利用ISSR和EST-SSR标记研究中国茶树资源的遗传多样性和遗传结构
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摘要
茶树(Camellia sinensis(L.)O.Kuntze)属于山茶科(Theaceae)山茶属(Camellia)茶组(Sect.Thea(L.)Dyer)植物,原产于中国,是世界上最重要的饮料作物之一。在复杂多样的生态条件下,经过长期的自然演化和人工选择,形成了丰富多样的茶树种质资源,这其中蕴含着高抗、优质等重要优异性状的基因资源。充分了解和掌握茶树种质资源的遗传多样性和遗传结构,是开展茶树种质资源收集保存、有益基因发掘和品种选育的重要基础。由于DNA标记具有多态性高、鉴定准确快速等优点,故它已成为茶树遗传多样性研究的重要技术和手段。本研究利用微卫星相关标记ISSR或EST-SSR技术,分析了中国不同类型、不同地区茶树资源的遗传多样性和遗传结构,并基于EST-SSR标记的基因分型,分析了茶树分子标记与表型性状的关联性。
1、ISSR和EST-SSR标记在茶树遗传多样性研究上的比较分析
比较了ISSR和EST-SSR在多态性位点数、引物解析能力、多态性信息含量和标记系数等方面的差异,结果表明在位点检测能力上ISSR明显高于SSR,每条ISSR引物可检测的平均条带数(12.5)比每对EST-SSR引物(3.1)高3倍。ISSR标记的Rp值是EST-SSR标记的6.3倍,表现出较高的品种鉴别方面能力。ISSR标记多态性信息含量(PIC)和标记系数(MI)也明显高于EST-SSR,说明ISSR具较高的位点多态性和较高的标记效率。
尽管两种标记在检测中国、日本和肯尼亚茶树资源的遗传多样性差异上表现出较一致的趋势,但基于ISSR估算的遗传多样性指数(H=0.21)低于EST-SSR(H=0.28),这可能是由于ISSR属显性标记,无法检测到等位位点的变异,遗漏了部分重要的遗传信息,导致对遗传多样性水平的估计出现偏差,进而影响到遗传距离的估算和聚类分析的结果。而EST-SSR可以检测到等位位点的变异,比ISSR能更准确地反映和揭示供试品种的遗传多样性水平。同时由于单个EST-SSR标记检测到的位点数量较ISSR标记少,且特异性较强,谱带较易分辨,因此EST-SSR比ISSR标记更适用于对大量样本的分析。
2、中国无性系育成品种的遗传多样性和亲缘关系分析
利用27个ISSR引物对36个无性系茶树育成品种的DNA进行了扩增,共获得了500条多态性条带,平均每个引物扩增的多态性条带为18.5条。ISSR引物的Rp值较高,平均为9.59(变异范围5.69-14.47),表明具备较强的品种鉴别能力。IR29和IR44单个引物扩增形成的DNA指纹即可辨别36个不同的茶树品种。遗传多样性分析表明,不同地区育成品种的遗传多样性水平略有差异,遗传多样性指数(H)和Shannon信息指数(Ⅰ)的变异范围分别是0.20-0.23和0.31-0.36。区域间茶树品种的遗传分化指数(Gst)的平均值为0.18,表明仅有18%的遗传多样性来源于区域间的差异,而82%的遗传多样性源自于区域内品种间的遗传差异。10个大面积主栽茶树品种的遗传多样性占供试品种总体多样性水平的88%。基于ISSR和EST-SSR标记的比较分析均表明,中国主栽茶树品种的遗传多样性明显高于日本和肯尼亚的茶树品种,表现出较广泛的遗传基础。聚类分析表明,茶树育成品种的亲缘关系不仅与其遗传背景有关,而且与地理来源有关。
3、中国绿茶与乌龙茶适制品种遗传多样性差异的比较分析
基于EST-SSR标记研究了31份绿茶和37份乌龙茶适制品种资源的遗传多样性差异,结果表明乌龙茶品种基因多样性指数(H)、多态性信息含量(PIC)和平均遗传距离(GD)均略高于绿茶品种。基于数学模型的聚类分析将供试品种分为两个亚类群,亚群A中67.9%的品种为乌龙茶适制品种;亚群B中71.0%的绿茶品种聚类其中。基于Nei遗传距离的聚类分析将供试品种分为三个类群,其中类群Ⅰ和Ⅱ中以乌龙茶品种为主,分别占69.6%和66.7%;而类群Ⅲ中包括了61.3%的绿茶品种。两种聚类方法均表明,大部分样本按品种适制类型聚类,但也有部分品种在群体结构中相互渗透,呈较明显的穿插分布,推测这与品种的地理来源和遗传背景有关。
4、中国茶树初选核心种质的遗传多样性和遗传结构分析
基于EST-SSR标记对272份初选茶树核心种质的遗传多样性和遗传结构进行了分析。结果表明供试种质的平均多态性信息含量(PIC)值为0.531,平均基因多样性(H)为0.562。依据PIC和H值的大小,对不同省区茶树资源的遗传多样性按由高到低的水平排序,依次为:广西＞云南＞广东＞福建＞浙江＞湖北＞江西＞重庆＞贵州＞陕西＞四川＞安徽＞湖南。我国茶树资源的遗传多样性的空间分布呈现的特点是,遗传多样性从茶树原产地由南向北,由西向东递减,并且沿海地区高于内陆地区,这为研究我国茶树遗传演化的地理路径提供了参考依据。
对不同种质类型茶树的遗传多样性进行比较分析,发现野生茶树群体的遗传多样性(H=0.563,PIC=0.529)高于地方品种(H=0.550,PIC=0.520)和选育品种(H=0.556,PIC=0.523),说明在栽培驯化和人工选择压力下,导致部分等位位点丢失,使栽培茶树的遗传多样性水平略有下降。对EST-SSR位点间的连锁不平衡(LD)情况进行配对检测,结果表明地方品种和选育品种(系)的不平衡成对位点数高于野生茶树资源,推测栽培茶树中较频繁的异交以及对特定基因位点的人为选择使位点间的连锁不平衡程度增加。
AMOVA分析表明,茶树的遗传多样性主要源于茶树群体内的遗传差异,群体间的遗传差异对整体遗传多样性的贡献较少(0.7%-1.2%),这主要是由于茶树作为异花授粉植物,其强大的基因流促进了不同群体间的基因交换,导致群体间的基因和基因型频率逐渐接近,分化系数降低,遗传距离较近。基于数学模型聚类将供试种质分为5个亚类群,而基于Nei遗传距离的聚类分析将供试种质分为4个群,其中亚群内的聚类品种基本与数学模型聚类的结果基本对应。两种聚类分析均表明,中国茶树资源存在明显的遗传结构,它与地理来源和种质类型均存在相关性。尽管多数地理来源相同的种质往往共聚在小类群中,但也有部分地理来源相同的种质分别在不同群中分散聚类的情况,说明中国初选茶树核心种质具有遗传多样性分布广泛的特点。
5、基于基因分型初步鉴定与茶树表型性状关联的EST-SSR标记
通过EST-SSR标记对112份材料进行基因分型,开展了分子标记与新梢一芽二叶长(BL)、一芽二叶百芽重(BW)、叶片长度(LL)、叶片宽度(LW)、咖啡碱含量(CAF)、氨基酸含量(AA)和茶多酚含量(TP)共7个茶树表型性状关联的初步分析。结果表明,在不考虑位点间的连锁不平衡(LD)和供试群体的结构(SA)时,利用ANOVA方法可检测到三个EST-SSR位点CS185、CS121和CS153与五个表型性状显著相关,其中标记185同时与BL、BW、LL和LW等4个表型性状显著相关,标记CS121同时与BW、LL和LW等3个表型性状显著相关,而骠CS153仅与AA显著相关。但在考虑位点间的连锁不平衡和供试群体结构的情况下,通过回归分析仅鉴定出2个EST-SSR标记CS153和CS84与两个表型性状显著关联,其中标记CS153与性状LL显著关联,对表型变异的解释率为0.07,而标记CS84与性状TP显著关联,对表型的解释率为0.35。
两种检测方法中,仅有一个标记CS153被同时检出,但与之关联的性状却不同。在不考虑供试样本群体结构的情况下,亚群的混合使整个群体所估计的LD强度增强,可能导致多态性位点与性状的相关性并非由功能性等位基因引起,从而可能提供了假阳性结果。因此在关联分析前有必要对群体结构进行分析和调节。
Tea (Camellia sinensis (L.) O. Kuntze) is an important non-alcoholic beverage crop which originated from China where there has diverse and abundant tea genetic resources. It is necessary to understand genetic variation and population structure in tea plant to guide germplsam collection, evaluation and breeding application. DNA markers are proved to be useful tools which have been broadly used in the study of accession identification, genetic diversity, genetic relationships of tea plant.
In this paper, the marker capability and efficiency were compared between ISSR and EST-SSR, and the genetic diversity and population structure were evaluated among tea genetic resources in China. Meanwhile, a preliminary study was carried out to analyze the relationship between EST-SSR markers andphenotypic traits .
1. Comparison of capability and efficiency between ISSR and EST-SSR marker
The capability and efficiency between ISSR and EST-SSR markers were compared based on parameters including polymorphic loci, resolving power (Rp), polymorphic information content (PIC) and marker index (MI). The results showed that the numbers of polymorphic bands amplified by each ISSR primer were 12.5, being three times higher than that of EST-SSR primers (3.1). Higher values of Rp, PIC and MI were obtained by ISSR marker than EST-SSR marker. These results indicated that ISSR has stronger capability for detecting polymorphic bands and higher marker efficiency than EST-SSR.
The study showed that ISSR and EST-SSR are both effective to reveal the level of genetic diversity among tea caltivars from China, Kenya and Japan. However, the average Nei's gene diversity (H) revealed by ISSR (H=0.21) was lower than EST-SSR (H=0.28), which could be ascribed to incapability for alleles detection by ISSR, leading to missing of some important genetic information. This will further influence the estimation of genetic distance and clustering analysis. While EST-SSR markers may be more accurate to evaluate genetic diversity than ISSR markers because of the former can reveal the alleles variation on a locus. Additionally, EST-SSR markers are more suitable for large-scale samples analysis than ISSR because the rare and clear bands are easily distinguished and recorded by EST-SSR.
2. Genetic diversity and relationship of clonal tea cultivars in China
The genetic diversity and relationship among 36 clonal tea cultivars were studied using ISSR makers. The total numbers of 500 polymorphic ISSR bands were produced, with average of 18.5 polymorphic bands per primer. The resolving power (Rp) of each primer varied from 5.69-14.47, with an average at 9.59. All of clutivars were discriminated by ISSR fingerprint amplified with primers IR29 and IR44, respectively. The polymorphism information content (PIC) of primers ranged from 0.79 to 0.95, with an average at 0.91. The Nei's gene diversity (H) and the Shannon's information index (I) varied from 0.20 to 0.23 and 0.31 to 0.36 in different region, respectively. The Gst was estimated to be 0.18, which indicated that most of genetic diversity came from the variation among cultivars (82%) rather than among regions (18%). And ten popular clonal cultivars which have planting area over 50 kha in China represented 88% of total genetic diversity. Comparing to Japan and Kenya, more abundant diversity were found in widely planted tea cultivars in China based on ISSR and EST-SSR markers. The clustering analysis showed that the genetic relationship was not only related to genetic background, but also to geographic origin.
3. Comparison of genetic diversity between green tea and Oolong tea cultivars
The genetic diversity between 31 green-tea cultivars and 37 Oolong-tea cultivars were studied by EST-SSR markers. The results showed that higher level of Nei's gene diversity (H), polymorphic information contents (PIC) and average genetic distance (GD) were estimated among Oolong-tea cultivars comparing to those among green-tea cultivars. Based on mathematic simulation model, the 68 accessions were classified into two populations A and B. In population A, Oolong-tea accessions accounted for 67.9% of clustering samples; while 71% of tested green cultivars were clustered into the population B. Based on the Nei's genetic distance, the 68 accessions were clustered into three populationsⅠ,ⅡandⅢ. In the populationsⅠandⅡ, Oolong tea cultivars occupied 69.6% and 66.7%, respectively, while 61.3% of tested green tea accessions were clustered into the populationⅢ. Both the above two kinds of clustering analysis showed that most of accessions were culstered into the same population according to theirs processing suitability. However it is exceptive for some cultivars, which may be attributed to theirs origin and genetic background.
4. Genetic diversity and population structure of primary core germplasm of tea in China
The genetic diversitiy and population structure were studied based on the 272 primary tea core germplasm in China using EST-SSR markers. The average values of PIC and H were estimated to be 0.531 and 0.562 among all 272 accessions, respectively. The level of genetic diversity was ranged from high to low in different provinces as following order as Guangxi>Yunnan>Guangdong>Fujian>Zhejiang>Hubei>Jiangxi>Chongqing>Guizhou>Shaanx i>Sichuan>Anhui>Hunan. The genetic diversity among tea plants showed decreasing tendency from original centers to noirh and east region, and higher level of genetic diversity existed in coastal region than that in inland region..
Wild tea plants showed higher level of genetic diversity than traditional landraces and bred cultivars, which indicated that the genetic diversity was influenced by long-standing domestication and artificial selection. The linkage disequilibrium (LD) between pairs of EST-SSR loci was ubiquitously found in different types of tea accessions. And lower level of LD was found in wild tea population comparing to traditional landraces and bred cultivars. It could be explained that frequent out-crossing and long-standing selection for special loci lead to the increase of LD degree among cultivated tea plants.
The analysis of molecular variance revealed that the variance component among accessions in same group was far higher than that among groups according to geographic origin and accession type. Strong gene flowing may gradually lead to similar frequency of gene and genotype among different populations for cross-pollinate crops like tea, resulting in low genetic differentiation and close genetic distance among populations. The 272 accessions were grouped into five populations by structure analysis based on mathematic simulation model, which was confirmed by N-J methods based on Nei's genetic distance. It is confirmed that the population structure was not only related with geographic origin, but accession types. Though a few of accessions from a same region were usually clustered together in small sub-population, most of tested accessions with a same origin and a same type were dispersedly distributed in different populations. It suggested that there had a broadly genetic variation among Chinese tea germplasm.
5. Association analysis for EST-SSR and tea phenotypic traits
The association between EST-SSR markers and phenotypic traits were studied by SSR genotyping. Three EST-SSR loci were detected to be correlated to five penotypic traits of tea by ANOVA methods if the LD between the loci and the population structure were not considered. Marker no.CS185 were significantly related to the length of fresh shoots with one bud and two leaves (BL), the weight of 100 fresh shoots with one bud and two leaves (BW), leaf length (LL) and leaf width (LW) and amino acid contents (AA). Marker no.CS121 was significantly related to BW, LL and LW while no.CS153 related to AA. However, the results were different if the LD between loci and population structure were considered. Only two loci were identified to be associated with leaf length and tea polyphenols contents (TP), respectively, by regression method. Only one marker (no.CS153) was detected in both of the above two method, but the related trait varied. The mixture of population could make high degree of LD among the tested populations, and it might lead to pseudo association between markers and traits. So it is necessary to consider LD and population structure during association analysis.
1、ISSR和EST-SSR标记在茶树遗传多样性研究上的比较分析
比较了ISSR和EST-SSR在多态性位点数、引物解析能力、多态性信息含量和标记系数等方面的差异,结果表明在位点检测能力上ISSR明显高于SSR,每条ISSR引物可检测的平均条带数(12.5)比每对EST-SSR引物(3.1)高3倍。ISSR标记的Rp值是EST-SSR标记的6.3倍,表现出较高的品种鉴别方面能力。ISSR标记多态性信息含量(PIC)和标记系数(MI)也明显高于EST-SSR,说明ISSR具较高的位点多态性和较高的标记效率。
尽管两种标记在检测中国、日本和肯尼亚茶树资源的遗传多样性差异上表现出较一致的趋势,但基于ISSR估算的遗传多样性指数(H=0.21)低于EST-SSR(H=0.28),这可能是由于ISSR属显性标记,无法检测到等位位点的变异,遗漏了部分重要的遗传信息,导致对遗传多样性水平的估计出现偏差,进而影响到遗传距离的估算和聚类分析的结果。而EST-SSR可以检测到等位位点的变异,比ISSR能更准确地反映和揭示供试品种的遗传多样性水平。同时由于单个EST-SSR标记检测到的位点数量较ISSR标记少,且特异性较强,谱带较易分辨,因此EST-SSR比ISSR标记更适用于对大量样本的分析。
2、中国无性系育成品种的遗传多样性和亲缘关系分析
利用27个ISSR引物对36个无性系茶树育成品种的DNA进行了扩增,共获得了500条多态性条带,平均每个引物扩增的多态性条带为18.5条。ISSR引物的Rp值较高,平均为9.59(变异范围5.69-14.47),表明具备较强的品种鉴别能力。IR29和IR44单个引物扩增形成的DNA指纹即可辨别36个不同的茶树品种。遗传多样性分析表明,不同地区育成品种的遗传多样性水平略有差异,遗传多样性指数(H)和Shannon信息指数(Ⅰ)的变异范围分别是0.20-0.23和0.31-0.36。区域间茶树品种的遗传分化指数(Gst)的平均值为0.18,表明仅有18%的遗传多样性来源于区域间的差异,而82%的遗传多样性源自于区域内品种间的遗传差异。10个大面积主栽茶树品种的遗传多样性占供试品种总体多样性水平的88%。基于ISSR和EST-SSR标记的比较分析均表明,中国主栽茶树品种的遗传多样性明显高于日本和肯尼亚的茶树品种,表现出较广泛的遗传基础。聚类分析表明,茶树育成品种的亲缘关系不仅与其遗传背景有关,而且与地理来源有关。
3、中国绿茶与乌龙茶适制品种遗传多样性差异的比较分析
基于EST-SSR标记研究了31份绿茶和37份乌龙茶适制品种资源的遗传多样性差异,结果表明乌龙茶品种基因多样性指数(H)、多态性信息含量(PIC)和平均遗传距离(GD)均略高于绿茶品种。基于数学模型的聚类分析将供试品种分为两个亚类群,亚群A中67.9%的品种为乌龙茶适制品种;亚群B中71.0%的绿茶品种聚类其中。基于Nei遗传距离的聚类分析将供试品种分为三个类群,其中类群Ⅰ和Ⅱ中以乌龙茶品种为主,分别占69.6%和66.7%;而类群Ⅲ中包括了61.3%的绿茶品种。两种聚类方法均表明,大部分样本按品种适制类型聚类,但也有部分品种在群体结构中相互渗透,呈较明显的穿插分布,推测这与品种的地理来源和遗传背景有关。
4、中国茶树初选核心种质的遗传多样性和遗传结构分析
基于EST-SSR标记对272份初选茶树核心种质的遗传多样性和遗传结构进行了分析。结果表明供试种质的平均多态性信息含量(PIC)值为0.531,平均基因多样性(H)为0.562。依据PIC和H值的大小,对不同省区茶树资源的遗传多样性按由高到低的水平排序,依次为:广西＞云南＞广东＞福建＞浙江＞湖北＞江西＞重庆＞贵州＞陕西＞四川＞安徽＞湖南。我国茶树资源的遗传多样性的空间分布呈现的特点是,遗传多样性从茶树原产地由南向北,由西向东递减,并且沿海地区高于内陆地区,这为研究我国茶树遗传演化的地理路径提供了参考依据。
对不同种质类型茶树的遗传多样性进行比较分析,发现野生茶树群体的遗传多样性(H=0.563,PIC=0.529)高于地方品种(H=0.550,PIC=0.520)和选育品种(H=0.556,PIC=0.523),说明在栽培驯化和人工选择压力下,导致部分等位位点丢失,使栽培茶树的遗传多样性水平略有下降。对EST-SSR位点间的连锁不平衡(LD)情况进行配对检测,结果表明地方品种和选育品种(系)的不平衡成对位点数高于野生茶树资源,推测栽培茶树中较频繁的异交以及对特定基因位点的人为选择使位点间的连锁不平衡程度增加。
AMOVA分析表明,茶树的遗传多样性主要源于茶树群体内的遗传差异,群体间的遗传差异对整体遗传多样性的贡献较少(0.7%-1.2%),这主要是由于茶树作为异花授粉植物,其强大的基因流促进了不同群体间的基因交换,导致群体间的基因和基因型频率逐渐接近,分化系数降低,遗传距离较近。基于数学模型聚类将供试种质分为5个亚类群,而基于Nei遗传距离的聚类分析将供试种质分为4个群,其中亚群内的聚类品种基本与数学模型聚类的结果基本对应。两种聚类分析均表明,中国茶树资源存在明显的遗传结构,它与地理来源和种质类型均存在相关性。尽管多数地理来源相同的种质往往共聚在小类群中,但也有部分地理来源相同的种质分别在不同群中分散聚类的情况,说明中国初选茶树核心种质具有遗传多样性分布广泛的特点。
5、基于基因分型初步鉴定与茶树表型性状关联的EST-SSR标记
通过EST-SSR标记对112份材料进行基因分型,开展了分子标记与新梢一芽二叶长(BL)、一芽二叶百芽重(BW)、叶片长度(LL)、叶片宽度(LW)、咖啡碱含量(CAF)、氨基酸含量(AA)和茶多酚含量(TP)共7个茶树表型性状关联的初步分析。结果表明,在不考虑位点间的连锁不平衡(LD)和供试群体的结构(SA)时,利用ANOVA方法可检测到三个EST-SSR位点CS185、CS121和CS153与五个表型性状显著相关,其中标记185同时与BL、BW、LL和LW等4个表型性状显著相关,标记CS121同时与BW、LL和LW等3个表型性状显著相关,而骠CS153仅与AA显著相关。但在考虑位点间的连锁不平衡和供试群体结构的情况下,通过回归分析仅鉴定出2个EST-SSR标记CS153和CS84与两个表型性状显著关联,其中标记CS153与性状LL显著关联,对表型变异的解释率为0.07,而标记CS84与性状TP显著关联,对表型的解释率为0.35。
两种检测方法中,仅有一个标记CS153被同时检出,但与之关联的性状却不同。在不考虑供试样本群体结构的情况下,亚群的混合使整个群体所估计的LD强度增强,可能导致多态性位点与性状的相关性并非由功能性等位基因引起,从而可能提供了假阳性结果。因此在关联分析前有必要对群体结构进行分析和调节。
Tea (Camellia sinensis (L.) O. Kuntze) is an important non-alcoholic beverage crop which originated from China where there has diverse and abundant tea genetic resources. It is necessary to understand genetic variation and population structure in tea plant to guide germplsam collection, evaluation and breeding application. DNA markers are proved to be useful tools which have been broadly used in the study of accession identification, genetic diversity, genetic relationships of tea plant.
In this paper, the marker capability and efficiency were compared between ISSR and EST-SSR, and the genetic diversity and population structure were evaluated among tea genetic resources in China. Meanwhile, a preliminary study was carried out to analyze the relationship between EST-SSR markers andphenotypic traits .
1. Comparison of capability and efficiency between ISSR and EST-SSR marker
The capability and efficiency between ISSR and EST-SSR markers were compared based on parameters including polymorphic loci, resolving power (Rp), polymorphic information content (PIC) and marker index (MI). The results showed that the numbers of polymorphic bands amplified by each ISSR primer were 12.5, being three times higher than that of EST-SSR primers (3.1). Higher values of Rp, PIC and MI were obtained by ISSR marker than EST-SSR marker. These results indicated that ISSR has stronger capability for detecting polymorphic bands and higher marker efficiency than EST-SSR.
The study showed that ISSR and EST-SSR are both effective to reveal the level of genetic diversity among tea caltivars from China, Kenya and Japan. However, the average Nei's gene diversity (H) revealed by ISSR (H=0.21) was lower than EST-SSR (H=0.28), which could be ascribed to incapability for alleles detection by ISSR, leading to missing of some important genetic information. This will further influence the estimation of genetic distance and clustering analysis. While EST-SSR markers may be more accurate to evaluate genetic diversity than ISSR markers because of the former can reveal the alleles variation on a locus. Additionally, EST-SSR markers are more suitable for large-scale samples analysis than ISSR because the rare and clear bands are easily distinguished and recorded by EST-SSR.
2. Genetic diversity and relationship of clonal tea cultivars in China
The genetic diversity and relationship among 36 clonal tea cultivars were studied using ISSR makers. The total numbers of 500 polymorphic ISSR bands were produced, with average of 18.5 polymorphic bands per primer. The resolving power (Rp) of each primer varied from 5.69-14.47, with an average at 9.59. All of clutivars were discriminated by ISSR fingerprint amplified with primers IR29 and IR44, respectively. The polymorphism information content (PIC) of primers ranged from 0.79 to 0.95, with an average at 0.91. The Nei's gene diversity (H) and the Shannon's information index (I) varied from 0.20 to 0.23 and 0.31 to 0.36 in different region, respectively. The Gst was estimated to be 0.18, which indicated that most of genetic diversity came from the variation among cultivars (82%) rather than among regions (18%). And ten popular clonal cultivars which have planting area over 50 kha in China represented 88% of total genetic diversity. Comparing to Japan and Kenya, more abundant diversity were found in widely planted tea cultivars in China based on ISSR and EST-SSR markers. The clustering analysis showed that the genetic relationship was not only related to genetic background, but also to geographic origin.
3. Comparison of genetic diversity between green tea and Oolong tea cultivars
The genetic diversity between 31 green-tea cultivars and 37 Oolong-tea cultivars were studied by EST-SSR markers. The results showed that higher level of Nei's gene diversity (H), polymorphic information contents (PIC) and average genetic distance (GD) were estimated among Oolong-tea cultivars comparing to those among green-tea cultivars. Based on mathematic simulation model, the 68 accessions were classified into two populations A and B. In population A, Oolong-tea accessions accounted for 67.9% of clustering samples; while 71% of tested green cultivars were clustered into the population B. Based on the Nei's genetic distance, the 68 accessions were clustered into three populationsⅠ,ⅡandⅢ. In the populationsⅠandⅡ, Oolong tea cultivars occupied 69.6% and 66.7%, respectively, while 61.3% of tested green tea accessions were clustered into the populationⅢ. Both the above two kinds of clustering analysis showed that most of accessions were culstered into the same population according to theirs processing suitability. However it is exceptive for some cultivars, which may be attributed to theirs origin and genetic background.
4. Genetic diversity and population structure of primary core germplasm of tea in China
The genetic diversitiy and population structure were studied based on the 272 primary tea core germplasm in China using EST-SSR markers. The average values of PIC and H were estimated to be 0.531 and 0.562 among all 272 accessions, respectively. The level of genetic diversity was ranged from high to low in different provinces as following order as Guangxi>Yunnan>Guangdong>Fujian>Zhejiang>Hubei>Jiangxi>Chongqing>Guizhou>Shaanx i>Sichuan>Anhui>Hunan. The genetic diversity among tea plants showed decreasing tendency from original centers to noirh and east region, and higher level of genetic diversity existed in coastal region than that in inland region..
Wild tea plants showed higher level of genetic diversity than traditional landraces and bred cultivars, which indicated that the genetic diversity was influenced by long-standing domestication and artificial selection. The linkage disequilibrium (LD) between pairs of EST-SSR loci was ubiquitously found in different types of tea accessions. And lower level of LD was found in wild tea population comparing to traditional landraces and bred cultivars. It could be explained that frequent out-crossing and long-standing selection for special loci lead to the increase of LD degree among cultivated tea plants.
The analysis of molecular variance revealed that the variance component among accessions in same group was far higher than that among groups according to geographic origin and accession type. Strong gene flowing may gradually lead to similar frequency of gene and genotype among different populations for cross-pollinate crops like tea, resulting in low genetic differentiation and close genetic distance among populations. The 272 accessions were grouped into five populations by structure analysis based on mathematic simulation model, which was confirmed by N-J methods based on Nei's genetic distance. It is confirmed that the population structure was not only related with geographic origin, but accession types. Though a few of accessions from a same region were usually clustered together in small sub-population, most of tested accessions with a same origin and a same type were dispersedly distributed in different populations. It suggested that there had a broadly genetic variation among Chinese tea germplasm.
5. Association analysis for EST-SSR and tea phenotypic traits
The association between EST-SSR markers and phenotypic traits were studied by SSR genotyping. Three EST-SSR loci were detected to be correlated to five penotypic traits of tea by ANOVA methods if the LD between the loci and the population structure were not considered. Marker no.CS185 were significantly related to the length of fresh shoots with one bud and two leaves (BL), the weight of 100 fresh shoots with one bud and two leaves (BW), leaf length (LL) and leaf width (LW) and amino acid contents (AA). Marker no.CS121 was significantly related to BW, LL and LW while no.CS153 related to AA. However, the results were different if the LD between loci and population structure were considered. Only two loci were identified to be associated with leaf length and tea polyphenols contents (TP), respectively, by regression method. Only one marker (no.CS153) was detected in both of the above two method, but the related trait varied. The mixture of population could make high degree of LD among the tested populations, and it might lead to pseudo association between markers and traits. So it is necessary to consider LD and population structure during association analysis.
引文
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