Unravelling rubber tree growth by integrating GWAS and biological network-based approaches

Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.

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Main Authors: Francisco, Felipe Roberto, Hild Aono, Alexandre, Da Silva, Carla Cristina, Gonçalves, Paulo S., Scaloppi Junior, Erivaldo José, Le Guen, Vincent, Fritsche-Neto, Roberto, Moura Souza, Livia, Pereira de Souza, Anete
Format: article biblioteca
Language:eng
Subjects:Hevea brasiliensis, locus des caractères quantitatifs, Transcription génique, génome, phytogénétique, expression des gènes, marqueur génétique, génotype, phénotype, caoutchouc, croissance, http://aims.fao.org/aos/agrovoc/c_3589, http://aims.fao.org/aos/agrovoc/c_37974, http://aims.fao.org/aos/agrovoc/c_35128, http://aims.fao.org/aos/agrovoc/c_3224, http://aims.fao.org/aos/agrovoc/c_49985, http://aims.fao.org/aos/agrovoc/c_27527, http://aims.fao.org/aos/agrovoc/c_24030, http://aims.fao.org/aos/agrovoc/c_3225, http://aims.fao.org/aos/agrovoc/c_5776, http://aims.fao.org/aos/agrovoc/c_6678, http://aims.fao.org/aos/agrovoc/c_3394,
Online Access:http://agritrop.cirad.fr/599926/
http://agritrop.cirad.fr/599926/1/EN2660.pdf
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id dig-cirad-fr-599926
record_format koha
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic Hevea brasiliensis
locus des caractères quantitatifs
Transcription génique
génome
phytogénétique
expression des gènes
marqueur génétique
génotype
phénotype
caoutchouc
croissance
http://aims.fao.org/aos/agrovoc/c_3589
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_35128
http://aims.fao.org/aos/agrovoc/c_3224
http://aims.fao.org/aos/agrovoc/c_49985
http://aims.fao.org/aos/agrovoc/c_27527
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_6678
http://aims.fao.org/aos/agrovoc/c_3394
Hevea brasiliensis
locus des caractères quantitatifs
Transcription génique
génome
phytogénétique
expression des gènes
marqueur génétique
génotype
phénotype
caoutchouc
croissance
http://aims.fao.org/aos/agrovoc/c_3589
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_35128
http://aims.fao.org/aos/agrovoc/c_3224
http://aims.fao.org/aos/agrovoc/c_49985
http://aims.fao.org/aos/agrovoc/c_27527
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_6678
http://aims.fao.org/aos/agrovoc/c_3394
spellingShingle Hevea brasiliensis
locus des caractères quantitatifs
Transcription génique
génome
phytogénétique
expression des gènes
marqueur génétique
génotype
phénotype
caoutchouc
croissance
http://aims.fao.org/aos/agrovoc/c_3589
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_35128
http://aims.fao.org/aos/agrovoc/c_3224
http://aims.fao.org/aos/agrovoc/c_49985
http://aims.fao.org/aos/agrovoc/c_27527
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_6678
http://aims.fao.org/aos/agrovoc/c_3394
Hevea brasiliensis
locus des caractères quantitatifs
Transcription génique
génome
phytogénétique
expression des gènes
marqueur génétique
génotype
phénotype
caoutchouc
croissance
http://aims.fao.org/aos/agrovoc/c_3589
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_35128
http://aims.fao.org/aos/agrovoc/c_3224
http://aims.fao.org/aos/agrovoc/c_49985
http://aims.fao.org/aos/agrovoc/c_27527
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_6678
http://aims.fao.org/aos/agrovoc/c_3394
Francisco, Felipe Roberto
Hild Aono, Alexandre
Da Silva, Carla Cristina
Gonçalves, Paulo S.
Scaloppi Junior, Erivaldo José
Le Guen, Vincent
Fritsche-Neto, Roberto
Moura Souza, Livia
Pereira de Souza, Anete
Unravelling rubber tree growth by integrating GWAS and biological network-based approaches
description Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.
format article
topic_facet Hevea brasiliensis
locus des caractères quantitatifs
Transcription génique
génome
phytogénétique
expression des gènes
marqueur génétique
génotype
phénotype
caoutchouc
croissance
http://aims.fao.org/aos/agrovoc/c_3589
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_35128
http://aims.fao.org/aos/agrovoc/c_3224
http://aims.fao.org/aos/agrovoc/c_49985
http://aims.fao.org/aos/agrovoc/c_27527
http://aims.fao.org/aos/agrovoc/c_24030
http://aims.fao.org/aos/agrovoc/c_3225
http://aims.fao.org/aos/agrovoc/c_5776
http://aims.fao.org/aos/agrovoc/c_6678
http://aims.fao.org/aos/agrovoc/c_3394
author Francisco, Felipe Roberto
Hild Aono, Alexandre
Da Silva, Carla Cristina
Gonçalves, Paulo S.
Scaloppi Junior, Erivaldo José
Le Guen, Vincent
Fritsche-Neto, Roberto
Moura Souza, Livia
Pereira de Souza, Anete
author_facet Francisco, Felipe Roberto
Hild Aono, Alexandre
Da Silva, Carla Cristina
Gonçalves, Paulo S.
Scaloppi Junior, Erivaldo José
Le Guen, Vincent
Fritsche-Neto, Roberto
Moura Souza, Livia
Pereira de Souza, Anete
author_sort Francisco, Felipe Roberto
title Unravelling rubber tree growth by integrating GWAS and biological network-based approaches
title_short Unravelling rubber tree growth by integrating GWAS and biological network-based approaches
title_full Unravelling rubber tree growth by integrating GWAS and biological network-based approaches
title_fullStr Unravelling rubber tree growth by integrating GWAS and biological network-based approaches
title_full_unstemmed Unravelling rubber tree growth by integrating GWAS and biological network-based approaches
title_sort unravelling rubber tree growth by integrating gwas and biological network-based approaches
url http://agritrop.cirad.fr/599926/
http://agritrop.cirad.fr/599926/1/EN2660.pdf
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spelling dig-cirad-fr-5999262024-01-29T05:44:29Z http://agritrop.cirad.fr/599926/ http://agritrop.cirad.fr/599926/ Unravelling rubber tree growth by integrating GWAS and biological network-based approaches. Francisco Felipe Roberto, Hild Aono Alexandre, Da Silva Carla Cristina, Gonçalves Paulo S., Scaloppi Junior Erivaldo José, Le Guen Vincent, Fritsche-Neto Roberto, Moura Souza Livia, Pereira de Souza Anete. 2021. Frontiers in Plant Science, 12:768589, 20 p.https://doi.org/10.3389/fpls.2021.768589 <https://doi.org/10.3389/fpls.2021.768589> Unravelling rubber tree growth by integrating GWAS and biological network-based approaches Francisco, Felipe Roberto Hild Aono, Alexandre Da Silva, Carla Cristina Gonçalves, Paulo S. Scaloppi Junior, Erivaldo José Le Guen, Vincent Fritsche-Neto, Roberto Moura Souza, Livia Pereira de Souza, Anete eng 2021 Frontiers in Plant Science Hevea brasiliensis locus des caractères quantitatifs Transcription génique génome phytogénétique expression des gènes marqueur génétique génotype phénotype caoutchouc croissance http://aims.fao.org/aos/agrovoc/c_3589 http://aims.fao.org/aos/agrovoc/c_37974 http://aims.fao.org/aos/agrovoc/c_35128 http://aims.fao.org/aos/agrovoc/c_3224 http://aims.fao.org/aos/agrovoc/c_49985 http://aims.fao.org/aos/agrovoc/c_27527 http://aims.fao.org/aos/agrovoc/c_24030 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_6678 http://aims.fao.org/aos/agrovoc/c_3394 Hevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/599926/1/EN2660.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.3389/fpls.2021.768589 10.3389/fpls.2021.768589 info:eu-repo/semantics/altIdentifier/doi/10.3389/fpls.2021.768589 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.3389/fpls.2021.768589 info:eu-repo/semantics/reference/purl/https://CRAN.R-project.org/package=snpReady