ArticleAlgorithms for molecular biology : AMB2009
Modeling genetic imprinting effects of DNA sequences with multilocus polymorphism data.
Article in Algorithms for molecular biology : AMB, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Graph statistics theory of individualized quantitative genetics under haplotype-resolved genome assembly.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Hypermethylation of the κ1 opioid receptor promoter in Chinese heroin and methamphetamine addicts.Experimental and therapeutic medicine · 2018Article
- Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses.The pharmacogenomics journal · 2017Article
- Nonparametric method for detecting imprinting effect using all members of general pedigrees with missing data.Journal of human genetics · 2014Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Single nucleotide polymorphisms (SNPs) represent the most widespread type of DNA sequence variation in the human genome and they have recently emerged as valuable genetic markers for revealing the genetic architecture of complex traits in terms of nucleotide combination and sequence. Here, we extend an algorithmic model for the haplotype analysis of SNPs to estimate the effects of genetic imprinting expressed at the DNA sequence level. The model provides a general procedure for identifying the number and types of optimal DNA sequence variants that are expressed differently due to their parental origin. The model is used to analyze a genetic data set collected from a pain genetics project. We find that DNA haplotype GAC from three SNPs, OPRKG36T (with two alleles G and T), OPRKA843G (with alleles A and G), and OPRKC846T (with alleles C and T), at the kappa-opioid receptor, triggers a significant effect on pain sensitivity, but with expression significantly depending on the parent from which it is inherited (p = 0.008). With a tremendous advance in SNP identification and automated screening, the model founded on haplotype discovery and statistical inference may provide a useful tool for genetic analysis of any quantitative trait with complex inheritance.
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Registered trials
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