Concatenation of paired-end reads improves taxonomic classification of amplicons for profiling microbial communities

Abstract

Background Taxonomic classification of genetic markers for microbiome analysis is affected by the numerous choices made from sample preparation to bioinformatics analysis. Paired-end read merging is routinely used to capture the entire amplicon sequence when the read ends overlap. However, the exclusion of unmerged reads from further analysis can result in underestimating the diversity in the sequenced microbial community and is influenced by bioinformatic processes such as read trimming and the choice of reference database. A potential solution to overcome this is to concatenate (join) reads that do not overlap and keep them for taxonomic classification. The use of concatenated reads can outperform taxonomic recovery from single-end reads, but it remains unclear how their performance compares to merged reads. Using various sequenced mock communities with different amplicons, read length, read depth, taxonomic composition, and sequence quality, we tested how merging and concatenating reads performed for genus recall and precision in bioinformatic pipelines combining different parameters for read trimming and taxonomic classification using different reference databases. Results The addition of concatenated reads to merged reads always increased pipeline performance. The top two performing pipelines both included read concatenation, with variable strengths depending on the mock community. The pipeline that combined merged and concatenated reads that were quality-trimmed performed best for mock communities with larger amplicons and higher average quality sequences. The pipeline that used length-trimmed concatenated reads outperformed quality trimming in mock communities with lower quality sequences but lost a significant amount of input sequences for taxonomic classification during processing. Genus level classification was more accurate using the SILVA reference database compared to Greengenes. Conclusions Merged sequences with the addition of concatenated sequences that were unable to be merged increased performance of taxonomic classifications. This was especially beneficial in mock communities with larger amplicons. We have shown for the first time, using an in-depth comparison of pipelines containing merged vs concatenated reads combined with different trimming parameters and reference databases, the potential advantages of concatenating sequences in improving resolution in microbiome investigations.

Don’t let valuable microbiome data go to waste: combined usage of merging and direct-joining of sequencing reads for low quality amplicon data

“…Notably, the method M-DJ inferred a highest number of taxa as compared to the other two approaches (Figure 3). Thus, in accordance with the earlier finding (Dacey and Chain, 2021), this study also supports that the analysis of merged sequences along with the directly-joined unmerged reads could improve the resolution of microbial composition in the samples. Further, the most important taxa (top ten) that could be used to explain the ecosystems were found to be different (Figure 4) for M, DJ and M-DJ, which could be due to the differences in the ASV distribution and abundance of taxa observed in the respective groups.…”

“…A recent study using mock community data has highlighted that directly-joined reads that lack overlapping regions along with the merged sequences could improve the taxonomic classification (Dacey and Chain, 2021). This study investigates how the analysis of merged sequences along with directly-joined unmerged PE reads ameliorates the problems associated with low quality data in environmental microbiome research.…”

Impact of seawater temperature on the Pacific oyster (

“…Using the DADA2 pipeline, the sequence reads were truncated at 120 bp on the basis of -the quality of sequence data and the reverse reads were reverse-complemented and concatenated with the forward reads. There is a possibility of reducing microbiome diversity estimates through exclusion of sequence reads that fail to merge (Aigle et al 2019;Dacey and Chain 2021). Concatenating paired reads together without a sequence overlap has been identified as an alternative to overcome this problem (Aigle et al 2019;Dacey and Chain 2021).…”

“…There is a possibility of reducing microbiome diversity estimates through exclusion of sequence reads that fail to merge (Aigle et al 2019;Dacey and Chain 2021). Concatenating paired reads together without a sequence overlap has been identified as an alternative to overcome this problem (Aigle et al 2019;Dacey and Chain 2021).…”

High-quality single amplicon sequencing method for illumina MiSeq platform using pool of ‘N’ (0–10) spacer-linked target specific primers without PhiX spike-in

“…Towards this, we performed two independent runs and the generated reads were further analysed using DADA2 pipeline [14]. It has also been shown that the choice of reference database impacts the downstream analysis significantly [15]. In this study we used SILVA database as reference for taxonomic assignment.…”