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Sunflower pan-genome analysis shows that hybridization altered gene content and disease resistance

Nature Plants volume 5, pages 54–62 (2019)Cite this article

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Abstract

Domesticated plants and animals often display dramatic responses to selection, but the origins of the genetic diversity underlying these responses remain poorly understood. Despite domestication and improvement bottlenecks, the cultivated sunflower remains highly variable genetically, possibly due to hybridization with wild relatives. To characterize genetic diversity in the sunflower and to quantify contributions from wild relatives, we sequenced 287 cultivated lines, 17 Native American landraces and 189 wild accessions representing 11 compatible wild species. Cultivar sequences failing to map to the sunflower reference were assembled de novo for each genotype to determine the gene repertoire, or ‘pan-genome’, of the cultivated sunflower. Assembled genes were then compared to the wild species to estimate origins. Results indicate that the cultivated sunflower pan-genome comprises 61,205 genes, of which 27% vary across genotypes. Approximately 10% of the cultivated sunflower pan-genome is derived through introgression from wild sunflower species, and 1.5% of genes originated solely through introgression. Gene ontology functional analyses further indicate that genes associated with biotic resistance are over-represented among introgressed regions, an observation consistent with breeding records. Analyses of allelic variation associated with downy mildew resistance provide an example in which such introgressions have contributed to resistance to a globally challenging disease.

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Fig. 1: Genomic variation in the SAM population based on 675,291 SNPs detected across all lines.
Fig. 2: The cultivated sunflower pan-genome.
Fig. 3: Average number of genes in the cultivated sunflower pan-genome assigned to the wild source.
Fig. 4: Genome-wide association mapping of downy mildew resistance in the SAM population.

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Data availability

All raw sequence data are stored in the Sequence Read Archive (SRA) under Bioproject PRJNA353001 for cultivars and PRJNA397453 for wild and landrace. Accession numbers for each sample are listed in Supplementary Table 10. The SNP data set in vcf format, pan-genome sequences in fasta format and genome scan statistics in bed files format can be downloaded from https://www.sunflowergenome.org/.

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Acknowledgements

We thank the Genome Quebec Innovation Centre and UBC’s Biodiversity Research Centre for conducting the sequencing, M. Heffernan for the development of the statistical pipeline for GWAS, K. Rashid for providing downy mildew isolates, W. Cheung for project coordination and assistance with experimental work, and SAP SE for computing resources. Funding was provided by Genome Canada and Genome BC (LSARP2014-223SUN), the NSF Plant Genome Program (DBI-0820451 and DBI-1444522) and the International Consortium for Sunflower Genomic Resources.

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Authors and Affiliations

  1. Department of Botany and Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada

    Sariel Hübner, Natalia Bercovich, Marco Todesco, Joon S. Lee, Gregory J. Baute, Gregory L. Owens, Christopher J. Grassa, Daniel P. Ebert, Katherine L. Ostevik, Brook T. Moyers, Sarah Yakimowski, Lexuan Gao, Nolan C. Kane & Loren H. Rieseberg

  2. Department of Biotechnology, Tel-Hai Academic College, Upper Galilee, Israel

    Sariel Hübner

  3. MIGAL—Galilee Research Institute, Kiryat Shmona, Israel

    Sariel Hübner

  4. Department of Biological Sciences, University of Memphis, Memphis, TN, USA

    Jennifer R. Mandel

  5. SAP SE, Dietmar-Hopp-Allee 16, Walldorf, Germany

    Jens Odenheimer, Emanuel Ziegler & Timo Kubach

  6. Department of Integrative Biology, University of California, Berkeley, CA, USA

    Gregory L. Owens

  7. Harvard University Herbaria , Cambridge, MA, USA

    Christopher J. Grassa

  8. The Beef Industry Centre, University of New England, Armidale, New South Wales, Australia

    Daniel P. Ebert

  9. Department of Biology , Duke University, Durham, NC, USA

    Katherine L. Ostevik

  10. Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO, USA

    Brook T. Moyers

  11. Department of Plant Biology, Miller Plant Sciences, University of Georgia, Athens, Georgia, USA

    Rishi R. Masalia, Irina Ćalić, John E. Bowers & John M. Burke

  12. Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA

    Nolan C. Kane

  13. Agricultural Research Council, Biotechnology Platform, Private Bag X05, Onderstepoort, South Africa

    Dirk Z. H. Swanevelder

  14. LIPM, Université de Toulouse, INRA, CNRS, Castanet-Tolosan, France

    Stephane Muños & Nicolas B. Langlade

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  1. Sariel Hübner
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Contributions

J.R.M., M.T., G.J.B., C.J.G., D.P.E., K.L.O., S.Y, B.T.M. and N.C.K. contributed to DNA sample collection and data production. N.B. and M.T. mapped downy mildew resistance. S.H., J.O. and E.Z. conducted the alignments and variant calling. S.H. performed the genome scans, pan-genome analyses, introgression analyses and GWAS. J.S.L. conducted the expression analyses. G.L.O. archived the data. J.E.B., I.C., L.G. and R.R.M. optimized the SNP data set for GWAS. L.H.R., J.M.B., N.B.L., S.M., T.K. and D.Z.H.S. designed the experiments and coordinated the project. S.H., N.B., J.M.B. and L.H.R. wrote the manuscript.

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Correspondence to Sariel Hübner.

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Hübner, S., Bercovich, N., Todesco, M. et al. Sunflower pan-genome analysis shows that hybridization altered gene content and disease resistance. Nature Plants 5, 54–62 (2019). https://doi.org/10.1038/s41477-018-0329-0

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