Cargando…

Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design

With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single-nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in out...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Yuhua, Wu, Hainan, Yang, Wenguo, Zhao, Wei, Tong, Chunfa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022933/
https://www.ncbi.nlm.nih.gov/pubmed/33604666
http://dx.doi.org/10.1093/g3journal/jkaa053
_version_ 1783675029682126848
author Chen, Yuhua
Wu, Hainan
Yang, Wenguo
Zhao, Wei
Tong, Chunfa
author_facet Chen, Yuhua
Wu, Hainan
Yang, Wenguo
Zhao, Wei
Tong, Chunfa
author_sort Chen, Yuhua
collection PubMed
description With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single-nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated with ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F(1) hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated with the tree height under the P-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but two chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore showed that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.
format Online
Article
Text
id pubmed-8022933
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-80229332021-04-09 Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design Chen, Yuhua Wu, Hainan Yang, Wenguo Zhao, Wei Tong, Chunfa G3 (Bethesda) Investigation With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single-nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated with ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F(1) hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated with the tree height under the P-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but two chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore showed that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus. Oxford University Press 2021-01-05 /pmc/articles/PMC8022933/ /pubmed/33604666 http://dx.doi.org/10.1093/g3journal/jkaa053 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Investigation
Chen, Yuhua
Wu, Hainan
Yang, Wenguo
Zhao, Wei
Tong, Chunfa
Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design
title Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design
title_full Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design
title_fullStr Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design
title_full_unstemmed Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design
title_short Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design
title_sort multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design
topic Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022933/
https://www.ncbi.nlm.nih.gov/pubmed/33604666
http://dx.doi.org/10.1093/g3journal/jkaa053
work_keys_str_mv AT chenyuhua multivariatelinearmixedmodelenhancedthepowerofidentifyinggenomewideassociationtopoplartreeheightsinarandomizedcompleteblockdesign
AT wuhainan multivariatelinearmixedmodelenhancedthepowerofidentifyinggenomewideassociationtopoplartreeheightsinarandomizedcompleteblockdesign
AT yangwenguo multivariatelinearmixedmodelenhancedthepowerofidentifyinggenomewideassociationtopoplartreeheightsinarandomizedcompleteblockdesign
AT zhaowei multivariatelinearmixedmodelenhancedthepowerofidentifyinggenomewideassociationtopoplartreeheightsinarandomizedcompleteblockdesign
AT tongchunfa multivariatelinearmixedmodelenhancedthepowerofidentifyinggenomewideassociationtopoplartreeheightsinarandomizedcompleteblockdesign