The authors assembled a comprehensive transcriptome of the scleractinian coral Porites astreoides that encompasses three developmental stages including swimming larvae, settling larvae and adults. The RNA from these developmental stages and the corresponding libraries appear to have been processed and sequenced separately. All sequences generated from these individual libraries were pooled to generate a single transcriptome with >800,000 transcripts, of which ~25% had a hit against known proteins in the SWISS-PROT database.

At the moment of writing, I was not able to download the transcriptome and corresponding annotation to further investigate the quality of the assembly and annotation. However, based on the use of different developmental stages and the amount of sequencing it can be expected that this transcriptome is an improvement to the currently available P. astroides transcriptome from Kenkel et al. (2013). However, a few things should be changed/added and the transcriptome and annotation should be accessible before publication.

1. The number of transcripts is overwhelmingly high and the authors do not provide any information regarding the number of cluster/unigenes. Trinity already clusters isoforms to potential gene units based on sequence similarity. Also, different clustering approaches can be used (e.g. CD-HIT) to further structure the transcriptome and minimize annotation time by only annotating the longest or highest expressed transcript of each cluster.

2. Due to the use of adult samples and an extensive amount of data, it can be assumed that the transcriptome contains contamination from associated microbes, most notably from Symbiodinium. There are several Symbiodinium genome and transcriptome data sets available to at least remove part of symbiont derived contamination.

3. The transcripts were only annotated against the SWISS-PROT database, which provided functional information for <25% of the transcripts. This substantially less than what is observed for other coral transcriptomes. Furthermore, the chosen cut-off (e-3) is quite weak. I would suggest re-annotating transcripts against TrEMBL and nr with a cut-off of e-5 or lower. To minimize computational time I suggest using the previously mentioned clustering approach and annotating only one representative transcript per cluster.

As previously mentioned this is not the first P. astreoides transcriptome and, although not absolutely necessary, it would have been quite informative to compare the two transcriptomes in order to assess the quality of the assembly and the additional information provided by the inclusion of the larval stages. Similarly, it would have been much more helpful to assemble the data separately in order to provide stage specific transcriptomes to the community but I assume the authors intend to publish this information in a separate paper.

Finally I suggest changing the line %GC in table one to 44 instead of 0.44.

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