The Genome Sequence of the Wild Tomato Solanum pimpinellifolium Provides Insights Into Salinity Tolerance
Morton, Mitchell J. L.
Arold, Stefan T.
Schmoeckel, Sandra Manuela
Tester, Mark A.
Bajic, Vladimir B.
KAUST DepartmentApplied Mathematics and Computational Science Program
Biological and Environmental Science and Engineering (BESE) Division
Center for Desert Agriculture
Computational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Publication Srvcs and Researcher Support
Red Sea Research Center (RSRC)
Structural Biology and Engineering
The Salt Lab
Permanent link to this recordhttp://hdl.handle.net/10754/626165
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AbstractSolanum pimpinellifolium, a wild relative of cultivated tomato, offers a wealth of breeding potential for desirable traits such as tolerance to abiotic and biotic stresses. Here, we report the genome assembly and annotation of S. pimpinellifolium ‘LA0480.’ Moreover, we present phenotypic data from one field experiment that demonstrate a greater salinity tolerance for fruit- and yield-related traits in S. pimpinellifolium compared with cultivated tomato. The ‘LA0480’ genome assembly size (811 Mb) and the number of annotated genes (25,970) are within the range observed for other sequenced tomato species. We developed and utilized the Dragon Eukaryotic Analyses Platform (DEAP) to functionally annotate the ‘LA0480’ protein-coding genes. Additionally, we used DEAP to compare protein function between S. pimpinellifolium and cultivated tomato. Our data suggest enrichment in genes involved in biotic and abiotic stress responses. To understand the genomic basis for these differences in S. pimpinellifolium and S. lycopersicum, we analyzed 15 genes that have previously been shown to mediate salinity tolerance in plants. We show that S. pimpinellifolium has a higher copy number of the inositol-3-phosphate synthase and phosphatase genes, which are both key enzymes in the production of inositol and its derivatives. Moreover, our analysis indicates that changes occurring in the inositol phosphate pathway may contribute to the observed higher salinity tolerance in ‘LA0480.’ Altogether, our work provides essential resources to understand and unlock the genetic and breeding potential of S. pimpinellifolium, and to discover the genomic basis underlying its environmental robustness.
CitationRazali R, Bougouffa S, Morton MJL, Lightfoot DJ, Alam I, et al. (2018) The Genome Sequence of the Wild Tomato Solanum pimpinellifolium Provides Insights Into Salinity Tolerance. Frontiers in Plant Science 9. Available: http://dx.doi.org/10.3389/fpls.2018.01402.
SponsorsWe thank John Hanks and Craig Kapfer for the great assistance with the computational resources and the installation of the many bioinformatics tools. Genome sequencing was performed at the biological core laboratories of KAUST. All the computational analyses were performed on Dragon and Snapdragon computer clusters of the Computational Bioscience Research Center (CBRC) at King Abdullah University of Science and Technology (KAUST). We thank Gabriele Fiene (KAUST) for her assistance with the field trial and phenotypic data collection. We also thank Hajime Ohyanagi for his comments on the phylogenetic analysis. Funding. This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. 2302-01-01 and KAUST Base Research Funds to VB Grant No. BAS/1/1606-01-01 and to MT Grant No. BAS/1/1038-01-01.
PublisherFrontiers Media SA
JournalFrontiers in Plant Science
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Bougouffa, S., Morton, M. J. L., Lightfoot, D. J., Mohamad Razali, R., Alam, I., Essack, M., … Sónia, N. (2016). Dataset for ‘The genome sequence of the wild tomato Solanum pimpinellifolium provides insights into salinity tolerance’ [Data set]. KAUST Research Repository. https://doi.org/10.25781/KAUST-4KWTX. DOI: 10.25781/KAUST-4KWTX Handle: 10754/628050
CollectionsArticles; Biological and Environmental Science and Engineering (BESE) Division; Red Sea Research Center (RSRC); Bioscience Program; Applied Mathematics and Computational Science Program; Computational Bioscience Research Center (CBRC); Center for Desert Agriculture; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
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