Dataset Information

Re-evaluation of missense variant classifications in NF2.

ABSTRACT: Missense variants in the NF2 gene result in variable NF2 disease presentation. Clinical classification of missense variants often represents a challenge, due to lack of evidence for pathogenicity and function. This study provides a summary of NF2 missense variants, with variant classifications based on currently available evidence. NF2 missense variants were collated from pathology-associated databases and existing literature. Association for Clinical Genomic Sciences Best Practice Guidelines (2020) were followed in the application of evidence for variant interpretation and classification. The majority of NF2 missense variants remain classified as variants of uncertain significance. However, NF2 missense variants identified in gnomAD occurred at a consistent rate across the gene, while variants compiled from pathology-associated databases displayed differing rates of variation by exon of NF2. The highest rate of NF2 disease-associated variants was observed in exon 7, while lower rates were observed toward the C-terminus of the NF2 protein, merlin. Further phenotypic information associated with variants, alongside variant-specific functional analysis, is necessary for more definitive variant interpretation. Our data identified differences in frequency of NF2 missense variants by exon between gnomAD population data and NF2 disease-associated variants, suggesting a potential genotype-phenotype correlation; further work is necessary to substantiate this.

SUBMITTER: Sadler KV

PROVIDER: S-EPMC9323416 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Re-evaluation of missense variant classifications in NF2.

Sadler Katherine V KV Rowlands Charlie F CF Smith Philip T PT Hartley Claire L CL Bowers Naomi L NL Roberts Nicola Y NY Harris Jade L JL Wallace Andrew J AJ Evans D Gareth DG Messiaen Ludwine M LM Smith Miriam J MJ

Human mutation 20220402 5

Missense variants in the NF2 gene result in variable NF2 disease presentation. Clinical classification of missense variants often represents a challenge, due to lack of evidence for pathogenicity and function. This study provides a summary of NF2 missense variants, with variant classifications based on currently available evidence. NF2 missense variants were collated from pathology-associated databases and existing literature. Association for Clinical Genomic Sciences Best Practice Guidelines (2 ...[more]

PMID: 35332608

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Project description:BACKGROUND:Discovering single nucleotide polymorphisms (SNPs) from agriculture crop genome sequences has been a widely used strategy for developing genetic markers for several applications including marker-assisted breeding, population diversity studies for eco-geographical adaption, genotyping crop germplasm collections, and others. Accurately detecting SNPs from large polyploid crop genomes such as wheat is crucial and challenging. A few variant calling methods have been previously developed but they show a low concordance between their variant calls. A gold standard of variant sets generated from one human individual sample was established for variant calling tool evaluations, however hitherto no gold standard of crop variant set is available for wheat use. The intent of this study was to evaluate seven SNP variant calling tools (FreeBayes, GATK, Platypus, Samtools/mpileup, SNVer, VarScan, VarDict) with the two most popular mapping tools (BWA-mem and Bowtie2) on wheat whole exome capture (WEC) re-sequencing data from allohexaploid wheat. RESULTS:We found the BWA-mem mapping tool had both a higher mapping rate and a higher accuracy rate than Bowtie2. With the same mapping quality (MQ) cutoff, BWA-mem detected more variant bases in mapping reads than Bowtie2. The reads preprocessed with quality trimming or duplicate removal did not significantly affect the final mapping performance in terms of mapped reads. Based on the concordance and receiver operating characteristic (ROC), the Samtools/mpileup variant calling tool with BWA-mem mapping of raw sequence reads outperformed other tests followed by FreeBayes and GATK in terms of specificity and sensitivity. VarDict and VarScan were the poorest performing variant calling tools with the wheat WEC sequence data. CONCLUSION:The BWA-mem and Samtools/mpileup pipeline, with no need to preprocess the raw read data before mapping onto the reference genome, was ascertained the optimum for SNP calling for the complex wheat genome re-sequencing. These results also provide useful guidelines for reliable variant identification from deep sequencing of other large polyploid crop genomes.

Dataset Information

Re-evaluation of missense variant classifications in NF2.

Publications

Re-evaluation of missense variant classifications in NF2.

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