Zou Shanmei, Fei Cong, Song Jiameng, Bao Yachao, He Meilin, Wang Changhai
Jiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Science, Nanjing Agricultural University, Nanjing 210095, PR China.
PLoS One. 2016 Apr 19;11(4):e0153833. doi: 10.1371/journal.pone.0153833. eCollection 2016.
Several different barcoding methods of distinguishing species have been advanced, but which method is the best is still controversial. Chlorella is becoming particularly promising in the development of second-generation biofuels. However, the taxonomy of Chlorella-like organisms is easily confused. Here we report a comprehensive barcoding analysis of Chlorella-like species from Chlorella, Chloroidium, Dictyosphaerium and Actinastrum based on rbcL, ITS, tufA and 16S sequences to test the efficiency of traditional barcoding, GMYC, ABGD, PTP, P ID and character-based barcoding methods. First of all, the barcoding results gave new insights into the taxonomic assessment of Chlorella-like organisms studied, including the clear species discrimination and resolution of potentially cryptic species complexes in C. sorokiniana, D. ehrenbergianum and C. Vulgaris. The tufA proved to be the most efficient barcoding locus, which thus could be as potential "specific barcode" for Chlorella-like species. The 16S failed in discriminating most closely related species. The resolution of GMYC, PTP, P ID, ABGD and character-based barcoding methods were variable among rbcL, ITS and tufA genes. The best resolution for species differentiation appeared in tufA analysis where GMYC, PTP, ABGD and character-based approaches produced consistent groups while the PTP method over-split the taxa. The character analysis of rbcL, ITS and tufA sequences could clearly distinguish all taxonomic groups respectively, including the potentially cryptic lineages, with many character attributes. Thus, the character-based barcoding provides an attractive complement to coalescent and distance-based barcoding. Our study represents the test that proves the efficiency of multiple DNA barcoding in species discrimination of microalgaes.
已经提出了几种不同的区分物种的条形码方法，但哪种方法是最好的仍存在争议。小球藻在第二代生物燃料的开发中变得特别有前景。然而，类小球藻生物的分类很容易混淆。在这里，我们基于rbcL、ITS、tufA和16S序列，对来自小球藻属、绿球藻属、盘星藻属和辐球藻属的类小球藻物种进行了全面的条形码分析，以测试传统条形码、GMYC、ABGD、PTP、P ID和基于特征的条形码方法的效率。首先，条形码分析结果为所研究的类小球藻生物的分类评估提供了新的见解，包括清晰的物种区分以及对索氏小球藻、埃氏盘星藻和普通小球藻中潜在隐性物种复合体的解析。tufA被证明是最有效的条形码位点，因此可以作为类小球藻物种潜在的“特定条形码”。16S在区分亲缘关系最近的物种时失败了。GMYC、PTP、P ID、ABGD和基于特征的条形码方法在rbcL、ITS和tufA基因之间的分辨率各不相同。在tufA分析中，物种分化的最佳分辨率出现，其中GMYC、PTP、ABGD和基于特征的方法产生了一致的类群，而PTP方法过度划分了分类单元。对rbcL、ITS和tufA序列的特征分析可以分别清晰地区分所有分类群，包括潜在的隐性谱系，具有许多特征属性。因此，基于特征的条形码为基于合并和距离的条形码提供了有吸引力的补充。我们的研究代表了证明多种DNA条形码在微藻物种鉴别中效率的测试。
