Article CC BY 4.0
refereed
published

Integrated multi‐omics analyses and genome‐wide association studies reveal prime candidate genes of metabolic and vegetative growth variation in canola

ORCID
0000-0002-9362-3105
Affiliation
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Molecular Genetics, Germany
Knoch, Dominic;
ORCID
0000-0002-6210-4900
Affiliation
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Molecular Genetics, Germany
Meyer, Rhonda C.;
ORCID
0000-0002-5520-5287
Affiliation
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Molecular Genetics, Germany
Heuermann, Marc C.;
GND
137110405
ORCID
0000-0002-9095-5518
Affiliation
Julius Kühn Institute (JKI), Institute for Ecological Chemistry, Plant Analysis and Stored Product Protection, Germany
Riewe, David;
ORCID
0000-0001-7394-5994
Affiliation
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Molecular Genetics, Germany
Peleke, Fritz F.;
ORCID
0000-0003-1086-0920
Affiliation
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Molecular Genetics, Germany
Szymański, Jędrzej;
ORCID
0000-0002-2389-978X
Affiliation
NPZ Innovation GmbH, Germany
Abbadi, Amine;
ORCID
0000-0001-5577-7616
Affiliation
Justus-Liebig-University Giessen, Department of Plant Breeding, Research Centre for Biosystems, Land Use and Nutrition (iFZ), Germany
Snowdon, Rod J.;
ORCID
0000-0002-3759-360X
Affiliation
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Molecular Genetics, Germany
Altmann, Thomas

Genome-wide association studies (GWAS) identified thousands of genetic loci associated with complex plant traits, including many traits of agronomical importance. However, functional interpretation of GWAS results remains challenging because of large candidate regions due to linkage disequilibrium. High-throughput omics technologies, such as genomics, transcriptomics, proteomics and metabolomics open new avenues for integrative systems biological analyses and help to nominate systems information supported (prime) candidate genes. In the present study, we capitalise on a diverse canola population with 477 spring-type lines which was previously analysed by high-throughput phenotyping of growth-related traits and by RNA sequencing and metabolite profiling for multi-omics-based hybrid performance prediction. We deepened the phenotypic data analysis, now providing 123 time-resolved image-based traits, to gain insight into the complex relations during early vegetative growth and reanalysed the transcriptome data based on the latest Darmor-bzh v10 genome assembly. Genome-wide association testing revealed 61 298 robust quantitative trait loci (QTL) including 187 metabolite QTL, 56814 expression QTL and 4297 phenotypic QTL, many clustered in pronounced hotspots. Combining information about QTL colocalisation across omics layers and correlations between omics features allowed us to discover prime candidate genes for metabolic and vegetative growth variation. Prioritised candidate genes for early biomass accumulation include A06p05760.1_BnaDAR (PIAL1), A10p16280.1_BnaDAR, C07p48260.1_BnaDAR (PRL1) and C07p48510.1_BnaDAR (CLPR4). Moreover, we observed unequal effects of the Brassica A and C subgenomes on early biomass production.

Preview

Cite

Citation style:
Could not load citation form.

Access Statistic

Total:
Downloads:
Abtractviews:
Last 12 Month:
Downloads:
Abtractviews:

Rights

License Holder: 2023 The Authors.

Use and reproduction: