优化一种高效的组合方法,以实现高质量的de novo转录组组的Thimus daenensis
Hosein Ahmadi1, Morteza Sheikh-Assadi1, Reza Fatahi2
1Department of Horticulture Science, Faculty of Agriculture and Natural Sciences, University of Tehran, Karaj, Iran.
Scientific reports
|July 31, 2023
概括
优化转录组组装对于准确的生物分析至关重要. 这项研究发现,合并方法,特别是使用EvidentialGene,在非模型物种 (如Thymus daenensis) 中显著改善了转录组组装质量.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 准确的转录组组合对于下游生物分析至关重要.
- 不同的de novo汇编器具有独特的优缺点,需要对数据集进行特定的评估.
- 非模型生物经常为转录组组装带来独特的挑战.
研究的目的:
- 为了评估七个最先进的de novo转录基因组装器的效率.
- 评估组合工作流程的性能,将多个组装器结合起来,以提高组装质量.
- 为了确定最佳的 Thymus daenensis 转录组组装器和策略.
主要方法:
- 的mRNA测序数据 (大约. 30 Gb) 来自Thymus daenensis被用于组装.
- 七个 de novo 组装器 (EvidentialGene,BinPacker,Trinity,rnaSPAdes,CAP3,IDBA-trans,Velvet-Oases) 进行了基准测试,这些组装器的使用情况是如下:
- 实施了一套整体工作流程,包括减少冗余,并使用16个指标进行评估.
主要成果:
- 证据基因在多个指标上表现出卓越的表现,包括完整性,可注释性和开放阅读框架 (ORF) 丰富性.
- 整体方法,特别是EvidentialGene,与单个组装器相比,产生了更多的独特BLAST命中,全长转录和更少的错组装.
- 有证据的基因产生了316,786个转录,其中74%具有独特的蛋白质命中和一半含有ORF,显著超过了最差的组装程序 (天绿洲).
结论:
- 依赖单一的转录组组装器可能会导致低于最佳的结果,特别是在非模型物种中.
- 对于T. daenensis的高级转录组组合,建议采用一个整体策略,优先考虑EvidentialGene,并纳入冗余减少.
- 这些发现为优化类似研究环境中的转录组组装提供了强大的框架.
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