University of Southern Denmark

About: University of Southern Denmark is a education organization based out in Odense, Syddanmark, Denmark. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 11928 authors who have published 37918 publications receiving 1258559 citations. The organization is also known as: SDU.

Towards a consistent classification scheme for geochemical environments, or, why we wish the term 'suboxic' would go away.

Abstract: It is our opinion that the nomenclature used to define geochemical environments is inconsistent and confusing, and in particular the use and meaning of the term ‘suboxic’, which is widely applied in the geochemical and ecological literature. Our purpose here is to review the redox zonation of natural systems and the nomenclature used to designate this. Finally, we will outline what we feel is a straightforward and non-contradictory scheme for classifying metabolic zones and geochemical environments.

Resequencing of 200 human exomes identifies an excess of low-frequency non-synonymous coding variants

Abstract: Targeted capture combined with massively parallel exome sequencing is a promising approach to identify genetic variants implicated in human traits. We report exome sequencing of 200 individuals from Denmark with targeted capture of 18,654 coding genes and sequence coverage of each individual exome at an average depth of 12-fold. On average, about 95% of the target regions were covered by at least one read. We identified 121,870 SNPs in the sample population, including 53,081 coding SNPs (cSNPs). Using a statistical method for SNP calling and an estimation of allelic frequencies based on our population data, we derived the allele frequency spectrum of cSNPs with a minor allele frequency greater than 0.02. We identified a 1.8-fold excess of deleterious, non-syonomyous cSNPs over synonymous cSNPs in the low-frequency range (minor allele frequencies between 2% and 5%). This excess was more pronounced for X-linked SNPs, suggesting that deleterious substitutions are primarily recessive.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Abstract: We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.