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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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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. |
format | Online Article Text |
id | pubmed-4912722 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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