Metagenome-enabled models improve genomic predictive ability and identification of herbivory-limiting genes in sweetpotato

Alhagie K Cham; Alison K Adams; Phillip A Wadl; Ma Del Carmen Ojeda-Zacarías; William B Rutter; D Michael Jackson; D Dewayne Shoemaker; G Craig Yencho; Bode A Olukolu

doi:10.1093/hr/uhae135

Metagenome-enabled models improve genomic predictive ability and identification of herbivory-limiting genes in sweetpotato

Hortic Res. 2024 May 10;11(7):uhae135. doi: 10.1093/hr/uhae135. eCollection 2024 Jul.

Authors

Affiliations

¹ Department of Entomology and Plant Pathology, University of Tennessee, Knoxville, TN 37996, USA.
² Genome Science and Technology, University of Tennessee, Knoxville, TN 37916, USA.
³ Department of Plant Pathology, University of Georgia, Griffin, GA 30223, USA.
⁴ US Vegetable Laboratory, United States Department of Agriculture, Agriculture Research Service, Charleston, SC 29414, USA.
⁵ Faculty of Agronomy, Autonomous University of Nuevo León, Francisco Villa s/n, Col. Ex Hacienda El Canadá, 66050, General Escobedo, Nuevo León, México.
⁶ Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695, USA.

Abstract

Plant-insect interactions are often influenced by host- or insect-associated metagenomic community members. The relative abundance of insects and the microbes that modulate their interactions were obtained from sweetpotato (Ipomoea batatas) leaf-associated metagenomes using quantitative reduced representation sequencing and strain/species-level profiling with the Qmatey software. Positive correlations were found between whitefly (Bemisia tabaci) and its endosymbionts (Candidatus Hamiltonella defensa, Candidatus Portiera aleyrodidarum, and Rickettsia spp.) and negative correlations with nitrogen-fixing bacteria that implicate nitric oxide in sweetpotato-whitefly interaction. Genome-wide associations using 252 975 dosage-based markers, and metagenomes as a covariate to reduce false positive rates, implicated ethylene and cell wall modification in sweetpotato-whitefly interaction. The predictive abilities (PA) for whitefly and Ocypus olens abundance were high in both populations (68%-69% and 33.3%-35.8%, respectively) and 69.9% for Frankliniella occidentalis. The metagBLUP (gBLUP) prediction model, which fits the background metagenome-based Cao dissimilarity matrix instead of the marker-based relationship matrix (G-matrix), revealed moderate PA (35.3%-49.1%) except for O. olens (3%-10.1%). A significant gain in PA after modeling the metagenome as a covariate (gGBLUP, ≤11%) confirms quantification accuracy and that the metagenome modulates phenotypic expression and might account for the missing heritability problem. Significant gains in PA were also revealed after fitting allele dosage (≤17.4%) and dominance effects (≤4.6%). Pseudo-diploidized genotype data underperformed for dominance models. Including segregation-distorted loci (SDL) increased PA by 6%-17.1%, suggesting that traits associated with fitness cost might benefit from the inclusion of SDL. Our findings confirm the holobiont theory of host-metagenome co-evolution and underscore its potential for breeding within the context of G × G × E interactions.