A comprehensive evaluation of single-end sequencing data analyses for environmental microbiome research

Area of Science:

• Environmental microbiology
• Bioinformatics
• Genomics

Background:

• Illumina MiSeq platforms are standard for amplicon-based environmental microbiome studies.
• Low-quality reverse reads (R2) in paired-end (PE) datasets can reduce sequencing depth and sample size, potentially skewing results.

Purpose of the Study:

• To evaluate the utility of single-end (SE) sequencing data for microbiome research, particularly when PE data quality is compromised.
• To compare the effectiveness of SE versus PE datasets in characterizing environmental soil microbiomes.

Main Methods:

• Analysis of amplicon data (V1V3, V3V4, V4V5, V6V8) from 128 soil samples obtained from the Sequence Read Archive (SRA).
• Comparison of microbiome structure and taxa identification between SE (R1 reads) and PE datasets.

Main Results:

• SE datasets effectively inferred core microbiome structure comparable to PE datasets.
• Forward (R1) SE reads identified more taxa than PE datasets across most amplicon regions, except V3V4.
• Few taxa present in PE datasets were absent in SE datasets, necessitating careful interpretation.

Conclusions:

• SE sequencing data, especially R1 reads, can mitigate issues caused by low-quality reverse reads in environmental microbiome studies.
• Utilizing SE data provides flexibility in amplicon data analysis, avoiding sample exclusion due to poor read quality.