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

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.

Acknowledgements

We thank Ty Phillips for assistance with planting, maintenance, and tissue sampling of the diversity population. The mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. The USDA is an equal opportunity employer. This study was funded by the USDA-NIFA Hatch/Multistate Project W5157-TEN00539, the Bill and Melinda Gates Foundation (grant ID OPP1052983 and OPP1213329), and the Illumina Agricultural Greater Good Initiative grant.

Data availability

The NGS data (Illumina short reads) used for the USDA diversity population are available on the NCBI (National Center for Biotechnology Information) SRA database (Bioproject ID: PRJNA880973), while the NGS data for the DC biparental population will be publicly available on the NCBI SRA database.

Conflict of interest statement

The authors declare no competing interests.

Supplementary data

Supplementary data are available at Horticulture Research Journal online.

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