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

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.

Deep long-read metagenomic sequencing reveals niche differentiation in carbon cycling potential between benthic and planktonic microbial populations

“…The sequencing depth for each MAG was estimated mapping the unassembled LRs using minimap2 v2.17 61 with the map-hifi option, and filtering mapped LRs at ≥ 95% identity using the jgi_summarize_bam_contig_depths script from MetaBAT v2.2.15 62 . These average sequencing depth values were normalized using the genome equivalents determined for each metagenome 27 .…”

“…The resulting read depth values were truncated to the middle 80% (TAD80) of depth values (i.e., the upper and lower 10% of outliers were removed) using a Python script from https://github.com/rotheconrad/00_in-situ_GeneCoverage 13,70 . Finally, to estimate the relative abundance with respect to the abundance of bacterial and archaeal communities, each TAD80 value was normalized by the "genome equivalents" value estimated using MicrobeCensus v1.1.0 27,71 .…”

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

“…Promisingly, third-generation platforms will overcome some short-read sequencing limitations, mainly regarding highly repetitive regions, high levels of sequence microdiversity, multiple copies of genes, or AT-rich/GC-rich regions. 73,76,77 Finally, users must also be familiar with technical aspects such as the sequencing depth, which may greatly impact the resolution of the results. 78 Quince et al 78 reported that a fixed depth of 10 million reads and a minimum of 1 Gb sequencing per sample are typically used or recommended in metagenomic studies, but high levels of host DNA may interfere with an accurate reconstitution of the microbiome profile.…”

Highly accurate metagenome-assembled genomes from human gut microbiota using long-read assembly, binning, and consolidation methods

“…PacBio HiFi sequencing produces highly accurate consensus reads (>Q20, median Q30) that are 10–20 kb in length (Wenger et al 2019). Several studies have demonstrated that HiFi sequencing generally produces more total MAGs and higher quality MAGs than short-read sequencing (Priest et al 2021; Gehrig et al 2022; Meslier et al 2022; Eisenhofer et al 2023; Orellana et al 2023; Tao et al 2023; Zhang et al 2023), and that HiFi sequencing outperforms ONT for metagenome assembly (Meslier et al 2022; Sereika et al 2022). The high accuracy of HiFi reads has led to the development of two new metagenome assembly methods, hifiasm-meta (Feng et al 2022) and metaMDBG (Benoit et al 2023), which perform better than previous methods such as HiCanu (Nurk et al 2020) and metaFlye (Kolmogorov et al 2020).…”