What is in my Sample? Challenges and Approaches for Unveiling the Hidden Diversity in Plankton Samples

Abstract

The goal of this work is to deploy a primer search tool (PriSeT) suitable for taxonomically broad, sparse, and uncurated datasets of reference sequences. I discuss the theoretical and practical challenges when sequence datasets are large. Uncurated online reference databases are often the only source available when designing new primer sequences, studying the effectiveness, and for species identification. As a case study, two different identification methods for planktonic microorganisms from freshwater samples are presented: identification via light microscopy and DNA sequencing. The sequencing approach will replace the manual method to a large extent, but still needs to be improved and requires many costly trial-and-error iterations. The robust primer search tool PriSeT is here developed and designed to shorten the optimization time and to facilitate new types of in silico analyses. I evaluate PriSeT on 18S rRNA genes from all major plankton clades and on whole RNA genomes. The resulting primer sequences are compared to published primer pairs. Finally, the workflow of an academic research group planning and conducting metabarcoding experiments is critically reviewed. I present a database schema designed to summarize key information and enable researchers to be more productive in less time. The scheme also alleviates new types of meta-analysis that are not possible when data are scattered, such as quantitative and qualitative comparisons between different studies.