Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields
Breeding for grain yield (GY) in bread wheat at the International Maize and Wheat Improvement Center (CIMMYT) involves three-stage testing at Obregon, Mexico in different selection environments (SEs). To understand the efficiency of selection in the SEs, we performed a large retrospective quantitati...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2020-08-01
|
| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fpls.2020.580136/full |
| _version_ | 1818542817175142400 |
|---|---|
| author | Philomin Juliana Ravi Prakash Singh Hans-Joachim Braun Julio Huerta-Espino Leonardo Crespo-Herrera Thomas Payne Jesse Poland Sandesh Shrestha Uttam Kumar Uttam Kumar Arun Kumar Joshi Arun Kumar Joshi Muhammad Imtiaz Mohammad Mokhlesur Rahman Fernando Henrique Toledo |
| author_facet | Philomin Juliana Ravi Prakash Singh Hans-Joachim Braun Julio Huerta-Espino Leonardo Crespo-Herrera Thomas Payne Jesse Poland Sandesh Shrestha Uttam Kumar Uttam Kumar Arun Kumar Joshi Arun Kumar Joshi Muhammad Imtiaz Mohammad Mokhlesur Rahman Fernando Henrique Toledo |
| author_sort | Philomin Juliana |
| collection | DOAJ |
| description | Breeding for grain yield (GY) in bread wheat at the International Maize and Wheat Improvement Center (CIMMYT) involves three-stage testing at Obregon, Mexico in different selection environments (SEs). To understand the efficiency of selection in the SEs, we performed a large retrospective quantitative genetics study using CIMMYT’s yield trials evaluated in the SEs (2013–2014 to 2017–2018), the South Asia Bread Wheat Genomic Prediction Yield Trials (SABWGPYTs) evaluated in India, Pakistan, and Bangladesh (2014–2015 to 2017–2018), and the Elite Spring Wheat Yield Trials (ESWYTs) evaluated in several sites globally (2003–2004 to 2016–2017). First, we compared the narrow-sense heritabilities in the Obregon SEs and target sites and observed that the mean heritability in the SEs was 44.2 and 92.3% higher than the mean heritabilities in the SABWGPYT and ESWYT sites, respectively. Second, we observed significant genetic correlations between a SE in Obregon and all the five SABWGPYT sites and 65.1% of the ESWYT sites. Third, we observed high ratios of response to indirect selection in the SEs of Obregon with a mean of 0.80 ± 0.21 and 2.6 ± 5.4 in the SABWGPYT and ESWYT sites, respectively. Furthermore, our results also indicated that for all the SABWGPYT sites and 82% of the ESWYT sites, a response greater than 0.5 can be achieved by indirect selection for GY in Obregon. We also performed genomic prediction for GY in the target sites using the performance of the same lines in the SEs of Obregon and observed moderate mean prediction accuracies of 0.24 ± 0.08 and 0.28 ± 0.08 in the SABWGPYT and ESWYT sites, respectively using the genotype x environment (GxE) model. However, we observed similar accuracies using the baseline model with environment and line effects and no advantage of modeling GxE interactions. Overall, this study provides important insights into the suitability of the Obregon SEs in breeding for GY, while the variable genomic predictabilities of GY and the high year-to-year GY fluctuations reported, highlight the importance of multi-environment testing across time and space to stave off GxE induced uncertainties in varietal yields. |
| first_indexed | 2024-12-11T22:27:07Z |
| format | Article |
| id | doaj.art-ccfa1261132444f8ad49329ac6cf8d94 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-12-11T22:27:07Z |
| publishDate | 2020-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-ccfa1261132444f8ad49329ac6cf8d942022-12-22T00:48:15ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2020-08-011110.3389/fpls.2020.580136580136Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat YieldsPhilomin Juliana0Ravi Prakash Singh1Hans-Joachim Braun2Julio Huerta-Espino3Leonardo Crespo-Herrera4Thomas Payne5Jesse Poland6Sandesh Shrestha7Uttam Kumar8Uttam Kumar9Arun Kumar Joshi10Arun Kumar Joshi11Muhammad Imtiaz12Mohammad Mokhlesur Rahman13Fernando Henrique Toledo14International Maize And Wheat Improvement Center (CIMMYT), Texcoco, MexicoInternational Maize And Wheat Improvement Center (CIMMYT), Texcoco, MexicoInternational Maize And Wheat Improvement Center (CIMMYT), Texcoco, MexicoCampo Experimental Valle de Mexico, Instituto Nacional de Investigaciones Forestales, Agricolas y Pecuarias (INIFAP), Chapingo, MexicoInternational Maize And Wheat Improvement Center (CIMMYT), Texcoco, MexicoInternational Maize And Wheat Improvement Center (CIMMYT), Texcoco, MexicoWheat Genetics Resource Center, Department of Plant Pathology, Kansas State University, Manhattan, KS, United StatesWheat Genetics Resource Center, Department of Plant Pathology, Kansas State University, Manhattan, KS, United StatesCIMMYT, New Delhi, IndiaBorlaug Institute for South Asia (BISA), New Delhi, IndiaCIMMYT, New Delhi, IndiaBorlaug Institute for South Asia (BISA), New Delhi, IndiaCIMMYT, Islamabad, PakistanRegional Agricultural Research Station, Bangladesh Agricultural Research Institute (BARI), Jamalpur, BangladeshInternational Maize And Wheat Improvement Center (CIMMYT), Texcoco, MexicoBreeding for grain yield (GY) in bread wheat at the International Maize and Wheat Improvement Center (CIMMYT) involves three-stage testing at Obregon, Mexico in different selection environments (SEs). To understand the efficiency of selection in the SEs, we performed a large retrospective quantitative genetics study using CIMMYT’s yield trials evaluated in the SEs (2013–2014 to 2017–2018), the South Asia Bread Wheat Genomic Prediction Yield Trials (SABWGPYTs) evaluated in India, Pakistan, and Bangladesh (2014–2015 to 2017–2018), and the Elite Spring Wheat Yield Trials (ESWYTs) evaluated in several sites globally (2003–2004 to 2016–2017). First, we compared the narrow-sense heritabilities in the Obregon SEs and target sites and observed that the mean heritability in the SEs was 44.2 and 92.3% higher than the mean heritabilities in the SABWGPYT and ESWYT sites, respectively. Second, we observed significant genetic correlations between a SE in Obregon and all the five SABWGPYT sites and 65.1% of the ESWYT sites. Third, we observed high ratios of response to indirect selection in the SEs of Obregon with a mean of 0.80 ± 0.21 and 2.6 ± 5.4 in the SABWGPYT and ESWYT sites, respectively. Furthermore, our results also indicated that for all the SABWGPYT sites and 82% of the ESWYT sites, a response greater than 0.5 can be achieved by indirect selection for GY in Obregon. We also performed genomic prediction for GY in the target sites using the performance of the same lines in the SEs of Obregon and observed moderate mean prediction accuracies of 0.24 ± 0.08 and 0.28 ± 0.08 in the SABWGPYT and ESWYT sites, respectively using the genotype x environment (GxE) model. However, we observed similar accuracies using the baseline model with environment and line effects and no advantage of modeling GxE interactions. Overall, this study provides important insights into the suitability of the Obregon SEs in breeding for GY, while the variable genomic predictabilities of GY and the high year-to-year GY fluctuations reported, highlight the importance of multi-environment testing across time and space to stave off GxE induced uncertainties in varietal yields.https://www.frontiersin.org/article/10.3389/fpls.2020.580136/fullwheatgrain yieldquantitative geneticsgenomic predictiongenotype x environment |
| spellingShingle | Philomin Juliana Ravi Prakash Singh Hans-Joachim Braun Julio Huerta-Espino Leonardo Crespo-Herrera Thomas Payne Jesse Poland Sandesh Shrestha Uttam Kumar Uttam Kumar Arun Kumar Joshi Arun Kumar Joshi Muhammad Imtiaz Mohammad Mokhlesur Rahman Fernando Henrique Toledo Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields Frontiers in Plant Science wheat grain yield quantitative genetics genomic prediction genotype x environment |
| title | Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields |
| title_full | Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields |
| title_fullStr | Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields |
| title_full_unstemmed | Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields |
| title_short | Retrospective Quantitative Genetic Analysis and Genomic Prediction of Global Wheat Yields |
| title_sort | retrospective quantitative genetic analysis and genomic prediction of global wheat yields |
| topic | wheat grain yield quantitative genetics genomic prediction genotype x environment |
| url | https://www.frontiersin.org/article/10.3389/fpls.2020.580136/full |
| work_keys_str_mv | AT philominjuliana retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT raviprakashsingh retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT hansjoachimbraun retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT juliohuertaespino retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT leonardocrespoherrera retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT thomaspayne retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT jessepoland retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT sandeshshrestha retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT uttamkumar retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT uttamkumar retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT arunkumarjoshi retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT arunkumarjoshi retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT muhammadimtiaz retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT mohammadmokhlesurrahman retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields AT fernandohenriquetoledo retrospectivequantitativegeneticanalysisandgenomicpredictionofglobalwheatyields |