Construction and analysis of the protein–protein interaction network for the detoxification enzymes of the silkworm, <i>Bombyx mori</i>

Xin, Shanghong; Zhang, Wenjun

doi:10.1002/arch.21850

Cited by 7 publications

(6 citation statements)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DmelGSTD2 and DmelGSTE7 overexpressed when exposed to organic isothiocyanates, showing a function of toxic detoxification (Gonzalez et al, 2018; Mazari et al, 2014). And previous studies have indicated the importance of GSTs in the olfactory PPIs interactions network in Bombyx mori (Xin & Zhang, 2020).…”

Section: Conclusion and Discussionmentioning

confidence: 86%

“…The analysis of topological properties of the PPIs network makes it possible to investigate candidate key proteins (Xin & Zhang, 2020, 2021; Zhang & Zhang, 2019). Generally, topological properties explain how important a node is in a network (Zhang, 2016, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…It controls the behavior of insects, including locating habitats and food sources, identifying mating partners and oviposition, and escaping predators and toxic environments (Gadenne et al, 2016; Guo et al, 2021; Hansson & Stensmyr, 2011; Haverkamp et al, 2018). With the rapid development of genomics and advances in functional analysis, considerable progress has been made in olfaction (Breer et al, 2019; Gadenne et al, 2016; Xin & Zhang, 2020). For insects, four types of hair‐like structures (also called sensillum) are housed in the third antennal segment and the maxillary palps, capturing the odorant molecules (Shanbhag et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Systematic analysis of olfactory protein–protein interactions network of fruitfly, Drosophila melanogaster

Yang

Zhang

2022

Arch Insect Biochem Physiol

Self Cite

View full text Add to dashboard Cite

Olfaction is one of the physiological traits of insect behavior. Insects have evolved a sophisticated olfactory system and use a combined coding strategy to process general odor. Drosophila melanogaster is a powerful model to reveal the molecular and cellular mechanisms of odor detection. Identifying new olfactory targets through complex interactions will contribute to a better understanding of the functions, interactions, and signaling pathways of olfactory proteins. However, the mechanism of D. melanogaster olfaction is still unclear, and more olfactory proteins are required to be discovered. In this study, we tried to explore essential proteins in the olfactory system of D. melanogaster and conduct protein–protein interactions (PPIs) analysis. We constructed the PPIs network of the olfactory system of D. melanogaster, consisting of 863 proteins and 18,959 interactions. Various methods were used to perform functional enrichment analysis, topological analysis and cluster analysis. Our results confirmed that Class B scavenger receptors (SR‐Bs), glutathione S‐transferases (GSTs), and UDP‐glycosyltransferases (UGTs) play an essential role in olfaction of D. melanogaster. The proteins obtained in this study can be used for subsequent functional identification in D. melanogaster olfactory.

show abstract

Section: Conclusion and Discussionmentioning

confidence: 86%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Systematic analysis of olfactory protein–protein interactions network of fruitfly, Drosophila melanogaster

Yang

Zhang

2022

Arch Insect Biochem Physiol

Self Cite

View full text Add to dashboard Cite

show abstract

“…Search tool for the Retrieval of Interacting Genes/Proteins STRING database ( https://www.string-db.org/ ) was used in the protein–protein interaction (PPI) analysis of the DEGs. Cytoscape 3.8 was used for producing the PPI network maps and the hub clustering modules of the PPI network were further analyzed [ 24 ].…”

Section: Methodsmentioning

confidence: 99%

Identification of key genes and signaling pathways related to Hetian sheep wool density by RNA-seq technology

Shi

Liu

et al. 2022

PLoS ONE

View full text Add to dashboard Cite

Hetian sheep is a breed of sheep unique to the Hetian area of Xinjiang whose wool is used for producing blankets. Individual differences and hair follicle density are the key factors affecting wool production. Therefore, this study aimed to assess the Hetian sheep having different wool densities to statistically analyze the wool traits and hair follicle parameters. Furthermore, the transcriptome sequencing analysis was performed on the skins with different wool densities. The results showed that wool quantity and total hair follicle density of the high wool density sheep was significantly higher than low wool density sheep. The sheepskin with high wool density was found to grow more and finer wool than sheepskin with low wool density. A total of 1,452 differentially expressed genes were screened from the two sets of samples, including 754 upregulated and 698 downregulated genes. The differentially expressed genes were involved in the TGF-β/BMP and MAPK signaling pathways related to hair growth. Eleven differentially expressed genes belonging to the KAPs and KIFs might affect the fineness of the wool. The key genes, like the TNF, MAP2K2, INHBA, FST, PTPN11, MAP3K7, KIT, and BMPR1A, were found to probably affect the growth and density of the wool. The qPCR verified eight genes related to the MAPK pathway whose gene expression trends were consistent with the transcriptome sequencing results. This study furnishes valuable resources for enhancing the quality and production of wool in the Hetian sheep.

show abstract

“…Transcriptome data generally contains thousands of genes, and these data can be narrowed down by a determination of the protein-protein interaction (PPI) network which is used to screen and pick up core genes. The PPI network intuitively displays the main characteristics of the interaction and functional characteristics of proteins in birth objects and reflects the unique and essential proteins, which have been widely used in gene function annotation and prediction ( Li et al, 2013 ; Zhang and Zhang, 2020 ; Xin and Zhang, 2021 ). STRING ( https://STRING-db.org/ ) is a database that searches for known and predicted interactions between proteins, built through PPI networks to better understand complex regulatory networks in organisms ( von Mering et al, 2005 ; Szklarczyk et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of sex-biased and neurodevelopment genes via brain transcriptome in Ostrinia furnacalis

et al. 2022

View full text Add to dashboard Cite

Insect brains play important roles in the regulation of sex-biased behaviors such as mating and oviposition. The neural structure and function of brain differences between males and females have been identified, in which the antenna lobes (AL) showed the most discrepancy, however, the whole repertoire of the genes expressed in the brains and the molecular mechanism of neural signaling and structural development are still unclear. In this study, high-throughput transcriptome analysis of male and female brains was carried on in the Asia corn borer, Ostrinia furnacalis, and a total of 39.23 Gb data and 34,092 unigenes were obtained. Among them, 276 genes displayed sex-biased expression by DEG analysis, of which 125 genes were highly expressed in the males and 151 genes were highly expressed in the females. Besides, by homology analysis against genes that have been confirmed to be related to brain neurodevelopment, a total of 24 candidate genes were identified in O. furnacalis. In addition, to further screen the core genes that may be important for sex-biased nerve signaling and neurodevelopment, protein-protein interaction networks were constructed for the sex-biased genes and neurodevelopment genes. We identified 10 (Mhc, Mlc1, Mlc2, Prm, Mf, wupA, TpnC25D, fln, l(2)efl, and Act5C), 11 (PPO2, GNBP3, Spn77Ba, Ppn, yellow-d2, PGRP-LB, PGRP-SD, PGRP-SC2, Hml, Cg25C, and vkg) and 8 (dac, wg, hh, ci, run, Lim1, Rbp9, and Bx) core hub genes that may be related to brain neural development from male-biased, female-biased, and neurodevelopment gene groups. Our results provide a reference for further analysis of the dimorphism of male and female brain structures in agricultural pests.

show abstract

Construction and analysis of the protein–protein interaction network for the detoxification enzymes of the silkworm, Bombyx mori

Cited by 7 publications

References 85 publications

Systematic analysis of olfactory protein–protein interactions network of fruitfly, Drosophila melanogaster

Systematic analysis of olfactory protein–protein interactions network of fruitfly, Drosophila melanogaster

Identification of key genes and signaling pathways related to Hetian sheep wool density by RNA-seq technology

Identification of sex-biased and neurodevelopment genes via brain transcriptome in Ostrinia furnacalis

Contact Info

Product

Resources

About