Spelman College, 350 Spelman Lane Southwest, Atlanta, GA, 30314, USA.
BMC Evol Biol. 2018 Nov 16;18(1):170. doi: 10.1186/s12862-018-1283-1.
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.
由于成本低、样本需求少，转录组测序已成为微生物真核生物进化研究的首选方法。转录组数据已广泛应用于系统发育基因组学研究，以推断古老的进化历史。然而，其在研究隐种多样性方面的应用尚未得到充分探索。本研究进行了一项实证调查，以检验转录组数据在解决较低分类水平的两种主要分歧类型中的适用性。这些分歧包括形态相同但遗传不同的物种（隐种）和形态不同但遗传相同的物种。我们构建了一个物种比较生物信息学管道，该管道考虑了具有此类分歧的变形虫微生物中转录组数据的性质。
无论培养方法、RNA 采集或测序方法如何，我们对已知或疑似隐种的分析都得出了一致的结果。在使用不同方法和隐种测序的相同物种样本中分析的单拷贝基因中，超过 95%的基因具有低于 2%的种内和种间差异。只有少数群体（2.91-4.87%）在这些分类群中具有超过 2%的高距离，这可能是由于数据质量低造成的。在具有不同形态的疑似遗传相似物种中也观察到了这种模式。转录组数据一致地区分了所有高于种级别的分类群，包括隐种多样的物种。通过我们的方法，我们能够解决隐种问题，发现错误鉴定并发现新物种。我们还确定了几个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，转录组数据适合于理解微生物真核生物中的隐种多样性。
