Single-nucleotide variations in the genes encoding the mitochondrial Hsp60/Hsp10 chaperone system and their disease-causing potential

Abstract Glycoside hydrolases (GHs) are found in all domains of life, and at least 87 distinct genes encoding proteins related to GHs are found in the human genome. GHs serve diverse functions from digestion of dietary polysaccharides to breakdown of intracellular oligosaccharides, glycoproteins, proteoglycans and glycolipids. Congenital disorders of GHs (CDGHs) represent more than 30 rare diseases caused by mutations in one of the GH genes. We previously used whole-exome sequencing of a homogenous Danish population of almost 2000 individuals to probe the incidence of deleterious mutations in the human glycosyltransferases (GTs) and developed a mutation map of human GT genes (GlyMAP-I). While deleterious disease-causing mutations in the GT genes were very rare, and in many cases lethal, we predicted deleterious mutations in GH genes to be less rare and less severe given the higher incidence of CDGHs reported worldwide. To probe the incidence of GH mutations, we constructed a mutation map of human GH-related genes (GlyMAP-II) using the Danish WES data, and correlating this with reported disease-causing mutations confirmed the higher prevalence of disease-causing mutations in several GH genes compared to GT genes. We identified 76 novel nonsynonymous single-nucleotide variations (nsSNVs) in 32 GH genes that have not been associated with a CDGH phenotype, and we experimentally validated two novel potentially damaging nsSNVs in the congenital sucrase-isomaltase deficiency gene, SI. Our study provides a global view of human GH genes and disease-causing mutations and serves as a discovery tool for novel damaging nsSNVs in CDGHs.

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Genetic Variants in Smoking-Related Genes in Two Smoking Cessation Programs: A Cross-Sectional Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18126597 ◽

2021 ◽

Vol 18 (12) ◽

pp. 6597

Author(s):

Gloria Pérez-Rubio ◽

Luis Alberto López-Flores ◽

Ana Paula Cupertino ◽

Francisco Cartujano-Barrera ◽

Luz Myriam Reynales-Shigematsu ◽

...

Keyword(s):

Smoking Cessation ◽

Cross Sectional Study ◽

Nucleotide Polymorphisms ◽

Sectional Study ◽

Cross Sectional ◽

Single Nucleotide ◽

Genotype Frequencies ◽

Quitting Smoking ◽

Genes Encoding ◽

Genomic Regions

Previous studies have identified variants in genes encoding proteins associated with the degree of addiction, smoking onset, and cessation. We aimed to describe thirty-one single nucleotide polymorphisms (SNPs) in seven candidate genomic regions spanning six genes associated with tobacco-smoking in a cross-sectional study from two different interventions for quitting smoking: (1) thirty-eight smokers were recruited via multimedia to participate in e-Decídete! program (e-Dec) and (2) ninety-four attended an institutional smoking cessation program on-site. SNPs genotyping was done by real-time PCR using TaqMan probes. The analysis of alleles and genotypes was carried out using the EpiInfo v7. on-site subjects had more years smoking and tobacco index than e-Dec smokers (p < 0.05, both); in CYP2A6 we found differences in the rs28399433 (p < 0.01), the e-Dec group had a higher frequency of TT genotype (0.78 vs. 0.35), and TG genotype frequency was higher in the on-site group (0.63 vs. 0.18), same as GG genotype (0.03 vs. 0.02). Moreover, three SNPs in NRXN1, two in CHRNA3, and two in CHRNA5 had differences in genotype frequencies (p < 0.01). Cigarettes per day were different (p < 0.05) in the metabolizer classification by CYP2A6 alleles. In conclusion, subjects attending a mobile smoking cessation intervention smoked fewer cigarettes per day, by fewer years, and by fewer cumulative pack-years. There were differences in the genotype frequencies of SNPs in genes related to nicotine metabolism and nicotine dependence. Slow metabolizers smoked more cigarettes per day than intermediate and normal metabolizers.

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Cytosine and adenine deaminase base-editors induce broad and nonspecific changes in gene expression and splicing

Communications Biology ◽

10.1038/s42003-021-02406-5 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Jiao Fan ◽

Yige Ding ◽

Chao Ren ◽

Ziguo Song ◽

Jie Yuan ◽

...

Keyword(s):

Gene Expression ◽

Double Strand Breaks ◽

Great Promise ◽

Single Nucleotide ◽

Strand Breaks ◽

Dna Base ◽

Target Dna ◽

Single Nucleotide Variations ◽

Adenine Deaminase ◽

Target Rna

AbstractCytosine or adenine base editors (CBEs or ABEs) hold great promise in therapeutic applications because they enable the precise conversion of targeted base changes without generating of double-strand breaks. However, both CBEs and ABEs induce substantial off-target DNA editing, and extensive off-target RNA single nucleotide variations in transfected cells. Therefore, the potential effects of deaminases induced by DNA base editors are of great importance for their clinical applicability. Here, the transcriptome-wide deaminase effects on gene expression and splicing is examined. Differentially expressed genes (DEGs) and differential alternative splicing (DAS) events, induced by base editors, are identified. Both CBEs and ABEs generated thousands of DEGs and hundreds of DAS events. For engineered CBEs or ABEs, base editor-induced variants had little effect on the elimination of DEGs and DAS events. Interestingly, more DEGs and DAS events are observed as a result of over expressions of cytosine and adenine deaminases. This study reveals a previously overlooked aspect of deaminase effects in transcriptome-wide gene expression and splicing, and underscores the need to fully characterize such effects of deaminase enzymes in base editor platforms.

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Proteome-Wide Analysis of Single-Nucleotide Variations in the N-Glycosylation Sequon of Human Genes

PLoS ONE ◽

10.1371/journal.pone.0036212 ◽

2012 ◽

Vol 7 (5) ◽

pp. e36212 ◽

Cited By ~ 26

Author(s):

Raja Mazumder ◽

Krishna Sudeep Morampudi ◽

Mona Motwani ◽

Sona Vasudevan ◽

Radoslav Goldman

Keyword(s):

Single Nucleotide ◽

Human Genes ◽

Single Nucleotide Variations

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Characterization and risk association of polymorphisms in Aurora kinases A, B and C with genetic susceptibility to gastric cancer development

BMC Cancer ◽

10.1186/s12885-019-6133-z ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Aner Mesic ◽

Marija Rogar ◽

Petra Hudler ◽

Nurija Bilalovic ◽

Izet Eminovic ◽

...

Keyword(s):

Gastric Cancer ◽

Transcription Factors ◽

In Silico ◽

In Silico Analysis ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Mitotic Kinases ◽

Genes Encoding ◽

Silico Analysis ◽

Control Study

Abstract Background Single nucleotide polymorphisms (SNPs) in genes encoding mitotic kinases could influence development and progression of gastric cancer (GC). Methods Case-control study of nine SNPs in mitotic genes was conducted using qPCR. The study included 116 GC patients and 203 controls. In silico analysis was performed to evaluate the effects of polymorphisms on transcription factors binding sites. Results The AURKA rs1047972 genotypes (CT vs. CC: OR, 1.96; 95% CI, 1.05–3.65; p = 0.033; CC + TT vs. CT: OR, 1.94; 95% CI, 1.04–3.60; p = 0.036) and rs911160 (CC vs. GG: OR, 5.56; 95% CI, 1.24–24.81; p = 0.025; GG + CG vs. CC: OR, 5.26; 95% CI, 1.19–23.22; p = 0.028), were associated with increased GC risk, whereas certain rs8173 genotypes (CG vs. CC: OR, 0.60; 95% CI, 0.36–0.99; p = 0.049; GG vs. CC: OR, 0.38; 95% CI, 0.18–0.79; p = 0.010; CC + CG vs. GG: OR, 0.49; 95% CI, 0.25–0.98; p = 0.043) were protective. Association with increased GC risk was demonstrated for AURKB rs2241909 (GG + AG vs. AA: OR, 1.61; 95% CI, 1.01–2.56; p = 0.041) and rs2289590 (AC vs. AA: OR, 2.41; 95% CI, 1.47–3.98; p = 0.001; CC vs. AA: OR, 6.77; 95% CI, 2.24–20.47; p = 0.001; AA+AC vs. CC: OR, 4.23; 95% CI, 1.44–12.40; p = 0.009). Furthermore, AURKC rs11084490 (GG + CG vs. CC: OR, 1.71; 95% CI, 1.04–2.81; p = 0.033) was associated with increased GC risk. A combined analysis of five SNPs, associated with an increased GC risk, detected polymorphism profiles where all the combinations contribute to the higher GC risk, with an OR increased 1.51-fold for the rs1047972(CT)/rs11084490(CG + GG) to 2.29-fold for the rs1047972(CT)/rs911160(CC) combinations. In silico analysis for rs911160 and rs2289590 demonstrated that different transcription factors preferentially bind to polymorphic sites, indicating that AURKA and AURKB could be regulated differently depending on the presence of particular allele. Conclusions Our results revealed that AURKA (rs1047972 and rs911160), AURKB (rs2241909 and rs2289590) and AURKC (rs11084490) are associated with a higher risk of GC susceptibility. Our findings also showed that the combined effect of these SNPs may influence GC risk, thus indicating the significance of assessing multiple polymorphisms, jointly. The study was conducted on a less numerous but ethnically homogeneous Bosnian population, therefore further investigations in larger and multiethnic groups and the assessment of functional impact of the results are needed to strengthen the findings.

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Sequence variability ofChrysanthemum stunt viroidin different chrysanthemum cultivars

PeerJ ◽

10.7717/peerj.2933 ◽

2017 ◽

Vol 5 ◽

pp. e2933 ◽

Cited By ~ 4

Author(s):

Hoseong Choi ◽

Yeonhwa Jo ◽

Ju-Yeon Yoon ◽

Seung-Kook Choi ◽

Won Kyong Cho

Keyword(s):

Infectious Agents ◽

Sequence Variability ◽

Rt Pcr ◽

Genome Sequences ◽

Single Nucleotide ◽

Genomic Variations ◽

The Family ◽

Chrysanthemum Plant ◽

Single Nucleotide Variations ◽

Polymerase Chain

Viroids are the smallest infectious agents, and their genomes consist of a short single strand of RNA that does not encode any protein.Chrysanthemum stunt viroid(CSVd), a member of the familyPospiviroidae, causes chrysanthemum stunt disease. Here, we report the genomic variations of CSVd to understand the sequence variability of CSVd in different chrysanthemum cultivars. We randomly sampled 36 different chrysanthemum cultivars and examined the infection of CSVd in each cultivar by reverse transcription polymerase chain reaction (RT-PCR). Eleven cultivars were infected by CSVd. Cloning followed by Sanger sequencing successfully identified a total of 271 CSVd genomes derived from 12 plants from 11 cultivars. They were further classified into 105 CSVd variants. Each single chrysanthemum plant had a different set of CSVd variants. Moreover, different single plants from the same cultivar had different sets of CSVd variants but identical consensus genome sequences. A phylogenetic tree using 12 consensus genome sequences revealed three groups of CSVd genomes, while six different groups were defined by the phylogenetic analysis using 105 variants. Based on the consensus CSVd genome, by combining all variant sequences, we identified 99 single-nucleotide variations (SNVs) as well as three nucleotide positions showing high mutation rates. Although 99 SNVs were identified, most CSVd genomes in this study were derived from variant 1, which is identical to known CSVd SK1 showing pathogenicity.

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Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis

10.1101/2019.12.31.19016253 ◽

2020 ◽

Author(s):

Shuo Li ◽

Zorawar Noor ◽

Weihua Zeng ◽

Xiaohui Ni ◽

Zuyang Yuan ◽

...

Keyword(s):

Low Frequency ◽

Sequencing Data ◽

Real Patient ◽

Single Nucleotide ◽

Lung Cancer Patients ◽

Wide Range ◽

Single Nucleotide Variations ◽

Innovative Techniques ◽

Error Suppression ◽

Mutation Profiling

AbstractLiquid biopsy using cell-free DNA (cfDNA) is attractive for a wide range of clinical applications, including cancer detection, locating, and monitoring. However, developing these applications requires precise and sensitive calling of somatic single nucleotide variations (SNVs) from cfDNA sequencing data. To date, no SNV caller addresses all the special challenges of cfDNA to provide reliable results. Here we present cfSNV, a revolutionary somatic SNV caller with five innovative techniques to overcome and exploit the unique properties of cfDNA. cfSNV provides hierarchical mutation profiling, thanks to cfDNA’s complete coverage of the clonal landscape, and multi-layer error suppression. In both simulated datasets and real patient data, we demonstrate that cfSNV is superior to existing tools, especially for low-frequency somatic SNVs. We also show how the five novel techniques contribute to its performance. Further, we demonstrate a clinical application using cfSNV to select non-small-cell lung cancer patients for immunotherapy treatment.

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De novo genome assembly and single nucleotide variations for Soybean yellow common mosaic virus using soybean flower bud transcriptome data

Journal of Applied Biological Chemistry ◽

10.3839/jabc.2020.026 ◽

2020 ◽

Vol 63 (3) ◽

pp. 189-195

Author(s):

Yeonhwa Jo ◽

Hoseong Choi ◽

Sang-Min Kim ◽

Bong Choon Lee ◽

Won Kyong Cho

Keyword(s):

Mosaic Virus ◽

Genome Assembly ◽

De Novo ◽

Transcriptome Data ◽

Flower Bud ◽

De Novo Genome Assembly ◽

Single Nucleotide ◽

Single Nucleotide Variations

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Genotyping common, large structural variations in 5,202 genomes using pangenomes, the Giraffe mapper, and the vg toolkit

10.1101/2020.12.04.412486 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jouni Sirén ◽

Jean Monlong ◽

Xian Chang ◽

Adam M. Novak ◽

Jordan M. Eizenga ◽

...

Keyword(s):

Human Populations ◽

Structural Variations ◽

Single Nucleotide ◽

Human Genomes ◽

Genome Wide ◽

Sequence Graph ◽

Long Read ◽

Comparable Accuracy ◽

Single Nucleotide Variations ◽

Allelic Variations

ABSTRACTWe introduce Giraffe, a pangenome short read mapper that can efficiently map to a collection of haplotypes threaded through a sequence graph. Giraffe, part of the variation graph toolkit (vg)1, maps reads to thousands of human genomes at around the same speed BWA-MEM2 maps reads to a single reference genome, while maintaining comparable accuracy to VG-MAP, vg’s original mapper. We have developed efficient genotyping pipelines using Giraffe. We demonstrate improvements in genotyping for single nucleotide variations (SNVs), insertions and deletions (indels) and structural variations (SVs) genome-wide. We use Giraffe to genotype and phase 167 thousands structural variations ascertained from long read studies in 5,202 human genomes sequenced with short reads, including the complete 1000 Genomes Project dataset, at an average cost of $1.50 per sample. We determine the frequency of these variations in diverse human populations, characterize their complex allelic variations and identify thousands of expression quantitative trait loci (eQTLs) driven by these variations.

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A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism

Nature Communications ◽

10.1038/s41467-019-11581-3 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 24

Author(s):

Hongzhong Lu ◽

Feiran Li ◽

Benjamín J. Sánchez ◽

Zhengming Zhu ◽

Gang Li ◽

...

Keyword(s):

Model Organism ◽

Metabolic Model ◽

Phenotypic Traits ◽

Cell Factory ◽

Scale Level ◽

Single Nucleotide ◽

Multi Scale ◽

Yeast Strains ◽

Single Nucleotide Variations ◽

Genome Scale

Abstract Genome-scale metabolic models (GEMs) represent extensive knowledgebases that provide a platform for model simulations and integrative analysis of omics data. This study introduces Yeast8 and an associated ecosystem of models that represent a comprehensive computational resource for performing simulations of the metabolism of Saccharomyces cerevisiae––an important model organism and widely used cell-factory. Yeast8 tracks community development with version control, setting a standard for how GEMs can be continuously updated in a simple and reproducible way. We use Yeast8 to develop the derived models panYeast8 and coreYeast8, which in turn enable the reconstruction of GEMs for 1,011 different yeast strains. Through integration with enzyme constraints (ecYeast8) and protein 3D structures (proYeast8DB), Yeast8 further facilitates the exploration of yeast metabolism at a multi-scale level, enabling prediction of how single nucleotide variations translate to phenotypic traits.

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