Genomic Prediction Informed by Biological Processes Expands Our Understanding of the Genetic Architecture Underlying Free Amino Acid Traits in Dry Arabidopsis Seeds

被引:9
作者
Turner-Hissong, Sarah D. [1 ]
Bird, Kevin A. [1 ]
Lipka, Alexander E. [2 ]
King, Elizabeth G. [1 ]
Beissinger, Timothy M. [3 ,4 ]
Angelovici, Ruthie [1 ]
机构
[1] Univ Missouri, Div Biol Sci, Columbia, MO 65211 USA
[2] Univ Illinois, Dept Crop Sci, Urbana, IL 61801 USA
[3] Georg August Univ, Dept Crop Sci, Div Plant Breeding Methodol, Gottingen, Germany
[4] Georg August Univ, Ctr Integrated Breeding Res, Gottingen, Germany
来源
G3-GENES GENOMES GENETICS | 2020年 / 10卷 / 11期
关键词
amino acids; genomic prediction; MultiBLUP; complex traits; Arabidopsis; GenPred; Shared Data Resources; WIDE ASSOCIATION; QUANTITATIVE TRAITS; SELECTION; PLANT; PATHWAYS; LYSINE; BIOSYNTHESIS; ACCUMULATION; METABOLISM; RESPONSES;
D O I
10.1534/g3.120.401240
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Toward this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana. Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes.
引用
收藏
页码:4227 / 4239
页数:13
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