Microsatellite Loci Reveal Genetic Diversity of Asian Callery Pear (Pyrus calleryana) in the Species Native Range and in the North American Cultivars.

Pyrus calleryana Decne. (Callery pear) includes cultivars that in the United States are popular ornamentals in commercial and residential landscapes. Last few decades, this species has increasingly naturalized across portions of the eastern and southern US. However, the mechanisms behind this plant's spread are not well understood. The genetic relationship of present-day P.calleryana trees with their Asian P. calleryana forebears (native trees from China, Japan, and Korea) and the original specimens of US cultivars are unknown. We developed and used 18 microsatellite markers to analyze 147 Pyrus source samples and to articulate the status of genetic diversity within Asian P. calleryana and US cultivars. We hypothesized that Asian P. calleryana specimens and US cultivars would be genetically diverse and would show genetic relatedness. Our data revealed high genetic diversity, high gene flow, and presence of population structure in P. calleryana, potentially relating to the highly invasive capability of this species. Strong evidence for genetic relatedness between Asian P. calleryana specimens and US cultivars was also demonstrated. Our data suggest the source for P. calleryana that have become naturalized in US was China. These results will help understand the genetic complexity of invasive P. calleryana when developing management for escaped populations: In follow-up studies, we use the gSSRs developed here to analyze P. calleryana escape populations from across US.

ngsComposer: an automated pipeline for empirically based NGS data quality filtering.

Next-generation sequencing (NGS) enables massively parallel acquisition of large-scale omics data; however, objective data quality filtering parameters are lacking. Although a useful metric, evidence reveals that platform-generated Phred values overestimate per-base quality scores. We have developed novel and empirically based algorithms that streamline NGS data quality filtering. The pipeline leverages known sequence motifs to enable empirical estimation of error rates, detection of erroneous base calls and removal of contaminating adapter sequence. The performance of motif-based error detection and quality filtering were further validated with read compression rates as an unbiased metric. Elevated error rates at read ends, where known motifs lie, tracked with propagation of erroneous base calls. Barcode swapping, an inherent problem with pooled libraries, was also effectively mitigated. The ngsComposer pipeline is suitable for various NGS protocols and platforms due to the universal concepts on which the algorithms are based.

Immunogene and viral transcript dynamics during parasitic Varroa destructor mite infection of developing honey bee (Apis mellifera) pupae.

The ectoparasitic Varroa destructor mite is a major contributor to the ongoing honey bee health crisis. Varroa interacts with honey bee viruses, exacerbating their pathogenicity. In addition to vectoring viruses, immunosuppression of the developing honey bee hosts by Varroa has been proposed to explain the synergy between viruses and mites. However, the evidence for honey bee immune suppression by V. destructor is contentious. We systematically studied the quantitative effects of experimentally introduced V. destructor mites on immune gene expression at five specific time points during the development of the honey bee hosts. Mites reproduced normally and were associated with increased titers of deformed wing virus in the developing bees. Our data on different immune genes show little evidence for immunosuppression of honey bees by V. destructor. Experimental wounding of developing bees increases relative immune gene expression and deformed wing virus titers. Combined, these results suggest that mite feeding activity itself and not immunosuppression may contribute to the synergy between viruses and mites. However, our results also suggest that increased expression of honey bee immune genes decreases mite reproductive success, which may be explored to enhance mite control strategies. Finally, our expression data for multiple immune genes across developmental time and different experimental treatments indicates co-regulation of several of these genes and thus improves our understanding of the understudied honey bee immune system.