Serious limitations of the QTL/Microarray approach for QTL gene discovery

<p>Abstract</p> <p>Background</p> <p>It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL). However, the effectiveness of this approach has not been assessed.</p> <p>Results</p> <p>Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons<b/> between congenic and background strains. Three studies led to the identification of an underlying <it>QTL </it>gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD) regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of <it>QTL </it>regulated in <it>cis </it>(<it>cis </it>eQTL) showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP).</p> <p>Conclusions</p> <p>The literature shows limited successes from the QTL/microarray approach to identify <it>QTL </it>genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select <it>cis-</it>eQTL over <it>trans-</it>eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false <it>cis-</it>eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes that were not tested. Together, our results explain the tendency to report QTL candidates as differentially expressed and indicate that the utility of the QTL/microarray as currently implemented is limited. Alternatives are proposed that make use of microarray data from multiple experiments to overcome the outlined limitations.</p

Corrigendum: How Can We Define “Optimal Microbiota?”: A Comparative Review of Structure and Functions of Microbiota of Animals, Fish, and Plants in Agriculture

In the original article, we regret that the following Funding statement was missing: This work was financially supported by the Japan Society for the Promotion of Science (JSPS) through JSPS Core-to-Core Program (Advanced Research Networks) entitled Establishment of international agricultural immunology research-core for a quantum improvement in food safety. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.</p

Uncoupling proteins, dietary fat and the metabolic syndrome

There has been intense interest in defining the functions of UCP2 and UCP3 during the nine years since the cloning of these UCP1 homologues. Current data suggest that both UCP2 and UCP3 proteins share some features with UCP1, such as the ability to reduce mitochondrial membrane potential, but they also have distinctly different physiological roles. Human genetic studies consistently demonstrate the effect of UCP2 alleles on type-2 diabetes. Less clear is whether UCP2 alleles influence body weight or body mass index (BMI) with many studies showing a positive effect while others do not. There is strong evidence that both UCP2 and UCP3 protect against mitochondrial oxidative damage by reducing the production of reactive oxygen species. The evidence that UCP2 protein is a negative regulator of insulin secretion by pancreatic β-cells is also strong: increased UCP2 decreases glucose stimulated insulin secretion ultimately leading to β-cell dysfunction. UCP2 is also neuroprotective, reducing oxidative stress in neurons. UCP3 may also transport fatty acids out of mitochondria thereby protecting the mitochondria from fatty acid anions or peroxides. Current data suggest that UCP2 plays a role in the metabolic syndrome through down-regulation of insulin secretion and development of type-2 diabetes. However, UCP2 may protect against atherosclerosis through reduction of oxidative stress and both UCP2 and UCP3 may protect against obesity. Thus, these UCP1 homologues may both contribute to and protect from the markers of the metabolic syndrome

Evidence of maternal QTL affecting growth and obesity in adult mice

Most quantitative trait loci (QTL) studies fail to account for the effect that the maternal genotype may have on an individual’s phenotypes, even though maternal effect QTL have been shown to account for considerable variation in growth and obesity traits in mouse models. Moreover, the fetal programming theory suggests that maternal effects influence an offspring’s adult fitness, although the genetic nature of fetal programming remains unclear. Within this context, our study focused on mapping genomic regions associated with maternal effect QTL by analyzing the phenotypes of chromosomes 2 and 7 subcongenic mice from genetically distinct dams. We analyzed 12 chromosome 2 subcongenic strains that spanned from 70 to 180 Mb with CAST/EiJ donor regions on the background of C57BL/6 J, and 14 chromosome 7 subcongenic strains that spanned from 81 to 111 Mb with BALB/cByJ donor regions on C57BL/6ByJ background. Maternal QTL analyses were performed on the basis of overlapping donor regions between subcongenic strains. We identified several highly significant (P < 5 × 10−4) maternal QTL influencing total body weight, organ weight, and fat pad weights in both sets of subcongenics. These QTL accounted for 1.9-11.7% of the phenotypic variance for growth and obesity and greatly narrowed the genomic regions associated with the maternal genetic effects. These maternal effect QTL controlled phenotypic traits in adult mice, suggesting that maternal influences at early stages of development may permanently affect offspring performance. Identification of maternal effects in our survey of two sets of subcongenic strains, representing approximately 5% of the mouse genome, supports the hypothesis that maternal effects represent significant sources of genetic variation that are largely ignored in genetic studies

Exercise and bone health across the lifespan

With ageing, bone tissue undergoes significant compositional, architectural and metabolic alterations potentially leading to osteoporosis. Osteoporosis is the most prevalent bone disorder, which is characterised by progressive bone weakening and an increased risk of fragility fractures. Although this metabolic disease is conventionally associated with ageing and menopause, the predisposing factors are thought to be established during childhood and adolescence. In light of this, exercise interventions implemented during maturation are likely to be highly beneficial as part of a long-term strategy to maximise peak bone mass and hence delay the onset of age- or menopause-related osteoporosis. This notion is supported by data on exercise interventions implemented during childhood and adolescence, which confirmed that weight-bearing activity, particularly if undertaken during peripubertal development, is capable of generating a significant osteogenic response leading to bone anabolism. Recent work on human ageing and epigenetics suggests that undertaking exercise after the fourth decade of life is still important, given the anti-ageing effect and health benefits provided, potentially occurring via a delay in telomere shortening and modification of DNA methylation patterns associated with ageing. Exercise is among the primary modifiable factors capable of influencing bone health by preserving bone mass and strength, preventing the death of bone cells and anti-ageing action provided

The case for strategic international alliances to harness nutritional genomics for public and personal health

Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene-nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient-genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countrie

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease

We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P ≤ 1 × 10−5. We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10−17; including ADGC data, meta P = 5.0 × 10−21) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10−14; including ADGC data, meta P = 1.2 × 10−16) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10−4; including ADGC data, meta P = 8.6 × 10−9), CD33 (GERAD+, P = 2.2 × 10−4; including ADGC data, meta P = 1.6 × 10−9) and EPHA1 (GERAD+, P = 3.4 × 10−4; including ADGC data, meta P = 6.0 × 10−10)

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease