Gene duplication led to divergence of expression patterns, protein–protein interaction patterns and floral development functions of AGL6-like genes in the basal angiosperm Magnolia wufengensis (Magnoliaceae)

2019 ◽  
Vol 39 (5) ◽  
pp. 861-876 ◽  
Author(s):  
Jiang Ma ◽  
Shixin Deng ◽  
Liyuan Chen ◽  
Zhongkui Jia ◽  
Ziyang Sang ◽  
...  
Keyword(s):  
Gene Duplication ◽  
Protein Interaction ◽  
Floral Development ◽  
Expression Patterns ◽  
Basal Angiosperm ◽  
Interaction Patterns ◽  
Protein Protein Interaction ◽  
Magnolia Wufengensis

Conservation and divergence of ancestral AGAMOUS/SEEDSTICK subfamily genes from the basal angiosperm Magnolia wufengensis

2019 ◽  
Vol 40 (1) ◽  
pp. 90-107 ◽  
Author(s):  
Jiang Ma ◽  
Shixin Deng ◽  
Zhongkui Jia ◽  
Ziyang Sang ◽  
Zhonglong Zhu ◽  
...  
Keyword(s):  
Gene Duplication ◽  
Current Knowledge ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Duplication Event ◽  
Basal Angiosperm ◽  
Interaction Patterns ◽  
Gene Duplication Event ◽  
Core Eudicots ◽  
Magnolia Wufengensis

Abstract AGAMOUS/SEEDSTICK (AG/STK) subfamily genes play crucial roles in the reproductive development of plants. However, most of our current knowledge of AG/STK subfamily genes is restricted to core eudicots and grasses, and the knowledge of ancestral exon–intron structures, expression patterns, protein–protein interaction patterns and functions of AG/STK subfamily genes remains unclear. To determine these, we isolated AG/STK subfamily genes (MawuAG1, MawuAG2 and MawuSTK) from a woody basal angiosperm Magnolia wufengensis (Magnoliaceae). MawuSTK arose from the gene duplication event occurring before the diversification of extant angiosperms, and MawuAG1 and MawuAG2 may result from a gene duplication event occurring before the divergence of Magnoliaceae and Lauraceae. Gene duplication led to apparent diversification in their expression and interaction patterns. It revealed that expression in both stamens and carpels likely represents the ancestral expression profiles of AG lineage genes, and expression of STK-like genes in stamens may have been lost soon after the appearance of the STK lineage. Moreover, AG/STK subfamily proteins may have immediately established interactions with the SEPALLATA (SEP) subfamily proteins following the emergence of the SEP subfamily; however, their interactions with the APETALA1/FRUITFULL subfamily proteins or themselves differ from those found in monocots and basal and core eudicots. MawuAG1 plays highly conserved roles in the determinacy of stamen, carpel and ovule identity, while gene duplication contributed to the functional diversification of MawuAG2 and MawuSTK. In addition, we investigated the evolutionary history of exon–intron structural changes of the AG/STK subfamily, and a novel splice-acceptor mode (GUU-AU) and the convergent evolution of N-terminal extension in the euAG and PLE subclades were revealed for the first time. These results further advance our understanding of ancestral AG/STK subfamily genes in terms of phylogeny, exon–intron structures, expression and interaction patterns, and functions, and provide strong evidence for the significance of gene duplication in the expansion and evolution of the AG/STK subfamily.

scholarly journals A multitask transfer learning framework for the prediction of virus-human protein–protein interactions

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Thi Ngan Dong ◽  
Graham Brogden ◽  
Gisa Gerold ◽  
Megha Khosla
Keyword(s):  
Transfer Learning ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Sequences ◽  
Human Protein ◽  
Interaction Patterns ◽  
Protein Protein Interactions ◽  
Interaction Prediction ◽  
Protein Protein Interaction ◽  
Protein Interaction Prediction

Abstract Background Viral infections are causing significant morbidity and mortality worldwide. Understanding the interaction patterns between a particular virus and human proteins plays a crucial role in unveiling the underlying mechanism of viral infection and pathogenesis. This could further help in prevention and treatment of virus-related diseases. However, the task of predicting protein–protein interactions between a new virus and human cells is extremely challenging due to scarce data on virus-human interactions and fast mutation rates of most viruses. Results We developed a multitask transfer learning approach that exploits the information of around 24 million protein sequences and the interaction patterns from the human interactome to counter the problem of small training datasets. Instead of using hand-crafted protein features, we utilize statistically rich protein representations learned by a deep language modeling approach from a massive source of protein sequences. Additionally, we employ an additional objective which aims to maximize the probability of observing human protein–protein interactions. This additional task objective acts as a regularizer and also allows to incorporate domain knowledge to inform the virus-human protein–protein interaction prediction model. Conclusions Our approach achieved competitive results on 13 benchmark datasets and the case study for the SARS-CoV-2 virus receptor. Experimental results show that our proposed model works effectively for both virus-human and bacteria-human protein–protein interaction prediction tasks. We share our code for reproducibility and future research at https://git.l3s.uni-hannover.de/dong/multitask-transfer.

scholarly journals ACE2 Protein-Protein Interaction Networks Reveal Potential Druggable Targets For SARS-CoV-2

2021 ◽  
Author(s):  
Qiaoxi Xia ◽  
Xiao Zhou ◽  
Mantong Chen ◽  
Ling Lin ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Biological Response ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Host Cells ◽  
Interacting Proteins ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks

Abstract Background: The novel coronavirus SARS-CoV-2 pandemic has infected more than 130 million people, killed over 2.3 million so far. Currently, no effective drugs are available to treat this infectious disease, due to limited knowledge of the molecular mechanisms of SARS-CoV-2 infection. ACE2 (angiotensin I converting enzyme 2) has long been identified as the major receptor for coronavirus entry the host cells. Methods: In this study, we constructed the protein-protein interaction networks (PPIN) based on ACE2 and its interacting proteins, considering with the expression alternation and co-expression relationship. The potential drugs targeting the proteins in the PPIN were explored.Results: ACE2 and its interacting proteins AAMP and HRAS are obviously increased, and their PPIN show distinguishing expression patterns during the COVID-19 progression. At least six pathways are activated for the host cell in the response to the virus. Moreover, drug-target networks were built to provide important clues to block ACE2 and its interacting proteins. Except the reported four drugs for ACE2, its interacting protein CALM1 and HRAS are great potentially druggable. We also considered the path initiated from ACE2 to nucleus by cascades of interaction, especially for the transcription factors in the PPIN which are also druggable.Conclusion: In summary, this study provides new insight into the disruption of the biological response to virus mediated by ACE2, but also its cascade interacting proteins when considering of PPIN.

scholarly journals Genome-wide identification and expression analysis of the Dof gene family under drought stress in tea (Camellia sinensis)

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9269
Author(s):  
Qian Yu ◽  
Chen Li ◽  
Jiucheng Zhang ◽  
Yueyue Tian ◽  
Hanyue Wang ◽  
...  
Keyword(s):  
Drought Stress ◽  
Gene Family ◽  
Camellia Sinensis ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Expression Patterns ◽  
Interaction Network ◽  
Severe Drought ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Background DNA-binding one zinc finger (Dof) proteins are plant-specific transcription factors important for seed development, hormone regulation, and defense against abiotic stress. Although drought stress is a key determinant of plant physiology and metabolic homeostasis, the role of Dof genes in different degrees of PEG6000-induced drought stress has received little attention. Methods Tea plants (Camellia sinensis) were exposed to mild, moderate and severe drought stress. The Tea Genome and Plant TFDB databases were used to identify Dof gene family members in the tea plant. Clustal W2.1, MEGA6.0, ScanProsite, SMART, ExPASy, GSDS, MEME and STRING were used to build a phylogenetic tree, predict the molecular masses and isoelectric points of the Dof proteins, and construct a predicted protein-protein interaction network between the CsDof TFs and proteins in the A. thaliana database. The expression patterns of Dof genes in different tissues were analyzed, and qRT-PCR was used to measure the expression of Dof genes under different degrees of drought stress in tea. Results We identified 16 Dof genes in tea (C. sinensis cv. Huangjinya) using whole-genome analysis. Through comparative analysis of tea and Arabidopsis thaliana, we divided the Dof genes into four families (A, B, C, and D). We identified 15 motifs in the amino acid sequences of the CsDof proteins. Gene sequences and motif structures were highly conserved among families, especially in the B1 and C2 subfamilies. The protein-protein interaction network indicated that multiple CsDof proteins may be involved in the response to drought stress. Real-time PCR was used to examine the tissue-specific expression patterns of the CsDof genes and to measure their responses to different levels of PEG6000-induced drought stress in mature leaves. Most CsDof genes responded to drought stress. These results provide information on the Dof gene family in tea, offer new insights into the function of CsDof genes in a perennial species, and lay the foundation for further analysis of their functions.

scholarly journals ACE2 Protein-protein Interaction Networks Reveal Potential Druggable Targets for SARS-CoV-2

2020 ◽  
Author(s):  
Qiaoxi Xia ◽  
Mantong Chen ◽  
Xiao Zhou ◽  
Ling Lin ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Host Cells ◽  
Interacting Proteins ◽  
Expression Change ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks

Abstract Background The novel coronavirus SARS-CoV-2 pandemic has infected more than 10 million people, killed over 500,000 so far. Currently, no effective drugs are available to treat this infectious disease, due to limited knowledge of the molecular mechanisms of SARS-CoV-2 infection. ACE2 (angiotensin I converting enzyme 2) has long been identified as the major receptor for coronavirus entry the host cells. Methods In this study, we constructed the protein-protein interaction networks (PPIN) based on ACE2 and its interacting proteins, combined with the expression change and co-expression relationship. The potential drugs targeting the proteins in the PPIN were explored.Results ACE2 and its interacting proteins AAMP and HRAS are obviously increased, and their PPIN show distinguishing expression patterns during the COVID-19 progression. At least six pathways are activated for the host cell in the response to the virus. Moreover, drug-target networks were built to provide important clues to block ACE2 and its interacting proteins. Except the reported four drugs for ACE2, its interacting protein CALM1 and HRAS are great potentially druggable. We also considered the path initiated from ACE2 to nucleus by cascades of interaction, especially for the transcription factors in the PPIN which are also druggable. Conclusion In summary, this study provides new insight into the disruption of the biological response to virus mediated by ACE2, but also its cascade interacting proteins when considering of PPIN.

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