Data from: aTRAM - automated Target Restricted Assembly Method: a fast method for assembling loci across divergent taxa from next-generation sequencing data

Background: Assembling genes from next-generation sequencing data is not only time consuming but computationally difficult, particularly for taxa without a closely related reference genome. Assembling even a draft genome using de novo approaches can take days, even on a powerful computer, and these assemblies typically require data from a variety of genomic libraries. Here we describe software that will alleviate these issues by rapidly assembling genes from distantly related taxa using a single library of paired-end reads: aTRAM, automated Target Restricted Assembly Method. The aTRAM pipeline uses a reference sequence, BLAST, and an iterative approach to target and locally assemble the genes of interest. Results: Our results demonstrate that aTRAM rapidly assembles genes across distantly related taxa. In comparative tests with a closely related taxon, aTRAM assembled the same sequence as reference-based and de novo approaches taking on average < 1 min per gene. As a test case with divergent sequences, we assembled >1,000 genes from six taxa ranging from 25 – 110 million years divergent from the reference taxon. The gene recovery was between 97 – 99% from each taxon. Conclusions: aTRAM can quickly assemble genes across distantly-related taxa, obviating the need for draft genome assembly of all taxa of interest. Because aTRAM uses a targeted approach, loci can be assembled in minutes depending on the size of the target. Our results suggest that this software will be useful in rapidly assembling genes for phylogenomic projects covering a wide taxonomic range, as well as other applications. The software is freely available: http://www.github.com/juliema/aTRAM

研究背景：从下一代测序（next-generation sequencing）数据中组装基因不仅耗时耗力，且计算难度颇高，对于缺乏近缘参考基因组的分类群而言尤为如此。即便采用从头组装（de novo）策略构建草图基因组，即便在高性能计算机上运行，往往也需要数日之久，且此类组装通常需要依托多种基因组文库的数据。本文介绍一款可缓解上述痛点的软件aTRAM（自动化靶标限制性组装方法，automated Target Restricted Assembly Method），其可通过单份双端测序读段文库，快速完成远缘分类群的基因组装。aTRAM流程依托参考序列、BLAST（碱基局部比对搜索工具，Basic Local Alignment Search Tool）与迭代策略，实现靶标基因的靶向定位与局部组装。

研究结果：本研究结果证实，aTRAM可高效完成跨远缘分类群的基因组装。在近缘参考分类群的对比测试中，aTRAM组装得到的序列与基于参考基因组的组装方法及从头组装方法的结果完全一致，单基因平均组装耗时不足1分钟。针对序列分歧度较高的测试案例，我们在与参考分类群分歧时间介于2500万至1.1亿年之间的6个分类群中，成功组装得到超过1000个基因，各分类群的基因回收率达97%~99%。

研究结论：aTRAM可快速完成跨远缘分类群的基因组装，无需对所有目标分类群开展草图基因组组装。由于aTRAM采用靶向组装策略，根据靶标序列的长度，基因座可在数分钟内完成组装。本研究结果表明，该软件可快速为覆盖广泛分类学范围的系统发育基因组学（phylogenomics）研究项目及其他应用场景完成基因组装。该软件可免费获取：http://www.github.com/juliema/aTRAM