Applications of Microarray-Based Technologies in Identifying Disease-Associated Single Nucleotide Variations

2019 ◽  
pp. 61-73
Author(s):  
Sartaj Khurana ◽  
Sudeep Bose ◽  
Dhruv Kumar
Keyword(s):  
Single Nucleotide ◽  
Single Nucleotide Variations

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

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.

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

PLoS ONE ◽  
2012 ◽  
Vol 7 (5) ◽  
pp. e36212 ◽  
Author(s):  
Raja Mazumder ◽  
Krishna Sudeep Morampudi ◽  
Mona Motwani ◽  
Sona Vasudevan ◽  
Radoslav Goldman
Keyword(s):  
Single Nucleotide ◽  
Human Genes ◽  
Single Nucleotide Variations

scholarly journals Sequence variability ofChrysanthemum stunt viroidin different chrysanthemum cultivars

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e2933 ◽  
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.

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

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.

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

2020 ◽  
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.

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

2019 ◽  
Vol 10 (1) ◽  
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.

scholarly journals Genomic surveillance of COVID-19 cases in Beijing

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Pengcheng Du ◽  
Nan Ding ◽  
Jiarui Li ◽  
Fujie Zhang ◽  
Qi Wang ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
High Frequency ◽  
Epidemiological Data ◽  
Genomic Diversity ◽  
Nucleotide Polymorphisms ◽  
Genomic Evolution ◽  
Single Nucleotide ◽  
Imported Cases ◽  
Single Nucleotide Variations ◽  
Local Transmission

Abstract The spread of SARS-CoV-2 in Beijing before May, 2020 resulted from transmission following both domestic and global importation of cases. Here we present genomic surveillance data on 102 imported cases, which account for 17.2% of the total cases in Beijing. Our data suggest that all of the cases in Beijing can be broadly classified into one of three groups: Wuhan exposure, local transmission and overseas imports. We classify all sequenced genomes into seven clusters based on representative high-frequency single nucleotide polymorphisms (SNPs). Genomic comparisons reveal higher genomic diversity in the imported group compared to both the Wuhan exposure and local transmission groups, indicating continuous genomic evolution during global transmission. The imported group show region-specific SNPs, while the intra-host single nucleotide variations present as random features, and show no significant differences among groups. Epidemiological data suggest that detection of cases at immigration with mandatory quarantine may be an effective way to prevent recurring outbreaks triggered by imported cases. Notably, we also identify a set of novel indels. Our data imply that SARS-CoV-2 genomes may have high mutational tolerance.

scholarly journals High-fidelity amplified FISH for the detection and allelic discrimination of single mRNA molecules

2019 ◽  
Vol 116 (28) ◽  
pp. 13921-13926 ◽  
Author(s):  
Salvatore A. E. Marras ◽  
Yuri Bushkin ◽  
Sanjay Tyagi
Keyword(s):  
Single Molecule ◽  
Hybridization Chain Reaction ◽  
Wild Type ◽  
Allelic Discrimination ◽  
Single Nucleotide ◽  
Tissue Sections ◽  
Powerful Approach ◽  
Probe System ◽  
Single Nucleotide Variations

Amplification of signals by the hybridization chain reaction (HCR) is a powerful approach for increasing signal strength in single-molecule fluorescence in situ hybridization, but probes tagged with an HCR initiator sequence are prone to producing false signals. Here we describe a system of interacting hairpin binary probes in which the HCR initiator sequence is conditionally sequestered. The binding of these probes to a perfectly complementary target unmasks the initiator, enabling the generation of an amplified signal. This probe system can distinguish single-nucleotide variations within single mRNA molecules and produces amplified signals in situ for both mutant and wild-type variants, each in a distinguishable color. This technology will augment studies of imbalanced allelic expression and will be useful for the detection of somatic mutations in cancer biopsies. By tiling these probes along the length of an mRNA target, enhanced signals can be obtained, thereby enabling the scanning of tissue sections for gene expression utilizing lower magnification microscopy, overcoming tissue autofluorescence, and allowing the detection of low-abundance biomarkers in flow cytometry.

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