scholarly journals Topology-driven protein-protein interaction network analysis detects genetic sub-networks regulating reproductive capacity

2019 ◽  
Author(s):  
Tarun Kumar ◽  
Leo Blondel ◽  
Cassandra G. Extavour
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Fundamental Problem ◽  
Genetic Regulation ◽  
Interaction Network ◽  
Egg Laying ◽  
Reproductive Capacity ◽  
Ovariole Number ◽  
Gene Regulatory ◽  
Hippo Signalling

AbstractUnderstanding the genetic regulation of organ structure is a fundamental problem in developmental biology. Here, we use egg-producing structures of insect ovaries, called ovarioles, to deduce systems-level gene regulatory relationships from quantitative functional genetic analysis. We previously showed that Hippo signalling, a conserved regulator of animal organ size, regulates ovariole number in Drosophila melanogaster. To comprehensively determine how Hippo signalling interacts with other pathways in this regulation, we screened all known signalling pathway genes, and identified Hpo-dependent and Hpo-independent signalling requirements. Network analysis of known protein-protein interactions among screen results identified independent gene regulatory sub-networks regulating one or both of ovariole number and egg laying. These sub-networks predict involvement of previously uncharacterised genes with higher accuracy than the original candidate screen. This shows that network analysis combining functional genetic and large-scale interaction data can predict function of novel genes regulating development.

scholarly journals Topology-driven protein-protein interaction network analysis detects genetic sub-networks regulating reproductive capacity

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Tarun Kumar ◽  
Leo Blondel ◽  
Cassandra G Extavour
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Fundamental Problem ◽  
Genetic Regulation ◽  
Interaction Network ◽  
Egg Laying ◽  
Reproductive Capacity ◽  
Ovariole Number ◽  
Gene Regulatory ◽  
Hippo Signalling

Understanding the genetic regulation of organ structure is a fundamental problem in developmental biology. Here, we use egg-producing structures of insect ovaries, called ovarioles, to deduce systems-level gene regulatory relationships from quantitative functional genetic analysis. We previously showed that Hippo signalling, a conserved regulator of animal organ size, regulates ovariole number in Drosophila melanogaster. To comprehensively determine how Hippo signalling interacts with other pathways in this regulation, we screened all known signalling pathway genes, and identified Hpo-dependent and Hpo-independent signalling requirements. Network analysis of known protein-protein interactions among screen results identified independent gene regulatory sub-networks regulating one or both of ovariole number and egg laying. These sub-networks predict involvement of previously uncharacterised genes with higher accuracy than the original candidate screen. This shows that network analysis combining functional genetic and large-scale interaction data can predict function of novel genes regulating development.

Understanding neighborhood isolation through spatial interaction network analysis using location big data

2019 ◽  
Vol 52 (6) ◽  
pp. 1027-1031 ◽  
Author(s):  
Timothy Prestby ◽  
Joseph App ◽  
Yuhao Kang ◽  
Song Gao
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Spatial Interaction ◽  
Interaction Network ◽  
Location Based Services ◽  
Interaction Patterns ◽  
Individual Level ◽  
Mobility Data ◽  
The Usa ◽  
Hidden Biases

Hidden biases of racial and socioeconomic preferences shape residential neighborhoods throughout the USA. Thereby, these preferences shape neighborhoods composed predominantly of a particular race or income class. However, the assessment of spatial extent and the degree of isolation outside the residential neighborhoods at large scale is challenging, which requires further investigation to understand and identify the magnitude and underlying geospatial processes. With the ubiquitous availability of location-based services, large-scale individual-level location data have been widely collected using numerous mobile phone applications and enable the study of neighborhood isolation at large scale. In this research, we analyze large-scale anonymized smartphone users’ mobility data in Milwaukee, Wisconsin, to understand neighborhood-to-neighborhood spatial interaction patterns of different racial classes. Several isolated neighborhoods are successfully identified through the mobility-based spatial interaction network analysis.

scholarly journals Reproductive capacity evolves in response to ecology through common developmental mechanisms in Hawai’ian Drosophila

2018 ◽  
Author(s):  
Didem P. Sarikaya ◽  
Samuel H. Church ◽  
Laura P. Lagomarsino ◽  
Karl N. Magnacca ◽  
Steven Montgomery ◽  
...  
Keyword(s):  
Environmental Control ◽  
Natural Populations ◽  
Evolutionary Process ◽  
Egg Laying ◽  
Reproductive Capacity ◽  
Proximate Mechanisms ◽  
Number Variation ◽  
Evolutionary Variation ◽  
Ovariole Number ◽  
Outstanding Question

AbstractLifetime reproductive capacity, or the total number of offspring that an individual can give rise to in its lifetime, is a fitness component critical to the evolutionary process. In insects, female reproductive capacity is largely determined by the number of ovarioles, the egg-producing subunits of the ovary. Recent work has provided insights into the genetic and environmental control of ovariole number in Drosophila melanogaster. However, whether regulatory mechanisms discovered under laboratory conditions also explain evolutionary variation in natural populations is an outstanding question. Here we report, for the first time, insights into the mechanisms regulating ovariole number and its evolution among Hawai’ian Drosophila, a large adaptive radiation of fruit flies in which the highest and lowest ovariole numbers of the genus have evolved within 25 million years. Using phylogenetic comparative methods, we show that ovariole number variation among Hawai’ian Drosophila is best explained by adaptation to specific oviposition substrates. Further, we show that evolution of oviposition on ephemeral egg-laying substrates is linked to changes the allometric relationship between body size and ovariole number. Finally, we provide evidence that the developmental mechanism principally responsible for controlling ovariole number in D. melanogaster also regulates ovariole number in natural populations of Hawai’ian drosophilids. By integrating ecology, organismal growth, and cell behavior during development to understand the evolution of ovariole number, this work connects the ultimate and proximate mechanisms of evolutionary change in reproductive capacity.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network

In Silico Protein Interaction Network Analysis of Virulence Proteins Associated with Invasive Aspergillosis for Drug Discovery

2019 ◽  
Vol 19 (2) ◽  
pp. 146-155 ◽  
Author(s):  
Renu Chaudhary ◽  
Meenakshi Balhara ◽  
Deepak Kumar Jangir ◽  
Mehak Dangi ◽  
Mrridula Dangi ◽  
...  
Keyword(s):  
Network Analysis ◽  
Invasive Aspergillosis ◽  
Protein Interaction ◽  
Drug Target ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Homology Model ◽  
Ppi Network ◽  
Virulence Proteins ◽  
Hub Proteins

<P>Background: Protein-Protein interaction (PPI) network analysis of virulence proteins of Aspergillus fumigatus is a prevailing strategy to understand the mechanism behind the virulence of A. fumigatus. The identification of major hub proteins and targeting the hub protein as a new antifungal drug target will help in treating the invasive aspergillosis. </P><P> Materials & Method: In the present study, the PPI network of 96 virulence (drug target) proteins of A. fumigatus were investigated which resulted in 103 nodes and 430 edges. Topological enrichment analysis of the PPI network was also carried out by using STRING database and Network analyzer a cytoscape plugin app. The key enriched KEGG pathway and protein domains were analyzed by STRING.Conclusion:Manual curation of PPI data identified three proteins (PyrABCN-43, AroM-34, and Glt1- 34) of A. fumigatus possessing the highest interacting partners. Top 10% hub proteins were also identified from the network using cytohubba on the basis of seven algorithms, i.e. betweenness, radiality, closeness, degree, bottleneck, MCC and EPC. Homology model and the active pocket of top three hub proteins were also predicted.</P>

scholarly journals Diabetic Retinopathy and Laser Therapy in Rats: A Protein-Protein Interaction Network Analysis

2017 ◽  
Vol 8 (Suppl 1) ◽  
pp. S20-S21 ◽  
Author(s):  
Akram Safaei ◽  
Mostafa Rezaei Tavirani ◽  
Mona Zamanian Azodi ◽  
Alireza Lashay ◽  
Seyed Farzad Mohammadi ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Network Analysis ◽  
Laser Therapy ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network
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