Mapping accuracy of short reads from massively parallel sequencing and the implications for quantitative expression profiling.
Mapping accuracy of short reads from massively parallel sequencing and the implications for quantitative expression profiling.
复制标题
映射大量平行测序的简短读取的精度以及对定量表达谱的含义。
DOI：
10.1371/journal.pone.0006323
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发表时间：
2009-07-28
期刊：
影响因子：
3.7
通讯作者：
Schlötterer C
中科院分区：
文献类型：
--
作者：
Palmieri N;Schlötterer C
大规模平行测序为表达谱分析提供了巨大的潜力，特别是用于种间比较。目前，用于大规模平行测序的不同平台是可用的，其在读取长度和测序成本方面不同。454技术提供最高的读取长度。其他测序技术更具成本效益，代价是更短的读取。通过大规模平行测序进行的可靠表达谱分析关键取决于读段可以映射到相应基因的准确性。我们进行了计算机模拟分析，以评估序列读数的不正确映射是否会导致偏倚的表达模式。对六种现有绘图软件工具的比较表明，在绘图速度和准确性方面存在相当大的差异。独立于用于定位读段的软件，我们发现对于紧凑基因组，短序列读段（35 bp，50 bp）和长序列读段（100 bp）都导致几乎无偏的表达模式。相比之下，对于具有包含更多基因家族和重复DNA的较大基因组的物种，较短的读取（35-50 bp）在基因表达中产生相当大的偏差。在人类中，大约10%的基因只有不到50%的序列读数被正确映射。高达9%的序列多态性对100 bp读数的定位准确性几乎没有影响。对于35 bp的读段，高达3%的序列分歧并不强烈影响作图准确性。插入缺失对作图效率的影响很大程度上取决于作图软件。在复杂的基因组中，通过大规模平行测序进行的表达谱分析可能会引入相当大的偏差，这是由于如果读段长度较短，则不正确映射的序列读段。然而，如果基因组序列已知，则可以解释这种偏倚。此外，序列多态性和插入缺失也会影响定位的准确性，并可能导致偏倚的基因表达测量。作图软件的选择是非常关键的，并且可靠性取决于indel的存在/不存在以及读段和参考基因组之间的分歧。总的来说，我们发现SSAHA 2和CLC产生最可靠的映射结果。
Massively parallel sequencing offers an enormous potential for expression profiling, in particular for interspecific comparisons. Currently, different platforms for massively parallel sequencing are available, which differ in read length and sequencing costs. The 454-technology offers the highest read length. The other sequencing technologies are more cost effective, on the expense of shorter reads. Reliable expression profiling by massively parallel sequencing depends crucially on the accuracy to which the reads could be mapped to the corresponding genes. We performed an in silico analysis to evaluate whether incorrect mapping of the sequence reads results in a biased expression pattern. A comparison of six available mapping software tools indicated a considerable heterogeneity in mapping speed and accuracy. Independently of the software used to map the reads, we found that for compact genomes both short (35 bp, 50 bp) and long sequence reads (100 bp) result in an almost unbiased expression pattern. In contrast, for species with a larger genome containing more gene families and repetitive DNA, shorter reads (35–50 bp) produced a considerable bias in gene expression. In humans, about 10% of the genes had fewer than 50% of the sequence reads correctly mapped. Sequence polymorphism up to 9% had almost no effect on the mapping accuracy of 100 bp reads. For 35 bp reads up to 3% sequence divergence did not affect the mapping accuracy strongly. The effect of indels on the mapping efficiency strongly depends on the mapping software. In complex genomes, expression profiling by massively parallel sequencing could introduce a considerable bias due to incorrectly mapped sequence reads if the read length is short. Nevertheless, this bias could be accounted for if the genomic sequence is known. Furthermore, sequence polymorphisms and indels also affect the mapping accuracy and may cause a biased gene expression measurement. The choice of the mapping software is highly critical and the reliability depends on the presence/absence of indels and the divergence between reads and the reference genome. Overall, we found SSAHA2 and CLC to produce the most reliable mapping results.
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