山药（Rhizoma Dioscorea）种质资源研究
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摘要
山药(Rhizoma Dioscorea)为薯蓣(Dioscorea opposita Thunb.)及其近缘种植物的块茎,是国家卫生部公布的药、食两用的中药,在我国有2500多年的栽培历史,许多地区均有栽培并相互引种交流,再加上山药易受周围环境影响,部分物种外部形态特征相近、变异范围重叠及珠芽、花、果实、种子等器官不能在同一栽培地区全都形成,导致很难从形态上鉴定相关物种是否为相同种或者相同类群。本研究运用形态标记、ISSR、 SRAP分子标记相结合的方法,对来自我国山东、安徽、江西、浙江、山西、河南、广西、陕西、广东、海南等13个省(区)的90份山药种质资源进行了指纹图谱构建及遗传多样性分析,提取并分析山药主要化学成分,最后构建山药核心种质。主要结果如下：
1.形态性状分析：以3年考察19个形态性状的平均值为指标,采用植物学分类方法进行系统分类,90份山药种质资源分为薯蓣、褐苞薯蓣、参薯和山薯4大类,在此基础上,本研究鉴定并分析了各类群的主要性状特征。
2. ISSR、SRAP指纹图谱构建：用ISSR和SRAP标记构建了90份山药种质资源的指纹图谱,分别用2种独立的方法(即单一引物的特殊标记及不同引物多态谱带类型的组合)可以有效地鉴别山药种质资源。结果表明,在90份山药资源中,有11份资源可以通过ISSR的特征谱带鉴别,有8份资源可由SRAP的特殊位点鉴别。以最少引物数鉴别尽可能多份资源为原则,选用10条ISSR及10对SRAP引物分别构建山药资源指纹图谱,结果表明,ISSR-DNA指纹图谱可鉴别75份山药资源,有15份资源无法鉴别：SRAP-DNA指纹图谱可鉴别82份山药资源,8份资源无法鉴别。
3. ISSR, SRAP遗传多样性分析：用ISSR分子标记对90份山药种质资源进行遗传多样性分析,从200条ISSR引物中筛选出22条多态性引物对90份供试材料进行条带扩增,共得到226个多态位点,并用这些位点数据来计算遗传距离,利用DPS统计软件中的UPGMA聚类分析法,建立起90份山药种质资源的遗传关系树状图。以遗传距离0.43为标准,90份山药种质资源可聚为两大类,第一大类含48份,第二大类含42份；当以遗传距离0.35为标准时,第一大类可分为两个亚类,第一亚类含28份,第二亚类含20份；再以遗传距离0.27为标准,第一亚类的28份资源可再细分为两个小类,第一小类含22份,第二小类含6份；采用ISSR标记可将90份山药种质资源区分为4个类群。
从49对SRAP引物中共筛选出30对能扩增得到稳定清晰可辨条带的引物,共得到616条多态性条带,同时运用DPS统计软件,对山药种质资源进行遗传多样性分析,结果表明,90份山药种质资源可分为5类：第Ⅰ类包括薯蓣群20份、第Ⅱ类包括褐色苞薯蓣群42份、第Ⅲ类包括山薯群6份、第Ⅳ、V类均包括参薯群22份,分别为第Ⅳ类3份和第V类19份。
4.ISSR、SRAP遗传多样性分析及差异比较：为了更好地利用ISSR和SRAP两种标记,对两种标记在分析山药资源情况进行了比较,结果表明：2个标记的多态性比率分别达到79.2%和80.47%,均说明山药资源间有较高的遗传多样性。从扩增总条带数、总多态位点数、平均扩增条带数上看,SRAP标记大大高于ISSR标记；2种标记结果均表明山药种质资源总的遗传变异中约有52%变异存在于种群间,约48%的变异存在于种群内；从遗传距离分析看,SRAP标记的遗传距离的范围比ISSR标记更广：ISSR标记和SRAP标记分别将90份山药资源分为4类和5类,SRAP显示出了其较为特殊的遗传结构；从指纹图谱的鉴别能力看,SRAP-DNA指纹图谱具有更强的鉴别能力。
5.主要化学成分分析：分别采用HPLC法、紫外比色法和硫酸苯酚法测定了90份山药种质资源的尿囊素、总黄酮、多糖和腺苷含量,并分别对全国资源、福建资源、薯蓣、褐苞薯蓣、参薯和山薯等6个群体的4种成分含量进行比较分析,结果表明：不同材料间各种成分含量差异明显,编号为38号(河北保定)的尿囊素含量最高(2.1179%),24号(福建宁化)的尿囊素含量最低(0.1030%),两者相差20.56倍；27号(福建安远)的总黄酮含量最高(0.9102%),42号(山东充州)总黄酮含量最低(0.0508%),两者相差17.92倍；48号(浙江温州)的多糖含量最高(9.1522%),56号(福建云霄)多糖含量最低(0.7388%),两者相差12.39倍；69(福建邵武)腺苷含量最高为0.2163%,33(河南焦作)最低仅为0.0185%。从6个群体4种成分含量平均水平来看,尿囊素平均含量从大到小依次为薯蓣(0.6277%)、全国资源(0.4969%)、褐苞薯蓣(0.4794%)、福建(0.4590%)、参薯(0.4415%)和山薯(0.2777%)。总黄酮平均含量从大到小依次为褐苞薯蓣(0.1789%)、参薯(0.1696%)、全国资源(0.1666%)、山薯(0.1646%)、福建(0.1605%)和薯蓣(0.1356%)。多糖平均含量从大到小依次为参薯(3.1913%)、福建(2.3493%)、全国资源(2.3279%)、褐苞薯蓣(2.2136%)、薯蓣(1.8075%)和山薯(1.7387%)。腺苷平均含量从大到小依次为褐苞薯蓣(0.1250%)、福建(0.1096%)、全国(0.1083%)、山薯(0.0949%)、薯蓣(0.0946%)和参薯(0.0850%)。
6.核心种质构建：首先对形态性状数据、ISSR标记数据和SRAP标记数据分别建立山药种质资源核心样本库,然后将三种类别数据进行累加；以三种类别数据信息均能鉴别的资源为核心种质资源、两种类别数据信息及单一类别数据信息不能鉴别的资源认定为后备资源库和三种类别数据信息均不能鉴别的则认定为重复资源的构建原则,建立山药核心种质及后备种质资源库,结果是核心种质库共有69份,分为4个样本库；后备资源库共有20份；淘汰1份重复种质资源。
Rhizoma Dioscorea is the tubers of Dioscorea opposita Thunb. and its close relatives.China's Ministry of Public Health publicized it as Chinese medicine used for both food and medicine. It has been cultivated for more than2,500years in many areas of China, where people often exchange their variety with each other. Rhizoma Dioscorea tend to be influenced by the surroundings. Some varieties are close in external features and overlapped in the range of variation. The bulbils, flowers, fruits, seeds are not formed in the same cultivated area. As a result, it is difficult to identify whether any two species are the same kind or the same class group just in terms of shape. The present study applied a combination of morphological markers, ISSR and SRAP molecular markers to construction of fingerprint and analysis of genetic diversity of90Rhizoma Dioscorea germplasm resources in13provinces (regions) in China, including Shangdong, Anhui, Jiangxi, Zhejiang, Shanxi, Henan, Guangxi, Shanxi, Guangdong, Hainan, etc. Then the main chemical compositions were extracted and analyzed. Finally core collection was constructed. Major findings are as follows.
1. Analysis of morphological characteristics:With the average value of the19morphological characters obtained in a3-year investigation as the index, we adopted the botanical means of classification to make a phylogenetic classification of Rhizoma Dioscorea germplasm resources. The90resources were then classified into four main types, i.e. D. opposita, D. persimilis, D. alata and D. fordii. Based on this, the present study analyzed and evaluated their main characteristics.
2. Construction of ISSR and SRAP fingerprint:The ISSR and SRAP markers were used to construct90germplasm resources by using two independent methods respectively (namely, a particular marker for a single primer and a combination of polymorphic band types for multiple primers) to effectively identify the germplasm resources. The result shows that among90germplasm resources,11resources were identified by using ISSR key band,8resources were identified by using SRAP special sites. The principle is to use the minimum number of primers to identify as more resources as possible. Then10ISSR and10pairs of SRAP primers were selected to construct Rhizoma Dioscorea resource fingerprint respectively and the result shows that75resources can be identified by ISSR-DNA fingerprint and15cannot;82resources can be identified by SRAP-DNA fingerprint and8cannot.
3. ISSR and SRAP analysis of genetic diversity:The ISSR molecular markers were used to analyze the genetic diversity of the90germplasm resources.22polymorphic primers were screened from200ISSR primers to amplify the bands of the90resources for test. And226polymorphic sites were obtained, which were used to calculate genetic distances. A phylogenetic tree of the90germplasma resources was constructed using the UPGMA clustering method with DPS Software. At the genetic distance of0.43.90germplasm resources were clustered into two large groups, one with48resources and the other42; at the genetic distance of0.35, the first large group was subdivided into two subgroups, one with28, the other20; at the genetic distance of0.27, the first subgroup of28resources was furt(?)er divided into two minor groups, one with22, the other with5. Therefore, the90resources were divided into4groups by ISSR markers.
30primer pairs that can amplify stable and clear bands were screened from49SRAP primer pairs, which amplified616polymorphic bands. Meanwhile an analysis of genetic diversity was made to the germplasm resources by using DPS Software. The resul(?)shows:90germplasma resources can be divided into5types:Type Ⅰ includes20resources of D. opposita, Type Ⅱ includes42resources of D. persimilis, Type Ⅲ includes6resources of D.fordii and Type Ⅳ and Type V include3and19resources of D. alata respectively.
4. Comparison of ISSR and SRAP analysis of genetic diversity:To make better use of ISSR and SRAP markers, they are compared in the analysis of germplasm resources. The result shows that the polymorphism rate of the two types of markers reach79.2%and80.47%respectively, which indicates that the genetic diversity between two germplasm resources is high. The total number of amplified bands and polymorphic sites and the average number of amplified bands in SRAP markers are much higher than those in ISSR markers. The results of both markers show that about52%of total genetic diversity of germplasm resources occurs in different species groups and48%occurs in the same species group. The range of genetic distance of SRAP markers is wider than that of ISSR markers. ISSR and SRAP markers divide90germplasm resources into4and5types respectively and SRAP reveals its unusual genetic structure. In terms of fingerprint, SRAP-DNA fingerprint has higher capability of identification.
4. Analysis of principal chemical compositions:The HPLC method, UV colorimetric method, and Phenol-sulphate acid method were used to measure the content of allantoin, flavone,polysaccharides and adenosine of the90resources respectively, and also made a comparative analysis of these four components in the six groups, i.e. the national resource, Fujian resource, D. opposita, D. persimilis, D. alata and D. fordii resources. The result shows: The content of various compositions differs greatly among different resources. No.38(Baoding, Hebei) has the highest level of allantoin while No.24(Ninghua, Fujian) has the lowest level (0.1030%), with the former20.56times higher than the latter; No.27(Anyuan, Fujian) has the highest level of flavone (0.9102%) while No.42(Yanzhou, Shandong) has the lowest level (0.0508%), with the former17.92times higher than the latter; No.48(Wenzhou, Zhejiang) has the highest level of polysaccharides (9.1522%) while No.56(Yunxiao, Fujian) has the lowest level (0.7388%), with the former12.39higher than the latter; No.69(Shaowu, Fujian) has the highest level of adenosine (0.2163%) while No.33(Jiaozuo, Henan) has the lowest (0.0185%). In terms of the average level of the four components in all groups, the average level of allantoin in decreasing order is0.6277%in D. opposita resource,0.4969%in the national resource,0.4794%in D. persimilis,0.4590%in Fujian resource,0.4415%in D. alata and0.2777%in D. fordii. The average level of flavone in decreasing order is0.1789%in D. persimilis,0.1696%in D. alata,0.1666%in the national resource,0.1646%in D. fordii,0.1605%in Fujian resource, and0.1356%in D. opposita. The average level of polysaccharides in decreasing order is3.1913%in D. alata,2.3493%in Fujian resource,2.3279%in the national resource,2.2136%in D. persimilis,1.8075%in D. opposita and1.7387%in D. fordii. The average level of adenosine in decreasing order is0.1250%in D. persimilis,0.1096%in Fujian resource,0.1083%in the national resource,0.0949%in D. fordii,0.0946%in D. opposita and0.0850%in D. alata.
6. Construction of core collection:Firstly, data of morphological traits, ISSR markers and SRAP markers were collected to create core sample banks of Rhizoma Dioscorea germplasm resources separately, and then the three categories of data were accumulated; The resources that can be identified by the above three categories of data are core collections. The resources that cannot be identified by any two categories of data and any individual category are regarded as backup resource pools and the resources that cannot be identified by all the three categories of data are regarded as redundant resources. Based on the above principle, we constructed core collections and backup resource pools, among which there are69core collections divided into4sample banks;20backup resource pools; and1redundant resource.
1.形态性状分析：以3年考察19个形态性状的平均值为指标,采用植物学分类方法进行系统分类,90份山药种质资源分为薯蓣、褐苞薯蓣、参薯和山薯4大类,在此基础上,本研究鉴定并分析了各类群的主要性状特征。
2. ISSR、SRAP指纹图谱构建：用ISSR和SRAP标记构建了90份山药种质资源的指纹图谱,分别用2种独立的方法(即单一引物的特殊标记及不同引物多态谱带类型的组合)可以有效地鉴别山药种质资源。结果表明,在90份山药资源中,有11份资源可以通过ISSR的特征谱带鉴别,有8份资源可由SRAP的特殊位点鉴别。以最少引物数鉴别尽可能多份资源为原则,选用10条ISSR及10对SRAP引物分别构建山药资源指纹图谱,结果表明,ISSR-DNA指纹图谱可鉴别75份山药资源,有15份资源无法鉴别：SRAP-DNA指纹图谱可鉴别82份山药资源,8份资源无法鉴别。
3. ISSR, SRAP遗传多样性分析：用ISSR分子标记对90份山药种质资源进行遗传多样性分析,从200条ISSR引物中筛选出22条多态性引物对90份供试材料进行条带扩增,共得到226个多态位点,并用这些位点数据来计算遗传距离,利用DPS统计软件中的UPGMA聚类分析法,建立起90份山药种质资源的遗传关系树状图。以遗传距离0.43为标准,90份山药种质资源可聚为两大类,第一大类含48份,第二大类含42份；当以遗传距离0.35为标准时,第一大类可分为两个亚类,第一亚类含28份,第二亚类含20份；再以遗传距离0.27为标准,第一亚类的28份资源可再细分为两个小类,第一小类含22份,第二小类含6份；采用ISSR标记可将90份山药种质资源区分为4个类群。
从49对SRAP引物中共筛选出30对能扩增得到稳定清晰可辨条带的引物,共得到616条多态性条带,同时运用DPS统计软件,对山药种质资源进行遗传多样性分析,结果表明,90份山药种质资源可分为5类：第Ⅰ类包括薯蓣群20份、第Ⅱ类包括褐色苞薯蓣群42份、第Ⅲ类包括山薯群6份、第Ⅳ、V类均包括参薯群22份,分别为第Ⅳ类3份和第V类19份。
4.ISSR、SRAP遗传多样性分析及差异比较：为了更好地利用ISSR和SRAP两种标记,对两种标记在分析山药资源情况进行了比较,结果表明：2个标记的多态性比率分别达到79.2%和80.47%,均说明山药资源间有较高的遗传多样性。从扩增总条带数、总多态位点数、平均扩增条带数上看,SRAP标记大大高于ISSR标记；2种标记结果均表明山药种质资源总的遗传变异中约有52%变异存在于种群间,约48%的变异存在于种群内；从遗传距离分析看,SRAP标记的遗传距离的范围比ISSR标记更广：ISSR标记和SRAP标记分别将90份山药资源分为4类和5类,SRAP显示出了其较为特殊的遗传结构；从指纹图谱的鉴别能力看,SRAP-DNA指纹图谱具有更强的鉴别能力。
5.主要化学成分分析：分别采用HPLC法、紫外比色法和硫酸苯酚法测定了90份山药种质资源的尿囊素、总黄酮、多糖和腺苷含量,并分别对全国资源、福建资源、薯蓣、褐苞薯蓣、参薯和山薯等6个群体的4种成分含量进行比较分析,结果表明：不同材料间各种成分含量差异明显,编号为38号(河北保定)的尿囊素含量最高(2.1179%),24号(福建宁化)的尿囊素含量最低(0.1030%),两者相差20.56倍；27号(福建安远)的总黄酮含量最高(0.9102%),42号(山东充州)总黄酮含量最低(0.0508%),两者相差17.92倍；48号(浙江温州)的多糖含量最高(9.1522%),56号(福建云霄)多糖含量最低(0.7388%),两者相差12.39倍；69(福建邵武)腺苷含量最高为0.2163%,33(河南焦作)最低仅为0.0185%。从6个群体4种成分含量平均水平来看,尿囊素平均含量从大到小依次为薯蓣(0.6277%)、全国资源(0.4969%)、褐苞薯蓣(0.4794%)、福建(0.4590%)、参薯(0.4415%)和山薯(0.2777%)。总黄酮平均含量从大到小依次为褐苞薯蓣(0.1789%)、参薯(0.1696%)、全国资源(0.1666%)、山薯(0.1646%)、福建(0.1605%)和薯蓣(0.1356%)。多糖平均含量从大到小依次为参薯(3.1913%)、福建(2.3493%)、全国资源(2.3279%)、褐苞薯蓣(2.2136%)、薯蓣(1.8075%)和山薯(1.7387%)。腺苷平均含量从大到小依次为褐苞薯蓣(0.1250%)、福建(0.1096%)、全国(0.1083%)、山薯(0.0949%)、薯蓣(0.0946%)和参薯(0.0850%)。
6.核心种质构建：首先对形态性状数据、ISSR标记数据和SRAP标记数据分别建立山药种质资源核心样本库,然后将三种类别数据进行累加；以三种类别数据信息均能鉴别的资源为核心种质资源、两种类别数据信息及单一类别数据信息不能鉴别的资源认定为后备资源库和三种类别数据信息均不能鉴别的则认定为重复资源的构建原则,建立山药核心种质及后备种质资源库,结果是核心种质库共有69份,分为4个样本库；后备资源库共有20份；淘汰1份重复种质资源。
Rhizoma Dioscorea is the tubers of Dioscorea opposita Thunb. and its close relatives.China's Ministry of Public Health publicized it as Chinese medicine used for both food and medicine. It has been cultivated for more than2,500years in many areas of China, where people often exchange their variety with each other. Rhizoma Dioscorea tend to be influenced by the surroundings. Some varieties are close in external features and overlapped in the range of variation. The bulbils, flowers, fruits, seeds are not formed in the same cultivated area. As a result, it is difficult to identify whether any two species are the same kind or the same class group just in terms of shape. The present study applied a combination of morphological markers, ISSR and SRAP molecular markers to construction of fingerprint and analysis of genetic diversity of90Rhizoma Dioscorea germplasm resources in13provinces (regions) in China, including Shangdong, Anhui, Jiangxi, Zhejiang, Shanxi, Henan, Guangxi, Shanxi, Guangdong, Hainan, etc. Then the main chemical compositions were extracted and analyzed. Finally core collection was constructed. Major findings are as follows.
1. Analysis of morphological characteristics:With the average value of the19morphological characters obtained in a3-year investigation as the index, we adopted the botanical means of classification to make a phylogenetic classification of Rhizoma Dioscorea germplasm resources. The90resources were then classified into four main types, i.e. D. opposita, D. persimilis, D. alata and D. fordii. Based on this, the present study analyzed and evaluated their main characteristics.
2. Construction of ISSR and SRAP fingerprint:The ISSR and SRAP markers were used to construct90germplasm resources by using two independent methods respectively (namely, a particular marker for a single primer and a combination of polymorphic band types for multiple primers) to effectively identify the germplasm resources. The result shows that among90germplasm resources,11resources were identified by using ISSR key band,8resources were identified by using SRAP special sites. The principle is to use the minimum number of primers to identify as more resources as possible. Then10ISSR and10pairs of SRAP primers were selected to construct Rhizoma Dioscorea resource fingerprint respectively and the result shows that75resources can be identified by ISSR-DNA fingerprint and15cannot;82resources can be identified by SRAP-DNA fingerprint and8cannot.
3. ISSR and SRAP analysis of genetic diversity:The ISSR molecular markers were used to analyze the genetic diversity of the90germplasm resources.22polymorphic primers were screened from200ISSR primers to amplify the bands of the90resources for test. And226polymorphic sites were obtained, which were used to calculate genetic distances. A phylogenetic tree of the90germplasma resources was constructed using the UPGMA clustering method with DPS Software. At the genetic distance of0.43.90germplasm resources were clustered into two large groups, one with48resources and the other42; at the genetic distance of0.35, the first large group was subdivided into two subgroups, one with28, the other20; at the genetic distance of0.27, the first subgroup of28resources was furt(?)er divided into two minor groups, one with22, the other with5. Therefore, the90resources were divided into4groups by ISSR markers.
30primer pairs that can amplify stable and clear bands were screened from49SRAP primer pairs, which amplified616polymorphic bands. Meanwhile an analysis of genetic diversity was made to the germplasm resources by using DPS Software. The resul(?)shows:90germplasma resources can be divided into5types:Type Ⅰ includes20resources of D. opposita, Type Ⅱ includes42resources of D. persimilis, Type Ⅲ includes6resources of D.fordii and Type Ⅳ and Type V include3and19resources of D. alata respectively.
4. Comparison of ISSR and SRAP analysis of genetic diversity:To make better use of ISSR and SRAP markers, they are compared in the analysis of germplasm resources. The result shows that the polymorphism rate of the two types of markers reach79.2%and80.47%respectively, which indicates that the genetic diversity between two germplasm resources is high. The total number of amplified bands and polymorphic sites and the average number of amplified bands in SRAP markers are much higher than those in ISSR markers. The results of both markers show that about52%of total genetic diversity of germplasm resources occurs in different species groups and48%occurs in the same species group. The range of genetic distance of SRAP markers is wider than that of ISSR markers. ISSR and SRAP markers divide90germplasm resources into4and5types respectively and SRAP reveals its unusual genetic structure. In terms of fingerprint, SRAP-DNA fingerprint has higher capability of identification.
4. Analysis of principal chemical compositions:The HPLC method, UV colorimetric method, and Phenol-sulphate acid method were used to measure the content of allantoin, flavone,polysaccharides and adenosine of the90resources respectively, and also made a comparative analysis of these four components in the six groups, i.e. the national resource, Fujian resource, D. opposita, D. persimilis, D. alata and D. fordii resources. The result shows: The content of various compositions differs greatly among different resources. No.38(Baoding, Hebei) has the highest level of allantoin while No.24(Ninghua, Fujian) has the lowest level (0.1030%), with the former20.56times higher than the latter; No.27(Anyuan, Fujian) has the highest level of flavone (0.9102%) while No.42(Yanzhou, Shandong) has the lowest level (0.0508%), with the former17.92times higher than the latter; No.48(Wenzhou, Zhejiang) has the highest level of polysaccharides (9.1522%) while No.56(Yunxiao, Fujian) has the lowest level (0.7388%), with the former12.39higher than the latter; No.69(Shaowu, Fujian) has the highest level of adenosine (0.2163%) while No.33(Jiaozuo, Henan) has the lowest (0.0185%). In terms of the average level of the four components in all groups, the average level of allantoin in decreasing order is0.6277%in D. opposita resource,0.4969%in the national resource,0.4794%in D. persimilis,0.4590%in Fujian resource,0.4415%in D. alata and0.2777%in D. fordii. The average level of flavone in decreasing order is0.1789%in D. persimilis,0.1696%in D. alata,0.1666%in the national resource,0.1646%in D. fordii,0.1605%in Fujian resource, and0.1356%in D. opposita. The average level of polysaccharides in decreasing order is3.1913%in D. alata,2.3493%in Fujian resource,2.3279%in the national resource,2.2136%in D. persimilis,1.8075%in D. opposita and1.7387%in D. fordii. The average level of adenosine in decreasing order is0.1250%in D. persimilis,0.1096%in Fujian resource,0.1083%in the national resource,0.0949%in D. fordii,0.0946%in D. opposita and0.0850%in D. alata.
6. Construction of core collection:Firstly, data of morphological traits, ISSR markers and SRAP markers were collected to create core sample banks of Rhizoma Dioscorea germplasm resources separately, and then the three categories of data were accumulated; The resources that can be identified by the above three categories of data are core collections. The resources that cannot be identified by any two categories of data and any individual category are regarded as backup resource pools and the resources that cannot be identified by all the three categories of data are regarded as redundant resources. Based on the above principle, we constructed core collections and backup resource pools, among which there are69core collections divided into4sample banks;20backup resource pools; and1redundant resource.
引文
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