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Relative impact of indels versus SNPs on complex disease.

ABSTRACT: It is unclear whether insertions and deletions (indels) are more likely to influence complex traits than abundant single-nucleotide polymorphisms (SNPs). We sought to understand which category of variation is more likely to impact health. Using the SardiNIA study as an exemplar, we characterized 478,876 common indels and 8,246,244 common SNPs in up to 5,949 well-phenotyped individuals from an isolated valley in Sardinia. We assessed association between 120 traits, resulting in 89 nonoverlapping-associated loci.We evaluated whether indels were enriched among credible sets of potential causal variants. These credible sets included 1,319 SNPs and 88 indels. We did not find indels to be significantly enriched. Indels were the most likely causal variant in seven loci, including one locus associated with monocyte count where an indel with causality and mechanism previously demonstrated (rs200748895:TGCTG/T) had a 0.999 posterior probability. Overall, our results show a very modest and nonsignificant enrichment for common indels in associated loci.

SUBMITTER: Gagliano SA

PROVIDER: S-EPMC6330128 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Relative impact of indels versus SNPs on complex disease.

Gagliano Sarah A SA Sengupta Sebanti S Sidore Carlo C Maschio Andrea A Cucca Francesco F Schlessinger David D Abecasis Gonçalo R GR

Genetic epidemiology 20181122 1

It is unclear whether insertions and deletions (indels) are more likely to influence complex traits than abundant single-nucleotide polymorphisms (SNPs). We sought to understand which category of variation is more likely to impact health. Using the SardiNIA study as an exemplar, we characterized 478,876 common indels and 8,246,244 common SNPs in up to 5,949 well-phenotyped individuals from an isolated valley in Sardinia. We assessed association between 120 traits, resulting in 89 nonoverlapping- ...[more]

PMID: 30565766

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Project description:BACKGROUND: Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to identify significant breed-by-probe interactions. RESULTS: Gene specific linear mixed models were fit to each of the log2 transformed probe intensities on these arrays, using fixed effects for breed, probe, breed-by-probe interaction, and a random effect for array. After surveying the day 25 placental transcriptome, 857 probes with a q-value < or = 0.05 and |fold change| > or = 2 for the breed-by-probe interaction were identified as candidates containing SFP. To address the quality of the bioinformatics approach, universal pyrosequencing assays were designed from Affymetrix exemplar sequences to independently assess polymorphisms within a subset of probes for validation. Additionally probes were randomly selected for sequencing to determine an unbiased confirmation rate. In most cases, the 25-mer probe sequence printed on the microarray diverged from Meishan, not occidental crosses. This analysis was used to define a set of highly reliable predicted SFPs according to their probability scores. CONCLUSION: By applying a SFP detection method to two mammalian breeds for the first time, we detected transition and transversion single nucleotide polymorphisms, as well as insertions/deletions which can be used to rapidly develop markers for genetic mapping and association analysis in species where high density genotyping platforms are otherwise unavailable.SNPs and INDELS discovered by this approach have been publicly deposited in NCBI's SNP repository dbSNP. This method is an attractive bioinformatics tool for uncovering breed-by-probe interactions, for rapidly identifying expressed SNPs, for investigating potential functional correlations between gene expression and breed polymorphisms, and is robust enough to be used on any Affymetrix gene expression platform.

Dataset Information

Relative impact of indels versus SNPs on complex disease.

Publications

Relative impact of indels versus SNPs on complex disease.

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