Cited by 176Genetic Associations and EpidemiologyBioinformatics and Genomic NetworksGenetic Mapping and Diversity in Plants and Animals

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How far from the SNP may the causative genes be?

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Brodie, Aharon, Azaria, Johnathan Roy, Ofran, Yanay·2016·Nucleic Acids Research

DOI 10.1093/nar/gkw500PMC PMC5291268

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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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Figure 1. Distribution of SNPs according to their proximity to the nearest gene. Bars depict percentage of SNPs that have a gene within a certain distance from them. Blue bars represent all known SNPs, the red bars represent only SNPs that were found by GWAS to be associated with phenotypes. The X-axis represents distance from the SNPs the Y-axis represents the percentage of SNPs that have a gene within that distance from them.CC BY-NC · PubMed Central

Figure 2. Associations based on mapping a SNP to genes at different intervals. (A) Number of pathways significantly associated with phenotypes if we map a SNP to all genes within a certain distance, in non-cumulative distance cutoffs (e.g. genes that are between 0–100 Kbps are not considered for the 100–200 Kbps interval, etc.). Red bars represent the number of associations expected by chance (median of 100 random resampling repetitions, see Methods). (B) Number of pathways significantly associated with phenotypes when for each distance cutoff genes are considered cumulatively (all genes between the SNPs and the distance cutoff are considered). Red line represents the number expected by chance, as above.CC BY-NC · PubMed Central

Figure 3. Average number of indels between SNPs and genes at different distances. Each point depicts the normalized average number of known indels between a SNPs and genes at a certain distance. The blue points represent indels between SNPs and genes that are linked to each other through a significance association with a pathway. Red points represent SNPs and genes that are not mapped to each other. For example, SNPs that are linked by pathways to genes that are 150 Kbps away have, on average, 3.5 known indels for every nucleotide in that distance. SNPs that have genes 150 Kbps away, but these genes are not associated to them by pathways, have on average only 2.1 indels per nucleotide.CC BY-NC · PubMed Central

Figure 4. Difference between observed and expected number of associated pathways. Subtracting the numbers represented by the red line in Figure 2B from the numbers represented by the blue line, reveals that until 200 Kbps away from the SNP, associations with pathways improves as we include more distant genes. From this distance on, adding of more distant genes decreases the number of significant associations.CC BY-NC · PubMed Central

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Authors: Brodie, A., Azaria, J. R., & Ofran, Y.
Affiliations: Bar-Ilan University (IL)
Corresponding author: Ofran, Yanay
Venue: Nucleic Acids Research
Publisher: Oxford University Press (OUP)
Published: 2016-06-06
Volume: 44
Issue: 13
Pages: 6046-6054
ISSN: 0305-1048 (ISSN-L)
1362-4962
DOI: 10.1093/nar/gkw500
PMC: PMC5291268
OpenAlex: W2411890015
Cited by: 172
References: 43
Citations by year: 2026: 14 · 2025: 14 · 2024: 10 · 2023: 18 · 2022: 26 · 2021: 25 · 2020: 21 · 2019: 23 · 2018: 15 · 2017: 5 · 2016: 1
FWCI: 11.85
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by-nc
creativecommons.org/licenses/by-nc/4.0/ (vor, 158 d)
Locations: Nucleic Acids Research (publishedVersion, cc-by-nc)
PubMed Central (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
HighWire Press Open Archive (submittedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords: single nucleotide polymorphisms, disease-associated SNPs, non-coding SNPs, indels, structural variants, disease mechanisms, genetic distance
MeSH terms: Genotype, Humans, Phenotype, Linkage Disequilibrium, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, INDEL Mutation, Genome-Wide Association Study, Genetic Association Studies

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