@phdthesis{LopezArboleda2021,
  author    = {L{\´o}pez Arboleda, William Andr{\´e}s},
  title     = {Global Genetic Heterogeneity in Adaptive Traits},
  doi       = {10.25972/OPUS-24246},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-242468},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {Genome Wide Association Studies (GWAS) have revolutionized the way on how genotype-phenotype relations are assessed. In the 20 years long history of GWAS, multiple challenges from a biological, computational, and statistical point of view have been faced. The implementation of this technique using the model plant species Arabidopsis thaliana, has enabled the detection of many association for multiple traits. Despite a lot of studies implementing GWAS have discovered new candidate genes for multiple traits, different samples are used across studies. In many cases, either globally diverse samples or samples composed of accessions from a geographically restricted area are used. With the aim of comparing GWAS outcomes between populations from different geographic areas, this thesis describes the performance of GWAS in different European samples of A. thaliana. Here, association mapping results for flowering time were compared. Chapter 2 describes the analyses of random resampling from this original sample. The aim was to establish reduced subsamples to later carry out GWAS and compare the outcomes between these subsamples. In Chapter 3, the European sample was split into eight equally-sized local samples representing different geographic regions. Next, GWAS was carried out and an attempt was made to clarify the differences in GWAS outcomes. Chapter 4 contains the results of a collaboration with Prof. Dr. Wolfgang Dr{\"o}ge- Laser, in which my mainly task was the analysis of RNAseq data from A. thaliana plants infected by pathogenic fungi. Finally, Appendix A presents a very short description of my participation in the GHP Project on Access to Care for Cardiometabolic Diseases (HPACC) at the university of Heidelberg.},
  language  = {en}
}
@article{LopezArboledaReinertNordborgetal.2021,
  author    = {Lopez-Arboleda, William Andres and Reinert, Stephan and Nordborg, Magnus and Korte, Arthur},
  title     = {Global genetic heterogeneity in adaptive traits},
  series = {Molecular Biology and Evolution},
  volume    = {38},
  journal   = {Molecular Biology and Evolution},
  number    = {11},
  doi       = {10.1093/molbev/msab208},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-270410},
  pages     = {4822-4831},
  year      = {2021},
  abstract  = {Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure.},
  language  = {en}
}
@phdthesis{Freudenthal2020,
  author    = {Freudenthal, Jan Alexander},
  title     = {Quantitative genetics from genome assemblies to neural network aided omics-based prediction of complex traits},
  doi       = {10.25972/OPUS-19942},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-199429},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2020},
  abstract  = {Quantitative genetics is the study of continuously distributed traits and their ge- netic components. Recent developments in DNA sequencing technologies and computational systems allow researchers to conduct large scale in silico studies. However, going from raw DNA reads to genomic prediction of quantitative traits with the help of neural networks is a long and error-prone process. In the course of this thesis, many steps involved in this process will be assessed in depth. Chap- ter 2 will feature a study that compares the landscape of chloroplast genome as- sembly tools. Chapter 3 will present a software to perform genome-wide associa- tion studies using modern tools, which allow GWAS-Flow to outperform current state of the art software packages. Chapter 4 will give an in depth introduc- tion to machine learning and the nature of quantitative traits and will combine those to genomic prediction with artificial neural networks and compares the re- sults to those of algorithms based on linear mixed models. Finally, in Chapter 5 the results from the previous chapters are summarized and used to elucidate the complex nature of studies concerning quantitative genetics.},
  subject      = {Genetics},
  language  = {en}
}
@article{BrevikvanDonkelaarWeberetal.2016,
  author    = {Brevik, Erlend J and van Donkelaar, Marjolein M. J. and Weber, Heike and S{\´a}nchez-Mora, Cristina and Jacob, Christian and Rivero, Olga and Kittel-Schneider, Sarah and Garcia-martinez, Iris and Aebi, Marcel and van Hulzen, Kimm and Cormand, Bru and Ramos-Quiroga, Josep A and Lesch, Klaus-Peter and Reif, Andreas and Ribases, Marta and Franke, Barbara and Posserud, Maj-Britt and Johansson, Stefan and Lundervold, Astri J. and Haavik, Jan and Zayats, Tetyana},
  title     = {Genome-wide analyses of aggressiveness in attention-deficit hyperactivity disorder},
  series = {American Journal of Medical Genetics Part B-Neuropsychiatric Genetics},
  volume    = {171B},
  journal   = {American Journal of Medical Genetics Part B-Neuropsychiatric Genetics},
  number    = {5},
  organization    = {IMAGE Consortium},
  doi       = {10.1002/ajmg.b.32434},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-188116},
  pages     = {733-747},
  year      = {2016},
  abstract  = {Aggressiveness is a behavioral trait that has the potential to be harmful to individuals and society. With an estimated heritability of about 40\%, genetics is important in its development. We performed an exploratory genome-wide association (GWA) analysis of childhood aggressiveness in attention deficit hyperactivity disorder (ADHD) to gain insight into the underlying biological processes associated with this trait. Our primary sample consisted of 1,060 adult ADHD patients (aADHD). To further explore the genetic architecture of childhood aggressiveness, we performed enrichment analyses of suggestive genome-wide associations observed in aADHD among GWA signals of dimensions of oppositionality (defiant/vindictive and irritable dimensions) in childhood ADHD (cADHD). No single polymorphism reached genome-wide significance (P<5.00E-08). The strongest signal in aADHD was observed at rs10826548, within a long noncoding RNA gene (beta = -1.66, standard error (SE) = 0.34, P = 1.07E-06), closely followed by rs35974940 in the neurotrimin gene (beta = 3.23, SE = 0.67, P = 1.26E-06). The top GWA SNPs observed in aADHD showed significant enrichment of signals from both the defiant/vindictive dimension (Fisher's P-value = 2.28E-06) and the irritable dimension in cADHD (Fisher's P-value = 0.0061). In sum, our results identify a number of biologically interesting markers possibly underlying childhood aggressiveness and provide targets for further genetic exploration of aggressiveness across psychiatric disorders.},
  language  = {en}
}
@article{JarickVolckmarPuetteretal.2014,
  author    = {Jarick, I. and Volckmar, A. L. and P{\"u}tter, C. and Pechlivanis, S. and Nguyen, T. T. and Dauvermann, M. R. and Beck, S. and Albayrak, {\"O}. and Scherag, S. and Gilsbach, S. and Cichon, S. and Hoffmann, P. and Degenhardt, F. and N{\"o}then, M. M. and Schreiber, S. and Wichmann, H. E. and J{\"o}ckel, K. H. and Heinrich, J. and Tiesler, C. M. T. and Faraone, S. V. and Walitza, S. and Sinzig, J. and Freitag, C. and Meyer, J. and Herpertz-Dahlmann, B. and Lehmkuhl, G. and Renner, T. J. and Warnke, A. and Romanos, M. and Lesch, K. P. and Reif, A. and Schimmelmann, B. G. and Hebebrand, J. and Scherag, A. and Hinney, A.},
  title     = {Genome-wide analysis of rare copy number variations reveals PARK2 as a candidate gene for attention-deficit/hyperactivity disorder},
  series = {Molecular Psychiatry},
  volume    = {19},
  journal   = {Molecular Psychiatry},
  number    = {19},
  doi       = {10.1038/mp.2012.161},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-121131},
  pages     = {115-21},
  year      = {2014},
  abstract  = {Attention-deficit/hyperactivity disorder (ADHD) is a common, highly heritable neurodevelopmental disorder. Genetic loci have not yet been identified by genome-wide association studies. Rare copy number variations (CNVs), such as chromosomal deletions or duplications, have been implicated in ADHD and other neurodevelopmental disorders. To identify rare (frequency ≤1\%) CNVs that increase the risk of ADHD, we performed a whole-genome CNV analysis based on 489 young ADHD patients and 1285 adult population-based controls and identified one significantly associated CNV region. In tests for a global burden of large (>500 kb) rare CNVs, we observed a nonsignificant (P=0.271) 1.126-fold enriched rate of subjects carrying at least one such CNV in the group of ADHD cases. Locus-specific tests of association were used to assess if there were more rare CNVs in cases compared with controls. Detected CNVs, which were significantly enriched in the ADHD group, were validated by quantitative (q)PCR. Findings were replicated in an independent sample of 386 young patients with ADHD and 781 young population-based healthy controls. We identified rare CNVs within the parkinson protein 2 gene (PARK2) with a significantly higher prevalence in ADHD patients than in controls \((P=2.8 × 10^{-4})\) after empirical correction for genome-wide testing). In total, the PARK2 locus (chr 6: 162 659 756-162 767 019) harboured three deletions and nine duplications in the ADHD patients and two deletions and two duplications in the controls. By qPCR analysis, we validated 11 of the 12 CNVs in ADHD patients \((P=1.2 × 10^{-3})\) after empirical correction for genome-wide testing). In the replication sample, CNVs at the PARK2 locus were found in four additional ADHD patients and one additional control \((P=4.3 × 10^{-2})\). Our results suggest that copy number variants at the PARK2 locus contribute to the genetic susceptibility of ADHD. Mutations and CNVs in PARK2 are known to be associated with Parkinson disease.},
  language  = {en}
}