Epistatic interaction has the reverse effects with its constitutive quantitative trait loci.

Epistatic interaction Quantitative trait locus Reverse effect Single segment substitution line

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
06 Aug 2024
Historique:
received: 07 02 2024
accepted: 01 08 2024
medline: 7 8 2024
pubmed: 7 8 2024
entrez: 6 8 2024
Statut: epublish

Résumé

Epistasis is one of important genetic components for a quantitative trait in plant. Eshed and Zamir found negative epistatic interactions of quantitative trait loci in Tomato first. We detected that positive (negative) QTLs generated mostly negative (positive) epistatic interactions on heading date in rice, and then proposed the hypothese that QTL epistasis plays a role of homeostasis in one of our recent papers. In order to further provide additional evidence, the effects of QTLs and their epistatic effects on two quantitative traits of plant height (ph) and thousand kernel weight (tkw) were analyzed in this study. The same regularity was verified again. We detected that positive ph QTLs and negative tkw QTLs always generated reverse epistatic effects, respectively. Moreover, high-order epistatic effects were estimated on these two traits. The sum of all epistatic effects would partially neutralize the additive of constitutive QTL effects. This feature of epistsis would be the mechanism for bionts to maintain homeostasis while the obstacle for human to achieve the pyramiding breeding objectives. More evidences are still being collected to support our assumption.

Identifiants

pubmed: 39107519
doi: 10.1038/s41598-024-69236-3
pii: 10.1038/s41598-024-69236-3
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

18169

Subventions

Organisme : STI 2030-Major Project
ID : 2023ZD04069
Organisme : Guangdong laboratory of Lingnan Modern agriculture of major scientific and technological research projects
ID : NT2021001

Informations de copyright

© 2024. The Author(s).

Références

Phillips, P. C. Epistasis—The essential role of gene interactions in the structure and evolution of genetic systems. Nat. Rev. Genet. 9, 855–867 (2008).
doi: 10.1038/nrg2452 pubmed: 18852697 pmcid: 2689140
Mackay, T. F. Epistasis and quantitative traits: Using model organisms to study gene–gene interactions. Nat. Rev. Genet. 15, 22–33 (2014).
doi: 10.1038/nrg3627 pubmed: 24296533
Carlborg, O. & Haley, C. S. Epistasis: Too often neglected in complex trait studies?. Nat. Rev. Genet. 5, 618–625 (2004).
doi: 10.1038/nrg1407 pubmed: 15266344
Mackay, T. F., Stone, E. A. & Ayroles, J. F. The genetics of quantitative traits: Challenges and prospects. Nat. Rev. Genet. 10, 565–577 (2009).
doi: 10.1038/nrg2612 pubmed: 19584810
Qin, M., Zhao, X. Q., Ru, J., Zhang, G. Q. & Ye, G. Y. Bigenic epistasis between QTLs for heading date in rice analyzed using single segment substitution lines. Field Crop Res. 178, 16–25 (2015).
doi: 10.1016/j.fcr.2015.03.020
Zhu, H. T. et al. Detection and characterization of epistasis between QTLs on plant height in rice using single segment substitution lines. Breed Sci. 65, 192–200 (2015).
doi: 10.1270/jsbbs.65.192 pubmed: 26175615 pmcid: 4482168
Wang, X. L. et al. QTL epistatic analysis for yield components with single-segment substitution lines in rice. Plant Breed. 137, 346–354 (2018).
doi: 10.1111/pbr.12578
Eshed, Y. & Zamir, D. Less-than-additive epistatic interactions of yield associated QTL. Genetics 141, 1147–1162 (1996).
doi: 10.1093/genetics/141.3.1147
Zhou, H. Q. et al. Unconditional and conditional analysis of epistasis between tillering QTLs based on single segment substitution lines in rice. Sci. Rep. 10, 15912 (2020).
doi: 10.1038/s41598-020-73047-7 pubmed: 32985566 pmcid: 7523009
Luan, X. et al. Functional mapping of tillering QTLs using the Wang–Lan–Ding model and a SSSL population. Mol. Genet. Genom. 296, 1279–1286 (2021).
doi: 10.1007/s00438-021-01819-5
Bu, S. H. et al. Identification, interaction, expression, and function of QTLs on leaf numbers with single-segment substitution lines in rice. Agronomy 12, 2968 (2022).
doi: 10.3390/agronomy12122968
Huang, L. L. et al. QTL epistasis plays a role of homeostasis on heading date in rice. Sci. Rep. 14, 373–384 (2024).
doi: 10.1038/s41598-023-50786-x pubmed: 38172169 pmcid: 10764746
Lin, H. X., Yamamoto, T., Sasaki, T. & Yano, M. Characterization and detection of epistatic interactions of 3 QTLs, Hd1, Hd2, and Hd3, controlling heading date in rice using nearly isogenic lines. Theor. Appl. Genet. 101, 1021–1028 (2000).
doi: 10.1007/s001220051576
Yamamoto, T., Lin, H., Sasaki, T. & Yano, M. Identification of heading date quantitative trait locus Hd6 and characterization of its epistatic interactions with Hd2 in rice using advanced backcross progeny. Genetics 154, 885–891 (2000).
doi: 10.1093/genetics/154.2.885 pubmed: 10655238 pmcid: 1460948
Zhu, J. Mixed linear model approaches for analyzing genetic models of complex quantitative traits (supplementary issue). Hereditas 20, 137–138 (1998).
Zhu, J. Mixed model approaches of mapping genes for complex quantitative traits. J. Zhejiang Univ. 33, 327–335 (1999).
Tanksley, S. D. Mapping polygenes. Annu. Rev. Genet. 27, 205–233 (1993).
doi: 10.1146/annurev.ge.27.120193.001225 pubmed: 8122902
Zhang, G. Q. The platform of breeding by design based on the SSSL library in rice. Hereditas 41, 754–760 (2019).
pubmed: 31447426
Yang, Z. F. et al. Analysis of epistasis among QTLs on heading date based on single segment substitution lines in rice. Sci. Rep. 8, 3059 (2018).
doi: 10.1038/s41598-018-20690-w pubmed: 29449579 pmcid: 5814450
Zhang, G. Q., Zeng, R. Z., Zhang, Z. M. & Lu, Y. G. The construction of a library of single segment substitution lines in rice (Oryza sativa L.). Rice Genet. Newsl. 21, 85–87 (2004).
Xi, Z. Y. et al. Development of a wide population of chromosome single-segment substitution lines in the genetic background of an elite cultivar of rice (Oryza sativa L.). Genome 49, 476–484 (2006).
doi: 10.1139/g06-005 pubmed: 16767172

Auteurs

Yuanyuan Liu (Y)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Bihuang Zhu (B)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Jichun Tang (J)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.
Kunpeng Institute of Modern Agriculture at Foshan, Foshan, 528200, People's Republic of China.

Lilong Huang (L)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Guodong Chen (G)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Leyi Chen (L)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Suhong Bu (S)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Haitao Zhu (H)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Zupei Liu (Z)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Zhan Li (Z)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.

Lijun Meng (L)

Kunpeng Institute of Modern Agriculture at Foshan, Foshan, 528200, People's Republic of China. menglijun@caas.cn.

Guifu Liu (G)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China. guifuliu@scau.edu.cn.

Shaokui Wang (S)

Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China. shaokuiwang@scau.edu.cn.

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