The Linkage Phase of the Polymorphism KCNH2-K897T Influences the Electrophysiological Phenotype in hiPSC Models of LQT2

While rare mutations in ion channel genes are primarily responsible for inherited cardiac arrhythmias, common genetic variants are also an important contributor to the clinical heterogeneity observed among mutation carriers. The common single nucleotide polymorphism (SNP) KCNH2-K897T is associated with QT interval duration, but its influence on the disease phenotype in patients with long QT syndrome type 2 (LQT2) remains unclear. Human induced pluripotent stem cells (hiPSCs), coupled with advances in gene editing technologies, are proving an invaluable tool for modeling cardiac genetic diseases and identifying variants responsible for variability in disease expressivity. In this study, we have used isogenic hiPSC-derived cardiomyocytes (hiPSC-CMs) to establish the functional consequences of having the KCNH2-K897T SNP in cis- or trans-orientation with LQT2-causing missense variants either within the pore-loop domain (KCNH2A561T/WT) or tail region (KCNH2N996I/WT) of the potassium ion channel, human ether-a-go-go-related gene (hERG). When KCNH2-K897T was on the same allele (cis) as the primary mutation, the hERG channel in hiPSC-CMs exhibited faster activation and deactivation kinetics compared to their trans-oriented counterparts. Consistent with this, hiPSC-CMs with KCNH2-K897T in cis orientation had longer action and field potential durations. Furthermore, there was an increased occurrence of arrhythmic events upon pharmacological blocking of hERG. Collectively, these results indicate that the common polymorphism KCNH2-K897T differs in its influence on LQT2-causing KCNH2 mutations depending on whether it is present in cis or trans. This study corroborates hiPSC-CMs as a powerful platform to investigate the modifying effects of common genetic variants on inherited cardiac arrhythmias and aids in unraveling their contribution to the variable expressivity of these diseases.

Prediction ability of genome-wide markers in Pinus taeda L. within and between population is affected by relatedness to the training population and trait genetic architecture

Genomic prediction has the potential to significantly increase the rate of genetic gain in tree breeding programs. In this study, a clonally replicated population (n = 2063) was used to train a genomic prediction model. The model was validated both within the training population and in a separate population (n = 451). The prediction abilities from random (20% vs. 80%) cross validation within the training population were 0.56 and 0.78 for height and stem form, respectively. Removal of all full-sib relatives within the training population resulted in ∼50% reduction in their genomic prediction ability for both traits. The average prediction ability for all 451 individual trees was 0.29 for height and 0.57 for stem form. The degree of genetic linkage (full sib family, half sib family, unrelated) between the training and validation sets had a strong impact on prediction ability for stem form but not for height. A dominant dwarfing allele, the first to be reported in a conifer species, was discovered via GWAS on linkage group 5 that conferred a 0.33 m mean height reduction. However, the QTL was family specific. The rapid decay of LD, large genome size, and inconsistencies in marker-QTL linkage phase suggest that large, diverse training populations are needed for genomic selection in Pinus taeda L.

Finite element simulation of marine generators

В статье рассмотрено численное моделирование синхронного генератора. Описана последовательность создания геометрической модели. Представлены результаты численного моделирования статической и динамической задачи. Получены временные осциллограммы потокосцепления, фазных токов и напряжений, сил и моментов. На их основании получены частотные характеристики заданного генератора на холостых режимах. С помощью вейвлет-преобразования проведен анализ переходного процесса. Исследование показало, что существует три частотные области: область нарастания скорости, достижение критической скорости и выход на установившийся режим. Анализ коэффициентов вейвлет-преобразования исследуемого сигнала дал информацию об энергии, содержащейся в соответствующих частотных составляющих ряда. Данная численная модель дает возможность идентифицировать спектры напряжений, токов, сил и моментов, соответствующих механическим и электромагнитным дефектам. Показана возможность диагностирования дефектов генератора, обусловленного эксцентриситетом ротора, с помощью модельного исследования на пусковых режимах. Наличие эксцентриситета ротора приводит к появлению гармонической составляющей в спектре силы большой амплитуды с максимальным значением на низкой частоте. The sequence of creating a geometric model is described. The results of numerical simulation of static and dynamic problems are presented. Time oscillograms of flux linkage, phase currents and voltages, forces and moments were obtained. The analysis of the transient process is carried out using the wavelet transform. The study showed that there are three frequency ranges: the area of increasing speed, reaching critical speed and reaching steady state. Analysis of the wavelet transform coefficients gave information about the energy, which is contained in the corresponding frequency components of the series. This numerical model makes it possible to identify the spectrum of voltages, currents, forces and moments corresponding to mechanical and electromagnetic defects. The possibility of diagnosing the eccentricity of the rotor using a model study in starting modes is shown. Eccentricity leads to the appearance of a harmonic component in the power spectrum with a large amplitude with a maximum value at a low frequency.

fullsibQTL: an R package for QTL mapping in biparental populations of outcrossing species

ABSTRACTAccurate QTL mapping in outcrossing species requires software programs which consider genetic features of these populations, such as markers with different segregation patterns and different level of information. Although the available mapping procedures to date allow inferring QTL position and effects, they are mostly not based on multilocus genetic maps. Having a QTL analysis based in such maps is crucial since they allow informative markers to propagate their information to less informative intervals of the map. We developed fullsibQTL, a novel and freely available R package to perform composite interval QTL mapping considering outcrossing populations and markers with different segregation patterns. It allows to estimate QTL position, effects, segregation patterns, and linkage phase with flanking markers. Additionally, several statistical and graphical tools are implemented, for straightforward analysis and interpretations. fullsibQTL is an R open source package with C and R source code (GPLv3). It is multiplatform and can be installed from https://github.com/augusto-garcia/fullsibQTL.

Exploring the potential genetic heterogeneity in the incidence of hoof and leg disorders in Austrian Fleckvieh and Braunvieh cattle

BackgroundGenetic heterogeneity denotes the situation when different genetic architectures underlying diverse populations result in the same phenotype. In this study, we explore the nature of differences in the incidence of the number of hoof and leg disorders between Braunvieh and Fleckvieh cattle in the context of genetic heterogeneity between the breeds.ResultsDespite potentially higher power of testing due to twice as large sample size, none of the SNPs was significantly associated with the number of hoof and leg disorders in Fleckvieh, while 16 SNPs were significant in Braunvieh. The most promising candidate genes in Braunvieh are: CBLB on BTA01, which causes arthritis in rats; CAV2 on BTA04, which in effects mouse skeletal muscles; PTHLH on BTA05, which causes disease phenotypes related to the skeleton in humans, mice and zebrafish; SORCS2 on BTA06, which causes decreased susceptibility to injury in the mouse. Some of the significant SNPs (BTA01, BTA04, BTA05, BTA13, BTA16) reveal allelic heterogeneity – i.e. differences due to different allele frequencies between Fleckvieh and Braunvieh. Some of the significant regions (BTA01, BTA05, BTA13, BTA16) correlate to inter-breed differences in LD structure and may thus represent false-positive heterogeneity. However, positions on BTA06 (SORCS2), BTA14 and BTA24 mark Braunvieh-specific regions.ConclusionsWe hypothesise that the observed genetic heterogeneity of hoof and leg disorders is a by-product of multigenerational differential selection of the breeds – towards dairy production in the case of Braunvieh and towards beef production in the case of Fleckvieh. Based on the current data set it is no possibly to unequivocally confirm/exclude the hypothesis of genetic heterogeneity in the susceptibility to leg disorders between Fleckvieh and Braunvieh because only explore it through associations and not the causal mutations. Rationales against genetic heterogeneity comprise a limited power of detection of true associations as well as differences in the length of LD blocks and in linkage phase between breeds. On the other hand, multigenerational differential selection of the breeds and no systematic differences in LD structure between the breeds favour the heterogeneity hypothesis at some of the significant sites.

Linkage Analysis and Haplotype Phasing in Experimental Autopolyploid Populations with High Ploidy Level Using Hidden Markov Models

Modern SNP genotyping technologies allow measurement of the relative abundance of different alleles for a given locus and consequently estimation of their allele dosage, opening a new road for genetic studies in autopolyploids. Despite advances in genetic linkage analysis in autotetraploids, there is a lack of statistical models to perform linkage analysis in organisms with higher ploidy levels. In this paper, we present a statistical method to estimate recombination fractions and infer linkage phases in full-sib populations of autopolyploid species with even ploidy levels for a set of SNP markers using hidden Markov models. Our method uses efficient two-point procedures to reduce the search space for the best linkage phase configuration and reestimate the final parameters by maximizing the likelihood of the Markov chain. To evaluate the method, and demonstrate its properties, we rely on simulations of autotetraploid, autohexaploid and autooctaploid populations and on a real tetraploid potato data set. The results show the reliability of our approach, including situations with complex linkage phase scenarios in hexaploid and octaploid populations.

Meiotic Drive and Survival Probability of Newly Inverted Chromosomes

When a new gene arrangement is generated by spontaneous mutation its survival is uncertain and largely unaffected by associated fitness effects. However, if a new chromosomal inversion is introduced into a population already polymorphic for inversions, then its survival probability will be a function of the relative size, position, and linkage phase of the gene rearrangements. This dependence on structural features is due to the complex meiotic behavior of overlapping inversions generating asymmetric dyads, which in turn cause both underdominance and meiotic drive/drag. Therefore, survival probabilities of new inversions can be expressed in terms of the probability of forming an asymmetric dyad via crossing over in meiosis I and the probability of recovery from that asymmetric dyad during disjunction in meiosis II. This model of female meiotic drive was parameterized with data from published experiments on laboratory constructs in Drosophila melanogaster. Generalizing this analysis to all possible inversions predicts a bias towards larger, proximally located inversions having a shorter persistence time in populations. These population genetic predictions are consistent with cytological evidence from natural populations of D. melanogaster. This research mathematically formalizes a cytogenetic mechanism for female meiotic drive/drag as the major force governing behavior of new gene arrangements entering populations, and therefore determining the genomic distribution of segregating inversion polymorphism.

Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models

Modern SNP genotyping technologies allow to measure the relative abundance of different alleles for a given locus and consequently to estimate their allele dosage, opening a new road for genetic studies in autopolyploids. Despite advances in genetic linkage analysis in autotetraploids, there is a lack of statistical models to perform linkage analysis in organisms with higher ploidy levels. In this paper, we present a statistical method to estimate recombination fractions and infer linkage phases in full-sib populations of autopolyploid species with even ploidy levels in a sequence of SNP markers using hidden Markov models. Our method uses efficient two-point procedures to reduce the search space for the best linkage phase configuration and reestimate the final parameters using the maximum-likelihood of the Markov chain. To evaluate the method, and demonstrate its properties, we rely on simulations of autotetraploid, autohexaploid and autooctaploid populations and on a real tetraploid potato data set. The results demonstrate the reliability of our approach, including situations with complex linkage phase scenarios in hexaploid and octaploid populations.Author summaryIn this paper, we present a complete multilocus solution based on hidden Markov models to estimate recombination fractions and infer the linkage phase configuration in full-sib mapping populations with even ploidy levels under random chromosome segregation. We also present an efficient pairwise loci analysis to be used in cases were the multilocus analysis becomes compute-intensive.

Efficiency of genomic prediction of non-assessed single crosses

ABSTRACTAn important application of genomic selection in plant breeding is the prediction of untested single crosses (SCs). Most investigations on the prediction efficiency were based on tested SCs, using cross-validation. The main objective was to assess the prediction efficiency by correlating the predicted and true genotypic values of untested SCs (accuracy) and measuring the efficacy of identification of the best 300 untested SCs (coincidence), using simulated data. We assumed 10,000 SNPs, 400 QTLs, two groups of 70 selected DH lines, and 4,900 SCs. The heritabilities for the assessed SCs were 30, 60 and 100%. The scenarios included three sampling processes of DH lines, two sampling processes of SCs for testing, two SNP densities, DH lines from distinct and same populations, DH lines from populations with lower LD, two genetic models, three statistical models, and three statistical approaches. We derived a model for genomic prediction based on SNP average effects of substitution and dominance deviations. The prediction accuracy is not affected by the linkage phase. The prediction of untested SCs is very efficient. The accuracies and coincidences ranged from approximately 0.8 and 0.5, respectively, under low heritability, to 0.9 and 0.7, assuming high heritability. Additionally, we highlighted the relevance of the overall LD and evidenced that efficient prediction of untested SCs can be achieved for crops that show no heterotic pattern, for reduced training set size (10%), for SNP density of 1 cM, and for distinct sampling processes of DH lines, based on random choice of the SCs for testing.

An across-breed genome wide association analysis of susceptibility to paratuberculosis in dairy cattle

Paratuberculosis is a chronic disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). It occurs worldwide and causes a significant loss in the animal production industry. There is no cure for MAP infection and vaccination is problematic. Identification of genetics of susceptibility could be a useful adjunct for programs that focus on management, testing and culling of diseased animals. A case-control, genome-wide association study (GWAS) was conducted using Holstein and Jersey cattle in a combined analysis in order to identify markers and chromosomal regions associated with susceptibility to MAP infection across-breed. A mixed-model method (GRAMMAR-GC) implemented in the GenABEL R package and a Bayes C analysis implemented in GenSel software were used as alternative approaches to conduct GWAS analysis focused on single SNPs and chromosomal segments, respectively. After conducting quality control, 22 406 SNPs from 2157 individuals were available for the GRAMMAR-GC (Bayes C) analysis and 45 640 SNPs from 2199 individuals were available for the Bayes C analysis. One SNP located on BTA27 (8·6 Mb) was identified as moderately associated (P < 5 × 10−5, FDR = 0·44) in the GRAMMAR-GC analysis of the combined breed data. Nine 1 Mb windows located on BTA 2, 3 (3 windows), 6, 8, 25, 27 and 29 each explained ≥1% of the total proportion of genetic variance in the Bayes C analysis. In an analysis ignoring differences in linkage phase, two moderately significantly associated SNPs were identified; ARS-BFGL-NGS-19381 on BTA23 (32 Mb) and Hapmap40994-BTA-46361 on BTA19 (61 Mb). New common genomic regions and candidate genes have been identified from the across-breed analysis that might be involved in the immune response and susceptibility to MAP infection.