杉木Cunninghamia lanceolata是中国南方重要的商品用材和碳汇造林树种。本研究以广东杉木33个第三代全同胞家系在不同生长地点的8年生径向生长表现(胸径)为基础开展多地点方差分析。结果表明，家系适生性遗传差异大(P<0.01)，且地点、区组及地点与家系间的互作效应显著。采用基于个体模型的BLUP分析法计算每个试验地点参试家系的个体育种值，可将参试家系适生性进行初步划分，并筛选出个体育种值水平较高、适生性好的家系(家系1、4、13和31)。在此基础上，运用GGE双标图分析法进一步获得参试家系“哪个赢在哪里”功能图、不同家系高产性与稳产性结论、理想家系选择列表，发现家系1、4、13、31和其他家系适生性评价结果与BLUP分析结果基本一致，具有较好的分析效果。
WANG Run-hui
,
HU De-huo
,
WEI Ru-ping
,
YAN Shu
,
WU Guan-di
,
HUANG Rong
,
ZHENG Hui-quan
. 基于BLUP育种值与GGE双标图分析杉木第三代全同胞家系生长性状的适生性[J]. 亚热带植物科学, 2023
, 52(1)
: 43
-49
.
DOI: 10.3969/j.issn.1009-7791.2023.01.007
Cunninghamia lanceolata is an important commercial timber and carbon sequestration tree species in south China. Based on the diameter at breast height (DBH) of 33 third-generation full-sib families of C. lanceolata from Guangdong at multiple tested sites and the multi-site ANOVAs approach, we identified a significant difference (P<0.01) of the genetic adaption in families. While, the site and block effects and the site×family interaction effect seemed to be profound. Regarding this, best linear unbiased prediction (BLUP) based on individual model was carried out to calculate the individual breeding value of the families in each experimental site. The obtained result highlighted the preliminarily separation of the families according to their adaptability and the superior families with higher individual breeding value and adaptability (e.g. families 1, 4, 13 and 31). Further genotype main effect plus genotype-by-environment interaction (GGE) biplot analysis directly gave ‘who won where’ functional diagram, high yield and stable families graph and ideal families selection result that highly agreed with that of BLUP’s, indicating a consistency of these two methods and their forecasting power.
[1] 怀特 T. L., 亚当斯 W. T., 尼尔 D. B (崔建国, 李火根译). 森林遗传学[M]. 北京: 科学出版社, 2013.
[2] Finlay K W, Wilkinson G N. The analysis of adaptation in a plant breeding program [J]. Australian Journal of Agricultural Research, 1963, 14(6): 742–754.
[3] Gauch H G, Zobel R W. Identifying mega-environments and targeting genotypes [J]. Crop Science, 1997, 37(2): 311–326.
[4] Yan W. GGE biplot: a Windows application for graphical analysis of multi-environment trial data and other types of two-way data [J]. Agronomy Journal, 2001, 93(5): 1111–1118.
[5] Ding M, Tier B, Yan W, Wu H X, Powell M B, McRAE T A. Application of GGE biplot analysis to evaluate genotype (G), environment (E) and G×E interaction on Pinus radiata: a case of study [J]. New Zealand Journal for Science, 2008, 38(1): 132–142.
[6] 郑聪慧, 张鸿景, 王玉忠, 代剑锋, 党磊, 杜子春, 刘建婷, 高运茹. 基于BLUP和GGE双标图的华北落叶松家系区域试验分析[J]. 林业科学, 2019, 55 (8): 73–83.
[7] Hortensia S, Jordi S, Marcos B, Ma P C, Isabel C. Genetic variation and genotype–environment interactions in short rotation Populus, plantations in southern Europe [J]. New Forests, 2011, 42(2): 163–177.
[8] Wang R H, Hu D H, Zheng H Q, Yan S, Wei R P. Genotype × environmental interaction by AMMI and GGE biplot analysis for the provenances of Michelia chapensis in South China [J]. Journal of Forest Research, 2016, 27(3): 659–664.
[9] 程玲, 张心菲, 张鑫鑫, 张卫华, 林元震. 基于BLUP和GGE双标图的林木多地点试验分析[J]. 西北农林科技大学学报: 自然科学版, 2018, 46(3): 87–93.
[10] 黄荣, 胡德活, 邓厚银, 王润辉, 韦如萍, 晏姝, 郑会全. 利用SNP标记解析速生优质杉木群体的遗传多样性与结构[J/OL]. 分子植物育种, 2021. https://kns.cnki.net/kcms/detail/ 46.1068.S.20211130.1703.012.html
[11] 王润辉, 胡德活, 韦如萍, 晏姝, 郑会全. 杉木育种亲本生长和结实性状早期测评与选择[J]. 热带亚热带植物学报, 2022, 30(2): 195–201.
[12] 林元震, 陈晓阳. R与Asreml–R统计分析教程[M]. 北京: 中国林业出版社, 2014.
[13] 郭敏杰, 邓丽, 任丽, 谷建中. 基于R语言的AMMI和GGE双标图在花生区试中的应用[J]. 花生学报, 2017, 46(2): 24–31.
[14] 艾斯克 F., 霍兰德 J., 蒙特卡 C (林元震, 丁昌俊译). 动植物育种遗传数据分析[M].北京: 科技出版社, 2019.
[15] 严威凯. 双标图分析在农作物品种多点试验中的应用[J]. 作物学报, 2010, 36(11): 1805–1819.
[16] 林元震. R与ASReml-R统计学[M]. 北京: 中国林业出版社, 2016.
[17] Marcio B, Vanderley B S, Antonio A S, Moisés S R. Stability and adaptability of upland rice genotypes [J]. Crop Breeding and Applied Biotechnology, 2010, 10(4): 357–363.
[18] 李金花. 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[J]. 林业科学, 2021, 57(6): 64–73.
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