@article{ThiemannFuSeifertetal.2014, author = {Thiemann, Alexander and Fu, Junjie and Seifert, Felix and Grant-Downton, Robert T and Schrag, Tobias A and Pospisil, Heike and Frisch, Matthias and Melchinger, Albrecht E and Scholten, Stefan}, title = {Genome-wide meta-analysis of maize heterosis reveals the potential role of additive gene expression at pericentromeric loci}, series = {BMC Plant Biology}, volume = {14}, journal = {BMC Plant Biology}, number = {88}, issn = {1471-2229}, doi = {10.1186/1471-2229-14-88}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-5999}, pages = {14}, year = {2014}, abstract = {The identification of QTL involved in heterosis formation is one approach to unravel the not yet fully understood genetic basis of heterosis - the improved agronomic performance of hybrid F1 plants compared to their inbred parents. The identification of candidate genes underlying a QTL is important both for developing markers and determining the molecular genetic basis of a trait, but remains difficult owing to the large number of genes often contained within individual QTL. To address this problem in heterosis analysis, we applied a meta-analysis strategy for grain yield (GY) of Zea mays L. as example, incorporating QTL-, hybrid field-, and parental gene expression data.}, language = {en} } @article{KleinPospisil2014, author = {Klein, Andreas and Pospisil, Heike}, title = {Gene Expression Profiling of Pancreatic Cancer Reveals a Significant Deregulation of the TGF-β Pathway and the Discovery of Genes for Prognosis}, series = {Global Journal of Human Genetics \& Gene Therapy}, volume = {2}, journal = {Global Journal of Human Genetics \& Gene Therapy}, number = {1}, issn = {2311-0309}, doi = {10.14205/2311-0309.2014.02.01.3}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-6519}, pages = {30 -- 39}, year = {2014}, abstract = {We have re-analyzed previously published gene expression data from ninety-four pancreatic ductal adenocarcinomas (PDAC) samples. We determined the gene expression profile of genes differentially expressed in PDAC compared to non-malignant pancreatic tissue. Using the 100 top-ranked genes, we were able to discriminate between PDAC and non-malignant pancreatic tissue. A hierarchical cluster analysis revealed only a 6 \% false discovery rate. The prognostic strength of these discriminative genes was underscored by a SVM classification and 3-fold cross validation with an 89 \% correct class assignment. The annotation of the 100 top-ranked genes revealed that most of the genes were involved in the processes of signal transduction, cell adhesion, extracellular matrix organization and cell migration. The most greatly affected signal cascade was the transforming growth factor β receptor signaling pathway, which was significantly enriched in the top-ranked genes. Furthermore, we identified eleven genes that were associated with good prognosis.}, language = {en} }