Polydnavirus genomes reflect their dual roles as mutualists and pathogens.

Symbionts often exhibit significant reductions in genome complexity while pathogens often exhibit increased complexity through acquisition and diversification of virulence determinants. A few organisms have evolved complex life cycles in which they interact as symbionts with one host and pathogens with another. How the predicted and opposing influences of symbiosis and pathogenesis affect genome evolution in such instances, however, is unclear. The Polydnaviridae is a family of double-stranded (ds) DNA viruses associated with parasitoid wasps that parasitize other insects. Polydnaviruses (PDVs) only replicate in wasps but infect and cause severe disease in parasitized hosts. This disease is essential for survival of the parasitoid's offspring. Thus, a true mutualism exists between PDVs and wasps as viral transmission depends on parasitoid survival and parasitoid survival depends on viral infection of the wasp's host. To investigate how life cycle and ancestry affect PDVs, we compared the genomes of Campoletis sonorensis ichnovirus (CsIV) and Microplitis demolitor bracovirus (MdBV). CsIV and MdBV have no direct common ancestor, yet their encapsidated genomes share several features including segmentation, diversification of virulence genes into families, and the absence of genes required for replication. In contrast, CsIV and MdBV share few genes expressed in parasitized hosts. We conclude that the similar organizational features of PDV genomes reflect their shared life cycle but that PDVs associated with ichneumonid and braconid wasps have likely evolved different strategies to cause disease in the wasp's host and promote parasitoid survival.

Validation study of the TrueAllele automated data review system.

The New York State Convicted Offender DNA Databank is the first U.S. lab to complete an internal validation of the TrueAllele expert data review system. TrueAllele is designed to assess short tandem repeat (STR) DNA data based on several key features such as peak height, shape, area, and position relative to a standard ladder and use this information to make accurate allele calls. The software then prioritizes the allele calls based on several user-defined rules. As a result, the user need only review low-quality data. The validation of this system consisted of an extensive optimization phase and a large concordance phase. During optimization, the rule settings were tailored to minimize the amount of high-quality data viewed by the user. In the concordance phase, a large dataset was typed in parallel with the ABI software Gene Scan and Genotyper (manual review) and TrueAllele (automated review) for comparison of allele calls and sample state assignment. Only one significant difference was discovered out of 2048 samples in the concordance study. In this case, TrueAllele revealed a spike in the profile that was interpreted as a DNA peak by the analyst in Genotyper. TrueAllele was designed to focus the review on poor data and to eliminate the need for complete reanalysis technical review. This validation project proved TrueAllele to be dependable for use at the NYS Convicted Offender DNA Databank.