records), the distribution of its parasite He. harmoniae comprises 33 countries in five continents (including two new country records since its description in 2022). We explore spatiotemporal trends of He. harmoniae in light of these records. Finally, we discuss challenges and new opportunities for citizen science in relation to species interactions such as these and provide future perspectives for the website as a home for future Laboulbeniales research and outreach

Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Orton et al.BACKGROUND: The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway. RESULTS: We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors. CONCLUSION: Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems.This work was funded by the Department of Trade and Industry (DTI), under their Bioscience Beacon project programme. AG was funded by an industrial PhD studentship from Scottish Enterprise and Cyclacel

Subcutaneous Adipose Tissue and Systemic Inflammation Are Associated With Peripheral but Not Hepatic Insulin Resistance in Humans

Obesity-related insulin resistance (IR) may develop in multiple organs, representing different etiologies towards cardiometabolic diseases. We identified abdominal subcutaneous adipose tissue (ScAT) transcriptome profiles in relation to liver or muscle IR by means of RNA sequencing in overweight/obese participants of the DiOGenes cohort (n=368). Tissue-specific IR phenotypes were derived from a 5-point oral glucose tolerance test. Hepatic and muscle IR were characterized by distinct abdominal ScAT transcriptome profiles. Genes related to extracellular remodeling were upregulated in individuals with primarily hepatic IR, whilst genes related to inflammation were upregulated in individuals with primarily muscle IR. In line with this, in two independent cohorts, CODAM (n=325) and the Maastricht Study (n=685), an increased systemic low-grade inflammation profile was specifically related to muscle IR, but not to liver IR. We propose that increased ScAT inflammatory gene expression may translate into an increased systemic inflammatory profile, linking ScAT inflammation to the muscle IR phenotype. These distinct IR phenotypes may provide leads for more personalized prevention of cardiometabolic diseases. DiOGenes was registered at clinicaltrials.gov as NCT00390637

52 Genetic Loci Influencing Myocardial Mass.

BACKGROUND: Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death. OBJECTIVES: This meta-analysis sought to gain insights into the genetic determinants of myocardial mass. METHODS: We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment. RESULTS: We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p < 1 × 10(-8). These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67 candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in vitro and in vivo. CONCLUSIONS: Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets