文献类型：期刊文献

英文题名：Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch

作者：Dong, Leiming[1,2] Xie, Yunhui[1] Zhang, Yalin[1] Wang, Ruizhen[2] Sun, Xiaomei[1]

第一作者：Dong, Leiming

通信作者：Sun, XM[1]

机构：[1]Chinese Acad Forestry, Res Inst Forestry, State Key Lab Tree Genet & Breeding, Key Lab Tree Breeding & Cultivat,State Forestry &, Beijing 100091, Peoples R China;[2]Beijing Bot Garden, Beijing Floriculture Engn Technol Res Ctr, Key Lab Natl Forestry & Grassland Adm Plant Ex sit, Beijing 100093, Peoples R China

年份：2024

卷号：25

期号：1

外文期刊名：BMC GENOMICS

收录：;Scopus(收录号：2-s2.0-85181230868);WOS:【SCI-EXPANDED(收录号:WOS:001135505200023)】；

基金：We would like to thank Dr. Weibo Xiang, Dr. Xingbin Chen and Dr. Chao Sun for their excellent technical assistance in preparing the genotype data. We sincerely acknowledge the editor and two anonymous referees for their constructive criticism and helpful comments, which have greatly improved the manuscript.

语种：英文

外文关键词：Genomic prediction; Dominance; Epistasis; GBLUP; RKHS; Japanese larch

摘要：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.) Carriere) 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.