Patterns of additive genotype-by-environment interaction in tree height of Norway spruce in southern and central Sweden

详细信息    查看全文

• 作者：Zhi-Qiang Chen ; Bo Karlsson ; Harry X. Wu
• 关键词：Picea abies ; Factor analysis ; MET ; Cluster analysis ; G × E interaction
• 刊名：Tree Genetics & Genomes
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：13
• 期：1
• 全文大小：1996KB
• 刊物主题：Forestry; Plant Genetics & Genomics; Plant Breeding/Biotechnology; Tree Biology; Biotechnology;
• 出版者：Springer Berlin Heidelberg
• ISSN：1614-2950
• 卷排序：13

文摘

Genotype-by-environment (G × E) interaction for tree height measured at ages 7 to 13 was investigated in 20 large open-pollinated progeny trials for Norway spruce (Picea abies (L.) H. Karst.) in southern and central Sweden. Factor analytic method using spatially adjusted data and a reduced animal model was used to explore the pattern of G × E interaction. Extended factor analyses captured 93.0% of additive G × E interaction variances using three factors. The mean daily temperature less than 3.2 °C in May and June explained 27.8% G × E interaction, and it was moderately correlated with the first factor, indicating that spring or autumn frost weather condition could be a main driver for G × E interaction in Norway spruce. Cluster analysis has divided 20 trials into either 6 clusters or 3 clusters. Both sets of clusters reflected the geography of the trials (climates) and the genetic connectedness among testing series, indicating that more trials with better connectedness are required to examine whether current delineation of breeding or seed zones is optimal. Parental stability using latent regression could be used to locate best parents that have the highest breeding values and are highly stable across trials.