Fine-scale congruence in bacterial community structure from marine sediments sequenced by short-reads on Illumina and long-reads on Nanopore
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Following the development of high-throughput sequencers, environmental prokaryotic communities are usually described by metabarcoding with genetic markers on the 16S domain. However, short-read sequencing encounters a limitation in phylogenetic coverage and taxonomic resolution, due to the primers choice and read length. On these critical points, nanopore sequencing, a rising technology, suitable for long-read metabarcoding, was much undervalued because of its relatively higher error rate per read. Here we compared the prokaryotic community structure in a mock community and 52 sediment samples from two contrasted mangrove sites, described by short-reads on 16SV4-V5 marker ( ca . 0.4kpb) analyzed by Illumina sequencing (MiSeq, V3), with those described by long-reads on bacterial nearly complete 16S ( ca . 1.5 kpb) analyzed by Oxford Nanopore (MinION, R9.2). Short- and long-reads retrieved all the bacterial genera from the mock, although both showing similar deviations from the awaited proportions. From the sediment samples, with a coverage-based rarefaction of reads and after singletons filtering, co-inertia and Procrustean tests showed that bacterial community structures inferred from short- and long-reads were significantly similar, showing both a comparable contrast between sites and a coherent sea-land orientation within sites. In our dataset, 84.7 and 98.8% of the short-reads were assigned strictly to the same species and genus, respectively, than those detected by long-reads. Primer specificities of long-16S allowed it to detect 92.2% of the 309 families and 87.7% of the 448 genera that were detected by the short 16SV4-V5. Long-reads recorded 973 additional taxa not detected by short-reads, among which 91.7% were identified to the genus rank, some belonging to 11 exclusive phyla, albeit accounting for only 0.2% of total long-reads.