Characterization of candidate odorant-binding proteins and chemosensory proteins in the tea geometrid Ectropis obliqua Prout (Lepidoptera: Geometridae).

Insects rely heavily on their sophisticated chemosensory systems to locate host plants and find conspecific mates. Although the molecular mechanisms of odorant recognition in many Lepidoptera species have been well explored, limited information has been reported on the geometrid moth Ectropis obliqua Prout, an economically important pest of tea plants. In the current study, we first attempted to identify and characterize the putative olfactory carrier proteins, including odorant-binding proteins (OBPs) and chemosensory proteins (CSPs). By analyzing previously obtained transcriptomic data of third-instar larvae, five OBPs and 14 CSPs in E. obliqua were identified. Sequence alignment, conserved motif identification, and phylogenetic analysis suggested that candidate proteins have typical characteristics of the insect OBP or CSP family. The expression patterns regarding life stages and different tissues were determined by quantitative real-time PCR. The results revealed that four transcripts (OBP2, OBP4 and CSP8, CSP10) had larvae preferential expression profiles and nine candidate genes (PBP1, OBP1 and CSP2, CSP4, CSP5, CSP6, CSP7, CSP11, and CSP13) were adult-biased expressed. Further specific tissue expression profile evaluation showed that OBP1, OBP2, OBP4, and PBP1 were highly expressed at olfactory organs, implying their potential involvement in chemical cue detection, whereas CSPs were ubiquitously detected among all of the tested tissues and could be associated with multiple physiological functions. This study provided a foundation for understanding the physiological functions of OBPs and CSPs in E. obliqua and will help pave the way for the development of a new environmental friendly pest management strategy against the tea geometrid moth.

Detecting deep divergence in seventeen populations of tea geometrid (Ectropis obliqua Prout) in China by COI mtDNA and cross-breeding.

The tea geometrid (Ectropis obliqua Prout, Lepidoptera: Geometridae) is a dominant chewing insect endemic in most tea-growing areas in China. Recently some E. obliqua populations have been found to be resistant to the nucleopolyhedrovirus (EoNPV), a host-specific virus that has so far been found only in E. obliqua. Although the resistant populations are morphologically indistinguishable from susceptible populations, we conducted a nationwide collection and examined the genetic divergence in the COI region of the mtDNA in E. obliqua. Phylogenetic analyses of mtDNA in 17 populations revealed two divergent clades with genetic distance greater than 3.7% between clades and less than 0.7% within clades. Therefore, we suggest that E. obliqua falls into two distinct groups. Further inheritance analyses using reciprocal single-pair mating showed an abnormal F1 generation with an unbalanced sex ratio and the inability to produce fertile eggs (or any eggs) through F1 self-crossing. These data revealed a potential cryptic species complex with deep divergence and reproductive isolation within E. obliqua. Uneven distribution of the groups suggests a possible geographic effect on the divergence. Future investigations will be conducted to examine whether EoNPV selection or other factors prompted the evolution of resistance.

A Bayesian approach for sample size determination in method comparison studies.

Studies involving two methods for measuring a continuous response are regularly conducted in health sciences to evaluate agreement of a method with itself and agreement between methods. Notwithstanding their wide usage, the design of such studies, in particular, the sample size determination, has not been addressed in the literature when the goal is the simultaneous evaluation of intra- and inter-method agreement. We fill this need by developing a simulation-based Bayesian methodology for determining sample sizes in a hierarchical model framework. Unlike a frequentist approach, it takes into account uncertainty in parameter estimates. This methodology can be used with any scalar measure of agreement available in the literature. We demonstrate this for four currently used measures. The proposed method is applied to an ongoing proteomics project, where we use pilot data to determine the number of individuals and the number of replications needed to evaluate the agreement between two methods for measuring protein ratios. We also apply our method to determine the sample size for an experiment involving measurement of blood pressure.