Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch.

Publisher: BioMed Central Country of Publication: England NLM ID: 100965258 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2164 (Electronic) Linking ISSN: 14712164 NLM ISO Abbreviation: BMC Genomics Subsets: MEDLINE

Original Publication: London : BioMed Central, [2000-

Larix*/genetics; Genomics/methods ; Genotype ; Japan ; Genome ; Phenotype ; Models, Genetic ; Polymorphism, Single Nucleotide

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.
(© 2023. The Author(s).)

PLoS One. 2014 Jan 08;9(1):e85792. (PMID: 24416447)
PLoS One. 2019 Jun 24;14(6):e0218747. (PMID: 31233563)
Theor Appl Genet. 2009 Dec;120(1):151-61. (PMID: 19841887)
Theor Appl Genet. 2022 Mar;135(3):965-978. (PMID: 34973112)
J Anim Breed Genet. 2007 Dec;124(6):323-30. (PMID: 18076469)
Genet Res (Camb). 2009 Feb;91(1):47-60. (PMID: 19220931)
Genetics. 2006 Jul;173(3):1761-76. (PMID: 16648593)
Nat Rev Genet. 2001 Jan;2(1):21-32. (PMID: 11253064)
BMC Genomics. 2018 Dec 18;19(1):946. (PMID: 30563448)
PLoS Genet. 2006 Mar;2(3):e41. (PMID: 16565746)
Heredity (Edinb). 2019 Sep;123(3):287-306. (PMID: 30858595)
Theor Appl Genet. 2017 Jul;130(7):1415-1430. (PMID: 28393303)
Theor Appl Genet. 1988 Nov;76(5):788-94. (PMID: 24232359)
Theor Appl Genet. 2005 May;110(7):1236-43. (PMID: 15754206)
Nat Genet. 2017 Dec;49(12):1741-1746. (PMID: 29038596)
Sci China Life Sci. 2018 Sep;61(9):1011-1023. (PMID: 29882115)
Genome Biol. 2021 Jun 13;22(1):179. (PMID: 34120648)
BMC Genomics. 2017 Dec 2;18(1):930. (PMID: 29197325)
PLoS One. 2011 May 04;6(5):e19379. (PMID: 21573248)
PLoS One. 2016 Jun 06;11(6):e0156744. (PMID: 27271781)
G3 (Bethesda). 2019 Aug 8;9(8):2739-2748. (PMID: 31263059)
Front Plant Sci. 2021 Sep 09;12:715910. (PMID: 34589099)
Genet Sel Evol. 2015 Apr 19;47:32. (PMID: 25928098)
G3 (Bethesda). 2017 Jun 7;7(6):1995-2014. (PMID: 28455415)
Heredity (Edinb). 2018 Jul;121(1):24-37. (PMID: 29472694)
J Dairy Sci. 2009 Feb;92(2):433-43. (PMID: 19164653)
Front Genet. 2019 Jul 30;10:677. (PMID: 31417604)
Sci Rep. 2022 Mar 10;12(1):3933. (PMID: 35273188)
Front Plant Sci. 2021 Jul 07;12:666820. (PMID: 34305966)
Bioinformatics. 2012 Aug 1;28(15):2086-7. (PMID: 22689388)
Mol Breed. 2018;38(3):26. (PMID: 29491726)
Theor Appl Genet. 2020 Mar;133(3):1009-1018. (PMID: 31907563)
Plant Sci. 2018 Feb;267:84-93. (PMID: 29362102)
G3 (Bethesda). 2015 Oct 04;5(12):2629-37. (PMID: 26438289)
Heredity (Edinb). 2015 Dec;115(6):547-55. (PMID: 26126540)
BMC Genomics. 2017 May 30;18(1):425. (PMID: 28558656)
Genetics. 2001 Apr;157(4):1819-29. (PMID: 11290733)
G3 (Bethesda). 2016 Jan 22;6(3):743-53. (PMID: 26801647)
Genetics. 2013 Jul;194(3):573-96. (PMID: 23636739)
BMC Plant Biol. 2017 Jun 29;17(1):110. (PMID: 28662679)
Genet Res (Camb). 2010 Aug;92(4):295-308. (PMID: 20943010)
Brief Funct Genomics. 2010 Mar;9(2):166-77. (PMID: 20156985)
Genet Sel Evol. 2016 Feb 01;48:8. (PMID: 26830030)
Mol Ecol. 2007 Mar;16(5):1099-106. (PMID: 17305863)
Evol Appl. 2019 Jun 20;13(1):76-94. (PMID: 31892945)
Genetics. 2014 Dec;198(4):1759-68. (PMID: 25324160)
Evol Appl. 2020 Aug 11;13(10):2704-2722. (PMID: 33294018)
Plant Sci. 2016 Jan;242:108-119. (PMID: 26566829)
Genetics. 2013 Feb;193(2):327-45. (PMID: 22745228)
Genetics. 2015 Oct;201(2):759-68. (PMID: 26219298)
Front Genet. 2018 Mar 06;9:78. (PMID: 29559995)
Plant Biotechnol J. 2023 Oct;21(10):2002-2018. (PMID: 37392407)
Heredity (Edinb). 2014 Jan;112(1):48-60. (PMID: 23572121)
J Hered. 2019 Dec 17;110(7):830-843. (PMID: 31629368)
Genet Sel Evol. 2016 Sep 13;48(1):67. (PMID: 27623617)
J Dairy Sci. 2008 Nov;91(11):4414-23. (PMID: 18946147)
Genetics. 2014 Oct;198(2):483-95. (PMID: 25009151)
Heredity (Edinb). 2014 Oct;113(4):343-52. (PMID: 24781808)
Front Plant Sci. 2015 Jan 27;5:780. (PMID: 25674092)
Genetics. 2007 May;176(1):553-61. (PMID: 17179077)
Genetics. 2008 Apr;178(4):2289-303. (PMID: 18430950)

6224061 Beijing Natural Science Foundation; 2022YFD2200302 National Key R&D Program of China

Keywords: Dominance; Epistasis; GBLUP; Genomic prediction; Japanese larch; RKHS

Date Created: 20240103 Date Completed: 20240105 Latest Revision: 20240106

20260130

PMC10759612

10.1186/s12864-023-09891-4

38166605