CSIR-National Environmental Engineering Research Institute (NEERI), Hyderabad Zonal Centre, IICT Campus, Tarnaka, Hyderabad, Telangana, 500007, India.
Arch Microbiol. 2021 Dec;203(10):6295-6302. doi: 10.1007/s00203-021-02597-9. Epub 2021 Oct 15.
Illumina sequencing platforms have been widely used for amplicon-based environmental microbiome research. Analyses of amplicon data of environmental samples, generated from Illumina MiSeq platform illustrate the reverse (R2) reads in the PE datasets to have low quality towards the 3' end of the reads which affect the sequencing depth of samples and ultimately impact the sample size which may possibly lead to an altered outcome. This study evaluates the usefulness of single-end (SE) sequencing data in microbiome research when the Illumina MiSeq PE dataset shows significantly high number of low-quality reverse reads. In this study, the amplicon data (V1V3, V3V4, V4V5 and V6V8) from 128 environmental (soil) samples, downloaded from SRA, demonstrate the efficiency of single-end (SE) sequencing data analyses in microbiome research. The SE datasets were found to infer the core microbiome structure as comparable to the PE dataset. Conspicuously, the forward (R1) datasets inferred a higher number of taxa as compared to PE datasets for most of the amplicon regions, except V3V4. Thus, analyses of SE sequencing data, especially R1 reads, in environmental microbiome studies could ameliorate the problems arising on sample size of the study due to low quality reverse reads in the dataset. However, care must be taken while interpreting the microbiome structure as few taxa observed in the PE datasets were absent in the SE datasets. In conclusion, this study demonstrates the availability of choices in analyzing the amplicon data without having the need to remove samples with low quality reverse reads.
Illumina 测序平台已广泛应用于基于扩增子的环境微生物组研究。Illumina MiSeq 平台产生的环境样本扩增子数据分析表明，PE 数据集的反向 (R2) reads 在读取的 3' 端质量较低，这会影响样本的测序深度，并最终影响样本量，从而可能导致结果改变。本研究评估了当 Illumina MiSeq PE 数据集显示出大量低质量反向 reads 时，单端 (SE) 测序数据在微生物组研究中的有用性。在这项研究中，从 SRA 下载的 128 个环境 (土壤) 样本的扩增子数据 (V1V3、V3V4、V4V5 和 V6V8) 展示了单端 (SE) 测序数据分析在微生物组研究中的效率。SE 数据集被发现可以推断核心微生物组结构，与 PE 数据集相当。值得注意的是，与大多数扩增子区域相比，PE 数据集的正向 (R1) 数据集推断出的分类单元数量更高，除了 V3V4。因此，在环境微生物组研究中，对 SE 测序数据（特别是 R1 读取）进行分析，可以改善由于数据集反向 reads 质量低而导致的样本量问题。然而，在解释微生物组结构时必须小心，因为在 PE 数据集中观察到的少数分类单元在 SE 数据集中不存在。总之，本研究表明，在不需要去除低质量反向 reads 的情况下，对扩增子数据进行分析有多种选择。
