生物多样性 ›› 2019, Vol. 27 ›› Issue (5): 526-533.doi: 10.17520/biods.2018209

• 综述 • 上一篇    下一篇

DNA条形码参考数据集构建和序列分析相关的新兴技术

刘山林()   

  1. 中国农业大学植物保护学院, 食品营养与人类健康高精尖创新中心, 北京 100193
  • 收稿日期:2018-07-30 接受日期:2018-12-25 出版日期:2019-05-20
  • 通讯作者: 刘山林 E-mail:shanlin1115@gmail.com
  • 基金项目:
    深圳市基础研究(自由探索 JCYJ20170817150755701)

DNA barcoding and emerging reference construction and data analysis technologies

Liu Shanlin()   

  1. Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Plant Protection, China Agricultural University, Beijing 100193
  • Received:2018-07-30 Accepted:2018-12-25 Online:2019-05-20
  • Contact: Liu Shanlin E-mail:shanlin1115@gmail.com

近年来DNA条形码技术迅速发展, 产生的条形码的数量及其应用范围都呈指数性增长, 现已广泛用于物种鉴定、食性分析、生物多样性评估等方面。本文重点总结并讨论了构建条形码参考数据库和序列聚类相关的信息分析的技术和方法, 包括: 基于高通量测序(high throughput sequencing, HTS)平台以高效并较低的成本获取条形码序列的方法; 同时还介绍了从原始测序序列到分类操作单元(operational taxonomic units, OTUs)过程中的一些计算逻辑以及被广泛采用的软件和技术。这是一个较新并快速发展的领域, 我们希望本文能为读者提供一个梗概, 了解DNA条形码技术在生物多样性研究应用中的方法和手段。

关键词: DNA条形码, 可操作物种单元, 聚类, 宏基因条形码, 高通量测序

DNA barcoding has been growing exponentially in terms of the number of barcode generated as well as its applications, e.g. as conservation tools in: species identification for damaged specimens, diet analysis from gut content and feces, biodiversity assessment from environmental DNA (eDNA), bulk arthropod samples or invertebrate-derived DNA (iDNA). These applications often require coupling with high throughput sequencing (HTS) technologies, and when done so are referred to as metabarcoding. Here, we discuss the methods used to generate reference barcodes using cost-efficient HTS platforms, and introduce several rules-of-thumb and some widely-used tools to conduct data quality control, denoising, and Operational Taxonomic Units (OTUs) clustering. We hope this review will help readers better understand how these emerging technologies can be implemented alongside existing technologies to accelerate biodiversity assessments in an accurate and efficient way.

Key words: DNA barcoding, OTUs, clustering, metabarcoding, high throughput sequencing

表1

广泛用于DNA条形码技术的标记基因"

标记基因 Marker gene 目标物种 Targeted group 数据库 Database
16S 细菌和古细菌 Bacteria and archea (Sogin et al, 2006) 核糖体数据库项目 Ribosomal Database Project (RDP, Cole et al, 2008); Greengenes (DeSantis et al, 2006); SILVA (Pruesse et al, 2007)
ITS 真菌(Schoch et al, 2012)、植物(Group et al, 2011)、原生生物(Pawlowski et al, 2012)
Fungi (Schoch et al, 2012); plant (Group et al, 2011); protist (Pawlowski et al, 2012)
UNITE (K?ljalg et al, 2005); GenBank (Benson et al, 2012)
18S 原生生物 Protist (Pawlowski et al, 2012) SILVA (Pruesse et al, 2007)
matK + rbcL 植物 Plant (Hollingsworth et al, 2009) 生命条形码数据库 Barcode of Life Data Systems
(BOLD, Ratnasingham & Hebert, 2007); GenBank (Benson et al, 2012)
COI 动物群(Hebert et al, 2003)、原生生物(Pawlowski et al, 2012)
Fauna (Hebert et al, 2003) and protist (Pawlowski et al, 2012)
核糖体数据库项目 Ribosomal Database Project (RDP, Cole et al, 2008)

表2

利用高通量测序平台批量获取DNA条形码的方法"

目标序列长度
Targeted region length (bp)
优势
Advantages
劣势
Disadvantages
参考文献
Reference
~300 - 无法处理较长的目标序列; Roche 454平台
Can not work on long fragments;
Roche 454 platform
Shokralla et al, 2014
~180 简单, 易操作, 成本低
Straightforward, easy to operate,
cost-efficient
目标序列偏短, 只能用于物种初筛
Short targeted region; can only be used
for species pre-clustering
Meier et al, 2016
~650 标准DNA条形码全长
Standard full-length COI
普适性差; 需要多轮PCR过程
Poor universality; multiple rounds of PCR
Shokralla et al, 2015;
Cruaud et al, 2017
~650 易操作, 标准DNA条形码全长
Easy to operate, standard full-length COI
相对较高的计算资源
Relatively high requirement for
computational resources
Liu et al, 2017
~650 易操作, 标准DNA条形码全长
Easy to operate, standard full-length COI
SMRT平台成本高
High cost of SMRT platform
Hebert et al, 2018
~650 易操作, 标准DNA条形码全长
Easy to operate, standard full-length COI
测序平台暂时不够普及
Not a mass production
Yang et al, 2018

图1

条形码分析的数据处理流程图"

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