Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch
Abstract Genomic dissection of genetic effects on desirable traits and the subsequent use of genomic selection hold great promise for accelerating the rate of genetic improvement of forest tree species. In this study, a total of 661 offspring trees from 66 open-pollinated families of Japanese larch...
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BMC
2024-01-01
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| Series: | BMC Genomics |
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| Online Access: | https://doi.org/10.1186/s12864-023-09891-4 |
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| author | Leiming Dong Yunhui Xie Yalin Zhang Ruizhen Wang Xiaomei Sun |
| author_facet | Leiming Dong Yunhui Xie Yalin Zhang Ruizhen Wang Xiaomei Sun |
| author_sort | Leiming Dong |
| collection | DOAJ |
| description | Abstract Genomic dissection of genetic effects on desirable traits and the subsequent use of genomic selection hold great promise for accelerating the rate of genetic improvement of forest tree species. In this study, a total of 661 offspring trees from 66 open-pollinated families of Japanese larch (Larix kaempferi (Lam.) Carrière) were sampled at a test site. The contributions of additive and non-additive effects (dominance, imprinting and epistasis) were evaluated for nine valuable traits related to growth, wood physical and chemical properties, and competitive ability using three pedigree-based and four Genomics-based Best Linear Unbiased Predictions (GBLUP) models and used to determine the genetic model. The predictive ability (PA) of two genomic prediction methods, GBLUP and Reproducing Kernel Hilbert Spaces (RKHS), was compared. The traits could be classified into two types based on different quantitative genetic architectures: for type I, including wood chemical properties and Pilodyn penetration, additive effect is the main source of variation (38.20-67.46%); for type II, including growth, competitive ability and acoustic velocity, epistasis plays a significant role (50.76-91.26%). Dominance and imprinting showed low to moderate contributions (< 36.26%). GBLUP was more suitable for traits of type I (PAs = 0.37–0.39 vs. 0.14–0.25), and RKHS was more suitable for traits of type II (PAs = 0.23–0.37 vs. 0.07–0.23). Non-additive effects make no meaningful contribution to the enhancement of PA of GBLUP method for all traits. These findings enhance our current understanding of the architecture of quantitative traits and lay the foundation for the development of genomic selection strategies in Japanese larch. |
| first_indexed | 2024-03-08T16:23:27Z |
| format | Article |
| id | doaj.art-83ea6e22ae4644a5ab385b05db79495b |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2024-03-08T16:23:27Z |
| publishDate | 2024-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genomics |
| spelling | doaj.art-83ea6e22ae4644a5ab385b05db79495b2024-01-07T12:12:17ZengBMCBMC Genomics1471-21642024-01-0125111510.1186/s12864-023-09891-4Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larchLeiming Dong0Yunhui Xie1Yalin Zhang2Ruizhen Wang3Xiaomei Sun4State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of ForestryState Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of ForestryState Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of ForestryKey Laboratory of National Forestry and Grassland Administration on Plant Ex situ Conservation, Beijing Floriculture Engineering Technology Research Centre, Beijing Botanical GardenState Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of ForestryAbstract Genomic dissection of genetic effects on desirable traits and the subsequent use of genomic selection hold great promise for accelerating the rate of genetic improvement of forest tree species. In this study, a total of 661 offspring trees from 66 open-pollinated families of Japanese larch (Larix kaempferi (Lam.) Carrière) were sampled at a test site. The contributions of additive and non-additive effects (dominance, imprinting and epistasis) were evaluated for nine valuable traits related to growth, wood physical and chemical properties, and competitive ability using three pedigree-based and four Genomics-based Best Linear Unbiased Predictions (GBLUP) models and used to determine the genetic model. The predictive ability (PA) of two genomic prediction methods, GBLUP and Reproducing Kernel Hilbert Spaces (RKHS), was compared. The traits could be classified into two types based on different quantitative genetic architectures: for type I, including wood chemical properties and Pilodyn penetration, additive effect is the main source of variation (38.20-67.46%); for type II, including growth, competitive ability and acoustic velocity, epistasis plays a significant role (50.76-91.26%). Dominance and imprinting showed low to moderate contributions (< 36.26%). GBLUP was more suitable for traits of type I (PAs = 0.37–0.39 vs. 0.14–0.25), and RKHS was more suitable for traits of type II (PAs = 0.23–0.37 vs. 0.07–0.23). Non-additive effects make no meaningful contribution to the enhancement of PA of GBLUP method for all traits. These findings enhance our current understanding of the architecture of quantitative traits and lay the foundation for the development of genomic selection strategies in Japanese larch.https://doi.org/10.1186/s12864-023-09891-4Genomic predictionDominanceEpistasisGBLUPRKHSJapanese larch |
| spellingShingle | Leiming Dong Yunhui Xie Yalin Zhang Ruizhen Wang Xiaomei Sun Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch BMC Genomics Genomic prediction Dominance Epistasis GBLUP RKHS Japanese larch |
| title | Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch |
| title_full | Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch |
| title_fullStr | Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch |
| title_full_unstemmed | Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch |
| title_short | Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch |
| title_sort | genomic dissection of additive and non additive genetic effects and genomic prediction in an open pollinated family test of japanese larch |
| topic | Genomic prediction Dominance Epistasis GBLUP RKHS Japanese larch |
| url | https://doi.org/10.1186/s12864-023-09891-4 |
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