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林业科学 ›› 2021, Vol. 57 ›› Issue (6): 64-73.doi: 10.11707/j.1001-7488.20210607

• 论文与研究报告 • 上一篇    下一篇

基于BLUP和GGE双标图的黑杨派无性系生长性状基因型与环境互作效应

李金花   

  1. 林木遗传育种国家重点实验室 国家林业和草原局林木培育重点实验室 中国林业科学研究院林业研究所 北京 100091
  • 收稿日期:2021-01-04 出版日期:2021-06-25 发布日期:2021-08-06
  • 基金资助:
    国家重点研发计划课题"杨树、泡桐、刺槐丰产增效技术集成与示范"(2017YFD0601203)

Genotype by Environment Interaction for Growth Traits of Clones of Populus Section Aigeiros Based on BLUP and GGE Biplot

Jinhua Li   

  1. State Key Laboratory of Tree Genetics and Breeding Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration Research Institute of Forestry, Chinese Academy of Forestry Beijing 100091
  • Received:2021-01-04 Online:2021-06-25 Published:2021-08-06

摘要:

目的: 基于BLUP和GGE双标图分析法综合评价多试验点区域化试验黑杨派无性系(品种)的速生性、稳定性和各试验地点的区分力、代表性,可为黑杨派引种无性系的选择和应用提供理论依据。方法: 对位于北京、河北和山东的9个试验地点15个黑杨派引种无性系(品种)进行生长性状测定,使用ASReml-R程序包拟合误差异质的线性混合效应模型,通过最佳线性无偏预测(BLUP)法获得各无性系在各试验点6年生胸径和树高BLUP数据,进行GGE双标图分析,对无性系和试验地点进行评价。结果: 基于胸径和树高BLUP数据GGE双标图分析的前2个主成分(PC1和PC2)的方差解释百分比为84.69%和69.83%。基于胸径BLUP数据GGE双标图显示,9个试验点之间均存在正相关关系,被分为2组:河北永清和山东金乡为一组,胸径最大的无性系为50;其余7个试验点为另一组,胸径最大的无性系为Por。区分力最好的地点为北京昌平和河北永清,代表性最好的地点为山东宁阳(高桥)和河北魏县。对于无性系高产性和稳产性,Por胸径最大,Pa、36、108、50、111和107的胸径均大于均值,而Og的胸径接近总体均值,La胸径最小;107、Me、108、Br、Og和36稳定性较好。结论: 胸径与树高BLUP-GGE双标图存在差异,胸径BLUP-GGE双标图较树高的可靠;无性系Por速生性突出,其次是Pa、36、108、50、111和107,稳定性较好的无性系为107、Me、108、Br、Og和36,速生性和稳定性均较强的无性系为Por、Pa、36、108和107。

关键词: 黑杨派, 多点区域试验, 线性混合模型, 最佳线性无偏预测(BLUP), GGE双标图, 基因型与环境互作

Abstract:

Objective: The aim of this study was to evaluate growth and stability of clones (varieties) of Populus Section Aigeiros, and discrimination and representativeness of each trial sites of the regional clonal trials based on BLUP and GGE (genotype main effect plus genotype-environmental interaction effect) biplot,and provide the theoretical basis for selection and application of the introduced clones. Method: DBH and height of 15 clones at 9 trial sites were measured at age of 6 years,linear mixed models (LMM) with site as fixed effect and clone,clone by site interaction as random effects were to be used for best linear unbiased prediction (BLUP) analysis. Then BLUP data of DBH and height for each clone at each site were obtained to conduct GGE biplot for evaluating these introduced clones and regional trial sites. Result: The first two principal components (PC1 and PC2) of GGE biplot explain respectively 84.69% and 69.83% of the variance based on BLUP data of DBH and height. GGE bioplot based on BLUP data of DBH showed that the 9 trial sites were positively correlated with each other. The 9 trial sites were divided into 2 groups: Yongqing of Hebei and Jinxiang of Shandong in a group,with the largest DBH of clone 50,and the other 7 sites in another group,with the largest DBH of clone Por. Changping of Beijing and Yongqing of Hebei were the most discriminative sites,while Ningyang (Gaoqiao) of Shandong and Weixian of Hebei were the most representative sites. The clone Por had the largest DBH,followed by the clones Pa,36,108,50,111,and 107,all of which were larger than the average. The clone Og had a DBH close to the average,and the clone La showed the smallest DBH,the clones 107,Me,108,Br,Og and 36 displayed a better stability. Conclusion: GGE biplots based on BLUP data of DBH and height were different,and the GGE biplots of DBH were more reliable than that of height. The clone Por had the largest DBH followed by Pa,36,108,50,111 and 107. The clones 107,Me,108,Br,Og and 36 showed a better stability with DBH. Comprehensively,the clones Por,Pa,36,108 and 107 showed both better stability and fast growth.

Key words: Populus Section Aigeiros, multi-environmental regional trial (MET), linear mixed model (LMM), best linear unbiased predication (BLUP), genotype main effect plus genotype-environment interaction effect (GGE) biplot, genotype by environment interaction (GEI)

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