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  1. Article ; Online: Study of coding genes and SNPs in the brain tissue genome of honeybee related to behavioral traits in Italian and African subspecies using RNA-Seq data analysis

    Aliakbar Hasankhani / Hossein Moradi Shahrbabak / Mohammad Moradi Shahrbabak / Abolfazl Bahrami / Gholamali Nehzati paghaleh / Mohammad Hossein Banabazi

    مجله بیوتکنولوژی کشاورزی, Vol 14, Iss 2, Pp 171-

    2022  Volume 192

    Abstract: ObjectiveHoneybees, as pollinating insects, are an important part of nature. Because behavioral traits are so important in honeybees, comparing brain tissue transcriptomes of the two subspecies with aggressive and calm behavioral characteristics makes it ...

    Abstract ObjectiveHoneybees, as pollinating insects, are an important part of nature. Because behavioral traits are so important in honeybees, comparing brain tissue transcriptomes of the two subspecies with aggressive and calm behavioral characteristics makes it possible to understand this behavioral difference genetically. This study aimed to investigate to gene expression profile and identify the key genes in brain tissue in Italian (Apis Mellifera Ligustica) and African (Apis mellifera Scutellata) honeybees concerning behavioral traits. The Italian honeybee has calm behavioral characteristics, while the African is known as an aggressive honeybee.Materials and methodsRNA-Seq data were obtained from the NCBI (GEO) database, and after pre-processing of reads, the brain tissue transcriptomes of both subspecies were aligned and mapped on the honey bee reference genome (v A.mel 4.5), and then data qualification, transcriptome assembly, differential expression analysis, and gene ontology were performed.ResultsDifferential gene expression analysis identified 16,701 genes on the honeybee reference genome, of which 22 genes in brain tissue between the two subspecies had significant differential expression (adj p-value <0 .05 and Log2FC>2). As well, some of these genes were first identified. Gene ontology analysis showed that among these 22 genes, such as ITPR, MRJP, HSP70Ab, MBS, GB45410, and Def1 are directly or indirectly involved in the occurrence of various traits such as defensive, health behavior, reproductive, heat, light, and smell sensitivity. In addition, the SNPs encoding the honeybee brain tissue genome were identified in both subspecies, and 99636 SNPs were identified in the Italian, and 92514 SNPs were identified in the African subspecies.ConclusionsRNA-seq data, due to its high throughput, can provide us with accurate information about the expression of genes in different tissues in various subspecies. In this study, genes involved in honeybee behavioral traits and the SNPs in these genes were identified
    Keywords : behavioral traits ; gene ; honeybee ; snp ; transcriptome ; Agriculture ; S ; Biotechnology ; TP248.13-248.65
    Subject code 616
    Language Persian
    Publishing date 2022-06-01T00:00:00Z
    Publisher Shahid Bahonar University of Kerman
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlying Mycobacterium bovis infection

    Aliakbar Hasankhani / Abolfazl Bahrami / Shayan Mackie / Sairan Maghsoodi / Heba Saed Kariem Alawamleh / Negin Sheybani / Farhad Safarpoor Dehkordi / Fatemeh Rajabi / Ghazaleh Javanmard / Hosein Khadem / Herman W. Barkema / Marcos De Donato

    Frontiers in Microbiology, Vol

    2022  Volume 13

    Abstract: ObjectiveBovine tuberculosis (bTB) is a chronic respiratory infectious disease of domestic livestock caused by intracellular Mycobacterium bovis infection, which causes ~$3 billion in annual losses to global agriculture. Providing novel tools for bTB ... ...

    Abstract ObjectiveBovine tuberculosis (bTB) is a chronic respiratory infectious disease of domestic livestock caused by intracellular Mycobacterium bovis infection, which causes ~$3 billion in annual losses to global agriculture. Providing novel tools for bTB managements requires a comprehensive understanding of the molecular regulatory mechanisms underlying the M. bovis infection. Nevertheless, a combination of different bioinformatics and systems biology methods was used in this study in order to clearly understand the molecular regulatory mechanisms of bTB, especially the immunomodulatory mechanisms of M. bovis infection.MethodsRNA-seq data were retrieved and processed from 78 (39 non-infected control vs. 39 M. bovis-infected samples) bovine alveolar macrophages (bAMs). Next, weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression modules in non-infected control bAMs as reference set. The WGCNA module preservation approach was then used to identify non-preserved modules between non-infected controls and M. bovis-infected samples (test set). Additionally, functional enrichment analysis was used to investigate the biological behavior of the non-preserved modules and to identify bTB-specific non-preserved modules. Co-expressed hub genes were identified based on module membership (MM) criteria of WGCNA in the non-preserved modules and then integrated with protein–protein interaction (PPI) networks to identify co-expressed hub genes/transcription factors (TFs) with the highest maximal clique centrality (MCC) score (hub-central genes).ResultsAs result, WGCNA analysis led to the identification of 21 modules in the non-infected control bAMs (reference set), among which the topological properties of 14 modules were altered in the M. bovis-infected bAMs (test set). Interestingly, 7 of the 14 non-preserved modules were directly related to the molecular mechanisms underlying the host immune response, immunosuppressive mechanisms of M. bovis, and bTB development. Moreover, among the ...
    Keywords bovine tuberculosis ; hub-central gene ; maximal clique centrality ; Mycobacterium bovis ; RNA-seq ; systems biology ; Microbiology ; QR1-502
    Subject code 570
    Language English
    Publishing date 2022-11-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

    Aliakbar Hasankhani / Abolfazl Bahrami / Negin Sheybani / Behzad Aria / Behzad Hemati / Farhang Fatehi / Hamid Ghaem Maghami Farahani / Ghazaleh Javanmard / Mahsa Rezaee / John P. Kastelic / Herman W. Barkema

    Frontiers in Immunology, Vol

    2021  Volume 12

    Abstract: BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate ... ...

    Abstract BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.MethodsRNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.ResultsBased on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19’s main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and ...
    Keywords systems biology ; systems immunology ; WGCNA ; hub-high traffic genes ; immunopathogenesis ; therapeutic targets in infectious diseases ; Immunologic diseases. Allergy ; RC581-607
    Subject code 570
    Language English
    Publishing date 2021-12-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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