ArticleNucleic acids research2016
How far from the SNP may the causative genes be?
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers, 2 of them syntheses that pooled it.
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Who cites it
110 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- A genome-wide association study of corneal astigmatism: The CREAM Consortium.Molecular vision · 2018Pooled it
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- Deletion of ARPKD-associated Pkhd1 gene in mice results in decreased Tfap2b expression and eye abnormalities.Nature communications · 2026Article
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- Studies of mice with a large deletion of the ARPKD-associatedbioRxiv : the preprint server for biology · 2026Article
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- Functional and Computational Interrogation of the Juvenile Idiopathic Arthritis Risk Loci Identifies Candidate Causal SNPs and Target Genes in CD4+ T cells.medRxiv : the preprint server for health sciences · 2025Article
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- Efficient candidate drug target discovery through proteogenomics in a Scottish cohort.Communications biology · 2025Article
- Polygenic strategies for host-specific and general virulence of Botrytis cinerea across diverse eudicot hosts.Genetics · 2025Article
- Genome-wide association analyses for revealing QTN, QTN-by-environment and QTN-by-QTN interactions in soybean phenology.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Mining the cucumber core collection: phenotypic and genetic characterization of morphological diversity for fruit quality characteristics.Horticulture research · 2025Article
50 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes we used a pathway-based approach. We found that affected genes are often up to 2 Mbps away from the associated SNP, and are not necessarily the closest genes to the SNP. Existing approaches for mapping SNPs to genes leave many SNPs unmapped to genes and reveal only 86 significant phenotype-pathway associations for all known GWAS hits combined. Using the pathway-based approach we propose here allows mapping of virtually all SNPs to genes and reveals 435 statistically significant phenotype-pathway associations. In search for mechanisms that may explain the relationships between SNPs and distant genes, we found that SNPs that are mapped to distant genes have significantly more large insertions/deletions around them than other SNPs, suggesting that these SNPs may sometimes be markers for large insertions/deletions that may affect large genomic regions.
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