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微型DNA条形码用于猛禽物种鉴定.doc

发布:2017-08-16约1.21万字共10页下载文档
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微型DNA条形码用于猛禽物种鉴定 高 航 摘要:以猛禽为研究对象,首先采用模拟实验(in silico analysis),将BOLD数据库中230个样本的序列拆成3或6段相同大小(216 bp或108 bp)的片段,选用Full-barcode、Mini-barcode216-1和Mini-barcode 108-1三个片段数据集以K2P为参数构建NJ树,并进行遗传距离分析得出解析度的准确性依次为84.1%、78.3%、75.2%;然后进行实验验证(Empirical test),设计PCR引物扩增40个样本的DNA条形码指定序列5′ 端114 bp、中间103 bp和3′ 端121 bp,分别以单一片段和两两组合后的片段序列数据集为分析基础计算物种鉴定的准确性,得出114+103 bp合并序列为85.0%、114+121 bp为85.7%。DNA条形码(Minimalist barcode)鉴定猛禽物种是可行的,和DNA条形码一样均可作为猛禽物种鉴定的可靠依据。 关键词:猛禽;DNA条形码;微型条形码;物种鉴定 Minimalist-barcoding on the Species Identification of Raptors Abstract This study testified the feasibility of species identification of Raptors with minimalist barcodes. We first tested the in silico performance of ‘mini-barcodes’ (216 bp or 108 bp) in species-level identifications of 230 COI sequences from BOLD system, and calculated the resolution of three segments of full-barcode, mini-barcode 216-1 and mini-barcode 108-1 by neighbour-joining (NJ) analysis. With the segments decreasing, the resolution of species identification lowered (84.1%, 78.3% and 75.2%, respectively). However, the choice of length and position of mini-barcodes was important in their ability to discriminate among species. We generated 111 mini-barcodes (~100 bp) from 5′ end, middle and 3′ end of DNA barcode, respectively. The combinated segments of 114+103 bp and 114+121 bp showed higher accuracy at 85.0% and 85.7%, as compared to others in species-level identification by NJ analysis. The mini-barcodes which produced species-level resolution congruent with DNA barcode were also valuable for the identification of the raptors species whose DNA were degraded. Key words: Raptors; DNA barcode; Minimalist-barcode; Species identification 猛禽是鸟类六大生态类群之一掠(李湘涛,2004)。随着年龄、性别、季节和亚种的不同,猛禽在形态上会出现显著变异,(莫帮辉等,2008)。随着现代分子生物技术的发展,利用DNA序列片断信息对生物进行种类鉴定、物种分类地位及种间亲缘关系探讨正在成为一个主流手段。其中,Hebert提出的线粒体COI基因指定片段(648 bp)为基础的DNA条形码(DNA barcode)是目前高等脊椎动物,包括鸟类选用的对物种进行鉴定的标准化DNA片断(Hebert et al.,2004b; Yoo et al., 2006; Kerr et al.,2007)。DNA条形码是对形态学方法的强有力补充,它可使对物种的鉴定过程
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