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新疆野苹果(Malus sieversii)群体遗传结构与核心种质构建方法

Population Genetic Structure and Method of Constructing Core Collection for Malus Sieversii

【作者】 张春雨

【导师】 陈学森; 束怀瑞;

【作者基本信息】 山东农业大学 , 果树学, 2008, 博士

【摘要】 新疆野苹果(Malus sieversii)可能是现代栽培苹果(M. domestica)的祖先种,遗传多样性极为丰富,主要分布在中亚天山山脉,在中国主要分布在新疆的巩留县、新源县、霍城县和裕民县。但近年来,新疆野苹果遭到严重的破坏,群落面积急剧减少,本文利用分子系统学的原理和方法,采用SSR和SRAP标记对新疆野苹果群体遗传结构和遗传变异进行分析,并采用分子标记和表型数据,分别探讨了新疆野苹果核心种质构建方法,研究结果将为这一珍贵资源的科学保护和有效利用以及丰富生物进化理论等具有重要意义。主要研究结果如下:1.利用SSR标记对新疆野苹果遗传多样性研究表明:8对SSR引物在109个株系中共扩增出128个位点,多态性位点百分比为100%,具有较高的Nei基因多样度和香农信息指数(H = 0.2619; I = 0.4082)。采用SRAP标记对新疆野苹果遗传多样性进行了研究,10对SRAP引物组合共扩增出209条带,多态性位点百分比为98.56%。结果显示,新疆野苹果遗传多样性较为丰富。2.利用SSR标记和SRAP标记对新疆野苹果四个群体的遗传多样性进行了研究。SSR标记显示,巩留群体遗传多样性最为丰富,扩增出113个位点,扩增的多态性位点百分比为88.28%,Nei基因多样度和香农信息指数分别为0.2538和0.3912,其次为霍城群体(A = 112; P = 87.5%; H = 0.2501; I = 0.388),之后为新源群体(A = 108; P = 84.38%; H = 0.245; I = 0.377),而裕民群体遗传多样性最低(A = 100; P = 78.12%; H = 0.2273; I = 0.3482)。SRAP标记显示,新疆野苹果巩留群体遗传多样性最为丰富(hs = 0.304),其次为霍城群体(hs = 0.287)、裕民群体(hs = 0.274)和新源群体(hs = 0.260)。因此,巩留群体应优先保护。3.采用SSR和SRAP标记对新疆野苹果四个群体的遗传结构研究都显示,新疆野苹果遗传变异主要存在群体内。对于SSR标记,群体内变异占总变异的93.6%,而群体间变异仅占总变异的6.4%。对于SRAP标记,群体内变异占总变异的77.9%,群体间变异占总变异的22.1%。SSR标记测得的GST基因流为7.265,说明新疆野苹果存在一定的基因交流,而花粉和种子的传播可能是基因交流的主要原因。4.根据SSR数据,对四个群体UPGMA聚类分析结果表明,巩留群体和新源群体遗传关系最近(D = 0.0147; I = 0.9854),霍城群体次之,裕民群体远离其它三个群体。对109个株系UPGMA聚类分析显示,所有的株系可以分为10类,来自同一群体的大多数株系都能聚在一起,说明巩留群体、新源群体、霍城群体和裕民群体,四个群体是相对独立的群体,但同时存在部分基因交流。5.对新疆野苹果四个群体的主坐标轴分析(PCOORD)显示,对于SRAP标记,巩留群体和新源群体之间株系有部分重叠,霍城和裕民群体间株系有部分重叠,位于伊犁野果林的巩留、新源和霍城群体可能是原初起源中心,而裕民群体由霍城群体传播而来,为次生起源中心。6.对于新疆野苹果,SSR和SRAP标记相比较,SSR具有更为广阔范围的株系间以及群体内株系间遗传变异,而SRAP具有更广范围的群体间遗传变异,因此SSR标记更适于新疆野苹果群体内株系间以及株系间遗传变异的分析,SRAP标记更适于新疆野苹果群体间遗传变异的分析。7.对SSR数据、SRAP数据和SSR与SRAP联合数据的株系间遗传相似性系数矩阵的相关性进行Mantel矩阵相关性检测显示,三者两两间极显著相关,其中SRAP数据同SSR与SRAP联合数据间具有较高的相关性(r = 0.929),因此将SSR和SRAP数据联合并不是估计新疆野苹果群体遗传多样性和群体遗传结构的最佳方案。8.采用SSR标记,以109个新疆野苹果株系为材料,研究了利用分子标记构建新疆野苹果核心种质的方法。同对照随机取样策略比较,位点优先取样策略能构建一个更有代表性的核心种质。当选取25个株系时,根据SM、Jaccard或Nei&Li遗传距离进行多次聚类,采用位点优先法,是构建新疆野苹果较合适的方法。9.以300个新疆野苹果株系的10个表型性状的遗传多样性为数据,研究了表型性状构建新疆野苹果核心种质的方法。采用马氏距离聚类优于欧氏距离,5种聚类方法比较,类平均法、离差平法和法和最长距离法优于最短距离法和中间距离法,优先取样策略优于随机和偏离度取样策略。本研究显示,当取样比例为20%时,采用马氏距离,利用离差平法和法进行多次聚类,结合优先取样策略构建的核心种质最有代表性,是构建新疆野苹果的最佳的方法。

【Abstract】 Malus sieversii, the main progenitor of domesticated apple (Malus×domestica Borkh.), is rich in genetic diversity. M. sieversii is mainly distributed in Tianshan Mountains in Central Asia including Gongliu population, Xinyuan population, Huocheng population and Yumin population in China. Recently, M. sieversii is suffering serious destruction and is sharply decreasing in area. The genetic diversity and population genetic structure for four M. sieversii groups were analyzed using principles of molecular systematics and SSR marker and SRAP marker techniques and the methods of constructing core collection were studied by molecular marker and morphology traits, respectively, in order to provide science evidence for conservation and utilization, to construct core collection of M. sieversii. The main results are as follows:1. The genetic diversity of M. sieversii was analyzed using SSR marker. The results showed that the total 128 alleles were amplified by 8 pair of SSR primers on 109 M. sieversii accessions. The percentage of polymorphic loci (P = 100%), Nei’s gene diversity (H = 0.2619) and Shannon information index (I = 0.4082). The genetic diversity of M. sieversii by SRAP marker showed that the total 209 bands were amplified by 10 pair of SRAP primers. The percentage of polymorphic loci (P) was 98.56%. The results showed that genetic diversity of M. sieversii was very abundant.2. The genetic diversity of four M. sieversii populations were studied using SSR marker and SRAP marker. SSR marker showed that the genetic diversity of Gongliu population was the richest in the four populations, with 113 for amplified bands, 88.28% for the percentage of polymorphic loci, 0.2538 for Nei’s gene diversity and 0.3912 for Shannon information index. Followed by Huocheng population (A = 112; P = 87.5%; H = 0.2501; I = 0.388), Xinyuan population (A = 108; P = 84.38%; H = 0.245; I = 0.377), Yunmin population (A = 100; P = 78.12%; H = 0.2273; I = 0.3482). SRAP marker showed that Gongliu population (hs = 0.304) was the richest in the diversity, followed by Huocheng population (hs = 0.287), Yumin population (hs = 0.274) and Xinyuan population (hs = 0.260). On the basis of the highest genetic diversity, Gongliu population should be given a high priority consideration in M. sieversii population’s in situ germplasm conservation.3. Both SSR marker and SRAP marker showed that genetic variation of M. sieversii was mainly within population. For SSR marker, genetic variation within groups accounted for 85.3% of total variations, genetic variation within population accounted for 85.3% of total variations, genetic variation between the populations accounted for 6.4% of total variations. For SRAP marker, genetic variation within population accounted for 77.9% of total variations, genetic variation between the populations accounted for 22.1% of total variations. Gene flow of GST was 7.265 according to SSR marker showed that there were partly gene exchanges among four populations. It is suggested that the main way of gene exchanges could be transferred by pollen or by seed.4. The results from UPGMA cluster analysis for four M. sieversii populations showed that the similarity between the Gongliu population and Xinyuan population was the highest (D = 0.0147; I = 0.9854), then between Huocheng population and Gongliu and Xinyuan populations, Yumnin population was the lowest with the other three population. UPGMA cluster analysis from 109 M. sieversii accessions showed all the accessions were clustered into ten groups. The accessions from the same population were clustered together, which demonstrated that the four populations were relatively independent populations, but there were partly gene exchanges5. Diagram among 109 M. sieversii from the four populations based on principal coordinates analysis showed that Huocheng and Yumin accessions had partly overlapped and Gongliu and Xinyuan accessions also had partly overlapped for SRAP marker. It is suggested that Gongliu population, Xinyuan population and Huocheng population located in Ily Valley was the primitive center of origin of M. sieversii and M. sieversii seeds and accessions of Huocheng population spread to the North and formed Yumin population. Yumin population was secondary center of origin of M. sieversii.6. For M. sieversii, SSR showed the highest range of genetic variation among the accessions and among the accessions within population, SRAP showed the highest range of genetic variation among the population. Therefore, SSR is a good choice to assess genetic variation among the accessions and among the accessions within population and SRAP is a good choice to assess genetic variation among the population.7. Mantel matrix correspondence test was used to compare the similarity matrices among SSR data, SRAP data and combined data SSR and SRAP. The results showed the correlation coefficients were statistically significant for two markers and their combination. The higher correspondence was found between SRAP and combined data (r = 0.929), which showed that analyses using SSR and SRAP data together do not seem to be the most efficient manner of assessing genetic diversity and population genetic structure of M. sieversii because the result was similar to using SRAP alone.8. The method for constructing core collection of M. sieversii based on molecular markers data was proposed, according to SSR marker, using 109 M. sieversii accessions. Compared with the random sampling strategy, allele preferred sampling could construct more representative core collections. When 25 M. sieversii accessions was selected, allele preferred sampling strategy combined with SM, Jaccard or Nei&Li genetic distances using stepwise clustering was the suitable method for constructing M. sieversii core collection.9. The genetic diversity of 10 traits from 300 M. sieversii accessions was used to study method for constructing M. sieversii core collection using morphology. The results showed that Mahalanobis distance was the much better than Euclidean distance, UPGMA, Ward’s method and Complete linkage was better than Single linkage and Median method, and preferred sampling was more suitable than random sampling and deviation sampling for constructing core collection. When 20% accessions were selected, Mahalanobis distance and Ward’s method using stepwise clustering combining with preferred sampling can construct a most reprehensive core collection and was the most suitable method for constructing M. sieversii core collection.

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