ArticleThe plant genome2018
Candidate Variants for Additive and Interactive Effects on Bioenergy Traits in Switchgrass (
Article in The plant genome, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Genome-Wide Associations with Resistance to Bipolaris Leaf Spot (Plants (Basel, Switzerland) · 2022Article
- High-Altitude Genetic Selection and Genome-Wide Association Analysis of Yield-Related Traits inFrontiers in plant science · 2022Article
- Genetic loci associated with winter survivorship in diverse lowland switchgrass populations.The plant genome · 2021Article
- Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize.Genetics · 2020Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Switchgrass ( L.) is a promising herbaceous energy crop, but further gains in biomass yield and quality must be achieved to enable a viable bioenergy industry. Developing DNA markers can contribute to such progress, but depiction of genetic bases should be reliable, involving simple additive marker effects and also interactions with genetic backgrounds (e.g., ecotypes) or synergies with other markers. We analyzed plant height, C content, N content, and mineral concentration in a diverse panel consisting of 512 genotypes of upland and lowland ecotypes. We performed association analyses based on exome capture sequencing and tested 439,170 markers for marginal effects, 83,290 markers for marker × ecotype interactions, and up to 311,445 marker pairs for pairwise interactions. Analyses of pairwise interactions focused on subsets of marker pairs preselected on the basis of marginal marker effects, gene ontology annotation, and pairwise marker associations. Our tests identified 12 significant effects. Homology and gene expression information corroborated seven effects and indicated plausible causal pathways: flowering time and lignin synthesis for plant height; plant growth and senescence for C content and mineral concentration. Four pairwise interactions were detected, including three interactions preselected on the basis of pairwise marker correlations. Furthermore, a marker × ecotype interaction and a pairwise interaction were confirmed in an independent switchgrass panel. Our analyses identified reliable candidate variants for important bioenergy traits. Moreover, they exemplified the importance of interactive effects for depicting genetic bases and illustrated the usefulness of preselecting marker pairs for identifying pairwise marker interactions in association studies.
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