scholarly journals Gene selection for studying frugivore-plant interactions: a review and an example using Queensland fruit fly in tomato

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11762
Author(s):  
Shirin Roohigohar ◽  
Anthony R. Clarke ◽  
Peter J. Prentis
Keyword(s):  
Gene Expression ◽  
Gene Selection ◽  
Induced Defense ◽  
Tomato Fruit ◽  
Gene Families ◽  
Fruit Fly ◽  
Defense Genes ◽  
Promising Alternative ◽  
Starting Point ◽  
Wide Range

Fruit production is negatively affected by a wide range of frugivorous insects, among them tephritid fruit flies are one of the most important. As a replacement for pesticide-based controls, enhancing natural fruit resistance through biotechnology approaches is a poorly researched but promising alternative. The use of quantitative reverse transcription PCR (RT-qPCR) is an approach to studying gene expression which has been widely used in studying plant resistance to pathogens and non-frugivorous insect herbivores, and offers a starting point for fruit fly studies. In this paper, we develop a gene selection pipe-line for known induced-defense genes in tomato fruit, Solanum lycopersicum, and putative detoxification genes in Queensland fruit fly, Bactrocera tryoni, as a basis for future RT-qPCR research. The pipeline started with a literature review on plant/herbivore and plant/pathogen molecular interactions. With respect to the fly, this was then followed by the identification of gene families known to be associated with insect resistance to toxins, and then individual genes through reference to annotated B. tryoni transcriptomes and gene identity matching with related species. In contrast for tomato, a much better studied species, individual defense genes could be identified directly through literature research. For B. tryoni, gene selection was then further refined through gene expression studies. Ultimately 28 putative detoxification genes from cytochrome P450 (P450), carboxylesterase (CarE), glutathione S-transferases (GST), and ATP binding cassette transporters (ABC) gene families were identified for B. tryoni, and 15 induced defense genes from receptor-like kinase (RLK), D-mannose/L-galactose, mitogen-activated protein kinase (MAPK), lipoxygenase (LOX), gamma-aminobutyric acid (GABA) pathways and polyphenol oxidase (PPO), proteinase inhibitors (PI) and resistance (R) gene families were identified from tomato fruit. The developed gene selection process for B. tryoni can be applied to other herbivorous and frugivorous insect pests so long as the minimum necessary genomic information, an annotated transcriptome, is available.

scholarly journals Conservation of expression regulation throughout the animal kingdom

2014 ◽  
Author(s):  
Michael Kuhn ◽  
Andreas Beyer
Keyword(s):  
Gene Expression ◽  
Related Species ◽  
Expression Patterns ◽  
Gene Families ◽  
Tissue Expression ◽  
Rate Of Change ◽  
Gene Expression Patterns ◽  
Transfer Of Knowledge ◽  
Tissue Specific ◽  
Wide Range

Following the increase in available sequenced genomes, tissue-specific transcriptomes are being determined for a rapidly growing number of highly diverse species. Traditionally, only the transcriptomes of related species with equivalent tissues have been compared. Such an analysis is much more challenging over larger evolutionary distances when complementary tissues cannot readily be defined. Here, we present a method for the cross-species mapping of tissue-specific and developmental gene expression patterns across a wide range of animals, including many non-model species. Our approach maps gene expression patterns between species without requiring the definition of homologous tissues. With the help of this mapping, gene expression patterns can be compared even across distantly related species. In our survey of 36 datasets across 27 species, we detected conserved expression programs on all taxonomic levels, both within animals and between the animals and their closest unicellular relatives, the choanoflagellates. We found that the rate of change in tissue expression patterns is a property of gene families. Our findings open new avenues of study for the comparison and transfer of knowledge between different species.

scholarly journals Finding Biomarkers from a High-Dimensional Imbalanced Dataset Using the Hybrid Method of Random Undersampling and Lasso

2020 ◽  
Vol 11 (2) ◽  
pp. 75-81
Author(s):  
Masithoh Yessi Rochayani ◽  
Umu Sa'adah ◽  
Ani Budi Astuti
Keyword(s):  
Gene Expression ◽  
Gene Selection ◽  
High Accuracy ◽  
High Dimensional ◽  
Simulation Studies ◽  
Selection Methods ◽  
Imbalanced Dataset ◽  
Random Undersampling ◽  
Starting Point ◽  
Imbalanced Class

The research conducted undersampling and gene selection as a starting point for cancer classification in gene expression datasets with a high-dimensional and imbalanced class. It investigated whether implementing undersampling before gene selection gave better results than without implementing undersampling. The used undersampling method was Random Undersampling (RUS), and for gene selection, it was Lasso. Then, the selected genes based on theory were validated. To explore the effectiveness of applying RUS before gene selection, the researchers used two gene expression datasets. Both of the datasets consisted of two classes, 1.545 observations and 10.935 genes, but had a different imbalance ratio. The results show that the proposed gene selection methods, namely Lasso and RUS + Lasso, can produce several important biomarkers, and the obtained model has high accuracy. However, the model is complicated since it involves too many genes. It also finds that undersampling is not affected when it is implemented in a less imbalanced class. Meanwhile, when the dataset is highly imbalanced, undersampling can remove a lot of information from the majority class. Nevertheless, the effectiveness of undersampling remains unclear. Simulation studies can be carried out in the next research to investigate when undersampling should be implemented.

Discovery of Antibacterial Agents Inhibiting the Energy-Coupling Factor (ECF) Transporters by Structure-Based Virtual Screening

2020 ◽  
Author(s):  
Eleonora Diamanti ◽  
Inda Setyawati ◽  
Spyridon Bousis ◽  
leticia mojas ◽  
lotteke Swier ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Antibacterial Agents ◽  
Antimicrobial Agents ◽  
Energy Coupling ◽  
Coupling Factor ◽  
Design Synthesis ◽  
Screening Design ◽  
Starting Point ◽  
Wide Range ◽  
Vitamin Uptake

Here, we report on the virtual screening, design, synthesis and structure–activity relationships (SARs) of the first class of selective, antibacterial agents against the energy-coupling factor (ECF) transporters. The ECF transporters are a family of transmembrane proteins involved in the uptake of vitamins in a wide range of bacteria. Inhibition of the activity of these proteins could reduce the viability of pathogens that depend on vitamin uptake. Because of their central role in the metabolism of bacteria and their absence in humans, ECF transporters are novel potential antimicrobial targets to tackle infection. The hit compound’s metabolic and plasma stability, the potency (20, MIC Streptococcus pneumoniae = 2 µg/mL), the absence of cytotoxicity and a lack of resistance development under the conditions tested here suggest that this scaffold may represent a promising starting point for the development of novel antimicrobial agents with an unprecedented mechanism of action.<br>

Reverse Screening Bioinformatics Approach to Identify Potential Anti Breast Cancer Targets Using Thymoquinone from Neutraceuticals Black Cumin Oil

2019 ◽  
Vol 19 (5) ◽  
pp. 599-609 ◽  
Author(s):  
Sumathi Sundaravadivelu ◽  
Sonia K. Raj ◽  
Banupriya S. Kumar ◽  
Poornima Arumugamand ◽  
Padma P. Ragunathan
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cell Cycle ◽  
Cell Death ◽  
In Silico ◽  
Chemotherapeutic Agents ◽  
Normal Cells ◽  
Black Cumin ◽  
In Silico Docking ◽  
Wide Range

Background: Functional foods, neutraceuticals and natural antioxidants have established their potential roles in the protection of human health and diseases. Thymoquinone (TQ), the main bioactive component of Nigella sativa seeds (black cumin seeds), a plant derived neutraceutical was used by ancient Egyptians because of their ability to cure a variety of health conditions and used as a dietary food supplement. Owing to its multi targeting nature, TQ interferes with a wide range of tumorigenic processes and counteracts carcinogenesis, malignant growth, invasion, migration, and angiogenesis. Additionally, TQ can specifically sensitize tumor cells towards conventional cancer treatments (e.g., radiotherapy, chemotherapy, and immunotherapy) and simultaneously minimize therapy-associated toxic effects in normal cells besides being cost effective and safe. TQ was found to play a protective role when given along with chemotherapeutic agents to normal cells. Methods: In the present study, reverse in silico docking approach was used to search for potential molecular targets for cancer therapy. Various metastatic and apoptotic targets were docked with the target ligand. TQ was also tested for its anticancer activities for its ability to cause cell death, arrest cell cycle and ability to inhibit PARP gene expression. Results: In silico docking studies showed that TQ effectively docked metastatic targets MMPs and other apoptotic and cell proliferation targets EGFR. They were able to bring about cell death mediated by apoptosis, cell cycle arrest in the late apoptotic stage and induce DNA damage too. TQ effectively down regulated PARP gene expression which can lead to enhanced cancer cell death. Conclusion: Thymoquinone a neutraceutical can be employed as a new therapeutic agent to target triple negative breast cancer which is otherwise difficult to treat as there are no receptors on them. Can be employed along with standard chemotherapeutic drugs to treat breast cancer as a combinatorial therapy.

scholarly journals Synonymous single nucleotide polymorphism in arsenic (+3) methyltransferase of the Western mosquitofish (Gambusia affinis) and its gene expression among field populations

Ecotoxicology ◽  
2021 ◽  
Author(s):  
Daesik Park ◽  
Catherine R. Propper ◽  
Guangning Wang ◽  
Matthew C. Salanga
Keyword(s):  
Gene Expression ◽  
Sequence Variation ◽  
Allelic Variation ◽  
Arsenic Concentration ◽  
Gambusia Affinis ◽  
Contamination Level ◽  
Water Medium ◽  
Single Nucleotide ◽  
Wide Range ◽  
High Arsenic

AbstractNaturally occurring arsenic is toxic at extremely low concentrations, yet some species persist even in high arsenic environments. We wanted to test if these species show evidence of evolution associated with arsenic exposure. To do this, we compared allelic variation across 872 coding nucleotides of arsenic (+3) methyltransferase (as3mt) and whole fish as3mt gene expression from three field populations of Gambusia affinis, from water sources containing low (1.9 ppb), medium-low (3.3 ppb), and high (15.7 ppb) levels of arsenic. The high arsenic site exceeds the US EPA’s Maximum Contamination Level for drinking water. Medium-low and high populations exhibited homozygosity, and no sequence variation across all animals sampled. Eleven of 24 fish examined (45.8%) in the low arsenic population harbored synonymous single nucleotide polymorphisms (SNPs) in exons 4 and/or 10. SNP presence in the low arsenic population was not associated with differences in as3mt transcript levels compared to fish from the medium-low site, where SNPs were noted; however, as3mt expression in fish from the high arsenic concentration site was significantly lower than the other two sites. Low sequence variation in fish populations from sites with medium-low and high arsenic concentrations suggests greater selective pressure on this allele, while higher variation in the low population suggests a relaxed selection. Our results suggest gene regulation associated with arsenic detoxification may play a more crucial role in influencing responses to arsenic than polymorphic gene sequence. Understanding microevolutionary processes to various contaminants require the evaluation of multiple populations across a wide range of pollution exposures.

scholarly journals Consumer Neuroscience Techniques in Advertising Research: A Bibliometric Citation Analysis

2021 ◽  
Vol 13 (3) ◽  
pp. 1589
Author(s):  
Juan Sánchez-Fernández ◽  
Luis-Alberto Casado-Aranda ◽  
Ana-Belén Bastidas-Manzano
Keyword(s):  
Self Report ◽  
Future Research ◽  
Complex Nature ◽  
Clear Understanding ◽  
Continuous Growth ◽  
Main Research ◽  
Consumer Neuroscience ◽  
Starting Point ◽  
Wide Range ◽  
Performance Analysis Tools

The limitations of self-report techniques (i.e., questionnaires or surveys) in measuring consumer response to advertising stimuli have necessitated more objective and accurate tools from the fields of neuroscience and psychology for the study of consumer behavior, resulting in the creation of consumer neuroscience. This recent marketing sub-field stems from a wide range of disciplines and applies multiple types of techniques to diverse advertising subdomains (e.g., advertising constructs, media elements, or prediction strategies). Due to its complex nature and continuous growth, this area of research calls for a clear understanding of its evolution, current scope, and potential domains in the field of advertising. Thus, this current research is among the first to apply a bibliometric approach to clarify the main research streams analyzing advertising persuasion using neuroimaging. Particularly, this paper combines a comprehensive review with performance analysis tools of 203 papers published between 1986 and 2019 in outlets indexed by the ISI Web of Science database. Our findings describe the research tools, journals, and themes that are worth considering in future research. The current study also provides an agenda for future research and therefore constitutes a starting point for advertising academics and professionals intending to use neuroimaging techniques.

scholarly journals Multi-view feature selection for identifying gene markers: a diversified biological data driven approach

2020 ◽  
Vol 21 (S18) ◽  
Author(s):  
Sudipta Acharya ◽  
Laizhong Cui ◽  
Yi Pan
Keyword(s):  
Gene Expression ◽  
Feature Selection ◽  
Gene Selection ◽  
Marker Gene ◽  
Biological Data ◽  
Protein Interaction Data ◽  
Marker Genes ◽  
Data Sets ◽  
Gene Markers ◽  
Multi Objective

Abstract Background In recent years, to investigate challenging bioinformatics problems, the utilization of multiple genomic and proteomic sources has become immensely popular among researchers. One such issue is feature or gene selection and identifying relevant and non-redundant marker genes from high dimensional gene expression data sets. In that context, designing an efficient feature selection algorithm exploiting knowledge from multiple potential biological resources may be an effective way to understand the spectrum of cancer or other diseases with applications in specific epidemiology for a particular population. Results In the current article, we design the feature selection and marker gene detection as a multi-view multi-objective clustering problem. Regarding that, we propose an Unsupervised Multi-View Multi-Objective clustering-based gene selection approach called UMVMO-select. Three important resources of biological data (gene ontology, protein interaction data, protein sequence) along with gene expression values are collectively utilized to design two different views. UMVMO-select aims to reduce gene space without/minimally compromising the sample classification efficiency and determines relevant and non-redundant gene markers from three cancer gene expression benchmark data sets. Conclusion A thorough comparative analysis has been performed with five clustering and nine existing feature selection methods with respect to several internal and external validity metrics. Obtained results reveal the supremacy of the proposed method. Reported results are also validated through a proper biological significance test and heatmap plotting.

scholarly journals Selection of reference genes for gene expression analysis in Liriodendron hybrids’ somatic embryogenesis and germinative tissues

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tingting Li ◽  
Weigao Yuan ◽  
Shuai Qiu ◽  
Jisen Shi
Keyword(s):  
Gene Expression ◽  
Somatic Embryogenesis ◽  
Reference Genes ◽  
Gene Selection ◽  
Elongation Factor ◽  
Reverse Transcription Pcr ◽  
Expression Of Genes ◽  
Suitable Reference ◽  
Functional Analyses ◽  
Elongation Factor 1

AbstractThe differential expression of genes is crucial for plant somatic embryogenesis (SE), and the accurate quantification of gene expression levels relies on choosing appropriate reference genes. To select the most suitable reference genes for SE studies, 10 commonly used reference genes were examined in synchronized somatic embryogenic and subsequent germinative cultures of Liriodendron hybrids by using quantitative real-time reverse transcription PCR. Four popular normalization algorithms: geNorm, NormFinder, Bestkeeper and Delta-Ct were used to select and validate the suitable reference genes. The results showed that elongation factor 1-gamma, histone H1 linker protein, glyceraldehyde-3-phosphate dehydrogenase and α-tubulin were suitable for SE tissues, while elongation factor 1-gamma and actin were best for the germinative organ tissues. Our work will benefit future studies of gene expression and functional analyses of SE in Liriodendron hybrids. It is also serves as a guide of reference gene selection in early embryonic gene expression analyses for other woody plant species.

scholarly journals Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity

2021 ◽  
Vol 11 (13) ◽  
pp. 5859
Author(s):  
Fernando N. Santos-Navarro ◽  
Yadira Boada ◽  
Alejandro Vignoni ◽  
Jesús Picó
Keyword(s):  
Gene Expression ◽  
Gene Transcription ◽  
Performance Metrics ◽  
Cell Mass ◽  
Gene Copy ◽  
Substrate Uptake ◽  
Promoter Strength ◽  
Expression Levels ◽  
Trade Offs ◽  
Wide Range

Optimal gene expression is central for the development of both bacterial expression systems for heterologous protein production, and microbial cell factories for industrial metabolite production. Our goal is to fulfill industry-level overproduction demands optimally, as measured by the following key performance metrics: titer, productivity rate, and yield (TRY). Here we use a multiscale model incorporating the dynamics of (i) the cell population in the bioreactor, (ii) the substrate uptake and (iii) the interaction between the cell host and expression of the protein of interest. Our model predicts cell growth rate and cell mass distribution between enzymes of interest and host enzymes as a function of substrate uptake and the following main lab-accessible gene expression-related characteristics: promoter strength, gene copy number and ribosome binding site strength. We evaluated the differential roles of gene transcription and translation in shaping TRY trade-offs for a wide range of expression levels and the sensitivity of the TRY space to variations in substrate availability. Our results show that, at low expression levels, gene transcription mainly defined TRY, and gene translation had a limited effect; whereas, at high expression levels, TRY depended on the product of both, in agreement with experiments in the literature.

scholarly journals Effect of directly acting anti-viral agents on immunological imprints in chronic HCV-4a patients: interleukin-10 and vascular endothelial growth factor genes expression level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Iman S. Naga ◽  
Amel Abdel Fattah Kamel ◽  
Said Ahmed Ooda ◽  
Hadeer Muhammad Fath Elbab ◽  
Rania Mohamed El-Sharkawy
Keyword(s):  
Gene Expression ◽  
Vascular Endothelial Growth Factor ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Growth Factor ◽  
Angiogenic Factor ◽  
Vascular Endothelial ◽  
Wide Range ◽  
Chronic Hcv ◽  
Endothelial Growth Factor

Abstract Background Hepatitis C virus infection is a global health challenge with Egypt being one of the highly affected countries. IL-10 has been suggested as a suitable marker to assess necroinflammation and to monitor the progression of liver damage. Vascular endothelial growth factor (VEGF) is a potent angiogenic factor playing a central role in many physiological as well as pathological processes. Several factors can be predictive of the response to treatment and achievement of SVR; some of which are host-related, and others are virus-related. The gene expression of IL-10 and VEGF have multiple effects for treatment response. The aim of the present work was to study the effect of treatment with directly acting agents (DAA) on the expression of VEGF and IL-10 genes in chronic hepatitis C virus-infected Egyptian genotype-4a patients. Twenty-five HCV subjects where evaluated for IL-10 and VEGF gene expression before and after treatment with DAA. Results IL-10 expression was downregulated in 92% of the cases. VEGF expression was heterogeneous showing spreading of values along a wide range with 64% of the cases being downregulated. Conclusion DAAs do not completely reverse the immunological imprints established upon chronic HCV infection.

Sign in / Sign up

Export Citation Format

Share Document