Studies On Genetic Diversity And Structure Of Tea Germplasm In China Based On ISSR And EST-SSR Markers

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 markerThe 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 cultivarsThe 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 populationsâ… ,â…¡andâ…¢. In the populationsâ… andâ…¡, Oolong tea cultivars occupied 69.6% and 66.7%, respectively, while 61.3% of tested green tea accessions were clustered into the populationâ…¢. 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 ChinaThe 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 traitsThe 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.