Selecting Superior De Novo Transcriptome Assemblies: Lessons Learned by Leveraging the Best Plant Genome.
Selecting Superior De Novo Transcriptome Assemblies: Lessons Learned by Leveraging the Best Plant Genome.
复制标题
DOI：
10.1371/journal.pone.0146062
复制
发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
dePamphilis CW
中科院分区：
文献类型：
--
作者：
Honaas LA;Wafula EK;Wickett NJ;Der JP;Zhang Y;Edger PP;Altman NS;Pires JC;Leebens-Mack JH;dePamphilis CW
尽管生命之树上越来越多的物种正在发表RNA-Seq数据的从头开始组装，但目前还没有被广泛接受的方法来评估这种组装。在这里，我们提供了99个转录组的详细比较，由6个从头组装产生，包括CLC，三一，肥皂，绿洲，深渊和NextGENe。对拟南芥和水稻转录本的从头组装的对照分析为转录组组装策略的优势和局限性提供了新的见解。我们发现，领先的组装者为大多数成绩单生成令人放心的准确组装。与此同时，我们发现装配者有一种无法完全组装高表达基因的倾向。令人惊讶的是，对于所有的组装者来说，真正的嵌合组装的实例非常少。标准化文库在高度丰富的转录本中减少，但它们也缺乏1000个低丰度转录本。我们的结论是，通过考虑以下指标的组合来评估从头转录组组件的质量是最好的：1)映射到组件的读取比例，2)保守的、广泛表达的基因的恢复，3)N50长度统计，以及4)非基因总数。我们提供了基准的Illumina转录组数据，并介绍了SCERNA，一种广泛适用的模块化协议，用于从头组装改进。最后，我们对拟南芥叶片转录组的重新组装揭示了大约20个可能的拟南芥基因在当前注释中缺失。
Whereas de novo assemblies of RNA-Seq data are being published for a growing number of species across the tree of life, there are currently no broadly accepted methods for evaluating such assemblies. Here we present a detailed comparison of 99 transcriptome assemblies, generated with 6 de novo assemblers including CLC, Trinity, SOAP, Oases, ABySS and NextGENe. Controlled analyses of de novo assemblies for Arabidopsis thaliana and Oryza sativa transcriptomes provide new insights into the strengths and limitations of transcriptome assembly strategies. We find that the leading assemblers generate reassuringly accurate assemblies for the majority of transcripts. At the same time, we find a propensity for assemblers to fail to fully assemble highly expressed genes. Surprisingly, the instance of true chimeric assemblies is very low for all assemblers. Normalized libraries are reduced in highly abundant transcripts, but they also lack 1000s of low abundance transcripts. We conclude that the quality of de novo transcriptome assemblies is best assessed through consideration of a combination of metrics: 1) proportion of reads mapping to an assembly 2) recovery of conserved, widely expressed genes, 3) N50 length statistics, and 4) the total number of unigenes. We provide benchmark Illumina transcriptome data and introduce SCERNA, a broadly applicable modular protocol for de novo assembly improvement. Finally, our de novo assembly of the Arabidopsis leaf transcriptome revealed ~20 putative Arabidopsis genes lacking in the current annotation.