Implications of accounting for marker-based population structure in the quantitative genetic evaluation of genetic parameters related to growth and wood properties in Norway spruce
Hayatgheibi, Haleh; Hallingbäck, Henrik R.; Lundqvist, Sven-Olof; Grahn, Thomas; Scheepers, Gerhard; Nordström, Peter; Chen, Zhi-Qiang; Kärkkäinen, Katri; Wu, Harry X.; García-Gil, M. Rosario (2024)
Lataukset
Hayatgheibi, Haleh
Hallingbäck, Henrik R.
Lundqvist, Sven-Olof
Grahn, Thomas
Scheepers, Gerhard
Nordström, Peter
Chen, Zhi-Qiang
Kärkkäinen, Katri
Wu, Harry X.
García-Gil, M. Rosario
Julkaisusarja
BMC Genomic Data
Volyymi
25
Numero
1
Sivut
14 p.
Springer Science and Business Media LLC
2024
Julkaisun pysyvä osoite on
http://urn.fi/URN:NBN:fi-fe2024101680640
http://urn.fi/URN:NBN:fi-fe2024101680640
Tiivistelmä
Background
Forest geneticists typically use provenances to account for population differences in their improvement schemes; however, the historical records of the imported materials might not be very precise or well-aligned with the genetic clusters derived from advanced molecular techniques. The main objective of this study was to assess the impact of marker-based population structure on genetic parameter estimates related to growth and wood properties and their trade-offs in Norway spruce, by either incorporating it as a fixed effect (model-B) or excluding it entirely from the analysis (model-A).
Results
Our results indicate that models incorporating population structure significantly reduce estimates of additive genetic variance, resulting in substantial reduction of narrow-sense heritability. However, these models considerably improve prediction accuracies. This was particularly significant for growth and solid-wood properties, which showed to have the highest population genetic differentiation (QST) among the studied traits. Additionally, although the pattern of correlations remained similar across the models, their magnitude was slightly lower for models that included population structure as a fixed effect. This suggests that selection, consistently performed within populations, might be less affected by unfavourable genetic correlations compared to mass selection conducted without pedigree restrictions.
Conclusion
We conclude that the results of models properly accounting for population structure are more accurate and less biased compared to those neglecting this effect. This might have practical implications for breeders and forest managers where, decisions based on imprecise selections can pose a high risk to economic efficiency.
Forest geneticists typically use provenances to account for population differences in their improvement schemes; however, the historical records of the imported materials might not be very precise or well-aligned with the genetic clusters derived from advanced molecular techniques. The main objective of this study was to assess the impact of marker-based population structure on genetic parameter estimates related to growth and wood properties and their trade-offs in Norway spruce, by either incorporating it as a fixed effect (model-B) or excluding it entirely from the analysis (model-A).
Results
Our results indicate that models incorporating population structure significantly reduce estimates of additive genetic variance, resulting in substantial reduction of narrow-sense heritability. However, these models considerably improve prediction accuracies. This was particularly significant for growth and solid-wood properties, which showed to have the highest population genetic differentiation (QST) among the studied traits. Additionally, although the pattern of correlations remained similar across the models, their magnitude was slightly lower for models that included population structure as a fixed effect. This suggests that selection, consistently performed within populations, might be less affected by unfavourable genetic correlations compared to mass selection conducted without pedigree restrictions.
Conclusion
We conclude that the results of models properly accounting for population structure are more accurate and less biased compared to those neglecting this effect. This might have practical implications for breeders and forest managers where, decisions based on imprecise selections can pose a high risk to economic efficiency.
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- Julkaisut [86778]