Genomics of sorghum local adaptation to a parasitic plant
- aDepartment of Biology, The Pennsylvania State University, University Park, PA 16802;
- bArkansas Biosciences Institute, Arkansas State University, State University, AR 72467;
- cDepartment of Computer Science, Arkansas State University, State University, AR 72467;
- dIntercollege Graduate Program in Plant Biology, The Pennsylvania State University, University Park, PA 16802;
- eApplied Science and Technology, Corteva Agriscience, Johnston, IA 50131;
- fInstitut Systématique Evolution Biodiversité, Muséum National d’Histoire Naturelle, CNRS, Sorbonne Université, École Pratique des Hautes Études, CP39, 75005 Paris, France;
- gIdentification & Naming, Royal Botanic Gardens, Kew, TW9 3AB Richmond, United Kingdom;
- hDepartment of Integrative Biology, University of Texas at Austin, Austin, TX 78712;
- iDepartment of Agronomy, Kansas State University, Manhattan, KS 66506;
- jDepartment of Plant Ecology and Evolution, Evolutionary Biology Centre, Uppsala University, SE-75236 Uppsala, Sweden;
- kDepartment of Biology, University of Virginia, Charlottesville, VA 22904;
- lWest and Central Africa Regional Program, International Crops Research Institute for the Semi-Arid Tropics, BP 320 Bamako, Mali;
- mDepartment of Biochemistry and Biotechnology, Kenyatta University, Nairobi, Kenya
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Edited by John N. Thompson, University of California, Santa Cruz, CA, and accepted by Editorial Board Member Douglas Futuyma January 7, 2020 (received for review May 21, 2019)

Significance
Understanding coevolution in crop–parasite systems is critical to management of myriad pests and pathogens confronting modern agriculture. In contrast to wild plant communities, parasites in agricultural ecosystems are usually expected to gain the upper hand in coevolutionary “arms races” due to limited genetic diversity of host crops in cultivation. Here, we develop a framework to characterize associations between genome variants in global landraces (traditional varieties) of the staple crop sorghum with the distribution of the devastating parasitic weed Striga hermonthica. We find long-term maintenance of diversity in genes related to parasite resistance, highlighting an important role of host adaptation for coevolutionary dynamics in smallholder agroecosystems.
Abstract
Host–parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica-prone regions and their absence elsewhere implicate potential trade-offs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and below-ground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with trade-offs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR–Cas9-edited sorghum further indicate that the benefit of LGS1-mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.
Footnotes
- ↵1To whom correspondence may be addressed. Email: ebellis{at}astate.edu.
Author contributions: E.S.B., E.A.K., C.M.L., H.G., R.M., N.D.C., T.E.J., G.P.M., C.W.d., and J.R.L. designed research; E.S.B., E.A.K., C.M.L., H.G., V.L.D., G.R., A.B., and G.B.B. performed research; H.G., M.P.T., B.N., S.M.R., and N.D.C. contributed new reagents/analytic tools; E.S.B., V.L.D., Z.H., and J.R.L. analyzed data; E.S.B. wrote the manuscript, with input from T.E.J.; G.P.M., C.W.d., and J.R.L.; E.A.K., C.M.L., H.G., and G.B.B. contributed to writing; V.L.D., G.R., A.B., R.M., M.P.T., and N.D.C. contributed to manuscript revision.
Competing interest statement: H.G. and N.D.C. are employees of Corteva Agriscience.
This article is a PNAS Direct Submission. J.N.T. is a guest editor invited by the Editorial Board.
Data deposition: Raw TagSeq reads generated for this study have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database, https://www.ncbi.nlm.nih.gov/sra (BioProject accession no. PRJNA542394). Environmental niche models and additional datasets are available from Penn State ScholarSphere (https://doi.org/10.26207/bfct-ca95).
This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1908707117/-/DCSupplemental.
Published under the PNAS license.
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