A multi-marker association method for genome-wide association studies without the need for population structure correction.
All common genome-wide association (GWA) methods rely on population structure correction, to avoid false genotype-to-phenotype associations. However, population structure correction is a stringent penalization, which also impedes identification of real associations. Using recent statistical advances, we developed a new GWA method, called Quantitative Trait Cluster Association Test (QTCAT), enabling simultaneous multi-marker associations while considering correlations between markers. With this, QTCAT overcomes the need for population structure correction and also reflects the polygenic nature of complex traits better than single-marker methods. Using simulated data, we show that QTCAT clearly outperforms linear mixed model approaches. Moreover, using QTCAT to reanalyse public human, mouse and Arabidopsis GWA data revealed nearly all known and some previously undetected associations. Following up on the most significant novel association in the Arabidopsis data allowed us to identify a so far unknown component of root growth.
Department of Plant Developmental Biology, Max Planck Institute for Plant Breeding Research (MPIPZ), Carl-von-Linné-Weg 10, 50829 Cologne, Germany.|Department of Plant Breeding and Genetics, Max Planck Institute for Plant Breeding Research (MPIPZ), Carl-von-Linné-Weg 10, 50829 Cologne, Germany.
Jonas R
JR
Klasen
Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), Dr Bohr-Gasse 3, 1030 Vienna, Austria.
Elke
E
Barbez
Seminar for Statistics, Department of Mathematics, Eidgenssische Technische Hochschule Zurich (ETHZ), Rämistrasse 101, 8092 Zurich, Switzerland.
Lukas
L
Meier
Seminar for Statistics, Department of Mathematics, Eidgenssische Technische Hochschule Zurich (ETHZ), Rämistrasse 101, 8092 Zurich, Switzerland.
Nicolai
N
Meinshausen
Seminar for Statistics, Department of Mathematics, Eidgenssische Technische Hochschule Zurich (ETHZ), Rämistrasse 101, 8092 Zurich, Switzerland.
Peter
P
Bühlmann
Department of Plant Breeding and Genetics, Max Planck Institute for Plant Breeding Research (MPIPZ), Carl-von-Linné-Weg 10, 50829 Cologne, Germany.
Maarten
M
Koornneef
Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), Dr Bohr-Gasse 3, 1030 Vienna, Austria.
Wolfgang
0000-0003-2042-7290
W
Busch
Department of Plant Developmental Biology, Max Planck Institute for Plant Breeding Research (MPIPZ), Carl-von-Linné-Weg 10, 50829 Cologne, Germany.
Korbinian
K
Schneeberger
D017360:Arabidopsis / Q000235:genetics; D002874:Chromosome Mapping / Q000379:methods*; D005787:Gene Frequency; D056726:Genetic Association Studies / Q000379:methods*; D018745:Genome, Plant / Q000235:genetics; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D016014:Linear Models; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci / Q000235:genetics*; D015203:Reproducibility of Results