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Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers

BACKGROUND: The identification of lines resistant to ear diseases is of great importance in maize breeding because such diseases directly interfere with kernel quality and yield. Among these diseases, ear rot disease is widely relevant due to significant decrease in grain yield. Ear rot may be cause...

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Autores principales: dos Santos, Jhonathan Pedroso Rigal, Pires, Luiz Paulo Miranda, de Castro Vasconcellos, Renato Coelho, Pereira, Gabriela Santos, Von Pinho, Renzo Garcia, Balestre, Marcio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912722/
https://www.ncbi.nlm.nih.gov/pubmed/27316946
http://dx.doi.org/10.1186/s12863-016-0392-3
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author dos Santos, Jhonathan Pedroso Rigal
Pires, Luiz Paulo Miranda
de Castro Vasconcellos, Renato Coelho
Pereira, Gabriela Santos
Von Pinho, Renzo Garcia
Balestre, Marcio
author_facet dos Santos, Jhonathan Pedroso Rigal
Pires, Luiz Paulo Miranda
de Castro Vasconcellos, Renato Coelho
Pereira, Gabriela Santos
Von Pinho, Renzo Garcia
Balestre, Marcio
author_sort dos Santos, Jhonathan Pedroso Rigal
collection PubMed
description BACKGROUND: The identification of lines resistant to ear diseases is of great importance in maize breeding because such diseases directly interfere with kernel quality and yield. Among these diseases, ear rot disease is widely relevant due to significant decrease in grain yield. Ear rot may be caused by the fungus Stenocarpella maydi; however, little information about genetic resistance to this pathogen is available in maize, mainly related to candidate genes in genome. In order to exploit this genome information we used 23.154 Dart-seq markers in 238 lines and apply genome-wide selection to select resistance genotypes. We divide the lines into clusters to identify groups related to resistance to Stenocarpella maydi and use Bayesian stochastic search variable approach and rr-BLUP methods to comparate their selection results. RESULTS: Through a principal component analysis (PCA) and hierarchical clustering, it was observed that the three main genetic groups (Stiff Stalk Synthetic, Non-Stiff Stalk Synthetic and Tropical) were clustered in a consistent manner, and information on the resistance sources could be obtained according to the line of origin where populations derived from genetic subgroup Suwan presenting higher levels of resistance. The ridge regression best linear unbiased prediction (rr-BLUP) and Bayesian stochastic search variable (BSSV) models presented equivalent abilities regarding predictive processes. CONCLUSION: Our work showed that is possible to select maize lines presenting a high resistance to Stenocarpella maydis. This claim is based on the acceptable level of predictive accuracy obtained by Genome-wide Selection (GWS) using different models. Furthermore, the lines related to background Suwan present a higher level of resistance than lines related to other groups. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-016-0392-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-49127222016-06-19 Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers dos Santos, Jhonathan Pedroso Rigal Pires, Luiz Paulo Miranda de Castro Vasconcellos, Renato Coelho Pereira, Gabriela Santos Von Pinho, Renzo Garcia Balestre, Marcio BMC Genet Research Article BACKGROUND: The identification of lines resistant to ear diseases is of great importance in maize breeding because such diseases directly interfere with kernel quality and yield. Among these diseases, ear rot disease is widely relevant due to significant decrease in grain yield. Ear rot may be caused by the fungus Stenocarpella maydi; however, little information about genetic resistance to this pathogen is available in maize, mainly related to candidate genes in genome. In order to exploit this genome information we used 23.154 Dart-seq markers in 238 lines and apply genome-wide selection to select resistance genotypes. We divide the lines into clusters to identify groups related to resistance to Stenocarpella maydi and use Bayesian stochastic search variable approach and rr-BLUP methods to comparate their selection results. RESULTS: Through a principal component analysis (PCA) and hierarchical clustering, it was observed that the three main genetic groups (Stiff Stalk Synthetic, Non-Stiff Stalk Synthetic and Tropical) were clustered in a consistent manner, and information on the resistance sources could be obtained according to the line of origin where populations derived from genetic subgroup Suwan presenting higher levels of resistance. The ridge regression best linear unbiased prediction (rr-BLUP) and Bayesian stochastic search variable (BSSV) models presented equivalent abilities regarding predictive processes. CONCLUSION: Our work showed that is possible to select maize lines presenting a high resistance to Stenocarpella maydis. This claim is based on the acceptable level of predictive accuracy obtained by Genome-wide Selection (GWS) using different models. Furthermore, the lines related to background Suwan present a higher level of resistance than lines related to other groups. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-016-0392-3) contains supplementary material, which is available to authorized users. BioMed Central 2016-06-18 /pmc/articles/PMC4912722/ /pubmed/27316946 http://dx.doi.org/10.1186/s12863-016-0392-3 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
dos Santos, Jhonathan Pedroso Rigal
Pires, Luiz Paulo Miranda
de Castro Vasconcellos, Renato Coelho
Pereira, Gabriela Santos
Von Pinho, Renzo Garcia
Balestre, Marcio
Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers
title Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers
title_full Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers
title_fullStr Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers
title_full_unstemmed Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers
title_short Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers
title_sort genomic selection to resistance to stenocarpella maydis in maize lines using dartseq markers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912722/
https://www.ncbi.nlm.nih.gov/pubmed/27316946
http://dx.doi.org/10.1186/s12863-016-0392-3
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