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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.
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 Dröge-
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.
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.
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.
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.