This study presents a new computer program for assessing the effects of different factors and sequencing strategies on de novo sequence assembly. The program uses reads from actual sequencing studies or from simulations with a reference genome that may also be real or simulated. The simulated reads can be created with our read simulator. They can be of differing length and coverage, consist of paired reads with varying distance, and include sequencing errors such as color space miscalls to imitate SOLiD data. The simulated or real reads are mapped to their reference genome and our assembly simulator is then used to obtain optimal assemblies that are limited only by the distribution of repeats. By way of this mapping, the assembly simulator determines which contigs are theoretically possible, or conversely (and perhaps more importantly), which are not. We illustrate the application and utility of our new simulation tools with several experiments that test the effects of genome complexity (repeats), read length and coverage, word size in De Bruijn graph assembly, and alternative sequencing strategies (e.g., BAC pooling) on sequence assemblies. These experiments highlight just some of the uses of our simulators in the experimental design of sequencing projects and in the further development of assembly algorithms.

Sponges are an ancient metazoan group with broad ecological, evolutionary, and biotechnological importance. As in other marine invertebrates with a biphasic life cycle, the developing sponge undergoes a significant morphological, physiological, and ecological transformation during settlement and metamorphosis. In this study, we compare new transcriptome datasets for three life cycle stages of the red sponge (Mycale phyllophila) to test whether gene expression (as in the model poriferan, Amphimedon queenslandica) also varies more after settlement and metamorphosis. In contrast to A. queenslandica, we find that the transcriptome of M. phyllophila changes more during the earlier pre-competent larva/post-larva transition that spans these defining events. We also find that this transition is marked by a greater frequency of significantly up-regulated Gene Ontology terms including those for morphogenesis, differentiation, and development and that the transcriptomes of its pre-competent larvae and adult are distinct. The life cycle transcriptome variation between M. phyllophila and A. queenslandica may be due to their long separate evolutionary histories and corresponding differences in developmental rates and timing. This study now calls for new transcriptome datasets of M. phyllophila and other sponges, which will allow for tests of the generality of our life cycle expression differences and for the greater exploitation of poriferans in both basic and applied research.

The population mutation rate (θ) remains one of the most fundamental parameters in genetics, ecology, and evolutionary biology. However, its accurate estimation can be seriously compromised when working with error prone data such as expressed sequence tags, low coverage draft sequences, and other such unfinished products. This study is premised on the simple idea that a random sequence error due to a chance accident during data collection or recording will be distributed within a population dataset as a singleton (i.e., as a polymorphic site where one sampled sequence exhibits a unique base relative to the common nucleotide of the others). Thus, one can avoid these random errors by ignoring the singletons within a dataset.