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Li Z, Tirado SB, Kadam DC, Coffey L, Miller ND, Spalding EP, Lorenz AJ, de Leon N, Kaeppler SM, Schnable PS, Springer NM, Hirsch CN. Correction to: Characterizing introgression‑by‑environment interactions using maize near isogenic lines. Theor Appl Genet 2021; 134:4077. [PMID: 34668979 DOI: 10.1007/s00122-021-03959-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Affiliation(s)
- Zhi Li
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
| | - Sara B Tirado
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
- Department of Plant and Microbial Biology, University of Minnesota, 1479 Gortner Avenue, Saint Paul, MN, 55108, USA
| | - Dnyaneshwar C Kadam
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
| | - Lisa Coffey
- Department of Agronomy, Iowa State University, 1111 WOI Rd, Ames, IA, 50011, USA
| | - Nathan D Miller
- Department of Botany, University of Wisconsin, 430 Lincoln Drive, Madison, WI, 53706, USA
| | - Edgar P Spalding
- Department of Botany, University of Wisconsin, 430 Lincoln Drive, Madison, WI, 53706, USA
| | - Aaron J Lorenz
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
| | - Natalia de Leon
- Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, WI, 53706, USA
| | - Shawn M Kaeppler
- Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, WI, 53706, USA
| | - Patrick S Schnable
- Department of Agronomy, Iowa State University, 1111 WOI Rd, Ames, IA, 50011, USA
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, 1479 Gortner Avenue, Saint Paul, MN, 55108, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA.
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Kadam DC, Rodriguez OR, Lorenz AJ. Optimization of training sets for genomic prediction of early-stage single crosses in maize. Theor Appl Genet 2021; 134:687-699. [PMID: 33398385 DOI: 10.1007/s00122-020-03722-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 11/03/2020] [Indexed: 06/12/2023]
Abstract
Training population optimization algorithms are useful for efficiently training genomic prediction models for single-cross performance, especially if the population is extended beyond only realized crosses to all possible single crosses. Genomic prediction of single-cross performance could allow effective evaluation of all possible single crosses between all inbreds developed in a hybrid breeding program. The objectives of the present study were to investigate the effect of different levels of relatedness on genomic predictive ability of single crosses, evaluate the usefulness of deterministic formula to forecast prediction accuracy in advance, and determine the potential for TRS optimization based on prediction error variance (PEVmean) and coefficient of determination (CDmean) criteria. We used 481 single crosses made by crossing 89 random recombinant inbred lines (RILs) belonging to the Iowa stiff stalk synthetic group with 103 random RILs belonging to the non-stiff stalk synthetic heterotic group. As expected, predictive ability was enhanced by ensuring close relationships between TRSs and target sets, even when TRS sizes were smaller. We found that designing a TRS based on PEVmean or CDmean criteria is useful for increasing the efficiency of genomic prediction of maize single crosses. We went further and extended the sampling space from that of all observed single crosses to all possible single crosses, providing a much larger genetic space within which to design a training population. Using all possible single crosses increased the advantage of the PEVmean and CDmean methods based on expected prediction accuracy. This finding suggests that it may be worthwhile using an optimization algorithm to select a training population from all possible single crosses to maximize efficiency in training accurate models for hybrid genomic prediction.
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Affiliation(s)
- Dnyaneshwar C Kadam
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Oscar R Rodriguez
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, 68583, USA
| | - Aaron J Lorenz
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
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Li Z, Tirado SB, Kadam DC, Coffey L, Miller ND, Spalding EP, Lorenz AJ, de Leon N, Kaeppler SM, Schnable PS, Springer NM, Hirsch CN. Characterizing introgression-by-environment interactions using maize near isogenic lines. Theor Appl Genet 2020; 133:2761-2773. [PMID: 32572549 DOI: 10.1007/s00122-020-03630-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 06/02/2020] [Indexed: 06/11/2023]
Abstract
Significant introgression-by-environment interactions are observed for traits throughout development from small introgressed segments of the genome. Relatively small genomic introgressions containing quantitative trait loci can have significant impacts on the phenotype of an individual plant. However, the magnitude of phenotypic effects for the same introgression can vary quite substantially in different environments due to introgression-by-environment interactions. To study potential patterns of introgression-by-environment interactions, fifteen near-isogenic lines (NILs) with > 90% B73 genetic background and multiple Mo17 introgressions were grown in 16 different environments. These environments included five geographical locations with multiple planting dates and multiple planting densities. The phenotypic impact of the introgressions was evaluated for up to 26 traits that span different growth stages in each environment to assess introgression-by-environment interactions. Results from this study showed that small portions of the genome can drive significant genotype-by-environment interaction across a wide range of vegetative and reproductive traits, and the magnitude of the introgression-by-environment interaction varies across traits. Some introgressed segments were more prone to introgression-by-environment interaction than others when evaluating the interaction on a whole plant basis throughout developmental time, indicating variation in phenotypic plasticity throughout the genome. Understanding the profile of introgression-by-environment interaction in NILs is useful in consideration of how small introgressions of QTL or transgene containing regions might be expected to impact traits in diverse environments.
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Affiliation(s)
- Zhi Li
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
| | - Sara B Tirado
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
- Department of Plant and Microbial Biology, University of Minnesota, 1479 Gortner Avenue, Saint Paul, MN, 55108, USA
| | - Dnyaneshwar C Kadam
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
| | - Lisa Coffey
- Department of Agronomy, Iowa State University, 1111 WOI Rd, Ames, IA, 50011, USA
| | - Nathan D Miller
- Department of Botany, University of Wisconsin, 430 Lincoln Drive, Madison, WI, 53706, USA
| | - Edgar P Spalding
- Department of Botany, University of Wisconsin, 430 Lincoln Drive, Madison, WI, 53706, USA
| | - Aaron J Lorenz
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
| | - Natalia de Leon
- Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, WI, 53706, USA
| | - Shawn M Kaeppler
- Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, WI, 53706, USA
| | - Patrick S Schnable
- Department of Agronomy, Iowa State University, 1111 WOI Rd, Ames, IA, 50011, USA
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, 1479 Gortner Avenue, Saint Paul, MN, 55108, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA.
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Kadam DC, Potts SM, Bohn MO, Lipka AE, Lorenz AJ. Genomic Prediction of Single Crosses in the Early Stages of a Maize Hybrid Breeding Pipeline. G3 (Bethesda) 2016; 6:3443-3453. [PMID: 27646704 PMCID: PMC5100843 DOI: 10.1534/g3.116.031286] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Accepted: 08/12/2016] [Indexed: 11/18/2022]
Abstract
Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objectives of this study were to evaluate the potential of genomic prediction for identifying superior single crosses early in the hybrid breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single crosses representing the Iowa Stiff Stalk synthetic/non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The performance of single crosses was predicted using parental combining ability and covariance among single crosses. Prediction accuracies were estimated using cross-validation and ranged from 0.28 to 0.77 for grain yield, 0.53 to 0.91 for plant height, and 0.49 to 0.94 for staygreen, depending on the number of tested parents of the single cross and genomic prediction method used. The genomic estimated general and specific combining abilities showed an advantage over genomic covariances among single crosses when one or both parents of the single cross were untested. Overall, our results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to redesign hybrid breeding and increase its efficiency.
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Affiliation(s)
- Dnyaneshwar C Kadam
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, Nebraska 68583
| | - Sarah M Potts
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Martin O Bohn
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Aaron J Lorenz
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, Nebraska 68583
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