Distinguishing Species Using GC Contents in Mixed DNA or RNA Sequences.

With the advent of whole transcriptome and genome analysis methods, classifying samples containing multiple origins has become a significant task. Nucleotide sequences can be allocated to a genome or transcriptome by aligning sequences to multiple target sequence sets, but this approach requires extensive computational resources and also depends on target sequence sets lacking contaminants, which is often not the case. Here, we demonstrate that raw sequences can be rapidly sorted into groups, in practice corresponding to genera, by exploiting differences in nucleotide GC content. To do so, we introduce GCSpeciesSorter, which uses classification, specifically Support Vector Machines (SVM) and the C4.5 decision tree generator, to differentiate sequences. It also implements a secondary BLAST feature to identify known outliers. In the test case presented, a hermatypic coral holobiont, the cnidarian host includes various endosymbionts. The best characterized and most common of these symbionts are zooxanthellae of the genus Symbiodinium. GCSpeciesSorter separates cnidarian from Symbiodinium sequences with a high degree of accuracy. We show that if the GC contents of the species differ enough, this method can be used to accurately distinguish the sequences of different species when using high-throughput sequencing technologies.

De novo assembly and annotation of the Acropora gemmifera transcriptome.

Stony corals from the genus Acropora are widely distributed, important reef-builders and have become increasingly utilized for investigating links between genetics and spawning behaviour. We assembled and annotated a composite transcriptome from Acropora gemmifera using Illumina HiSeq2500 analysis of two libraries from different lunar and solar phases to identify genes that have potential functional roles in reproductive-related traits. A total of 31.6 million combined raw reads were assembled using Trinity and built into 104,000 contigs. Functional gene annotation was performed using dammit, Gene Ontology (GO), KOG (WebMGA) and KEGG pathway analyses (Kaas). This resource will be valuable for researchers studying gene expression patterns in coral reproductive cycles and evolution of the genus Acropora.

Transcriptome dynamics over a lunar month in a broadcast spawning acroporid coral.

On one night per year, at a specific point in the lunar cycle, one of the most extraordinary reproductive events on the planet unfolds as hundreds of millions of broadcast spawning corals release their trillions of gametes into the waters of the tropical seas. Each species spawns on a specific night within the lunar cycle, typically from full moon to third quarter moon, and in a specific time window after sunset. This accuracy is essential to achieve efficient fertilization in the vastness of the oceans. In this report, we use transcriptome sequencing at noon and midnight across an entire lunar cycle to explore how acroporid corals interpret lunar signals. The data were interrogated by both time-of-day-dependent and time-of-day-independent methods to identify different types of lunar cycles. Time-of-day methods found that genes associated with biological clocks and circadian processes change their diurnal cycles over the course of a synodic lunar cycle. Some genes have large differences between day and night at some lunar phases, but little or no diurnal differences at other phases. Many clock genes display an oscillation pattern indicative of phase shifts linked to the lunar cycle. Time-independent methods found that signal transduction, protein secretion and modification, cell cycle and ion transport change over the lunar timescale and peak at various phases of the moon. Together these data provide unique insights into how the moon impinges on coral transcription cycles and how lunar light may regulate circalunar timing systems and coral biology.