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Genetic Analysis in Common Bean for Variation Affecting the Human Gut Microbiome
Our increasing understanding of host-diet-microbiome interactions in health and disease creates a new opportunity to orient crop-improvement programs toward quality traits that can be used to improve human health through the microbiome. One of the biggest barriers to developing/improving human health traits that affect the human microbiome is the lack of approaches for phenotyping “Microbiome Active Traits” (MATs) in crop plants. To overcome this, a high-throughput Automated in vitro Microbiome Screen (AiMS) that enables study of MATs as complex traits of crops was developed. To demonstrate utility and multi-dimensional scalability of AiMS for phenotyping, we capitalized on the unique ancestry, population structure, and genomics of a globally important commodity, common beans (Phaseolus vulgaris L.). Using the AiMS platform, 24 cultivars of common bean representing genetic diversity from the Mesoamerican Diversity Panel (MDP) were studied across 12 microbiomes. Results indicated population structure of common bean (landraces and market classes) had significant, shared effects on microbial diversity, composition, and function across multiple microbiomes. AiMS was further leveraged in a Genome-Wide Association Study (GWAS) to study the genetic architecture of MATs using 299 genotypes of common bean of the MDP across three human microbiomes. Features of the microbiome from the AiMS-based phenotyping were used as quantitative traits in the GWAS. GWAS identified seven pleiotropic major effect loci (MEL) on six chromosomes in the common bean genome where genetic variation had significant influence on microbiome features. Genomic analyses within the MEL with the most significant marker-trait associations identified genes related to glycyrrhetinate biosynthesis, a precursor of saponins that have known bioactivity. In conclusion, the studies presented in this dissertation illustrate that genetic analysis of AiMS-based phenotypes provides a powerful approach for identifying new types of traits (MATs) in food crops that may have important impacts on the human gut microbiome, ultimately providing breeders with unique, human-health associated phenotypes that can be incorporated into crop improvement programs.
Van Haute, Mallory J. Suhr, "Genetic Analysis in Common Bean for Variation Affecting the Human Gut Microbiome" (2021). ETD collection for University of Nebraska-Lincoln. AAI28865399.