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Theory-Based Demarcation of Hot Spring Microbial Mat Species from Large DNA Sequence Datasets

机译:从大DNA序列数据集中基于理论的温泉微生物种类划分

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摘要

The identification of closely related, ecologically distinct populations within microbial communities is paramount to understanding the structure and function of these communities. Microbial systematists have long used differences in DNA sequence relatedness to categorize the observed diversity in a community of microbes without including ecological theory to identify whether or not the identified groups are ecologically distinct. Ecotype Simulation, an evolutionary simulation algorithm based on the Stable Ecotype Model of microbial species and speciation, has been used successfully to study the diversification of thermophilic A/B'-lineage Synechococcus living in the effluent channels of alkaline-siliceous hot springs in Yellowstone National Park. However, Ecotype Simulation is an extremely slow program that is unable to handle the quantity of data produced by modern DNA sequencing technologies. I introduce a new version of this algorithm, called Ecotype Simulation 2, that permits the rapid analyses of microbial diversity from very large DNA sequence datasets. Results from this new version of the Ecotype Simulation algorithm compare favorably with results from the old version, but with analyses performed much more quickly on a much greater quantity of sequences sampled. The new algorithm was used to analyze three datasets. First, the biogeography of thermophilic A/B'-lineage Synechococcus living in hot springs of the American Northwest was analyzed. Results suggested a surprising amount of endemism among springs sampled, as well as implications for adaptations to physical and chemical environmental features not seen before. Second, Ecotype Simulation 2 was used to study the history of change in Synechococcus populations, seasonally (winter to summer) and over a twenty-five year period. Results suggested changes in population abundances and distribution seasonally, but stability in population genetic structure over many years. Finally, Ecotype Simulation 2 was used to study the populations of other predominant phototrophic microbes living along temperature and depth gradients in the same microbial mat community. Results suggested that the algorithm and the Stable Ecotype Model can successfully predict ecological diversity within all predominant mat taxa. Ecotype Simulation 2 provides the means for other microbiologists to base their understanding of the communities they study on evolutionary and ecological principals.
机译:识别微生物群落内密切相关,生态上不同的种群对于了解这些群落的结构和功能至关重要。微生物系统学家长期以来一直使用DNA序列相关性的差异来对微生物群落中观察到的多样性进行分类,而没有采用生态学理论来确定所鉴定的群体在生态学上是否独特。生态型模拟是一种基于微生物物种和物种稳定生态型模型的进化模拟算法,已成功用于研究生活在黄石公园碱性硅质温泉出水通道中的嗜热A / B'谱系突触球菌的多样性公园。但是,Ecotype Simulation是一个非常慢的程序,无法处理现代DNA测序技术产生的数据量。我介绍了该算法的新版本,称为Ecotype Simulation 2,它可以从非常大的DNA序列数据集中快速分析微生物多样性。这种新版本的Ecotype Simulation算法的结果与旧版本的结果相比具有优势,但是对大量采样序列进行的分析要快得多。该新算法用于分析三个数据集。首先,分析了生活在美国西北部温泉中的嗜热A / B'系Synechococcus的生物地理分布。结果表明,在抽样的春季中,地方病数量惊人,并且对适应以前从未见过的物理和化学环境特征具有影响。其次,使用生态型模拟2研究季节性,冬季(夏季至夏季)和25年内Synechococcus种群变化的历史。结果表明种群丰度和分布在季节性上有所变化,但多年来种群遗传结构却保持稳定。最后,Ecotype Simulation 2用于研究在同一微生物垫群落中沿温度和深度梯度生活的其他主要光养微生物的种群。结果表明,该算法和稳定生态型模型可以成功地预测所有主要垫类群中的生态多样性。 《生态型模拟2》为其他微生物学家提供了基于进化和生态原理对他们研究的群落的理解基础。

著录项

  • 作者

    Wood, Jason Michael.;

  • 作者单位

    Montana State University.;

  • 授予单位 Montana State University.;
  • 学科 Microbiology.;Bioinformatics.;Ecology.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 209 p.
  • 总页数 209
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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