Replication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize
Fusarium stalk rot (FSR) poses a threat to maize cultivation around the world. Phenotypic selection to improve FSR resistance cannot meet this challenge alone. Genome-wide association studies (GWAS) and genomic prediction (GP) can also help to uncover genetic determinants of FSR resistance that could be used in breeding. This study provides genotypic and phenotypic data from 562 tropical maize inbred lines that were used to perform GWAS and GP analyses for two populations. The FSR severity is presented in the phenotypic data files. The measurement details and results of the analysis are presented in the accompanying journal article.
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Format: | Experimental data biblioteca |
Language: | English |
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CIMMYT Research Data & Software Repository Network
2024
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Subjects: | Agricultural Sciences, Fusarium Stalk Rot Incidence, Maize, Agricultural research, Genomic selection, Zea mays, Plant Breeding, |
Online Access: | https://hdl.handle.net/11529/10549066 |
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dat-cimmyt-11529105490662024-05-22T01:00:06ZReplication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maizehttps://hdl.handle.net/11529/10549066Song, JunqiaoLiu, YuboGuo, RuiPacheca, ÁngelaMuñoz-Zavala, CarlosSong, WeiWang, HuiCao, ShiliangHu, GuanghuiZheng, HongjianDhliwayo, ThandaSan Vicente, FelixPrasanna, Boddupalli M.Wang, ChunpingZhang, XuecaiCIMMYT Research Data & Software Repository NetworkFusarium stalk rot (FSR) poses a threat to maize cultivation around the world. Phenotypic selection to improve FSR resistance cannot meet this challenge alone. Genome-wide association studies (GWAS) and genomic prediction (GP) can also help to uncover genetic determinants of FSR resistance that could be used in breeding. This study provides genotypic and phenotypic data from 562 tropical maize inbred lines that were used to perform GWAS and GP analyses for two populations. The FSR severity is presented in the phenotypic data files. The measurement details and results of the analysis are presented in the accompanying journal article.Agricultural SciencesFusarium Stalk Rot IncidenceMaizeAgricultural researchGenomic selectionZea maysPlant BreedingEnglish2024Dreher, KateCGIARCGIAR Research Program on Maize (MAIZE)Global Maize Program (GMP)Bill and Melinda Gates Foundation (BMGF)United States Agency for International Development (USAID)Foundation for Agricultural Research (FFAR)Shennong LaboratoryOneCGIAR Initiative on Accelerated BreedingAccelerating Genetic Gains in Maize and Wheat for Improved Livelihoods (AGG)Experimental dataGenotypic dataPhenotypic data |
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MX |
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biblioteca |
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America del Norte |
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Centro Internacional de Mejoramiento de Maíz y Trigo |
language |
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Agricultural Sciences Fusarium Stalk Rot Incidence Maize Agricultural research Genomic selection Zea mays Plant Breeding Agricultural Sciences Fusarium Stalk Rot Incidence Maize Agricultural research Genomic selection Zea mays Plant Breeding |
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Agricultural Sciences Fusarium Stalk Rot Incidence Maize Agricultural research Genomic selection Zea mays Plant Breeding Agricultural Sciences Fusarium Stalk Rot Incidence Maize Agricultural research Genomic selection Zea mays Plant Breeding Song, Junqiao Liu, Yubo Guo, Rui Pacheca, Ángela Muñoz-Zavala, Carlos Song, Wei Wang, Hui Cao, Shiliang Hu, Guanghui Zheng, Hongjian Dhliwayo, Thanda San Vicente, Felix Prasanna, Boddupalli M. Wang, Chunping Zhang, Xuecai Replication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize |
description |
Fusarium stalk rot (FSR) poses a threat to maize cultivation around the world. Phenotypic selection to improve FSR resistance cannot meet this challenge alone. Genome-wide association studies (GWAS) and genomic prediction (GP) can also help to uncover genetic determinants of FSR resistance that could be used in breeding.
This study provides genotypic and phenotypic data from 562 tropical maize inbred lines that were used to perform GWAS and GP analyses for two populations. The FSR severity is presented in the phenotypic data files. The measurement details and results of the analysis are presented in the accompanying journal article. |
author2 |
Dreher, Kate |
author_facet |
Dreher, Kate Song, Junqiao Liu, Yubo Guo, Rui Pacheca, Ángela Muñoz-Zavala, Carlos Song, Wei Wang, Hui Cao, Shiliang Hu, Guanghui Zheng, Hongjian Dhliwayo, Thanda San Vicente, Felix Prasanna, Boddupalli M. Wang, Chunping Zhang, Xuecai |
format |
Experimental data |
topic_facet |
Agricultural Sciences Fusarium Stalk Rot Incidence Maize Agricultural research Genomic selection Zea mays Plant Breeding |
author |
Song, Junqiao Liu, Yubo Guo, Rui Pacheca, Ángela Muñoz-Zavala, Carlos Song, Wei Wang, Hui Cao, Shiliang Hu, Guanghui Zheng, Hongjian Dhliwayo, Thanda San Vicente, Felix Prasanna, Boddupalli M. Wang, Chunping Zhang, Xuecai |
author_sort |
Song, Junqiao |
title |
Replication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize |
title_short |
Replication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize |
title_full |
Replication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize |
title_fullStr |
Replication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize |
title_full_unstemmed |
Replication Data for: Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize |
title_sort |
replication data for: exploiting genomic tools for genetic dissection and improving the resistance to fusarium stalk rot in tropical maize |
publisher |
CIMMYT Research Data & Software Repository Network |
publishDate |
2024 |
url |
https://hdl.handle.net/11529/10549066 |
work_keys_str_mv |
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