scholarly journals dbCNS: A New Database for Conserved Noncoding Sequences

2020 ◽  
Author(s):  
Jun Inoue ◽  
Naruya Saitou
Keyword(s):  
Phylogenetic Trees ◽  
Morphological Changes ◽  
Genetic Diseases ◽  
Nucleotide Polymorphisms ◽  
Test Analysis ◽  
Noncoding Sequences ◽  
Expression Control ◽  
Conserved Noncoding Sequences ◽  
Genome Scale ◽  
Keyword Searches

Abstract We developed dbCNS (http://yamasati.nig.ac.jp/dbcns), a new database for conserved noncoding sequences (CNSs). CNSs exist in many eukaryotes and are assumed to be involved in protein expression control. Version 1 of dbCNS, introduced here, includes a powerful and precise CNS identification pipeline for multiple vertebrate genomes. Mutations in CNSs may induce morphological changes and cause genetic diseases. For this reason, many vertebrate CNSs have been identified, with special reference to primate genomes. We integrated ∼6.9 million CNSs from many vertebrate genomes into dbCNS, which allows users to extract CNSs near genes of interest using keyword searches. In addition to CNSs, dbCNS contains published genome sequences of 161 species. With purposeful taxonomic sampling of genomes, users can employ CNSs as queries to reconstruct CNS alignments and phylogenetic trees, to evaluate CNS modifications, acquisitions, and losses, and to roughly identify species with CNSs having accelerated substitution rates. dbCNS also produces links to dbSNP for searching pathogenic single-nucleotide polymorphisms in human CNSs. Thus, dbCNS connects morphological changes with genetic diseases. A test analysis using 38 gnathostome genomes was accomplished within 30 s. dbCNS results can evaluate CNSs identified by other stand-alone programs using genome-scale data.

Conserved noncoding sequences are selectively constrained and not mutation cold spots

2005 ◽  
Vol 38 (2) ◽  
pp. 223-227 ◽  
Author(s):  
Jared A Drake ◽  
Christine Bird ◽  
James Nemesh ◽  
Daryl J Thomas ◽  
Christopher Newton-Cheh ◽  
...  
Keyword(s):  
Noncoding Sequences ◽  
Conserved Noncoding Sequences ◽  
Cold Spots

scholarly journals Pathogenesis and characteristics of large ameloblastoma of the jaw: a report of two rare cases

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110148
Author(s):  
Xue Qiao ◽  
Xing Niu ◽  
Jiayi Liu ◽  
Lijie Chen ◽  
Yan Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Epithelial Mesenchymal Transition ◽  
Morphological Changes ◽  
Molecular Evidence ◽  
Nucleotide Polymorphisms ◽  
Related Gene ◽  
Epithelial Tumor ◽  
Single Nucleotide ◽  
Mesenchymal Transition ◽  
Hras Gene

Ameloblastoma is a common odontogenic epithelial tumor that exhibits various biological behaviors, ranging from simple cystic expansion to aggressive solid masses characterized by local invasiveness, a high risk of recurrence, and even malignant transformation. We report on two cases of unusually large solid ameloblastomas. We detected epithelial–mesenchymal transition-related gene expression and HRAS gene single nucleotide polymorphisms, providing possible molecular evidence of mesenchymal morphological changes in ameloblastoma. The detailed analysis of the pathogenesis of these two cases of ameloblastoma may deepen our understanding of this rare disease and offer promising targets for future targeted therapy.

scholarly journals Conserved Noncoding Sequences Boost ADR1 and SP1 Regulated Human Swiprosin-1 Promoter Activity

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Ramesh P. Thylur ◽  
Sung Yong Ahn ◽  
Eunhea Jung ◽  
Chang-Duk Jun ◽  
Young-Min Hyun
Keyword(s):  
Promoter Activity ◽  
Noncoding Sequences ◽  
Conserved Noncoding Sequences

The SNP rs560426 Within ABCA4-ARHGAP29 Locus and the Risk of Nonsyndromic Oral Clefts

2020 ◽  
Vol 57 (6) ◽  
pp. 671-677 ◽  
Author(s):  
Yah-Huei Wu-Chou ◽  
Kuo-Ting Philip Chen ◽  
Yi-Chieh Lu ◽  
Yin-Ting Lin ◽  
Hsien-Fang Chang ◽  
...  
Keyword(s):  
Cleft Palate ◽  
Cleft Lip ◽  
Strong Association ◽  
Nucleotide Polymorphisms ◽  
Test Analysis ◽  
Oral Clefts ◽  
The Family ◽  
Abca4 Gene ◽  
Family Based ◽  
New Evidence

Objective: Nonsyndromic oral clefts are common birth defect with complex etiology. In the present study, we attempt to further validate the possible role for ABCA4 and ARHGAP29 in the susceptibility to nonsyndromic oral clefts. Design: We performed allelic transmission disequilibrium test analysis, on 10 eligible single nucleotide polymorphisms (SNPs) and SNP haplotypes using the Family-Based Association Test. Participants: The study sample consisted of 334 case–parent trios of nonsyndromic oral clefts from Taiwanese population, separated into nonsyndromic cleft lip with or without cleft palate (NSCL/P) and nonsyndromic cleft palate only (NSCPO) groups. Results: We found only the SNP rs560426 within the ABCA4 gene showed strong association with NSCPO ( P = .03498; Permuted P = .05382). No association between other 9 selected SNPs in ABCA4-ARHGAP29 region and the risk of nonsyndromic oral clefts was found. For the haplotype analyses, we found only haplotype T-C (rs570926 and rs3789431) in ABCA4 block 2 showed significant association with nonsyndromic NSCL/P in these Taiwanese trios. Conclusions: We used a family-based analysis in 334 Taiwanese case–parent trios to validate the possible role for ABCA4 and ARHGAP29 in the susceptibility to nonsyndromic oral clefts. This study provides a new evidence for an association between the intron variant rs560426 within ABCA4 and nonsyndromic cleft palate which may contribute their regulatory role in craniofacial development.

scholarly journals Genome-scale reconstructions to assess metabolic phylogeny and organism clustering

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0240953
Author(s):  
Christian Schulz ◽  
Eivind Almaas
Keyword(s):  
Phylogenetic Trees ◽  
Metabolic Networks ◽  
Sulfur Metabolism ◽  
Phylogenetic Analyses ◽  
Tree Of Life ◽  
Significant Heterogeneity ◽  
Metabolic Reaction ◽  
High Quality ◽  
Conserved Genes ◽  
Genome Scale

Approaches for systematizing information of relatedness between organisms is important in biology. Phylogenetic analyses based on sets of highly conserved genes are currently the basis for the Tree of Life. Genome-scale metabolic reconstructions contain high-quality information regarding the metabolic capability of an organism and are typically restricted to metabolically active enzyme-encoding genes. While there are many tools available to generate draft reconstructions, expert-level knowledge is still required to generate and manually curate high-quality genome-scale metabolic models and to fill gaps in their reaction networks. Here, we use the tool AutoKEGGRec to construct 975 genome-scale metabolic draft reconstructions encoded in the KEGG database without further curation. The organisms are selected across all three domains, and their metabolic networks serve as basis for generating phylogenetic trees. We find that using all reactions encoded, these metabolism-based comparisons give rise to a phylogenetic tree with close similarity to the Tree of Life. While this tree is quite robust to reasonable levels of noise in the metabolic reaction content of an organism, we find a significant heterogeneity in how much noise an organism may tolerate before it is incorrectly placed in the tree. Furthermore, by using the protein sequences for particular metabolic functions and pathway sets, such as central carbon-, nitrogen-, and sulfur-metabolism, as basis for the organism comparisons, we generate highly specific phylogenetic trees. We believe the generation of phylogenetic trees based on metabolic reaction content, in particular when focused on specific functions and pathways, could aid the identification of functionally important metabolic enzymes and be of value for genome-scale metabolic modellers and enzyme-engineers.

scholarly journals Enriching human interactome with functional mutations to detect high-impact network modules underlying complex diseases

2019 ◽  
Author(s):  
Hongzhu Cui ◽  
Suhas Srinivasan ◽  
Dmitry Korkin
Keyword(s):  
Biological Networks ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Genetic Diseases ◽  
Detection Methods ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Human Interactome ◽  
Module Detection ◽  
Disease Module

AbstractProgress in high-throughput -omics technologies moves us one step closer to the datacalypse in life sciences. In spite of the already generated volumes of data, our knowledge of the molecular mechanisms underlying complex genetic diseases remains limited. Increasing evidence shows that biological networks are essential, albeit not sufficient, for the better understanding of these mechanisms. The identification of disease-specific functional modules in the human interactome can provide a more focused insight into the mechanistic nature of the disease. However, carving a disease network module from the whole interactome is a difficult task. In this paper, we propose a computational framework, DIMSUM, which enables the integration of genome-wide association studies (GWAS), functional effects of mutations, and protein-protein interaction (PPI) network to improve disease module detection. Specifically, our approach incorporates and propagates the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) on PPIs to implicate the genes that are most likely influenced by the disruptive mutations, and to identify the module with the greatest impact. Comparison against state-of-the-art seed-based module detection methods shows that our approach could yield modules that are biologically more relevant and have stronger association with the studied disease. We expect for our method to become a part of the common toolbox for disease module analysis, facilitating discovery of new disease markers.

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