基于18S rDNA 的Metabarcoading技术分析环境生物多样性
文献类型：学位论文
| 作者 | 杨晨雪 |
| 学位类别 | 博士 |
| 答辩日期 | 2015-07 |
| 授予单位 | 中国科学院研究生院 |
| 授予地点 | 北京 |
| 导师 | Douglas w Yu |
| 关键词 | DNA条形码 高通量测序 土壤动物 metabarcoding 18S rDNA |
| 其他题名 | Using 18S rDNA-based metabarcoding technology to investigate environment biodiversity |
| 中文摘要 | 通常生态学问题，制作样方，野外采样很重要，直接决定着我们所研究的问题的现实逻辑性和可靠性。同时，野外采样也是耗时耗力的一个生态学研究瓶颈。怎样能更快更好地在野外采集样本，采集什么样的样本，针对不同的研究，我们需要更多选择。最常见的马氏网，灯诱等陷阱，通常要在野外放置一段时间，这就需要研究人员至少两次的返回采样地，同时等待大量时间，不仅耗时耗力，更重要的是，在这段时间里，陷阱很有可能被人为破坏，丢失，或者遭到动物破坏，比如大象踩踏，猴子也会因好奇破坏我们的陷阱器材。因此，一个快速的，便捷的，安全的并且确实可以得到可靠地多样性数据的样本采集方法急需被搬上生态学多样性研究的平台。 生态和环境管理方面的很多基本问题都需要涉及土壤及腐殖质小型动物多样性的特征描述。当前利用高通量测序技术获得条形码基因扩增子序列的方法（‘metabarcoding’）在生物多样性调查方面提供了高效有力的方法。然而，这一技术的广泛应用面临一个很大的阻碍，就是需要从大量原始序列数据中通过生物信息学方法处理获得很多候选基因。 在本文第一部分我们比较了三个针对从固体基质中获得的18S rDNA metabarcode数据的信息学处理方法：（1）USEARCH/CROP,（2）Denoiser/UCLUST，以及（3）OCTUPUS。令人满意的是，这三个信息学处理方法得到了相似并且与环境样本中已知特征分类单元高度相关的群落组成。然而，OCTUPUS由于过高的序列噪音出现了过度估计系统发育多样性的问题。因此我们推荐USEARCH/CROP或者Denoiser/UCLUST方法。这两者均可以在QIIME环境下运行。尽管如此，仅仅依靠条形码技术是不够的，想要用生物多样性对环境进行即时性评估，还需对样本的分析技术进行较大改进。因此，我们将多种诱捕法、DNA测序和生物信息学技术相结合对大量的样本和数据进行分析，以此测量陆地生物多样性。 本文第二部分以土壤和腐殖质为对象，运用metabarcoding技术，与传统的马氏网等采样方案相比，对中国及越南多个地区同一样点的多样性数据分析，证实了土壤，腐殖质这种一次性快速采样得到的数据可以有效地检测区域多样性变化。 |
| 英文摘要 | Making quadrat and field sampling is very important in ecological, they directly determine the logic and reliability of what we studied. At the same time, field sampling is a time consuming rate-limiting step for the ecological research. How can we get field samples batter and faster? What kind of samples we collection? According to different research, we need more options. The most commonly traps like Malaise trap, light trap, etc. this are need to place for a period of time in the field, which requires researchers to return at least twice of sampling. Such things is not only time consuming and more importantly, in that time, the traps are likely to be destroyed artificially, loss, or damaged by animals, such as elephants trample, the monkey will also ruin our equipment as curiosity. Therefore, a fast, convenient, safe method and which really can get reliable biodiversity data are in urgent need for ecology diversity research. Many basic problems of ecological and environmental management are involving environment biodiversity survey. Numerous methods for environment biodiversity investigation are used, including bird-watching, voice recording of birds, vegetation investigation, manmmal dung collection and capture and identification of indicator species, ect. Currently, the most widely used method for investigation of environment biodiversity is biological indicator as the irreplaceable advantages of it. The species we captured is usually dominant species and easy to catch, also it will not result in a population fluctuation influenced by our scientific research to capture the species. The important thing is that this species can reflect the abundance of other species. Most researchers will choose several methods auxiliary to each other to complete a regional diversity of survey, because it can be different aspects from different angles comprehensive understanding of an area of the environment. Refer to the indicator species, traditional species identification needs a lot of professional knowledge and time consuming. Especially for the arthropod and annelid which are small and not easy to distinguish as the variety. Facing the uneasiness eye observed animals like bottom meiofauna and soil meiofauna, the experienced zoologist will nail-biting. In recent years, the rapid development of DNA barcode identification technology was accepted by taxonomists from all walks and is widely used in identification of plants and animals. However, there are still many obstacles to be solved, such as species appraisal need multiple barcode parsing, Sanger sequencing platform is disable to handle mixed samples. With the development of the second generation sequencing technology, high throughput sequencing platform promoted the realization of the Metabarcoding technology. In this dissertation, we mainly discuss on the DNA extraction from animal tissues mixed samples and environmental samples for sequencing and environment species diversity identification, namely Metabarcoding. However, one obstacle to broad uptake of this technique is the need to choose amongst many candidates for bioinformatic processing of the raw sequencing data. In the first part in this artcal, we compare three candidate pipelines for the processing of 18S small subunit rDNA metabarcode data from solid substrates: (1) USEARCH/CROP, (2) Denoiser/UCLUST, and (3) OCTUPUS. The three pipelines produced reassuringly similar and highly correlated assessments of community composition that are dominated by taxa known to characterize the sampled environments. However, OCTUPUS appears to inflate phylogenetic diversity, because of higher sequencing noise. We therefore recommend either the USEARCH/CROP or Denoiser/UCLUST pipelines, both of which can be run within the QIIME (Quantitative Insights Into Microbial Ecology) environment. We choose USEARCH/CROP method at the subsequent study in this dissertation, and at present, we also recommend the method widely used in ecological survey in study of Metabarcoding technology. In the second part, we use soil and leaf litter as object, using metabarcoding technology, compared with traditional Malaise trap sampling scheme, to investigate multiple areas with the same plots diversity in China and Vietnam. And our research attested that soil and leaf litter, which are one-off fast sampling data, could effectively detect the regional changes of environment biodiversity. |
| 语种 | 中文 |
| 源URL | [http://159.226.149.26:8080/handle/152453/10141]  |
| 专题 | 昆明动物研究所_动物生态学研究中心 |
| 推荐引用方式 GB/T 7714 | 杨晨雪. 基于18S rDNA 的Metabarcoading技术分析环境生物多样性[D]. 北京. 中国科学院研究生院. 2015. |
入库方式： OAI收割
来源：昆明动物研究所
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