11 resultados para 23S

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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中国科学院生物分类区系学科发展特别支持项目

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采用末端终止法对蓝藻类颤藻科Oscilatoriasp.rDNA16S-23S基因间隔区进行了序列测定,获得了Oscilatoriasp.rDNA基因间隔区427个核苷酸,其中包含1个异亮氨酸tRNA基因(tRNAIle)。并通过计算机联网从国际分子生物学数据弹库中获取颤藻科其它种的rDNA基因间隔区序列,通过比较分析,从分子水平对颤藻科Oscilatoriaceae属间的某些分类学问题进行了讨论,并根据序列中核苷酸差异值探讨了颤藻科属间界定的分子标准。提出了rDNA基因间隔区是良好的分子标记,可用于“赤

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生物多样性科学(BiodiversityScience)的国际规划提出生物多样性对生态系统功能的影响是整个研究计划五大核心的核心.生物多样性包括遗传、物种和生态系统三个水平,其中遗传多样性是其它两个水平多样性的基础和最终来源.该文在实验室多年研究毛乌素沙地柠条遗传多样性的基础上,分别从表型(生理生化)、蛋白质、同工酶以及遗传型(rDNA)水平探讨中间锦鸡儿根瘤菌的遗传多样性,并模拟沙地生境,建立人工共生体系,以期发现最有效的共生伙伴关系,这不仅有得提高毛乌素地区农牧业产量,更重要的是在当今沙尘暴肆虐的情况下,发挥柠条防风固沙的能力具有现实意义. 1.毛乌素沙地中间锦鸡儿根瘤菌遗传多样性(1)全细胞可溶性蛋白质谱将供试中间锦鸡儿根瘤菌菌株分为两大类群,其中硬梁覆沙地菌株GH72不同于来自沙丘顶部和底部的菌株,而且中间锦鸡儿根瘤菌独立于参比菌株。酯酶同工酶谱分析表明,中间锦鸡儿根瘤菌与参比菌株仅存在一个等位酶位点差异,其余等位点与参菌株共享,因此,酯酶同工酶反映出中间锦鸡儿根瘤菌的异质性。(2)16SrDNA部分序列与16S-23S rDNA IGS结果表明,所有供试菌株扩增产物均较前人报道的分子量偏高。经16S rDNA PCR-RFLP分析,中间锦鸡儿根瘤菌共形成12种基因型,表现出丰富的遗传多样性,其中属于基因型2的菌株占42.4%。代表菌株GH33 16S rDNA全序列结果显示,与已知的快生型根瘤菌同源性在95%以上。(3)中间锦鸡儿根瘤菌生理生化反应特性B.T.B实验证明所有中间锦鸡儿根瘤菌均产酸,符合快生型根瘤菌的特征.唯一碳源测试显示,95%中间锦鸡儿根瘤菌不利用淀粉,33%菌株不利用乳糖,对其他测试碳源不具有选择性。检洲在不同盐离子浓度、不同酸性梯度以及不同温度条件下菌株生长状况,发现毛乌素沙地中间锦鸡儿根瘤菌具极强的耐盐性.53.8%的菌株可以在9%NaCl的YMA培养基生长.75%的菌株在pH4.O和pHl0,0 环境中仍能生长,66.7%菌株在60℃处理1 0min后仍具有生活力。体现出对于干旱沙地的适应。 2.不同实验共生系统中植物和根瘤菌对生态系统功能的影响14株根瘤菌分与三个柠条种(小叶锦鸡儿,中间锦鸡儿和柠条锦鸡儿)回接,用土壤上覆沙模拟毛乌索沙地景观生态条件,以多石砾贫瘠土壤为对照,比较不同基因型柠条与根瘤菌人工共生体的长和结瘤与生境的关系,初步证明根瘤菌很可能是该生态系统的关键种。寄主植物与共生根瘤菌的遗传多样性对生态系统功能的影响与生态环境有关。实验还表明,选择适当的共生组合对于防治沙漠化有很大潜力。3.银染变性聚丙烯酰胺凝胶电泳检测RAPD遗传模式以85株小钻杨F2代为材料,用本实验室改良的银染变性聚丙烯酰胺凝胶电泳法检测RAPD遗传模式。结果表明,仅用9个引物共扩增到399个位点,其中98个位点表现为多态性,卡方测验显示,79个多态位点符合经典的孟德尔遗传(3:1),占多态位点80.6%。这种改良的检测RAPD标记的方法必将推动RAPD标汜构建连锁图谱的进程。

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The success of some phylogenetic markers in cyanobacteria owes to the design of cyanobacteria-specific primers, but a few studies have directly investigated the evolution "behavior" of the loci. In this study, we performed a case study in Nostoc to evaluate rpoC1, hetR, rbcLX, and 16S rRNA-tRNA(Ile)-tRNA(Ala)-23S rRNA internal transcribed spacer (ITS) as phylogenetic markers. The results indicated that the gene trees of these loci are not congruent with the phylogeny based on 16S rRNA gene. The mechanisms contributing to the incongruence include randomized variation and recombination. As the results suggested, one should be careful to choose the molecular markers for phylogenetic reconstruction at the intrageneric level in cyanobacteria.

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本文应用nifD-nifK IGS及16S-23S rDNAIGSPCR-RFLP方法,系统研究了分布于云南横断山的旱冬瓜以及吉林长白山的西伯利亚赤杨、色赤杨和东北赤杨根瘤内Frankia菌的遗传多样性。该研究可加深对Frankia菌起源与进化的认识,并为保护和利用这一固氮共生资源提供科学依据。从113株赤杨的根瘤样品中共检测到48种基因型的Frankia菌株。首次确切报道了自然条件下不同基因型Frankia菌可与同一宿主植株同时共生,并且这种混乱性在横断山区普遍存在。通过对Frankia菌群体遗传结构的分析,查明云南省横断山旱冬瓜Frankia菌群体内遗传变异水平由高到低的顺序是苍山群体、高黎贡山群体、鸡足山群体、来凤山群体和无量山群体。酶切带型9为云南横断山旱冬瓜Frankia菌群体中最古老的类型;大部分(75.63%)遗传变异发生在Frankia菌的各群体内,同一气候区的Frankia菌群体有较近的亲缘关系。旱冬瓜Fran辰a菌遗传多样性特点与横断山气候特征及冰川运动历史密切相关。宿主赤杨的进化地位不同,其共生Frankia菌的群体遗传多样性水平也不同。古老的旱冬瓜共生Fran舫“菌群体内遗传分化最大,分化最晚的东北赤杨共生Frankia菌群体内遗传变异最小;属同一生活型的西伯利亚赤杨和色赤杨共生Fronkia菌间存在着较近亲缘关系;早冬瓜Fran舫。菌群体可能为其它赤杨共生Fran舫“菌提供祖先,因此认为赤杨与其共生Frankia菌间存在着协同进化。

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Molecular diagnosis is playing an increasingly important role in the rapid detection and identification of pathogenic organisms in clinical samples. The genetic variation of ribosomal genes in bacteria offers an alternative to culturing for the detection and identification of these organisms. Here 16S rRNA and 16S-23S rRNA spacer region genes were chosen as the amplified targets for single-strand conformation polymorphism (SSCP) and restriction fragment length polymorphism (RFLP) capillary electrophoresis analysis and bacterial identification. The multiple fluorescence based SSCP method for the 16S rRNA gene and the RFLP method for the 16S-23S rRNA spacer region gene were developed and applied to the identification of pathogenic bacteria in clinical samples, in which home-made short-chained linear polyacrylamide (LPA) was used as a sieving matrix; a higher sieving capability and shorter analysis time were achieved than with a commercial sieving matrix because of the simplified template preparation procedure. A set of 270 pathogenic bacteria representing 34 species in 14 genera were analyzed, and a total of 34 unique SSCP patterns representing 34 different pathogenic bacterial species were determined. Based on the use of machine code to represent peak patterns developed in this paper, the identification of bacterial species becomes much easier.