Identifying and testing marker-trait associations for growth and phenology in three pine species: Implications for genomic prediction
| Autor: | Witold Wachowiak, Joan Cottrell, Stephen Cavers, Glenn R. Iason, Annika Perry, Joan K. Beaton |
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| Rok vydání: | 2021 |
| Předmět: |
Phenology
media_common.quotation_subject Single-nucleotide polymorphism Biology biology.organism_classification Ecology and Environment predictive model quantitative trait Pinus mugo Evolutionary biology marker–trait association Genotype genetic variation Trait Genetics Scots pine Reproduction common garden trial General Agricultural and Biological Sciences SNP array Gene Genotyping Ecology Evolution Behavior and Systematics local adaptation media_common |
| Zdroj: | Perry, A, Wachowiak, W, Beaton, J, Iason, G, Cottrell, J & Cavers, S 2022, ' Identifying and testing marker–trait associations for growth and phenology in three pine species : Implications for genomic prediction ', Evolutionary Applications, vol. 15, no. 2, pp. 330-348 . https://doi.org/10.1111/eva.13345 |
| ISSN: | 1752-4571 |
| DOI: | 10.1111/eva.13345 |
| Popis: | In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 SNPs from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments. |
| Databáze: | OpenAIRE |
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