Resolving the microalgal gene landscape at the strain level: A novel hybrid transcriptome of Emiliania huxleyi CCMP3266

Microalgae are key ecological players with a complex evolutionary history. Genomic diversity, in addition to limited availability of high-quality genomes, challenge studies that aim to elucidate molecular mechanisms underlying microalgal ecophysiology. Here, we present a novel and comprehensive transcriptomic hybrid approach to generate a reference for genetic analyses, and resolve the microalgal gene landscape at the strain level. The approach is demonstrated for a strain of the coccolithophore microalga Emiliania huxleyi , which is a species complex with considerable genome variability. The investigated strain is commonly studied as a model for algal-bacterial interactions, and was therefore sequenced in the presence of bacteria to elicit the expression of interaction-relevant genes. We applied complementary PacBio Iso-Seq full-length cDNA, and poly(A)-independent Illumina total RNA sequencing, which resulted in a de novo assembled, near complete hybrid transcriptome. In particular, hybrid sequencing improved the reconstruction of long transcripts and increased the recovery of full-length transcript isoforms. To use the resulting hybrid transcriptome as a reference for genetic analyses, we demonstrate a method that collapses the transcriptome into a genome-like dataset, termed “synthetic genome” (sGenome). We used the sGenome as a reference to visually confirm the robustness of the CCMP3266 gene assembly, to conduct differential gene expression analysis, and to characterize novel E. huxleyi genes. The newly-identified genes contribute to our understanding of E. huxleyi genome diversification, and are predicted to play a role in microbial interactions. Our transcriptomic toolkit can be implemented in various microalgae to facilitate mechanistic studies on microalgal diversity and ecology. Importance Microalgae are key players in the ecology and biogeochemistry of our oceans. Efforts to implement genomic and transcriptomic tools in laboratory studies involving microalgae suffer from the lack of published genomes. In the case of coccolithophore microalgae, the problem has long been recognized; the model species Emiliania huxleyi is a species complex with genomes composed of a core, and a large variable portion. To study the role of the variable portion in niche adaptation, and specifically in microbial interactions, strain-specific genetic information is required. Here we present a novel transcriptomic hybrid approach, and generated strain-specific genome-like information. We demonstrate our approach on an E. huxleyi strain that is co-cultivated with bacteria. By constructing a “synthetic genome”, we generated comprehensive gene annotations that enabled accurate analyses of gene expression patterns. Importantly, we unveiled novel genes in the variable portion of E. huxleyi that play putative roles in microbial interactions.