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A novel single cell method to identify the genetic composition at a single nuclear body.

ABSTRACT: Gene loci make specific associations with compartments of the nucleus (e.g. the nuclear envelope, nucleolus, and transcription factories) and this association may determine or reflect a mechanism of genetic control. With current methods, it is not possible to identify sets of genes that converge to form a "gene hub" as there is a reliance on loci-specific probes, or immunoprecipitation of a particular protein from bulk cells. We introduce a method that will allow for the identification of loci contained within the vicinity of a single nuclear body in a single cell. For the first time, we demonstrate that the DNA sequences originating from a single sub-nuclear structure in a single cell targeted by two-photon irradiation can be determined, and mapped to a particular locus. Its application to single PML nuclear bodies reveals ontologically related loci that frequently associate with each other and with PML bodies in a population of cells, and a possible nuclear body targeting role for specific transcription factor binding sites.

SUBMITTER: Anchel D

PROVIDER: S-EPMC4937434 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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A novel single cell method to identify the genetic composition at a single nuclear body.

Anchel David D Ching Reagan W RW Cotton Rachel R Li Ren R Bazett-Jones David P DP

Scientific reports 20160708

Gene loci make specific associations with compartments of the nucleus (e.g. the nuclear envelope, nucleolus, and transcription factories) and this association may determine or reflect a mechanism of genetic control. With current methods, it is not possible to identify sets of genes that converge to form a "gene hub" as there is a reliance on loci-specific probes, or immunoprecipitation of a particular protein from bulk cells. We introduce a method that will allow for the identification of loci c ...[more]

PMID: 27389808

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Project description:Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)-rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Dataset Information

A novel single cell method to identify the genetic composition at a single nuclear body.

Publications

A novel single cell method to identify the genetic composition at a single nuclear body.

Similar Datasets

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