Abstract
Background: Potato is the third most consumed crop in the world. Breeding for traits such as yield, product quality and pathogen resistance are main priorities. Identifying molecular signatures of these and other important traits is important in future breeding efforts. In this study, a progeny population from a cross between a breeding line, SW93-1015, and a cultivar, Désireé, was studied by trait analysis and RNA-seq in order to develop understanding of segregating traits at the molecular level and identify transcripts with expressional correlation to these traits. Transcript markers with predictive value for field performance applicable under controlled environments would be of great value for plant breeding. Results: A total of 34 progeny lines from SW93-1015 and Désireé were phenotyped for 17 different traits in a field in Nordic climate conditions and controlled climate settings. A master transcriptome was constructed with all 34 progeny lines and the parents through a de novo assembly of RNA-seq reads. Gene expression data obtained in a controlled environment from the 34 lines was correlated to traits by different similarity indices, including Pearson and Spearman, as well as DUO, which calculates the co-occurrence between high and low values for gene expression and trait. Our study linked transcripts to traits such as yield, growth rate, high laying tubers, late and tuber blight, tuber greening and early flowering. We found several transcripts associated to late blight resistance and transcripts encoding receptors were associated to Dickeya solani susceptibility. Transcript levels of a UBX-domain protein was negatively associated to yield and a GLABRA2 expression modulator was negatively associated to growth rate. Conclusion: In our study, we identify 100's of transcripts, putatively linked based on expression with 17 traits of potato, representing both well-known and novel associations. This approach can be used to link the transcriptome to traits. We explore the possibility of associating the level of transcript expression from controlled, optimal environments to traits in a progeny population with different methods introducing the application of DUO for the first time on transcriptome data. We verify the expression pattern for five of the putative transcript markers in another progeny population.
| Original language | English |
|---|---|
| Article number | 120 |
| Journal | BMC Plant Biology |
| Volume | 20 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 18 2020 |
Funding
This work is supported by research funds from The Swedish Foundation for Environmental Strategic research (Mistra Biotech), The Swedish Research Council Formas (2015–442), Swedish farmer’s foundation for agricultural research (0–15–20-557) and the Plant Breeding Platform, Swedish University of Agricultural Sciences. The authors acknowledge support from Uppsala Multidisciplinary Center for Advanced Computational Science for access to the UPPMAX computational infrastructure. This research was also supported by the Plant-Microbe Interfaces Scientific Focus Area (http://pmi.ornl.gov) in the Genomic Science Program, the Office of Biological and Environmental Research (BER) in the U.S. Department of Energy Office of Science and by the Department of Energy, Laboratory Directed Research and Development funding (8321), at the Oak Ridge National Laboratory. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the US DOE under contract DE-AC05-00OR22725. This research was also supported by National Institutes of Health grants (RF1 AG053303 and GM100364), and by a Knight Alzheimer’s Disease Research Center (ADRC) Pilot Grant. Open access funding provided by Swedish University of Agricultural Sciences.