基于SSR标记的132份甘薯种质指纹图谱的构建及遗传多样性分析

利用SSR分子标记技术,构建132份甘薯种质的DNA指纹图谱,并进行遗传多样性分析,旨在为甘薯种质资源亲缘关系鉴定、分类提供理论依据。利用筛选的核心引物进行PCR扩增,通过聚丙烯酰胺凝胶电泳检测显示,19对引物共扩增出232个条带,其中多态性条带165条,多态性比率为71.1%,平均每对引物扩增出8.68个条带,多态性信息含量变化范围在0.6706~0.9331之间,平均为0.8158;其中引物SSR9和引物C33可将132份种质完全区分开,并构建供试材料的DNA指纹图谱,供试材料遗传距离在0.0363~0.5939之间,平均为0.4087,表明种质资源间遗传多样性丰富。基于SSR标记对供试材料进行聚类分析,将供试材料分为2个类群,第Ⅰ类群分为两个亚类,第Ⅰ-1亚类包括济薯25和3份日本引进品种日本金千贯、安納芋、日本薯;第Ⅰ-2亚类包括济徐薯23、苏丹、济薯09281。第Ⅱ类群分为两个亚类,第Ⅱ-1亚类由S07甘薯品系和与其亲缘关系较近的20份甘薯种质组成;第Ⅱ-2亚类由剩余的70份甘薯种质组成,为甘薯分子辅助育种中亲本的选择提供理论依据。     

基于TP-M13-SSR指纹图谱的中国原产苹果属植物分子身份证的建立

利用TP-M13-SSR分子标记方法,构建27份中国原产苹果属植物在12个SSR位点的指纹图谱,运用条码技术生成其分子身份证。12对引物共获得251个等位基因,平均21个。引物多态性好,仅用引物CH05b06即可区分全部供试材料。27份苹果材料在12个SSR位点遗传多样性、多态性信息含量和位点杂合度的变化范围为0.6620～0.9455、0.6327～0.9211和0.6538～0.9319。基于CH05b06位点处获得的指纹谱图即可得到每份供试材料独有的分子身份证。TP-M13-SSR分子标记技术适用于苹果属植物种质资源的指纹图谱构建,利于分子基础数据库的积累。基于苹果种质资源TP-M13-SSR指纹图谱可获得每份苹果种质资源独有的分子身份证。     

32个柿主栽品种SSR图谱构建及遗传变异分析

以32份柿主栽品种为试验材料,利用SSR标记技术构建其指纹图谱并进行遗传多样性分析。从78对候选引物中筛选出20对多态性高、稳定性好的引物作为核心引物,构建柿主栽品种SSR指纹图谱。结果显示:(1)20对引物在32份材料中共扩增出183条多态性条带,每对引物扩增出3～20条不等,平均每对引物扩增出9.15条,多态性比率为81.3%。各个位点的杂合度在0.410 3～0.914 3之间,平均为0.702 7。(2)8对引物在12个品种上具有特征带型,采用5对引物进行组合鉴定即可将32个柿品种完全区分开。(3)依据SSR带型特征,对每对引物生成的不同带型直接编号,简化柿SSR带型记录方法,并利用每个品种的带型编号,建立其DNA指纹图谱,结果表明,核心引物组合法比特征谱带法更适用于构建中国柿主栽品种DNA指纹图谱。(4)根据系统聚类分析将32个柿主栽品种分为两大类,品种间的亲缘关系与地理来源具有一定的相关性。     

中国鸭茅主栽品种DNA指纹图谱构建

利用SSR标记和SCoT标记构建了我国主栽的21个鸭茅品种的DNA指纹图谱。从180对SSR引物和80个SCoT引物中,筛选出多态性高、谱带清晰的SSR引物和SCoT引物各24个。24对SSR引物在供试材料中共检测到186个条带,其中多态性条带为175个,品种特异条带6个,平均多态性比率94.03%,多态性信息量均值0.845,Shannon指数变幅0.4479~0.6549,基因多样性指数变幅0.2946~0.4633,可鉴别的品种数2~21个;利用24个SCoT引物在供试材料中共检测到321个条带,其中多态性条带为249个,品种特异条带6个,平均多态性比率76.33%,多态性信息量均值0.907,Shannon指数变幅0.2588~0.6329,基因多样性指数变幅0.1695~0.4451,可鉴别的品种数1~21个;5对SSR引物和5个SCoT引物在10个品种上具有唯一特征谱带,最终综合各项指标筛选出5个引物(A01E14、A01K14、B03E14、D02K13和SCoT23)上的37个条带用于鸭茅品种DNA指纹图谱构建,数据库中每个品种均具有唯一DNA指纹编码,构建的DNA指纹数据可用于鸭茅品种真伪鉴定,为品种权保护提供了科学依据。     

中国35个苦荞审定品种EST-SSR指纹图谱构建与遗传多样性分析

核心引物对种质资源遗传多样性分析、品种鉴定、指纹图谱构建等研究具有重要价值。本研究以35个苦荞（Fagopyrum tataricum（L.） Gaertn）审定品种为材料,从91对苦荞EST-SSR引物中筛选出50对多态性引物。综合考虑引物多态性信息量（PIC）大小、鉴别力（DP）,筛选出等位变异位点数在2~4,PIC值在0.60~0.78之间的6对引物（SSR9007、SSR6873、SSR7642、SSR2234、SSR6789、SSR68216）构建了供试品种的分子指纹图谱。遗传多样性聚类分析结果表明,供试品种的相似系数为0.50~0.99。当遗传相似系数为0.60时,可将供试品种分为4大类群,其中54.3%的供试品种被聚为一类,表明苦荞审定品种遗传组成差异较小,遗传基础狭窄。聚类结果表明各类群间没有明显的地域分布趋势,但能较好的反映供试品种间的亲缘关系。     

应用SRAP标记绘制88份南瓜属种质资源DNA指纹图谱

为了给南瓜属种质资源鉴定和分类提供分子生物学依据,本研究采用SRAP分子标记技术与DNAMAN指纹图谱绘制软件对88份南瓜属种质资源(包含美洲南瓜、中国南瓜、印度南瓜)进行分子指纹图谱绘制。结果表明:35对SRAP多态性引物共扩增出499条清晰条带,其中多态性条带438条,多态性条带比率高达87.8%。根据扩增出的条带成功绘制出88份南瓜属种质资源的DNA指纹图谱,每一份种质都具有其独特的分子身份证,使得每份种质均可被区别开来。其中,多态性最好的引物是E5EM8,可以同时绘制72份南瓜属种质资源的指纹图谱。所有供试材料用5对多态性SRAP引物即可全部区别开来。研究表明,SRAP分子标记技术可成功地绘制南瓜属种质资源DNA指纹图谱。本研究对南瓜属种质资源鉴别、分子数据库构建及品种权保护具有较重要的意义。     

基于EST-SSR标记的甘薯种质资源DNA指纹图谱构建

采用EST-SSR标记构建了国家种质广州甘薯圃中52份甘薯种质资源的DNA指纹图谱。利用52份供试资源,从早期筛选出的342对候选多态性引物中筛选出16对核心引物,16对引物在52份资源中共扩增出159个等位位点,每对引物的等位位点数为5~19个不等,平均为9.94个,多态性信息含量变化范围为0.6235~0.9593,平均为0.7991。选择带型清晰、重复性好、易于统计且能将52份资源完全区分开的2对引物组合构建供试资源的DNA指纹图谱。NTSYS软件聚类分析表明,EST-SSR标记能正确反映出不同资源间的亲缘关系,为构建甘薯大型DNA指纹图谱数据库奠定了基础。     

太湖稻区与国内部分香稻SSR指纹图谱构建及遗传多样性初析

以太湖稻区和国内其他地区的39个香稻品种,以及籼型恢复系2个对照品种为研究材料,利用SSR分子标记进行DNA指纹图谱构建和遗传多样性分析。从40对国标中公布的水稻SSR引物中筛选出13对核心引物,在41个水稻品种中共检测到36个多态性片段。据此建立41个水稻品种的DNA指纹图谱,进行聚类分析,发现供试41个品种的遗传相似系数在0.58以上,而供试香稻品种的遗传相似系数在0.64以上,基本反映了不同品种间的亲缘关系。     

小麦DUS测试已知品种DNA指纹数据库构建及其应用

为解决DUS测试中特异性测试近似品种筛选难的问题,本研究基于2256份DUS测试小麦已知品种构建DNA指纹数据库。首先利用81对SSR引物对96份小麦品种进行遗传相似度分析。结果表明,81对SSR引物扩增出84个位点,共检测到731个等位变异,每个位点的等位变异数在3～18之间,多态性信息指数(PIC)变化范围为0.29～0.89。选取42个SSR标记构建了2256份小麦品种DNA指纹数据库,共获得148493个数据,除引物barc14、xgwm341之外,其他引物数据缺失率在5%以内。对176份小麦品种进行DNA指纹数据采集和特异性测试,结果表明不具有特异性的申请品种与其最近似品种的遗传相似度都在90%以上;本研究基于42对SSR荧光标记引物构建了我国小麦DUS测试已知品种的DNA指纹数据库,确定近似品种筛选的遗传相似度阈值为80%,建议将与申请品种遗传相似度高于80%的已知品种作为近似品种进行田间种植和特异性评价。     

虎杖种质资源的分子标记研究

本文应用RAPD、ISSR和SRAP标记对26份虎杖种质资源遗传多样性进行检测.在22个引物中有17个引物(77.3%)扩增产物具多态性,多态性水平相对较高.22个引物共得到98条扩增DNA片段,其中90.8%具有多态性.每个多态性引物平均可扩增出5.24个多态性片段.聚类分析表明,利用BAPD、ISSR和SRAP技术相结合可将全部供试材料区分开,26份材料在Gs值0.54水平上全部聚为一类,以所有材料间的平均遗传相似遗传系数0.71为阈值,将其分为11类.虎杖种质资源在分子水平上确实存在较大遗传差异,RAPD、ISSR和SRAP标记可作为构建虎杖DNA指纹图谱的有效工具.     

基于SSR标记的山东省小麦DNA指纹图谱的构建

本文以山东省41份小麦种质资源为材料,使用46对引物,通过SSR技术对其进行了DNA指纹数据库的构建。结果显示,所采用的46对引物在本实验材料中共检测到69个等位基因,有较好的多态性。利用NTSYS进行UPGMA聚类分析后,发现这41种材料在遗传相似系数0.68为阀值处可以分为3个类群。实验证明该方法能够分辨各个种质间的亲缘关系,能够较好满足小麦DNA指纹数据库的构建要求,对山东省小麦遗传资源的收集、保存、分类、评价、核心种质的建立等研究工作提供理论依据。     

High throughput analysis of grape genetic diversity as a tool for germplasm collection management

Using 20 SSR markers well scattered across the 19 grape chromosomes, we analyzed 4,370 accessions of the INRA grape repository at Vassal, mostly cultivars of Vitis vinifera subsp. sativa (3,727), but also accessions of V. vinifera subsp. sylvestris (80), interspecific hybrids (364), and rootstocks (199). The analysis revealed 2,836 SSR single profiles: 2,323 sativa cultivars, 72 wild individuals (sylvestris), 306 interspecific hybrids, and 135 rootstocks, corresponding to 2,739 different cultivars in all. A total of 524 alleles were detected, with a mean of 26.20 alleles per locus. For the 2,323 cultivars of V. vinifera, 338 alleles were detected with a mean of 16.9 alleles per locus. The mean genetic diversity (GDI) was 0.797 and the level of heterozygosity was 0.76, with broad variation from 0.20 to 1. Interspecific hybrids and rootstocks were more heterozygous and more diverse (GDI?=?0.839 and 0.865, respectively) than V. vinifera cultivars (GDI?=?0.769), Vitis vinifera subsp. sylvestris being the least divergent with GDI?=?0.708. Principal coordinates analysis distinguished the four groups. Slight clonal polymorphism was detected. The limit between clonal variation and cultivar polymorphism was set at four allelic differences out of 40. SSR markers were useful as a complementary tool to traditional ampelography for cultivar identification. Finally, a set of nine SSR markers was defined that was sufficient to distinguish 99.8% of the analyzed accessions. This set is suitable for routine characterization and will be valuable for germplasm management.     

基于引物“随机组合”构建观赏桃SSR指纹图谱

近年来,我国观赏桃新品种日渐繁多、名称混乱、市场难以监管,同时用以区分品种的SSR指纹图谱的构建方法在研究界无统一的科学标准,尤其是构成最终引物组合的核心引物的确定,具体操作流程层出不穷、五花八门。为探索筛选SSR指纹图谱核心引物的科学方法,同时构建观赏桃SSR指纹图谱,该研究选用35对已报道的SSR引物对22份观赏桃种质进行试验。结果表明:通过PCR扩增与分析,多态性较高的8对引物——候选引物总共扩增出31个多态性条带,变幅为3~5个,PIC值变幅为0.458~0.668,MI值变幅为1.374~3.340。采用"随机组合"法对8对引物进行C_8~1、C_8~2、C_8~3…依次分析,得到区分能力最强的3种不同的最少引物组合方式——候选组合,并能区分出18份种质,从中发现区分能力最强的3种引物组合方式并不都是由引物PIC值、alleles数量或MI值等多态性指标最高的引物组成,而是由互补性最强的引物组成。选用组合内各引物多态性条带总数最多的组合方式"4-3"(BPPCT001+BPPCT015a+BPPCT017+BPPCT025)为22份观赏桃种质构建了指纹图谱。基于此,通过常规多态性指标筛选候选引物可以确定出单对引物鉴别能力最强的少量引物;通过"随机组合"筛选候选组合可以进一步确定出引物之间互补性最强的几种组合方式;根据组合内各引物的多态性条带总数确定最终核心引物可以确定出可扩容性最大的引物组合。该研究最终建立了候选引物——候选组合——核心引物组合"三步法"确定SSR指纹图谱核心引物组合的科学方法,不仅为22份供试观赏桃种质构建了SSR指纹图谱,也为其它作物SSR指纹图谱的构建提供了新的思路。     

Microsatellite marker-based identification and genetic relationships of olive cultivars from the Extremadura region of Spain

Seventy-seven olive accessions corresponding to 25 cultivars from the Extremadura region of Spain were studied using four microsatellite or SSR markers in order to fingerprint them, and evaluate genetic similarity and relationships between local and introduced olive cultivars. The number of alleles per locus ranged from 4 to 8, with a mean of 6.25 alleles per primer pair (a total of 25 alleles). The observed heterozygosity ranged from 0.58 to 0.95, while the expected heterozygosity varied between 0.68 and 0.83. The polymorphism information content values ranged from 0.63 to 0.79. The mean polymorphism information content value of 0.70 for the SSR loci provided sufficient discriminating ability to evaluate the genetic diversity among the cultivars. The SSR data allowed unequivocal identification of all the cultivars; a combination of three SSR markers was sufficient to discriminate all 25 olive cultivars. A dendrogram was prepared, using the unweighted pair-group method with arithmetic mean clustering algorithm; it depicted the pattern of relationships between the cultivars. Most of the local cultivars grouped according to their geographic origin. No clear clustering trends were observed when the morphological traits of fruit endocarps or fruit use of cultivars were employed as analysis criteria. We conclude that there is a high level of variability among local olive cultivars from the Extremadura region at both the morphological and molecular levels; these data should be useful for identifying and distinguishing local germplasm.     

中国主栽香菇品种SSR指纹图谱的构建

以商业栽培的25个香菇(Lentinula edodes)品种为材料,应用SSR分子标记技术进行区别性分析。本研究使用14对引物,引物的多态性为100%,每对引物产生的等位基因数为2～9个,平均5.0个,基因型数为2～12个,平均6.3个。预期杂合度为0.1151～0.8131,平均预期杂合度为0.6126;PIC值为0.1064～0.7736,平均PIC值为0.5541。25个品种中,除申香10号和申香12号不能区分外,对其他23个品种清晰鉴别,为构建香菇栽培品种的SSR分子指纹图谱提供了依据和方法。本方法获得的数据可以成为重复性良好、实验室间可比对的香菇栽培品种标准指纹图谱,在品种特异性鉴定中不再需要已有所有品种做参照,较RAPD、ISSR、SRAP等鉴定方法工作量大大减少。     

红麻微卫星DNA标记指纹图谱的构建

DNA指纹图谱对新品种选育、种质资源保存和管理具有重要的意义。然而,利用SSR标记构建红麻DNA指纹图谱的研究仍十分有限。在本研究中,利用课题组开发并筛选出的131对SSR引物,分析不同来源的96份红麻种质资源,包括红麻品种审定的区试对照品种福红952。结果表明,131对引物共扩增出375条带,平均每对引物扩增出2.6条带。以遗传相似系数0.614为切割线时,可以分为2个类群,52个为类群P1,44个为类群P2;以遗传相似系数0.710做切割线,可分为5个亚群。利用这131对引物标记所得的数据成功绘制了一份85个品种独特的指纹图谱,其中福红952可被HcEMS238引物特异识别。其他11份因存在遗传相似性高的现象,未被识别。上述结果为红麻品种的真实性鉴定及遗传多样性分析提供依据。     

Simple sequence repeat (SSR) analysis for assessment of genetic variability in apricot germplasm

Thirty SSR primer combinations, developed from peach SSR-enriched genomic libraries and BAC libraries of peach [ Prunus persica (L.) Batsch.], were tested for cross amplification with 74 apricot ( Prunus armeniaca L.) germplasm accessions. Twelve primer pairs amplified 14 polymorphic SSR loci useful for discriminating most apricot cultivars, as well as for investigating patterns of variation in apricot germplasm. Levels of polymorphism were higher than the levels described using other codominant marker systems (i.e., isozymes, RFLP markers). Overall, 107 alleles were identified, and all but 11 accessions were unambiguously discriminated. Genetic differentiation of native germplasm into traditional ecogeographical groups was low, with a high level of genetic identity (> 0.75) between the groups. However, neighbor joining cluster analysis of marker distances between cultivars reflected the complex history of apricot domestication, producing groupings not evidently based on the geographical origin of the cultivars. Distant positioning of Chinese cultivars on UPGMA and neighbor joining dendrograms supports the authors' consideration of Chinese apricots as subspecies, Prunus armeniaca var. ansu Maxim., rather than a separate species.     

河北省大豆推广品种遗传多样性分析

利用主要农艺性状以及SSR和AFLP2种分子标记,对河北省41个大豆推广品种进行遗传多样性分析,以便为种质资源利用和创新提供依据。农艺性状聚类结果将41个材料划分为3个类群和2个特殊品种,聚类结果与材料系谱来源相差悬殊,不能反映材料间亲缘关系。SSR和AFLP数据聚类结果将41个材料划分为4个SAG（SSR and AFLP—basedgroups）分子类群。30对SSR引物共检测出135个等位变异,平均每个位点上有4．47个等位变异,SSR的遗传多样性指数（Simpson）分布范围为0．0928～0．7800,平均值为0、6442。10对AFLP引物共扩增出93个多态性标记,平均每对引物9．3个多态性标记。品种间的遗传相似系数（GS）变化范围为0．5877～0．9868,平均值变化范围为0．6732～0．7653,总体平均值为0.7237,遗传相似系数较高,说明材料间遗传变异较小。     

Genetic diversity in watermelon (Citrullus lanatus) landraces from Zimbabwe revealed by RAPD and SSR markers

Low polymorphism in cultivated watermelon has been reported in previous studies, based mainly on US Plant Introductions and watermelon cultivars, most of which were linked to breeding programmes associated with disease resistance. Since germplasm sampled in a putative centre of origin in southern Africa may harbour considerably higher variability, DNA marker-based diversity was estimated among 81 seedlings from eight accessions of watermelon collected in Zimbabwe; five accessions of cow-melons (Citrullus lanatus var. citroides) and three of sweet watermelons (C. lanatus var. lanatus). Two molecular marker methods were used, random amplified polymorphic DNA (RAPD) and simple sequence repeats (SSR) also known as microsatellite DNA. Ten RAPD primers produced 138 markers of which 122 were polymorphic. Nine SSR primer pairs detected a total of 43 alleles with an average of 4.8 alleles per locus. The polymorphic information content (PIC) ranged from 0.47 to 0.77 for the RAPD primers and from 0.39 to 0.97 for the SSR loci. Similarity matrices obtained with SSR and RAPD, respectively, were highly correlated but only RAPD was able to provide each sample with an individual-specific DNA profile. Dendrograms and multidimensional scaling (MDS) produced two major clusters; one with the five cow-melon accessions and the other with the three sweet watermelon accessions. One of the most variable cow-melon accessions took an intermediate position in the MDS analysis, indicating the occurrence of gene flow between the two subspecies. Analysis of molecular variation (AMOVA) attributed most of the variability to within-accessions, and contrary to previous reports, sweet watermelon accessions apparently contain diversity of the same magnitude as the cow-melons.