Genomic prediction of yield and root development in wheat under changing water availability
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Genomic prediction of yield and root development in wheat under changing water availability. / Guo, Xiangyu; Svane, Simon F.; Fuchtbauer, Winnie S.; Andersen, Jeppe R.; Jensen, Just; Thorup-Kristensen, Kristian.
In: Plant Methods, Vol. 16, No. 1, 90, 2020.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Genomic prediction of yield and root development in wheat under changing water availability
AU - Guo, Xiangyu
AU - Svane, Simon F.
AU - Fuchtbauer, Winnie S.
AU - Andersen, Jeppe R.
AU - Jensen, Just
AU - Thorup-Kristensen, Kristian
PY - 2020
Y1 - 2020
N2 - Background Deeper roots help plants take up available resources in deep soil ensuring better growth and higher yields under conditions of drought. A large-scale semi-field root phenotyping facility was developed to allow a water availability gradient and detect potential interaction of genotype by water availability gradient. Genotyped winter wheat lines were grown as rows in four beds of this facility, where indirect genetic effects from neighbors could be important to trait variation. The objective was to explore the possibility of genomic prediction for grain-related traits and deep root traits collected via images taken in a minirhizotron tube under each row of winter wheat measured. Results The analysis comprised four grain-related traits: grain yield, thousand-kernel weight, protein concentration, and total nitrogen content measured on each half row that were harvested separately. Two root traits, total root length between 1.2 and 2 m depth and root length in four intervals on each tube were also analyzed. Two sets of models with or without the effects of neighbors from both sides of each row were applied. No interaction between genotypes and changing water availability were detected for any trait. Estimated genomic heritabilities ranged from 0.263 to 0.680 for grain-related traits and from 0.030 to 0.055 for root traits. The coefficients of genetic variation were similar for grain-related and root traits. The prediction accuracy of breeding values ranged from 0.440 to 0.598 for grain-related traits and from 0.264 to 0.334 for root traits. Including neighbor effects in the model generally increased the estimated genomic heritabilities and accuracy of predicted breeding values for grain yield and nitrogen content. Conclusions Similar relative amounts of additive genetic variance were found for both yield traits and root traits but no interaction between genotypes and water availability were detected. It is possible to obtain accurate genomic prediction of breeding values for grain-related traits and reasonably accurate predicted breeding values for deep root traits using records from the semi-field facility. Including neighbor effects increased the estimated additive genetic variance of grain-related traits and accuracy of predicting breeding values. High prediction accuracy can be obtained although heritability is low.
AB - Background Deeper roots help plants take up available resources in deep soil ensuring better growth and higher yields under conditions of drought. A large-scale semi-field root phenotyping facility was developed to allow a water availability gradient and detect potential interaction of genotype by water availability gradient. Genotyped winter wheat lines were grown as rows in four beds of this facility, where indirect genetic effects from neighbors could be important to trait variation. The objective was to explore the possibility of genomic prediction for grain-related traits and deep root traits collected via images taken in a minirhizotron tube under each row of winter wheat measured. Results The analysis comprised four grain-related traits: grain yield, thousand-kernel weight, protein concentration, and total nitrogen content measured on each half row that were harvested separately. Two root traits, total root length between 1.2 and 2 m depth and root length in four intervals on each tube were also analyzed. Two sets of models with or without the effects of neighbors from both sides of each row were applied. No interaction between genotypes and changing water availability were detected for any trait. Estimated genomic heritabilities ranged from 0.263 to 0.680 for grain-related traits and from 0.030 to 0.055 for root traits. The coefficients of genetic variation were similar for grain-related and root traits. The prediction accuracy of breeding values ranged from 0.440 to 0.598 for grain-related traits and from 0.264 to 0.334 for root traits. Including neighbor effects in the model generally increased the estimated genomic heritabilities and accuracy of predicted breeding values for grain yield and nitrogen content. Conclusions Similar relative amounts of additive genetic variance were found for both yield traits and root traits but no interaction between genotypes and water availability were detected. It is possible to obtain accurate genomic prediction of breeding values for grain-related traits and reasonably accurate predicted breeding values for deep root traits using records from the semi-field facility. Including neighbor effects increased the estimated additive genetic variance of grain-related traits and accuracy of predicting breeding values. High prediction accuracy can be obtained although heritability is low.
KW - Genomic prediction
KW - Wheat
KW - Semi-field
KW - Grain-related yield
KW - Deep root
KW - NITROGEN-USE EFFICIENCY
KW - GRAIN-YIELD
KW - MULTILEVEL SELECTION
KW - POPULATION-STRUCTURE
KW - ASSISTED SELECTION
KW - INHERITANCE
KW - CULTIVARS
KW - ACCURACY
KW - TRAITS
KW - PLAINS
U2 - 10.1186/s13007-020-00634-0
DO - 10.1186/s13007-020-00634-0
M3 - Journal article
C2 - 32625241
VL - 16
JO - Plant Methods
JF - Plant Methods
SN - 1746-4811
IS - 1
M1 - 90
ER -
ID: 249533703