@phdthesis{Anwar2022,
  author    = {Anwar, Ammarah},
  title     = {Natural variation of gene regulatory networks in \(Arabidopsis\) \(thaliana\)},
  doi       = {10.25972/OPUS-29154},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-291549},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {Understanding the causal relationship between genotype and phenotype is a major objective in biology. The main interest is in understanding trait architecture and identifying loci contributing to the respective traits. Genome-wide association mapping (GWAS) is one tool to elucidate these relationships and has been successfully used in many different species. However, most studies concentrate on marginal marker effects and ignore epistatic and gene-environment interactions. These interactions are problematic to account for, but are likely to make major contributions to many phenotypes that are not regulated by independent genetic effects, but by more sophisticated gene-regulatory networks. Further complication arises from the fact that these networks vary in different natural accessions. However, understanding the differences of gene regulatory networks and gene-gene interactions is crucial to conceive trait architecture and predict phenotypes. The basic subject of this study - using data from the Arabidopsis 1001 Genomes Project - is the analysis of pre-mature stop codons. These have been incurred in nearly one-third of the ~ 30k genes. A gene-gene interaction network of the co-occurrence of stop codons has been built and the over and under representation of different pairs has been statistically analyzed. To further classify the significant over and under- represented gene-gene interactions in terms of molecular function of the encoded proteins, gene ontology terms (GO-SLIM) have been applied. Furthermore, co- expression analysis specifies gene clusters that co-occur over different genetic and phenotypic backgrounds. To link these patterns to evolutionary constrains, spatial location of the respective alleles have been analyzed as well. The latter shows clear patterns for certain gene pairs that indicate differential selection.},
  subject      = {Arabidopsis thaliana},
  language  = {en}
}
@article{SerenGrimmFitzetal.2016,
  author    = {Seren, {\"U}mit and Grimm, Dominik and Fitz, Joffrey and Weigel, Detlef and Nordborg, Magnus and Borgwardt, Karsten and Korte, Arthur},
  title     = {AraPheno: a public database for Arabidopsis thaliana phenotypes},
  series = {Nucleic Acids Research},
  volume    = {45},
  journal   = {Nucleic Acids Research},
  number    = {D1},
  doi       = {10.1093/nar/gkw986},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147909},
  pages     = {D1054-D1059},
  year      = {2016},
  abstract  = {Natural genetic variation makes it possible to discover evolutionary changes that have been maintained in a population because they are advantageous. To understand genotype-phenotype relationships and to investigate trait architecture, the existence of both high-resolution genotypic and phenotypic data is necessary. Arabidopsis thaliana is a prime model for these purposes. This herb naturally occurs across much of the Eurasian continent and North America. Thus, it is exposed to a wide range of environmental factors and has been subject to natural selection under distinct conditions. Full genome sequencing data for more than 1000 different natural inbred lines are available, and this has encouraged the distributed generation of many types of phenotypic data. To leverage these data for meta analyses, AraPheno (https://arapheno.1001genomes.org) provide a central repository of population-scale phenotypes for A. thaliana inbred lines. AraPheno includes various features to easily access, download and visualize the phenotypic data. This will facilitate a comparative analysis of the many different types of phenotypic data, which is the base to further enhance our understanding of the genotype-phenotype map.},
  language  = {en}
}