scholarly journals miR2Diabetes: A Literature-Curated Database of microRNA Expression Patterns, in Diabetic Microvascular Complications

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 784 ◽  
Author(s):  
Sungjin Park ◽  
SeongRyeol Moon ◽  
Kiyoung Lee ◽  
Ie Byung Park ◽  
Dae Ho Lee ◽  
...  
Keyword(s):  
Association Studies ◽  
Microvascular Complications ◽  
Expression Patterns ◽  
Disease Model ◽  
Model Organisms ◽  
Web Interface ◽  
Diabetic Microvascular Complications ◽  
User Friendly ◽  
Rats And Mice ◽  
Kidney Liver

microRNAs (miRNAs) have been established as critical regulators of the pathogenesis of diabetes mellitus (DM), and diabetes microvascular complications (DMCs). However, manually curated databases for miRNAs, and DM (including DMCs) association studies, have yet to be established. Here, we constructed a user-friendly database, “miR2Diabetes,” equipped with a graphical web interface for simple browsing or searching manually curated annotations. The annotations in our database cover 14 DM and DMC phenotypes, involving 156 miRNAs, by browsing diverse sample origins (e.g., blood, kidney, liver, and other tissues). Additionally, we provide miRNA annotations for disease-model organisms (including rats and mice), of DM and DMCs, for the purpose of improving knowledge of the biological complexity of these pathologies. We assert that our database will be a comprehensive resource for miRNA biomarker studies, as well as for prioritizing miRNAs for functional validation, in DM and DMCs, with likely extension to other diseases.

scholarly journals SpatialDB: a database for spatially resolved transcriptomes

2019 ◽  
Author(s):  
Zhen Fan ◽  
Runsheng Chen ◽  
Xiaowei Chen
Keyword(s):  
Spatial Organization ◽  
Expression Patterns ◽  
Functional Enrichment ◽  
Web Interface ◽  
Current Version ◽  
Transcriptomic Data ◽  
Spatially Resolved ◽  
User Friendly ◽  
New Strategies

Abstract Spatially resolved transcriptomic techniques allow the characterization of spatial organization of cells in tissues, which revolutionize the studies of tissue function and disease pathology. New strategies for detecting spatial gene expression patterns are emerging, and spatially resolved transcriptomic data are accumulating rapidly. However, it is not convenient for biologists to exploit these data due to the diversity of strategies and complexity in data analysis. Here, we present SpatialDB, the first manually curated database for spatially resolved transcriptomic techniques and datasets. The current version of SpatialDB contains 24 datasets (305 sub-datasets) from 5 species generated by 8 spatially resolved transcriptomic techniques. SpatialDB provides a user-friendly web interface for visualization and comparison of spatially resolved transcriptomic data. To further explore these data, SpatialDB also provides spatially variable genes and their functional enrichment annotation. SpatialDB offers a repository for research community to investigate the spatial cellular structure of tissues, and may bring new insights into understanding the cellular microenvironment in disease. SpatialDB is freely available at https://www.spatialomics.org/SpatialDB.

scholarly journals Diabetes Microvascular Complications: An Overview of Epigenetic Modifications

2020 ◽  
Author(s):  
Neerja Aggarwal ◽  
Pawan Kumar Kare
Keyword(s):  
Association Studies ◽  
Microvascular Complications ◽  
Vascular Complications ◽  
Polyol Pathway ◽  
Epigenetic Modifications ◽  
Epigenetic Mechanisms ◽  
Diabetic Vascular Complications ◽  
Current Scenario ◽  
History Of ◽  
Diabetic Microvascular Complications

Diabetic nephropathy (DN) and diabetic retinopathy (DR) are two serious and long-standing microvascular complications of type 2 diabetes mellitus (T2DM) whose burden is increasing worldwide due to increasing burden of T2DM. Several factors which may predispose to the development of DN and DR are persistent hyperglycemia and its consequences such as formation of advanced glycation end products (AGEs), activation of hexosamine pathway, polyol pathway, uncontrolled blood pressure, increased oxidative stress, age, family history of kidney disease or hypertension, ethnic background etc. However, the pathophysiological mechanisms of these complications are complicated and not completely understood yet. Hence it is the demand to discover newer approaches to treat these devastating complications completely. Recently, various epigenetic modifications, which are the transmissible alterations in the expressions of a gene, are being studied to understand the pathophysiology of diabetic vascular complications. Metabolic and environmental factors may lead to dysregulated epigenetic mechanisms which might further affect the chromatin structure and related expressions of a gene, which may lead to diabetes-associated complications. Therefore, it is the need to explore its role in vascular complications in the current scenario. In this chapter, various epigenetic studies with regard to DN and DR, epigenome-wide association studies (EWAS) approach, and starting clinical material for such studies have been discussed. We have also summarized the better understanding of epigenetic alterations and their role in microvascular complications of diabetes through this chapter. The better understanding of epigenetic mechanisms and their role in diabetic microvascular complications could be used in clinical management of DN as well as DR or could be helpful to improve the available therapies for these complications.

scholarly journals A Systematic Comparison of Differential Analysis Methods for CyTOF Data

2021 ◽  
Author(s):  
Lis Arend ◽  
Judith Bernett ◽  
Quirin Manz ◽  
Melissa Klug ◽  
Olga Lazareva ◽  
...  
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Differential Analysis ◽  
Web Interface ◽  
Analysis Methods ◽  
Shiny App ◽  
R Shiny ◽  
User Friendly

Cytometry techniques are widely used to discover cellular characteristics at single-cell resolution. Many data analysis methods for cytometry data focus solely on identifying subpopulations via clustering and testing for differential cell abundance. For differential expression analysis of markers between conditions, only few tools exist. These tools either reduce the data distribution to medians, discarding valuable information, or have underlying assumptions that may not hold for all expression patterns. Here, we systematically evaluated existing and novel approaches for differential expression analysis on real and simulated CyTOF data. We found that methods using median marker expressions compute fast and reliable results when the data is not strongly zero-inflated. Methods using all data detect changes in strongly zero-inflated markers, but partially suffer from overprediction or cannot handle big datasets. We present a new method, CyEMD, based on calculating the Earth Mover's Distance between expression distributions that can handle strong zero-inflation without being too sensitive. Additionally, we developed CYANUS, a user-friendly R Shiny App allowing the user to analyze cytometry data with state-of-the-art tools, including well-performing methods from our comparison. A public web interface is available at https://exbio.wzw.tum.de/cyanus/.

scholarly journals Genome-wide characterization of 2-oxoglutarate and Fe(II)-dependent dioxygenase family genes in tomato during growth cycle and their roles in metabolism

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shuo Wei ◽  
Wen Zhang ◽  
Rao Fu ◽  
Yang Zhang
Keyword(s):  
Metabolic Pathways ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Growth Cycle ◽  
Model Organisms ◽  
Gibberellin Biosynthesis ◽  
Type I ◽  
Multiple Model ◽  
Genome Wide ◽  
Tomato Growth

Abstract Background 2-Oxoglutarate and Fe(II)-dependent dioxygenases (2ODDs) belong to the 2-oxoglutarate-dependent dioxygenase (2OGD) superfamily and are involved in various vital metabolic pathways of plants at different developmental stages. These proteins have been extensively investigated in multiple model organisms. However, these enzymes have not been systematically analyzed in tomato. In addition, type I flavone synthase (FNSI) belongs to the 2ODD family and contributes to the biosynthesis of flavones, but this protein has not been characterized in tomato. Results A total of 131 2ODDs from tomato were identified and divided into seven clades by phylogenetic classification. The Sl2ODDs in the same clade showed similar intron/exon distributions and conserved motifs. The Sl2ODDs were unevenly distributed across the 12 chromosomes, with different expression patterns among major tissues and at different developmental stages of the tomato growth cycle. We characterized several Sl2ODDs and their expression patterns involved in various metabolic pathways, such as gibberellin biosynthesis and catabolism, ethylene biosynthesis, steroidal glycoalkaloid biosynthesis, and flavonoid metabolism. We found that the Sl2ODD expression patterns were consistent with their functions during the tomato growth cycle. These results indicated the significance of Sl2ODDs in tomato growth and metabolism. Based on this genome-wide analysis of Sl2ODDs, we screened six potential FNSI genes using a phylogenetic tree and coexpression analysis. However, none of them exhibited FNSI activity. Conclusions Our study provided a comprehensive understanding of the tomato 2ODD family and demonstrated the significant roles of these family members in plant metabolism. We also suggest that no FNSI genes in tomato contribute to the biosynthesis of flavones.

scholarly journals BREC: an R package/Shiny app for automatically identifying heterochromatin boundaries and estimating local recombination rates along chromosomes

2021 ◽  
Vol 22 (S6) ◽  
Author(s):  
Yasmine Mansour ◽  
Annie Chateau ◽  
Anna-Sophie Fiston-Lavier
Keyword(s):  
Data Quality ◽  
Data Science ◽  
Fruit Fly ◽  
R Package ◽  
Model Organisms ◽  
Data Quality Control ◽  
Recombination Rates ◽  
Functional Dynamics ◽  
Shiny App ◽  
User Friendly

Abstract Background Meiotic recombination is a vital biological process playing an essential role in genome's structural and functional dynamics. Genomes exhibit highly various recombination profiles along chromosomes associated with several chromatin states. However, eu-heterochromatin boundaries are not available nor easily provided for non-model organisms, especially for newly sequenced ones. Hence, we miss accurate local recombination rates necessary to address evolutionary questions. Results Here, we propose an automated computational tool, based on the Marey maps method, allowing to identify heterochromatin boundaries along chromosomes and estimating local recombination rates. Our method, called BREC (heterochromatin Boundaries and RECombination rate estimates) is non-genome-specific, running even on non-model genomes as long as genetic and physical maps are available. BREC is based on pure statistics and is data-driven, implying that good input data quality remains a strong requirement. Therefore, a data pre-processing module (data quality control and cleaning) is provided. Experiments show that BREC handles different markers' density and distribution issues. Conclusions BREC's heterochromatin boundaries have been validated with cytological equivalents experimentally generated on the fruit fly Drosophila melanogaster genome, for which BREC returns congruent corresponding values. Also, BREC's recombination rates have been compared with previously reported estimates. Based on the promising results, we believe our tool has the potential to help bring data science into the service of genome biology and evolution. We introduce BREC within an R-package and a Shiny web-based user-friendly application yielding a fast, easy-to-use, and broadly accessible resource. The BREC R-package is available at the GitHub repository https://github.com/GenomeStructureOrganization.

Power comparison of Cochran-Armitage trend test against allelic and genotypic tests in large-scale case-control genetic association studies

2016 ◽  
Vol 27 (9) ◽  
pp. 2657-2673 ◽  
Author(s):  
Mathieu Emily
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Disease Model ◽  
Trend Test ◽  
Genome Wide Association Studies ◽  
Power Functions ◽  
Power Comparison ◽  
Powerful Test ◽  
Armitage Trend Test ◽  
Mode Of Inheritance

The Cochran-Armitage trend test (CA) has become a standard procedure for association testing in large-scale genome-wide association studies (GWAS). However, when the disease model is unknown, there is no consensus on the most powerful test to be used between CA, allelic, and genotypic tests. In this article, we tackle the question of whether CA is best suited to single-locus scanning in GWAS and propose a power comparison of CA against allelic and genotypic tests. Our approach relies on the evaluation of the Taylor decompositions of non-centrality parameters, thus allowing an analytical comparison of the power functions of the tests. Compared to simulation-based comparison, our approach offers the advantage of simultaneously accounting for the multidimensionality of the set of features involved in power functions. Although power for CA depends on the sample size, the case-to-control ratio and the minor allelic frequency (MAF), our results first show that it is largely influenced by the mode of inheritance and a deviation from Hardy–Weinberg Equilibrium (HWE). Furthermore, when compared to other tests, CA is shown to be the most powerful test under a multiplicative disease model or when the single-nucleotide polymorphism largely deviates from HWE. In all other situations, CA lacks in power and differences can be substantial, especially for the recessive mode of inheritance. Finally, our results are illustrated by the comparison of the performances of the statistics in two genome scans.

N-acetylglucosamine-phosphate mutase genotype and diabetic microvascular complications

2003 ◽  
Vol 20 (5) ◽  
pp. 419-420 ◽  
Author(s):  
H. Pang ◽  
Y. Koda ◽  
S.-I. Yamagishi ◽  
S. Amano ◽  
Y. Inagaki ◽  
...  
Keyword(s):  
Microvascular Complications ◽  
Diabetic Microvascular Complications

scholarly journals Age at menarche and the risk of diabetic microvascular complications in patients with type 1 diabetes

Diabetologia ◽  
2015 ◽  
Vol 59 (3) ◽  
pp. 472-480 ◽  
Author(s):  
Valma Harjutsalo ◽  
◽  
Christine Maric-Bilkan ◽  
Carol Forsblom ◽  
Per-Henrik Groop
Keyword(s):  
Type 1 Diabetes ◽  
Microvascular Complications ◽  
Age At Menarche ◽  
Diabetic Microvascular Complications

Association Between Serum Fibrinogen Levels and Diabetic Microvascular Complications in Type 2 Diabetes Mellitus

2007 ◽  
Vol 17 (6) ◽  
pp. 306-308 ◽  
Author(s):  
Huseyin Demirci ◽  
Husamettin Erdamar ◽  
Ayhan Karakoc ◽  
Fusun Balos Toruner ◽  
Mehmet Akif Ozturk ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Microvascular Complications ◽  
Diabetic Microvascular Complications
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