Comparing genomes recovered from time-series metagenomes using long- and short-read sequencing technologies

利用长读长和短读长测序技术比较从时间序列宏基因组中恢复的基因组

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Abstract

BACKGROUND: Over the past years, sequencing technologies have expanded our ability to examine novel microbial metabolisms and diversity previously obscured by isolation approaches. Long-read sequencing promises to revolutionize the metagenomic field and recover less fragmented genomes from environmental samples. Nonetheless, how to best benefit from long-read sequencing and whether long-read sequencing can provide recovered genomes of similar characteristics as short-read approaches remains unclear. RESULTS: We recovered metagenome-assembled genomes (MAGs) from the free-living fraction at four-time points during a spring bloom in the North Sea. The taxonomic composition of all MAGs recovered was comparable between technologies. However, differences consisted of higher sequencing depth for contigs and higher genome population diversity in short-read compared to long-read metagenomes. When pairing population genomes recovered from both sequencing approaches that shared ≥ 99% average nucleotide identity, long-read MAGs were composed of fewer contigs, a higher N50, and a higher number of predicted genes when compared to short-read MAGs. Moreover, 88% of the total long-read MAGs carried a 16S rRNA gene compared to only 23% of MAGs recovered from short-read metagenomes. Relative abundances for population genomes recovered using both technologies were similar, although disagreements were observed for high and low GC content MAGs. CONCLUSIONS: Our results highlight that short-read technologies recovered more MAGs and a higher number of species than long-read due to an overall higher sequencing depth. Long-read samples produced higher quality MAGs and similar species composition compared to short-read sequencing. Differences in the GC content recovered by each sequencing technology resulted in divergences in the diversity recovered and relative abundance of MAGs within the GC content boundaries.

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