Prediction of Genetic Gains from Selection in Tree Breeding
The prediction of genetic gain from artificial selection in a trait is important in plant and animal breeding. Lush’s classical breeder’s equation (BE) is widely used for this purpose, although it is also applied to predicting evolution under natural selection. The current application of high throug...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | Forests |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4907/14/3/520 |
| _version_ | 1797611705996410880 |
|---|---|
| author | Zi-Han He Yu Xiao Yan-Wen Lv Francis C. Yeh Xi Wang Xin-Sheng Hu |
| author_facet | Zi-Han He Yu Xiao Yan-Wen Lv Francis C. Yeh Xi Wang Xin-Sheng Hu |
| author_sort | Zi-Han He |
| collection | DOAJ |
| description | The prediction of genetic gain from artificial selection in a trait is important in plant and animal breeding. Lush’s classical breeder’s equation (BE) is widely used for this purpose, although it is also applied to predicting evolution under natural selection. The current application of high throughput sequencing techniques potentially allows breeders at the individual gene level to capture both additive and non-additive genetic effects. Here, we provide a comprehensive evaluation of predicting genetic gains from the selection at multiple hierarchical levels of population structure (provenances, families within provenances, and individuals within families within provenances). We discuss the processes that could influence the power of prediction under the classical BE, including genetic drift, natural selection, and gene flow. We extend the classical BE to molecular breeding methods for improving the prediction of genetic gains; they include the conventional breeding approach, marker-assistant selection (MAS), genome-wide association study (GWAS), and genomic selection (GS). Lastly, we discuss the genetic gains from the selection using multi-omics traits, including gene expression and epigenetic traits. Our overall synthesis should contribute to a better understanding of predicting genetic gains from the artificial selection under classical and molecular breeding. |
| first_indexed | 2024-03-11T06:32:30Z |
| format | Article |
| id | doaj.art-ee5ec7144b884e8b983485598e725681 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-11T06:32:30Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-ee5ec7144b884e8b983485598e7256812023-11-17T11:09:44ZengMDPI AGForests1999-49072023-03-0114352010.3390/f14030520Prediction of Genetic Gains from Selection in Tree BreedingZi-Han He0Yu Xiao1Yan-Wen Lv2Francis C. Yeh3Xi Wang4Xin-Sheng Hu5College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaCollege of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaCollege of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaDepartment of Renewable Resources, University of Alberta, 751 General Service Building, Edmonton, AB T6G 2H1, CanadaCollege of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaCollege of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, ChinaThe prediction of genetic gain from artificial selection in a trait is important in plant and animal breeding. Lush’s classical breeder’s equation (BE) is widely used for this purpose, although it is also applied to predicting evolution under natural selection. The current application of high throughput sequencing techniques potentially allows breeders at the individual gene level to capture both additive and non-additive genetic effects. Here, we provide a comprehensive evaluation of predicting genetic gains from the selection at multiple hierarchical levels of population structure (provenances, families within provenances, and individuals within families within provenances). We discuss the processes that could influence the power of prediction under the classical BE, including genetic drift, natural selection, and gene flow. We extend the classical BE to molecular breeding methods for improving the prediction of genetic gains; they include the conventional breeding approach, marker-assistant selection (MAS), genome-wide association study (GWAS), and genomic selection (GS). Lastly, we discuss the genetic gains from the selection using multi-omics traits, including gene expression and epigenetic traits. Our overall synthesis should contribute to a better understanding of predicting genetic gains from the artificial selection under classical and molecular breeding.https://www.mdpi.com/1999-4907/14/3/520breeder’s equationgenetic gainartificial selectionmolecular breedingmarker-assistant selection |
| spellingShingle | Zi-Han He Yu Xiao Yan-Wen Lv Francis C. Yeh Xi Wang Xin-Sheng Hu Prediction of Genetic Gains from Selection in Tree Breeding Forests breeder’s equation genetic gain artificial selection molecular breeding marker-assistant selection |
| title | Prediction of Genetic Gains from Selection in Tree Breeding |
| title_full | Prediction of Genetic Gains from Selection in Tree Breeding |
| title_fullStr | Prediction of Genetic Gains from Selection in Tree Breeding |
| title_full_unstemmed | Prediction of Genetic Gains from Selection in Tree Breeding |
| title_short | Prediction of Genetic Gains from Selection in Tree Breeding |
| title_sort | prediction of genetic gains from selection in tree breeding |
| topic | breeder’s equation genetic gain artificial selection molecular breeding marker-assistant selection |
| url | https://www.mdpi.com/1999-4907/14/3/520 |
| work_keys_str_mv | AT zihanhe predictionofgeneticgainsfromselectionintreebreeding AT yuxiao predictionofgeneticgainsfromselectionintreebreeding AT yanwenlv predictionofgeneticgainsfromselectionintreebreeding AT franciscyeh predictionofgeneticgainsfromselectionintreebreeding AT xiwang predictionofgeneticgainsfromselectionintreebreeding AT xinshenghu predictionofgeneticgainsfromselectionintreebreeding |