Transcriptome characterisation and simple sequence repeat marker discovery in the seagrass Posidonia oceanica

Abstract

Posidonia oceanica is an endemic seagrass in the Mediterranean Sea, where it provides important ecosystem services and sustains a rich and diverse ecosystem. P. oceanica meadows extend from the surface to 40 meters depth. With the aim of boosting research in this iconic species, we generated a comprehensive RNA-Seq data set for P. oceanica by sequencing specimens collected at two depths and two times during the day. With this approach we attempted to capture the transcriptional diversity associated with change in light and other depth-related environmental factors. Using this extensive data set we generated gene predictions and identified an extensive catalogue of potential Simple Sequence Repeats (SSR) markers. The data generated here will open new avenues for the analysis of population genetic features and functional variation in P. oceanica. In total, 79,235 contigs were obtained by the assembly of 70,453,120 paired end reads. 43,711 contigs were successfully annotated. A total of 17,436 SSR were identified within 13,912 contigs.

Figure 1. Effect of contigs length on the percentage of BLAST hits against NR protein database.

The red bars indicate the length distribution of the contigs, the green bars indicate the number of contigs with a blast hit.

Figure 2. Characteristics of homology search of contigs against the NR protein database.

(a) E-value distribution of the top BLAST hits for each contig (E-value ≤1.0e-5). (b) Hit species distribution.

Figure 3. COG functional classification of the Posidonia oceanica transcriptome.

Figure 4. Venn diagram showing distribution of similarity search results.

(a) BLAST results against NCBI NR protein database, Zostera marina proteins, Elaeis guineensis proteins, Phoenix dactylifera proteins and Vitis vinifera proteins. (b) Annotation from InterPro and COGs. (c) Summary of the annotation obtained in a and b.

Figure 5. Histogram presentation of Gene Ontology classification.

The results are summarized in three main categories: biological process, cellular component and molecular function. The right and left y-axis indicates the number and the percentage of contigs in a sub-category, respectively.