云南松材用种质保存库的构建策略及检验
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摘要
为探讨云南松(Pinus yunnanensis Franch.)材用种质保存库构建的抽样策略并获得代表性子集,在其全分布区内选择26个代表性种群,每个种群选择30株样株组成原种质集,并选取18个表型性状测定值作为种质保存库的源数据。在此基础上,以地理种群分组,根据不加权类平均聚类分析结果进行取样;设定抽样比例分别为10%、20%、30%和40%,采用多样性指数法和改进的最小距离逐步取样法构建种质子集,并采用5个评价参数和主成分分析对不同抽样比例种质子集进行综合评价和确认。结果表明:各种质子集与原种质集18个表型性状的均值t检验均无显著差异;而40%、30%、20%和10%抽样比例种质子集分别有11、14、15和12个表型性状的方差总体上大于原种质集且差异显著,说明各种质子集表型性状的取值分散程度总体上大于原种质集。通过χ~2检验,40%、30%和20%抽样比例种质子集与原种质集18个表型性状的频率分布均无显著差异,而10%抽样比例种质子集仅有2个表型性状的频率分布与原种质集分别存在极显著和显著差异。在原种质集和4个种质子集中,不同等级样株的分布频率基本相同,但随抽样比例降低,1级、9级和10级的样株比例逐渐增大,说明在构建种质保存库时,应适当增加极端样株的比例。4个种质子集各表型性状的Shannon-Weaver遗传多样性指数(H′)普遍高于原种质集,且随抽样比例下降H′值总体增大;其中,20%抽样比例种质子集与原种质集表型性状的H′均值存在极显著差异,30%和10%抽样比例种质子集与原种质集表型性状的H′均值存在显著差异。综合评价结果表明:10%、20%、30%和40%抽样比例种质子集均可代表原种质集,其中,20%抽样比例种质子集可客观地代表原种质集的表型遗传多样性,且该种质子集的5个评价参数值综合效应优于其他种质子集。主成分分析结果表明:按照20%抽样比例构建的种质保存库能够解释的表型遗传信息量大于原种质集,且既保留了大量分布外缘的样株,又减少了中心区域大量重叠的样株,据此确认20%抽样比例种质保存库可以作为云南松材用种质的代表性子集。
To investigate sampling strategy for construction of timber-used germplasm conservation bank of Pinus yunnanensis Franch. and acquire representative subsets, 26 representative populations were selected from its whole distribution area, and 30 sampling plants were selected from each population as an original germplasm set, meanwhile measured values of 18 phenotypic traits were selected as original data of germplasm conservation bank. On the basis, sampling was conducted according to the result of unweighted average cluster analysis by dividing groups of geographic population; setting sampling percentages of 10%, 20%, 30%, and 40%, respectively, germplasm subsets were constructed by using diversity index method and improved least distance stepwise sampling method, and 5 evaluation parameters and principal component analysis were employed to make comprehensive evaluation and confirmation of germplasm subsets with different sampling percentages. The results show that there is no significant difference in mean t-test of 18 phenotypic traits between each germplasm subset and original germplasm set; variances of 11, 14, 15, and 12 phenotypic traits in germplasm subsets with 40%, 30%, 20%, and 10% sampling percentages are generally greater than those in original germplasm set, and the differences are significant, indicating that scatter degree of phenotypic trait values in each germplasm subset is generally greater than that in original germplasm set. According to χ~2-test, there is no significant difference in frequency distribution of 18 phenotypic traits between germplasm subsets with 40%, 30%, and 20% sampling percentages and original germplasm set, while there are extremely significant and significant differences in frequency distribution of 2 phenotypic traits between germplasm subset with 10% sampling percentage and original germplasm set. Among original germplasm set and 4 germplasm subsets, distribution frequencies of sampling plants in different classes are basically identical, but percentage of sampling plants in class 1, class 9, and class 10 gradually increases with the decrease of sampling percentage, indicating that percentage of extreme sampling plants should be increased appropriately when constructing germplasm conservation bank. Shannon-Weaver genetic diversity index(H′) of each phenotypic trait in 4 germplasm subsets is generally higher than that in original germplasm set, and H′ value increases in general with the decrease of sampling percentage; in which, there is an extremely significant difference in mean H′ value of phenotypic traits between germplasm subset with 20% sampling percentage and original germplasm set, and significant differences in mean H′ values of phenotypic traits between germplasm subsets with 30% and 10% sampling percentages and original germplasm set. The comprehensive evaluation results show that germplasm subsets with 10%, 20%, 30%, and 40% sampling percentages can represent original germplasm set, in which, germplasm subset with 20% sampling percentage can objectively represent the phenotypic genetic diversity of original germplasm set, and comprehensive effect of 5 evaluation parameters of this germplasm subset are better than that of other germplasm subsets. The principal component analysis result shows that germplasm conservation bank constructed with 20% sampling percentage can explain more phenotypic genetic information than original germplasm set, which reserves a lot of sampling plants distributed at the outer margin and reduces a lot of overlapping sampling plants in the center area, confirming accordingly that germplasm conservation bank constructed with 20% sampling percentage can be used as representative subset of timber-used germplasm of P. yunnanensis.
To investigate sampling strategy for construction of timber-used germplasm conservation bank of Pinus yunnanensis Franch. and acquire representative subsets, 26 representative populations were selected from its whole distribution area, and 30 sampling plants were selected from each population as an original germplasm set, meanwhile measured values of 18 phenotypic traits were selected as original data of germplasm conservation bank. On the basis, sampling was conducted according to the result of unweighted average cluster analysis by dividing groups of geographic population; setting sampling percentages of 10%, 20%, 30%, and 40%, respectively, germplasm subsets were constructed by using diversity index method and improved least distance stepwise sampling method, and 5 evaluation parameters and principal component analysis were employed to make comprehensive evaluation and confirmation of germplasm subsets with different sampling percentages. The results show that there is no significant difference in mean t-test of 18 phenotypic traits between each germplasm subset and original germplasm set; variances of 11, 14, 15, and 12 phenotypic traits in germplasm subsets with 40%, 30%, 20%, and 10% sampling percentages are generally greater than those in original germplasm set, and the differences are significant, indicating that scatter degree of phenotypic trait values in each germplasm subset is generally greater than that in original germplasm set. According to χ~2-test, there is no significant difference in frequency distribution of 18 phenotypic traits between germplasm subsets with 40%, 30%, and 20% sampling percentages and original germplasm set, while there are extremely significant and significant differences in frequency distribution of 2 phenotypic traits between germplasm subset with 10% sampling percentage and original germplasm set. Among original germplasm set and 4 germplasm subsets, distribution frequencies of sampling plants in different classes are basically identical, but percentage of sampling plants in class 1, class 9, and class 10 gradually increases with the decrease of sampling percentage, indicating that percentage of extreme sampling plants should be increased appropriately when constructing germplasm conservation bank. Shannon-Weaver genetic diversity index(H′) of each phenotypic trait in 4 germplasm subsets is generally higher than that in original germplasm set, and H′ value increases in general with the decrease of sampling percentage; in which, there is an extremely significant difference in mean H′ value of phenotypic traits between germplasm subset with 20% sampling percentage and original germplasm set, and significant differences in mean H′ values of phenotypic traits between germplasm subsets with 30% and 10% sampling percentages and original germplasm set. The comprehensive evaluation results show that germplasm subsets with 10%, 20%, 30%, and 40% sampling percentages can represent original germplasm set, in which, germplasm subset with 20% sampling percentage can objectively represent the phenotypic genetic diversity of original germplasm set, and comprehensive effect of 5 evaluation parameters of this germplasm subset are better than that of other germplasm subsets. The principal component analysis result shows that germplasm conservation bank constructed with 20% sampling percentage can explain more phenotypic genetic information than original germplasm set, which reserves a lot of sampling plants distributed at the outer margin and reduces a lot of overlapping sampling plants in the center area, confirming accordingly that germplasm conservation bank constructed with 20% sampling percentage can be used as representative subset of timber-used germplasm of P. yunnanensis.
引文
[1] 曾宪君, 李丹, 胡彦鹏, 等. 欧洲黑杨优质核心种质库的初步构建[J]. 林业科学, 2014, 50(9): 51-58.
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[7] 魏志刚, 高玉池, 刘关君, 等. 白桦核心种质构建的聚类方法研究[J]. 植物遗传资源学报, 2009, 10(3): 405-410.
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[11] 徐宁, 程须珍, 王素华, 等. 以地理来源分组和利用表型数据构建中国小豆核心种质[J]. 作物学报, 2008, 34(8): 1366-1373.
[12] 刘旭, 马缘生, 谭富娟, 等. 小麦特殊遗传材料核心样品的建立[J]. 植物遗传资源科学, 2000, 1(2): 1-8.
[13] VAIJAYANTHI P V, RAMESH S , GOWDA M B, et al. Identification of trait-specific accessions from a core set of dolichos bean germplasm[J]. Journal of Crop Improvement, 2016, 30(2): 244-257.
[14] 姜慧芳, 任小平, 廖伯寿, 等. 中国花生核心种质的建立[J]. 武汉植物学研究, 2007, 25(3): 289-293.
[15] REDDY L J , UPADHYAYA H D, GOWDA C L L, et al. Development of core collection in pigeonpea [Cajanus cajan (L.) Millspaugh] using geographic and qualitative morphological descriptors[J]. Genetic Resources and Crop Evolution, 2005, 52 (8): 1049-1056.
[16] 刘娟, 廖康, 曹倩, 等. 利用表型性状构建新疆野杏种质资源核心种质[J]. 果树学报, 2015, 32(5): 787-796.
[17] 李秀兰, 贾继文, 王军辉, 等. 灰楸形态多样性分析及核心种质初步构建[J]. 植物遗传资源学报, 2013, 14(2): 243-248.
[18] 刘德浩, 张方秋, 张卫华. 基于地理种源分组和表型数据构建尾叶桉核心种质[J]. 西南林业大学学报, 2013, 33(5): 1-8.
[19] 云南省林业厅, 《云南松》编委会, 金振洲, 等. 云南松[M]. 昆明: 云南科技出版社, 2004.
[20] 作者不详. 第二批国家林木种质资源库名单公布[J]. 园林科技, 2016(4): 47-48.
[21] 李莲芳, 郑畹, 韩明跃, 等. 云南松遗传改良进展及其育种策略剖析[J]. 西部林业科学, 2010, 39(2): 104-110.
[22] 许玉兰. 云南松天然群体遗传变异研究[D]. 北京: 北京林业大学林学院, 2015: 15-19.
[23] DANGASUK O G, PANETSOS K P. Altitudinal and longitudinal variations in Pinus brutia (Ten.) of Crete Island, Greece; some needle, cone and seed traits under natural habitats[J]. New Forest, 2004, 27(3):269-284.
[24]URBANIAK L, KARLIN'SKI L, POPIELARZ R.Variation of morphological needle characters of Scots pine (Pinus sylvestris L.) populations in different habitats[J]. Acta Societatis Botanicorum Poloniae, 2003, 72(1):37-44.
[25]BORATYN'SKA K,JASIN'SKA A K,CIEPLUCH E.Effect of tree age on needle morphology and anatomy of Pinus uliginosa and Pinus silvestris:species-specific character separation during ontogenesis[J]. Flora, 2008, 203(8): 617-626.
[26] 孟宪宇. 测树学[M]. 3版. 北京: 中国林业出版社, 2006: 10-11, 43-66.
[27] DIWAN N, BAUCHAN G R, MCINTOSH M S. A core collection for the United States annual Medicago germplasm collection[J]. Crop Science, 1994, 34: 279-285.
[2] 李自超, 张洪亮, 曾亚文, 等. 云南地方稻种资源核心种质取样方案研究[J]. 中国农业科学, 2000, 33(5): 1-7.
[3] GEPTS P. Plant genetic resources conservation and utilization: the accomplishments and future of a societal insurance policy[J]. Crop Science, 2006, 46: 2278-2292.
[4] UPADHYAYA H D, REDDY K N, GOWDA C L L, et al. Phenotypic diversity in the pigeonpea (Cajanus cajan) core collection[J]. Genetic Resources and Crop Evolution, 2007, 54(6): 1167-1184.
[5] 刘宁宁. 植物资源核心种质构建与评价新方法的研究[D]. 杭州: 浙江大学农业与生物技术学院, 2007.
[6] 赵冰, 张启翔. 中国蜡梅种质资源核心种质的初步构建[J]. 北京林业大学学报, 2007, 29(S1): 16-21.
[7] 魏志刚, 高玉池, 刘关君, 等. 白桦核心种质构建的聚类方法研究[J]. 植物遗传资源学报, 2009, 10(3): 405-410.
[8] 魏志刚, 高玉池, 杨传平, 等. 白桦核心种质构建的抽样方法[J]. 东北林业大学学报, 2009, 37(7): 1-4.
[9] 向青. 川渝地区油桐种质资源评价和核心种质的初步构建[D]. 雅安: 四川农业大学林学院, 2012: 42-47.
[10] 徐海明. 种质资源核心库构建方法的研究及其应用[D]. 杭州: 浙江大学农业与生物技术学院, 2005: 36-44.
[11] 徐宁, 程须珍, 王素华, 等. 以地理来源分组和利用表型数据构建中国小豆核心种质[J]. 作物学报, 2008, 34(8): 1366-1373.
[12] 刘旭, 马缘生, 谭富娟, 等. 小麦特殊遗传材料核心样品的建立[J]. 植物遗传资源科学, 2000, 1(2): 1-8.
[13] VAIJAYANTHI P V, RAMESH S , GOWDA M B, et al. Identification of trait-specific accessions from a core set of dolichos bean germplasm[J]. Journal of Crop Improvement, 2016, 30(2): 244-257.
[14] 姜慧芳, 任小平, 廖伯寿, 等. 中国花生核心种质的建立[J]. 武汉植物学研究, 2007, 25(3): 289-293.
[15] REDDY L J , UPADHYAYA H D, GOWDA C L L, et al. Development of core collection in pigeonpea [Cajanus cajan (L.) Millspaugh] using geographic and qualitative morphological descriptors[J]. Genetic Resources and Crop Evolution, 2005, 52 (8): 1049-1056.
[16] 刘娟, 廖康, 曹倩, 等. 利用表型性状构建新疆野杏种质资源核心种质[J]. 果树学报, 2015, 32(5): 787-796.
[17] 李秀兰, 贾继文, 王军辉, 等. 灰楸形态多样性分析及核心种质初步构建[J]. 植物遗传资源学报, 2013, 14(2): 243-248.
[18] 刘德浩, 张方秋, 张卫华. 基于地理种源分组和表型数据构建尾叶桉核心种质[J]. 西南林业大学学报, 2013, 33(5): 1-8.
[19] 云南省林业厅, 《云南松》编委会, 金振洲, 等. 云南松[M]. 昆明: 云南科技出版社, 2004.
[20] 作者不详. 第二批国家林木种质资源库名单公布[J]. 园林科技, 2016(4): 47-48.
[21] 李莲芳, 郑畹, 韩明跃, 等. 云南松遗传改良进展及其育种策略剖析[J]. 西部林业科学, 2010, 39(2): 104-110.
[22] 许玉兰. 云南松天然群体遗传变异研究[D]. 北京: 北京林业大学林学院, 2015: 15-19.
[23] DANGASUK O G, PANETSOS K P. Altitudinal and longitudinal variations in Pinus brutia (Ten.) of Crete Island, Greece; some needle, cone and seed traits under natural habitats[J]. New Forest, 2004, 27(3):269-284.
[24]URBANIAK L, KARLIN'SKI L, POPIELARZ R.Variation of morphological needle characters of Scots pine (Pinus sylvestris L.) populations in different habitats[J]. Acta Societatis Botanicorum Poloniae, 2003, 72(1):37-44.
[25]BORATYN'SKA K,JASIN'SKA A K,CIEPLUCH E.Effect of tree age on needle morphology and anatomy of Pinus uliginosa and Pinus silvestris:species-specific character separation during ontogenesis[J]. Flora, 2008, 203(8): 617-626.
[26] 孟宪宇. 测树学[M]. 3版. 北京: 中国林业出版社, 2006: 10-11, 43-66.
[27] DIWAN N, BAUCHAN G R, MCINTOSH M S. A core collection for the United States annual Medicago germplasm collection[J]. Crop Science, 1994, 34: 279-285.