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Loladze A, Rodrigues F, Petroli CD, Muñoz-Zavala C, Naranjo S, Vicente FS, Gerard B, Montesinos-Lopez OA, Crossa J, Martini JW. Multispectral and thermal infrared data, visual scores for severity of common rust symptoms, and genotypic single nucleotide polymorphism data of three F2-derived biparental doubled-haploid maize populations. Data Brief 2024; 54:110300. [PMID: 38586147 PMCID: PMC10997887 DOI: 10.1016/j.dib.2024.110300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 04/09/2024] Open
Abstract
Three F2-derived biparental doubled haploid (DH) maize populations were generated for genetic mapping of resistance to common rust. Each of the three populations has the same susceptible parent, but a different resistance donor parent. Population 1 and 3 consist of 320 lines each, population 2 consists of 260 lines. The DH lines were evaluated for their susceptibility to common rust in two years and with two replications in each year. For phenotyping, a visual score (VS) for susceptibility was assigned. Additionally, unmanned aerial vehicle (UAV) derived multispectral and thermal infrared data was recorded and combined in different vegetation indices ("remote sensing", RS). The DH lines were genotyped with the DarTseq method, to obtain data on single nucleotide polymorphisms (SNPs). After quality control, 9051 markers remained. Missing values were "imputed" by the empirical mean of the marker scores of the respective locus. We used the data for comparison of genome-wide association studies and genomic prediction when based on different phenotyping methods, that is either VS or RS data. The data may be interesting for reuse for instance for benchmarking genomic prediction models, for phytopathological studies addressing common rust, or for specifications of vegetation indices.
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Affiliation(s)
| | | | - Cesar D. Petroli
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
| | | | - Sergio Naranjo
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
| | | | - Bruno Gerard
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
- College of Agriculture and Environmental Sciences (CAES), University Mohammed VI Polytechnic (UM6P), Ben Guerir, Morocco
| | | | - Jose Crossa
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
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Loladze A, Rodrigues FA, Petroli CD, Muñoz-Zavala C, Naranjo S, San Vicente F, Gerard B, Montesinos-Lopez OA, Crossa J, Martini JW. Use of remote sensing for linkage mapping and genomic prediction for common rust resistance in maize. Field Crops Res 2024; 308:109281. [PMID: 38495466 PMCID: PMC10933745 DOI: 10.1016/j.fcr.2024.109281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 11/24/2023] [Accepted: 01/28/2024] [Indexed: 03/19/2024]
Abstract
Breeding for disease resistance is a central component of strategies implemented to mitigate biotic stress impacts on crop yield. Conventionally, genotypes of a plant population are evaluated through a labor-intensive process of assigning visual scores (VS) of susceptibility (or resistance) by specifically trained staff, which limits manageable volumes and repeatability of evaluation trials. Remote sensing (RS) tools have the potential to streamline phenotyping processes and to deliver more standardized results at higher through-put. Here, we use a two-year evaluation trial of three newly developed biparental populations of maize doubled haploid lines (DH) to compare the results of genomic analyses of resistance to common rust (CR) when phenotyping is either based on conventional VS or on RS-derived (vegetation) indices. As a general observation, for each population × year combination, the broad sense heritability of VS was greater than or very close to the maximum heritability across all RS indices. Moreover, results of linkage mapping as well as of genomic prediction (GP), suggest that VS data was of a higher quality, indicated by higher - log p values in the linkage studies and higher predictive abilities for genomic prediction. Nevertheless, despite the qualitative differences between the phenotyping methods, each successfully identified the same genomic region on chromosome 10 as being associated with disease resistance. This region is likely related to the known CR resistance locus Rp1. Our results indicate that RS technology can be used to streamline genetic evaluation processes for foliar disease resistance in maize. In particular, RS can potentially reduce costs of phenotypic evaluations and increase trialing capacities.
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Affiliation(s)
| | | | - Cesar D. Petroli
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
| | | | - Sergio Naranjo
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
| | | | - Bruno Gerard
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
- College of Agriculture and Environmental Sciences (CAES), University Mohammed VI Polytechnic (UM6P), Ben Guerir, Morocco
| | | | - Jose Crossa
- International Maize and Wheat Improvement Center – CIMMYT, Mexico
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Resende MDV, Resende MFR, Sansaloni CP, Petroli CD, Missiaggia AA, Aguiar AM, Abad JM, Takahashi EK, Rosado AM, Faria DA, Pappas GJ, Kilian A, Grattapaglia D. Genomic selection for growth and wood quality in Eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees. New Phytol 2012; 194:116-128. [PMID: 22309312 DOI: 10.1111/j.1469-8137.2011.04038.x] [Citation(s) in RCA: 89] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
• Genomic selection (GS) is expected to cause a paradigm shift in tree breeding by improving its speed and efficiency. By fitting all the genome-wide markers concurrently, GS can capture most of the 'missing heritability' of complex traits that quantitative trait locus (QTL) and association mapping classically fail to explain. Experimental support of GS is now required. • The effectiveness of GS was assessed in two unrelated Eucalyptus breeding populations with contrasting effective population sizes (N(e) = 11 and 51) genotyped with > 3000 DArT markers. Prediction models were developed for tree circumference and height growth, wood specific gravity and pulp yield using random regression best linear unbiased predictor (BLUP). • Accuracies of GS varied between 0.55 and 0.88, matching the accuracies achieved by conventional phenotypic selection. Substantial proportions (74-97%) of trait heritability were captured by fitting all genome-wide markers simultaneously. Genomic regions explaining trait variation largely coincided between populations, although GS models predicted poorly across populations, likely as a result of variable patterns of linkage disequilibrium, inconsistent allelic effects and genotype × environment interaction. • GS brings a new perspective to the understanding of quantitative trait variation in forest trees and provides a revolutionary tool for applied tree improvement. Nevertheless population-specific predictive models will likely drive the initial applications of GS in forest tree breeding.
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Affiliation(s)
- Marcos D V Resende
- EMBRAPA Forestry Research, Colombo, PR, 83411-000, Brazil
- Universidade Federal de Viçosa - Viçosa MG, 36570-000, Brazil
| | | | - Carolina P Sansaloni
- EMBRAPA Genetic Resources and Biotechnology - EPqB, 70770-910, Brasilia, DF, Brazil
- Universidade de Brasilia - Campus Darcy Ribeiro Brasília, DF, 70910-900, Brazil
| | - Cesar D Petroli
- EMBRAPA Genetic Resources and Biotechnology - EPqB, 70770-910, Brasilia, DF, Brazil
- Universidade de Brasilia - Campus Darcy Ribeiro Brasília, DF, 70910-900, Brazil
| | - Alexandre A Missiaggia
- FIBRIA Celulose S.A., Rod. Aracruz/Barra do Riacho, km 25, Aracruz, ES, 29197-900, Brazil
| | - Aurelio M Aguiar
- FIBRIA Celulose S.A., Rod. Aracruz/Barra do Riacho, km 25, Aracruz, ES, 29197-900, Brazil
| | - Jupiter M Abad
- FIBRIA Celulose S.A., Rod. Aracruz/Barra do Riacho, km 25, Aracruz, ES, 29197-900, Brazil
| | | | - Antonio M Rosado
- CENIBRA Celulose Nipo Brasileira S.A, Belo Oriente, MG, 35196-000, Brazil
| | - Danielle A Faria
- EMBRAPA Genetic Resources and Biotechnology - EPqB, 70770-910, Brasilia, DF, Brazil
| | - Georgios J Pappas
- EMBRAPA Genetic Resources and Biotechnology - EPqB, 70770-910, Brasilia, DF, Brazil
- Universidade Catolica de Brasília- SGAN, 916 modulo B, Brasilia, DF, 70790-160, Brazil
| | - Andrzej Kilian
- DArT - Diversity Arrays Technology, POB 7141, Yarralumla, ACT, Australia 2600
| | - Dario Grattapaglia
- EMBRAPA Genetic Resources and Biotechnology - EPqB, 70770-910, Brasilia, DF, Brazil
- Universidade Catolica de Brasília- SGAN, 916 modulo B, Brasilia, DF, 70790-160, Brazil
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