@article{VogelKamitzHallahanetal.2018,
  author    = {Vogel, Heike and Kamitz, Anne and Hallahan, Nicole and Lebek, Sandra and Schallschmidt, Tanja and Jonas, Wenke and J{\"a}hnert, Markus and Gottmann, Pascal and Zellner, Lisa and Kanzleiter, Timo and Damen, Mareike and Altenhofen, Delsi and Burkhardt, Ralph and Renner, Simone and Dahlhoff, Maik and Wolf, Eckhard and M{\"u}ller, Timo Dirk and Bl{\"u}her, Matthias and Joost, Hans-Georg and Chadt, Alexandra and Al-Hasani, Hadi and Sch{\"u}rmann, Annette},
  title     = {A collective diabetes cross in combination with a computational framework to dissect the genetics of human obesity and Type 2 diabetes},
  series = {Human molecular genetics},
  volume    = {27},
  journal   = {Human molecular genetics},
  number    = {17},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0964-6906},
  doi       = {10.1093/hmg/ddy217},
  pages     = {3099 -- 3112},
  year      = {2018},
  abstract  = {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.},
  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}
}
@phdthesis{Hallahan2016,
  author    = {Hallahan, Nicole},
  title     = {Identification and characterization of a T2D QTL arising from an NZO.DBA mouse cross},
  school      = {Universit{\"a}t Potsdam},
  pages     = {133},
  year      = {2016},
  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}
}