转录本组装与质量评价

转录本组装是基于第二代测序技术研究转录组的关键环节,其质量好坏直接影响到下游结果的可靠性,也是目前的研究热点与难点。转录本组装方法可以分为Genome-guided和de novo两类,它们在理论基础与算法实现方面各有优劣。转录本组装质量的高低依赖于PCR扩增错误率、第二代测序技术准确率、组装算法和参考基因组完整性等方面,而现有的算法还无法完全处理由这些因素带来的影响。本文从转录本组装方法与软件、影响组装质量的因素和对组装质量的评价指标等方面进行讨论,以期能指导纯生物学家对分析软件的选择。     

基于Illumina RNA Seq短序列的转录组从头组装软件比较与优化

利用公共数据库中果蝇F1代和栽培水稻基于高通量Illumina测序平台的RNA Seq短序列数据,比较了8个 (ABySS, Velvet, SOAPdenovo, Oases, Trinity, Multiple k, T IDBA and Trans ABySS) 转录组从头组装软件。结果显示,在基于单一k mer和多重k mer方法的两类软件中,Trinity和Trans ABySS分别表现出最好的组装性能,而其它软件性能比较接近。我们还发现基于多重k mer比单一k mer可以组装获得更多的总碱基数目,但是即使利用最好的多重k mer组装软件,所获得的数据质量也比研究人员所期望的要低。鉴于此,我们提出了“ETM”优化方法,将多重k mer方法组合到Trinity中,使其在具有最好的组装性能的基础上兼具了多重k mer的优势,测试结果显示了该方法具有一定的优越性。我们的研究结果为用户选择合适的软件提供了依据,对推动基于高通量Illumina测序的转录组研究具有重要意义。     

De novo assembly of the Pseudomonas syringae pv. syringae B728a genome using Illumina/Solexa short sequence reads

Illumina's Genome Analyzer generates ultra-short sequence reads, typically 36 nucleotides in length, and is primarily intended for resequencing. We tested the potential of this technology for de novo sequence assembly on the 6 Mbp genome of Pseudomonas syringae pv. syringae B728a with several freely available assembly software packages. Using an unpaired data set, velvet assembled >96% of the genome into contigs with an N50 length of 8289 nucleotides and an error rate of 0.33%. edena generated smaller contigs (N50 was 4192 nucleotides) and comparable error rates. ssake and vcake yielded shorter contigs with very high error rates. Assembly of paired-end sequence data carrying 400 bp inserts produced longer contigs (N50 up to 15 628 nucleotides), but with increased error rates (0.5%). Contig length and error rate were very sensitive to the choice of parameter values. Noncoding RNA genes were poorly resolved in de novo assemblies, while >90% of the protein-coding genes were assembled with 100% accuracy over their full length. This study demonstrates that, in practice, de novo assembly of 36-nucleotide reads can generate reasonably accurate assemblies from about 40 × deep sequence data sets. These draft assemblies are useful for exploring an organism's proteomic potential, at a very economic low cost.