Morphological characteristics,developmental dynamics,and gene temporal expressions across various development stages of Aphis gossypii sexual female

Background Aphis gossypii(Hemiptera:Aphididae)is a worldwide polyphagous phloem-feeding agricultural pest,and it can produce offspring by sexual or asexual reproduction.Compared with dozens of generations by parthenogenesis,sexual reproduction is performed in only one generation within one year,and little is known about the sexual reproduction of A.gossypii.In this study,sexual females of A.gossypii were successfully obtained through a previously established induction platform,and the morphological characteristics,developmental dynamics,and temporal gene expression were examined.Subsequently,signaling pathways potentially involved in regulating the growth,development,and reproduction of sexual females were investigated.Results The morphological observation showed that from the 1st instar nymph to adult,sexual females exhibited a gradually deepened body color,an enlarged body size,longer antennae with a blackened end,and obviously protruding cauda(in adulthood).The anatomy found that the ovaries of sexual females developed rapidly from the 2^(nd)instar nymph,and the embedded oocytes matured in adulthood.In addition,time-course transcriptome analysis revealed that gene expression profiles across the development of sexual females fell into 9 clusters with distinct patterns,in which gene expression levels in clusters 1,5,and 8 peaked at the 2^(nd)instar nymphal stage with the largest number of up-regulated genes,suggesting that the 2^(nd)instar nymph was an important ovary development period.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis revealed that a large number of genes in the sexual female adult were enriched in the TGF-beta signaling pathway and Forkhead box O(FoxO)signaling pathway,highlighting their important role in sexual female adult development and reproduction.Conclusion The morphological changes of the sexual female at each developmental stage were revealed for the first time.In addition,time-course transcriptomic analyses suggest genes enriched in the TGF-beta signaling pathway and FoxO signaling pathway probably contribute to regulating the development and oocyte maturation of sexual females.Overall,these findings will facilitate the regulating mechanism research in the growth and development of sexual females by providing candidate genes.

Evolutionary dynamics of the Wnt gene family:implications for lophotrochozoans

Genes encoding Wnt ligands, which have important roles in cell communication and organ development, are restricted to multicellular animals. We systematically studied W nt genes from eumetazoan genomes, with emphasis on the poorly studied superphylum Lophotrochozoa(four annelids, seven mollusks, eight platyhelminths, one bdelloid rotifer, and one brachiopod species). Between 3 and 39 W nt loci were identified in each genome, and the protostome-specific loss of Wnt3 genes was confirmed. We identified gastropod-specific loss of Wnt8, refining the previously proposed mollusk-specific loss. Some duplicated Wnt genes belonging to a same subfamily or closely related subfamilies showed tandem distribution in the lophotrochozoan genomes, indicating tandem duplication events during Wnt family evolution. Members of the conserved Wnt10-Wnt6-Wnt1-Wnt9 cluster showed highly correlated expression patterns over time in two assayed lophotrochozoans, the oyster C rassostrea gigas and the brachiopod L ingula anatina, reflecting the possible similar function of the clustered W nt genes.

Computing a Predictor Set Influence Zone through a Multi-Layer Genetic Network to Explore the Role of Estrogen in Breast Cancer

Modeling inter-relationships of genes over a specific genetic network is one of the most challenging studies in systems biology. Among the families of models proposed one commonly used is the discrete stochastic, based on conditionally independent Markov chains. In practice, this model is estimated from time sequential sampling, usually obtained by microarray experiments. In order to improve the accuracy of the estimation method, we can use biological knowledge. In this paper, we decided to apply this idea to study the role of estrogen in breast cancer proliferation. The n-influence zone of a set S of genes in a given multi-layer genetic network is a set L of genes regulated, directly or indirectly, by genes in S, after at most n-1 layers. In this manuscript we describe a new approach for computing the n-influence zone of S through the estimation of a multi-layer genetic network from gene expression time series, measured by microarrays, and biological knowledge. Using seed genes related to cell proliferation, our method was able to add to the third layer of the network other genes related to this biological function and validated in the literature. Using a set of genes directly influenced by estrogen, we could find a new role for cell adhesion genes estrogen dependent. Our pipeline is user-friendly and does not have high system requirements. We believe this paper could contribute to improve the data mining for biologists in microarray time series.

Characterization and modeling of supercritical CO_(2) pulse pressures:Effects of activator mass and discharge plate thickness

Utilizing a bespoke CO_(2) phase transition pulse pressure experimental system,we conducted pulse pressure characterization tests across various activator masses,CO_(2) filling pressures,and energy discharge plate thick-nesses.This approach enabled us to ascertain the pulse pressure's response characteristics and variation patterns under diverse conditions.The formula for calculating the peak supercritical CO_(2) pulse pressure was deduced by modeling the ultimate load calculation of the clamped circular plate,and then the time-course expression of the supercritical CO_(2) phase transition pulse pressure and energy was carried out by introducing the time factor and taking into account the parameters of the activator mass and the thickness of the energy discharging plate.Our findings reveal a four-stage pressure evolution in the cracking tube during initiation:a gradual increase,a rapid spike,swift attenuation,and eventual negative pressure formation.The activator mass and discharge plate thickness critically influence the peak pressure's timing and magnitude.Specifically,increased activator mass hastens peak pressure onset,while a thicker discharge plate amplifies it.The errors between calculated and experimental values for peak supercritical CO_(2) phase transition pressure fall within5%–5%.Furthermore,the pressure peak and arrival time model demonstrates less than 10%error compared to experimental data,affirming its strong applicability.These insights offer theoretical guidance for controlling phase transition pressure and optimizing energy in supercritical CO_(2) systems.

Network-Based Predictions and Simulations by Biological State Space Models: Search for Drug Mode of Action

Since time-course microarrav data are short but contain a large number of genes, most of statistical models should be extended so that they can handle such statistically irregular situations. We introduce biological state space models that are established as suitable computational models for constructing gene networks from microarray gene expression data. This chapter elucidates theory and methodology of our biological state space models together with some representative analyses including discovery of drug mode of action. Through the applications we show the whole strategy of biological state space model analysis involving experimental design of time-course data, model building and analysis of the estimated networks.