Alternative methods improve the accuracy of genomic prediction using information from a causal point mutation in a dairy sheep model

Background Genomic evaluation is usually based on a set of markers assumed to be linked with causal mutations. Selection and precise management of major genes and the remaining polygenic component might be improved by including causal polymorphisms in the evaluation models. In this study, various methods involving a known mutation were used to estimate prediction accuracy. The SOCS2 gene, which influences body growth, milk production and somatic cell scores, a proxy for mastitis, was studied as an example in dairy sheep. Methods The data comprised 1,503,148 phenotypes and 9844 54K SNPs genotypes. The SOCS2 SNP was genotyped for 4297 animals and imputed in the above 9844 animals. Breeding values and their accuracies were estimated for each of nine traits by using single-step approaches. Pedigree-based BLUP, single-step genomic BLUP (ssGBLUP) involving the 54K ovine SNPs chip, and four weighted ssGBLUP (WssGBLUP) methods were compared. In WssGBLUP methods, weights are assigned to SNPs depending on their effect on the trait. The ssGBLUP and WssGBLUP methods were again tested after including the SOCS2 causal mutation as a SNP. Finally, the Gene Content approach was tested, which uses a multiple-trait model that considers the SOCS2 genotype as a trait. Results EBV accuracies were increased by 14.03% between the pedigree-based BLUP and ssGBLUP methods and by 3.99% between ssGBLUP and WssGBLUP. Adding the SOCS2 SNP to ssGBLUP methods led to an average gain of 0.26%. Construction of the kinship matrix and estimation of breeding values was generally improved by placing emphasis on SNPs in regions with a strong effect on traits. In the absence of chip data, the Gene Content method, compared to pedigree-based BLUP, efficiently accounted for partial genotyping information on SOCS2 as accuracy was increased by 6.25%. This method also allowed dissociation of the genetic component due to the major gene from the remaining polygenic component. Conclusions Causal mutations with a moderate to strong effect can be captured with conventional SNP chips by applying appropriate genomic evaluation methods. The Gene Content method provides an efficient way to account for causal mutations in populations lacking genome-wide genotyping.

Genome-wide Association Study of Multisite Chronic Pain in UK Biobank

Chronic pain is highly prevalent worldwide, contributing a significant socioeconomic and public health burden. Several aspects of chronic pain, for example back pain and a severity-related phenotype, chronic pain grade, have been shown to be complex, heritable traits with a polygenic component. Additional pain-related phenotypes capturing aspects of an individual’s overall sensitivity to experiencing and reporting chronic pain have also been suggested. We have here made use of a measure of the number of sites of chronic pain in individuals within the general UK population. This measure, termed Multisite Chronic Pain (MCP), is also a complex trait, but its genetic architecture has not previously been investigated. To address this, a large-scale genome-wide association study (GWAS) of MCP was carried out in ~380,000 UK Biobank participants to identify associated genetic variants. Findings were consistent with MCP having a significant polygenic component with a SNP heritability of 10.2%, and 76 independent lead single nucleotide polymorphisms (SNPs) at 39 risk loci were identified. Additional gene-level association analyses identified neurogenesis, synaptic plasticity, nervous system development, cell-cycle progression and apoptosis genes as being enriched for genetic association with MCP. Genetic correlations were observed between MCP and a range of psychiatric, autoimmune and anthropometric traits including major depressive disorder (MDD), asthma and BMI. Furthermore, in Mendelian randomisation (MR) analyses a bi-directional causal relationship was observed between MCP and MDD. A polygenic risk score (PRS) for MCP was found to significantly predict chronic widespread pain (pain all over the body), indicating the existence of genetic variants contributing to both of these pain phenotypes. These findings support the proposition that chronic pain involves a strong nervous system component and have implications for our understanding of the physiology of chronic pain and for the development of novel treatment strategies.

The BRCA1 c. 5096G>A p.Arg1699Gln (R1699Q) intermediate risk variant: breast and ovarian cancer risk estimation and recommendations for clinical management from the ENIGMA consortium

BackgroundWe previously showed that the BRCA1 variant c.5096G>A p.Arg1699Gln (R1699Q) was associated with an intermediate risk of breast cancer (BC) and ovarian cancer (OC). This study aimed to assess these cancer risks for R1699Q carriers in a larger cohort, including follow-up of previously studied families, to further define cancer risks and to propose adjusted clinical management of female BRCA1*R1699Q carriers.MethodsData were collected from 129 BRCA1*R1699Q families ascertained internationally by ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) consortium members. A modified segregation analysis was used to calculate BC and OC risks. Relative risks were calculated under both monogenic model and major gene plus polygenic model assumptions.ResultsIn this cohort the cumulative risk of BC and OC by age 70 years was 20% and 6%, respectively. The relative risk for developing cancer was higher when using a model that included the effects of both the R1699Q variant and a residual polygenic component compared with monogenic model (for BC 3.67 vs 2.83, and for OC 6.41 vs 5.83).ConclusionOur results confirm that BRCA1*R1699Q confers an intermediate risk for BC and OC. Breast surveillance for female carriers based on mammogram annually from age 40 is advised. Bilateral salpingo-oophorectomy should be considered based on family history.

Influence of DAOA and RGS4 genes on the risk for psychotic disorders and their associated executive dysfunctions: A family-based study

BackgroundGlutamatergic neurotransmission dysfunction has classically been related to the aetiology of psychotic disorders. A substantial polygenic component shared across these disorders has been reported and molecular genetics studies have associated glutamatergic-related genes, such as d-amino acid oxidase activator (DAOA) and regulator of G-protein signalling 4 (RGS4) with the risk for psychotic disorders. Our aims were to examine: (i) the relationship between DAOA and RGS4 and the risk for psychotic disorders using a family-based association approach, and (ii) whether variations in these genes are associated with differences in patients’ cognitive performance.MethodsThe sample comprised 753 subjects (222 patients with psychotic disorders and 531 first-degree relatives). Six SNPs in DAOA and 5 SNPs in RGS4 were genotyped. Executive cognitive performance was assessed with Trail Making Test B (TMT-B) and Wisconsin Card Sorting Test (WCST). Genetic association analyses were conducted with PLINK, using the transmission disequilibrium test (TDT) for the family-based study and linear regression for cognitive performance analyses.ResultsThe haplotype GAGACT at DAOA was under-transmitted to patients (P = 0.0008), indicating its association with these disorders. With regards to cognitive performance, the DAOA haplotype GAGGCT was associated with worse scores in TMT-B (P = 0.018) in SZ patients only. RGS4 analyses did not report significant results.ConclusionsOur findings suggest that the DAOA gene may contribute to the risk for psychotic disorders and that this gene may play a role as a modulator of executive function, probably through the dysregulation of the glutamatergic signalling.

Different estimations of heritabilities in dependence of major gene effects (Brief Report)

Knowledge of major gene effects for quantitative traits (e.g. milk performance traits) and the consequent selection of animals with desirable genotypes can accelerate breeding progress and can therefore equal large gain in profits. It is generally accepted that in most cases, the total breeding value for quantitative traits of any animal can be divided in one or some major gene effects and a pure random polygenic component, in which the latter results from a finite number of remaining loci (FERNANDO et al. 1994). Thus, the aim of this study was to investigate, how the estimation of heritability is influenced by the application of two different models, one of them containing a major single gene effect. The myostatin gene (MSTN) was chosen because the knowledge of this gene effect is used for selection decisions in the Dual Purpose Belgian Blue Breed (DP-BBB) in the Walloon Region of Belgium.

Functional consequences of attenuating mutations in the haemagglutinin–neuraminidase, fusion and polymerase proteins of a wild-type mumps virus strain

Wild-type mumps viruses (MuVs) are highly neurotropic and, prior to widespread vaccination programmes, were a major cause of viral meningitis and encephalitis in most developed countries. At present, there are no markers for virus attenuation, apart from the failure of a passaged isolate to produce clinical symptoms in vaccinees. Indeed, some MuV vaccines have retained residual neurovirulence properties and have caused aseptic meningitis in vaccinees. Three amino acid changes associated with the neuroattenuation of a wild-type MuV strain were identified previously. This study evaluated the impact of these changes on the function of the respective proteins. The data demonstrated that the Ser→Asp amino acid substitution at position 466 in the haemagglutinin–neuraminidase protein resulted in decreased receptor binding and neuraminidase activity, the Ala/Thr→Thr selection in the fusion protein resulted in decreased fusion activity, and the Ile→Val substitution in the polymerase resulted in increased replicative/transcriptional activity. These data suggest a polygenic component (i.e. specific and inter-related roles of these amino acid changes) to MuV neuroattenuation.

Application of a Polygenic Model of Breast and Ovarian Cancer to Critical Illness Insurance

ABSTRACTMutations in the BRCA1 and BRCA2 genes confer very high risk of breast cancer (BC), but only account for about 25% of the observed familial clustering of BC. Antoniou et al. (2002) proposed a model which included the BRCA1 and BRCA2 genes, and a polygenic component which acted multiplicatively on the rate of onset of BC. We use this model to find premium rates for critical illness insurance: (a) given knowledge of an applicant's polygenotype; and (b) given knowledge of a family history of BC or ovarian cancer. We find that the polygenic component causes large variation in premium rates even among non-mutation carriers, therefore affecting the whole population. In some cases the polygenic contribution is protective enough to reduce or remove the additional risk of a BRCA1/2 mutation, leading to cases where it will be advantageous to disclose genetic test results which are adverse in absolute terms. Premiums based on family history are lower than those found in an earlier study which attributed all genetic BC risk to the BRCA1/2 genes.

Response from marker-assisted selection when various proportions of animals are marker typed: a multiple trait simulation study relevant to the sheepmeat industry

A simulation study, based on a closed sheepmeat breeding nucleus and incorporating marker-assisted selection (MAS), was used to evaluate response when different proportions of animals were marker typed. Two traits were included in the simulation: trait 1, a production trait where phenotypes were available prior to selection, and trait 2, a carcass trait where phenotypic information was not available on breeding animals. Selection on an index which comprised estimated breeding values (EBVs) for both traits was possible by calculating EBVs for trait 2 as the sum of EBVs for a polygenic component, obtained from a genetic regression, and EBVs for a major gene component, obtained by inferring genotypes at a major gene locus from a linked marker locus. Different marker typing strategies were evaluated. These differed in the criteria used to select progeny for typing, and in the proportion of male and female progeny selected. Typing progeny that were likely to be used as a breeding animal, but excluding those whose marker genotype could be predicted with reasonable certainty, was an efficient genotyping strategy. Close to maximum gain at the major gene locus was achieved when only a proportion of animals were marker typed (for example 90% of maximum response was achieved with a little over one-third of the selection candidates marker typed). This indicates the potential for substantial savings in relation to the cost of marker typing in commercial breeding flocks.