Genomic prediction for canopy height and dry matter yield in alfalfa using family bulks. Issue 3 (11th July 2022)
- Record Type:
- Journal Article
- Title:
- Genomic prediction for canopy height and dry matter yield in alfalfa using family bulks. Issue 3 (11th July 2022)
- Main Title:
- Genomic prediction for canopy height and dry matter yield in alfalfa using family bulks
- Authors:
- Murad Leite Andrade, Mario Henrique
Acharya, Janam P.
Benevenuto, Juliana
de Bem Oliveira, Ivone
Lopez, Yolanda
Munoz, Patricio
Resende, Marcio F. R.
Rios, Esteban F. - Abstract:
- Abstract: Genomic selection (GS) has proven to be an effective method to increase genetic gain rates and accelerate breeding cycles in many crop species. However, its implementation requires large investments to phenotype of the training population and for routine genotyping. Alfalfa ( Medicago sativa L.) is one of the major cultivated forage legumes, showing high‐quality nutritional value. Alfalfa breeding is usually carried out by phenotypic recurrent selection and is commonly done at the family level. The application of GS in alfalfa could be simplified and less costly by genotyping and phenotyping families in bulks. For this study, an alfalfa reference population composed of 142 full‐sib and 35 half‐sib families was bulk‐genotyped using target enrichment sequencing and phenotyped for dry matter yield (DMY) and canopy height (CH) in Florida, USA. Genotyping of the family bulks with 17, 707 targeted probes resulted in 114, 945 single‐nucleotide polymorphisms. The markers revealed a population structure that matched the mating design, and the linkage disequilibrium slowly decayed in this breeding population. After exploring multiple prediction scenarios, a strategy was proposed including data from multiple harvests and accounting for the G×E in the training population, which led to a higher predictive ability of up to 38 and 24% for DMY and CH, respectively. Although this study focused on the implementation of GS in alfalfa families, the bulk methodology and the predictionAbstract: Genomic selection (GS) has proven to be an effective method to increase genetic gain rates and accelerate breeding cycles in many crop species. However, its implementation requires large investments to phenotype of the training population and for routine genotyping. Alfalfa ( Medicago sativa L.) is one of the major cultivated forage legumes, showing high‐quality nutritional value. Alfalfa breeding is usually carried out by phenotypic recurrent selection and is commonly done at the family level. The application of GS in alfalfa could be simplified and less costly by genotyping and phenotyping families in bulks. For this study, an alfalfa reference population composed of 142 full‐sib and 35 half‐sib families was bulk‐genotyped using target enrichment sequencing and phenotyped for dry matter yield (DMY) and canopy height (CH) in Florida, USA. Genotyping of the family bulks with 17, 707 targeted probes resulted in 114, 945 single‐nucleotide polymorphisms. The markers revealed a population structure that matched the mating design, and the linkage disequilibrium slowly decayed in this breeding population. After exploring multiple prediction scenarios, a strategy was proposed including data from multiple harvests and accounting for the G×E in the training population, which led to a higher predictive ability of up to 38 and 24% for DMY and CH, respectively. Although this study focused on the implementation of GS in alfalfa families, the bulk methodology and the prediction schemes used herein could guide future studies in alfalfa and other crops bred in bulks. Core Ideas: Application of genomic selection in alfalfa could be facilitated and less costly using family bulks. Target enrichment sequencing generated 114, 945 single‐nucleotide polymorphisms. Alfalfa families were bulk‐genotyped/phenotyped for dry matter yield and canopy height. Low to moderate predictive abilities were obtained for dry matter yield and canopy height. Accounting for G×E by the inclusion of multi‐harvest data increased the predictive ability. … (more)
- Is Part Of:
- plant genome. Volume 15:Issue 3(2022)
- Journal:
- plant genome
- Issue:
- Volume 15:Issue 3(2022)
- Issue Display:
- Volume 15, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 15
- Issue:
- 3
- Issue Sort Value:
- 2022-0015-0003-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-07-11
- Subjects:
- Plant genomes -- Periodicals
Plant genome mapping -- Periodicals
572.862 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
https://acsess.onlinelibrary.wiley.com/journal/19403372 ↗ - DOI:
- 10.1002/tpg2.20235 ↗
- Languages:
- English
- ISSNs:
- 1940-3372
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23209.xml