Association analysis of phenotypic traits in selected and propagated lines derived from different winter wheat CCPs
Creators: name: Dennenmoser, Dominic
name: Schmidt, Jan Henrik
name: Backes, Gunter
Publisher: name: Zenodo
Year: 2019
Subjects: Composite cross population (CCP)
Genome-wide association studies (GWAS)
Winter wheat
Triticum aestivum
Self-regulating systems
SNP
GAPIT-related GWAS
Network-based GWAS
Biodiversity
Plant breeding

description: <strong>Background</strong> Biodiversity at all levels from microbial populations up to inter- and intra-specific diversity of plants is a major component in self-regulating systems. Aims and methods for breeding of crops adapted to self-regulating systems, such as heterogeneous populations, are different from most current breeding programs in several aspects. This study attempts to use wheat lines selected from composite cross populations (CCPs) in order to test the applicability as diverse, but still restricted population for genome-wide association studies (GWAS). <strong>Material and Methods</strong> Out of 200 CCP lines, derived from different winter wheat CCPs, DNA was isolated from 184, selected for contrasting phenotypes and homozygosity and genotyped using a 20K (15K+5K) SNP micro array chip. The genotyping data, together with the phenotypic data are being used for the GWAS to link allelic changes to trait expressions. GAPIT-related GWAS: GLM, MLM, MLMM, and FarmCPU included K and Q matrix. Covariate (Q matrix) was calculated using principal component analysis (PCA) based on 8961 selected SNPs. Network-based GWAS: using Gaussian copula graphical model for reconstructing conditional independence networks. <strong>Results</strong> Preliminary GWAS results were obtained from up to ten phenotypic traits at the organically and conventional managed trial farms of the University of Kassel (KU) and the Technical University of Munich (TUM; Germany) for the season 2017/18. GAPIT-related GWAS resulted in up to 13 candidate for up 6 of the 10 traits and 31--65 potential candidates for all traits. In contrast, the network-based GWAS resulted in 50--52 candidates for 9 of the 10 traits. <strong>Conclusions</strong> Further investigations and comparison with different environments and methods are needed for a more complex understanding of the phenotypic traits in the development of diverse populations and mixtures in organic plant breeding.
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