Background High-throughput DNA sequencing platforms have become widely available. As a result, personal genomes are increasingly being sequenced in research and clinical settings. However, the resulting massive amounts of variants data pose significant challenges to the average biologists and clinicians without bioinformatics skills. Methods and results We developed a web server called wANNOVAR to address the critical needs for functional annotation of genetic variants from personal genomes. The server provides simple and intuitive interface to help users determine the functional significance of variants. These include annotating single nucleotide variants and insertions/deletions for their effects on genes, reporting their conservation levels (such as PhyloP and GERP++ scores), calculating their predicted functional importance scores (such as SIFT and PolyPhen scores), retrieving allele frequencies in public databases (such as the 1000 Genomes Project and NHLBI-ESP 5400 exomes), and implementing a ‘variants reduction’ protocol to identify a subset of potentially deleterious variants/genes. We illustrated how wANNOVAR can help draw biological insights from sequencing data, by analysing genetic variants generated on two Mendelian diseases. Conclusions We conclude that wANNOVAR will help biologists and clinicians take advantage of the personal genome information to expedite scientific discoveries. The wANNOVAR server is available at http://wannovar.usc.edu, and will be continuously updated to reflect the latest annotation information.
Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.
Meningiomas are central nervous system tumors that originate from the meningeal coverings of the brain and spinal cord. Most meningiomas are pathologically benign or atypical, but 3–5% display malignant features. Despite previous studies on benign and atypical meningiomas, the key molecular pathways involved in malignant transformation remain to be determined, as does the extent of epigenetic alteration in malignant meningiomas. In this study, we explored the landscape of DNA methylation in ten benign, five atypical and four malignant meningiomas. Compared to the benign tumors, the atypical and malignant meningiomas demonstrate increased global DNA hypomethylation. Clustering analysis readily separates malignant from atypical and benign tumors, implicating that DNA methylation patterns may serve as diagnostic biomarkers for malignancy. Genes with hypermethylated CpG islands in malignant meningiomas (such as HOXA6 and HOXA9) tend to coincide with the binding sites of polycomb repressive complexes (PRC) in early developmental stages. Most genes with hypermethylated CpG islands at promoters are suppressed in malignant and benign meningiomas, suggesting the switching of gene silencing machinery from PRC binding to DNA methylation in malignant meningiomas. One exception is the MAL2 gene that is highly expressed in benign group and silenced in malignant group, representing de novo gene silencing induced by DNA methylation. In summary, our results suggest that malignant meningiomas have distinct DNA methylation patterns compared to their benign and atypical counterparts, and that the differentially methylated genes may serve as diagnostic biomarkers or candidate causal genes for malignant transformation.
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