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

• Published in: Horticulture research Vol. 11; no. 7
• Main Authors: Cham, Alhagie K, Adams, Alison K, Wadl, Phillip A, Ojeda-Zacarías, Ma del Carmen, Rutter, William B, Jackson, D Michael, Shoemaker, D Dewayne, Yencho, G Craig, Olukolu, Bode A
• Format: Journal Article
• Language: English
• Published: Oxford University Press 01-07-2024
• ISSN: 2052-7276; 2662-6810; 2052-7276
• DOI: 10.1093/hr/uhae135

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.