@article{ZulawskiSchulzeBraginetsetal.2014,
  author    = {Zulawski, Monika and Schulze, Gunnar and Braginets, Rostyslav and Hartmann, Stefanie and Schulze, Waltraud X.},
  title     = {The Arabidopsis Kinome: phylogeny and evolutionary insights into functional diversification},
  series = {BMC genomics},
  volume    = {15},
  journal   = {BMC genomics},
  publisher = {BioMed Central},
  address   = {London},
  issn      = {1471-2164},
  doi       = {10.1186/1471-2164-15-548},
  pages     = {14},
  year      = {2014},
  abstract  = {Background: Protein kinases constitute a particularly large protein family in Arabidopsis with important functions in cellular signal transduction networks. At the same time Arabidopsis is a model plant with high frequencies of gene duplications. Here, we have conducted a systematic analysis of the Arabidopsis kinase complement, the kinome, with particular focus on gene duplication events. We matched Arabidopsis proteins to a Hidden-Markov Model of eukaryotic kinases and computed a phylogeny of 942 Arabidopsis protein kinase domains and mapped their origin by gene duplication. Results: The phylogeny showed two major clades of receptor kinases and soluble kinases, each of which was divided into functional subclades. Based on this phylogeny, association of yet uncharacterized kinases to families was possible which extended functional annotation of unknowns. Classification of gene duplications within these protein kinases revealed that representatives of cytosolic subfamilies showed a tendency to maintain segmentally duplicated genes, while some subfamilies of the receptor kinases were enriched for tandem duplicates. Although functional diversification is observed throughout most subfamilies, some instances of functional conservation among genes transposed from the same ancestor were observed. In general, a significant enrichment of essential genes was found among genes encoding for protein kinases. Conclusions: The inferred phylogeny allowed classification and annotation of yet uncharacterized kinases. The prediction and analysis of syntenic blocks and duplication events within gene families of interest can be used to link functional biology to insights from an evolutionary viewpoint. The approach undertaken here can be applied to any gene family in any organism with an annotated genome.},
  language  = {en}
}
@misc{ZulawskiSchulzeBraginetsetal.2014,
  author    = {Zulawski, Monika and Schulze, Gunnar and Braginets, Rostyslav and Hartmann, Stefanie and Schulze, Waltraud X},
  title     = {The Arabidopsis Kinome},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {861},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43290},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-432907},
  pages     = {17},
  year      = {2014},
  abstract  = {Background Protein kinases constitute a particularly large protein family in Arabidopsis with important functions in cellular signal transduction networks. At the same time Arabidopsis is a model plant with high frequencies of gene duplications. Here, we have conducted a systematic analysis of the Arabidopsis kinase complement, the kinome, with particular focus on gene duplication events. We matched Arabidopsis proteins to a Hidden-Markov Model of eukaryotic kinases and computed a phylogeny of 942 Arabidopsis protein kinase domains and mapped their origin by gene duplication. Results The phylogeny showed two major clades of receptor kinases and soluble kinases, each of which was divided into functional subclades. Based on this phylogeny, association of yet uncharacterized kinases to families was possible which extended functional annotation of unknowns. Classification of gene duplications within these protein kinases revealed that representatives of cytosolic subfamilies showed a tendency to maintain segmentally duplicated genes, while some subfamilies of the receptor kinases were enriched for tandem duplicates. Although functional diversification is observed throughout most subfamilies, some instances of functional conservation among genes transposed from the same ancestor were observed. In general, a significant enrichment of essential genes was found among genes encoding for protein kinases. Conclusions The inferred phylogeny allowed classification and annotation of yet uncharacterized kinases. The prediction and analysis of syntenic blocks and duplication events within gene families of interest can be used to link functional biology to insights from an evolutionary viewpoint. The approach undertaken here can be applied to any gene family in any organism with an annotated genome.},
  language  = {en}
}
@article{Schulze2014,
  author    = {Schulze, Gunnar},
  title     = {Workflow for rapid metagenome analysis},
  series = {Process design for natural scientists: an agile model-driven approach},
  journal   = {Process design for natural scientists: an agile model-driven approach},
  number    = {500},
  publisher = {Springer},
  address   = {Berlin},
  isbn      = {978-3-662-45005-5},
  issn      = {1865-0929},
  pages     = {88 -- 100},
  year      = {2014},
  abstract  = {Analyses of metagenomes in life sciences present new opportunities as well as challenges to the scientific community and call for advanced computational methods and workflows. The large amount of data collected from samples via next-generation sequencing (NGS) technologies render manual approaches to sequence comparison and annotation unsuitable. Rather, fast and efficient computational pipelines are needed to provide comprehensive statistics and summaries and enable the researcher to choose appropriate tools for more specific analyses. The workflow presented here builds upon previous pipelines designed for automated clustering and annotation of raw sequence reads obtained from next-generation sequencing technologies such as 454 and Illumina. Employing specialized algorithms, the sequence reads are processed at three different levels. First, raw reads are clustered at high similarity cutoff to yield clusters which can be exported as multifasta files for further analyses. Independently, open reading frames (ORFs) are predicted from raw reads and clustered at two strictness levels to yield sets of non-redundant sequences and ORF families. Furthermore, single ORFs are annotated by performing searches against the Pfam database},
  language  = {en}
}
@article{KanzleiterJaehnertSchulzeetal.2015,
  author    = {Kanzleiter, Timo and Jaehnert, Markus and Schulze, Gunnar and Selbig, Joachim and Hallahan, Nicole and Schwenk, Robert Wolfgang and Sch{\"u}rmann, Annette},
  title     = {Exercise training alters DNA methylation patterns in genes related to muscle growth and differentiation in mice},
  series = {American journal of physiology : Endocrinology and metabolism},
  volume    = {308},
  journal   = {American journal of physiology : Endocrinology and metabolism},
  number    = {10},
  publisher = {American Chemical Society},
  address   = {Bethesda},
  issn      = {0193-1849},
  doi       = {10.1152/ajpendo.00289.2014},
  pages     = {E912 -- E920},
  year      = {2015},
  abstract  = {The adaptive response of skeletal muscle to exercise training is tightly controlled and therefore requires transcriptional regulation. DNA methylation is an epigenetic mechanism known to modulate gene expression, but its contribution to exercise-induced adaptations in skeletal muscle is not well studied. Here, we describe a genome-wide analysis of DNA methylation in muscle of trained mice (n = 3). Compared with sedentary controls, 2,762 genes exhibited differentially methylated CpGs (P < 0.05, meth diff >5\%, coverage > 10) in their putative promoter regions. Alignment with gene expression data (n = 6) revealed 200 genes with a negative correlation between methylation and expression changes in response to exercise training. The majority of these genes were related to muscle growth and differentiation, and a minor fraction involved in metabolic regulation. Among the candidates were genes that regulate the expression of myogenic regulatory factors (Plexin A2) as well as genes that participate in muscle hypertrophy (Igfbp4) and motor neuron innervation (Dok7). Interestingly, a transcription factor binding site enrichment study discovered significantly enriched occurrence of CpG methylation in the binding sites of the myogenic regulatory factors MyoD and myogenin. These findings suggest that DNA methylation is involved in the regulation of muscle adaptation to regular exercise training.},
  language  = {en}
}
@article{AgaBarfknechtHallahanGottmannetal.2020,
  author    = {Aga-Barfknecht, Heja and Hallahan, Nicole and Gottmann, Pascal and J{\"a}hnert, Markus and Osburg, Sophie and Schulze, Gunnar and Kamitz, Anne and Arends, Danny and Brockmann, Gudrun and Schallschmidt, Tanja and Lebek, Sandra and Chadt, Alexandra and Al-Hasani, Hadi and Joost, Hans-Georg and Sch{\"u}rmann, Annette and Vogel, Heike},
  title     = {Identification of novel potential type 2 diabetes genes mediating beta-cell loss and hyperglycemia using positional cloning},
  series = {Frontiers in genetics},
  volume    = {11},
  journal   = {Frontiers in genetics},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {1664-8021},
  doi       = {10.3389/fgene.2020.567191},
  pages     = {11},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}