1
|
Tessema BB, Raffo MA, Guo X, Svane SF, Krusell L, Jensen JD, Ruud AK, Malinowska M, Thorup-Kristensen K, Jensen J. Genomic prediction for root and yield traits of barley under a water availability gradient: a case study comparing different spatial adjustments. PLANT METHODS 2024; 20:8. [PMID: 38216953 PMCID: PMC10785381 DOI: 10.1186/s13007-023-01121-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 12/04/2023] [Indexed: 01/14/2024]
Abstract
BACKGROUND In drought periods, water use efficiency depends on the capacity of roots to extract water from deep soil. A semi-field phenotyping facility (RadiMax) was used to investigate above-ground and root traits in spring barley when grown under a water availability gradient. Above-ground traits included grain yield, grain protein concentration, grain nitrogen removal, and thousand kernel weight. Root traits were obtained through digital images measuring the root length at different depths. Two nearest-neighbor adjustments (M1 and M2) to model spatial variation were used for genetic parameter estimation and genomic prediction (GP). M1 and M2 used (co)variance structures and differed in the distance function to calculate between-neighbor correlations. M2 was the most developed adjustment, as accounted by the Euclidean distance between neighbors. RESULTS The estimated heritabilities ([Formula: see text]) ranged from low to medium for root and above-ground traits. The genetic coefficient of variation ([Formula: see text]) ranged from 3.2 to 7.0% for above-ground and 4.7 to 10.4% for root traits, indicating good breeding potential for the measured traits. The highest [Formula: see text] observed for root traits revealed that significant genetic change in root development can be achieved through selection. We studied the genotype-by-water availability interaction, but no relevant interaction effects were detected. GP was assessed using leave-one-line-out (LOO) cross-validation. The predictive ability (PA) estimated as the correlation between phenotypes corrected by fixed effects and genomic estimated breeding values ranged from 0.33 to 0.49 for above-ground and 0.15 to 0.27 for root traits, and no substantial variance inflation in predicted genetic effects was observed. Significant differences in PA were observed in favor of M2. CONCLUSIONS The significant [Formula: see text] and the accurate prediction of breeding values for above-ground and root traits revealed that developing genetically superior barley lines with improved root systems is possible. In addition, we found significant spatial variation in the experiment, highlighting the relevance of correctly accounting for spatial effects in statistical models. In this sense, the proposed nearest-neighbor adjustments are flexible approaches in terms of assumptions that can be useful for semi-field or field experiments.
Collapse
Affiliation(s)
- Biructawit B Tessema
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.
- Section of Plant Breeding and Genetics, School of Integrative Plant Sciences, Cornell University, Ithaca, NY, USA.
| | - Miguel A Raffo
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark.
| | - Xiangyu Guo
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark
- Danish Pig Research Centre, Danish Agriculture & Food Council, Copenhagen, Denmark
| | - Simon F Svane
- Department of Plant and Environmental Science, University of Copenhagen, 1871, Frederiksberg, Denmark
| | - Lene Krusell
- Sejet Plant Breeding I/S, 8700, Horsens, Denmark
| | | | - Anja Karine Ruud
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark
- Faculty of Biosciences, Department of Plant Science, Norwegian University of Life Sciences (NMBU), Ås, Norway
| | - Marta Malinowska
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark
| | | | - Just Jensen
- Center for Quantitative Genetics and Genomics, Aarhus University, 8830, Tjele, Denmark
| |
Collapse
|