OPRD1 SNPs associated with opioid addiction are cis-eQTLs for the phosphatase and actin regulator 4 gene, PHACTR4, a mediator of cytoskeletal dynamics

Several OPRD1 intronic variants were associated with opioid addiction (OD) in a population-specific manner. This follow-up study aims to further characterize the OPRD1 haplotype pattern of the risk variants in different populations and apply in silico analysis to identify potential causal variants. A population-specific haplotype pattern was revealed based on six OPRD1 eQTL SNPs and five common haplotypes were identified in a sample of European ancestry (CEU). A European-specific haplotype (‘Hap 3’) that includes SNPs previously associated with OD and is tagged by SNP rs2236861 is more common in subjects with OD. It is quite common (10%) in CEU but is absent in the African sample (YRI) and extends upstream of OPRD1. SNP rs2236857 is most probably a non-causal variant in LD with the causal SNP/s in a population-specific manner. The study provides an explanation for the lack of association in African Americans, despite its high frequency in this population. OD samples homozygous for ‘Hap 3’ were reanalyzed using a denser coverage of the region and revealed at least 25 potentially regulatory SNPs in high LD. Notably, GTEx data indicate that some of the SNPs are eQTLs for the upstream phosphatase and actin regulator 4 (PHACTR4), in the cortex, and others are eQTLs for OPRD1 and the upstream lncRNA ENSG00000270605, in the cerebellum. The study highlights the limitation of single SNP analysis and the sensitivity of association studies of OPRD1 to a genetic background. It proposes a long-range functional connection between OPRD1 and PHACTR4. PHACTR4, a mediator of cytoskeletal dynamics, may contribute to drug addiction by modulating synaptic plasticity.

Hierarchical Modelling of Haplotype Effects on a Phylogeny

We introduce a hierarchical model to estimate haplotype effects based on phylogenetic relationships between haplotypes and their association with observed phenotypes. In a population there are many, but not all possible, distinct haplotypes and few observations per haplotype. Further, haplotype frequencies tend to vary substantially. Such data structure challenge estimation of haplotype effects. However, haplotypes often differ only due to few mutations, and leveraging similarities can improve the estimation of effects. We build on extensive literature and develop an autoregressive model of order one that models haplotype effects by leveraging phylogenetic relationships described with a directed acyclic graph. The phylogenetic relationships can be either in a form of a tree or a network, and we refer to the model as the haplotype network model. The model can be included as a component in a phenotype model to estimate associations between haplotypes and phenotypes. Our key contribution is that we obtain a sparse model, and by using hierarchical autoregression, the flow of information between similar haplotypes is estimated from the data. A simulation study shows that the hierarchical model can improve estimates of haplotype effects compared to an independent haplotype model, especially with few observations for a specific haplotype. We also compared it to a mutation model and observed comparable performance, though the haplotype model has the potential to capture background specific effects. We demonstrate the model with a study of mitochondrial haplotype effects on milk yield in cattle. We provide R code to fit the model with the INLA package.

Haplotype Analysis of GJB2 Mutations: Founder Effect or Mutational Hot Spot?

The GJB2 gene is the most frequent cause of congenital or early onset hearing loss worldwide. In this study, we investigated the haplotypes of six GJB2 mutations frequently observed in Japanese hearing loss patients (i.e., c.235delC, p.V37I, p.[G45E; Y136X], p.R143W, c.176_191del, and c.299_300delAT) and analyzed whether the recurring mechanisms for each mutation are due to founder effects or mutational hot spots. Furthermore, regarding the mutations considered to be caused by founder effects, we also calculated the age at which each mutation occurred using the principle of genetic clock analysis. As a result, all six mutations were observed in a specific haplotype and were estimated to derive from founder effects. Our haplotype data together with their distribution patterns indicated that p.R143W and p.V37I may have occurred as multiple events, and suggested that both a founder effect and hot spot may be involved in some mutations. With regard to the founders’ age of frequent GJB2 mutations, each mutation may have occurred at a different time, with the oldest, p.V37I, considered to have occurred around 14,500 years ago, and the most recent, c.176_191del, considered to have occurred around 4000 years ago.

Haplotyping by CRISPR-mediated DNA circularization (CRISPR-hapC) broadens allele-specific gene editing

Allele-specific protospacer adjacent motif (asPAM)-positioning SNPs and CRISPRs are valuable resources for gene therapy of dominant disorders. However, one technical hurdle is to identify the haplotype comprising the disease-causing allele and the distal asPAM SNPs. Here, we describe a novel CRISPR-based method (CRISPR-hapC) for haplotyping. Based on the generation (with a pair of CRISPRs) of extrachromosomal circular DNA in cells, the CRISPR-hapC can map haplotypes from a few hundred bases to over 200 Mb. To streamline and demonstrate the applicability of the CRISPR-hapC and asPAM CRISPR for allele-specific gene editing, we reanalyzed the 1000 human pan-genome and generated a high frequency asPAM SNP and CRISPR database (www.crispratlas.com/knockout) for four CRISPR systems (SaCas9, SpCas9, xCas9 and Cas12a). Using the huntingtin (HTT) CAG expansion and transthyretin (TTR) exon 2 mutation as examples, we showed that the asPAM CRISPRs can specifically discriminate active and dead PAMs for all 23 loci tested. Combination of the CRISPR-hapC and asPAM CRISPRs further demonstrated the capability for achieving highly accurate and haplotype-specific deletion of the HTT CAG expansion allele and TTR exon 2 mutation in human cells. Taken together, our study provides a new approach and an important resource for genome research and allele-specific (haplotype-specific) gene therapy.

HaploBlocker: Creation of subgroup specific haplotype blocks and libraries

ABSTRACTThe concept of haplotype blocks has been shown to be useful in genetics. Fields of application range from the detection of regions under positive selection to statistical methods that make use of dimension reduction. We propose a novel approach (“HaploBlocker”) for defining and inferring haplotype blocks that focuses on linkage instead of the commonly used population-wide measures of linkage disequilibrium. We define a haplotype block as a sequence of genetic markers that has a predefined minimum frequency in the population and only haplotypes with a similar sequence of markers are considered to carry that block, effectively screening a dataset for group-wise identity-by-descent. From these haplotype blocks we construct a haplotype library that represents a large proportion of genetic variability with a limited number of blocks. Our method is implemented in the associated R-package HaploBlocker and provides flexibility to not only optimize the structure of the obtained haplotype library for subsequent analyses, but is also able to handle datasets of different marker density and genetic diversity. By using haplotype blocks instead of SNPs, local epistatic interactions can be naturally modelled and the reduced number of parameters enables a wide variety of new methods for further genomic analyses such as genomic prediction and the detection of selection signatures. We illustrate our methodology with a dataset comprising 501 doubled haploid lines in a European maize landrace genotyped at 501’124 SNPs. With the suggested approach, we identified 2’991 haplotype blocks with an average length of 2’685 SNPs that together represent 94% of the dataset.