Department of Energy Joint Genome Institute, Walnut Creek, California, USA.
Nat Methods. 2010 Oct;7(10):807-12. doi: 10.1038/nmeth.1507. Epub 2010 Sep 19.
The predominance of rRNAs in the transcriptome is a major technical challenge in sequence-based analysis of cDNAs from microbial isolates and communities. Several approaches have been applied to deplete rRNAs from (meta)transcriptomes, but no systematic investigation of potential biases introduced by any of these approaches has been reported. Here we validated the effectiveness and fidelity of the two most commonly used approaches, subtractive hybridization and exonuclease digestion, as well as combinations of these treatments, on two synthetic five-microorganism metatranscriptomes using massively parallel sequencing. We found that the effectiveness of rRNA removal was a function of community composition and RNA integrity for these treatments. Subtractive hybridization alone introduced the least bias in relative transcript abundance, whereas exonuclease and in particular combined treatments greatly compromised mRNA abundance fidelity. Illumina sequencing itself also can compromise quantitative data analysis by introducing a G+C bias between runs.
在基于序列的微生物分离物和群落 cDNA 的分析中,rRNAs 在转录组中占优势是一个主要的技术挑战。已经应用了几种方法来从(宏)转录组中去除 rRNAs,但没有报道过对任何这些方法引入的潜在偏差进行系统调查。在这里,我们使用大规模平行测序验证了两种最常用的方法(消减杂交和核酸外切酶消化)以及这些处理的组合在两个合成的五微生物元转录组上的有效性和保真度。我们发现,对于这些处理方法,rRNA 去除的有效性是群落组成和 RNA 完整性的函数。单独的消减杂交引入的相对转录物丰度偏差最小,而核酸外切酶,特别是联合处理极大地损害了 mRNA 丰度的保真度。Illumina 测序本身也可以通过在运行之间引入 G+C 偏差来破坏定量数据分析。