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bioRxiv · 10.64898/2026.04.17.719029

Systematic comparisons between long-read and short-read based amplicon sequencing to characterize mixed microalgal communities.

Abstract

The 18S rRNA gene has emerged as the primary molecular marker for amplicon-based characterization of microalgal communities, including in wastewater treatment systems, yet trade-offs between short- and long-read approaches remain poorly defined. We systematically compared V8-V9 short-read sequencing (Illumina MiSeq), full-length long-read sequencing with ss5ss3 primers (PacBio Sequel II), and computationally extracted V8-V9 regions from long-read data. Both in silico and in vitro analyses confirmed V8-V9 captured broader taxonomic coverage than ss5ss3, though partial reference sequences and taxonomic mis-annotations biased in silico assessments. Long-reads taxonomic advantage was database-dependent, constrained by SILVA databases genus-level curation but fully realized when paired with the species-level-curated and eukaryotes-focused PR{superscript 2} (Protist Ribosomal Reference) database. Long-read sequencing uniquely identified amplicon sequence variants (ASVs) assigned to key phosphorus assimilators (Scenedesmus obliquus, Desmodesmus sp., and Acutodesmus sp.) at species level during successful phosphorus removal in a full-scale microalgal cultivation system, while V8-V9 short-read sequencing revealed ASVs assigned to algal-predatory (Leptophryidae) and bacterivorous (Choanoflagellata and Rhogostoma-lineage) protists when performance declined, suggesting grazing pressure on the phosphorus-removing community. Although both approaches performed comparably for operational monitoring, these complementary strengths support short-read sequencing for routine community profiling and long-read sequencing for detailed functional investigations of Chlorophyta.

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Dai, Z., Alam, M. M., Gincley, B., Khan, F., Kim, G.-Y., Molitor, H., Guest, J. S., Bradley, I., Pinto, A. J.. 2026-04-18. Systematic comparisons between long-read and short-read based amplicon sequencing to characterize mixed microalgal communities.. https://doi.org/10.64898/2026.04.17.719029

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