30个粳稻品种SSR标记遗传多样性分析

选用分布于水稻12条染色体上的64对SSR引物,对江苏省育成以及日本引进的粳稻品种共30份材料进行遗传多样性分析。结果表明,有50对SSR引物在30个品种间表现为多态性。共检测到140个等位基因,每对引物的等位基因数变幅为2～5个,平均为2．8个。有效等位基因为94．336个,平均为1．887。每个SSR位点的多态性信息量（PIC）变化范围为0．064～0．752,平均为0．410。30个品种间的遗传相似系数变幅为0．386～0．956之间,平均值为0．719,且81．4％的供试品种其遗传相似系数在0．600～0．800之间,亲缘关系较近;以遗传相似系数为原始数据,按UPGMA方法将30个品种划分为3大类群,结合系谱分析结果表明,江苏省育成的水稻品种遗传多样性不够丰富,多数品种间的亲缘关系较近,欲进一步提高江苏省水稻产量还需拓宽亲本选择范围,扩大遗传背景。     

四川核桃良种SSR指纹图谱构建及遗传多样性分析

为构建四川核桃良种指纹图谱,分析遗传多样性,增强品种间的区分能力,该研究利用SSR标记技术,对四川29个核桃良种进行遗传多样性和聚类分析。结果表明:(1)11对SSR引物共检测到121个基因型和80个等位基因,平均每个位点7.273个等位基因和11个基因型。(2)11个位点的平均有效等位基因数为3.644,平均观察杂合度为0.645,平均期望杂合度为0.718,平均香农信息指数为1.518,平均多态信息含量为0.680。(3)采用引物组合法利用引物wga001、wga032和zmz02构建了29个核桃品种的指纹图谱。(4)聚类分析结果表明,29个核桃品种按照品种类型优先聚类,四川本地核桃品种聚类关系与地理来源没有明显的相关性。研究认为,选用的11个SSR标记能够较好地运用于四川核桃品种的遗传多样性研究(PIC0.5);29个四川核桃品种间亲缘关系较近,遗传基础相对较窄。     

水稻新品种测试的标准品种DNA指纹图谱多样性分析

以植物新品种特异性、一致性和稳定性(DUS)测试指南中选定的49个水稻标准品种为材料,采用农业行业标准(NY/1433-2077)中推荐的24对水稻SSR引物进行DNA指纹图谱构建和遗传多样性分析。结果表明,24对SSR引物在19个籼稻和30个粳稻品种中分别检测到141和156个等位变异,平均每对引物可以检测到5.88(籼稻)和6.50(粳稻)个等位变异;籼、粳稻类群中24对SSR引物的平均Shannon's多样性指数分别为1.5141(1.0460~1.9959)和1.4389(0.4677~2.4503);经聚类分析后,籼、粳稻群体内品种间的相似系数分别介于0.45~0.81和0.36~0.76,取相似系数0.72为阈值,可将19个籼稻和30个粳稻品种分别分为16类和28类。由此可见,本研究的49个品种的遗传多样性丰富。结合形态性状和基因型聚类分析结果,可将现有的49个水稻DUS测试标准品种减少到46个。     

SSR标记揭示的云南地方稻品种遗传多样性及其保育意义

为了探索水稻(Oryza　sativa　L.)地方品种的遗传多样性及其有效保育方法,对采自云南省17个村寨的82个水稻地方品种和3个国际常用的典型籼稻和粳稻品种进行了微卫星(SSR)分子标记的分析。利用19对SSR引物在85个水稻品种中共扩增出了83个基因型,其分子量变异在100～500　bp之间。基于各品种SSR基因型遗传相似系数聚类分析而获得的UPGMA树状图表明各水稻品种之间存在较大的遗传多样性,其相似系数变异在0.15～0.90之间。但这些地方品种的遗传多样性并非呈均等的地理分布。这85个水稻品种在相似系数为0.52之处分为二组,其中一组包括几乎所有的籼稻品种,而另一组包括全部的粳稻品种,表明SSR标记能很好揭示水稻籼-粳分化。同时,有些来自不同采集地的同名品种表现出一定的遗传差异,说明同名异物的现象存在。云南水稻地方品种具有丰富的遗传多样性,对其有效保育十分重要和迫切,　但只有根据遗传多样性的水平和分布特点,采用正确的保育对策和取样方法才能确保对云南水稻地方品种的有效保育。结果进一步表明,选用适当的微卫星引物,可以为准确鉴定籼稻和粳稻品种及研究其进化规律提供有效的分子标记方法,并有利于有目标的水稻遗传资源保育和育种创新。     

SSR标记揭示的云南地方稻品种遗传多样性及其保育意义

为了探索水稻(Oryza sativa L.)地方品种的遗传多样性及其有效保育方法,对采自云南省17个村寨的82个水稻地方品种和3个国际常用的典型籼稻和粳稻品种进行了微卫星(SSR)分子标记的分析.利用19对SSR引物在85个水稻品种中共扩增出了83个基因型,其分子量变异在100～500 bp之间.基于各品种SSR基因型遗传相似系数聚类分析而获得的UPGMA树状图表明各水稻品种之间存在较大的遗传多样性,其相似系数变异在0.15～0.90之间.但这些地方品种的遗传多样性并非呈均等的地理分布.这85个水稻品种在相似系数为0.52之处分为二组,其中一组包括几乎所有的籼稻品种,而另一组包括全部的粳稻品种,表明SSR标记能很好揭示水稻籼-粳分化.同时,有些来自不同采集地的同名品种表现出一定的遗传差异,说明同名异物的现象存在.云南水稻地方品种具有丰富的遗传多样性,对其有效保育十分重要和迫切,但只有根据遗传多样性的水平和分布特点,采用正确的保育对策和取样方法才能确保对云南水稻地方品种的有效保育.结果进一步表明,选用适当的微卫星引物,可以为准确鉴定籼稻和粳稻品种及研究其进化规律提供有效的分子标记方法,并有利于有目标的水稻遗传资源保育和育种创新.     

宁夏水稻选育品种遗传多样性和亲缘关系分析

选择31份宁夏近年来育成或审定的水稻品种(系),利用分布于12条染色体的36对SSR引物进行遗传多样性和遗传距离分析.共检测到159个等位基因,品种间不同位点等位基因数目不等,平均4.4个.Nei基因多样性指数变幅为0.031 7～0.844 4,平均为0.508 8.按育成或审定年份,把31份水稻分为3组,SSR分析...     

元阳3个长期连续栽培水稻地方品种内部遗传异质性分析

水稻地方品种是稻种资源的重要组成部分,遗传多样性十分丰富,具有推广改良品种所缺少或没有的优质种质,是水稻育种和稻种起源、进化研究不可缺少的过渡材料。目前,对水稻地方品种间遗传多样性研究较多,而对其内部异质性研究甚微。本研究用24对微卫星(SSR)引物对云南元阳梯田3个栽种历史悠久的水稻地方品种的内部遗传异质性进行了分析。共检测出117个等位基因,香农指数为红脚老粳居群(0.5911)>白脚老粳A居群(0.4875)>月亮谷居群(0.3070)。结果显示:3个地方品种的内部遗传异质性丰富,且遗传异质性主要得益于个体间,而非居群间。     

黑龙江省近年审定水稻品种基于SSR标记的遗传多样性分析

为评估黑龙江省水稻品种的遗传基础,利用24个用于水稻DNA指纹图谱构建的SSR标记以及其他均匀分布于水稻12条染色体的38个SSR标记,对黑龙江省近年审定的73个水稻常规稻品种进行遗传多样性分析。结果表明,在62个SSR标记位点中,共检测到142个等位基因,平均每个标记2.3个,多态性比率平均为71.0%,多态性频率变幅为0~0.775,平均值为0.246。供试品种间两两遗传相似系数的平均值为0.759,变幅为0.622~0.966,且96.4%的品种间遗传相似系数在0.66~0.86之间,表明供试的73个品种亲缘关系较近。通过SSR标记基因型聚类分析将这些品种划分为6个类群,与系谱分析趋势一致,类群间的差异主要表现在生育期和米质方面。综上所述,黑龙江省近年审定的水稻品种遗传基础狭窄,在育种中需要导入新的种质资源,加强种质资源创新,以期丰富水稻品种的遗传多样性,进一步提高水稻产量和抗性。     

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。     

云南栽培稻种SSR 遗传多样性比较

采用64个SSR标记对96份云南水稻(Oryz a sativa)地方品种和选育品种的遗传多样性进行比较分析。结果发现64个标记都具有多态性, 共检测到741个等位基因, 每个多态性位点检测到的等位基因数为2-29个, 平均11.57个; Nei基因多样性指数(He)范围在0.345(RM321)-0.932(RM1)之间, 平均为0.56。水稻品种的遗传多样性并非按地理位置均匀分布, 而是在相 似系数为0.17的水平上明显分为2个不同类群, 即籼稻类群和粳稻类群, 且籼粳亚种间的SSR多样性差异不明显, 籼稻平均等位基因数(Ap)和Nei基因多样性指数(Ap=10.6, He=0.46)与粳稻品种(Ap=10.7, He=0.48)十分接近, 可能与这些品种间存在一定频率的基因交流有关。糯稻和非糯稻在籼稻群和粳稻群中都有表现, 没有特别的分布规律。云南栽培稻选育品种与地方稻亲缘关系较近, 其遗传基础可能来源于云南水稻地方品种。本研究结果表明, SSR标记能较好地区分云南栽培稻品种, 且云南水稻地方品种遗传多样性丰富, 存在大量的优质性状可供育种实践选择。     

Genetic diversity in basmati rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) germplasm as revealed by microsatellite (SSR) markers

Genetic diversity among rice genotypes, including 15 indica basmati advance lines and 5 basmati improved varieties were investigated by 28 SSR markers including one indel marker. The SSRs covered all the 12 chromosomes that distributed across the rice genomes. The mean number of alleles per locus was 3.60, showing average number of polymorphism information content was 0.48. A total of 101 alleles were also identified from the microsatellite marker loci. A number of SSR markers were also identified that could be utilized to differentiate between rice genotypes. Pair wise Nei’s genetic distance between rice genotypes ranged from 0.07 to 0.95. The dendrogram based on cluster analysis by using SSR polymorphism that grouped the 20 genotypes of rice in to five clusters based on their genetic similarity. The result could be useful for the identification and selection of the diverse genotypes for the future cross breeding program and development of new rice varieties.     

Genetic diversity in basmati rice (Oryza sativa L.) germplasm as revealed by microsatellite (SSR) markers

Genetic diversity among rice genotypes, including 15 indica basmati advance lines and 5 basmati improved varieties were investigated by 28 SSR markets including one indel marker. The SSRs covered all the 12 chromosomes that distributed across the rice genomes. The mean number of alleles per locus was 3.60, showing average number of polymorphism information content was 0.48. A total of 101 alleles were also identified from the microsatellite marker loci. A number of SSR markers were also identified that could be utilized to differentiate between rice genotypes. Pair wise Nei,s genetic distance between rice genotypes ranged from 0.07 to 0.95. The dendrogram based on cluster analysis by using SSR polymorphism that grouped the 20 genotypes of rice in to five clusters based on their genetic similarity. The result could be useful for the identification and selection of the diverse genotypes for the future cross breeding program and development of new rice varieties.     

Informative SSR markers for commercial variety discrimination in watermelon (Citrullus lanatus)

SSR markers were used for variety discrimination and genetic assessment in watermelon varieties. Genetic characterization of 49 watermelon varieties was investigated using 30 SSR markers developed from melon and watermelon. A total of 121 polymorphic amplified fragments were obtained by using 30 SSR markers. The average polymorphism information content (PIC) was 0.502 ranging from 0.223 to 0.800. One hundred twenty one SSR loci were used to calculate Jaccard’s distance coefficients for unweighted pair group method using the arithmetic averages (UPGMA) cluster analysis. A clustering group of varieties, based on the results of SSR analysis, were categorized into 5 major groups corresponding to morphological traits. Inheritance mode of 2 SSR markers was investigated to F₁ plants and F₂ populations of 2 crosses. Parental alleles were transmitted from F1 plants and F2 populations. Therefore, these marker sets may prove to be effectively applicable to genetic assessment of germplasm, genome mapping, and fingerprinting of watermelon varieties.     

Genetic diversity among silkworm (Bombyx mori L., Lep., Bombycidae) germplasms revealed by microsatellites.

To determine genetic relationships among strains of silkworm, Bombyx mori L., 31 strains with different origins, number of generations per year, number of molts per generation, and morphological characters were studied using simple sequence repeat (SSR) markers. Twenty-six primer pairs flanking microsatellite sequences in the silkworm genome were assayed. All were polymorphic and unambiguously separated silkworm strains from each other. A total of 188 alleles were detected with a mean value of 7.2 alleles/locus (range 2-17). The average heterozygosity value for each SSR locus ranged from 0 to 0.60, and the highest one was 0.96 (Fl0516 in 4013). The mean polymorphism index content (PIC) was 0.66 (range 0.12-0.89). Unweighted pair group method with arithmetic means (UPGMA) cluster analysis of Nei's genetic distance grouped silkworm strains based on their origin. Seven major ecotypic silkworm groups were analyzed. Principal components analysis (PCA) for SSR data support their UPGMA clustering. The results indicated that SSR markers are an efficient tool for fingerprinting cultivars and conducting genetic-diversity studies in the silkworm.     

Genetic diversity and origin of weedy rice (Oryza sativa f. spontanea) populations found in North-eastern China revealed by simple sequence repeat (SSR) markers

BACKGROUND AND AIMS: Weedy rice (Oryza sativa f. spontanea) is one of the most notorious weeds occurring in rice-planting areas worldwide. The objectives of this study are to determine the genetic diversity and differentiation of weedy rice populations from Liaoning Province in North-eastern China and to explore the possible origin of these weedy populations by comparing their genetic relationships with rice varieties (O. sativa) and wild rice (O. rufipogon) from different sources. METHODS: Simple sequence repeat (SSR) markers were used to estimate the genetic diversity of 30 weedy rice populations from Liaoning, each containing about 30 individuals, selected rice varieties and wild O. rufipogon. Genetic differentiation and the relationships of weedy rice populations were analysed using cluster analysis (UPGMA) and principle component analysis (PCA). KEY RESULTS: The overall genetic diversity of weedy rice populations from Liaoning was relatively high (H(e) = 0.313, I = 0.572), with about 35 % of the genetic variation found among regions. The Liaoning weedy rice populations were closely related to rice varieties from Liaoning and japonica varieties from other regions but distantly related to indica rice varieties and wild O. rufipogon. CONCLUSIONS: Weedy rice populations from Liaoning are considerably variable genetically and most probably originated from Liaoning rice varieties by mutation and intervarietal hybrids. Recent changes in farming practices and cultivation methods along with less weed management may have promoted the re-emergence and divergence of weedy rice in North-eastern China.     

宁夏60份粳稻种质资源遗传多样性分析

试验用SSR分子标记对60份宁夏粳稻种质资源进行遗传多样性分析。103对SSR引物表现多态性的有58对,共扩增出212条多态性条带,等位变异范围为2～9,平均每对引物3.7个;多态性信息含量(PIC)变幅为0.032～0.788,平均为0.403;高多态性位点主要发生在3号、6号和11号染色体上,而无多态性或低多态性位点主要发生在1号和10号染色体上;成对供试材料的遗传相似系数GS值变幅为0.642～0.958,平均为0.790,单个供试材料的平均GS值变幅为0.710～0.816,平均为0.781,亲缘关系较近;UPGMA聚类表明,在遗传相似系数约0.785处,供试材料可被分为11类,大部分材料被聚在一类中。     

东北地区杂草稻与栽培稻的遗传多样性及籼粳分化

利用88对籼粳特异性分子标记对收集于我国东北三省的35份杂草稻和36份栽培稻遗传基础及籼粳分化进行研究,结果表明上述标记能够高效地鉴别稻属资源的籼粳属性,共检测到156个等位基因,平均有效等位基因(Na)为1.773。遗传多样性分析表明,东北地区杂草稻多样性水平略高于当地栽培稻,其中杂草稻的等位基因数(Na)、杂合度(He)、基因多样性(Hsk)以及多态性信息含量(PIC)分别为1.659、0.006、0.076和0.085,而东北栽培稻分别为1.557、0.004、0.060和0.067。遗传结构和聚类分析结果表明,东北地区杂草稻与栽培稻具有较近的亲缘关系,均存在一定程度的籼粳分化。进一步对籼粳血缘进行相对量化分析发现,杂草稻的籼型基因型频率(F_i=0.050)略高于当地栽培稻(F_i=0.043)。东北三省籼型基因型频率变化趋势为:辽宁杂草稻(0.062)辽宁栽培稻(0.058)吉林栽培稻(0.048)黑龙江杂草稻(0.041)吉林杂草稻(0.024)黑龙江栽培稻(0.020)。     

SSR analysis of 38 genotypes of soybean (Glycine Max (L.) Merr.) genetic diversity in India

Sixteen polymorphic Simple sequence repeat (SSR) markers were used to determine the genetic diversity and varietal identification among 38 soybean (Glycine max (L.) Merr.) genotypes which are at present under seed multiplication chain in India. A total of 51 alleles with an average of 2.22 alleles per locus were detected. The polymorphic information content (PIC) among genotypes varied from 0.049 (Sat_243 and Satt337) to 0.526 (Satt431) with an average of 0.199. The pair wise genetic similarity between soybean varieties varied from 0.56 to 0.97 with an average of 0.761. These 16 SSR markers successfully distinguished 12 of the 38 soybean genotypes. These results suggest that used SSR markers are efficient for measuring genetic diversity and relatedness as well as identifying varieties of soybeans. Diverse genetic materials may be used for genetic improvements of soybean genotypes.