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Abstract Background Juvenile hormones (JH) play crucial role in regulating development and reproduction in insects. The most common form of JH is JH III, derived from MF through epoxidation by CYP15 enzymes. However, in the higher dipterans, such as the fruitfly, Drosophila melanogaster, a bis-epoxide form of JHB3, accounted most of the JH detected. Moreover, these higher dipterans have lost the CYP15 gene from their genomes. As a result, the identity of the P450 epoxidase in the JH biosynthesis pathway in higher dipterans remains unknown. Results In this study, we show that Cyp6g2 serves as the major JH epoxidase responsible for the biosynthesis of JHB3 and JH III in D. melanogaster. The Cyp6g2 is predominantly expressed in the corpus allatum (CA), concurring with the expression pattern of jhamt, another well-studied gene that is crucial in the last steps of JH biosynthesis. Mutation in Cyp6g2 leads to severe disruptions in larval-pupal metamorphosis and exhibits reproductive deficiencies, exceeding those seen in jhamt mutants. Notably, Cyp6g2 −/− ::jhamt 2 double mutants all died at the pupal stage but could be rescued through the topical application of JH analogs. JH titer analyses revealed that both Cyp6g2 −/− mutant and jhamt 2 mutant lacking JHB3 and JH III, while overexpression of Cyp6g2 or jhamt caused a significant increase in JHB3 and JH III titer. Conclusions These findings collectively established that Cyp6g2 as the major JH epoxidase in the higher dipterans and laid the groundwork for the further understanding of JH biosynthesis. Moreover, these findings pave the way for developing specific Cyp6g2 inhibitors as insect growth regulators or insecticides.

Wings are an important flight organ of insects. Wing development is a complex process controlled by a series of genes. The flightless wing pad transforms into a mature wing with the function of migratory flight during the nymph-to-adult metamorphosis. However, the mechanism of wing morphogenesis in locusts is still unclear. This study analyzed the microstructures of the locust wing pads at pre-eclosion and the wings after eclosion and performed the comparative transcriptome analysis. RNA-seq identified 25,334 unigenes and 3,430 differentially expressed genes (DEGs) (1,907 up-regulated and 1,523 down-regulated). The DEGs mainly included cuticle development (LmACPs), chitin metabolism (LmIdgf4), lipid metabolism-related genes, cell adhesion (Integrin), zinc finger transcription factors (LmSalm, LmZF593 and LmZF521), and others. Functional analysis based on RNA interference and hematoxylin and eosin (H&E) staining showed that the three genes encoded zinc finger transcription factors are essential for forming wing cuticle and maintaining morphology in Locusta migratoria. Finally, the study found that the LmSalm regulates the expression of LmACPs in the wing pads at pre-eclosion, and LmZF593 and LmZF521 regulate the expression of LmIntegrin/LmIdgf4/LmHMT420 in the wings after eclosion. This study revealed that the molecular regulatory axis controls wing morphology in nymphal and adult stages of locusts, offering a theoretical basis for the study of wing development mechanisms in hemimetabolous insects.

Deep learning methods are widely used in building information extraction from remote sensing images (RSIs). However, this task still faces great challenges. First, it is difficult to perform accurate boundary localization due to the complex contextual relationship of the building boundary area. Second, the heterogeneity caused by different materials on building tops, as well as environmental factors such as climate and vegetation, complicates the extraction of top information. Finally, given the complexity of the RSIs, the accuracy and generalization of the existing method still need to be further enhanced. This study introduces the boundary enhancement and multiscale refinement fusion network to overcome these challenges. The boundary-aware self-attention module is initially proposed to refine the network's boundary detection capabilities. It applies the distance transform algorithm across both channel and spatial dimensions, reducing boundary fluctuation and enhancing the accuracy of building boundary extraction. Subsequently, we present the multiscale refined fusion module to resolve discontinuities within buildings caused by rooftop obstructions. This module effectively merges high and low-level features, overcoming information gaps through the strategic integration of multiscale data. To demonstrate the efficacy of our methodology, we conducted comprehensive experiments and analyses using the WHU Building Dataset and the Inria Aerial Image Labeling Dataset, both known for their complexity. Our method surpassed 16 contemporary state-of-the-art techniques, achieving IoU scores of 91.15% and 79.52% for each dataset, respectively, marking the highest accuracy levels reported. Furthermore, in-depth discussions on efficiency, generalizability, and ablation studies emphasized our method's robustness and adaptability.

Summary: The mystery of appendage regeneration has fascinated humans for centuries, while the underlying regulatory mechanisms remain unclear. In this study, we establish a transcriptional landscape of regenerating leg in the American cockroach, Periplaneta americana, an ideal model in appendage regeneration studies showing remarkable regeneration capacity. Through a large-scale in vivo screening, we identify multiple signaling pathways and transcription factors controlling leg regeneration. Specifically, zfh-2 and bowl contribute to blastema cell proliferation and morphogenesis in two transcriptional cascades: bone morphogenetic protein (BMP)/JAK-STAT-zfh-2-B-H2 and Notch-drm/bowl-bab1. Notably, we find zfh-2 is working as a direct target of BMP signaling to promote cell proliferation in the blastema. These mechanisms might be conserved in the appendage regeneration of vertebrates from an evolutionary perspective. Overall, our findings reveal that two crucial transcriptional cascades orchestrate distinct cockroach leg regeneration processes, significantly advancing the comprehension of molecular mechanism in appendage regeneration.

Abstract With the population projections indicating continued growth during this century, construction of large dams can be considered as one of the best available options to meet the future increases in water, food, and energy demands. While there are reports that thousands of large dams will be built in the near future, a key question is: what are the appropriate conditions for selecting the sites for these dams? The site of a large dam should be carefully evaluated based on many factors, such as socioeconomic development, water resources availability, topographic characteristics, and environmental impacts. This study aims to partly address the above question through identifying the relationship between two topographic characteristics (i.e., catchment area and slope) of a river reach to build a large dam based on the 30-m-resolution global drainage networks. The information about 2815 existing large dams from the Global Reservoir and Dam (GRanD) database is collected for analysis. The confidence ellipse approach is introduced to establish the quantitative relationship between these two variables, which is then used to evaluate the site selection of a large dam from the perspective of topographic characteristics. The results show that: (1) each large dam can well correspond to the nearest river reach in the global drainage networks and (2) the logarithmic values of catchment area and slope can be well described by a confidence ellipse, which is obtained based on the means, standard deviations, and Pearson correlation coefficients of the two variables. The outcomes of this study will be of great value for policymakers to have a more comprehensive understanding of large dam development in future.

Post-harvest handling and ripening techniques have an impact on peach quality and shelf life, which has a big impact on consumer satisfaction and market competitiveness. This review paper examines recent advancements in ripening techniques and post-harvest technologies with the goal of improving peach fruit quality and sustainability. The factors impacting fruit quality after harvest and the physiological changes that occur throughout peach ripening are fully explained. For maintaining peach freshness and reducing losses, novel handling methods like modified atmosphere packaging (MAP) and controlled atmosphere storage (CAS) have been investigated. The study explores the possibilities of nanotechnology applications and low-temperature storage for prolonging shelf life while maintaining texture, flavor, and aroma. This study further analyzes the effectiveness and waste reduction potential of automation and mechanization in post-harvest activities. The paper also discusses ethylene-based and non-ethylene-based ripening agents, as well as innovative techniques including gene editing and RNAi technology for controlled and delayed ripening. Analyses are performed on how these technologies affect the sensory qualities and nutrient profiles of peaches. The study emphasizes the significance of sustainable practices in the peach industry by focusing on waste reduction, resource efficiency, and circular economy integration. Post-harvest technologies’ potential environmental consequences are taken into consideration, and the paper encourages more studies and cooperation to increase sustainability.

Extreme rainfall can be affected by various climatic factors such as the large-scale climate patterns (LCPs). Understanding the changing LCPs can improve the accuracy of extreme rainfall prediction. This study explores the variation trend of extreme rainfall in the middle and lower reaches of the Yangtze River Basin (MLRYRB) and the telecorrelation with four LCPs, namely WPSHI (Western Pacific Subtropical High Index), EAMI (East Asia Monsoon Index), ENSO (El Niño-Southern Oscillation) and PDO (Pacific Decadal Oscillation), through modified Mann-Kendall (MMK) analysis, Pearson correlation coefficient, wavelet coherence analysis (WTC) and improved partial wavelet analysis (PWC). Previous studies have ignored the interdependence between these climate indices when analyzing their effects on precipitation. This study introduces the improved PWC, which can remove the correlations between them and reveal the influence of a single LCP. The results show that: 1) extreme rainfall in the MLRYRB has an obvious increasing trend and has a significant correlation with the LCPs; 2) the LCPs have a significant cyclical relationship with extreme rainfall, which can be significantly affected by the intergenerational variation of the LCPs; and 3) the improved PWC can accurately reveal the influence of a single LCP. EAMI is the main influencing factor in the 1-year cycle, while WPSHI is the main influencing factor in the 5-year cycle. ENSO and PDO can always influence extreme rainfall by coupling WPSHI or EAMI.

The frequent occurrence of drought events in recent years has caused significant changes in plant biodiversity. Understanding vegetation dynamics and their responses to climate change is of great significance to reveal the behaviour mechanism of terrestrial ecosystems. In this study, NDVI and SIF were used to evaluate the dynamic changes of vegetation in the Pearl River Basin (PRB). The relationship between vegetation and meteorological drought in the PRB was evaluated from both linear and nonlinear perspectives, and the difference of vegetation response to meteorological drought in different land types was revealed. Cross wavelet analysis was used to explore the teleconnection factors (e.g., large-scale climate patterns and solar activity) that may affect the relationship between meteorological drought and vegetation dynamics. The results show that 1) from 2001 to 2019, the vegetation cover and photosynthetic capacity of the PRB both showed increasing trends, with changing rates of 0.055/10a and 0.036/10a, respectively; 2) compared with NDVI, the relationship between SIF and meteorological drought was closer; 3) the vegetation response time (VRT) obtained based on NDVI was mainly 4–5 months, which was slightly longer than that based on SIF (mainly 3–4 months); 4) the VRT of woody vegetation (mainly 3–4 months) was longer than that of herbaceous vegetation (mainly 4–5 months); and 5) vegetation had significant positive correlations with the El Niño Southern Oscillation (ENSO) and sunspots but a significant negative correlation with the Pacific Decadal Oscillation (PDO). Compared with sunspots, the ENSO and the PDO were more closely related to the response relationship between meteorological drought and vegetation. The outcomes of this study can help reveal the relationship between vegetation dynamics and climate change under the background of global warming and provide a new perspective for studying the relationship between drought and vegetation.

Abstract This study focuses on the evolution of flood risk in the Yangtze River Basin under climate change, which is a critical issue for socioeconomic development in future. In this study, we (1) compared the 1998 and 2020 floods and found that the destructiveness of a given discharge is now greater than before; (2) revealed three issues related to the above finding; and (3) prospected the future development of up-to-date technologies to better address the issue that floods with high water levels will frequently threaten us. The outcomes of this study would be of great significance to future flood control operation of large river basins.

Juvenile hormone (JH) regulates insect development and reproduction through both intracellular and membrane signaling, and the two pathways might crosstalk with each other. Recent studies have reported that JH membrane signaling induces phosphorylation of the JH intracellular receptor Met, thus enhancing its transcriptional activity. To gain more insights into JH-induced Met phosphorylation, we here performed phosphoproteomics to identify potential phosphorylation sites of Met and its paralog Germ-cell expressed (Gce) in Drosophila Kc cells. In vitro experiments demonstrate that JH-induced phosphorylation sites in the basic helix-loop-helix (bHLH) domain, but not in the Per-Arnt-Sim-B (PAS-B) domain, are required for maximization of Met transcriptional activity. Moreover, phosphoproteomics analysis reveale that JH also induces the phosphorylation of Hsp83, a chaperone protein involved in JH-activated Met nuclear import. The JH-induced Hsp83 phosphorylation at S219 facilitates Hsp83-Met binding, thus promoting Met nuclear import and its transcription. By using proteomics, subcellular distribution, and co-immunoprecipitation approaches, we further characterized 14-3-3 proteins as negative regulators of Met nuclear import through physical interaction with Hsp83. These results show that JH membrane signaling induces phosphorylation of the key components in JH intracellular signaling, such as Met and Hsp83, and consequently facilitating JH intracellular signaling.

In the field of insect endocrinology, juvenile hormone (JH) is one of the most wondrous entomological terms. As a unique sesquiterpenoid hormone produced and released by the endocrine gland, corpus allatum (CA), JH is a critical regulator in multiple developmental and physiological processes, such as metamorphosis, reproduction, and behavior. Benefited from the precise genetic interventions and simplicity, the fruit fly, Drosophila melanogaster, is an indispensable model in JH studies. This review is aimed to present the regulatory factors on JH biosynthesis and an overview of the regulatory roles of JH in Drosophila. The future directions of JH studies are also discussed, and a few hot spots are highlighted.

Climate change and land use/cover change (LUCC) have been widely recognized as the main driving forces that can affect regional hydrological processes, and quantitative assessment of their impacts is of great importance for the sustainable development of regional ecosystems, land use planning and water resources management. This study investigates the impacts of climate change and LUCC on variables such as streamflow (SF), soil moisture (SM) and evapotranspiration (ET) in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) by using Soil and Water Assessment Tools (SWAT) model under different scenarios during 1979–2018. The results show that the simulation performances were overall good, with Nash-Sutcliffe Efficiency Coefficient (NSE) and coefficient of determination (R2) greater than 0.80 for the monthly-scale SF calibration and validation. According to the results of trend and change point tests of meteorological series, the baseline period (1979–1997) and the interference period (1998–2018) were determined. Interestingly, other land use types were basically converted to urban land, leading to a rapid urbanization in the GBA. Compared with the SF values of the eight estuaries of the Pearl River Basin in the baseline period, both climate change and LUCC has led to the decrease in the SF values in the interference period, and the combined effect of climate change and LUCC was slightly greater than their individual effect. Overall, climate change and LUCC both have important impacts on regional hydrological processes in the GBA.

Correlation analysis is the common method to evaluate the relationship between two variables; however, it may sometimes cause spurious correlations. Specifically, in the field of hydrometeorology, with the impacts of climate change and human activities, correlation analysis is difficult to identify the true relationship between variables, and thus, causality analysis should be adopted instead. This study analyzed the causal relationship between meteorological drought and hydrological drought in different climatic regions of China by using convergent cross mapping (CCM). We improved the identification of CCM convergence by using the coefficient of variation and applied it in the field of large-scale hydrometeorology. The results of correlation analysis were compared, and the applicability of causality analysis was explored. The results revealed that: In Southeast China, the correlation and causality between meteorological drought and hydrological drought were both large. In Northeast China and central Qinghai–Tibet Plateau, the correlation between meteorological drought and hydrological drought was small, but the causality was large. In view of the spurious correlation, introducing causality analysis can better explain the relationship between meteorological drought and hydrological drought, especially in areas with snowmelt runoff. Overall, CCM can provide valuable causal information from common time series in the field of large-scale hydrometeorology and has a wide range of application values. However, causality analysis cannot explain the positive or negative relationship between variables. Therefore, when analyzing the relationship between variables, the advantages of the two methods should be given full play.

Study region: Central eastern continental United States. Study focus: Groundwater level prediction is of great significance for the management of global water resources. Recently, machine learning, which can deal with highly nonlinear interactions among complex hydrological factors, has been widely applied to groundwater level prediction. However, previous studies mainly focused on improving the simulation performance in specific regions using different machine learning methods, while this study focused on the impacts of regional characteristics on improving the accuracy of groundwater level prediction using machine learning. New hydrological insights for the region: A gated recurrent unit (GRU) neural network was built for groundwater level simulation in 78 catchments in the study region, and principal component analysis was used to cluster a variety of catchment hydrological variables and determine the input variables for the GRU model. Detrended fluctuation analysis was applied to analyze the autocorrelation of groundwater level in each catchment. This study further explored the influences of the hydrogeological properties of different catchments and the autocorrelation of groundwater levels on machining learning simulations. The results showed that the GRU model performed better in regions where hydrogeological properties could promote more effective responses of groundwater to external changes. Moreover, a negative correlation between the simulation performance of machine learning and the autocorrelation of the groundwater level was found.

Vegetation, a key intermediary linking water, the atmosphere, and the ground, performs extremely important functions in nature and for our existence. Although satellite-based remote-sensing technologies have become important for monitoring vegetation dynamics, selecting the correct remote-sensing vegetation indicator has become paramount for such investigations. This study investigated the consistencies between a photosynthetic activity index (the solar-induced chlorophyll fluorescence (SIF) indicator) and the traditional vegetation index (the Normalized Difference Vegetation Index (NDVI)) among different land-cover types and in different seasons and explored the applicability of NDVI and SIF in different cases by comparing their performances in gross primary production (GPP) and grain-yield-monitoring applications. The vegetation cover and photosynthesis showed decreasing trends, which were mainly concentrated in northern Xinjiang and part of the Qinghai–Tibet Plateau; a decreasing trend was also identified in a small part of Northeast China. The correlations between NDVI and SIF were strong for all land-cover types except evergreen needleleaf forests and evergreen broadleaf forests. Compared with NDVI, SIF had some advantages when monitoring the GPP and grain yields among different land-cover types. For example, SIF could capture the effects of drought on GPP and grain yields better than NDVI. To summarize, as the temporal extent of the available SIF data is extended, SIF will certainly perform increasingly wide applications in agricultural-management research that is closely related to GPP and grain-yield monitoring.

In recent years, extreme hydro-climate events (such as floods and droughts) have occurred more frequently, leading to significant threats to lives and damage of property [...]

Study region: Pearl River basin (PRB) in South China. Study focus: This study aims to assess future socioeconomic drought events under a changing climate over the study region. Variable Infiltration Capacity (VIC) model is used to simulate the streamflow in the PRB during the period of 2020–2099, and 48 projected precipitation datasets from General Circulation Models (GCMs) are selected to drive the VIC model at 0.5° × 0.5° spatial resolution and daily temporal resolution. Then, the minimum in-stream water requirement (MIWR) of the PRB is determined, and trend analysis of the simulated streamflow is conducted. Socioeconomic drought index (SEDI) is used to detect the occurrence of socioeconomic drought event, and further, the impact of the reservoirs in the PRB on drought analysis is evaluated. New hydrological insights for the region: Based on any dataset, nearly one hundred socioeconomic drought events at different severity levels can be identified in the PRB; however, most of them, especially those at severe and extreme levels, can be mitigated through reservoir operation, i.e., reserving at least 40 % of the total manageable storage capacity (TMSC) in the reservoirs. Overall, this study can improve the recognition of future socioeconomic drought events, which is of great value for our society to effectively assess the impacts of climate change and water projects on sustainable water resources utilization in such river basins.

The American cockroach (Periplaneta americana) is an hemimetabolous insect with rapid growth, high fecundity, and remarkable tissue-regeneration capability. Here Li et al sequence its 3.38-Gb genome and perform the functional studies, yielding insights into its environmental adaptation and developmental plasticity.

Evapotranspiration (ET) is one of the important components of the global hydrologic cycle, energy exchange, and carbon cycle. However, basin scale actual ET (hereafter ETa) is difficult to estimate accurately. We present an evaluation of four actual ET products (hereafter ETp) in seven sub-basins in the Tibetan Plateau. The actual ET calculated by the water balance method (hereafter ETref) was used as the reference for correction of the different ETp. The ETref and ETp show obvious seasonal cycles, but the ETp overestimated or underestimated the ET of the sub-basins in the Tibetan Plateau. A simple and effective method was proposed to correct the basin-scale ETp. The method was referred to as ratio bias correction, and it can effectively remove nearly all biases of the ETp. The proposed method is simpler and more effective in correcting the four ETp compared with the gamma distribution bias correction method. The reliability of the ETp is significantly increased after the ratio bias correction. The ratio bias correction method was used to correct the ETp in the seven sub-basins in the Tibetan Plateau, and regional ET was significantly improved. The results may help improve estimation of the ET of the Tibetan Plateau and thereby contribute to a better understanding of the hydrologic cycle of the plateau.

As a primary artificial project in a river basin, the role of large dams and related reservoirs in mitigating the hydrological and meteorological extremes has been widely recognized. Moreover, construction of additional large dams is considered as one of the best available options to meet future increases in water, food, and energy demands, although this may drastically affect the surrounding natural environment. However, the issue about the degree of such effects is still unclear, although the interactive impacts of dams and related reservoirs on the changes in meteorological variables are of great scientific importance. Therefore, this study aims to explore the impacts of reservoir characteristic factors (RCFs) on local climate change near the reservoir through examining the correlations between the RCFs of selected dams and related reservoirs and meteorological variables all over the world. The major findings are: (a) the correlations of the RCFs with evaporation are the opposite of those with precipitation; (b) dams and related reservoirs can have completely opposite (weakening or enhancing) effects on different meteorological variables; and (c) the RCFs outperform the geographical factors in terms of the impact on precipitation, whereas the variation of evaporation is more sensitive to geographical factors. Overall, the outcomes of this study will be useful for policymakers to have a more informed understanding of local climate change affected by large dams and related reservoirs in the future.

Floods are usually highly destructive, which may cause enormous losses to lives and property. It is, therefore, important and necessary to develop effective flood early warning systems and disseminate the information to the public through various information sources, to prevent or at least mitigate the flood damages. For flood early warning, novel methods can be developed by taking advantage of the state-of-the-art techniques (e.g., ensemble forecast, numerical weather prediction, and service-oriented architecture) and data sources (e.g., social media), and such developments can offer new insights for modeling flood disasters, including facilitating more accurate forecasts, more efficient communication, and more timely evacuation. The present Special Issue aims to collect the latest methodological developments and applications in the field of flood early warning. More specifically, we collected a number of contributions dealing with: (1) an urban flash flood alert tool for megacities; (2) a copula-based bivariate flood risk assessment; and (3) an analytic hierarchy process approach to flash flood impact assessment.

Sexually dimorphic phenotypes are a universal phenomenon in animals. In the model animal fruit fly Drosophila, males and females exhibit long- and short-sleep phenotypes, respectively. However, the mechanism is still a mystery. In this study, we showed that juvenile hormone (JH) is involved in regulation of sexually dimorphic sleep in Drosophila, in which gain of JH function enlarges differences of the dimorphic sleep phenotype with higher sleep in males and lower sleep in females, while loss of JH function blurs these differences and results in feminization of male sleep and masculinization of female sleep. Further studies indicate that germ cell-expressed (GCE), one of the JH receptors, mediates the response in the JH pathway because the sexually dimorphic sleep phenotypes cannot be rescued by JH hormone in a gce deletion mutant. The JH-GCE regulated sleep dimorphism is generated through the sex differentiation-related genes -fruitless (fru) and doublesex (dsx) in males and sex-lethal (sxl), transformer (tra) and doublesex (dsx) in females. These are the "switch" genes that separately control the sleep pattern in males and females. Moreover, analysis of sleep deprivation and circadian behaviors showed that the sexually dimorphic sleep induced by JH signals is a change of sleep drive and independent of the circadian clock. Furthermore, we found that JH seems to also play an unanticipated role in antagonism of an aging-induced sleep decrease in male flies. Taken together, these results indicate that the JH signal pathway is critical for maintenance of sexually dimorphic sleep by regulating sex-relevant genes.

BACKGROUND:Orthopteran migratory locust, Locusta migratoria, and lepidopteran Asian corn borer, Ostrinia furnacalis, are two types of insects undergoing incomplete and complete metamorphosis, respectively. Identification of candidate genes regulating wing development in these two insects would provide insights into the further study about the molecular mechanisms controlling metamorphosis development. We have sequenced the transcriptome of O. furnacalis larvae previously. Here we sequenced and characterized the transcriptome of L. migratoria wing discs with special emphasis on wing development-related signaling pathways. METHODOLOGY/PRINCIPAL FINDINGS:Illumina Hiseq2000 was used to sequence 8.38 Gb of the transcriptome from dissected nymphal wing discs. De novo assembly generated 91,907 unigenes with mean length of 610 nt. All unigenes were searched against five databases including Nt, Nr, Swiss-Prot, COG, and KEGG for annotations using blastn or blastx algorithm with an cut-off E-value of 10-5. A total of 23,359 (25.4%) unigenes have homologs within at least one database. Based on sequence similarity to homologs known to regulate Drosophila melanogaster wing development, we identified 50 and 46 potential wing development-related unigenes from L. migratoria and O. furnacalis transcriptome, respectively. The identified unigenes encode putative orthologs for nearly all components of the Hedgehog (Hh), Decapentaplegic (Dpp), Notch (N), and Wingless (Wg) signaling pathways, which are essential for growth and pattern formation during wing development. We investigated the expression profiles of the component genes involved in these signaling pathways in forewings and hind wings of L. migratoria and O. furnacalis. The results revealed the tested genes had different expression patterns in two insects. CONCLUSIONS/SIGNIFICANCE:This study provides the comprehensive sequence resource of the wing development-related signaling pathways of L. migratoria. The obtained data gives an insight into better understanding the molecular mechanisms involved in the wing development in L. migratoria and O. furnacalis, two insect species with different metamorphosis types.