scholarly journals Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast

2016 ◽  
Author(s):  
Daniel C. Jeffares ◽  
Clemency Jolly ◽  
Mimoza Hoti ◽  
Doug Speed ◽  
Liam Shaw ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reproductive Isolation ◽  
Cell Shape ◽  
Quantitative Traits ◽  
Phenotypic Diversity ◽  
Copy Number Variants ◽  
Nucleotide Polymorphisms ◽  
Structural Variations ◽  
Single Nucleotide ◽  
Sugar Utilization

AbstractLarge structural variations (SVs) in the genome are harder to identify than smaller genetic variants but may substantially contribute to phenotypic diversity and evolution. Here we analyze the effects of SVs on gene expression, quantitative traits, and intrinsic reproductive isolation in the yeast Schizosaccharomyces pombe. We establish a high-quality curated catalog of SVs in the genomes of a worldwide library of S. pombe strains, including duplications, deletions, inversions and translocations. We show that copy number variants (CNVs) frequently segregate within closely related clonal populations, are weakly linked to single nucleotide polymorphisms (SNPs), and show other genetic signals consistent with rapid turnover. These transient CNVs produce stoichiometric effects on gene expression both within and outside the duplicated regions. CNVs make substantial contributions to quantitative traits such as cell shape, cell growth under diverse conditions, sugar utilization in winemaking, whereas rearrangements are strongly associated with reproductive isolation. Collectively, these findings have broad implications for evolution and for our understanding of quantitative traits including complex human diseases.

The genomic basis of medicine

2020 ◽  
pp. 218-235
Author(s):  
Paweł Stankiewicz ◽  
James R. Lupski
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Complex Traits ◽  
Copy Number ◽  
Clinical Medicine ◽  
Association Studies ◽  
Copy Number Variants ◽  
Nucleotide Polymorphisms ◽  
Structural Variations ◽  
Single Nucleotide ◽  
Practical Applications

The first phase of the studies on genetic variation in humans has been focused on single nucleotide polymorphisms and common variation. The large number of single nucleotide polymorphisms identified has enabled successful genome-wide association studies for disease susceptibility risk of complex traits (e.g. diabetes and cancer), but for the most part has had limited practical applications in clinical medicine. This chapter examines the recent technological developments which have enabled a higher-resolution analysis of the human genome and its extensive submicroscopic structural variation, including copy-number variants. Copy-number variants involving dosage-sensitive genes result in several diseases and contribute to human diversity and evolution. An emerging group of genetic diseases have been described that result from DNA rearrangements (e.g. copy-number variants and other structural variations including copy-number neutral inversions and translocations), rather than from single nucleotide changes.

scholarly journals The role of 25-hydroxyvitamin-D3 and vitamin D receptor gene in human periodontal ligament fibroblasts as response to orthodontic compressive strain: an in vitro study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Erika Calvano Küchler ◽  
Agnes Schröder ◽  
Vinicius Broska Teodoro ◽  
Ute Nazet ◽  
Rafaela Scariot ◽  
...  
Keyword(s):  
Gene Expression ◽  
Vitamin D ◽  
Single Nucleotide Polymorphisms ◽  
Periodontal Ligament ◽  
Compressive Strain ◽  
Nucleotide Polymorphisms ◽  
Periodontal Ligament Fibroblasts ◽  
Single Nucleotide ◽  
Cox 2

Abstract Background This study aimed to investigate, if different physiological concentrations of vitamin D (25(OH)D3) and single nucleotide polymorphisms in vitamin D receptor (VDR) gene have an impact on gene expression in human periodontal ligament (hPDL) fibroblasts induced by simulated orthodontic compressive strain. Methods A pool of hPDL fibroblasts was treated in absence or presence of 25(OH)D3 in 3 different concentrations (10, 40 and 60 ng/ml). In order to evaluate the role of single nucleotide polymorphisms in the VDR gene, hPDL fibroblasts from 9 patients were used and treated in absence or presence of 40 ng/ml 25(OH)D3. Each experiment was performed with and without simulated orthodontic compressive strain. Real-time PCR was used for gene expression and allelic discrimination analysis. Relative expression of dehydrocholesterol reductase (DHCR7), Sec23 homolog A, amidohydrolase domain containing 1 (AMDHD1), vitamin D 25-hydroxylase (CYP2R1), Hydroxyvitamin D-1-α hydroxylase, receptor activator of nuclear factor-κB ligand (RANKL), osteoprotegerin (OPG), cyclooxygenase-2 (COX-2) and interleukin-6 (IL6) was assessed. Three single nucleotide polymorphisms in VDR were genotyped. Parametric or non-parametric tests were used with an alpha of 5%. Results RANKL, RANKL:OPG ratio, COX-2, IL-6, DHCR7, CYP2R1 and AMDHD1 were differentially expressed during simulated orthodontic compressive strain (p < 0.05). The RANKL:OPG ratio was downregulated by all concentrations (10 ng/ml, 40 ng/ml and 60 ng/ml) of 25(OH)D3 (mean = 0.96 ± 0.68, mean = 1.61 ± 0.66 and mean = 1.86 ± 0.78, respectively) in comparison to the control (mean 2.58 ± 1.16) (p < 0.05). CYP2R1 gene expression was statistically modulated by the different 25(OH)D3 concentrations applied (p = 0.008). Samples from individuals carrying the GG genotype in rs739837 presented lower VDR mRNA expression and samples from individuals carrying the CC genotype in rs7975232 presented higher VDR mRNA expression (p < 0.05). Conclusions Simulated orthodontic compressive strain and physiological concentrations of 25(OH)D3 seem to regulate the expression of orthodontic tooth movement and vitamin-D-related genes in periodontal ligament fibroblasts in the context of orthodontic compressive strain. Our study also suggests that single nucleotide polymorphisms in the VDR gene regulate VDR expression in periodontal ligament fibroblasts in the context of orthodontic compressive strain.

scholarly journals Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

2016 ◽  
Vol 283 (1835) ◽  
pp. 20160569 ◽  
Author(s):  
M. E. Goddard ◽  
K. E. Kemper ◽  
I. M. MacLeod ◽  
A. J. Chamberlain ◽  
B. J. Hayes
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Crop Breeding ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Phenotype Identification

Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.

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 TADA – a Machine Learning Tool for Functional Annotation based Prioritisation of Putative Pathogenic CNVs

2020 ◽  
Author(s):  
J. Hertzberg ◽  
S. Mundlos ◽  
M. Vingron ◽  
G. Gallone
Keyword(s):  
Machine Learning ◽  
Functional Annotation ◽  
Copy Number Variants ◽  
Enrichment Analysis ◽  
Computational Prediction ◽  
Nucleotide Polymorphisms ◽  
Automated Classification ◽  
Single Nucleotide ◽  
Pathogenic Cnvs ◽  
Disease Impact

AbstractThe computational prediction of disease-associated genetic variation is of fundamental importance for the genomics, genetics and clinical research communities. Whereas the mechanisms and disease impact underlying coding single nucleotide polymorphisms (SNPs) and small Insertions/Deletions (InDels) have been the focus of intense study, little is known about the corresponding impact of structural variants (SVs), which are challenging to detect, phase and interpret. Few methods have been developed to prioritise larger chromosomal alterations such as Copy Number Variants (CNVs) based on their pathogenicity. We address this issue with TADA, a method to prioritise pathogenic CNVs through manual filtering and automated classification, based on an extensive catalogue of functional annotation supported by rigorous enrichment analysis. We demonstrate that our machine-learning classifiers for deletions and duplications are able to accurately predict pathogenic CNVs (AUC: 0.8042 and 0.7869, respectively) and produce a well-calibrated pathogenicity score. The combination of enrichment analysis and classifications suggests that prioritisation of pathogenic CNVs based on functional annotation is a promising approach to support clinical diagnostic and to further the understanding of mechanisms that control the disease impact of larger genomic alterations.

scholarly journals Single Nucleotide Polymorphisms at a Distance from Aryl Hydrocarbon Receptor (AHR) Binding Sites Influence AHR Ligand–Dependent Gene Expression

2019 ◽  
Vol 47 (9) ◽  
pp. 983-994 ◽  
Author(s):  
Drew R. Neavin ◽  
Jeong-Heon Lee ◽  
Duan Liu ◽  
Zhenqing Ye ◽  
Hu Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Nucleotide Polymorphisms ◽  
Aryl Hydrocarbon Receptor ◽  
Binding Sites ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Aryl Hydrocarbon

scholarly journals simuG: a general-purpose genome simulator

2019 ◽  
Vol 35 (21) ◽  
pp. 4442-4444 ◽  
Author(s):  
Jia-Xing Yue ◽  
Gianni Liti
Keyword(s):  
Copy Number Variants ◽  
General Purpose ◽  
Supplementary Information ◽  
Nucleotide Polymorphisms ◽  
Bioinformatics Analyses ◽  
Full Spectrum ◽  
Single Nucleotide ◽  
Genomic Variants ◽  
Wide Range ◽  
Simulation Based

Abstract Summary Simulated genomes with pre-defined and random genomic variants can be very useful for benchmarking genomic and bioinformatics analyses. Here we introduce simuG, a lightweight tool for simulating the full-spectrum of genomic variants (single nucleotide polymorphisms, Insertions/Deletions, copy number variants, inversions and translocations) for any organisms (including human). The simplicity and versatility of simuG make it a unique general-purpose genome simulator for a wide-range of simulation-based applications. Availability and implementation Code in Perl along with user manual and testing data is available at https://github.com/yjx1217/simuG. This software is free for use under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online.

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