Journal article

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


Authors listKnoch, Dominic; Meyer, Rhonda C.; Heuermann, Marc C.; Riewe, David; Peleke, Fritz F.; Szymanski, Jedrzej; Abbadi, Amine; Snowdon, Rod J.; Altmann, Thomas

Publication year2024

Pages713-728

JournalThe Plant Journal

Volume number117

Issue number3

ISSN0960-7412

eISSN1365-313X

Open access statusHybrid

DOI Linkhttps://doi.org/10.1111/tpj.16524

PublisherWiley


Abstract

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.




Citation Styles

Harvard Citation styleKnoch, D., Meyer, R., Heuermann, M., Riewe, D., Peleke, F., Szymanski, J., et al. (2024) Integrated multi-omics analyses and genome-wide association studies reveal prime candidate genes of metabolic and vegetative growth variation in canola, The Plant Journal, 117(3), pp. 713-728. https://doi.org/10.1111/tpj.16524

APA Citation styleKnoch, D., Meyer, R., Heuermann, M., Riewe, D., Peleke, F., Szymanski, J., Abbadi, A., Snowdon, R., & Altmann, T. (2024). Integrated multi-omics analyses and genome-wide association studies reveal prime candidate genes of metabolic and vegetative growth variation in canola. The Plant Journal. 117(3), 713-728. https://doi.org/10.1111/tpj.16524


Last updated on 2025-10-06 at 12:00