Genome-wide analysis of cuticle protein family genes in rice stem borer Chilo suppressalis: Insights into their role in environmental adaptation and insecticidal stress response.

Insect cuticle plays a key role in insect survival, adaptation and prosperity by serving as the exoskeleton and the first barrier against environmental stresses. As the major components of insect cuticle, the diverse structural cuticle proteins (CPs) contribute to variation in physical properties and functions of cuticle. However, the roles of CPs in cuticular versatility, especially in the stress response or adaption, remain incompletely understood. In this study, we performed a genome-wide analysis of CP superfamily in the rice-boring pest Chilosuppressalis. A total of 211 CP genes were identified and their encoding proteins were classified into eleven families and three subfamilies (RR1, RR2, and RR3). The comparative genomic analysis of CPs revealed that C. suppressalis had fewer CP genes compared to other lepidopteran species, which largely resulted from a less expansion of his-rich RR2 genes involved in cuticular sclerotization, suggesting long-term boring life of C. suppressalis inside rice hosts might evolutionarily prefer cuticular elasticity rather than cuticular sclerotization. We also investigated the response pattern of all CP genes under insecticidal stresses. >50 % CsCPs were upregulated at least 2-fold under insecticidal stresses. Notably, the majority of the highly upregulated CsCPs formed gene pairs or gene clusters on chromosomes, indicating the rapid response of adjacent CsCPs to insecticidal stress. Most high-response CsCPs encoded AAPA/V/L motifs that are related to cuticular elasticity and >50 % of the sclerotization-related his-rich RR2 genes were also upregulated. These results suggested the potential roles of CsCPs in balancing the elasticity and sclerotization of cuticles, which is essential for the survival and adaptation of plant borers including C. suppressalis. Our study provides valuable information for further developing cuticle-based strategies of both pest management and biomimetic applications.

Genome-Wide Identification, Characterization, and Expression Profile Analysis of CONSTANS-like Genes in Woodland Strawberry (Fragaria vesca).

CONSTANS-like (CO-like) gene is one of the most important regulators in the flowering process of the plant, playing a core role in the photoperiodic flowering induction pathway. In this study, we identified 10 distinct CO-like genes (FveCOs) in woodland strawberry (Fragaria vesca). They were classified into three groups with specific gene structure characteristics or protein domains in each group. The effect of selection pressure on the FveCOs in the woodland strawberry was tested by Ka/Ks, and it was shown that the evolution rate of FveCOs was controlled by purification selection factors. Intraspecific synteny analysis of woodland strawberry FveCOs showed that at least one duplication event existed in the gene family members. Collinearity analysis of woodland strawberry genome with genomes of Arabidopsis, rice (Oryza sativa), and apple (Malus × domestica) showed that CO-like genes of F. vesca and Malus × domestica owned higher similarity for their similar genomes compared with those of other two species. The FveCOs showed different tissue-specific expression patterns. Moreover, real-time quantitative PCR results revealed that the expressions of the most FveCOs followed a 24-h rhythm oscillation under both long-day (LD) and short-day (SD) conditions. Further expression analysis showed that the individual expression changing profile of FveCO3 and FveCO5 was opposite to each other under both LD and SD conditions. Moreover, the expression of FveCO3 and FveCO5 was both negatively correlated with the flowering time variation of the woodland strawberry grown under LD and SD conditions, indicating their potential vital roles in the photoperiodic flowering regulation. Further protein interaction network analysis also showed that most of the candidate interaction proteins of FveCO3 and FveCO5 were predicted to be the flowering regulators. Finally, LUC assay indicated that both FveCO3 and FveCO5 could bind to the promoter of FveFT1, the key regulator of flowering regulation in the woodland strawberry, and thus activate its expression. Taken together, this study laid a foundation for understanding the exact roles of FveCOs in the reproductive development regulation of the woodland strawberry, especially in the photoperiodic flowering process.

DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks.

Chromosome enumeration is an essential but tedious procedure in karyotyping analysis. To automate the enumeration process, we develop a chromosome enumeration framework, DeepACEv2, based on the region based object detection scheme. The framework is developed following three steps. Firstly, we take the classical ResNet-101 as the backbone and attach the Feature Pyramid Network (FPN) to the backbone. The FPN takes full advantage of the multiple level features, and we only output the level of feature map that most of the chromosomes are assigned to. Secondly, we enhance the region proposal network's ability by adding a newly proposed Hard Negative Anchors Sampling to extract unapparent but essential information about highly confusing partial chromosomes. Next, to alleviate serious occlusion problems, besides the traditional detection branch, we novelly introduce an isolated Template Module branch to extract unique embeddings of each proposal by utilizing the chromosome's geometric information. The embeddings are further incorporated into the No Maximum Suppression (NMS) procedure to improve the detection of overlapping chromosomes. Finally, we design a Truncated Normalized Repulsion Loss and add it to the loss function to avoid inaccurate localization caused by occlusion. In the newly collected 1375 metaphase images that came from a clinical laboratory, a series of ablation studies validate the effectiveness of each proposed module. Combining them, the proposed DeepACEv2 outperforms all the previous methods, yielding the Whole Correct Ratio(WCR)(%) with respect to images as 71.39, and the Average Error Ratio(AER)(%) with respect to chromosomes as about 1.17.

Nontargeted metabolomic analysis of skeletal muscle in a dehydroepiandrosterone-induced mouse model of polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is the most common endocrinopathy and an important metabolic disorder in women of reproductive age. Insulin resistance (IR) is one of its most important clinical features in patients with PCOS. Androgen excess-induced mitochondrial dysfunction contributes to skeletal muscle IR in dehydroepiandrosterone (DHEA)-induced PCOS mice. The effect of androgen excess on the skeletal muscle, however, is incompletely characterized. A nontargeted metabolomics approach was thus applied to analyze the metabolites in skeletal muscle of DHEA-induced PCOS mice. Data from metabolomic analysis revealed the significant changes in 32 metabolites and the marked impact of five metabolic pathways. ATP production was also found to be significantly reduced in skeletal muscle of DHEA mice. Combined with the quantification of type I and II myofibers and lipid measurement in the skeletal muscle of the mice, the results from the present study supported the role of mitochondrial impairment rather than lipid accumulation in the pathogenesis of skeletal muscle IR in DHEA-induced PCOS mice. In summary, we show here for the first time the profile of the metabolites in the skeletal muscle of DHEA-induced PCOS mice which exhibit IR. The work would help better understand the pathology of skeletal muscle IR in PCOS.