Reverse transcriptase enzyme and priming strategy affect quantification and diversity of environmental transcripts
Reverse transcriptase enzyme and priming strategy affect quantification and diversity of environmental transcripts
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DOI：
10.1111/1462-2920.15017
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发表时间：
2020-04-29
影响因子：
5.1
通讯作者：
Smith, Cindy J.
中科院分区：
文献类型：
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作者：
Cholet, Fabien;Ijaz, Umer Z.;Smith, Cindy J.
逆转录酶定量PCR （RT-Q-PCR）和RT-PCR扩增子测序为基因表达研究提供了一种方便、靶向、高灵敏度的方法，在环境微生物学中得到了广泛的应用。然而，逆转录步骤的有效性和可重复性尚未得到评估。因此，我们测试了四种商业逆转录酶与两种引物技术的组合，以忠实地转录来自海洋沉积物的16S rRNA和amoA转录物。酶和引物策略对同一靶标的定量影响很大，差异可达600倍。此外，RT系统的选择显著改变了恢复的群落。对于16S rRNA，酶和引物均有显著影响，酶的影响强于引物。相反，对于amoA，只有启动策略的变化才会导致相同样品之间的显著差异。具体而言，GS引物获得了更多的OTUs和更好的amoA转录本多样性覆盖率，表明该方法在恢复amoA转录本多样性方面效果更好。此外，RNA模拟群落的测序显示，尽管转录α多样性（即样本内的OTU计数）可能受到RT的偏倚，但β多样性（即样本间OTU计数的差异）的比较是可靠的，因为这些偏倚在不同环境之间是可重复的。
Reverse-transcriptase-quantitative PCR (RT-Q-PCR) and RT-PCR amplicon sequencing, provide a convenient, target-specific, high-sensitivity approach for gene expression studies and are widely used in environmental microbiology. Yet, the effectiveness and reproducibility of the reverse transcription step has not been evaluated. Therefore, we tested a combination of four commercial reverse transcriptases with two priming techniques to faithfully transcribe 16S rRNA and amoA transcripts from marine sediments. Both enzyme and priming strategy greatly affected quantification of the exact same target with differences of up to 600-fold. Furthermore, the choice of RT system significantly changed the communities recovered. For 16S rRNA, both enzyme and priming had a significant effect with enzyme having a stronger impact than priming. Inversely, for amoA only the change in priming strategy resulted in significant differences between the same samples. Specifically, more OTUs and better coverage of amoA transcripts diversity were obtained with GS priming indicating this approach was better at recovering the diversity of amoA transcripts. Moreover, sequencing of RNA mock communities revealed that, even though transcript alpha diversities (i.e., OTU counts within a sample) can be biased by the RT, the comparison of beta diversities (i.e., differences in OTU counts between samples) is reliable as those biases are reproducible between environments.