@article{JonasKluthHelmsetal.2022,
  author    = {Jonas, Wenke and Kluth, Oliver and Helms, Anett and Voss, Sarah and Jahnert, Markus and Gottmann, Pascal and Speckmann, Thilo and Knebel, Birgit and Chadt, Alexandra and Al-Hasani, Hadi and Sch{\"u}rmann, Annette and Vogel, Heike},
  title     = {Identification of novel genes involved in hyperglycemia in mice},
  series = {International journal of molecular sciences},
  volume    = {23},
  journal   = {International journal of molecular sciences},
  number    = {6},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1661-6596},
  doi       = {10.3390/ijms23063205},
  pages     = {13},
  year      = {2022},
  abstract  = {Current attempts to prevent and manage type 2 diabetes have been moderately effective, and a better understanding of the molecular roots of this complex disease is important to develop more successful and precise treatment options. Recently, we initiated the collective diabetes cross, where four mouse inbred strains differing in their diabetes susceptibility were crossed with the obese and diabetes-prone NZO strain and identified the quantitative trait loci (QTL) Nidd13/NZO, a genomic region on chromosome 13 that correlates with hyperglycemia in NZO allele carriers compared to B6 controls. Subsequent analysis of the critical region, harboring 644 genes, included expression studies in pancreatic islets of congenic Nidd13/NZO mice, integration of single-cell data from parental NZO and B6 islets as well as haplotype analysis. Finally, of the five genes (Acot12, S100z, Ankrd55, Rnf180, and Iqgap2) within the polymorphic haplotype block that are differently expressed in islets of B6 compared to NZO mice, we identified the calcium-binding protein S100z gene to affect islet cell proliferation as well as apoptosis when overexpressed in MINE cells. In summary, we define S100z as the most striking gene to be causal for the diabetes QTL Nidd13/NZO by affecting beta-cell proliferation and apoptosis. Thus, S100z is an entirely novel diabetes gene regulating islet cell function.},
  language  = {en}
}
@article{deAbreueLimaLiWenetal.2018,
  author    = {de Abreu e Lima, Francisco Anastacio and Li, Kun and Wen, Weiwei and Yan, Jianbing and Nikoloski, Zoran and Willmitzer, Lothar and Brotman, Yariv},
  title     = {Unraveling lipid metabolism in maize with time-resolved multi-omics data},
  series = {The plant journal},
  volume    = {93},
  journal   = {The plant journal},
  number    = {6},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0960-7412},
  doi       = {10.1111/tpj.13833},
  pages     = {1102 -- 1115},
  year      = {2018},
  abstract  = {Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 x By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species.},
  language  = {en}
}