Genomics of sorghum local adaptation to a parasitic plant

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.

A genomics resource for genetics, physiology, and breeding of West African sorghum

“…Historically, West African sorghum germplasm has been useful for global sorghum breeding including durra and caudatum accessions that were sources of yellow endosperm and The Plant Genome drought tolerance for U.S. breeding programs (Rosenow & Dahlberg, 2000). Whole-genome resequencing would complement the GBS SNP dataset to more easily identify putative causal variants for adaptive traits in the West African germplasm (Bellis et al, 2020). The development of traitpredictive markers could facilitate more rapid breeding of locally and regionally adapted sorghum varieties for the diverse stakeholders of WA.…”

GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum

“…In sorghum, earlier Striga resistance loci mapping studies used quantitative trail loci (QTL) analysis based on simple sequence repeat and amplified fragment length polymorphism (AFLP) markers in two recombinant inbred line (RIL) populations derived from crosses between; (i) post-attachment resistant cultivar N13 and the susceptible cultivar E36–1 (ii) pre-attachment resistant IS9830 crossed to the susceptible cultivar E36–1 [ 18 ]. Subsequent studies have used genotyping by sequencing (GBS)-based single nucleotide polymorphisms (SNPs) in genome wide association studies (GWAS) to determine genomic regions of sorghum associated with adaptation to Striga [ 19 ]. Although these studies have provided insights to genetic/genomic regions linked to Striga resistance in sorghum, interpreting field GWAS studies is confounded by environmental variability that sometimes complicate interpretation of association data [ 18 ].…”

The witchweed Striga gesnerioides and the cultivated cowpea: A geographical and historical analysis of their West African distribution points to the prevalence of agro-ecological factors and the parasite’s multilocal evolution potential

“…hermonthica too, the distribution of the parasite prevails on that of the potential hosts and host shifting takes place within it. Thus, Bellis et al [ 36 ] obtained the same distribution pattern with 1050 observations on different hosts or with a subsample of 262 observations on sorghum alone. And impressive evolutions in S .…”

“…hermonthica African distribution using the Worldclim database, and projecting it on two models predicting the 2020 climate. More recently, Bellis et al [ 36 ] produced an African distribution model for the same species, based on bioclimatic, topographic and soil variables. They reported (i) that annual rainfall and total soil nitrogen were the most informative variables to predict S .…”