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Genes in the noncanonical WNT signaling pathway controlling planar cell polarity have been linked to the neural tube defect myelomeningocele. We hypothesized that some genes in the WNT signaling network have a higher mutational burden in myelomeningocele subjects than in reference subjects in gnomAD. Exome sequencing data from 511 myelomeningocele subjects was obtained in-house and data from 29,940 ethnically matched subjects was provided by version 2 of the publicly available Genome Aggregation Database. To compare mutational burden, we collapsed rare deleterious variants across each of 523 human WNT signaling genes in case and reference populations. Ten WNT signaling genes were disrupted with a higher mutational burden among Mexican American myelomeningocele subjects compared to reference subjects (Fishers exact test, P ≤ 0.05) and seven different genes were disrupted among individuals of European ancestry compared to reference subjects. Gene ontology enrichment analyses indicate that genes disrupted only in the Mexican American population play a role in planar cell polarity whereas genes identified in both populations are important for the regulation of canonical WNT signaling. In summary, evidence for WNT signaling genes that may contribute to myelomeningocele in humans is presented and discussed.
Pubmed ID: 32970752 RIS Download
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A tool for performing multi-cluster gene functional enrichment analyses on large scale data (microarray experiments with many time-points, cell-types, tissue-types, etc.). It facilitates co-analysis of multiple gene lists and yields as output a rich functional map showing the shared and list-specific functional features. The output can be visualized in tabular, heatmap or network formats using built-in options as well as third-party software. It uses the hypergeometric test to obtain functional enrichment achieved via the gene list enrichment analysis option available in ToppGene.
View all literature mentionsA software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
View all literature mentionsA database for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. Version 2.0 is based on the Gencode release 9 / Ensembl version 64 and includes a total of 87,347,043 nsSNVs and 2,270,742 essential splice site SNVs. It compiles prediction scores from six prediction algorithms (SIFT, Polyphen2, LRT, MutationTaster, MutationAssessor and FATHMM), three conservation scores (PhyloP, GERP++ and SiPhy) and other related information including allele frequencies observed in the 1000 Genomes Project phase 1 data and the NHLBI Exome Sequencing Project, various gene IDs from different databases, functional descriptions of genes, gene expression and gene interaction information, etc. Some dbNSFP contents (may not be up-to-date though) can also be accessed through variant tools, ANNOVAR, KGGSeq, UCSC Genome Browser''s Variant Annotation Integrator, Ensembl Variant Effect Predictor and HGMD.
View all literature mentionsDatabase (anonymous FTP) resulting from a collaborative effort to identify a core set of human and mouse protein coding regions that are consistently annotated and of high quality. The long term goal is to support convergence towards a standard set of gene annotations. Collaborators are EBI, NCBI, UCSC, WTSI and the initial results are also available from the participants'''' genome browser Web sites. In addition, CCDS identifiers are indicated on the relevant NCBI RefSeq and Entrez Gene records and in Map Viewer displays of RNA (RefSeq) and Gene annotations on the reference assembly.
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