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To explore the genetic determinants of obesity and Type 2 diabetes (T2D), the German Center for Diabetes Research (DZD) conducted crossbreedings of the obese and diabetes-prone New Zealand Obese mouse strain with four different lean strains (B6, DBA, C3H, 129P2) that vary in their susceptibility to develop T2D. Genome-wide linkage analyses localized more than 290 quantitative trait loci (QTL) for obesity, 190 QTL for diabetes-related traits and 100 QTL for plasma metabolites in the out-cross populations. A computational framework was developed that allowed to refine critical regions and to nominate a small number of candidate genes by integrating reciprocal haplotype mapping and transcriptome data. The efficiency of the complex procedure was demonstrated for one obesity QTL. The genomic interval of 35 Mb with 502 annotated candidate genes was narrowed down to six candidates. Accordingly, congenic mice retained the obesity phenotype owing to an interval that contains three of the six candidate genes. Among these the phospholipase PLA2G4A exhibited an elevated expression in adipose tissue of obese human subjects and is therefore a critical regulator of the obesity locus. Together, our broad and complex approach demonstrates that combined- and comparative-cross analysis exhibits improved mapping resolution and represents a valid tool for the identification of disease genes.
Die sozialen Sicherungs- und Fürsorgesysteme in Deutschland befinden sich in einem radikalen Umbau im Sinne eines neoliberalen Gesellschaftsmodells mit der Folge, dass sich die gesellschaftlichen Widersprüche und Konflikte zuspitzen. Gleichzeitig weisen die aktuellen Debatten in der Sozialen Arbeit darauf hin, dass die gesellschaftlichen, und damit strukturellen, Widersprüche in deren Mitte angekommen sind. Sie manifestieren sich u.a. in Handlungsdilemmata, mit denen die Sozialarbeiter/innen in ihrem Berufsalltag und in ihrer pädagogischen Praxis konfrontiert sind und auf die sie reagieren (müssen). Hier liegt auch der Ausgangspunkt der vorliegenden Arbeit. Es wird der Frage nachgegangen, welche Strategien die in der Jugendberufshilfe tätigen Sozialarbeiter/innen bei der Konfrontation mit sich widersprechenden Handlungsanforderungen entwickeln, die sich aus den institutionellen und gesellschaftlichen Rahmenbedingungen einerseits und der sozialpädagogischen Berufspraxis andererseits ergeben. Von besonderem Interesse ist die Frage, welche Probleme und Handlungsdilemmata überhaupt von den Sozialarbeiter/innen wahrgenommen werden. Der Fokus dieser Arbeit liegt auf der Jugendsozialarbeit, und insbesondere auf der Jugendberufshilfe, als demjenigen Teil des sozialen Sicherungssystems, der sich speziell an individuell beeinträchtigte und sozial benachteiligte Jugendliche richtet und an ihrer Übergangsproblematik ansetzt. Dem qualitativen Forschungsansatz der grounded theory folgend werden zwei Fallanalysen von Sozialarbeiterinnen durchgeführt, die als Beraterinnen am Übergang Schule – Beruf tätig sind. Die Ergebnisse weisen darauf hin, dass die Umgangsformen mit Handlungsdilemmata in einem engen individuellen, institutionellen sowie gesellschaftlichen Kontext stehen, da sie stets gleichsam eine individuelle, institutionelle und gesellschaftliche Funktion erfüllen.
Decisions for the conservation of biodiversity and sustainable management of natural resources are typically related to large scales, i.e. the landscape level. However, understanding and predicting the effects of land use and climate change on scales relevant for decision-making requires to include both, large scale vegetation dynamics and small scale processes, such as soil-plant interactions. Integrating the results of multiple BIOTA subprojects enabled us to include necessary data of soil science, botany, socio-economics and remote sensing into a high resolution, process-based and spatially-explicit model. Using an example from a sustainably-used research farm and a communally used and degraded farming area in semiarid southern Namibia we show the power of simulation models as a tool to integrate processes across disciplines and scales.
Type 2 diabetes (T2D) is a complex metabolic disease regulated by an interaction of genetic predisposition and environmental factors. To understand the genetic contribution in the development of diabetes, mice varying in their disease susceptibility were crossed with the obese and diabetes-prone New Zealand obese (NZO) mouse. Subsequent whole-genome sequence scans revealed one major quantitative trait loci (QTL),Nidd/DBAon chromosome 4, linked to elevated blood glucose and reduced plasma insulin and low levels of pancreatic insulin. Phenotypical characterization of congenic mice carrying 13.6 Mbp of the critical fragment of DBA mice displayed severe hyperglycemia and impaired glucose clearance at week 10, decreased glucose response in week 13, and loss of beta-cells and pancreatic insulin in week 16. To identify the responsible gene variant(s), further congenic mice were generated and phenotyped, which resulted in a fragment of 3.3 Mbp that was sufficient to induce hyperglycemia. By combining transcriptome analysis and haplotype mapping, the number of putative responsible variant(s) was narrowed from initial 284 to 18 genes, including gene models and non-coding RNAs. Consideration of haplotype blocks reduced the number of candidate genes to four (Kti12,Osbpl9,Ttc39a, andCalr4) as potential T2D candidates as they display a differential expression in pancreatic islets and/or sequence variation. In conclusion, the integration of comparative analysis of multiple inbred populations such as haplotype mapping, transcriptomics, and sequence data substantially improved the mapping resolution of the diabetes QTLNidd/DBA. Future studies are necessary to understand the exact role of the different candidates in beta-cell function and their contribution in maintaining glycemic control.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.