A practical implementation of large transcriptomic data analysis to resolve cryptic species diversity problems in microbial eukaryotes.
A practical implementation of large transcriptomic data analysis to resolve cryptic species diversity problems in microbial eukaryotes.
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DOI：
10.1186/s12862-018-1283-1
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发表时间：
2018-11-16
影响因子：
3.4
通讯作者：
Wood FC
中科院分区：
文献类型：
--
作者：
Tekle YI;Wood FC
转录组测序由于成本低和样品需求少，已成为微生物真核生物进化研究的一种选择方法。转录组数据已广泛用于系统基因组学研究，以推断古代进化史。然而，它在研究隐物种多样性方面的应用还没有得到很好的探索。为了检验转录组数据在较低分类水平上解决两种主要类型不一致的适用性，进行了一项实证调查。这些情况包括物种具有相同的形态但不同的遗传（隐种）和物种具有不同的形态但具有相同的遗传。我们建立了一个物种比较生物信息学管道，考虑到变形虫微生物中转录组数据的性质，举例说明了这种不一致。我们对已知或疑似隐种的分析得出了一致的结果，无论采用哪种培养方法、RNA收集方法或测序方法。用不同方法测序的同一物种和隐种样品中，95%以上的单拷贝基因的种内和种间差异低于2%。只有少数类群（2.91 ~ 4.87%）的高度距离超过2%，这可能是由于数据质量较低造成的。这种模式也在疑似基因相似但形态不同的物种中观察到。转录组数据一致地描述了物种水平以上的所有分类群，包括隐多样性物种。利用我们的方法，我们能够解决神秘物种的问题，发现错误的识别并发现新物种。我们还确定了几种具有不同进化速率的潜在条形码标记，可用于具有不同进化历史的谱系。我们的研究结果表明，转录组数据适用于理解微生物真核生物的隐物种多样性。本文的在线版本（10.1186/s12862-018-1283-1）包含补充内容，仅供授权用户使用。
Transcriptome sequencing has become a method of choice for evolutionary studies in microbial eukaryotes due to low cost and minimal sample requirements. Transcriptome data has been extensively used in phylogenomic studies to infer ancient evolutionary histories. However, its utility in studying cryptic species diversity is not well explored. An empirical investigation was conducted to test the applicability of transcriptome data in resolving two major types of discordances at lower taxonomic levels. These include cases where species have the same morphology but different genetics (cryptic species) and species of different morphologies but have the same genetics. We built a species comparison bioinformatic pipeline that takes into account the nature of transcriptome data in amoeboid microbes exemplifying such discordances. Our analyses of known or suspected cryptic species yielded consistent results regardless of the methods of culturing, RNA collection or sequencing. Over 95% of the single copy genes analyzed in samples of the same species sequenced using different methods and cryptic species had intra- and interspecific divergences below 2%. Only a minority of groups (2.91–4.87%) had high distances exceeding 2% in these taxa, which was likely caused by low data quality. This pattern was also observed in suspected genetically similar species with different morphologies. Transcriptome data consistently delineated all taxa above species level, including cryptically diverse species. Using our approach we were able to resolve cryptic species problems, uncover misidentification and discover new species. We also identified several potential barcode markers with varying evolutionary rates that can be used in lineages with different evolutionary histories. Our findings demonstrate that transcriptome data is appropriate for understanding cryptic species diversity in microbial eukaryotes. The online version of this article (10.1186/s12862-018-1283-1) contains supplementary material, which is available to authorized users.
影响因子：
10.1
作者：
Tekle YI;Parfrey LW;Katz LA
通讯作者：
Katz LA