The Typology of Negation

Auwera, Johan van der; Krasnoukhova, Olga

doi:10.1093/oxfordhb/9780198830528.013.3

Cited by 286 publications

(306 citation statements)

References 241 publications

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“…To assess validation rates of these variants, we utilized the RNA-Seq data to validate WGS variants in protein coding regions of the genome. Reads from samples in each substrain were combined and GATK best practices pipeline for RNA-Seq variant calling 52 was used. Average genome-wide read coverage of RNA-Seq data for fourteen substrains ranged from 1.81x to 3.71x with a median of 3.08x.…”

Section: Star Methodsmentioning

confidence: 99%

“…WGS SNPs and INDELs which intersect with protein coding exon and UTR annotations (from Ensembl) and have at least 3X coverage in RNA-Seq dataset are considered for validation. Variants from RNA-Seq data were called by GATK best practices 52 for each substrain separately (see also STAR Methods). Validation rate between different categories of variants are compared.…”

Section: Supplemental Informationmentioning

confidence: 99%

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Polymorphic SNPs, short tandem repeats and structural variants are responsible for differential gene expression across C57BL/6 and C57BL/10 substrains

Mortazavi

Ren

Saini

et al. 2020

Preprint

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C57BL/6J is the most widely used inbred mouse strain and is the basis for the mouse reference genome. In addition to C57BL/6J, several other C57BL/6 and C57BL/10 substrains exist. Previous studies have documented extensive phenotypic and genetic differences among these substrains, which are presumed to be due to the accumulation of new mutations. These differences can be used for genome wide association studies.They can also have unintended consequences for reproducibility when substrain differences are not properly accounted for. In this paper, we performed genomic sequencing and RNA-sequencing in the hippocampus of 9 C57BL/6 and 5 C57BL/10 substrains. We identified 985,329 SNPs, 150,344 Short Tandem Repeats (STR) and 896Structural Variants (SV), out of which 330,178 SNPs and 14,367 STRs differentiated the C57BL/6 and C57BL/10 groups. We found several regions that contained dense polymorphisms. We also identified 578 differentially expressed genes for C57BL/6 substrains and 37 differentially expressed genes for C57BL/10 substrains (FDR < 0.01).We then identified nearby SNPs, STRs and SVs that matched the gene expression patterns. In so doing, we identified SVs in coding regions of Wdfy1, Ide, Fgfbp3 and Btaf1 that explain the expression patterns observed. We replicated several previously reported gene expression differences between substrains (Nnt, Gabra2) as well as many novel gene expression differences (e.g. Kcnc2). Our results illustrate the impact of new mutations on gene expression among these substrains and provides a resource for future mapping studies.

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Section: Star Methodsmentioning

confidence: 99%

Section: Supplemental Informationmentioning

confidence: 99%

Polymorphic SNPs, short tandem repeats and structural variants are responsible for differential gene expression across C57BL/6 and C57BL/10 substrains

Mortazavi

Ren

Saini

et al. 2020

Preprint

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show abstract

“…This increases the speed of MitoHPC while still retaining sufficient coverage to have confidence in low level (3% variant allele frequency) heteroplasmy calls. We incorporated two programs for calling mtDNA heteroplamic and homoplasmic variants, GATK Mutect2 ( 23 , 24 ) and Mutserve ( 11 ) (Figure 2 ). For the first iteration of variant identification, we used the rCRS as the reference genome, although the RSRS is included as an optional reference.…”

Section: Methodsmentioning

confidence: 99%

A bioinformatics pipeline for estimating mitochondrial DNA copy number and heteroplasmy levels from whole genome sequencing data

Battle

Puiu

Verlouw

et al. 2022

NAR Genomics and Bioinformatics

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Mitochondrial diseases are a heterogeneous group of disorders that can be caused by mutations in the nuclear or mitochondrial genome. Mitochondrial DNA (mtDNA) variants may exist in a state of heteroplasmy, where a percentage of DNA molecules harbor a variant, or homoplasmy, where all DNA molecules have the same variant. The relative quantity of mtDNA in a cell, or copy number (mtDNA-CN), is associated with mitochondrial function, human disease, and mortality. To facilitate accurate identification of heteroplasmy and quantify mtDNA-CN, we built a bioinformatics pipeline that takes whole genome sequencing data and outputs mitochondrial variants, and mtDNA-CN. We incorporate variant annotations to facilitate determination of variant significance. Our pipeline yields uniform coverage by remapping to a circularized chrM and by recovering reads falsely mapped to nuclear-encoded mitochondrial sequences. Notably, we construct a consensus chrM sequence for each sample and recall heteroplasmy against the sample's unique mitochondrial genome. We observe an approximately 3-fold increased association with age for heteroplasmic variants in non-homopolymer regions and, are better able to capture genetic variation in the D-loop of chrM compared to existing software. Our bioinformatics pipeline more accurately captures features of mitochondrial genetics than existing pipelines that are important in understanding how mitochondrial dysfunction contributes to disease.

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“…The reference genome was first indexed with samtools faidx v1.11 (Danecek et al ., 2021) and a sequence dictionary was generated with Picard CreateSequenceDictionary v2.25.6 (https://broadinstitute.github.io/picard). The VCF containing the SV produced from our Nanopore sequencing was also indexed with gatk (Van der Auwera GA & O’Connor BD, 2020) IndexFeatureFile v4.2.0.0 (https://gatk.broadinstitute.org/hc/en-us/articles/360037262651-IndexFeatureFile). FastaAlternateReferenceMaker v4.2.0.0 (https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker) was then run with the reference genome and the VCF file to generate a substituted genome representative of our Fragaria accession (Fb2).…”

Section: Methodsmentioning

confidence: 99%

DNA methylation dynamics during stress-response in woodland strawberry (Fragaria vesca)

López

Roquis

Becker

et al. 2022

Preprint

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SummaryEnvironmental stresses can result in a wide range of physiological and molecular responses in plants. These responses can also impact epigenetic information in genomes especially at the level of DNA methylation. DNA methylation is the hallmark heritable epigenetic modification and plays a key role in silencing transposable elements (TEs). Although DNA methylation is an essential epigenetic mechanism, fundamental aspects of its contribution to stress responses and adaptation remain obscure.We investigated epigenome dynamics of wild strawberry (Fragaria vesca) in response to variable environmental conditions at DNA methylation level. F. vesca methylome responded with great plasticity to ecologically relevant abiotic and hormonal stresses. Thermal stress resulted in substantial genome-wide loss of DNA methylation. Notably, all tested stress conditions resulted in marked hot spots of differential DNA methylation near centromeric or pericentromeric regions, particularly in non-symmetrical DNA methylation context. Additionally, we identified differentially methylated regions (DMRs) within promoter regions of transcription factor (TF) superfamilies involved in plant stress-response and assessed the effects of these changes on gene expression.These findings improve our understanding on stress-response at the epigenome level by highlighting the correlation between DNA methylation, TEs and gene expression regulation in plants subjected to a broad range of environmental stresses.

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The Typology of Negation

Cited by 286 publications

References 241 publications

Polymorphic SNPs, short tandem repeats and structural variants are responsible for differential gene expression across C57BL/6 and C57BL/10 substrains

Polymorphic SNPs, short tandem repeats and structural variants are responsible for differential gene expression across C57BL/6 and C57BL/10 substrains

A bioinformatics pipeline for estimating mitochondrial DNA copy number and heteroplasmy levels from whole genome sequencing data

DNA methylation dynamics during stress-response in woodland strawberry (Fragaria vesca)

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