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首页> 外文期刊>BMC Genomics >Identifying similar transcripts in a related organism from de Bruijn graphs of RNA-Seq data, with applications to the study of salt and waterlogging tolerance in Melilotus
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Identifying similar transcripts in a related organism from de Bruijn graphs of RNA-Seq data, with applications to the study of salt and waterlogging tolerance in Melilotus

机译：从RNA-SEQ数据的De Bruijn图表中鉴定相关生物体中的类似转录物，其中包含在Melilotus中的盐和涝耐受性研究

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摘要

A popular strategy to study alternative splicing in non-model organisms starts from sequencing the entire transcriptome, then assembling the reads by using de novo transcriptome assembly algorithms to obtain predicted transcripts. A similarity search algorithm is then applied to a related organism to infer possible function of these predicted transcripts. While some of these predictions may be inaccurate and transcripts with low coverage are often missed, we observe that it is possible to obtain a more complete set of transcripts to facilitate possible functional assignments by starting the search from the intermediate de Bruijn graph that contains all branching possibilities. We develop an algorithm to extract similar transcripts in a related organism by starting the search from the de Bruijn graph that represents the transcriptome instead of from predicted transcripts. We show that our algorithm is able to recover more similar transcripts than existing algorithms, with large improvements in obtaining longer transcripts and a finer resolution of isoforms. We apply our algorithm to study salt and waterlogging tolerance in two Melilotus species by constructing new RNA-Seq libraries. We have developed an algorithm to identify paths in the de Bruijn graph that correspond to similar transcripts in a related organism directly. Our strategy bypasses the transcript prediction step in RNA-Seq data and makes use of support from evolutionary information.
机译：在非模型生物中学习替代拼接的流行策略开始测序整个转录组，然后通过使用de novo转录组合算法组装读取以获得预测的转录物。然后将相似性搜索算法应用于相关的生物体以推断出这些预测的转录物的可能功能。虽然这些预测中的一些可能是不准确的，并且经常错过具有低覆盖的成绩单，但我们观察到，可以通过从包含所有分支的中间de Bruijn图表开始搜索来促进可能的功能分配来获得更完整的一组竞争分子可能性。我们开发一种算法，通过从代表转录组代替来自预测的转录物的DE BRUIJN图表中搜索来提取相关生物中的类似转录物。我们表明我们的算法能够恢复比现有算法更类似的成绩单，并且获得更长的成绩单和异构型的更精细分辨率的大改进。我们通过构建新的RNA-SEQ文库来应用我们的算法来研究两种Melilotus物种中的盐和涝耐受性。我们开发了一种算法，用于识别DE BRUIJN图表中的路径，该图表直接对应于相关生物中的类似转录物。我们的策略绕过RNA-SEQ数据中的转录程序预测步骤，并利用来自进化信息的支持。

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