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Breedbase: a digital ecosystem for modern plant breeding

Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-dr...

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Autores principales: Morales, Nicolas, Ogbonna, Alex C, Ellerbrock, Bryan J, Bauchet, Guillaume J, Tantikanjana, Titima, Tecle, Isaak Y, Powell, Adrian F, Lyon, David, Menda, Naama, Simoes, Christiano C, Saha, Surya, Hosmani, Prashant, Flores, Mirella, Panitz, Naftali, Preble, Ryan S, Agbona, Afolabi, Rabbi, Ismail, Kulakow, Peter, Peteti, Prasad, Kawuki, Robert, Esuma, Williams, Kanaabi, Micheal, Chelangat, Doreen M, Uba, Ezenwanyi, Olojede, Adeyemi, Onyeka, Joseph, Shah, Trushar, Karanja, Margaret, Egesi, Chiedozie, Tufan, Hale, Paterne, Agre, Asfaw, Asrat, Jannink, Jean-Luc, Wolfe, Marnin, Birkett, Clay L, Waring, David J, Hershberger, Jenna M, Gore, Michael A, Robbins, Kelly R, Rife, Trevor, Courtney, Chaney, Poland, Jesse, Arnaud, Elizabeth, Laporte, Marie-Angélique, Kulembeka, Heneriko, Salum, Kasele, Mrema, Emmanuel, Brown, Allan, Bayo, Stanley, Uwimana, Brigitte, Akech, Violet, Yencho, Craig, de Boeck, Bert, Campos, Hugo, Swennen, Rony, Edwards, Jeremy D, Mueller, Lukas A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258556/
https://www.ncbi.nlm.nih.gov/pubmed/35385099
http://dx.doi.org/10.1093/g3journal/jkac078
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author Morales, Nicolas
Ogbonna, Alex C
Ellerbrock, Bryan J
Bauchet, Guillaume J
Tantikanjana, Titima
Tecle, Isaak Y
Powell, Adrian F
Lyon, David
Menda, Naama
Simoes, Christiano C
Saha, Surya
Hosmani, Prashant
Flores, Mirella
Panitz, Naftali
Preble, Ryan S
Agbona, Afolabi
Rabbi, Ismail
Kulakow, Peter
Peteti, Prasad
Kawuki, Robert
Esuma, Williams
Kanaabi, Micheal
Chelangat, Doreen M
Uba, Ezenwanyi
Olojede, Adeyemi
Onyeka, Joseph
Shah, Trushar
Karanja, Margaret
Egesi, Chiedozie
Tufan, Hale
Paterne, Agre
Asfaw, Asrat
Jannink, Jean-Luc
Wolfe, Marnin
Birkett, Clay L
Waring, David J
Hershberger, Jenna M
Gore, Michael A
Robbins, Kelly R
Rife, Trevor
Courtney, Chaney
Poland, Jesse
Arnaud, Elizabeth
Laporte, Marie-Angélique
Kulembeka, Heneriko
Salum, Kasele
Mrema, Emmanuel
Brown, Allan
Bayo, Stanley
Uwimana, Brigitte
Akech, Violet
Yencho, Craig
de Boeck, Bert
Campos, Hugo
Swennen, Rony
Edwards, Jeremy D
Mueller, Lukas A
author_facet Morales, Nicolas
Ogbonna, Alex C
Ellerbrock, Bryan J
Bauchet, Guillaume J
Tantikanjana, Titima
Tecle, Isaak Y
Powell, Adrian F
Lyon, David
Menda, Naama
Simoes, Christiano C
Saha, Surya
Hosmani, Prashant
Flores, Mirella
Panitz, Naftali
Preble, Ryan S
Agbona, Afolabi
Rabbi, Ismail
Kulakow, Peter
Peteti, Prasad
Kawuki, Robert
Esuma, Williams
Kanaabi, Micheal
Chelangat, Doreen M
Uba, Ezenwanyi
Olojede, Adeyemi
Onyeka, Joseph
Shah, Trushar
Karanja, Margaret
Egesi, Chiedozie
Tufan, Hale
Paterne, Agre
Asfaw, Asrat
Jannink, Jean-Luc
Wolfe, Marnin
Birkett, Clay L
Waring, David J
Hershberger, Jenna M
Gore, Michael A
Robbins, Kelly R
Rife, Trevor
Courtney, Chaney
Poland, Jesse
Arnaud, Elizabeth
Laporte, Marie-Angélique
Kulembeka, Heneriko
Salum, Kasele
Mrema, Emmanuel
Brown, Allan
Bayo, Stanley
Uwimana, Brigitte
Akech, Violet
Yencho, Craig
de Boeck, Bert
Campos, Hugo
Swennen, Rony
Edwards, Jeremy D
Mueller, Lukas A
author_sort Morales, Nicolas
collection PubMed
description Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem.
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spelling pubmed-92585562022-07-07 Breedbase: a digital ecosystem for modern plant breeding Morales, Nicolas Ogbonna, Alex C Ellerbrock, Bryan J Bauchet, Guillaume J Tantikanjana, Titima Tecle, Isaak Y Powell, Adrian F Lyon, David Menda, Naama Simoes, Christiano C Saha, Surya Hosmani, Prashant Flores, Mirella Panitz, Naftali Preble, Ryan S Agbona, Afolabi Rabbi, Ismail Kulakow, Peter Peteti, Prasad Kawuki, Robert Esuma, Williams Kanaabi, Micheal Chelangat, Doreen M Uba, Ezenwanyi Olojede, Adeyemi Onyeka, Joseph Shah, Trushar Karanja, Margaret Egesi, Chiedozie Tufan, Hale Paterne, Agre Asfaw, Asrat Jannink, Jean-Luc Wolfe, Marnin Birkett, Clay L Waring, David J Hershberger, Jenna M Gore, Michael A Robbins, Kelly R Rife, Trevor Courtney, Chaney Poland, Jesse Arnaud, Elizabeth Laporte, Marie-Angélique Kulembeka, Heneriko Salum, Kasele Mrema, Emmanuel Brown, Allan Bayo, Stanley Uwimana, Brigitte Akech, Violet Yencho, Craig de Boeck, Bert Campos, Hugo Swennen, Rony Edwards, Jeremy D Mueller, Lukas A G3 (Bethesda) Software and Data Resources Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem. Oxford University Press 2022-04-06 /pmc/articles/PMC9258556/ /pubmed/35385099 http://dx.doi.org/10.1093/g3journal/jkac078 Text en © The Author(s) 2022. 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 (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 Software and Data Resources
Morales, Nicolas
Ogbonna, Alex C
Ellerbrock, Bryan J
Bauchet, Guillaume J
Tantikanjana, Titima
Tecle, Isaak Y
Powell, Adrian F
Lyon, David
Menda, Naama
Simoes, Christiano C
Saha, Surya
Hosmani, Prashant
Flores, Mirella
Panitz, Naftali
Preble, Ryan S
Agbona, Afolabi
Rabbi, Ismail
Kulakow, Peter
Peteti, Prasad
Kawuki, Robert
Esuma, Williams
Kanaabi, Micheal
Chelangat, Doreen M
Uba, Ezenwanyi
Olojede, Adeyemi
Onyeka, Joseph
Shah, Trushar
Karanja, Margaret
Egesi, Chiedozie
Tufan, Hale
Paterne, Agre
Asfaw, Asrat
Jannink, Jean-Luc
Wolfe, Marnin
Birkett, Clay L
Waring, David J
Hershberger, Jenna M
Gore, Michael A
Robbins, Kelly R
Rife, Trevor
Courtney, Chaney
Poland, Jesse
Arnaud, Elizabeth
Laporte, Marie-Angélique
Kulembeka, Heneriko
Salum, Kasele
Mrema, Emmanuel
Brown, Allan
Bayo, Stanley
Uwimana, Brigitte
Akech, Violet
Yencho, Craig
de Boeck, Bert
Campos, Hugo
Swennen, Rony
Edwards, Jeremy D
Mueller, Lukas A
Breedbase: a digital ecosystem for modern plant breeding
title Breedbase: a digital ecosystem for modern plant breeding
title_full Breedbase: a digital ecosystem for modern plant breeding
title_fullStr Breedbase: a digital ecosystem for modern plant breeding
title_full_unstemmed Breedbase: a digital ecosystem for modern plant breeding
title_short Breedbase: a digital ecosystem for modern plant breeding
title_sort breedbase: a digital ecosystem for modern plant breeding
topic Software and Data Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258556/
https://www.ncbi.nlm.nih.gov/pubmed/35385099
http://dx.doi.org/10.1093/g3journal/jkac078
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