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Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection
Cacao (Theobroma cacao) is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches’ broom disease (WBD) and frosty pod rot disease (FPRD), are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri, respec...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5890178/ https://www.ncbi.nlm.nih.gov/pubmed/29662497 http://dx.doi.org/10.3389/fpls.2018.00343 |
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author | McElroy, Michel S. Navarro, Alberto J. R. Mustiga, Guiliana Stack, Conrad Gezan, Salvador Peña, Geover Sarabia, Widem Saquicela, Diego Sotomayor, Ignacio Douglas, Gavin M. Migicovsky, Zoë Amores, Freddy Tarqui, Omar Myles, Sean Motamayor, Juan C. |
author_facet | McElroy, Michel S. Navarro, Alberto J. R. Mustiga, Guiliana Stack, Conrad Gezan, Salvador Peña, Geover Sarabia, Widem Saquicela, Diego Sotomayor, Ignacio Douglas, Gavin M. Migicovsky, Zoë Amores, Freddy Tarqui, Omar Myles, Sean Motamayor, Juan C. |
author_sort | McElroy, Michel S. |
collection | PubMed |
description | Cacao (Theobroma cacao) is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches’ broom disease (WBD) and frosty pod rot disease (FPRD), are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri, respectively. Resistant cultivars are the most effective long-term strategy to address Moniliophthora diseases, but efficiently generating resistant and productive new cultivars will require robust methods for screening germplasm before field testing. Marker-assisted selection (MAS) and genomic selection (GS) provide two potential avenues for predicting the performance of new genotypes, potentially increasing the selection gain per unit time. To test the effectiveness of these two approaches, we performed a genome-wide association study (GWAS) and GS on three related populations of cacao in Ecuador genotyped with a 15K single nucleotide polymorphism (SNP) microarray for three measures of WBD infection (vegetative broom, cushion broom, and chirimoya pod), one of FPRD (monilia pod) and two productivity traits (total fresh weight of pods and % healthy pods produced). GWAS yielded several SNPs associated with disease resistance in each population, but none were significantly correlated with the same trait in other populations. Genomic selection, using one population as a training set to estimate the phenotypes of the remaining two (composed of different families), varied among traits, from a mean prediction accuracy of 0.46 (vegetative broom) to 0.15 (monilia pod), and varied between training populations. Simulations demonstrated that selecting seedlings using GWAS markers alone generates no improvement over selecting at random, but that GS improves the selection process significantly. Our results suggest that the GWAS markers discovered here are not sufficiently predictive across diverse germplasm to be useful for MAS, but that using all markers in a GS framework holds substantial promise in accelerating disease-resistance in cacao. |
format | Online Article Text |
id | pubmed-5890178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58901782018-04-16 Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection McElroy, Michel S. Navarro, Alberto J. R. Mustiga, Guiliana Stack, Conrad Gezan, Salvador Peña, Geover Sarabia, Widem Saquicela, Diego Sotomayor, Ignacio Douglas, Gavin M. Migicovsky, Zoë Amores, Freddy Tarqui, Omar Myles, Sean Motamayor, Juan C. Front Plant Sci Plant Science Cacao (Theobroma cacao) is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches’ broom disease (WBD) and frosty pod rot disease (FPRD), are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri, respectively. Resistant cultivars are the most effective long-term strategy to address Moniliophthora diseases, but efficiently generating resistant and productive new cultivars will require robust methods for screening germplasm before field testing. Marker-assisted selection (MAS) and genomic selection (GS) provide two potential avenues for predicting the performance of new genotypes, potentially increasing the selection gain per unit time. To test the effectiveness of these two approaches, we performed a genome-wide association study (GWAS) and GS on three related populations of cacao in Ecuador genotyped with a 15K single nucleotide polymorphism (SNP) microarray for three measures of WBD infection (vegetative broom, cushion broom, and chirimoya pod), one of FPRD (monilia pod) and two productivity traits (total fresh weight of pods and % healthy pods produced). GWAS yielded several SNPs associated with disease resistance in each population, but none were significantly correlated with the same trait in other populations. Genomic selection, using one population as a training set to estimate the phenotypes of the remaining two (composed of different families), varied among traits, from a mean prediction accuracy of 0.46 (vegetative broom) to 0.15 (monilia pod), and varied between training populations. Simulations demonstrated that selecting seedlings using GWAS markers alone generates no improvement over selecting at random, but that GS improves the selection process significantly. Our results suggest that the GWAS markers discovered here are not sufficiently predictive across diverse germplasm to be useful for MAS, but that using all markers in a GS framework holds substantial promise in accelerating disease-resistance in cacao. Frontiers Media S.A. 2018-03-20 /pmc/articles/PMC5890178/ /pubmed/29662497 http://dx.doi.org/10.3389/fpls.2018.00343 Text en Copyright © 2018 McElroy, Navarro, Mustiga, Stack, Gezan, Peña, Sarabia, Saquicela, Sotomayor, Douglas, Migicovsky, Amores, Tarqui, Myles and Motamayor. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science McElroy, Michel S. Navarro, Alberto J. R. Mustiga, Guiliana Stack, Conrad Gezan, Salvador Peña, Geover Sarabia, Widem Saquicela, Diego Sotomayor, Ignacio Douglas, Gavin M. Migicovsky, Zoë Amores, Freddy Tarqui, Omar Myles, Sean Motamayor, Juan C. Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection |
title | Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection |
title_full | Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection |
title_fullStr | Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection |
title_full_unstemmed | Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection |
title_short | Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection |
title_sort | prediction of cacao (theobroma cacao) resistance to moniliophthora spp. diseases via genome-wide association analysis and genomic selection |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5890178/ https://www.ncbi.nlm.nih.gov/pubmed/29662497 http://dx.doi.org/10.3389/fpls.2018.00343 |
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