ena-STUDY-CLM-11-12-2013-08:21:38:180-158
Reducing erroneous identification using Miseq system
The cost of DNA sequencing has been declined with an advancement of next generation sequencing. Throughput sequences of Illumina platform is larger than the other platforms, it has been tried to use for microbial community study. However, a large amount of sequence read generates other challenges of analysis process and increasing erroneous reads toward 3’ end terminal sequence. Several studies have proposed curating pipelines to increase accuracy of reads, and used Illumina system to metagenomics analysis. In this study, we evaluated the possibility of erroneous results in the analysis of community composition using Illumina MiSeq platform, and improved a pipeline to reduce erroneous identifications. We compared different sequencing conditions such as proportion of mixed PhiX, concentration of sequencing library, and target region of 16S rRNA gene using a mock community sample, which is composed of known sequences. Our recommended method corrected erroneous sequences and improved identification accuracy; up to 99.5% of the total reads had a 95% similarity with the corresponding template sequences, and up to 93.6% of the total reads had over a 97% similarity. This improved analysis can be applied amplicon studies in various environments using high-throughput reads generating MiSeq platform with high accuracy.
The cost of DNA sequencing has been declined with an advancement of next generation sequencing. Throughput sequences of Illumina platform is larger than the other platforms, it has been tried to use for microbial community study. However, a large amount of sequence read generates other challenges of analysis process and increasing erroneous reads toward 3’ end terminal sequence. Several studies have proposed curating pipelines to increase accuracy of reads, and used Illumina system to metagenomics analysis. In this study, we evaluated the possibility of erroneous results in the analysis of community composition using Illumina MiSeq platform, and improved a pipeline to reduce erroneous identifications. We compared different sequencing conditions such as proportion of mixed PhiX, concentration of sequencing library, and target region of 16S rRNA gene using a mock community sample, which is composed of known sequences. Our recommended method corrected erroneous sequences and improved identification accuracy; up to 99.5% of the total reads had a 95% similarity with the corresponding template sequences, and up to 93.6% of the total reads had over a 97% similarity. This improved analysis can be applied amplicon studies in various environments using high-throughput reads generating MiSeq platform with high accuracy.