Genotype imputation for the prediction of genomic breeding values in non-genotyped and low-density genotyped individuals

<p>Abstract</p> <p>Background</p> <p>There is wide interest in calculating genomic breeding values (GEBVs) in livestock using dense, genome-wide SNP data. The general framework for genomic selection assumes all individuals are genotyped at high-density, which may not be true in practice. Methods to add additional genotypes for individuals not genotyped at high density have the potential to increase GEBV accuracy with little or no additional cost. In this study a long haplotype library was created using a long range phasing algorithm and used in combination with segregation analysis to impute dense genotypes for non-genotyped dams in the training dataset (S1) and for non-genotyped or low-density genotyped individuals in the prediction dataset (S2), using the 14^th QTL-MAS Workshop dataset. Alternative low-density scenarios were evaluated for accuracy of imputed genotypes and prediction of GEBVs.</p> <p>Results</p> <p>In S1, females in the training population were not genotyped and prediction individuals were either not genotyped or genotyped at low-density (evenly spaced at 2, 5 or 10 Mb). The proportion of correctly imputed genotypes for training females did not change when genotypes were added for individuals in the prediction set whereas the number of correctly imputed genotypes in the prediction set increased slightly (S1). The S2 scenario assumed the complete training set was genotyped for all SNPs and the prediction set was not genotyped or genotyped at low-density. The number of correctly imputed genotypes increased with genotyping density in the prediction set. Accuracy of genomic breeding values for the prediction set in each scenario were the correlation of GEBVs with true breeding values and were used to evaluate the potential loss in accuracy with reduced genotyping. For both S1 and S2 the GEBV accuracies were similar when the prediction set was not genotyped and increased with the addition of low-density genotypes, with the increase larger for S2 than S1.</p> <p>Conclusions</p> <p>Genotype imputation using a long haplotype library and segregation analysis is promising for application in sparsely-genotyped pedigrees. The results of this study suggest that dense genotypes can be imputed for selection candidates with some loss in genomic breeding value accuracy, but with levels of accuracy higher than traditional BLUP estimated breeding values. Accurate genotype imputation would allow for a single low-density SNP panel to be used across traits.</p

Preoperative predictors of death and sustained ventricular tachycardia after pulmonary valve replacement in patients with repaired tetralogy of fallot enrolled in the INDICATOR Cohort

Background -Risk factors for adverse clinical outcomes have been identified in patients with repaired tetralogy of Fallot (rTOF) before pulmonary valve replacement (PVR). However, pre-PVR predictors for post-PVR sustained ventricular tachycardia (VT) and death have not been identified. Methods -Patients with rTOF enrolled in the INDICATOR cohort-a 4-center international cohort study- who had a comprehensive preoperative evaluation and subsequently underwent PVR were included. Pre-procedural clinical, electrocardiogram, cardiovascular magnetic resonance (CMR), and postoperative outcome data were analyzed. Cox proportional hazards multivariable regression analysis was used to evaluate factors associated with time from pre-PVR CMR until the primary outcome-death, aborted sudden cardiac death, or sustained VT. Results -Of the 452 eligible patients (median age at PVR 25.8 years), 36 (8%) reached the primary outcome (27 deaths, 2 resuscitated death, and 7 sustained VT) at a median time after PVR of 6.5 years. Cox proportional hazards regression identified pre-PVR right ventricular (RV) ejection fraction < 40% (hazard ratio [HR] 2.39; 95% confidence interval [CI] 1.18 to 4.85; P = 0.02), RV mass-to-volume ratio ≥ 0.45 g/mL (HR 4.08; 95%, CI 1.57 to 10.6; P = 0.004), and age at PVR ≥ 28 years (HR 3.10; 95% CI 1.42 to 6.78; P = 0.005) as outcome predictors. In a subgroup analysis of 230 patients with Doppler data, predicted RV systolic pressure ≥40 mm Hg was associated with the primary outcome (HR 3.42; 95% CI 1.09 to 10.7; P = 0.04). Preoperative predictors of a composite secondary outcome-postoperative arrhythmias and heart failure-included older age at PVR, pre-PVR atrial tachyarrhythmias, and a higher left ventricular end-systolic volume index. Conclusions -In this observational investigation of patients with rTOF, an older age at PVR and pre-PVR RV hypertrophy and dysfunction were predictive of shorter time to postoperative death and sustained VT. These findings may inform the timing of PVR if confirmed by prospective clinical trials

A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

<p>Abstract</p> <p>Background</p> <p>Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation.</p> <p>Methods</p> <p>An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis.</p> <p>Results</p> <p>Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored.</p> <p>Conclusions</p> <p>The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations.</p

Half-integer quantized anomalous thermal Hall effect in the Kitaev material α\alpha-RuCl3_3

Heat transport mediated by Majorana edge modes in a magnetic insulator leads to a half-integer thermal quantum Hall conductance, which has recently been reported for the two-dimensional honeycomb material $\alpha$-RuCl$_3$. While the conventional electronic Hall effect requires a perpendicular magnetic field, we find that this is not the case in $\alpha$-RuCl$_3$. Strikingly, the thermal Hall plateau appears even for a magnetic field with no out-of-plane components. The field-angular variation of the quantized thermal Hall conductance has the same sign structure of the topological Chern number, which is either $\pm$1, as the Majorana band structure of the pure Kitaev spin liquid. This observation of a half-integer anomalous thermal Hall effect firmly establishes that the Kitaev interaction is primarily responsible and that the non-Abelian topological order associated with fractionalization of the local magnetic moments persists even in the presence of non-Kitaev interactions in $\alpha$-RuCl$_3$.Comment: 14 pages, 4 figure

Changes in urinary metabolomic profile during relapsing renal vasculitis

Current biomarkers of renal disease in systemic vasculitis lack predictive value and are insensitive to early damage. To identify novel biomarkers of renal vasculitis flare, we analysed the longitudinal urinary metabolomic profile of a rat model of anti-neutrophil cytoplasmic antibody (ANCA) vasculitis. Wistar-Kyoto (WKY) rats were immunised with human myeloperoxidase (MPO). Urine was obtained at regular intervals for 181 days, after which relapse was induced by re-challenge with MPO. Urinary metabolites were assessed in an unbiased fashion using nuclear magnetic resonance (NMR) spectroscopy, and analysed using partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLS-R). At 56 days post-immunisation, we found that rats with vasculitis had a significantly different urinary metabolite profile than control animals; the observed PLS-DA clusters dissipated between 56 and 181 days, and re-emerged with relapse. The metabolites most altered in rats with active or relapsing vasculitis were trimethylamine N-oxide (TMAO), citrate and 2-oxoglutarate. Myo-inositol was also moderately predictive. The key urine metabolites identified in rats were confirmed in a large cohort of patients using liquid chromatography-mass spectrometry (LC-MS). Hypocitraturia and elevated urinary myo-inositol remained associated with active disease, with the urine myo-inositol:citrate ratio being tightly correlated with active renal vasculitis

A Unifying Model of Genome Evolution Under Parsimony

We present a data structure called a history graph that offers a practical basis for the analysis of genome evolution. It conceptually simplifies the study of parsimonious evolutionary histories by representing both substitutions and double cut and join (DCJ) rearrangements in the presence of duplications. The problem of constructing parsimonious history graphs thus subsumes related maximum parsimony problems in the fields of phylogenetic reconstruction and genome rearrangement. We show that tractable functions can be used to define upper and lower bounds on the minimum number of substitutions and DCJ rearrangements needed to explain any history graph. These bounds become tight for a special type of unambiguous history graph called an ancestral variation graph (AVG), which constrains in its combinatorial structure the number of operations required. We finally demonstrate that for a given history graph $G$, a finite set of AVGs describe all parsimonious interpretations of $G$, and this set can be explored with a few sampling moves.Comment: 52 pages, 24 figure

The Huntington's disease mutation impairs Huntingtin's role in the transport of NF-κB from the synapse to the nucleus

Expansion of a polyglutamine (polyQ) tract in the Huntingtin (Htt) protein causes Huntington's disease (HD), a fatal inherited neurodegenerative disorder. Loss of the normal function of Htt is thought to be an important pathogenetic component of HD. However, the function of wild-type Htt is not well defined. Htt is thought to be a multifunctional protein that plays distinct roles in several biological processes, including synaptic transmission, intracellular transport and neuronal transcription. Here, we show with biochemical and live cell imaging studies that wild-type Htt stimulates the transport of nuclear factor κ light-chain-enhancer of activated B cells (NF-κB) out of dendritic spines (where NF-κB is activated by excitatory synaptic input) and supports a high level of active NF-κB in neuronal nuclei (where NF-κB stimulates the transcription of target genes). We show that this novel function of Htt is impaired by the polyQ expansion and thus may contribute to the etiology of HD