Genomics-Enabled Management of Genetic Resources in Radiata Pine
Traditional tree improvement is cumbersome and costly. Our main objective was to assess the extent to which genomic data can currently accelerate and improve decision making in this field. We used diameter at breast height (DBH) and wood density (WD) data for 4430 tree genotypes and single-nucleotid...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Forests |
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| Online Access: | https://www.mdpi.com/1999-4907/13/2/282 |
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| author | Jaroslav Klápště Ahmed Ismael Mark Paget Natalie J. Graham Grahame T. Stovold Heidi S. Dungey Gancho T. Slavov |
| author_facet | Jaroslav Klápště Ahmed Ismael Mark Paget Natalie J. Graham Grahame T. Stovold Heidi S. Dungey Gancho T. Slavov |
| author_sort | Jaroslav Klápště |
| collection | DOAJ |
| description | Traditional tree improvement is cumbersome and costly. Our main objective was to assess the extent to which genomic data can currently accelerate and improve decision making in this field. We used diameter at breast height (DBH) and wood density (WD) data for 4430 tree genotypes and single-nucleotide polymorphism (SNP) data for 2446 tree genotypes. Pedigree reconstruction was performed using a combination of maximum likelihood parentage assignment and matching based on identity-by-state (IBS) similarity. In addition, we used best linear unbiased prediction (BLUP) methods to predict phenotypes using SNP markers (GBLUP), recorded pedigree information (ABLUP), and single-step “blended” BLUP (HBLUP) combining SNP and pedigree information. We substantially improved the accuracy of pedigree records, resolving the inconsistent parental information of 506 tree genotypes. This led to substantially increased predictive ability (i.e., by up to 87%) in HBLUP analyses compared to a baseline from ABLUP. Genomic prediction was possible across populations and within previously untested families with moderately large training populations (<i>N</i> = 800–1200 tree genotypes) and using as few as 2000–5000 SNP markers. HBLUP was generally more effective than traditional ABLUP approaches, particularly after dealing appropriately with pedigree uncertainties. Our study provides evidence that genome-wide marker data can significantly enhance tree improvement. The operational implementation of genomic selection has started in radiata pine breeding in New Zealand, but further reductions in DNA extraction and genotyping costs may be required to realise the full potential of this approach. |
| first_indexed | 2024-03-09T21:57:03Z |
| format | Article |
| id | doaj.art-c0b75d943a3047558f48f0b4f4fbc779 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-09T21:57:03Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-c0b75d943a3047558f48f0b4f4fbc7792023-11-23T19:57:04ZengMDPI AGForests1999-49072022-02-0113228210.3390/f13020282Genomics-Enabled Management of Genetic Resources in Radiata PineJaroslav Klápště0Ahmed Ismael1Mark Paget2Natalie J. Graham3Grahame T. Stovold4Heidi S. Dungey5Gancho T. Slavov6Scion (New Zealand Forest Research Institute Ltd.), Private Bag 3020, Rotorua 3010, New ZealandScion (New Zealand Forest Research Institute Ltd.), Private Bag 3020, Rotorua 3010, New ZealandRadiata Pine Breeding Company, 99 Sala Street, Rotorua 3010, New ZealandScion (New Zealand Forest Research Institute Ltd.), Private Bag 3020, Rotorua 3010, New ZealandScion (New Zealand Forest Research Institute Ltd.), Private Bag 3020, Rotorua 3010, New ZealandScion (New Zealand Forest Research Institute Ltd.), Private Bag 3020, Rotorua 3010, New ZealandScion (New Zealand Forest Research Institute Ltd.), Private Bag 3020, Rotorua 3010, New ZealandTraditional tree improvement is cumbersome and costly. Our main objective was to assess the extent to which genomic data can currently accelerate and improve decision making in this field. We used diameter at breast height (DBH) and wood density (WD) data for 4430 tree genotypes and single-nucleotide polymorphism (SNP) data for 2446 tree genotypes. Pedigree reconstruction was performed using a combination of maximum likelihood parentage assignment and matching based on identity-by-state (IBS) similarity. In addition, we used best linear unbiased prediction (BLUP) methods to predict phenotypes using SNP markers (GBLUP), recorded pedigree information (ABLUP), and single-step “blended” BLUP (HBLUP) combining SNP and pedigree information. We substantially improved the accuracy of pedigree records, resolving the inconsistent parental information of 506 tree genotypes. This led to substantially increased predictive ability (i.e., by up to 87%) in HBLUP analyses compared to a baseline from ABLUP. Genomic prediction was possible across populations and within previously untested families with moderately large training populations (<i>N</i> = 800–1200 tree genotypes) and using as few as 2000–5000 SNP markers. HBLUP was generally more effective than traditional ABLUP approaches, particularly after dealing appropriately with pedigree uncertainties. Our study provides evidence that genome-wide marker data can significantly enhance tree improvement. The operational implementation of genomic selection has started in radiata pine breeding in New Zealand, but further reductions in DNA extraction and genotyping costs may be required to realise the full potential of this approach.https://www.mdpi.com/1999-4907/13/2/282tree breedingpedigree reconstructiongenomic selectiongenomic predictionsingle-step BLUP<i>Pinus radiata</i> |
| spellingShingle | Jaroslav Klápště Ahmed Ismael Mark Paget Natalie J. Graham Grahame T. Stovold Heidi S. Dungey Gancho T. Slavov Genomics-Enabled Management of Genetic Resources in Radiata Pine Forests tree breeding pedigree reconstruction genomic selection genomic prediction single-step BLUP <i>Pinus radiata</i> |
| title | Genomics-Enabled Management of Genetic Resources in Radiata Pine |
| title_full | Genomics-Enabled Management of Genetic Resources in Radiata Pine |
| title_fullStr | Genomics-Enabled Management of Genetic Resources in Radiata Pine |
| title_full_unstemmed | Genomics-Enabled Management of Genetic Resources in Radiata Pine |
| title_short | Genomics-Enabled Management of Genetic Resources in Radiata Pine |
| title_sort | genomics enabled management of genetic resources in radiata pine |
| topic | tree breeding pedigree reconstruction genomic selection genomic prediction single-step BLUP <i>Pinus radiata</i> |
| url | https://www.mdpi.com/1999-4907/13/2/282 |
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