Genomewide predictions from maize single-cross data.

PubMed

Massman, Jon M; Gordillo, Andres; Lorenzana, Robenzon E; Bernardo, Rex

2013-01-01

Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r(MG)) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r(MG) values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r(MG) values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r(2) between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (cofmpared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.

There is room for selection in a small local pig breed when using optimum contribution selection: a simulation study.

PubMed

Gourdine, J L; Sørensen, A C; Rydhmer, L

2012-01-01

Selection progress must be carefully balanced against the conservation of genetic variation in small populations of local breeds. Well-defined breeding programs with specified selection traits are rare in local pig breeds. Given the small population size, the focus is often on the management of genetic diversity. However, in local breeds, optimum contribution selection can be applied to control the rate of inbreeding and to avoid reduced performance in traits with high market value. The aim of this study was to assess the extent to which a breeding program aiming for improved product quality in a small local breed would be feasible. We used stochastic simulations to compare 25 scenarios. The scenarios differed in size of population, selection intensity of boars, type of selection (random selection, truncation selection based on BLUP breeding values, or optimum contribution selection based on BLUP breeding values), and heritability of the selection trait. It was assumed that the local breed is used in an extensive system for a high-meat-quality market. The simulations showed that in the smallest population (300 female reproducers), inbreeding increased by 0.8% when selection was performed at random. With optimum contribution selection, genetic progress can be achieved that is almost as great as that with truncation selection based on BLUP breeding values (0.2 to 0.5 vs. 0.3 to 0.5 genetic SD, P < 0.05), but at a considerably decreased rate of inbreeding (0.7 to 1.2 vs. 2.3 to 5.7%, P < 0.01). This confirmation of the potential utilization of OCS even in small populations is important in the context of sustainable management and the use of animal genetic resources.

Accuracies of breeding values for dry matter intake using nongenotyped animals and predictor traits in different lactations.

PubMed

Manzanilla-Pech, C I V; Veerkamp, R F; de Haas, Y; Calus, M P L; Ten Napel, J

2017-11-01

Given the interest of including dry matter intake (DMI) in the breeding goal, accurate estimated breeding values (EBV) for DMI are needed, preferably for separate lactations. Due to the limited amount of records available on DMI, 2 main approaches have been suggested to compute those EBV: (1) the inclusion of predictor traits, such as fat- and protein-corrected milk (FPCM) and live weight (LW), and (2) the addition of genomic information of animals using what is called genomic prediction. Recently, several methodologies to estimate EBV utilizing genomic information (EBV) have become available. In this study, a new method known as single-step ridge-regression BLUP (SSRR-BLUP) is suggested. The SSRR-BLUP method does not have an imposed limit on the number of genotyped animals, as the commonly used methods do. The objective of this study was to estimate genetic parameters using a relatively large data set with DMI records, as well as compare the accuracies of the EBV for DMI. These accuracies were obtained using 4 different methods: BLUP (using pedigree for all animals with phenotypes), genomic BLUP (GBLUP; only for genotyped animals), single-step GBLUP (SS-GBLUP), and SSRR-BLUP (for genotyped and nongenotyped animals). Records from different lactations, with or without predictor traits (FPCM and LW), were used in the model. Accuracies of EBV for DMI (defined as the correlation between the EBV and pre-adjusted DMI phenotypes divided by the average accuracy of those phenotypes) ranged between 0.21 and 0.38 across methods and scenarios. Accuracies of EBV for DMI using BLUP were the lowest accuracies obtained across methods. Meanwhile, accuracies of EBV for DMI were similar in SS-GBLUP and SSRR-BLUP, and lower for the GBLUP method. Hence, SSRR-BLUP could be used when the number of genotyped animals is large, avoiding the construction of the inverse genomic relationship matrix. Adding information on DMI from different lactations in the reference population gave higher accuracies in comparison when only lactation 1 was included. Finally, no benefit was obtained by adding information on predictor traits to the reference population when DMI was already included. However, in the absence of DMI records, having records on FPCM and LW from different lactations is a good way to obtain EBV with a relatively good accuracy. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Simultaneous fitting of genomic-BLUP and Bayes-C components in a genomic prediction model.

PubMed

Iheshiulor, Oscar O M; Woolliams, John A; Svendsen, Morten; Solberg, Trygve; Meuwissen, Theo H E

2017-08-24

The rapid adoption of genomic selection is due to two key factors: availability of both high-throughput dense genotyping and statistical methods to estimate and predict breeding values. The development of such methods is still ongoing and, so far, there is no consensus on the best approach. Currently, the linear and non-linear methods for genomic prediction (GP) are treated as distinct approaches. The aim of this study was to evaluate the implementation of an iterative method (called GBC) that incorporates aspects of both linear [genomic-best linear unbiased prediction (G-BLUP)] and non-linear (Bayes-C) methods for GP. The iterative nature of GBC makes it less computationally demanding similar to other non-Markov chain Monte Carlo (MCMC) approaches. However, as a Bayesian method, GBC differs from both MCMC- and non-MCMC-based methods by combining some aspects of G-BLUP and Bayes-C methods for GP. Its relative performance was compared to those of G-BLUP and Bayes-C. We used an imputed 50 K single-nucleotide polymorphism (SNP) dataset based on the Illumina Bovine50K BeadChip, which included 48,249 SNPs and 3244 records. Daughter yield deviations for somatic cell count, fat yield, milk yield, and protein yield were used as response variables. GBC was frequently (marginally) superior to G-BLUP and Bayes-C in terms of prediction accuracy and was significantly better than G-BLUP only for fat yield. On average across the four traits, GBC yielded a 0.009 and 0.006 increase in prediction accuracy over G-BLUP and Bayes-C, respectively. Computationally, GBC was very much faster than Bayes-C and similar to G-BLUP. Our results show that incorporating some aspects of G-BLUP and Bayes-C in a single model can improve accuracy of GP over the commonly used method: G-BLUP. Generally, GBC did not statistically perform better than G-BLUP and Bayes-C, probably due to the close relationships between reference and validation individuals. Nevertheless, it is a flexible tool, in the sense, that it simultaneously incorporates some aspects of linear and non-linear models for GP, thereby exploiting family relationships while also accounting for linkage disequilibrium between SNPs and genes with large effects. The application of GBC in GP merits further exploration.

Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2017-01-01

An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differences between these types of GP methods suggest a diagnostic for revealing genetic architectures underlying traits of interest. In addition to genetic architecture, the performance of GP methods may be influenced by the sample size of the training population, the number of QTL, and the proportion of phenotypic variability due to genotypic variability (heritability). Possible values for these factors and the number of combinations of the factor levels that influence the performance of GP methods can be large. Thus, efficient methods for identifying combinations of factor levels that produce most accurate GPs is needed. Herein, we employ response surface methods (RSMs) to find the experimental conditions that produce the most accurate GPs. We illustrate RSM with an example of simulated doubled haploid populations and identify the combination of factors that maximize the difference between prediction accuracies of best linear unbiased prediction (BLUP) and support vector machine (SVM) GP methods. The greatest impact on the response is due to the genetic architecture of the population, heritability of the trait, and the sample size. When epistasis is responsible for all of the genotypic variance and heritability is equal to one and the sample size of the training population is large, the advantage of using the SVM method vs. the BLUP method is greatest. However, except for values close to the maximum, most of the response surface shows little difference between the methods. We also determined that the conditions resulting in the greatest prediction accuracy for BLUP occurred when genetic architecture consists solely of additive effects, and heritability is equal to one. PMID:28720710

Selecting elephant grass families and progenies to produce bioenergy through mixed models (REML/BLUP).

PubMed

Rodrigues, E V; Daher, R F; Dos Santos, A; Vivas, M; Machado, J C; Gravina, G do A; de Souza, Y P; Vidal, A K; Rocha, A Dos S; Freitas, R S

2017-05-18

Brazil has great potential to produce bioenergy since it is located in a tropical region that receives high incidence of solar energy and presents favorable climatic conditions for such purpose. However, the use of bioenergy in the country is below its productivity potential. The aim of the current study was to select full-sib progenies and families of elephant grass (Pennisetum purpureum S.) to optimize phenotypes relevant to bioenergy production through mixed models (REML/BLUP). The circulating diallel-based crossing of ten elephant grass genotypes was performed. An experimental design using the randomized block methodology, with three repetitions, was set to assess both the hybrids and the parents. Each plot comprised 14-m rows, 1.40 m spacing between rows, and 1.40 m spacing between plants. The number of tillers, plant height, culm diameter, fresh biomass production, dry biomass rate, and the dry biomass production were assessed. Genetic-statistical analyses were performed through mixed models (REML/BLUP). The genetic variance in the assessed families was explained through additive genetic effects and dominance genetic effects; the dominance variance was prevalent. Families such as Capim Cana D'África x Guaçu/I.Z.2, Cameroon x Cuba-115, CPAC x Cuba-115, Cameroon x Guaçu/I.Z.2, and IAC-Campinas x CPAC showed the highest dry biomass production. The family derived from the crossing between Cana D'África and Guaçu/I.Z.2 showed the largest number of potential individuals for traits such as plant height, culm diameter, fresh biomass production, dry biomass production, and dry biomass rate. The individual 5 in the family Cana D'África x Guaçu/I.Z.2, planted in blocks 1 and 2, showed the highest dry biomass production.

Using single-step genomic best linear unbiased predictor to enhance the mitigation of seasonal losses due to heat stress in pigs.

PubMed

Fragomeni, B O; Lourenco, D A L; Tsuruta, S; Bradford, H L; Gray, K A; Huang, Y; Misztal, I

2016-12-01

The purposes of this study were to analyze the impact of seasonal losses due to heat stress in pigs from different breeds raised in different environments and to evaluate the accuracy improvement from adding genomic information to genetic evaluations. Data were available for 2 different swine populations: purebred Duroc animals raised in Texas and North Carolina and commercial crosses of Duroc and F females (Landrace × Large White) raised in Missouri and North Carolina; pedigrees provided links for animals from different states. Pedigree information was available for 553,442 animals, of which 8,232 pure breeds were genotyped. Traits were BW at 170 d for purebred animals and HCW for crossbred animals. Analyses were done with an animal model as either single- or 2-trait models using phenotypes measured in different states as separate traits. Additionally, reaction norm models were fitted for 1 or 2 traits using heat load index as a covariable. Heat load was calculated as temperature-humidity index greater than 70 and was averaged over 30 d prior to data collection. Variance components were estimated with average information REML, and EBV and genomic EBV (GEBV) with BLUP or single-step genomic BLUP (ssGBLUP). Validation was assessed for 146 genotyped sires with progeny in the last generation. Accuracy was calculated as a correlation between EBV and GEBV using reduced data (all animals, except the last generation) and using complete data. Heritability estimates for purebred animals were similar across states (varying from 0.23 to 0.26), and reaction norm models did not show evidence of a heat stress effect. Genetic correlations between states for heat loads were always strong (>0.91). For crossbred animals, no differences in heritability were found in single- or 2-trait analysis (from 0.17 to 0.18), and genetic correlations between states were moderate (0.43). In the reaction norm for crossbreeds, heritabilities ranged from 0.15 to 0.30 and genetic correlations between heat loads were as weak as 0.36, with heat load ranging from 0 to 12. Accuracies with ssGBLUP were, on average, 25% greater than with BLUP. Accuracies were greater in 2-trait reaction norm models and at extreme heat load values. Impacts of seasonality are evident only for crossbred animals. Genomic information can help producers mitigate heat stress in swine by identifying superior sires that are more resistant to heat stress.

Ridge, Lasso and Bayesian additive-dominance genomic models.

PubMed

Azevedo, Camila Ferreira; de Resende, Marcos Deon Vilela; E Silva, Fabyano Fonseca; Viana, José Marcelo Soriano; Valente, Magno Sávio Ferreira; Resende, Márcio Fernando Ribeiro; Muñoz, Patricio

2015-08-25

A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes). G-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close. Amongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (-2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.

REML/BLUP and sequential path analysis in estimating genotypic values and interrelationships among simple maize grain yield-related traits.

PubMed

Olivoto, T; Nardino, M; Carvalho, I R; Follmann, D N; Ferrari, M; Szareski, V J; de Pelegrin, A J; de Souza, V Q

2017-03-22

Methodologies using restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) in combination with sequential path analysis in maize are still limited in the literature. Therefore, the aims of this study were: i) to use REML/BLUP-based procedures in order to estimate variance components, genetic parameters, and genotypic values of simple maize hybrids, and ii) to fit stepwise regressions considering genotypic values to form a path diagram with multi-order predictors and minimum multicollinearity that explains the relationships of cause and effect among grain yield-related traits. Fifteen commercial simple maize hybrids were evaluated in multi-environment trials in a randomized complete block design with four replications. The environmental variance (78.80%) and genotype-vs-environment variance (20.83%) accounted for more than 99% of the phenotypic variance of grain yield, which difficult the direct selection of breeders for this trait. The sequential path analysis model allowed the selection of traits with high explanatory power and minimum multicollinearity, resulting in models with elevated fit (R 2 > 0.9 and ε < 0.3). The number of kernels per ear (NKE) and thousand-kernel weight (TKW) are the traits with the largest direct effects on grain yield (r = 0.66 and 0.73, respectively). The high accuracy of selection (0.86 and 0.89) associated with the high heritability of the average (0.732 and 0.794) for NKE and TKW, respectively, indicated good reliability and prospects of success in the indirect selection of hybrids with high-yield potential through these traits. The negative direct effect of NKE on TKW (r = -0.856), however, must be considered. The joint use of mixed models and sequential path analysis is effective in the evaluation of maize-breeding trials.

Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture.

PubMed

Vallejo, Roger L; Leeds, Timothy D; Gao, Guangtu; Parsons, James E; Martin, Kyle E; Evenhuis, Jason P; Fragomeni, Breno O; Wiens, Gregory D; Palti, Yniv

2017-02-01

Previously, we have shown that bacterial cold water disease (BCWD) resistance in rainbow trout can be improved using traditional family-based selection, but progress has been limited to exploiting only between-family genetic variation. Genomic selection (GS) is a new alternative that enables exploitation of within-family genetic variation. We compared three GS models [single-step genomic best linear unbiased prediction (ssGBLUP), weighted ssGBLUP (wssGBLUP), and BayesB] to predict genomic-enabled breeding values (GEBV) for BCWD resistance in a commercial rainbow trout population, and compared the accuracy of GEBV to traditional estimates of breeding values (EBV) from a pedigree-based BLUP (P-BLUP) model. We also assessed the impact of sampling design on the accuracy of GEBV predictions. For these comparisons, we used BCWD survival phenotypes recorded on 7893 fish from 102 families, of which 1473 fish from 50 families had genotypes [57 K single nucleotide polymorphism (SNP) array]. Naïve siblings of the training fish (n = 930 testing fish) were genotyped to predict their GEBV and mated to produce 138 progeny testing families. In the following generation, 9968 progeny were phenotyped to empirically assess the accuracy of GEBV predictions made on their non-phenotyped parents. The accuracy of GEBV from all tested GS models were substantially higher than the P-BLUP model EBV. The highest increase in accuracy relative to the P-BLUP model was achieved with BayesB (97.2 to 108.8%), followed by wssGBLUP at iteration 2 (94.4 to 97.1%) and 3 (88.9 to 91.2%) and ssGBLUP (83.3 to 85.3%). Reducing the training sample size to n = ~1000 had no negative impact on the accuracy (0.67 to 0.72), but with n = ~500 the accuracy dropped to 0.53 to 0.61 if the training and testing fish were full-sibs, and even substantially lower, to 0.22 to 0.25, when they were not full-sibs. Using progeny performance data, we showed that the accuracy of genomic predictions is substantially higher than estimates obtained from the traditional pedigree-based BLUP model for BCWD resistance. Overall, we found that using a much smaller training sample size compared to similar studies in livestock, GS can substantially improve the selection accuracy and genetic gains for this trait in a commercial rainbow trout breeding population.

Breeding and Genetics Symposium: really big data: processing and analysis of very large data sets.

PubMed

Cole, J B; Newman, S; Foertter, F; Aguilar, I; Coffey, M

2012-03-01

Modern animal breeding data sets are large and getting larger, due in part to recent availability of high-density SNP arrays and cheap sequencing technology. High-performance computing methods for efficient data warehousing and analysis are under development. Financial and security considerations are important when using shared clusters. Sound software engineering practices are needed, and it is better to use existing solutions when possible. Storage requirements for genotypes are modest, although full-sequence data will require greater storage capacity. Storage requirements for intermediate and results files for genetic evaluations are much greater, particularly when multiple runs must be stored for research and validation studies. The greatest gains in accuracy from genomic selection have been realized for traits of low heritability, and there is increasing interest in new health and management traits. The collection of sufficient phenotypes to produce accurate evaluations may take many years, and high-reliability proofs for older bulls are needed to estimate marker effects. Data mining algorithms applied to large data sets may help identify unexpected relationships in the data, and improved visualization tools will provide insights. Genomic selection using large data requires a lot of computing power, particularly when large fractions of the population are genotyped. Theoretical improvements have made possible the inversion of large numerator relationship matrices, permitted the solving of large systems of equations, and produced fast algorithms for variance component estimation. Recent work shows that single-step approaches combining BLUP with a genomic relationship (G) matrix have similar computational requirements to traditional BLUP, and the limiting factor is the construction and inversion of G for many genotypes. A naïve algorithm for creating G for 14,000 individuals required almost 24 h to run, but custom libraries and parallel computing reduced that to 15 m. Large data sets also create challenges for the delivery of genetic evaluations that must be overcome in a way that does not disrupt the transition from conventional to genomic evaluations. Processing time is important, especially as real-time systems for on-farm decisions are developed. The ultimate value of these systems is to decrease time-to-results in research, increase accuracy in genomic evaluations, and accelerate rates of genetic improvement.

Selection of core animals in the Algorithm for Proven and Young using a simulation model.

PubMed

Bradford, H L; Pocrnić, I; Fragomeni, B O; Lourenco, D A L; Misztal, I

2017-12-01

The Algorithm for Proven and Young (APY) enables the implementation of single-step genomic BLUP (ssGBLUP) in large, genotyped populations by separating genotyped animals into core and non-core subsets and creating a computationally efficient inverse for the genomic relationship matrix (G). As APY became the choice for large-scale genomic evaluations in BLUP-based methods, a common question is how to choose the animals in the core subset. We compared several core definitions to answer this question. Simulations comprised a moderately heritable trait for 95,010 animals and 50,000 genotypes for animals across five generations. Genotypes consisted of 25,500 SNP distributed across 15 chromosomes. Genotyping errors and missing pedigree were also mimicked. Core animals were defined based on individual generations, equal representation across generations, and at random. For a sufficiently large core size, core definitions had the same accuracies and biases, even if the core animals had imperfect genotypes. When genotyped animals had unknown parents, accuracy and bias were significantly better (p ≤ .05) for random and across generation core definitions. © 2017 The Authors. Journal of Animal Breeding and Genetics Published by Blackwell Verlag GmbH.

Response to Selection in Finite Locus Models with Nonadditive Effects.

PubMed

Esfandyari, Hadi; Henryon, Mark; Berg, Peer; Thomasen, Jørn Rind; Bijma, Piter; Sørensen, Anders Christian

2017-05-01

Under the finite-locus model in the absence of mutation, the additive genetic variation is expected to decrease when directional selection is acting on a population, according to quantitative-genetic theory. However, some theoretical studies of selection suggest that the level of additive variance can be sustained or even increased when nonadditive genetic effects are present. We tested the hypothesis that finite-locus models with both additive and nonadditive genetic effects maintain more additive genetic variance (VA) and realize larger medium- to long-term genetic gains than models with only additive effects when the trait under selection is subject to truncation selection. Four genetic models that included additive, dominance, and additive-by-additive epistatic effects were simulated. The simulated genome for individuals consisted of 25 chromosomes, each with a length of 1 M. One hundred bi-allelic QTL, 4 on each chromosome, were considered. In each generation, 100 sires and 100 dams were mated, producing 5 progeny per mating. The population was selected for a single trait (h2 = 0.1) for 100 discrete generations with selection on phenotype or BLUP-EBV. VA decreased with directional truncation selection even in presence of nonadditive genetic effects. Nonadditive effects influenced long-term response to selection and among genetic models additive gene action had highest response to selection. In addition, in all genetic models, BLUP-EBV resulted in a greater fixation of favorable and unfavorable alleles and higher response than phenotypic selection. In conclusion, for the schemes we simulated, the presence of nonadditive genetic effects had little effect in changes of additive variance and VA decreased by directional selection. © The American Genetic Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement

PubMed Central

Spindel, J E; Begum, H; Akdemir, D; Collard, B; Redoña, E; Jannink, J-L; McCouch, S

2016-01-01

To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable to keep pace with demand. Genomic selection (GS) is a new technique that helps accelerate the rate of genetic gain in breeding by using whole-genome data to predict the breeding value of offspring. Here, we describe a new GS model that combines RR-BLUP with markers fit as fixed effects selected from the results of a genome-wide-association study (GWAS) on the RR-BLUP training data. We term this model GS + de novo GWAS. In a breeding population of tropical rice, GS + de novo GWAS outperformed six other models for a variety of traits and in multiple environments. On the basis of these results, we propose an extended, two-part breeding design that can be used to efficiently integrate novel variation into elite breeding populations, thus expanding genetic diversity and enhancing the potential for sustainable productivity gains. PMID:26860200

On a stronger-than-best property for best prediction

NASA Astrophysics Data System (ADS)

Teunissen, P. J. G.

2008-03-01

The minimum mean squared error (MMSE) criterion is a popular criterion for devising best predictors. In case of linear predictors, it has the advantage that no further distributional assumptions need to be made, other then about the first- and second-order moments. In the spatial and Earth sciences, it is the best linear unbiased predictor (BLUP) that is used most often. Despite the fact that in this case only the first- and second-order moments need to be known, one often still makes statements about the complete distribution, in particular when statistical testing is involved. For such cases, one can do better than the BLUP, as shown in Teunissen (J Geod. doi: 10.1007/s00190-007-0140-6, 2006), and thus devise predictors that have a smaller MMSE than the BLUP. Hence, these predictors are to be preferred over the BLUP, if one really values the MMSE-criterion. In the present contribution, we will show, however, that the BLUP has another optimality property than the MMSE-property, provided that the distribution is Gaussian. It will be shown that in the Gaussian case, the prediction error of the BLUP has the highest possible probability of all linear unbiased predictors of being bounded in the weighted squared norm sense. This is a stronger property than the often advertised MMSE-property of the BLUP.

Genomic prediction of reproduction traits for Merino sheep.

PubMed

Bolormaa, S; Brown, D J; Swan, A A; van der Werf, J H J; Hayes, B J; Daetwyler, H D

2017-06-01

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording. © 2017 Stichting International Foundation for Animal Genetics.

Nucleotide polymorphisms in a pine ortholog of the Arabidopsis degrading enzyme cellulase KORRIGAN are associated with early growth performance in Pinus pinaster.

PubMed

Cabezas, José Antonio; González-Martínez, Santiago C; Collada, Carmen; Guevara, María Angeles; Boury, Christophe; de María, Nuria; Eveno, Emmanuelle; Aranda, Ismael; Garnier-Géré, Pauline H; Brach, Jean; Alía, Ricardo; Plomion, Christophe; Cervera, María Teresa

2015-09-01

We have carried out a candidate-gene-based association genetic study in Pinus pinaster Aiton and evaluated the predictive performance for genetic merit gain of the most significantly associated genes and single nucleotide polymorphisms (SNPs). We used a second generation 384-SNP array enriched with candidate genes for growth and wood properties to genotype mother trees collected in 20 natural populations covering most of the European distribution of the species. Phenotypic data for total height, polycyclism, root-collar diameter and biomass were obtained from a replicated provenance-progeny trial located in two sites with contrasting environments (Atlantic vs Mediterranean climate). General linear models identified strong associations between growth traits (total height and polycyclism) and four SNPs from the korrigan candidate gene, after multiple testing corrections using false discovery rate. The combined genomic breeding value predictions assessed for the four associated korrigan SNPs by ridge regression-best linear unbiased prediction (RR-BLUP) and cross-validation accounted for up to 8 and 15% of the phenotypic variance for height and polycyclic growth, respectively, and did not improve adding SNPs from other growth-related candidate genes. For root-collar diameter and total biomass, they accounted for 1.6 and 1.1% of the phenotypic variance, respectively, but increased to 15 and 4.1% when other SNPs from lp3.1, lp3.3 and cad were included in RR-BLUP models. These results point towards a desirable integration of candidate-gene studies as a means to pre-select relevant markers, and aid genomic selection in maritime pine breeding programs. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Accuracy of Genomic Prediction for Foliar Terpene Traits in Eucalyptus polybractea.

PubMed

Kainer, David; Stone, Eric A; Padovan, Amanda; Foley, William J; Külheim, Carsten

2018-06-11

Unlike agricultural crops, most forest species have not had millennia of improvement through phenotypic selection, but can contribute energy and material resources and possibly help alleviate climate change. Yield gains similar to those achieved in agricultural crops over millennia could be made in forestry species with the use of genomic methods in a much shorter time frame. Here we compare various methods of genomic prediction for eight traits related to foliar terpene yield in Eucalyptus polybractea , a tree grown predominantly for the production of Eucalyptus oil. The genomic markers used in this study are derived from shallow whole genome sequencing of a population of 480 trees. We compare the traditional pedigree-based additive best linear unbiased predictors (ABLUP), genomic BLUP (GBLUP), BayesB genomic prediction model, and a form of GBLUP based on weighting markers according to their influence on traits (BLUP|GA). Predictive ability is assessed under varying marker densities of 10,000, 100,000 and 500,000 SNPs. Our results show that BayesB and BLUP|GA perform best across the eight traits. Predictive ability was higher for individual terpene traits, such as foliar α-pinene and 1,8-cineole concentration (0.59 and 0.73, respectively), than aggregate traits such as total foliar oil concentration (0.38). This is likely a function of the trait architecture and markers used. BLUP|GA was the best model for the two biomass related traits, height and 1 year change in height (0.25 and 0.19, respectively). Predictive ability increased with marker density for most traits, but with diminishing returns. The results of this study are a solid foundation for yield improvement of essential oil producing eucalypts. New markets such as biopolymers and terpene-derived biofuels could benefit from rapid yield increases in undomesticated oil-producing species. Copyright © 2018, G3: Genes, Genomes, Genetics.

Cow genotyping strategies for genomic selection in a small dairy cattle population.

PubMed

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Trait-specific long-term consequences of genomic selection in beef cattle.

PubMed

de Rezende Neves, Haroldo Henrique; Carvalheiro, Roberto; de Queiroz, Sandra Aidar

2018-02-01

Simulation studies allow addressing consequences of selection schemes, helping to identify effective strategies to enable genetic gain and maintain genetic diversity. The aim of this study was to evaluate the long-term impact of genomic selection (GS) in genetic progress and genetic diversity of beef cattle. Forward-in-time simulation generated a population with pattern of linkage disequilibrium close to that previously reported for real beef cattle populations. Different scenarios of GS and traditional pedigree-based BLUP (PBLUP) selection were simulated for 15 generations, mimicking selection for female reproduction and meat quality. For GS scenarios, an alternative selection criterion was simulated (wGBLUP), intended to enhance long-term gains by attributing more weight to favorable alleles with low frequency. GS allowed genetic progress up to 40% greater than PBLUP, for female reproduction and meat quality. The alternative criterion wGBLUP did not increase long-term response, although allowed reducing inbreeding rates and loss of favorable alleles. The results suggest that GS outperforms PBLUP when the selected trait is under less polygenic background and that attributing more weight to low-frequency favorable alleles can reduce inbreeding rates and loss of favorable alleles in GS.

Comparison of methods for the implementation of genome-assisted evaluation of Spanish dairy cattle.

PubMed

Jiménez-Montero, J A; González-Recio, O; Alenda, R

2013-01-01

The aim of this study was to evaluate methods for genomic evaluation of the Spanish Holstein population as an initial step toward the implementation of routine genomic evaluations. This study provides a description of the population structure of progeny tested bulls in Spain at the genomic level and compares different genomic evaluation methods with regard to accuracy and bias. Two bayesian linear regression models, Bayes-A and Bayesian-LASSO (B-LASSO), as well as a machine learning algorithm, Random-Boosting (R-Boost), and BLUP using a realized genomic relationship matrix (G-BLUP), were compared. Five traits that are currently under selection in the Spanish Holstein population were used: milk yield, fat yield, protein yield, fat percentage, and udder depth. In total, genotypes from 1859 progeny tested bulls were used. The training sets were composed of bulls born before 2005; including 1601 bulls for production and 1574 bulls for type, whereas the testing sets contained 258 and 235 bulls born in 2005 or later for production and type, respectively. Deregressed proofs (DRP) from January 2009 Interbull (Uppsala, Sweden) evaluation were used as the dependent variables for bulls in the training sets, whereas DRP from the December 2011 DRPs Interbull evaluation were used to compare genomic predictions with progeny test results for bulls in the testing set. Genomic predictions were more accurate than traditional pedigree indices for predicting future progeny test results of young bulls. The gain in accuracy, due to inclusion of genomic data varied by trait and ranged from 0.04 to 0.42 Pearson correlation units. Results averaged across traits showed that B-LASSO had the highest accuracy with an advantage of 0.01, 0.03 and 0.03 points in Pearson correlation compared with R-Boost, Bayes-A, and G-BLUP, respectively. The B-LASSO predictions also showed the least bias (0.02, 0.03 and 0.10 SD units less than Bayes-A, R-Boost and G-BLUP, respectively) as measured by mean difference between genomic predictions and progeny test results. The R-Boosting algorithm provided genomic predictions with regression coefficients closer to unity, which is an alternative measure of bias, for 4 out of 5 traits and also resulted in mean squared errors estimates that were 2%, 10%, and 12% smaller than B-LASSO, Bayes-A, and G-BLUP, respectively. The observed prediction accuracy obtained with these methods was within the range of values expected for a population of similar size, suggesting that the prediction method and reference population described herein are appropriate for implementation of routine genome-assisted evaluations in Spanish dairy cattle. R-Boost is a competitive marker regression methodology in terms of predictive ability that can accommodate large data sets. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Strategies in identifying individuals in a segregant population of common bean and implications of genotype x environment interaction in the success of selection.

PubMed

Mendes, M P; Ramalho, M A P; Abreu, A F B

2012-04-10

The objective of this study was to compare the BLUP selection method with different selection strategies in F(2:4) and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F(2:4) progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.

Genetic analysis of semen production traits of Japanese Black and Holstein bulls: genome-wide marker-based estimation of genetic parameters and environmental effect trends.

PubMed

Atagi, Y; Onogi, A; Kinukawa, M; Ogino, A; Kurogi, K; Uchiyama, K; Yasumori, T; Adachi, K; Togashi, K; Iwata, H

2017-05-01

The semen production traits of bulls from 2 major cattle breeds in Japan, Holstein and Japanese Black, were analyzed comprehensively using genome-wide markers. Weaker genetic correlations were observed between the 2 age groups (1 to 3 yr old and 4 to 6 yr old) regarding semen volume and sperm motility compared with those observed for sperm number and motility after freeze-thawing. The preselection of collected semen for freezing had a limited effect. Given the increasing importance of bull proofs at a young age because of genomic selection and the results from preliminary studies, we used a multiple-trait model that included motility after freeze-thawing with records collected at young ages. Based on variations in contemporary group effects, accounting for both seasonal and management factors, Holstein bulls may be more sensitive than Japanese Black bulls to seasonal environmental variations; however, the seasonal variations of contemporary group effects were smaller than those of overall contemporary group effects. The improvement of motilities, recorded immediately after collection and freeze-thawing, was observed in recent years; thus, good management and better freeze-thawing protocol may alleviate seasonal phenotypic differences. The detrimental effects of inbreeding were observed in all traits of both breeds; accordingly, the selection of candidate bulls with high inbreeding coefficients should be avoided per general recommendations. Semen production traits have never been considered for bull selection. However, negative genetic trends were observed. The magnitudes of the estimated h were comparable to those of other economically important traits. A single-step genomic BLUP will provide more accurate predictions of breeding values compared with BLUP; thus, marker genotype information is useful for estimating the genetic merits of bulls for semen production traits. The selection of these traits would improve sperm viability, a component related to breeding success, and alleviate negative genetic trends.

Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.

PubMed

Lourenco, D A L; Tsuruta, S; Fragomeni, B O; Masuda, Y; Aguilar, I; Legarra, A; Bertrand, J K; Amen, T S; Wang, L; Moser, D W; Misztal, I

2015-06-01

Predictive ability of genomic EBV when using single-step genomic BLUP (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth weight (BiW) and weaning weight (WW), almost 3.4 million on postweaning gain (PWG), and over 1.3 million on calving ease (CE). Genomic information was available on, at most, 51,883 animals, which included high and low EBV accuracy animals. Traditional EBV was computed by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects was derived from ssGBLUP; SNP effects were calculated based on the following reference populations: ref_2k (contains top bulls and top cows that had an EBV accuracy for BiW ≥0.85), ref_8k (contains all parents that were genotyped), and ref_33k (contains all genotyped animals born up to 2012). Indirect prediction was obtained as direct genomic value (DGV) or as an index of DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the genomic relationship matrix calculated by an algorithm for proven and young animals (APY) that uses recursions on a small subset of reference animals. An extra reference subset included 3,872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess predictive ability on a validation population of 18,721 animals born in 2013. Computations for growth traits used multiple-trait linear model and, for CE, a bivariate CE-BiW threshold-linear model. With BLUP, predictivities were 0.29, 0.34, 0.23, and 0.12 for BiW, WW, PWG, and CE, respectively. With ssGBLUP and ref_2k, predictivities were 0.34, 0.35, 0.27, and 0.13 for BiW, WW, PWG, and CE, respectively, and with ssGBLUP and ref_33k, predictivities were 0.39, 0.38, 0.29, and 0.13 for BiW, WW, PWG, and CE, respectively. Low predictivity for CE was due to low incidence rate of difficult calving. Indirect predictions with ref_33k were as accurate as with full ssGBLUP. Using the APY and recursions on ref_4k gave 88% gains of full ssGBLUP and using the APY and recursions on ref_8k gave 97% gains of full ssGBLUP. Genomic evaluation in beef cattle with ssGBLUP is feasible while keeping the models (maternal, multiple trait, and threshold) already used in regular BLUP. Gains in predictivity are dependent on the composition of the reference population. Indirect predictions via SNP effects derived from ssGBLUP allow for accurate genomic predictions on young animals, with no advantage of including PA in the index if the reference population is large. With the APY conditioning on about 10,000 reference animals, ssGBLUP is potentially applicable to a large number of genotyped animals without compromising predictive ability.

In situ genetic association for serotiny, a fire-related trait, in Mediterranean maritime pine (Pinus pinaster).

PubMed

Budde, Katharina B; Heuertz, Myriam; Hernández-Serrano, Ana; Pausas, Juli G; Vendramin, Giovanni G; Verdú, Miguel; González-Martínez, Santiago C

2014-01-01

Wildfire is a major ecological driver of plant evolution. Understanding the genetic basis of plant adaptation to wildfire is crucial, because impending climate change will involve fire regime changes worldwide. We studied the molecular genetic basis of serotiny, a fire-related trait, in Mediterranean maritime pine using association genetics. A single nucleotide polymorphism (SNP) set was used to identify genotype : phenotype associations in situ in an unstructured natural population of maritime pine (eastern Iberian Peninsula) under a mixed-effects model framework. RR-BLUP was used to build predictive models for serotiny in this region. Model prediction power outside the focal region was tested using independent range-wide serotiny data. Seventeen SNPs were potentially associated with serotiny, explaining approximately 29% of the trait phenotypic variation in the eastern Iberian Peninsula. Similar prediction power was found for nearby geographical regions from the same maternal lineage, but not for other genetic lineages. Association genetics for ecologically relevant traits evaluated in situ is an attractive approach for forest trees provided that traits are under strong genetic control and populations are unstructured, with large phenotypic variability. This will help to extend the research focus to ecological keystone non-model species in their natural environments, where polymorphisms acquired their adaptive value. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Mastitis of periparturient Holstein cattle: a phenotypic and genetic study.

PubMed

Detilleux, J C; Kehrli, M E; Freeman, A E; Fox, L K; Kelley, D H

1995-10-01

Environmental and genetic factors affecting somatic cell scores, clinical mastitis, and IMI by minor and major pathogens were studied on 137 periparturient Holstein cows selected for milk production. Environmental effects were obtained by generalized least squares and logistic regression. Genetic parameters were from BLUP and threshold animal models. Lactation number affected the number of quarters with clinical mastitis and the number of quarters infected with minor pathogens. The DIM affected somatic cell score and number of quarters infected with major pathogens. Heritabilities for all mastitis indicators averaged 10%, but differences occurred among the indicators. Correlations between breeding values of the number of quarters infected with minor pathogens and the number infected with major pathogens were antagonistic and statistically significant.

Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing.

PubMed

Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Chen, Charles; Porth, Ilga; El-Kassaby, Yousry A

2015-05-09

Genomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits of low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost. Genotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites in British Columbia, Canada. Four imputation algorithms were compared (mean value (MI), singular value decomposition (SVD), expectation maximization (EM), and a newly derived, family-based k-nearest neighbor (kNN-Fam)). Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about trait architecture. Finally, using PCA, multi-trait GS prediction models were developed. The EM and kNN-Fam imputation methods were superior for 30 and 60% missing data, respectively. The RR-BLUP GS prediction model produced better accuracies than the GRR indicating that the genetic architecture for these traits is complex. GS prediction accuracies for multi-site were high and better than those of single-sites while multi-site predictability produced the lowest accuracies reflecting type-b genetic correlations and deemed unreliable. The incorporation of genomic information in quantitative genetics analyses produced more realistic heritability estimates as half-sib pedigree tended to inflate the additive genetic variance and subsequently both heritability and gain estimates. Principle component scores as representatives of multi-trait GS prediction models produced surprising results where negatively correlated traits could be concurrently selected for using PCA2 and PCA3. The application of GS to open-pollinated family testing, the simplest form of tree improvement evaluation methods, was proven to be effective. Prediction accuracies obtained for all traits greatly support the integration of GS in tree breeding. While the within-site GS prediction accuracies were high, the results clearly indicate that single-site GS models ability to predict other sites are unreliable supporting the utilization of multi-site approach. Principle component scores provided an opportunity for the concurrent selection of traits with different phenotypic optima.

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

Genotyping by sequencing for genomic prediction in a soybean breeding population.

PubMed

Jarquín, Diego; Kocak, Kyle; Posadas, Luis; Hyma, Katie; Jedlicka, Joseph; Graef, George; Lorenz, Aaron

2014-08-29

Advances in genotyping technology, such as genotyping by sequencing (GBS), are making genomic prediction more attractive to reduce breeding cycle times and costs associated with phenotyping. Genomic prediction and selection has been studied in several crop species, but no reports exist in soybean. The objectives of this study were (i) evaluate prospects for genomic selection using GBS in a typical soybean breeding program and (ii) evaluate the effect of GBS marker selection and imputation on genomic prediction accuracy. To achieve these objectives, a set of soybean lines sampled from the University of Nebraska Soybean Breeding Program were genotyped using GBS and evaluated for yield and other agronomic traits at multiple Nebraska locations. Genotyping by sequencing scored 16,502 single nucleotide polymorphisms (SNPs) with minor-allele frequency (MAF) > 0.05 and percentage of missing values ≤ 5% on 301 elite soybean breeding lines. When SNPs with up to 80% missing values were included, 52,349 SNPs were scored. Prediction accuracy for grain yield, assessed using cross validation, was estimated to be 0.64, indicating good potential for using genomic selection for grain yield in soybean. Filtering SNPs based on missing data percentage had little to no effect on prediction accuracy, especially when random forest imputation was used to impute missing values. The highest accuracies were observed when random forest imputation was used on all SNPs, but differences were not significant. A standard additive G-BLUP model was robust; modeling additive-by-additive epistasis did not provide any improvement in prediction accuracy. The effect of training population size on accuracy began to plateau around 100, but accuracy steadily climbed until the largest possible size was used in this analysis. Including only SNPs with MAF > 0.30 provided higher accuracies when training populations were smaller. Using GBS for genomic prediction in soybean holds good potential to expedite genetic gain. Our results suggest that standard additive G-BLUP models can be used on unfiltered, imputed GBS data without loss in accuracy.

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

PubMed

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs.

PubMed

Vitezica, Zulma G; Varona, Luis; Elsen, Jean-Michel; Misztal, Ignacy; Herring, William; Legarra, Andrès

2016-01-29

Most developments in quantitative genetics theory focus on the study of intra-breed/line concepts. With the availability of massive genomic information, it becomes necessary to revisit the theory for crossbred populations. We propose methods to construct genomic covariances with additive and non-additive (dominance) inheritance in the case of pure lines and crossbred populations. We describe substitution effects and dominant deviations across two pure parental populations and the crossbred population. Gene effects are assumed to be independent of the origin of alleles and allelic frequencies can differ between parental populations. Based on these assumptions, the theoretical variance components (additive and dominant) are obtained as a function of marker effects and allelic frequencies. The additive genetic variance in the crossbred population includes the biological additive and dominant effects of a gene and a covariance term. Dominance variance in the crossbred population is proportional to the product of the heterozygosity coefficients of both parental populations. A genomic BLUP (best linear unbiased prediction) equivalent model is presented. We illustrate this approach by using pig data (two pure lines and their cross, including 8265 phenotyped and genotyped sows). For the total number of piglets born, the dominance variance in the crossbred population represented about 13 % of the total genetic variance. Dominance variation is only marginally important for litter size in the crossbred population. We present a coherent marker-based model that includes purebred and crossbred data and additive and dominant actions. Using this model, it is possible to estimate breeding values, dominant deviations and variance components in a dataset that comprises data on purebred and crossbred individuals. These methods can be exploited to plan assortative mating in pig, maize or other species, in order to generate superior crossbred individuals in terms of performance.

Multiple trait genetic evaluation of clinical mastitis in three dairy cattle breeds.

PubMed

Govignon-Gion, A; Dassonneville, R; Baloche, G; Ducrocq, V

2016-04-01

In 2010, a routine genetic evaluation on occurrence of clinical mastitis in three main dairy cattle breeds-- Montbéliarde (MO), Normande (NO) and Holstein (HO)--was implemented in France. Records were clinical mastitis events reported by farmers to milk recording technicians and the analyzed trait was the binary variable describing the occurrence of a mastitis case within the first 150 days of the first three lactations. Genetic parameters of clinical mastitis were estimated for the three breeds. Low heritability estimates were found: between 2% and 4% depending on the breed. Despite its low heritability, the trait exhibits genetic variation so efficient genetic improvement is possible. Genetic correlations with other traits were estimated, showing large correlations (often>0.50, in absolute value) between clinical mastitis and somatic cell score (SCS), longevity and some udder traits. Correlation with milk yield was moderate and unfavorable (ρ=0.26 to 0.30). High milking speed was genetically associated with less mastitis in MO (ρ=-0.14) but with more mastitis in HO (ρ=0.18). A two-step approach was implemented for routine evaluation: first, a univariate evaluation based on a linear animal model with permanent environment effect led to pre-adjusted records (defined as records corrected for all non-genetic effects) and associated weights. These data were then combined with similar pre-adjusted records for others traits in a multiple trait BLUP animal model. The combined breeding values for clinical mastitis obtained are the official (published) ones. Mastitis estimated breeding values (EBV) were then combined with SCSs EBV into an udder health index, which receives a weight of 14.5% to 18.5% in the French total merit index (ISU) of the three breeds. Interbull genetic correlations for mastitis occurrence were very high (ρ=0.94) with Nordic countries, where much stricter recording systems exist reflecting a satisfactory quality of phenotypes as reported by the farmers. They were lower (around 0.80) with countries supplying SCS as a proxy for the international evaluation on clinical mastitis.

Metabolomic prediction of yield in hybrid rice.

PubMed

Xu, Shizhong; Xu, Yang; Gong, Liang; Zhang, Qifa

2016-10-01

Rice (Oryza sativa) provides a staple food source for more than 50% of the world's population. An increase in yield can significantly contribute to global food security. Hybrid breeding can potentially help to meet this goal because hybrid rice often shows a considerable increase in yield when compared with pure-bred cultivars. We recently developed a marker-guided prediction method for hybrid yield and showed a substantial increase in yield through genomic hybrid breeding. We now have transcriptomic and metabolomic data as potential resources for prediction. Using six prediction methods, including least absolute shrinkage and selection operator (LASSO), best linear unbiased prediction (BLUP), stochastic search variable selection, partial least squares, and support vector machines using the radial basis function and polynomial kernel function, we found that the predictability of hybrid yield can be further increased using these omic data. LASSO and BLUP are the most efficient methods for yield prediction. For high heritability traits, genomic data remain the most efficient predictors. When metabolomic data are used, the predictability of hybrid yield is almost doubled compared with genomic prediction. Of the 21 945 potential hybrids derived from 210 recombinant inbred lines, selection of the top 10 hybrids predicted from metabolites would lead to a ~30% increase in yield. We hypothesize that each metabolite represents a biologically built-in genetic network for yield; thus, using metabolites for prediction is equivalent to using information integrated from these hidden genetic networks for yield prediction. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Estimates of genetic parameters and environmental effects for measures of hunting performance in Finnish hounds.

PubMed

Liinamo, A E; Karjalainen, L; Ojala, M; Vilva, V

1997-03-01

Data from field trials of Finnish Hounds between 1988 and 1992 in Finland were used to estimate genetic parameters and environmental effects for measures of hunting performance using REML procedures and an animal model. The original data set included 28,791 field trial records from 5,666 dogs. Males and females had equal hunting performance, whereas experience acquired by age improved trial results compared with results for young dogs (P < .001). Results were mostly better on snow than on bare ground (P < .001), and testing areas, years, months, and their interactions affected results (P < .001). Estimates of heritabilities and repeatabilities were low for most of the 28 measures, mainly due to large residual variances. The highest heritabilities were for frequency of tonguing (h2 = .15), pursuit score (h2 = .13), tongue score (h2 = .13), ghost trailing score (h2 = .12), and merit and final score (both h2 = .11). Estimates of phenotypic and genetic correlations were positive and moderate or high for search scores, pursuit scores, and final scores but lower for other studied measures. The results suggest that, due to low heritabilities, evaluation of breeding values for Finnish Hounds with respect to their hunting ability should be based on animal model BLUP methods instead of mere performance testing. The evaluation system of field trials should also be revised for more reliability.

Methods to approximate reliabilities in single-step genomic evaluation

USDA-ARS?s Scientific Manuscript database

Reliability of predictions from single-step genomic BLUP (ssGBLUP) can be calculated by inversion, but that is not feasible for large data sets. Two methods of approximating reliability were developed based on decomposition of a function of reliability into contributions from records, pedigrees, and...

Finalizing host range determination of a weed biological control pathogen with BLUPs and damage assessment

USDA-ARS?s Scientific Manuscript database

Colletotrichum gloeosporioides f. sp. salsolae (Penz.) Penz. & Sacc. in Penz. (CGS) is a facultative parasitic fungus being evaluated as a classical biological control agent of Russian thistle or tumbleweed (Salsola tragus L.). In initial host range determination tests, Henderson’s mixed model equat...

Estimation of genomic breeding values for milk yield in UK dairy goats.

PubMed

Mucha, S; Mrode, R; MacLaren-Lee, I; Coffey, M; Conington, J

2015-11-01

The objective of this study was to estimate genomic breeding values for milk yield in crossbred dairy goats. The research was based on data provided by 2 commercial goat farms in the UK comprising 590,409 milk yield records on 14,453 dairy goats kidding between 1987 and 2013. The population was created by crossing 3 breeds: Alpine, Saanen, and Toggenburg. In each generation the best performing animals were selected for breeding, and as a result, a synthetic breed was created. The pedigree file contained 30,139 individuals, of which 2,799 were founders. The data set contained test-day records of milk yield, lactation number, farm, age at kidding, and year and season of kidding. Data on milk composition was unavailable. In total 1,960 animals were genotyped with the Illumina 50K caprine chip. Two methods for estimation of genomic breeding value were compared-BLUP at the single nucleotide polymorphism level (BLUP-SNP) and single-step BLUP. The highest accuracy of 0.61 was obtained with single-step BLUP, and the lowest (0.36) with BLUP-SNP. Linkage disequilibrium (r(2), the squared correlation of the alleles at 2 loci) at 50 kb (distance between 2 SNP) was 0.18. This is the first attempt to implement genomic selection in UK dairy goats. Results indicate that the single-step method provides the highest accuracy for populations with a small number of genotyped individuals, where the number of genotyped males is low and females are predominant in the reference population. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Single-Step BLUP with Varying Genotyping Effort in Open-Pollinated Picea glauca.

PubMed

Ratcliffe, Blaise; El-Dien, Omnia Gamal; Cappa, Eduardo P; Porth, Ilga; Klápště, Jaroslav; Chen, Charles; El-Kassaby, Yousry A

2017-03-10

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce ( Picea glauca ) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm. Copyright © 2017 Ratcliffe et al.

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value.

PubMed

Shin, Donghyun; Lee, Chul; Park, Kyoung-Do; Kim, Heebal; Cho, Kwang-Hyeon

2017-03-01

Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value

PubMed Central

Shin, Donghyun; Lee, Chul; Park, Kyoung-Do; Kim, Heebal; Cho, Kwang-hyeon

2017-01-01

Objective Holsteins are known as the world’s highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins. PMID:26954162

Genomic evaluation of regional dairy cattle breeds in single-breed and multibreed contexts.

PubMed

Jónás, D; Ducrocq, V; Fritz, S; Baur, A; Sanchez, M-P; Croiseau, P

2017-02-01

An important prerequisite for high prediction accuracy in genomic prediction is the availability of a large training population, which allows accurate marker effect estimation. This requirement is not fulfilled in case of regional breeds with a limited number of breeding animals. We assessed the efficiency of the current French routine genomic evaluation procedure in four regional breeds (Abondance, Tarentaise, French Simmental and Vosgienne) as well as the potential benefits when the training populations consisting of males and females of these breeds are merged to form a multibreed training population. Genomic evaluation was 5-11% more accurate than a pedigree-based BLUP in three of the four breeds, while the numerically smallest breed showed a < 1% increase in accuracy. Multibreed genomic evaluation was beneficial for two breeds (Abondance and French Simmental) with maximum gains of 5 and 8% in correlation coefficients between yield deviations and genomic estimated breeding values, when compared to the single-breed genomic evaluation results. Inflation of genomic evaluation of young candidates was also reduced. Our results indicate that genomic selection can be effective in regional breeds as well. Here, we provide empirical evidence proving that genetic distance between breeds is only one of the factors affecting the efficiency of multibreed genomic evaluation. © 2016 Blackwell Verlag GmbH.

Accuracy and training population design for genomic selection in elite north american oats

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) is a method to estimate the breeding values of individuals by using markers throughout the genome. We evaluated the accuracies of GS using data from five traits on 446 oat lines genotyped with 1005 Diversity Array Technology (DArT) markers and two GS methods (RR-BLUP and Bayes...

Path analysis of the genetic integration of traits in the sand cricket: a novel use of BLUPs.

PubMed

Roff, D A; Fairbairn, D J

2011-09-01

This study combines path analysis with quantitative genetics to analyse a key life history trade-off in the cricket, Gryllus firmus. We develop a path model connecting five traits associated with the trade-off between flight capability and reproduction and test this model using phenotypic data and estimates of breeding values (best linear unbiased predictors) from a half-sibling experiment. Strong support by both types of data validates our causal model and indicates concordance between the phenotypic and genetic expression of the trade-off. Comparisons of the trade-off between sexes and wing morphs reveal that these discrete phenotypes are not genetically independent and that the evolutionary trajectories of the two wing morphs are more tightly constrained to covary than those of the two sexes. Our results illustrate the benefits of combining a quantitative genetic analysis, which examines statistical correlations between traits, with a path model that focuses upon the causal components of variation. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis.

PubMed

Piepho, H P

1994-11-01

Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets.

Changes in variance explained by top SNP windows over generations for three traits in broiler chicken.

PubMed

Fragomeni, Breno de Oliveira; Misztal, Ignacy; Lourenco, Daniela Lino; Aguilar, Ignacio; Okimoto, Ronald; Muir, William M

2014-01-01

The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

PubMed

Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP effects (SNP-BLUP model). When reducing marker density from WGS data to 30 K, SNP-BLUP tended to yield the highest accuracies, at least in the short term. Based on SVD of the genotype matrix, we developed a direct method for the calculation of BayesC estimates of marker effects. Although SVD- and MCMC-based marker effects differed slightly, their prediction accuracies were similar. Assuming that the SVD of the marker genotype matrix is already performed for other reasons (e.g. for SNP-BLUP), computation times for the BayesC predictions were comparable to those of SNP-BLUP.

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

Variation in cassava germplasm for tolerance to post-harvest physiological deterioration.

PubMed

Venturini, M T; Santos, L R; Vildoso, C I A; Santos, V S; Oliveira, E J

2016-05-06

Tolerant varieties can effectively control post-harvest physiological deterioration (PPD) of cassava, although knowledge on the genetic variability and inheritance of this trait is needed. The objective of this study was to estimate genetic parameters and identify sources of tolerance to PPD and their stability in cassava accessions. Roots from 418 cassava accessions, grown in four independent experiments, were evaluated for PPD tolerance 0, 2, 5, and 10 days post-harvest. Data were transformed into area under the PPD-progress curve (AUP-PPD) to quantify tolerance. Genetic parameters, stability (Si), adaptability (Ai), and the joint analysis of stability and adaptability (Zi) were obtained via residual maximum likelihood (REML) and best linear unbiased prediction (BLUP) methods. Variance in the genotype (G) x environment (E) interaction and genotypic variance were important for PPD tolerance. Individual broad-sense heritability (hg(2)= 0.38 ± 0.04) and average heritability in accessions (hmg(2)= 0.52) showed high genetic control of PPD tolerance. Genotypic correlation of AUP-PPD in different experiments was of medium magnitude (ȓgA = 0.42), indicating significant G x E interaction. The predicted genotypic values o f G x E free of interaction (û + ĝi) showed high variation. Of the 30 accessions with high Zi, 19 were common to û + ĝi, Si, and Ai parameters. The genetic gain with selection of these 19 cassava accessions was -55.94, -466.86, -397.72, and -444.03% for û + ĝi, Si, Ai, and Zi, respectively, compared with the overall mean for each parameter. These results demonstrate the variability and potential of cassava germplasm to introduce PPD tolerance in commercial varieties.

Genomic selection for fruit quality traits in apple (Malus×domestica Borkh.).

PubMed

Kumar, Satish; Chagné, David; Bink, Marco C A M; Volz, Richard K; Whitworth, Claire; Carlisle, Charmaine

2012-01-01

The genome sequence of apple (Malus×domestica Borkh.) was published more than a year ago, which helped develop an 8K SNP chip to assist in implementing genomic selection (GS). In apple breeding programmes, GS can be used to obtain genomic breeding values (GEBV) for choosing next-generation parents or selections for further testing as potential commercial cultivars at a very early stage. Thus GS has the potential to accelerate breeding efficiency significantly because of decreased generation interval or increased selection intensity. We evaluated the accuracy of GS in a population of 1120 seedlings generated from a factorial mating design of four females and two male parents. All seedlings were genotyped using an Illumina Infinium chip comprising 8,000 single nucleotide polymorphisms (SNPs), and were phenotyped for various fruit quality traits. Random-regression best liner unbiased prediction (RR-BLUP) and the Bayesian LASSO method were used to obtain GEBV, and compared using a cross-validation approach for their accuracy to predict unobserved BLUP-BV. Accuracies were very similar for both methods, varying from 0.70 to 0.90 for various fruit quality traits. The selection response per unit time using GS compared with the traditional BLUP-based selection were very high (>100%) especially for low-heritability traits. Genome-wide average estimated linkage disequilibrium (LD) between adjacent SNPs was 0.32, with a relatively slow decay of LD in the long range (r(2) = 0.33 and 0.19 at 100 kb and 1,000 kb respectively), contributing to the higher accuracy of GS. Distribution of estimated SNP effects revealed involvement of large effect genes with likely pleiotropic effects. These results demonstrated that genomic selection is a credible alternative to conventional selection for fruit quality traits.

Persistency of accuracy of genomic breeding values for different simulated pig breeding programs in developing countries.

PubMed

Akanno, E C; Schenkel, F S; Sargolzaei, M; Friendship, R M; Robinson, J A B

2014-10-01

Genetic improvement of pigs in tropical developing countries has focused on imported exotic populations which have been subjected to intensive selection with attendant high population-wide linkage disequilibrium (LD). Presently, indigenous pig population with limited selection and low LD are being considered for improvement. Given that the infrastructure for genetic improvement using the conventional BLUP selection methods are lacking, a genome-wide selection (GS) program was proposed for developing countries. A simulation study was conducted to evaluate the option of using 60 K SNP panel and observed amount of LD in the exotic and indigenous pig populations. Several scenarios were evaluated including different size and structure of training and validation populations, different selection methods and long-term accuracy of GS in different population/breeding structures and traits. The training set included previously selected exotic population, unselected indigenous population and their crossbreds. Traits studied included number born alive (NBA), average daily gain (ADG) and back fat thickness (BFT). The ridge regression method was used to train the prediction model. The results showed that accuracies of genomic breeding values (GBVs) in the range of 0.30 (NBA) to 0.86 (BFT) in the validation population are expected if high density marker panels are utilized. The GS method improved accuracy of breeding values better than pedigree-based approach for traits with low heritability and in young animals with no performance data. Crossbred training population performed better than purebreds when validation was in populations with similar or a different structure as in the training set. Genome-wide selection holds promise for genetic improvement of pigs in the tropics. © 2014 Blackwell Verlag GmbH.

Extension of the Haseman-Elston regression model to longitudinal data.

PubMed

Won, Sungho; Elston, Robert C; Park, Taesung

2006-01-01

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.

Whole-genome sequence-based genomic prediction in laying chickens with different genomic relationship matrices to account for genetic architecture.

PubMed

Ni, Guiyan; Cavero, David; Fangmann, Anna; Erbe, Malena; Simianer, Henner

2017-01-16

With the availability of next-generation sequencing technologies, genomic prediction based on whole-genome sequencing (WGS) data is now feasible in animal breeding schemes and was expected to lead to higher predictive ability, since such data may contain all genomic variants including causal mutations. Our objective was to compare prediction ability with high-density (HD) array data and WGS data in a commercial brown layer line with genomic best linear unbiased prediction (GBLUP) models using various approaches to weight single nucleotide polymorphisms (SNPs). A total of 892 chickens from a commercial brown layer line were genotyped with 336 K segregating SNPs (array data) that included 157 K genic SNPs (i.e. SNPs in or around a gene). For these individuals, genome-wide sequence information was imputed based on data from re-sequencing runs of 25 individuals, leading to 5.2 million (M) imputed SNPs (WGS data), including 2.6 M genic SNPs. De-regressed proofs (DRP) for eggshell strength, feed intake and laying rate were used as quasi-phenotypic data in genomic prediction analyses. Four weighting factors for building a trait-specific genomic relationship matrix were investigated: identical weights, -(log 10 P) from genome-wide association study results, squares of SNP effects from random regression BLUP, and variable selection based weights (known as BLUP|GA). Predictive ability was measured as the correlation between DRP and direct genomic breeding values in five replications of a fivefold cross-validation. Averaged over the three traits, the highest predictive ability (0.366 ± 0.075) was obtained when only genic SNPs from WGS data were used. Predictive abilities with genic SNPs and all SNPs from HD array data were 0.361 ± 0.072 and 0.353 ± 0.074, respectively. Prediction with -(log 10 P) or squares of SNP effects as weighting factors for building a genomic relationship matrix or BLUP|GA did not increase accuracy, compared to that with identical weights, regardless of the SNP set used. Our results show that little or no benefit was gained when using all imputed WGS data to perform genomic prediction compared to using HD array data regardless of the weighting factors tested. However, using only genic SNPs from WGS data had a positive effect on prediction ability.

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat.

PubMed

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-06-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection.

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat

PubMed Central

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-01-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection. PMID:24518889

A comparison of five methods to predict genomic breeding values of dairy bulls from genome-wide SNP markers

PubMed Central

2009-01-01

Background Genomic selection (GS) uses molecular breeding values (MBV) derived from dense markers across the entire genome for selection of young animals. The accuracy of MBV prediction is important for a successful application of GS. Recently, several methods have been proposed to estimate MBV. Initial simulation studies have shown that these methods can accurately predict MBV. In this study we compared the accuracies and possible bias of five different regression methods in an empirical application in dairy cattle. Methods Genotypes of 7,372 SNP and highly accurate EBV of 1,945 dairy bulls were used to predict MBV for protein percentage (PPT) and a profit index (Australian Selection Index, ASI). Marker effects were estimated by least squares regression (FR-LS), Bayesian regression (Bayes-R), random regression best linear unbiased prediction (RR-BLUP), partial least squares regression (PLSR) and nonparametric support vector regression (SVR) in a training set of 1,239 bulls. Accuracy and bias of MBV prediction were calculated from cross-validation of the training set and tested against a test team of 706 young bulls. Results For both traits, FR-LS using a subset of SNP was significantly less accurate than all other methods which used all SNP. Accuracies obtained by Bayes-R, RR-BLUP, PLSR and SVR were very similar for ASI (0.39-0.45) and for PPT (0.55-0.61). Overall, SVR gave the highest accuracy. All methods resulted in biased MBV predictions for ASI, for PPT only RR-BLUP and SVR predictions were unbiased. A significant decrease in accuracy of prediction of ASI was seen in young test cohorts of bulls compared to the accuracy derived from cross-validation of the training set. This reduction was not apparent for PPT. Combining MBV predictions with pedigree based predictions gave 1.05 - 1.34 times higher accuracies compared to predictions based on pedigree alone. Some methods have largely different computational requirements, with PLSR and RR-BLUP requiring the least computing time. Conclusions The four methods which use information from all SNP namely RR-BLUP, Bayes-R, PLSR and SVR generate similar accuracies of MBV prediction for genomic selection, and their use in the selection of immediate future generations in dairy cattle will be comparable. The use of FR-LS in genomic selection is not recommended. PMID:20043835

Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2014-01-01

Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289

A two step Bayesian approach for genomic prediction of breeding values.

PubMed

Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

2012-05-21

In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

PubMed

Schiavo, G; Galimberti, G; Calò, D G; Samorè, A B; Bertolini, F; Russo, V; Gallo, M; Buttazzoni, L; Fontanesi, L

2016-04-01

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni  < 0.10. However, there was an increasing number of SNPs with a decreasing level of allele frequency changes over time, representing a continuous profile across the genome. The largest proportion of the 493 SNPs was on porcine chromosome (SSC) 7, SSC2, SSC8 and SSC18 for a total of 204 haploblocks. Functional annotations of genomic regions, including the 493 shifted SNPs, reported a few Gene Ontology terms that might underly the biological processes that contributed to increase performances of the pigs over the 20 years of the selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population. © 2015 Stichting International Foundation for Animal Genetics.

Genome-Wide Association Study for Carcass Traits in an Experimental Nelore Cattle Population

PubMed Central

Medeiros de Oliveira Silva, Rafael; Bonvino Stafuzza, Nedenia; de Oliveira Fragomeni, Breno; Miguel Ferreira de Camargo, Gregório; Matos Ceacero, Thaís; Noely dos Santos Gonçalves Cyrillo, Joslaine; Baldi, Fernando; Augusti Boligon, Arione; Zerlotti Mercadante, Maria Eugênia; Lino Lourenco, Daniela; Misztal, Ignacy; Galvão de Albuquerque, Lucia

2017-01-01

The purpose of this study was to identify genomic regions associated with carcass traits in an experimental Nelore cattle population. The studied data set contained 2,306 ultrasound records for longissimus muscle area (LMA), 1,832 for backfat thickness (BF), and 1,830 for rump fat thickness (RF). A high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA) was used for genotyping. After genomic data quality control, 437,197 SNPs from 761 animals were available, of which 721 had phenotypes for LMA, 669 for BF, and 718 for RF. The SNP solutions were estimated using a single-step genomic BLUP approach (ssGWAS), which calculated the variance for windows of 50 consecutive SNPs and the regions that accounted for more than 0.5% of the additive genetic variance were used to search for candidate genes. The results indicated that 12, 18, and 15 different windows were associated to LMA, BF, and RF, respectively. Confirming the polygenic nature of the studied traits, 43, 65, and 53 genes were found in those associated windows, respectively for LMA, BF, and RF. Among the candidate genes, some of them, which already had their functions associated with the expression of energy metabolism, were found associated with fat deposition in this study. In addition, ALKBH3 and HSD17B12 genes, which are related in fibroblast death and metabolism of steroids, were found associated with LMA. The results presented here should help to better understand the genetic and physiologic mechanism regulating the muscle tissue deposition and subcutaneous fat cover expression of Zebu animals. The identification of candidate genes should contribute for Zebu breeding programs in order to consider carcass traits as selection criteria in their genetic evaluation. PMID:28118362

Genomic prediction in a nuclear population of layers using single-step models.

PubMed

Yan, Yiyuan; Wu, Guiqin; Liu, Aiqiao; Sun, Congjiao; Han, Wenpeng; Li, Guangqi; Yang, Ning

2018-02-01

Single-step genomic prediction method has been proposed to improve the accuracy of genomic prediction by incorporating information of both genotyped and ungenotyped animals. The objective of this study is to compare the prediction performance of single-step model with a 2-step models and the pedigree-based models in a nuclear population of layers. A total of 1,344 chickens across 4 generations were genotyped by a 600 K SNP chip. Four traits were analyzed, i.e., body weight at 28 wk (BW28), egg weight at 28 wk (EW28), laying rate at 38 wk (LR38), and Haugh unit at 36 wk (HU36). In predicting offsprings, individuals from generation 1 to 3 were used as training data and females from generation 4 were used as validation set. The accuracies of predicted breeding values by pedigree BLUP (PBLUP), genomic BLUP (GBLUP), SSGBLUP and single-step blending (SSBlending) were compared for both genotyped and ungenotyped individuals. For genotyped females, GBLUP performed no better than PBLUP because of the small size of training data, while the 2 single-step models predicted more accurately than the PBLUP model. The average predictive ability of SSGBLUP and SSBlending were 16.0% and 10.8% higher than the PBLUP model across traits, respectively. Furthermore, the predictive abilities for ungenotyped individuals were also enhanced. The average improvements of prediction abilities were 5.9% and 1.5% for SSGBLUP and SSBlending model, respectively. It was concluded that single-step models, especially the SSGBLUP model, can yield more accurate prediction of genetic merits and are preferable for practical implementation of genomic selection in layers. © 2017 Poultry Science Association Inc.

Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes.

PubMed

Silva, V B; Daher, R F; Araújo, M S B; Souza, Y P; Cassaro, S; Menezes, B R S; Gravina, L M; Novo, A A C; Tardin, F D; Júnior, A T Amaral

2017-09-27

Genetically improved cultivars of elephant grass need to be adapted to different ecosystems with a faster growth speed and lower seasonality of biomass production over the year. This study aimed to use selection indices using mixed models (REML/BLUP) for selecting families and progenies within full-sib families of elephant grass (Pennisetum purpureum) for biomass production. One hundred and twenty full-sib progenies were assessed from 2014 to 2015 in a randomized block design with three replications. During this period, the traits dry matter production, the number of tillers, plant height, stem diameter, and neutral detergent fiber were assessed. Families 3 and 1 were the best classified, being the most indicated for selection effect. Progenies 40, 45, 46, and 49 got the first positions in the three indices assessed in the first cut. The gain for individual 40 was 161.76% using Mulamba and Mock index. The use of selection indices using mixed models is advantageous in elephant grass since they provide high gains with the selection, which are distributed among all the assessed traits in the most appropriate situation to breeding programs.

Genetic Basis for Variation in Wheat Grain Yield in Response to Varying Nitrogen Application.

PubMed

Mahjourimajd, Saba; Taylor, Julian; Sznajder, Beata; Timmins, Andy; Shahinnia, Fahimeh; Rengel, Zed; Khabaz-Saberi, Hossein; Kuchel, Haydn; Okamoto, Mamoru; Langridge, Peter

2016-01-01

Nitrogen (N) is a major nutrient needed to attain optimal grain yield (GY) in all environments. Nitrogen fertilisers represent a significant production cost, in both monetary and environmental terms. Developing genotypes capable of taking up N early during development while limiting biomass production after establishment and showing high N-use efficiency (NUE) would be economically beneficial. Genetic variation in NUE has been shown previously. Here we describe the genetic characterisation of NUE and identify genetic loci underlying N response under different N fertiliser regimes in a bread wheat population of doubled-haploid lines derived from a cross between two Australian genotypes (RAC875 × Kukri) bred for a similar production environment. NUE field trials were carried out at four sites in South Australia and two in Western Australia across three seasons. There was genotype-by-environment-by-treatment interaction across the sites and also good transgressive segregation for yield under different N supply in the population. We detected some significant Quantitative Trait Loci (QTL) associated with NUE and N response at different rates of N application across the sites and years. It was also possible to identify lines showing positive N response based on the rankings of their Best Linear Unbiased Predictions (BLUPs) within a trial. Dissecting the complexity of the N effect on yield through QTL analysis is a key step towards elucidating the molecular and physiological basis of NUE in wheat.

An attempt at predicting blood β-hydroxybutyrate from Fourier-transform mid-infrared spectra of milk using multivariate mixed models in Polish dairy cattle.

PubMed

Belay, T K; Dagnachew, B S; Kowalski, Z M; Ådnøy, T

2017-08-01

Fourier transform mid-infrared (FT-MIR) spectra of milk are commonly used for phenotyping of traits of interest through links developed between the traits and milk FT-MIR spectra. Predicted traits are then used in genetic analysis for ultimate phenotypic prediction using a single-trait mixed model that account for cows' circumstances at a given test day. Here, this approach is referred to as indirect prediction (IP). Alternatively, FT-MIR spectral variable can be kept multivariate in the form of factor scores in REML and BLUP analyses. These BLUP predictions, including phenotype (predicted factor scores), were converted to single-trait through calibration outputs; this method is referred to as direct prediction (DP). The main aim of this study was to verify whether mixed modeling of milk spectra in the form of factors scores (DP) gives better prediction of blood β-hydroxybutyrate (BHB) than the univariate approach (IP). Models to predict blood BHB from milk spectra were also developed. Two data sets that contained milk FT-MIR spectra and other information on Polish dairy cattle were used in this study. Data set 1 (n = 826) also contained BHB measured in blood samples, whereas data set 2 (n = 158,028) did not contain measured blood values. Part of data set 1 was used to calibrate a prediction model (n = 496) and the remaining part of data set 1 (n = 330) was used to validate the calibration models, as well as to evaluate the DP and IP approaches. Dimensions of FT-MIR spectra in data set 2 were reduced either into 5 or 10 factor scores (DP) or into a single trait (IP) with calibration outputs. The REML estimates for these factor scores were found using WOMBAT. The BLUP values and predicted BHB for observations in the validation set were computed using the REML estimates. Blood BHB predicted from milk FT-MIR spectra by both approaches were regressed on reference blood BHB that had not been used in the model development. Coefficients of determination in cross-validation for untransformed blood BHB were from 0.21 to 0.32, whereas that for the log-transformed BHB were from 0.31 to 0.38. The corresponding estimates in validation were from 0.29 to 0.37 and 0.21 to 0.43, respectively, for untransformed and logarithmic BHB. Contrary to expectation, slightly better predictions of BHB were found when univariate variance structure was used (IP) than when multivariate covariance structures were used (DP). Conclusive remarks on the importance of keeping spectral data in multivariate form for prediction of phenotypes may be found in data sets where the trait of interest has strong relationships with spectral variables. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Accounting for unknown foster dams in the genetic evaluation of embryo transfer progeny.

PubMed

Suárez, M J; Munilla, S; Cantet, R J C

2015-02-01

Animals born by embryo transfer (ET) are usually not included in the genetic evaluation of beef cattle for preweaning growth if the recipient dam is unknown. This is primarily to avoid potential bias in the estimation of the unknown age of dam. We present a method that allows including records of calves with unknown age of dam. Assumptions are as follows: (i) foster cows belong to the same breed being evaluated, (ii) there is no correlation between the breeding value (BV) of the calf and the maternal BV of the recipient cow, and (iii) cows of all ages are used as recipients. We examine the issue of bias for the fixed level of unknown age of dam (AOD) and propose an estimator of the effect based on classical measurement error theory (MEM) and a Bayesian approach. Using stochastic simulation under random mating or selection, the MEM estimating equations were compared with BLUP in two situations as follows: (i) full information (FI); (ii) missing AOD information on some dams. Predictions of breeding value (PBV) from the FI situation had the smallest empirical average bias followed by PBV obtained without taking measurement error into account. In turn, MEM displayed the highest bias, although the differences were small. On the other hand, MEM showed the smallest MSEP, for either random mating or selection, followed by FI, whereas ignoring measurement error produced the largest MSEP. As a consequence from the smallest MSEP with a relatively small bias, empirical accuracies of PBV were larger for MEM than those for full information, which in turn showed larger accuracies than the situation ignoring measurement error. It is concluded that MEM equations are a useful alternative for analysing weaning weight data when recipient cows are unknown, as it mitigates the effects of bias in AOD by decreasing MSEP. © 2014 Blackwell Verlag GmbH.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

PubMed Central

Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

2012-01-01

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.

PubMed

Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza

2017-09-27

Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.

The efficiency of genome-wide selection for genetic improvement of net merit.

PubMed

Togashi, K; Lin, C Y; Yamazaki, T

2011-10-01

Four methods of selection for net merit comprising 2 correlated traits were compared in this study: 1) EBV-only index (I₁), which consists of the EBV of both traits (i.e., traditional 2-trait BLUP selection); 2) GEBV-only index (I₂), which comprises the genomic EBV (GEBV) of both traits; 3) GEBV-assisted index (I₃), which combines both the EBV and the GEBV of both traits; and 4) GBV-assisted index (I₄), which combines both the EBV and the true genomic breeding value (GBV) of both traits. Comparisons of these indices were based on 3 evaluation criteria [selection accuracy, genetic response (ΔH), and relative efficiency] under 64 scenarios that arise from combining 2 levels of genetic correlation (r(G)), 2 ratios of genetic variances between traits, 2 ratios of the genomic variance to total genetic variances for trait 1, 4 accuracies of EBV, and 2 proportions of r(G) explained by the GBV. Both selection accuracy and genetic responses of the indices I₁, I₃, and I₄ increased as the accuracy of EBV increased, but the efficiency of the indices I₃ and I₄ relative to I₁ decreased as the accuracy of EBV increased. The relative efficiency of both I₃ and I₄ was generally greater when the accuracy of EBV was 0.6 than when it was 0.9, suggesting that the genomic markers are most useful to assist selection when the accuracy of EBV is low. The GBV-assisted index I₄ was superior to the GEBV-assisted I₃ in all 64 cases examined, indicating the importance of improving the accuracy of prediction of genomic breeding values. Other parameters being identical, increasing the genetic variance of a high heritability trait would increase the genetic response of the genomic indices (I₂, I₃, and I₄). The genetic responses to I₂, I₃, and I(4) was greater when the genetic correlation between traits was positive (r(G) = 0.5) than when it was negative (r(G) = -0.5). The results of this study indicate that the effectiveness of the GEBV-assisted index I₃ is affected by heritability of and genetic correlation between traits, the ratio of genetic variances between traits, the genomic-genetic variance ratio of each index trait, the proportion of genetic correlation accounted for by the genomic markers, and the accuracy of predictions of both EBV and GBV. However, most of these affecting factors are genetic characteristics of a population that is beyond the control of the breeders. The key factor subject to manipulation is to maximize both the proportion of the genetic variance explained by GEBV and the accuracy of both GEBV and EBV. The developed procedures provide means to investigate the efficiency of various genomic indices for any given combination of the genetic factors studied.

Efficiency of multi-breed genomic selection for dairy cattle breeds with different sizes of reference population.

PubMed

Hozé, C; Fritz, S; Phocas, F; Boichard, D; Ducrocq, V; Croiseau, P

2014-01-01

Single-breed genomic selection (GS) based on medium single nucleotide polymorphism (SNP) density (~50,000; 50K) is now routinely implemented in several large cattle breeds. However, building large enough reference populations remains a challenge for many medium or small breeds. The high-density BovineHD BeadChip (HD chip; Illumina Inc., San Diego, CA) containing 777,609 SNP developed in 2010 is characterized by short-distance linkage disequilibrium expected to be maintained across breeds. Therefore, combining reference populations can be envisioned. A population of 1,869 influential ancestors from 3 dairy breeds (Holstein, Montbéliarde, and Normande) was genotyped with the HD chip. Using this sample, 50K genotypes were imputed within breed to high-density genotypes, leading to a large HD reference population. This population was used to develop a multi-breed genomic evaluation. The goal of this paper was to investigate the gain of multi-breed genomic evaluation for a small breed. The advantage of using a large breed (Normande in the present study) to mimic a small breed is the large potential validation population to compare alternative genomic selection approaches more reliably. In the Normande breed, 3 training sets were defined with 1,597, 404, and 198 bulls, and a unique validation set included the 394 youngest bulls. For each training set, estimated breeding values (EBV) were computed using pedigree-based BLUP, single-breed BayesC, or multi-breed BayesC for which the reference population was formed by any of the Normande training data sets and 4,989 Holstein and 1,788 Montbéliarde bulls. Phenotypes were standardized by within-breed genetic standard deviation, the proportion of polygenic variance was set to 30%, and the estimated number of SNP with a nonzero effect was about 7,000. The 2 genomic selection (GS) approaches were performed using either the 50K or HD genotypes. The correlations between EBV and observed daughter yield deviations (DYD) were computed for 6 traits and using the different prediction approaches. Compared with pedigree-based BLUP, the average gain in accuracy with GS in small populations was 0.057 for the single-breed and 0.086 for multi-breed approach. This gain was up to 0.193 and 0.209, respectively, with the large reference population. Improvement of EBV prediction due to the multi-breed evaluation was higher for animals not closely related to the reference population. In the case of a breed with a small reference population size, the increase in correlation due to multi-breed GS was 0.141 for bulls without their sire in reference population compared with 0.016 for bulls with their sire in reference population. These results demonstrate that multi-breed GS can contribute to increase genomic evaluation accuracy in small breeds. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic Basis for Variation in Wheat Grain Yield in Response to Varying Nitrogen Application

PubMed Central

Mahjourimajd, Saba; Taylor, Julian; Sznajder, Beata; Timmins, Andy; Shahinnia, Fahimeh; Rengel, Zed; Khabaz-Saberi, Hossein; Kuchel, Haydn; Okamoto, Mamoru

2016-01-01

Nitrogen (N) is a major nutrient needed to attain optimal grain yield (GY) in all environments. Nitrogen fertilisers represent a significant production cost, in both monetary and environmental terms. Developing genotypes capable of taking up N early during development while limiting biomass production after establishment and showing high N-use efficiency (NUE) would be economically beneficial. Genetic variation in NUE has been shown previously. Here we describe the genetic characterisation of NUE and identify genetic loci underlying N response under different N fertiliser regimes in a bread wheat population of doubled-haploid lines derived from a cross between two Australian genotypes (RAC875 × Kukri) bred for a similar production environment. NUE field trials were carried out at four sites in South Australia and two in Western Australia across three seasons. There was genotype-by-environment-by-treatment interaction across the sites and also good transgressive segregation for yield under different N supply in the population. We detected some significant Quantitative Trait Loci (QTL) associated with NUE and N response at different rates of N application across the sites and years. It was also possible to identify lines showing positive N response based on the rankings of their Best Linear Unbiased Predictions (BLUPs) within a trial. Dissecting the complexity of the N effect on yield through QTL analysis is a key step towards elucidating the molecular and physiological basis of NUE in wheat. PMID:27459317

Genomic selection using beef commercial carcass phenotypes.

PubMed

Todd, D L; Roughsedge, T; Woolliams, J A

2014-03-01

In this study, an industry terminal breeding goal was used in a deterministic simulation, using selection index methodology, to predict genetic gain in a beef population modelled on the UK pedigree Limousin, when using genomic selection (GS) and incorporating phenotype information from novel commercial carcass traits. The effect of genotype-environment interaction was investigated by including the model variations of the genetic correlation between purebred and commercial cross-bred performance (ρX). Three genomic scenarios were considered: (1) genomic breeding values (GBV)+estimated breeding values (EBV) for existing selection traits; (2) GBV for three novel commercial carcass traits+EBV in existing traits; and (3) GBV for novel and existing traits plus EBV for existing traits. Each of the three scenarios was simulated for a range of training population (TP) sizes and with three values of ρX. Scenarios 2 and 3 predicted substantially higher percentage increases over current selection than Scenario 1. A TP of 2000 sires, each with 20 commercial progeny with carcass phenotypes, and assuming a ρX of 0.7, is predicted to increase gain by 40% over current selection in Scenario 3. The percentage increase in gain over current selection increased with decreasing ρX; however, the effect of varying ρX was reduced at high TP sizes for Scenarios 2 and 3. A further non-genomic scenario (4) was considered simulating a conventional population-wide progeny test using EBV only. With 20 commercial cross-bred progenies per sire, similar gain was predicted to Scenario 3 with TP=5000 and ρX=1.0. The range of increases in genetic gain predicted for terminal traits when using GS are of similar magnitude to those observed after the implementation of BLUP technology in the United Kingdom. It is concluded that implementation of GS in a terminal sire breeding goal, using purebred phenotypes alone, will be sub-optimal compared with the inclusion of novel commercial carcass phenotypes in genomic evaluations.

Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. II. Genetic trends

PubMed Central

Zhang, Siqing; Bidanel, Jean-Pierre; Burlot, Thierry; Legault, Christian; Naveau, Jean

2000-01-01

The Tiameslan line was created between 1983 and 1985 by mating Meishan × Jiaxing crossbred Chinese boars with sows from the Laconie composite male line. The Tiameslan line has been selected since then on an index combining average backfat thickness (ABT) and days from 20 to 100 kg (DT). Direct and correlated responses to 11 years of selection were estimated using BLUP methodology applied to a multiple trait animal model. A total of 11 traits were considered, i.e.: ABT, DT, body weight at 4 (W4w), 8 (W8w) and 22 (W22w) weeks of age, teat number (TEAT), number of good teats (GTEAT), total number of piglets born (TNB), born alive (NBA) and weaned (NW) per litter, and birth to weaning survival rate (SURV). Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. The models included both direct and maternal effects for ABT, W4w and W8w. Male and female performances were considered as different traits for W22w, DT and ABT. Genetic parameters estimated in another paper (Zhang et al., Genet. Sel. Evol. 32 (2000) 41-56) were used to perform the analyses. Favourable phenotypic (ΔP) and direct genetic trends (ΔGd) were obtained for post-weaning growth traits and ABT. Trends for maternal effects were limited. Phenotypic and genetic trends were larger in females than in males for ABT (e.g. ΔGd = -0.48 vs. -0.38 mm/year), were larger in males for W22w (ΔGd = 0.90 vs. 0.58 kg/year) and were similar in both sexes for DT (ΔGd = -0.54 vs. -0.55 day/year). Phenotypic and genetic trends were slightly favourable for W4w, W8w, TEAT and GTEAT and close to zero for reproductive traits. PMID:14736407

Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Wang, Quanchao; Yu, Yang; Li, Fuhua; Zhang, Xiaojun; Xiang, Jianhai

2017-09-01

Genomic selection (GS) can be used to accelerate genetic improvement by shortening the selection interval. The successful application of GS depends largely on the accuracy of the prediction of genomic estimated breeding value (GEBV). This study is a first attempt to understand the practicality of GS in Litopenaeus vannamei and aims to evaluate models for GS on growth traits. The performance of GS models in L. vannamei was evaluated in a population consisting of 205 individuals, which were genotyped for 6 359 single nucleotide polymorphism (SNP) markers by specific length amplified fragment sequencing (SLAF-seq) and phenotyped for body length and body weight. Three GS models (RR-BLUP, BayesA, and Bayesian LASSO) were used to obtain the GEBV, and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes. The mean reliability of the GEBVs for body length and body weight predicted by the different models was 0.296 and 0.411, respectively. For each trait, the performances of the three models were very similar to each other with respect to predictability. The regression coefficients estimated by the three models were close to one, suggesting near to zero bias for the predictions. Therefore, when GS was applied in a L. vannamei population for the studied scenarios, all three models appeared practicable. Further analyses suggested that improved estimation of the genomic prediction could be realized by increasing the size of the training population as well as the density of SNPs.

Genetic Dissection of End-Use Quality Traits in Adapted Soft White Winter Wheat

PubMed Central

Jernigan, Kendra L.; Godoy, Jayfred V.; Huang, Meng; Zhou, Yao; Morris, Craig F.; Garland-Campbell, Kimberly A.; Zhang, Zhiwu; Carter, Arron H.

2018-01-01

Soft white wheat is used in domestic and foreign markets for various end products requiring specific quality profiles. Phenotyping for end-use quality traits can be costly, time-consuming and destructive in nature, so it is advantageous to use molecular markers to select experimental lines with superior traits. An association mapping panel of 469 soft white winter wheat cultivars and advanced generation breeding lines was developed from regional breeding programs in the U.S. Pacific Northwest. This panel was genotyped on a wheat-specific 90 K iSelect single nucleotide polymorphism (SNP) chip. A total of 15,229 high quality SNPs were selected and combined with best linear unbiased predictions (BLUPs) from historical phenotypic data of the genotypes in the panel. Genome-wide association mapping was conducted using the Fixed and random model Circulating Probability Unification (FarmCPU). A total of 105 significant marker-trait associations were detected across 19 chromosomes. Potentially new loci for total flour yield, lactic acid solvent retention capacity, flour sodium dodecyl sulfate sedimentation and flour swelling volume were also detected. Better understanding of the genetic factors impacting end-use quality enable breeders to more effectively discard poor quality germplasm and increase frequencies of favorable end-use quality alleles in their breeding populations. PMID:29593752

Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

Transformations to multiple trait mixed model equations (MME) which are intended to improve computational efficiency in best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are described. It is shown that traits that are expected or estimated to have zero residual variance...

Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals.

PubMed

Masuda, Y; Misztal, I; Tsuruta, S; Legarra, A; Aguilar, I; Lourenco, D A L; Fragomeni, B O; Lawlor, T J

2016-03-01

The objectives of this study were to develop and evaluate an efficient implementation in the computation of the inverse of genomic relationship matrix with the recursion algorithm, called the algorithm for proven and young (APY), in single-step genomic BLUP. We validated genomic predictions for young bulls with more than 500,000 genotyped animals in final score for US Holsteins. Phenotypic data included 11,626,576 final scores on 7,093,380 US Holstein cows, and genotypes were available for 569,404 animals. Daughter deviations for young bulls with no classified daughters in 2009, but at least 30 classified daughters in 2014 were computed using all the phenotypic data. Genomic predictions for the same bulls were calculated with single-step genomic BLUP using phenotypes up to 2009. We calculated the inverse of the genomic relationship matrix GAPY(-1) based on a direct inversion of genomic relationship matrix on a small subset of genotyped animals (core animals) and extended that information to noncore animals by recursion. We tested several sets of core animals including 9,406 bulls with at least 1 classified daughter, 9,406 bulls and 1,052 classified dams of bulls, 9,406 bulls and 7,422 classified cows, and random samples of 5,000 to 30,000 animals. Validation reliability was assessed by the coefficient of determination from regression of daughter deviation on genomic predictions for the predicted young bulls. The reliabilities were 0.39 with 5,000 randomly chosen core animals, 0.45 with the 9,406 bulls, and 7,422 cows as core animals, and 0.44 with the remaining sets. With phenotypes truncated in 2009 and the preconditioned conjugate gradient to solve mixed model equations, the number of rounds to convergence for core animals defined by bulls was 1,343; defined by bulls and cows, 2,066; and defined by 10,000 random animals, at most 1,629. With complete phenotype data, the number of rounds decreased to 858, 1,299, and at most 1,092, respectively. Setting up GAPY(-1) for 569,404 genotyped animals with 10,000 core animals took 1.3h and 57 GB of memory. The validation reliability with APY reaches a plateau when the number of core animals is at least 10,000. Predictions with APY have little differences in reliability among definitions of core animals. Single-step genomic BLUP with APY is applicable to millions of genotyped animals. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An experimental validation of genomic selection in octoploid strawberry

PubMed Central

Gezan, Salvador A; Osorio, Luis F; Verma, Sujeet; Whitaker, Vance M

2017-01-01

The primary goal of genomic selection is to increase genetic gains for complex traits by predicting performance of individuals for which phenotypic data are not available. The objective of this study was to experimentally evaluate the potential of genomic selection in strawberry breeding and to define a strategy for its implementation. Four clonally replicated field trials, two in each of 2 years comprised of a total of 1628 individuals, were established in 2013–2014 and 2014–2015. Five complex yield and fruit quality traits with moderate to low heritability were assessed in each trial. High-density genotyping was performed with the Affymetrix Axiom IStraw90 single-nucleotide polymorphism array, and 17 479 polymorphic markers were chosen for analysis. Several methods were compared, including Genomic BLUP, Bayes B, Bayes C, Bayesian LASSO Regression, Bayesian Ridge Regression and Reproducing Kernel Hilbert Spaces. Cross-validation within training populations resulted in higher values than for true validations across trials. For true validations, Bayes B gave the highest predictive abilities on average and also the highest selection efficiencies, particularly for yield traits that were the lowest heritability traits. Selection efficiencies using Bayes B for parent selection ranged from 74% for average fruit weight to 34% for early marketable yield. A breeding strategy is proposed in which advanced selection trials are utilized as training populations and in which genomic selection can reduce the breeding cycle from 3 to 2 years for a subset of untested parents based on their predicted genomic breeding values. PMID:28090334

Nonparametric method for genomics-based prediction of performance of quantitative traits involving epistasis in plant breeding.

PubMed

Sun, Xiaochun; Ma, Ping; Mumm, Rita H

2012-01-01

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.

Nonparametric Method for Genomics-Based Prediction of Performance of Quantitative Traits Involving Epistasis in Plant Breeding

PubMed Central

Sun, Xiaochun; Ma, Ping; Mumm, Rita H.

2012-01-01

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression. PMID:23226325

Genomic predictability of single-step GBLUP for production traits in US Holstein

USDA-ARS?s Scientific Manuscript database

The objective of this study was to validate genomic predictability of single-step genomic BLUP for 305-day protein yield for US Holsteins. The genomic relationship matrix was created with the Algorithm of Proven and Young (APY) with 18,359 core animals. The full data set consisted of phenotypes coll...

A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods

PubMed Central

Ratcliffe, B; El-Dien, O G; Klápště, J; Porth, I; Chen, C; Jaquish, B; El-Kassaby, Y A

2015-01-01

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3–40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31–0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04–0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated. PMID:26126540

A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

PubMed

Ratcliffe, B; El-Dien, O G; Klápště, J; Porth, I; Chen, C; Jaquish, B; El-Kassaby, Y A

2015-12-01

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3-40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31-0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04-0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.

Can multi-subpopulation reference sets improve the genomic predictive ability for pigs?

PubMed

Fangmann, A; Bergfelder-Drüing, S; Tholen, E; Simianer, H; Erbe, M

2015-12-01

In most countries and for most livestock species, genomic evaluations are obtained from within-breed analyses. To achieve reliable breeding values, however, a sufficient reference sample size is essential. To increase this size, the use of multibreed reference populations for small populations is considered a suitable option in other species. Over decades, the separate breeding work of different pig breeding organizations in Germany has led to stratified subpopulations in the breed German Large White. Due to this fact and the limited number of Large White animals available in each organization, there was a pressing need for ascertaining if multi-subpopulation genomic prediction is superior compared with within-subpopulation prediction in pigs. Direct genomic breeding values were estimated with genomic BLUP for the trait "number of piglets born alive" using genotype data (Illumina Porcine 60K SNP BeadChip) from 2,053 German Large White animals from five different commercial pig breeding companies. To assess the prediction accuracy of within- and multi-subpopulation reference sets, a random 5-fold cross-validation with 20 replications was performed. The five subpopulations considered were only slightly differentiated from each other. However, the prediction accuracy of the multi-subpopulations approach was not better than that of the within-subpopulation evaluation, for which the predictive ability was already high. Reference sets composed of closely related multi-subpopulation sets performed better than sets of distantly related subpopulations but not better than the within-subpopulation approach. Despite the low differentiation of the five subpopulations, the genetic connectedness between these different subpopulations seems to be too small to improve the prediction accuracy by applying multi-subpopulation reference sets. Consequently, resources should be used for enlarging the reference population within subpopulation, for example, by adding genotyped females.

Combining Genome-Wide Information with a Functional Structural Plant Model to Simulate 1-Year-Old Apple Tree Architecture.

PubMed

Migault, Vincent; Pallas, Benoît; Costes, Evelyne

2016-01-01

In crops, optimizing target traits in breeding programs can be fostered by selecting appropriate combinations of architectural traits which determine light interception and carbon acquisition. In apple tree, architectural traits were observed to be under genetic control. However, architectural traits also result from many organogenetic and morphological processes interacting with the environment. The present study aimed at combining a FSPM built for apple tree, MAppleT, with genetic determinisms of architectural traits, previously described in a bi-parental population. We focused on parameters related to organogenesis (phyllochron and immediate branching) and morphogenesis processes (internode length and leaf area) during the first year of tree growth. Two independent datasets collected in 2004 and 2007 on 116 genotypes, issued from a 'Starkrimson' × 'Granny Smith' cross, were used. The phyllochron was estimated as a function of thermal time and sylleptic branching was modeled subsequently depending on phyllochron. From a genetic map built with SNPs, marker effects were estimated on four MAppleT parameters with rrBLUP, using 2007 data. These effects were then considered in MAppleT to simulate tree development in the two climatic conditions. The genome wide prediction model gave consistent estimations of parameter values with correlation coefficients between observed values and estimated values from SNP markers ranging from 0.79 to 0.96. However, the accuracy of the prediction model following cross validation schemas was lower. Three integrative traits (the number of leaves, trunk length, and number of sylleptic laterals) were considered for validating MAppleT simulations. In 2007 climatic conditions, simulated values were close to observations, highlighting the correct simulation of genetic variability. However, in 2004 conditions which were not used for model calibration, the simulations differed from observations. This study demonstrates the possibility of integrating genome-based information in a FSPM for a perennial fruit tree. It also showed that further improvements are required for improving the prediction ability. Especially temperature effect should be extended and other factors taken into account for modeling GxE interactions. Improvements could also be expected by considering larger populations and by testing other genome wide prediction models. Despite these limitations, this study opens new possibilities for supporting plant breeding by in silico evaluations of the impact of genotypic polymorphisms on plant integrative phenotypes.

Host range determination of Colletotrichum gloeosporioides f. sp. salsolae, a biological control agent of tumbleweed: from BLUPs to biomass loss

USDA-ARS?s Scientific Manuscript database

Host range tests were conducted with Colletotrichum gloeosporioides f. sp. salsolae (CGS) in quarantine to determine whether the fungus is safe to release in N. America for biological control of tumbleweed (Salsola tragus L., Chenopodiaceae). Ninety-two accessions were analyzed from 19 families and...

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

PubMed

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

PubMed Central

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

Genomic Selection in Commercial Perennial Crops: Applicability and Improvement in Oil Palm (Elaeis guineensis Jacq.).

PubMed

Kwong, Qi Bin; Ong, Ai Ling; Teh, Chee Keng; Chew, Fook Tim; Tammi, Martti; Mayes, Sean; Kulaveerasingam, Harikrishna; Yeoh, Suat Hui; Harikrishna, Jennifer Ann; Appleton, David Ross

2017-06-06

Genomic selection (GS) uses genome-wide markers to select individuals with the desired overall combination of breeding traits. A total of 1,218 individuals from a commercial population of Ulu Remis x AVROS (UR x AVROS) were genotyped using the OP200K array. The traits of interest included: shell-to-fruit ratio (S/F, %), mesocarp-to-fruit ratio (M/F, %), kernel-to-fruit ratio (K/F, %), fruit per bunch (F/B, %), oil per bunch (O/B, %) and oil per palm (O/P, kg/palm/year). Genomic heritabilities of these traits were estimated to be in the range of 0.40 to 0.80. GS methods assessed were RR-BLUP, Bayes A (BA), Cπ (BC), Lasso (BL) and Ridge Regression (BRR). All methods resulted in almost equal prediction accuracy. The accuracy achieved ranged from 0.40 to 0.70, correlating with the heritability of traits. By selecting the most important markers, RR-BLUP B has the potential to outperform other methods. The marker density for certain traits can be further reduced based on the linkage disequilibrium (LD). Together with in silico breeding, GS is now being used in oil palm breeding programs to hasten parental palm selection.

Genetic Dissection of Maize Embryonic Callus Regenerative Capacity Using Multi-Locus Genome-Wide Association Studies

PubMed Central

Ma, Langlang; Liu, Min; Yan, Yuanyuan; Qing, Chunyan; Zhang, Xiaoling; Zhang, Yanling; Long, Yun; Wang, Lei; Pan, Lang; Zou, Chaoying; Li, Zhaoling; Wang, Yanli; Peng, Huanwei; Pan, Guangtang; Jiang, Zhou; Shen, Yaou

2018-01-01

The regenerative capacity of the embryonic callus, a complex quantitative trait, is one of the main limiting factors for maize transformation. This trait was decomposed into five traits, namely, green callus rate (GCR), callus differentiating rate (CDR), callus plantlet number (CPN), callus rooting rate (CRR), and callus browning rate (CBR). To dissect the genetic foundation of maize transformation, in this study multi-locus genome-wide association studies (GWAS) for the five traits were performed in a population of 144 inbred lines genotyped with 43,427 SNPs. Using the phenotypic values in three environments and best linear unbiased prediction (BLUP) values, as a result, a total of 127, 56, 160, and 130 significant quantitative trait nucleotides (QTNs) were identified by mrMLM, FASTmrEMMA, ISIS EM-BLASSO, and pLARmEB, respectively. Of these QTNs, 63 QTNs were commonly detected, including 15 across multiple environments and 58 across multiple methods. Allele distribution analysis showed that the proportion of superior alleles for 36 QTNs was <50% in 31 elite inbred lines. Meanwhile, these superior alleles had obviously additive effect on the regenerative capacity. This indicates that the regenerative capacity-related traits can be improved by proper integration of the superior alleles using marker-assisted selection. Moreover, a total of 40 candidate genes were found based on these common QTNs. Some annotated genes were previously reported to relate with auxin transport, cell fate, seed germination, or embryo development, especially, GRMZM2G108933 (WOX2) was found to promote maize transgenic embryonic callus regeneration. These identified candidate genes will contribute to a further understanding of the genetic foundation of maize embryonic callus regeneration. PMID:29755499

Single-step GBLUP using APY inverse for protein yield in US Holstein with a large number of genotyped animals

USDA-ARS?s Scientific Manuscript database

The objective of this study was to provide initial results in an application of single-step genomic BLUP with a genomic relationship matrix (G^-1APY) calculated using the Algorithm of Proven and Young (APY) to 305-day protein yield for US Holsteins. Two G^-1APY were tested; one was from 139,057 geno...

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction.

PubMed

Brøndum, R F; Su, G; Janss, L; Sahana, G; Guldbrandtsen, B; Boichard, D; Lund, M S

2015-06-01

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The accuracy of Genomic Selection in Norwegian red cattle assessed by cross-validation.

PubMed

Luan, Tu; Woolliams, John A; Lien, Sigbjørn; Kent, Matthew; Svendsen, Morten; Meuwissen, Theo H E

2009-11-01

Genomic Selection (GS) is a newly developed tool for the estimation of breeding values for quantitative traits through the use of dense markers covering the whole genome. For a successful application of GS, accuracy of the prediction of genomewide breeding value (GW-EBV) is a key issue to consider. Here we investigated the accuracy and possible bias of GW-EBV prediction, using real bovine SNP genotyping (18,991 SNPs) and phenotypic data of 500 Norwegian Red bulls. The study was performed on milk yield, fat yield, protein yield, first lactation mastitis traits, and calving ease. Three methods, best linear unbiased prediction (G-BLUP), Bayesian statistics (BayesB), and a mixture model approach (MIXTURE), were used to estimate marker effects, and their accuracy and bias were estimated by using cross-validation. The accuracies of the GW-EBV prediction were found to vary widely between 0.12 and 0.62. G-BLUP gave overall the highest accuracy. We observed a strong relationship between the accuracy of the prediction and the heritability of the trait. GW-EBV prediction for production traits with high heritability achieved higher accuracy and also lower bias than health traits with low heritability. To achieve a similar accuracy for the health traits probably more records will be needed.

Genomic prediction using different estimation methodology, blending and cross-validation techniques for growth traits and visual scores in Hereford and Braford cattle.

PubMed

Campos, G S; Reimann, F A; Cardoso, L L; Ferreira, C E R; Junqueira, V S; Schmidt, P I; Braccini Neto, J; Yokoo, M J I; Sollero, B P; Boligon, A A; Cardoso, F F

2018-05-07

The objective of the present study was to evaluate the accuracy and bias of direct and blended genomic predictions using different methods and cross-validation techniques for growth traits (weight and weight gains) and visual scores (conformation, precocity, muscling and size) obtained at weaning and at yearling in Hereford and Braford breeds. Phenotypic data contained 126,290 animals belonging to the Delta G Connection genetic improvement program, and a set of 3,545 animals genotyped with the 50K chip and 131 sires with the 777K. After quality control, 41,045 markers remained for all animals. An animal model was used to estimate (co)variances components and to predict breeding values, which were later used to calculate the deregressed estimated breeding values (DEBV). Animals with genotype and phenotype for the traits studied were divided into four or five groups by random and k-means clustering cross-validation strategies. The values of accuracy of the direct genomic values (DGV) were moderate to high magnitude for at weaning and at yearling traits, ranging from 0.19 to 0.45 for the k-means and 0.23 to 0.78 for random clustering among all traits. The greatest gain in relation to the pedigree BLUP (PBLUP) was 9.5% with the BayesB method with both the k-means and the random clustering. Blended genomic value accuracies ranged from 0.19 to 0.56 for k-means and from 0.21 to 0.82 for random clustering. The analyzes using the historical pedigree and phenotypes contributed additional information to calculate the GEBV and in general, the largest gains were for the single-step (ssGBLUP) method in bivariate analyses with a mean increase of 43.00% among all traits measured at weaning and of 46.27% for those evaluated at yearling. The accuracy values for the marker effects estimation methods were lower for k-means clustering, indicating that the training set relationship to the selection candidates is a major factor affecting accuracy of genomic predictions. The gains in accuracy obtained with genomic blending methods, mainly ssGBLUP in bivariate analyses, indicate that genomic predictions should be used as a tool to improve genetic gains in relation to the traditional PBLUP selection.

Performance of genomic prediction within and across generations in maritime pine.

PubMed

Bartholomé, Jérôme; Van Heerwaarden, Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

2016-08-11

Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85. This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program.

Beyond Genomic Prediction: Combining Different Types of omics Data Can Improve Prediction of Hybrid Performance in Maize.

PubMed

Schrag, Tobias A; Westhues, Matthias; Schipprack, Wolfgang; Seifert, Felix; Thiemann, Alexander; Scholten, Stefan; Melchinger, Albrecht E

2018-04-01

The ability to predict the agronomic performance of single-crosses with high precision is essential for selecting superior candidates for hybrid breeding. With recent technological advances, thousands of new parent lines, and, consequently, millions of new hybrid combinations are possible in each breeding cycle, yet only a few hundred can be produced and phenotyped in multi-environment yield trials. Well established prediction approaches such as best linear unbiased prediction (BLUP) using pedigree data and whole-genome prediction using genomic data are limited in capturing epistasis and interactions occurring within and among downstream biological strata such as transcriptome and metabolome. Because mRNA and small RNA (sRNA) sequences are involved in transcriptional, translational and post-translational processes, we expect them to provide information influencing several biological strata. However, using sRNA data of parent lines to predict hybrid performance has not yet been addressed. Here, we gathered genomic, transcriptomic (mRNA and sRNA) and metabolomic data of parent lines to evaluate the ability of the data to predict the performance of untested hybrids for important agronomic traits in grain maize. We found a considerable interaction for predictive ability between predictor and trait, with mRNA data being a superior predictor for grain yield and genomic data for grain dry matter content, while sRNA performed relatively poorly for both traits. Combining mRNA and genomic data as predictors resulted in high predictive abilities across both traits and combining other predictors improved prediction over that of the individual predictors alone. We conclude that downstream "omics" can complement genomics for hybrid prediction, and, thereby, contribute to more efficient selection of hybrid candidates. Copyright © 2018 by the Genetics Society of America.

Estimating variance components and breeding values for number of oocytes and number of embryos in dairy cattle using a single-step genomic evaluation.

PubMed

Cornelissen, M A M C; Mullaart, E; Van der Linde, C; Mulder, H A

2017-06-01

Reproductive technologies such as multiple ovulation and embryo transfer (MOET) and ovum pick-up (OPU) accelerate genetic improvement in dairy breeding schemes. To enhance the efficiency of embryo production, breeding values for traits such as number of oocytes (NoO) and number of MOET embryos (NoM) can help in selection of donors with high MOET or OPU efficiency. The aim of this study was therefore to estimate variance components and (genomic) breeding values for NoO and NoM based on Dutch Holstein data. Furthermore, a 10-fold cross-validation was carried out to assess the accuracy of pedigree and genomic breeding values for NoO and NoM. For NoO, 40,734 OPU sessions between 1993 and 2015 were analyzed. These OPU sessions originated from 2,543 donors, from which 1,144 were genotyped. For NoM, 35,695 sessions between 1994 and 2015 were analyzed. These MOET sessions originated from 13,868 donors, from which 3,716 were genotyped. Analyses were done using only pedigree information and using a single-step genomic BLUP (ssGBLUP) approach combining genomic information and pedigree information. Heritabilities were very similar based on pedigree information or based on ssGBLUP [i.e., 0.32 (standard error = 0.03) for NoO and 0.21 (standard error = 0.01) for NoM with pedigree, 0.31 (standard error = 0.03) for NoO, and 0.22 (standard error = 0.01) for NoM with ssGBLUP]. For animals without their own information as mimicked in the cross-validation, the accuracy of pedigree-based breeding values was 0.46 for NoO and NoM. The accuracies of genomic breeding values from ssGBLUP were 0.54 for NoO and 0.52 for NoM. These results show that including genomic information increases the accuracies. These moderate accuracies in combination with a large genetic variance show good opportunities for selection of potential bull dams. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

Accounting for trait architecture in genomic predictions of US Holstein cattle using a weighted realized relationship matrix.

PubMed

Tiezzi, Francesco; Maltecca, Christian

2015-04-02

Genomic BLUP (GBLUP) can predict breeding values for non-phenotyped individuals based on the identity-by-state genomic relationship matrix (G). The G matrix can be constructed from thousands of markers spread across the genome. The strongest assumption of G and consequently of GBLUP is that all markers contribute equally to the genetic variance of a trait. This assumption is violated for traits that are controlled by a small number of quantitative trait loci (QTL) or individual QTL with large effects. In this paper, we investigate the performance of using a weighted genomic relationship matrix (wG) that takes into consideration the genetic architecture of the trait in order to improve predictive ability for a wide range of traits. Multiple methods were used to calculate weights for several economically relevant traits in US Holstein dairy cattle. Predictive performance was tested by k-means cross-validation. Relaxing the GBLUP assumption of equal marker contribution by increasing the weight that is given to a specific marker in the construction of the trait-specific G resulted in increased predictive performance. The increase was strongest for traits that are controlled by a small number of QTL (e.g. fat and protein percentage). Furthermore, bias in prediction estimates was reduced compared to that resulting from the use of regular G. Even for traits with low heritability and lower general predictive performance (e.g. calving ease traits), weighted G still yielded a gain in accuracy. Genomic relationship matrices weighted by marker realized variance yielded more accurate and less biased predictions for traits regulated by few QTL. Genome-wide association analyses were used to derive marker weights for creating weighted genomic relationship matrices. However, this can be cumbersome and prone to low stability over generations because of erosion of linkage disequilibrium between markers and QTL. Future studies may include other sources of information, such as functional annotation and gene networks, to better exploit the genetic architecture of traits and produce more stable predictions.

Evaluation of methods and marker Systems in Genomic Selection of oil palm (Elaeis guineensis Jacq.).

PubMed

Kwong, Qi Bin; Teh, Chee Keng; Ong, Ai Ling; Chew, Fook Tim; Mayes, Sean; Kulaveerasingam, Harikrishna; Tammi, Martti; Yeoh, Suat Hui; Appleton, David Ross; Harikrishna, Jennifer Ann

2017-12-11

Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits. The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods. Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation.

Selection of sugar cane families by using BLUP and multi-diverse analyses for planting in the Brazilian savannah.

PubMed

Barbosa, M H P; Ferreira, A; Peixoto, L A; Resende, M D V; Nascimento, M; Silva, F F

2014-03-12

This study evaluated different strategies to select sugar cane families and obtain clones adapted to the conditions of the Brazilian savannah. Specifically, 7 experiments were conducted, with 10 full sib families, and 2 witnesses in common to all experiments, in each experiment. The plants were grown in random blocks, with witnesses in common (incomplete blocks), and 6 repetitions of each experiment. The data were analyzed through the methodology of mixed patterns, in which the matrices of kinship between the families were identified by the method of restricted maximum likelihood. The characteristics that were evaluated included soluble solids content (BRIX), BRIX ton/ha, average mass of a culm, number of culms/m, and tons of culms/ha. A multi-diverse alternative based on the analysis of groupings by using the UPGMA method was used to identify the most viable families for selection, when considering the genotypic effects on all characteristics. This method appeared suitable for the selection of families, with 5 family groups being formed. The families that formed Group 2 appeared superior to all other families for all the evaluated characteristics. It is recommended that the families in Group 2 are preferentially used in sugar cane improvement programs to obtain varieties optimally adapted to the conditions of the Brazilian savannah.

Prediction accuracy of direct and indirect approaches, and their relationships with prediction ability of calibration models.

PubMed

Belay, T K; Dagnachew, B S; Boison, S A; Ådnøy, T

2018-03-28

Milk infrared spectra are routinely used for phenotyping traits of interest through links developed between the traits and spectra. Predicted individual traits are then used in genetic analyses for estimated breeding value (EBV) or for phenotypic predictions using a single-trait mixed model; this approach is referred to as indirect prediction (IP). An alternative approach [direct prediction (DP)] is a direct genetic analysis of (a reduced dimension of) the spectra using a multitrait model to predict multivariate EBV of the spectral components and, ultimately, also to predict the univariate EBV or phenotype for the traits of interest. We simulated 3 traits under different genetic (low: 0.10 to high: 0.90) and residual (zero to high: ±0.90) correlation scenarios between the 3 traits and assumed the first trait is a linear combination of the other 2 traits. The aim was to compare the IP and DP approaches for predictions of EBV and phenotypes under the different correlation scenarios. We also evaluated relationships between performances of the 2 approaches and the accuracy of calibration equations. Moreover, the effect of using different regression coefficients estimated from simulated phenotypes (β p ), true breeding values (β g ), and residuals (β r ) on performance of the 2 approaches were evaluated. The simulated data contained 2,100 parents (100 sires and 2,000 cows) and 8,000 offspring (4 offspring per cow). Of the 8,000 observations, 2,000 were randomly selected and used to develop links between the first and the other 2 traits using partial least square (PLS) regression analysis. The different PLS regression coefficients, such as β p , β g , and β r , were used in subsequent predictions following the IP and DP approaches. We used BLUP analyses for the remaining 6,000 observations using the true (co)variance components that had been used for the simulation. Accuracy of prediction (of EBV and phenotype) was calculated as a correlation between predicted and true values from the simulations. The results showed that accuracies of EBV prediction were higher in the DP than in the IP approach. The reverse was true for accuracy of phenotypic prediction when using β p but not when using β g and β r , where accuracy of phenotypic prediction in the DP was slightly higher than in the IP approach. Within the DP approach, accuracies of EBV when using β g were higher than when using β p only at the low genetic correlation scenario. However, we found no differences in EBV prediction accuracy between the β p and β g in the IP approach. Accuracy of the calibration models increased with an increase in genetic and residual correlations between the traits. Performance of both approaches increased with an increase in accuracy of the calibration models. In conclusion, the DP approach is a good strategy for EBV prediction but not for phenotypic prediction, where the classical PLS regression-based equations or the IP approach provided better results. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Economic evaluation of progeny-testing and genomic selection schemes for small-sized nucleus dairy cattle breeding programs in developing countries.

PubMed

Kariuki, C M; Brascamp, E W; Komen, H; Kahi, A K; van Arendonk, J A M

2017-03-01

In developing countries minimal and erratic performance and pedigree recording impede implementation of large-sized breeding programs. Small-sized nucleus programs offer an alternative but rely on their economic performance for their viability. We investigated the economic performance of 2 alternative small-sized dairy nucleus programs [i.e., progeny testing (PT) and genomic selection (GS)] over a 20-yr investment period. The nucleus was made up of 453 male and 360 female animals distributed in 8 non-overlapping age classes. Each year 10 active sires and 100 elite dams were selected. Populations of commercial recorded cows (CRC) of sizes 12,592 and 25,184 were used to produce test daughters in PT or to create a reference population in GS, respectively. Economic performance was defined as gross margins, calculated as discounted revenues minus discounted costs following a single generation of selection. Revenues were calculated as cumulative discounted expressions (CDE, kg) × 0.32 (€/kg of milk) × 100,000 (size commercial population). Genetic superiorities, deterministically simulated using pseudo-BLUP index and CDE, were determined using gene flow. Costs were for one generation of selection. Results show that GS schemes had higher cumulated genetic gain in the commercial cow population and higher gross margins compared with PT schemes. Gross margins were between 3.2- and 5.2-fold higher for GS, depending on size of the CRC population. The increase in gross margin was mostly due to a decreased generation interval and lower running costs in GS schemes. In PT schemes many bulls are culled before selection. We therefore also compared 2 schemes in which semen was stored instead of keeping live bulls. As expected, semen storage resulted in an increase in gross margins in PT schemes, but gross margins remained lower than those of GS schemes. We conclude that implementation of small-sized GS breeding schemes can be economically viable for developing countries. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Prediction of genomic breeding values for dairy traits in Italian Brown and Simmental bulls using a principal component approach.

PubMed

Pintus, M A; Gaspa, G; Nicolazzi, E L; Vicario, D; Rossoni, A; Ajmone-Marsan, P; Nardone, A; Dimauro, C; Macciotta, N P P

2012-06-01

The large number of markers available compared with phenotypes represents one of the main issues in genomic selection. In this work, principal component analysis was used to reduce the number of predictors for calculating genomic breeding values (GEBV). Bulls of 2 cattle breeds farmed in Italy (634 Brown and 469 Simmental) were genotyped with the 54K Illumina beadchip (Illumina Inc., San Diego, CA). After data editing, 37,254 and 40,179 single nucleotide polymorphisms (SNP) were retained for Brown and Simmental, respectively. Principal component analysis carried out on the SNP genotype matrix extracted 2,257 and 3,596 new variables in the 2 breeds, respectively. Bulls were sorted by birth year to create reference and prediction populations. The effect of principal components on deregressed proofs in reference animals was estimated with a BLUP model. Results were compared with those obtained by using SNP genotypes as predictors with either the BLUP or Bayes_A method. Traits considered were milk, fat, and protein yields, fat and protein percentages, and somatic cell score. The GEBV were obtained for prediction population by blending direct genomic prediction and pedigree indexes. No substantial differences were observed in squared correlations between GEBV and EBV in prediction animals between the 3 methods in the 2 breeds. The principal component analysis method allowed for a reduction of about 90% in the number of independent variables when predicting direct genomic values, with a substantial decrease in calculation time and without loss of accuracy. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genomic Prediction of Testcross Performance in Canola (Brassica napus)

PubMed Central

Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

2016-01-01

Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable potential for pre-selection of promising hybrid combinations prior to resource-intensive field testing over multiple locations and years. PMID:26824924

Genome-wide association study for ketosis in US Jerseys using producer-recorded data.

PubMed

Parker Gaddis, K L; Megonigal, J H; Clay, J S; Wolfe, C W

2018-01-01

Ketosis is one of the most frequently reported metabolic health events in dairy herds. Several genetic analyses of ketosis in dairy cattle have been conducted; however, few have focused specifically on Jersey cattle. The objectives of this research included estimating variance components for susceptibility to ketosis and identification of genomic regions associated with ketosis in Jersey cattle. Voluntary producer-recorded health event data related to ketosis were available from Dairy Records Management Systems (Raleigh, NC). Standardization was implemented to account for the various acronyms used by producers to designate an incidence of ketosis. Events were restricted to the first reported incidence within 60 d after calving in first through fifth parities. After editing, there were a total of 42,233 records from 23,865 cows. A total of 1,750 genotyped animals were used for genomic analyses using 60,671 markers. Because of the binary nature of the trait, a threshold animal model was fitted using THRGIBBS1F90 (version 2.110) using only pedigree information, and genomic information was incorporated using a single-step genomic BLUP approach. Individual single nucleotide polymorphism (SNP) effects and the proportion of variance explained by 10-SNP windows were calculated using postGSf90 (version 1.38). Heritability of susceptibility to ketosis was 0.083 [standard deviation (SD) = 0.021] and 0.078 (SD = 0.018) in pedigree-based and genomic analyses, respectively. The marker with the largest associated effect was located on chromosome 10 at 66.3 Mbp. The 10-SNP window explaining the largest proportion of variance (0.70%) was located on chromosome 6 beginning at 56.1 Mbp. Gene Ontology (GO) and Medical Subject Heading (MeSH) enrichment analyses identified several overrepresented processes and terms related to immune function. Our results indicate that there is a genetic component related to ketosis susceptibility in Jersey cattle and, as such, genetic selection for improved resistance to ketosis is feasible. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Mineral Nutritional Yield and Nutrient Density of Locally Adapted Wheat Genotypes under Organic Production

PubMed Central

Moreira-Ascarrunz, Sergio Daniel; Larsson, Hans; Prieto-Linde, Maria Luisa; Johansson, Eva

2016-01-01

The aim of the present investigation was to investigate the nutritional yield, nutrient density, stability, and adaptability of organically produced wheat for sustainable and nutritional high value food production. This study evaluated the nutritional yield of four minerals (Fe, Zn, Cu, and Mg) in 19 wheat genotypes, selected as being locally adapted under organic agriculture conditions. The new metric of nutritional yield was calculated for each genotype and they were evaluated for stability using the Additive Main effects and Multiplicative Interaction (AMMI) stability analysis and for genotypic value, stability, and adaptability using the Best Linear Unbiased Prediction (BLUP procedure). The results indicated that there were genotypes suitable for production under organic agriculture conditions with satisfactory yields (>4000 kg·ha−1). Furthermore, these genotypes showed high nutritional yield and nutrient density for the four minerals studied. Additionally, since these genotypes were stable and adaptable over three environmentally different years, they were designated “balanced genotypes” for the four minerals and for the aforementioned characteristics. Selection and breeding of such “balanced genotypes” may offer an alternative to producing nutritious food under low-input agriculture conditions. Furthermore, the type of evaluation presented here may also be of interest for implementation in research conducted in developing countries, following the objectives of producing enough nutrients for a growing population. PMID:28231184

Accuracy of genomic prediction using deregressed breeding values estimated from purebred and crossbred offspring phenotypes in pigs.

PubMed

Hidalgo, A M; Bastiaansen, J W M; Lopes, M S; Veroneze, R; Groenen, M A M; de Koning, D-J

2015-07-01

Genomic selection is applied to dairy cattle breeding to improve the genetic progress of purebred (PB) animals, whereas in pigs and poultry the target is a crossbred (CB) animal for which a different strategy appears to be needed. The source of information used to estimate the breeding values, i.e., using phenotypes of CB or PB animals, may affect the accuracy of prediction. The objective of our study was to assess the direct genomic value (DGV) accuracy of CB and PB pigs using different sources of phenotypic information. Data used were from 3 populations: 2,078 Dutch Landrace-based, 2,301 Large White-based, and 497 crossbreds from an F1 cross between the 2 lines. Two female reproduction traits were analyzed: gestation length (GLE) and total number of piglets born (TNB). Phenotypes used in the analyses originated from offspring of genotyped individuals. Phenotypes collected on CB and PB animals were analyzed as separate traits using a single-trait model. Breeding values were estimated separately for each trait in a pedigree BLUP analysis and subsequently deregressed. Deregressed EBV for each trait originating from different sources (CB or PB offspring) were used to study the accuracy of genomic prediction. Accuracy of prediction was computed as the correlation between DGV and the DEBV of the validation population. Accuracy of prediction within PB populations ranged from 0.43 to 0.62 across GLE and TNB. Accuracies to predict genetic merit of CB animals with one PB population in the training set ranged from 0.12 to 0.28, with the exception of using the CB offspring phenotype of the Dutch Landrace that resulted in an accuracy estimate around 0 for both traits. Accuracies to predict genetic merit of CB animals with both parental PB populations in the training set ranged from 0.17 to 0.30. We conclude that prediction within population and trait had good predictive ability regardless of the trait being the PB or CB performance, whereas using PB population(s) to predict genetic merit of CB animals had zero to moderate predictive ability. We observed that the DGV accuracy of CB animals when training on PB data was greater than or equal to training on CB data. However, when results are corrected for the different levels of reliabilities in the PB and CB training data, we showed that training on CB data does outperform PB data for the prediction of CB genetic merit, indicating that more CB animals should be phenotyped to increase the reliability and, consequently, accuracy of DGV for CB genetic merit.

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

PubMed Central

Pecetti, Luciano; Brummer, E. Charles; Palmonari, Alberto; Tava, Aldo

2017-01-01

Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3–0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits (by genomic selection or MAS) and forage yield. PMID:28068350

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits.

PubMed

Biazzi, Elisa; Nazzicari, Nelson; Pecetti, Luciano; Brummer, E Charles; Palmonari, Alberto; Tava, Aldo; Annicchiarico, Paolo

2017-01-01

Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits (by genomic selection or MAS) and forage yield.

Use of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses--a simulation study.

PubMed

Fragomeni, B O; Lourenco, D A L; Tsuruta, S; Masuda, Y; Aguilar, I; Misztal, I

2015-10-01

The purpose of this study was to examine accuracy of genomic selection via single-step genomic BLUP (ssGBLUP) when the direct inverse of the genomic relationship matrix (G) is replaced by an approximation of G(-1) based on recursions for young genotyped animals conditioned on a subset of proven animals, termed algorithm for proven and young animals (APY). With the efficient implementation, this algorithm has a cubic cost with proven animals and linear with young animals. Ten duplicate data sets mimicking a dairy cattle population were simulated. In a first scenario, genomic information for 20k genotyped bulls, divided in 7k proven and 13k young bulls, was generated for each replicate. In a second scenario, 5k genotyped cows with phenotypes were included in the analysis as young animals. Accuracies (average for the 10 replicates) in regular EBV were 0.72 and 0.34 for proven and young animals, respectively. When genomic information was included, they increased to 0.75 and 0.50. No differences between genomic EBV (GEBV) obtained with the regular G(-1) and the approximated G(-1) via the recursive method were observed. In the second scenario, accuracies in GEBV (0.76, 0.51 and 0.59 for proven bulls, young males and young females, respectively) were also higher than those in EBV (0.72, 0.35 and 0.49). Again, no differences between GEBV with regular G(-1) and with recursions were observed. With the recursive algorithm, the number of iterations to achieve convergence was reduced from 227 to 206 in the first scenario and from 232 to 209 in the second scenario. Cows can be treated as young animals in APY without reducing the accuracy. The proposed algorithm can be implemented to reduce computing costs and to overcome current limitations on the number of genotyped animals in the ssGBLUP method. © 2015 Blackwell Verlag GmbH.

A function accounting for training set size and marker density to model the average accuracy of genomic prediction.

PubMed

Erbe, Malena; Gredler, Birgit; Seefried, Franz Reinhold; Bapst, Beat; Simianer, Henner

2013-01-01

Prediction of genomic breeding values is of major practical relevance in dairy cattle breeding. Deterministic equations have been suggested to predict the accuracy of genomic breeding values in a given design which are based on training set size, reliability of phenotypes, and the number of independent chromosome segments ([Formula: see text]). The aim of our study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically. Two data sets of 5'698 Holstein Friesian bulls genotyped with 50 K SNPs and 1'332 Brown Swiss bulls genotyped with 50 K SNPs and imputed to ∼600 K SNPs were available. Different k-fold (k = 2-10, 15, 20) cross-validation scenarios (50 replicates, random assignment) were performed using a genomic BLUP approach. A maximum likelihood approach was used to estimate the parameters of different prediction equations. The highest likelihood was obtained when using a modified form of the deterministic equation of Daetwyler et al. (2010), augmented by a weighting factor (w) based on the assumption that the maximum achievable accuracy is [Formula: see text]. The proportion of genetic variance captured by the complete SNP sets ([Formula: see text]) was 0.76 to 0.82 for Holstein Friesian and 0.72 to 0.75 for Brown Swiss. When modifying the number of SNPs, w was found to be proportional to the log of the marker density up to a limit which is population and trait specific and was found to be reached with ∼20'000 SNPs in the Brown Swiss population studied.

A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice.

PubMed

Jacquin, Laval; Cao, Tuong-Vi; Ahmadi, Nourollah

2016-01-01

One objective of this study was to provide readers with a clear and unified understanding of parametric statistical and kernel methods, used for genomic prediction, and to compare some of these in the context of rice breeding for quantitative traits. Furthermore, another objective was to provide a simple and user-friendly R package, named KRMM, which allows users to perform RKHS regression with several kernels. After introducing the concept of regularized empirical risk minimization, the connections between well-known parametric and kernel methods such as Ridge regression [i.e., genomic best linear unbiased predictor (GBLUP)] and reproducing kernel Hilbert space (RKHS) regression were reviewed. Ridge regression was then reformulated so as to show and emphasize the advantage of the kernel "trick" concept, exploited by kernel methods in the context of epistatic genetic architectures, over parametric frameworks used by conventional methods. Some parametric and kernel methods; least absolute shrinkage and selection operator (LASSO), GBLUP, support vector machine regression (SVR) and RKHS regression were thereupon compared for their genomic predictive ability in the context of rice breeding using three real data sets. Among the compared methods, RKHS regression and SVR were often the most accurate methods for prediction followed by GBLUP and LASSO. An R function which allows users to perform RR-BLUP of marker effects, GBLUP and RKHS regression, with a Gaussian, Laplacian, polynomial or ANOVA kernel, in a reasonable computation time has been developed. Moreover, a modified version of this function, which allows users to tune kernels for RKHS regression, has also been developed and parallelized for HPC Linux clusters. The corresponding KRMM package and all scripts have been made publicly available.

Empirical comparison between different methods for genomic prediction of number of piglets born alive in moderate sized breeding populations.

PubMed

Fangmann, A; Sharifi, R A; Heinkel, J; Danowski, K; Schrade, H; Erbe, M; Simianer, H

2017-04-01

Currently used multi-step methods to incorporate genomic information in the prediction of breeding values (BV) implicitly involve many assumptions which, if violated, may result in loss of information, inaccuracies and bias. To overcome this, single-step genomic best linear unbiased prediction (ssGBLUP) was proposed combining pedigree, phenotype and genotype of all individuals for genetic evaluation. Our objective was to implement ssGBLUP for genomic predictions in pigs and to compare the accuracy of ssGBLUP with that of multi-step methods with empirical data of moderately sized pig breeding populations. Different predictions were performed: conventional parent average (PA), direct genomic value (DGV) calculated with genomic BLUP (GBLUP), a GEBV obtained by blending the DGV with PA, and ssGBLUP. Data comprised individuals from a German Landrace (LR) and Large White (LW) population. The trait 'number of piglets born alive' (NBA) was available for 182,054 litters of 41,090 LR sows and 15,750 litters from 4534 LW sows. The pedigree contained 174,021 animals, of which 147,461 (26,560) animals were LR (LW) animals. In total, 526 LR and 455 LW animals were genotyped with the Illumina PorcineSNP60 BeadChip. After quality control and imputation, 495 LR (424 LW) animals with 44,368 (43,678) SNP on 18 autosomes remained for the analysis. Predictive abilities, i.e., correlations between de-regressed proofs and genomic BV, were calculated with a five-fold cross validation and with a forward prediction for young genotyped validation animals born after 2011. Generally, predictive abilities for LR were rather small (0.08 for GBLUP, 0.19 for GEBV and 0.18 for ssGBLUP). For LW, ssGBLUP had the greatest predictive ability (0.45). For both breeds, assessment of reliabilities for young genotyped animals indicated that genomic prediction outperforms PA with ssGBLUP providing greater reliabilities (0.40 for LR and 0.32 for LW) than GEBV (0.35 for LR and 0.29 for LW). Grouping of animals according to information sources revealed that genomic prediction had the highest potential benefit for genotyped animals without their own phenotype. Although, ssGBLUP did not generally outperform GBLUP or GEBV, the results suggest that ssGBLUP can be a useful and conceptually convincing approach for practical genomic prediction of NBA in moderately sized LR and LW populations.

Genomic analysis of cow mortality and milk production using a threshold-linear model.

PubMed

Tsuruta, S; Lourenco, D A L; Misztal, I; Lawlor, T J

2017-09-01

The objective of this study was to investigate the feasibility of genomic evaluation for cow mortality and milk production using a single-step methodology. Genomic relationships between cow mortality and milk production were also analyzed. Data included 883,887 (866,700) first-parity, 733,904 (711,211) second-parity, and 516,256 (492,026) third-parity records on cow mortality (305-d milk yields) of Holsteins from Northeast states in the United States. The pedigree consisted of up to 1,690,481 animals including 34,481 bulls genotyped with 36,951 SNP markers. Analyses were conducted with a bivariate threshold-linear model for each parity separately. Genomic information was incorporated as a genomic relationship matrix in the single-step BLUP. Traditional and genomic estimated breeding values (GEBV) were obtained with Gibbs sampling using fixed variances, whereas reliabilities were calculated from variances of GEBV samples. Genomic EBV were then converted into single nucleotide polymorphism (SNP) marker effects. Those SNP effects were categorized according to values corresponding to 1 to 4 standard deviations. Moving averages and variances of SNP effects were calculated for windows of 30 adjacent SNP, and Manhattan plots were created for SNP variances with the same window size. Using Gibbs sampling, the reliability for genotyped bulls for cow mortality was 28 to 30% in EBV and 70 to 72% in GEBV. The reliability for genotyped bulls for 305-d milk yields was 53 to 65% to 81 to 85% in GEBV. Correlations of SNP effects between mortality and 305-d milk yields within categories were the highest with the largest SNP effects and reached >0.7 at 4 standard deviations. All SNP regions explained less than 0.6% of the genetic variance for both traits, except regions close to the DGAT1 gene, which explained up to 2.5% for cow mortality and 4% for 305-d milk yields. Reliability for GEBV with a moderate number of genotyped animals can be calculated by Gibbs samples. Genomic information can greatly increase the reliability of predictions not only for milk but also for mortality. The existence of a common region on Bos taurus autosome 14 affecting both traits may indicate a major gene with a pleiotropic effect on milk and mortality. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar).

PubMed

Bangera, Rama; Correa, Katharina; Lhorente, Jean P; Figueroa, René; Yáñez, José M

2017-01-31

Salmon Rickettsial Syndrome (SRS) caused by Piscirickettsia salmonis is a major disease affecting the Chilean salmon industry. Genomic selection (GS) is a method wherein genome-wide markers and phenotype information of full-sibs are used to predict genomic EBV (GEBV) of selection candidates and is expected to have increased accuracy and response to selection over traditional pedigree based Best Linear Unbiased Prediction (PBLUP). Widely used GS methods such as genomic BLUP (GBLUP), SNPBLUP, Bayes C and Bayesian Lasso may perform differently with respect to accuracy of GEBV prediction. Our aim was to compare the accuracy, in terms of reliability of genome-enabled prediction, from different GS methods with PBLUP for resistance to SRS in an Atlantic salmon breeding program. Number of days to death (DAYS), binary survival status (STATUS) phenotypes, and 50 K SNP array genotypes were obtained from 2601 smolts challenged with P. salmonis. The reliability of different GS methods at different SNP densities with and without pedigree were compared to PBLUP using a five-fold cross validation scheme. Heritability estimated from GS methods was significantly higher than PBLUP. Pearson's correlation between predicted GEBV from PBLUP and GS models ranged from 0.79 to 0.91 and 0.79-0.95 for DAYS and STATUS, respectively. The relative increase in reliability from different GS methods for DAYS and STATUS with 50 K SNP ranged from 8 to 25% and 27-30%, respectively. All GS methods outperformed PBLUP at all marker densities. DAYS and STATUS showed superior reliability over PBLUP even at the lowest marker density of 3 K and 500 SNP, respectively. 20 K SNP showed close to maximal reliability for both traits with little improvement using higher densities. These results indicate that genomic predictions can accelerate genetic progress for SRS resistance in Atlantic salmon and implementation of this approach will contribute to the control of SRS in Chile. We recommend GBLUP for routine GS evaluation because this method is computationally faster and the results are very similar with other GS methods. The use of lower density SNP or the combination of low density SNP and an imputation strategy may help to reduce genotyping costs without compromising gain in reliability.

Stabilized determination of geopotential coefficients by the mixed hom-BLUP approach

NASA Technical Reports Server (NTRS)

Middel, B.; Schaffrin, B.

1989-01-01

For the determination of geopotential coefficients, data can be used from rather different sources, e.g., satellite tracking, gravimetry, or altimetry. As each data type is particularly sensitive to certain wavelengths of the spherical harmonic coefficients it is of essential importance how they are treated in a combination solution. For example the longer wavelengths are well described by the coefficients of a model derived by satellite tracking, while other observation types such as gravity anomalies, delta g, and geoid heights, N, from altimetry contain only poor information for these long wavelengths. Therefore, the lower coefficients of the satellite model should be treated as being superior in the combination. In the combination a new method is presented which turns out to be highly suitable for this purpose due to its great flexibility combined with robustness.

Genome-wide association study for birth, weaning and yearling weight in Colombian Brahman cattle

PubMed Central

Martínez, Rodrigo; Bejarano, Diego; Gómez, Yolanda; Dasoneville, Romain; Jiménez, Ariel; Even, Gael; Sölkner, Johann; Mészáros, Gabor

2017-01-01

Abstract Genotypic and phenotypic data of 1,562 animals were analyzed to find genomic regions that potentially influence the birth weight (BW), weaning weight at seven months of age (WW) and yearling weight (YW) of Colombian Brahman cattle, with genotyping conducted using Illumina Bead chip array with 74,669 SNPs. A Single Step Genomic BLUP (ssGBLP), approach was used to estimate the proportion of variance explained by each marker. Multiple regions scattered across the genome were found to influence weights at different ages, also dependent on the trait component (direct or maternal). The most interesting regions were connected to previously identified QTLs and genes, such as ADAMTSL3, CAPN2, CAPN2, FABP6, ZEB2 influencing growth and weight traits. The identified regions will contribute to the development and refinement of genomic selection programs for Zebu Brahman cattle in Colombia. PMID:28534927

Applied genetic evaluations for production and functional traits in dairy cattle.

PubMed

Mark, T

2004-08-01

The objective of this study was to review the current status of genetic evaluation systems for production and functional traits as practiced in different Interbull member countries and to discuss that status in relation to research results and potential improvements. Thirty-one countries provided information. Substantial variation was evident for number of traits considered per country, trait definition, genetic evaluation procedure within trait, effects included, and how these were treated in genetic evaluation models. All countries lacked genetic evaluations for one or more economically important traits. Improvement in the genetic evaluation models, especially for many functional traits, could be achieved by closing the gaps between research and practice. More detailed and up to date information about national genetic evaluation systems for traits in different countries is available at www.interbull.org. Female fertility and workability traits were considered in many countries and could be next in line for international genetic evaluations.

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number.

PubMed

Sukumaran, Sivakumar; Lopes, Marta; Dreisigacker, Susanne; Reynolds, Matthew

2018-04-01

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number. Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci-6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)-were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79-85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

Acceptance of genetically modified foods: the relation between technology and evaluation.

PubMed

Tenbült, Petra; De Vries, Nanne K; van Breukelen, Gerard; Dreezens, Ellen; Martijn, Carolien

2008-07-01

This study investigates why consumers accept different genetically modified food products to different extents. The study shows that whether food products are genetically modified or not and whether they are processed or not are the two important features that affect the acceptance of food products and their evaluation (in terms of perceived healthiness, naturalness, necessity and tastiness). The extent to which these evaluation attributes and acceptance of a product are affected by genetic modification or processing depends on whether the product is negatively affected by the other technology: Any technological change to a 'natural' product (when nonprocessed products are genetically modified or when non-genetically modified products are processed) affect evaluation and acceptance stronger than a change to an technologically adapted product (when processed products are also genetically modified or vice versa). Furthermore, evaluation attributes appear to mediate the effects of genetic modification and processing on acceptance.

Evaluation of body condition score measured throughout lactation as an indicator of fertility in dairy cattle.

PubMed

Banos, G; Brotherstone, S; Coffey, M P

2004-08-01

Body condition score (BCS) records of primiparous Holstein cows were analyzed both as a single measure per animal and as repeated measures per sire of cow. The former resulted in a single, average, genetic evaluation for each sire, and the latter resulted in separate genetic evaluations per day of lactation. Repeated measure analysis yielded genetic correlations of less than unity between days of lactation, suggesting that BCS may not be the same trait across lactation. Differences between daily genetic evaluations on d 10 or 30 and subsequent daily evaluations were used to assess BCS change at different stages of lactation. Genetic evaluations for BCS level or change were used to estimate genetic correlations between BCS measures and fertility traits in order to assess the capacity of BCS to predict fertility. Genetic correlation estimates with calving interval and non-return rate were consistently higher for daily BCS than single measure BCS evaluations, but results were not always statistically different. Genetic correlations between BCS change and fertility traits were not significantly different from zero. The product of the accuracy of BCS evaluations with their genetic correlation with the UK fertility index, comprising calving interval and non-return rate, was consistently higher for daily than for single BCS evaluations, by 28 to 53%. This product is associated with the conceptual correlated response in fertility from BCS selection and was highest for early (d 10 to 75) evaluations.

Uptake of Predictive Genetic Testing and Cardiac Evaluation for Children at Risk for an Inherited Arrhythmia or Cardiomyopathy.

PubMed

Christian, Susan; Atallah, Joseph; Clegg, Robin; Giuffre, Michael; Huculak, Cathleen; Dzwiniel, Tara; Parboosingh, Jillian; Taylor, Sherryl; Somerville, Martin

2018-02-01

Predictive genetic testing in minors should be considered when clinical intervention is available. Children who carry a pathogenic variant for an inherited arrhythmia or cardiomyopathy require regular cardiac screening and may be prescribed medication and/or be told to modify their physical activity. Medical genetics and pediatric cardiology charts were reviewed to identify factors associated with uptake of genetic testing and cardiac evaluation for children at risk for long QT syndrome, hypertrophic cardiomyopathy or arrhythmogenic right ventricular cardiomyopathy. The data collected included genetic diagnosis, clinical symptoms in the carrier parent, number of children under 18 years of age, age of children, family history of sudden cardiac arrest/death, uptake of cardiac evaluation and if evaluated, phenotype for each child. We identified 97 at risk children from 58 families found to carry a pathogenic variant for one of these conditions. Sixty six percent of the families pursued genetic testing and 73% underwent cardiac screening when it was recommended. Declining predictive genetic testing was significantly associated with genetic specialist recommendation (p < 0.001) and having an asymptomatic carrier father (p = 0.006). Cardiac evaluation was significantly associated with uptake of genetic testing (p = 0.007). This study provides a greater understanding of factors associated with uptake of genetic testing and cardiac evaluation in children at risk of an inherited arrhythmia or cardiomyopathy. It also identifies a need to educate families about the importance of cardiac evaluation even in the absence of genetic testing.

Stability of fruit quality traits in diverse watermelon cultivars tested in multiple environments

PubMed Central

Dia, Mahendra; Wehner, Todd C; Perkins-Veazie, Penelope; Hassell, Richard; Price, Daniel S; Boyhan, George E; Olson, Stephen M; King, Stephen R; Davis, Angela R; Tolla, Gregory E; Bernier, Jerome; Juarez, Benito

2016-01-01

Lycopene is a naturally occurring red carotenoid compound that is found in watermelon. Lycopene has antioxidant properties. Lycopene content, sugar content and hollowheart resistance are subject to significant genotype×environment interaction (G×E), which makes breeding for these fruit quality traits difficult. The objectives of this study were to (i) evaluate the influence of years and locations on lycopene content, sugar content and hollowheart resistance for a set of watermelon genotypes, and (ii) identify genotypes with high stability for lycopene, sugar, and hollowheart resistance. A diverse set of 40 genotypes was tested over 3 years and 8 locations across the southern United States in replicated, multi-harvest trials. Lycopene was tested in a subset of 10 genotypes. Data were analyzed using univariate and multivariate stability statistics (BLUP-GGE biplot) using SASGxE and RGxE programs. There were strong effects of environment as well as G×E interaction on watermelon quality traits. On the basis of stability measures, genotypes were classified as stable or unstable for each quality trait. 'Crimson Sweet' is an inbred line with high quality trait performance as well as trait stability. 'Stone Mountain', 'Tom Watson', 'Crimson Sweet' and 'Minilee' were among the best genotypes for lycopene content, sugar content and hollowheart resistance. We developed a stability chart based on marketable yield and average ranking generated from different stability measures for yield attributes and quality traits. The chart will assist in choosing parents for improvement of watermelon cultivars. See http://cuke.hort.ncsu.edu/cucurbit/wmelon/wmelonmain.html. PMID:28066557

Genetic evaluation for cow livability

USDA-ARS?s Scientific Manuscript database

When genetic evaluations for Productive Life were introduced by USDA in 1994, U.S. dairy producers had an opportunity to produce healthier cows, and it happened. The genetic evaluations were incorporated into selection programs and the deterioration occurring in pregnancy rate and somatic cell score...

Multiple Query Evaluation Based on an Enhanced Genetic Algorithm.

ERIC Educational Resources Information Center

Tamine, Lynda; Chrisment, Claude; Boughanem, Mohand

2003-01-01

Explains the use of genetic algorithms to combine results from multiple query evaluations to improve relevance in information retrieval. Discusses niching techniques, relevance feedback techniques, and evolution heuristics, and compares retrieval results obtained by both genetic multiple query evaluation and classical single query evaluation…

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

PubMed

Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

2018-04-01

The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

Invited review: Genetics and claw health: Opportunities to enhance claw health by genetic selection

USDA-ARS?s Scientific Manuscript database

Routine recording of claw health status at claw trimming of dairy cattle have been established in several countries, providing valuable data for genetic evaluation. In this review, issues related to genetic evaluation of claw health are examined, data sources, trait definitions and data validation p...

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy

PubMed Central

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-01-01

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling. PMID:28287497

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy.

PubMed

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-03-12

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling.

Consumers' views of direct-to-consumer genetic information.

PubMed

McBride, Colleen M; Wade, Christopher H; Kaphingst, Kimberly A

2010-01-01

In this report, we describe the evolution and types of genetic information provided directly to consumers, discuss potential advantages and disadvantages of these products, and review research evaluating consumer responses to direct-to-consumer (DTC) genetic testing. The available evidence to date has focused on predictive tests and does not suggest that individuals, health care providers, or health care systems have been harmed by a DTC provision of genetic information. An understanding of consumer responses to susceptibility tests has lagged behind. The Multiplex Initiative is presented as a case study of research to understand consumers' responses to DTC susceptibility tests. Three priority areas are recommended for accelerated research activities to inform public policy regarding DTC genetic information: (a) exploring consumer's long-term responses to DTC genetic testing on a comprehensive set of outcomes, (b) evaluating optimal services to support decision making about genetic testing, and (c) evaluating best practices in promoting genetic competencies among health providers.

Genetic Identity in Genebanks: Application of the SolCAP 12K SNP Array in Fingerprinting and Diversity Analysis in the Global In Trust Potato Collection.

PubMed

Ellis, David; Chavez, Oswaldo; Coombs, Joseph J; Soto, Julian V; Gomez, Rene; Douches, David S; Panta, Ana; Silvestre, Rocio; Anglin, Noelle Lynette

2018-05-24

Breeders rely on genetic integrity of material from genebanks, however, mislabeling and errors in original data can occur. Paired samples of original material and their in vitro counterparts from 250 diverse potato landrace accessions from the International Potato Center (CIP), were fingerprinted using the Infinium 12K V2 Potato Array to confirm genetic identity and evaluate genetic diversity. Diploid, triploid, and tetraploid accessions were included representing seven cultivated potato taxa (Hawkes, 1990). Fingerprints between mother field plants and in vitro clones, were used to evaluate identity, relatedness, and ancestry. Clones of the same accession grouped together, however eleven (4.4%) accessions were mismatches genetically. SNP genotypes were used to construct a phylogeny to evaluate inter- and intraspecific relationships and population structure. Data suggests that the triploids evaluated are genetically similar. STRUCTURE analysis identified several putative hybrids and suggests six populations with significant gene flow between. This study provides a model for genetic identity of plant genetic resources collections as mistakes in conservation of these collections and in genebanks is a reality and confirmed identity is critical for breeders and other users of these collections, as well as for quality management programs and to provide insights into the diversity of the accessions evaluated.

Genetic Evaluation of Short Stature

PubMed Central

Rosenfeld, Ron G.

2014-01-01

Context: Genetics plays a major role in determining an individual's height. Although there are many monogenic disorders that lead to perturbations in growth and result in short stature, there is still no consensus as to the role that genetic diagnostics should play in the evaluation of a child with short stature. Evidence Acquisition: A search of PubMed was performed, focusing on the genetic diagnosis of short stature as well as on specific diagnostic subgroups included in this article. Consensus guidelines were reviewed. Evidence Synthesis: There are a multitude of rare genetic causes of severe short stature. There is no high-quality evidence to define the optimal approach to the genetic evaluation of short stature. We review genetic etiologies of a number of diagnostic subgroups and propose an algorithm for genetic testing based on these subgroups. Conclusion: Advances in genomic technologies are revolutionizing the diagnostic approach to short stature. Endocrinologists must become facile with the use of genetic testing in order to identify the various monogenic disorders that present with short stature. PMID:24915122

Aerodynamic Optimization of a Supersonic Bending Body Projectile by a Vector-Evaluated Genetic Algorithm

DTIC Science & Technology

2016-12-01

Evaluated Genetic Algorithm prepared by Justin L Paul Academy of Applied Science 24 Warren Street Concord, NH 03301 under contract W911SR...Supersonic Bending Body Projectile by a Vector-Evaluated Genetic Algorithm prepared by Justin L Paul Academy of Applied Science 24 Warren Street... Genetic Algorithm 5a. CONTRACT NUMBER W199SR-15-2-001 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Justin L Paul 5d. PROJECT

Random regression models using Legendre orthogonal polynomials to evaluate the milk production of Alpine goats.

PubMed

Silva, F G; Torres, R A; Brito, L F; Euclydes, R F; Melo, A L P; Souza, N O; Ribeiro, J I; Rodrigues, M T

2013-12-11

The objective of this study was to identify the best random regression model using Legendre orthogonal polynomials to evaluate Alpine goats genetically and to estimate the parameters for test day milk yield. On the test day, we analyzed 20,710 records of milk yield of 667 goats from the Goat Sector of the Universidade Federal de Viçosa. The evaluated models had combinations of distinct fitting orders for polynomials (2-5), random genetic (1-7), and permanent environmental (1-7) fixed curves and a number of classes for residual variance (2, 4, 5, and 6). WOMBAT software was used for all genetic analyses. A random regression model using the best Legendre orthogonal polynomial for genetic evaluation of milk yield on the test day of Alpine goats considered a fixed curve of order 4, curve of genetic additive effects of order 2, curve of permanent environmental effects of order 7, and a minimum of 5 classes of residual variance because it was the most economical model among those that were equivalent to the complete model by the likelihood ratio test. Phenotypic variance and heritability were higher at the end of the lactation period, indicating that the length of lactation has more genetic components in relation to the production peak and persistence. It is very important that the evaluation utilizes the best combination of fixed, genetic additive and permanent environmental regressions, and number of classes of heterogeneous residual variance for genetic evaluation using random regression models, thereby enhancing the precision and accuracy of the estimates of parameters and prediction of genetic values.

A Genome-Wide Association Study for Clinical Mastitis in First Parity US Holstein Cows Using Single-Step Approach and Genomic Matrix Re-Weighting Procedure

PubMed Central

Tiezzi, Francesco; Parker-Gaddis, Kristen L.; Cole, John B.; Clay, John S.; Maltecca, Christian

2015-01-01

Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 were also involved in regulating immune response (IFIH1, LY75, and DPP4), or are themselves regulated in the presence of specific pathogens (ITGB6, NR4A2). Other genes annotated on chromosome 20 are involved in mammary gland metabolism (GHR, OXCT1), antibody production and phagocytosis of bacterial cells (C6, C7, C9, C1QTNF3), tumor suppression (DAB2), involution of mammary epithelium (OSMR) and cytokine regulation (PRLR). DAVID enrichment analysis revealed 5 KEGG pathways. The JAK-STAT signaling pathway (cell proliferation and apoptosis) and the ‘Cytokine-cytokine receptor interaction’ (cytokine and interleukines response to infectious agents) are co-regulated and linked to the ‘ABC transporters’ pathway also found here. Gene network analysis performed using GeneMania revealed a co-expression network where 665 interactions existed among 145 of the genes reported above. Clinical mastitis is a complex trait and the different genes regulating immune response are known to be pathogen-specific. Despite the lack of information in this study, candidate QTL for CM were identified in the US Holstein population. PMID:25658712

Genomic Prediction of Resistance to Pasteurellosis in Gilthead Sea Bream (Sparus aurata) Using 2b-RAD Sequencing

PubMed Central

Palaiokostas, Christos; Ferraresso, Serena; Franch, Rafaella; Houston, Ross D.; Bargelloni, Luca

2016-01-01

Gilthead sea bream (Sparus aurata) is a species of paramount importance to the Mediterranean aquaculture industry, with an annual production exceeding 140,000 metric tons. Pasteurellosis due to the Gram-negative bacterium Photobacterium damselae subsp. piscicida (Phdp) causes significant mortality, especially during larval and juvenile stages, and poses a serious threat to bream production. Selective breeding for improved resistance to pasteurellosis is a promising avenue for disease control, and the use of genetic markers to predict breeding values can improve the accuracy of selection, and allow accurate calculation of estimated breeding values of nonchallenged animals. In the current study, a population of 825 sea bream juveniles, originating from a factorial cross between 67 broodfish (32 sires, 35 dams), were challenged by 30 min immersion with 1 × 105 CFU virulent Phdp. Mortalities and survivors were recorded and sampled for genotyping by sequencing. The restriction-site associated DNA sequencing approach, 2b-RAD, was used to generate genome-wide single nucleotide polymorphism (SNP) genotypes for all samples. A high-density linkage map containing 12,085 SNPs grouped into 24 linkage groups (consistent with the karyotype) was constructed. The heritability of surviving days (censored data) was 0.22 (95% highest density interval: 0.11–0.36) and 0.28 (95% highest density interval: 0.17–0.4) using the pedigree and the genomic relationship matrix respectively. A genome-wide association study did not reveal individual SNPs significantly associated with resistance at a genome-wide significance level. Genomic prediction approaches were tested to investigate the potential of the SNPs obtained by 2b-RAD for estimating breeding values for resistance. The accuracy of the genomic prediction models (r = 0.38–0.46) outperformed the traditional BLUP approach based on pedigree records (r = 0.30). Overall results suggest that major quantitative trait loci affecting resistance to pasteurellosis were not present in this population, but highlight the effectiveness of 2b-RAD genotyping by sequencing for genomic selection in a mass spawning fish species. PMID:27652890

Computational Integration of Human Genetic Data to Evaluate AOP-Specific Susceptibility

EPA Science Inventory

There is a need for approaches to efficiently evaluate human genetic variability and susceptibility related to environmental chemical exposure. Direct estimation of the genetic contribution to variability in susceptibility to environmental chemicals is only possible in special ca...

Random forest estimation of genomic breeding values for disease susceptibility over different disease incidences and genomic architectures in simulated cow calibration groups.

PubMed

Naderi, S; Yin, T; König, S

2016-09-01

A simulation study was conducted to investigate the performance of random forest (RF) and genomic BLUP (GBLUP) for genomic predictions of binary disease traits based on cow calibration groups. Training and testing sets were modified in different scenarios according to disease incidence, the quantitative-genetic background of the trait (h(2)=0.30 and h(2)=0.10), and the genomic architecture [725 quantitative trait loci (QTL) and 290 QTL, populations with high and low levels of linkage disequilibrium (LD)]. For all scenarios, 10,005 SNP (depicting a low-density 10K SNP chip) and 50,025 SNP (depicting a 50K SNP chip) were evenly spaced along 29 chromosomes. Training and testing sets included 20,000 cows (4,000 sick, 16,000 healthy, disease incidence 20%) from the last 2 generations. Initially, 4,000 sick cows were assigned to the testing set, and the remaining 16,000 healthy cows represented the training set. In the ongoing allocation schemes, the number of sick cows in the training set increased stepwise by moving 10% of the sick animals from the testing set to the training set, and vice versa. The size of the training and testing sets was kept constant. Evaluation criteria for both GBLUP and RF were the correlations between genomic breeding values and true breeding values (prediction accuracy), and the area under the receiving operating characteristic curve (AUROC). Prediction accuracy and AUROC increased for both methods and all scenarios as increasing percentages of sick cows were allocated to the training set. Highest prediction accuracies were observed for disease incidences in training sets that reflected the population disease incidence of 0.20. For this allocation scheme, the largest prediction accuracies of 0.53 for RF and of 0.51 for GBLUP, and the largest AUROC of 0.66 for RF and of 0.64 for GBLUP, were achieved using 50,025 SNP, a heritability of 0.30, and 725 QTL. Heritability decreases from 0.30 to 0.10 and QTL reduction from 725 to 290 were associated with decreasing prediction accuracy and decreasing AUROC for all scenarios. This decrease was more pronounced for RF. Also, the increase of LD had stronger effect on RF results than on GBLUP results. The highest prediction accuracy from the low LD scenario was 0.30 from RF and 0.36 from GBLUP, and increased to 0.39 for both methods in the high LD population. Random forest successfully identified important SNP in close map distance to QTL explaining a high proportion of the phenotypic trait variations. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis

DTIC Science & Technology

2012-08-01

AD_________________ Award Number: W81XWH-10-1-0469 TITLE: Genetic Evaluation for the Scoliosis ...Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis PRINCIPAL INVESTIGATOR: David W. Polly, Jr., M.D...2011 – 31 July 2012 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1

Moderation of genetic factors by parental divorce in adolescents' evaluations of family functioning and subjective wellbeing.

PubMed

van der Aa, Niels; Boomsma, Dorret I; Rebollo-Mesa, Irene; Hudziak, James J; Bartels, Meike

2010-04-01

Adolescents' evaluations of family functioning may have a significant impact on their subjective well-being and adjustment. The aim of the study was to investigate the degree to which genetic and environmental influences affect variation in evaluations of general family functioning, family conflict, and quality of life and the overlap between them. We assessed whether genetic and environmental influences are moderated by parental divorce by analyzing self-report data from 6,773 adolescent twins and their non-twin siblings. Genetic, shared, and nonshared environmental influences accounted for variation in general family functioning and family conflict, with genetic influences being relatively more important in girls than boys in general family functioning. Genetic and nonshared environmental influences accounted for variation in quality of life, with genetic influences being relatively more important in girls. Evidence was found for interaction between genetic factors and parental divorce: genetic influence on general family functioning was larger in participants from divorced families. The overlap between general family functioning and quality of life, and family conflict and quality of life was accounted for the largest part by genetic effects, with nonshared environmental effects accounting for the remaining part. By examining the data from monozygotic twins, we found evidence for interaction between genotype and nonshared, non-measured, environmental influences on evaluations of general family functioning, family conflict, and quality of life.

A Road Map for 21st Century Genetic Restoration: Gene Pool Enrichment of the Black-Footed Ferret.

PubMed

Wisely, Samantha M; Ryder, Oliver A; Santymire, Rachel M; Engelhardt, John F; Novak, Ben J

2015-01-01

Interspecies somatic cell nuclear transfer (iSCNT) could benefit recovery programs of critically endangered species but must be weighed with the risks of failure. To weigh the risks and benefits, a decision-making process that evaluates progress is needed. Experiments that evaluate the efficiency and efficacy of blastocyst, fetal, and post-parturition development are necessary to determine the success or failure or species-specific iSCNT programs. Here, we use the black-footed ferret (Mustela nigripes) as a case study for evaluating this emerging biomedical technology as a tool for genetic restoration. The black-footed ferret has depleted genetic variation yet genome resource banks contain genetic material of individuals not currently represented in the extant lineage. Thus, genetic restoration of the species is in theory possible and could help reduce the persistent erosion of genetic diversity from drift. Extensive genetic, genomic, and reproductive science tools have previously been developed in black-footed ferrets and would aid in the process of developing an iSCNT protocol for this species. Nonetheless, developing reproductive cloning will require years of experiments and a coordinated effort among recovery partners. The information gained from a well-planned research effort with the goal of genetic restoration via reproductive cloning could establish a 21st century model for evaluating and implementing conservation breeding that would be applicable to other genetically impoverished species. © The American Genetic Association. 2015.

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

NASA Astrophysics Data System (ADS)

Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

Stakeholder perspectives on decision-analytic modeling frameworks to assess genetic services policy.

PubMed

Guzauskas, Gregory F; Garrison, Louis P; Stock, Jacquie; Au, Sylvia; Doyle, Debra Lochner; Veenstra, David L

2013-01-01

Genetic services policymakers and insurers often make coverage decisions in the absence of complete evidence of clinical utility and under budget constraints. We evaluated genetic services stakeholder opinions on the potential usefulness of decision-analytic modeling to inform coverage decisions, and asked them to identify genetic tests for decision-analytic modeling studies. We presented an overview of decision-analytic modeling to members of the Western States Genetic Services Collaborative Reimbursement Work Group and state Medicaid representatives and conducted directed content analysis and an anonymous survey to gauge their attitudes toward decision-analytic modeling. Participants also identified and prioritized genetic services for prospective decision-analytic evaluation. Participants expressed dissatisfaction with current processes for evaluating insurance coverage of genetic services. Some participants expressed uncertainty about their comprehension of decision-analytic modeling techniques. All stakeholders reported openness to using decision-analytic modeling for genetic services assessments. Participants were most interested in application of decision-analytic concepts to multiple-disorder testing platforms, such as next-generation sequencing and chromosomal microarray. Decision-analytic modeling approaches may provide a useful decision tool to genetic services stakeholders and Medicaid decision-makers.

Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient.

PubMed

Masuda, Y; Misztal, I; Legarra, A; Tsuruta, S; Lourenco, D A L; Fragomeni, B O; Aguilar, I

2017-01-01

This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix () including genotyped animals and their ancestors. The elements of were rapidly calculated with the Henderson's rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix-vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.

Invited review: Genetics and claw health: Opportunities to enhance claw health by genetic selection.

PubMed

Heringstad, B; Egger-Danner, C; Charfeddine, N; Pryce, J E; Stock, K F; Kofler, J; Sogstad, A M; Holzhauer, M; Fiedler, A; Müller, K; Nielsen, P; Thomas, G; Gengler, N; de Jong, G; Ødegård, C; Malchiodi, F; Miglior, F; Alsaaod, M; Cole, J B

2018-06-01

Routine recording of claw health status at claw trimming of dairy cattle has been established in several countries, providing valuable data for genetic evaluation. In this review, we examine issues related to genetic evaluation of claw health; discuss data sources, trait definitions, and data validation procedures; and present a review of genetic parameters, possible indicator traits, and status of genetic and genomic evaluations for claw disorders. Different sources of data and traits can be used to describe claw health. Severe cases of claw disorders can be identified by veterinary diagnoses. Data from lameness and locomotion scoring, activity information from sensors, and feet and leg conformation traits are used as auxiliary traits. The most reliable and comprehensive information is data from regular hoof trimming. In genetic evaluation, claw disorders are usually defined as binary traits, based on whether or not the claw disorder was present (recorded) at least once during a defined time period. The traits can be specific disorders, composite traits, or overall claw health. Data validation and editing criteria are needed to ensure reliable data at the trimmer, herd, animal, and record levels. Different strategies have been chosen, reflecting differences in herd sizes, data structures, management practices, and recording systems among countries. Heritabilities of the most commonly analyzed claw disorders based on data from routine claw trimming were generally low, with ranges of linear model estimates from 0.01 to 0.14, and threshold model estimates from 0.06 to 0.39. Estimated genetic correlations among claw disorders varied from -0.40 to 0.98. The strongest genetic correlations were found among sole hemorrhage (SH), sole ulcer (SU), and white line disease (WL), and between digital/interdigital dermatitis (DD/ID) and heel horn erosion (HHE). Genetic correlations between DD/ID and HHE on the one hand and SH, SU, or WL on the other hand were, in most cases, low. Although some of the studies were based on relatively few records and the estimated genetic parameters had large standard errors, there was, with some exceptions, consistency among studies. Various studies evaluate the potential of various data soureces for use in breeding. The use of hoof trimming data is recommended for maximization of genetic gain, although auxiliary traits, such as locomotion score and some conformation traits, may be valuable for increasing the reliability of genetic evaluations. Routine genetic evaluation of direct claw health has been implemented in the Netherlands (2010); Denmark, Finland, and Sweden (joint Nordic evaluation; 2011); and Norway (2014), and other countries plan to implement evaluations in the near future. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Longitudinal Effects on Early Adolescent Language: A Twin Study

ERIC Educational Resources Information Center

Harlarr, Nicole; De Thorne, Laura Segebart; Smith, Jamie Mahurin; Betancourt, Mariana Aparicio; Petrill, Stephen A.

2016-01-01

Purpose: We evaluated genetic and environmental contributions to individual differences in language skills during early adolescence, measured by both language sampling and standardized tests, and examined the extent to which these genetic and environmental effects are stable across time. Purpose: We evaluated genetic and environmental…

A Road Map for 21st Century Genetic Restoration: Gene Pool Enrichment of the Black-Footed Ferret

PubMed Central

Ryder, Oliver A.; Santymire, Rachel M.; Engelhardt, John F.; Novak, Ben J.

2015-01-01

Interspecies somatic cell nuclear transfer (iSCNT) could benefit recovery programs of critically endangered species but must be weighed with the risks of failure. To weigh the risks and benefits, a decision-making process that evaluates progress is needed. Experiments that evaluate the efficiency and efficacy of blastocyst, fetal, and post-parturition development are necessary to determine the success or failure or species-specific iSCNT programs. Here, we use the black-footed ferret (Mustela nigripes) as a case study for evaluating this emerging biomedical technology as a tool for genetic restoration. The black-footed ferret has depleted genetic variation yet genome resource banks contain genetic material of individuals not currently represented in the extant lineage. Thus, genetic restoration of the species is in theory possible and could help reduce the persistent erosion of genetic diversity from drift. Extensive genetic, genomic, and reproductive science tools have previously been developed in black-footed ferrets and would aid in the process of developing an iSCNT protocol for this species. Nonetheless, developing reproductive cloning will require years of experiments and a coordinated effort among recovery partners. The information gained from a well-planned research effort with the goal of genetic restoration via reproductive cloning could establish a 21st century model for evaluating and implementing conservation breeding that would be applicable to other genetically impoverished species. PMID:26304983

Genetically altered mice for evaluation of mode-of-action (MOA)

EPA Science Inventory

Genetically altered mice for evaluation of mode-of-action (MOA). Barbara D. Abbott, Cynthia J. Wolf, Kaberi P. Das, Christopher S. Lau. (Presented by B. Abbott). This presentation provides an example of the use of genetically modified mice to determine the mode-of-action of r...

Clinical review of genetic epileptic encephalopathies

PubMed Central

Noh, Grace J.; Asher, Y. Jane Tavyev; Graham, John M.

2012-01-01

Seizures are a frequently encountered finding in patients seen for clinical genetics evaluations. The differential diagnosis for the cause of seizures is quite diverse and complex, and more than half of all epilepsies have been attributed to a genetic cause. Given the complexity of such evaluations, we highlight the more common causes of genetic epileptic encephalopathies and emphasize the usefulness of recent technological advances. The purpose of this review is to serve as a practical guide for clinical geneticists in the evaluation and counseling of patients with genetic epileptic encephalopathies. Common syndromes will be discussed, in addition to specific seizure phenotypes, many of which are refractory to anti-epileptic agents. Divided by etiology, we overview the more common causes of infantile epileptic encephalopathies, channelopathies, syndromic, metabolic, and chromosomal entities. For each condition, we will outline the diagnostic evaluation and discuss effective treatment strategies that should be considered. PMID:22342633

Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment.

PubMed

da Fonseca Neto, João Viana; Abreu, Ivanildo Silva; da Silva, Fábio Nogueira

2010-04-01

Toward the synthesis of state-space controllers, a neural-genetic model based on the linear quadratic regulator design for the eigenstructure assignment of multivariable dynamic systems is presented. The neural-genetic model represents a fusion of a genetic algorithm and a recurrent neural network (RNN) to perform the selection of the weighting matrices and the algebraic Riccati equation solution, respectively. A fourth-order electric circuit model is used to evaluate the convergence of the computational intelligence paradigms and the control design method performance. The genetic search convergence evaluation is performed in terms of the fitness function statistics and the RNN convergence, which is evaluated by landscapes of the energy and norm, as a function of the parameter deviations. The control problem solution is evaluated in the time and frequency domains by the impulse response, singular values, and modal analysis.

Genetic Influences on Learning Disabilties I: Clinical Genetics.

ERIC Educational Resources Information Center

Smith, Shelley D.; Pennington, Bruce F.

1983-01-01

A discussion of basic genetic principles is followed by a review of selected genetic syndromes involving learning disabilites (such as Noonan Syndrome, Neurofibromatosis, Pheuylketonuria, and cleft lip and palate). Guidelines for securing a genetic evaluation are given. (CL)

Evaluation of genetically-improved (glandless) and genetically-modified low-gossypol cottonseed meal as alternative protein sources in the diet of juvenile southern flounder Paralichthys lethostigma reared in a recirculating

USDA-ARS?s Scientific Manuscript database

Cottonseed meal (CSM) proteins from genetically-improved (glandless) seed (GI-CSM, 52.1% crude protein, CP), genetically-modified low-gossypol seed (GMO-CSM, 56.0% CP) and from an untreated regular (glanded) seed (R-CSM 49.9% CP) were evaluated to replace fish meal (FM) protein (59.5% CP) in juvenil...

Genetic and phenotypic correlations of quantitative traits in two long-term randomly mated soybean populations

USDA-ARS?s Scientific Manuscript database

The genetic effects of long term random mating and natural selection aided by genetic male sterility (gms) were evaluated in two soybean [Glycine max (L.) Merr.] populations designated: RSII and RSIII. These populations were evaluated in the field at three locations each with two replications. Genot...

The current state of genetic counseling and newborn screening: an interview with Megan Tucker

PubMed Central

Tucker, Megan

2017-01-01

Megan Tucker talks to Francesca Lake, Managing Editor: A certified genetic counselor for over 10 years, Megan is currently the director of the Indiana State University Genetic Counseling Graduate Program and the Genetic Counseling Clinic at Union Hospital (Terre Haute, IN, USA). She began her career split between the Center for Prenatal Diagnosis and the Medical Genetics and Neurodevelopmental Center at St Vincent Hospital (Indianapolis, IN, USA). During this time she was instrumental in both the development of the statewide Perinatal Loss Evaluation Program and a hospital protocol to ensure collection of cord blood to allow time to effectively genetically evaluate babies. Her current clinical focus is in cancer and psychiatric genetic counseling. PMID:28883988

Impact of genetic counseling and Connexin-26 and Connexin-30 testing on deaf identity and comprehension of genetic test results in a sample of deaf adults: a prospective, longitudinal study.

PubMed

Palmer, Christina G S; Boudreault, Patrick; Baldwin, Erin E; Sinsheimer, Janet S

2014-01-01

Using a prospective, longitudinal study design, this paper addresses the impact of genetic counseling and testing for deafness on deaf adults and the Deaf community. This study specifically evaluated the effect of genetic counseling and Connexin-26 and Connexin-30 genetic test results on participants' deaf identity and understanding of their genetic test results. Connexin-26 and Connexin-30 genetic testing was offered to participants in the context of linguistically and culturally appropriate genetic counseling. Questionnaire data collected from 209 deaf adults at four time points (baseline, immediately following pre-test genetic counseling, 1-month following genetic test result disclosure, and 6-months after result disclosure) were analyzed. Four deaf identity orientations (hearing, marginal, immersion, bicultural) were evaluated using subscales of the Deaf Identity Development Scale-Revised. We found evidence that participants understood their specific genetic test results following genetic counseling, but found no evidence of change in deaf identity based on genetic counseling or their genetic test results. This study demonstrated that culturally and linguistically appropriate genetic counseling can improve deaf clients' understanding of genetic test results, and the formation of deaf identity was not directly related to genetic counseling or Connexin-26 and Connexin-30 genetic test results.

Initial clinical validation of Health Heritage, a patient-facing tool for personal and family history collection and cancer risk assessment.

PubMed

Baumgart, Leigh A; Postula, Kristen J Vogel; Knaus, William A

2016-04-01

Personal and family health histories remain important independent risk factors for cancer; however they are currently not being well collected or used effectively. Health Heritage was designed to address this need. The purpose of this study was to validate the ability of Health Heritage to identify patients appropriate for further genetic evaluation and to accurately stratify cancer risk. A retrospective chart review was conducted on 100 random patients seen at an adult genetics clinic presenting with concern for an inherited predisposition to cancer. Relevant personal and family history obtained from the patients' medical records was entered into Health Heritage. Recommendations by Health Heritage were compared to national guidelines of eligibility for genetic evaluation. Agreement between Health Heritage referral for genetic evaluation and guideline eligibility for genetic evaluation was 97% (sensitivity 98% and specificity 88%). Risk stratification for cancer was also compared between Health Heritage and those documented by a geneticist. For patients at increased risk for breast, ovarian, or colorectal cancer as determined by the geneticist, risk stratification by Health Heritage agreed 90, 93, and 75%, respectively. Discordances in risk stratification were attributed to both complex situations better handled by the geneticist and Health Heritage's adherence to incorporating all information into its algorithms. Health Heritage is a clinically valid tool to identify patients appropriate for further genetic evaluation and to encourage them to confirm the assessment and management recommendations with cancer genetic experts. Health Heritage also provides an estimate of cancer risk that is complementary to a genetics team.

Making Sense of Your Genes: A Guide to Genetic Counseling

MedlinePlus

... to think about genetic counseling and perhaps genetic testing. A cancer genetic counselor will evaluate your family health history and talk about risks for inherited cancer, as well as screening and ...

Genetic diversity among 16 genotypes of Coffea arabica in the Brazilian cerrado.

PubMed

Machado, C M S; Pimentel, N S; Golynsk, A; Ferreira, A; Vieira, H D; Partelli, F L

2017-09-21

For the selection of coffee plants that have favorable characteristics, it is necessary to evaluate variables related to production. Knowledge of the genetic divergence of arabica coffee is of extreme importance, as this knowledge can be associated with plant breeding programs in order to combine genetic divergence with good productive performance. The objective of this study was to evaluate the genetic divergence among 16 genotypes of Coffea arabica with the purpose of identifying the most dissimilar genotypes for the establishment of breeding programs and adaptation to the Brazilian cerrado. The genetic divergence was evaluated using multivariate procedures, the analysis of the average grouping unweighted pair group method with arithmetic mean (UPGMA) and main components in 2013 and 2014. Eight characters were evaluated in an experiment conducted in Morrinhos, Goiás. The presence of genetic divergence among the 16 C. arabica genotypes under cerrado conditions was recorded. The formation of UPGMA groups for the evaluated characteristics was pertinent due to the number of genotypes. The first three major components accounted for 81.77% of the total variance. The genotype H-419-3-4-4-13(C-241) of low size was the most divergent, followed by Catucaí 2 SL and Catiguá MG2, according to the main components.

Evaluation of the innate immune response of Angus heifers with genetic marker variation for intramuscular fat deposition following a lipopolysaccharide challenge

USDA-ARS?s Scientific Manuscript database

This study evaluated the effect of genetic selection for markers related to marbling deposition in Angus heifers on the immune response following a lipopolysaccharide (LPS) challenge. Fall-born heifers (n = 19; ~7 months of age, 274 +/- 24 kg) with genetic variation for marbling were utilized inclu...

Evaluating Genetic Counseling for Family Members of Individuals With Schizophrenia in the Molecular Age

PubMed Central

Bassett, Anne S.

2014-01-01

Background: Myths and concerns about the extent and meaning of genetic risk in schizophrenia may contribute to significant stigma and burden for families. Genetic counseling has long been proposed to be a potentially informative and therapeutic intervention for schizophrenia. Surprisingly, however, available data are limited. We evaluated a contemporary genetic counseling protocol for use in a community mental health-care setting by non–genetics professionals. Methods: We used a pre-post study design with longitudinal follow-up to assess the impact of genetic counseling on family members of individuals with schizophrenia, where molecular testing had revealed no known clinically relevant genetic risk variant. We assessed the outcome using multiple measures, including standard items and scales used to evaluate genetic counseling for other complex diseases. Results: Of the 122 family members approached, 78 (63.9%) actively expressed an interest in the study. Participants (n = 52) on average overestimated the risk of familial recurrence at baseline, and demonstrated a significant improvement in this estimate postintervention (P < .0001). This change was associated with an enduring decrease in concern about recurrence (P = .0003). Significant and lasting benefits were observed in other key areas, including increased knowledge (P < .0001) and a decreased sense of stigma (P = .0047). Endorsement of the need for genetic counseling was high (96.1%). Conclusions: These results provide initial evidence of the efficacy of schizophrenia genetic counseling for families, even in the absence of individually relevant genetic test results or professional genetics services. The findings support the integration of contemporary genetic counseling for families into the general management of schizophrenia in the community. PMID:23104866

Poa secunda local collections and commercial releases: A genotypic evaluation

PubMed Central

Shaw, Alanna N.; Mummey, Daniel L.

2017-01-01

The genetics of native plants influence the success of ecological restoration, yet genetic variability of local seed collections and commercial seed releases remains unclear for most taxa. Poa secunda, a common native grass species in Intermountain West grasslands and a frequent component of restoration seed mixes, is one such species. Here, we evaluate the genetic variation of local Poa secunda collections in the context of wild populations and commercial seed releases. We evaluated AFLP markers for seven Poa secunda collections made over a 4000-hectare area and four commercial releases (High Plains, MT-1, Opportunity, and Sherman). We compare the genetic distance and distribution of genetic variation within and between local collections and commercial releases. The extent and patterns of genetic variation in our local collections indicate subtle site differences with most variation occurring within rather than between collections. Identical genetic matches were usually, but not always, found within 5 m2 collection sites. Our results suggest that the genetic variation in two Poa secunda releases (High Plains and MT-1) is similar to our local collections. Our results affirm that guidelines for Poa secunda seed collection should follow recommendations for selfing species, by collecting from many sites over large individual sites. PMID:28369130

Poa secunda local collections and commercial releases: A genotypic evaluation.

PubMed

Shaw, Alanna N; Mummey, Daniel L

2017-01-01

The genetics of native plants influence the success of ecological restoration, yet genetic variability of local seed collections and commercial seed releases remains unclear for most taxa. Poa secunda, a common native grass species in Intermountain West grasslands and a frequent component of restoration seed mixes, is one such species. Here, we evaluate the genetic variation of local Poa secunda collections in the context of wild populations and commercial seed releases. We evaluated AFLP markers for seven Poa secunda collections made over a 4000-hectare area and four commercial releases (High Plains, MT-1, Opportunity, and Sherman). We compare the genetic distance and distribution of genetic variation within and between local collections and commercial releases. The extent and patterns of genetic variation in our local collections indicate subtle site differences with most variation occurring within rather than between collections. Identical genetic matches were usually, but not always, found within 5 m2 collection sites. Our results suggest that the genetic variation in two Poa secunda releases (High Plains and MT-1) is similar to our local collections. Our results affirm that guidelines for Poa secunda seed collection should follow recommendations for selfing species, by collecting from many sites over large individual sites.

Evaluating a hybrid web-based basic genetics course for health professionals.

PubMed

Wallen, Gwenyth R; Cusack, Georgie; Parada, Suzan; Miller-Davis, Claiborne; Cartledge, Tannia; Yates, Jan

2011-08-01

Health professionals, particularly nurses, continue to struggle with the expanding role of genetics information in the care of their patients. This paper describes an evaluation study of the effectiveness of a hybrid basic genetics course for healthcare professionals combining web-based learning with traditional face-to-face instructional techniques. A multidisciplinary group from the National Institutes of Health (NIH) created "Basic Genetics Education for Healthcare Providers" (BGEHCP). This program combined 7 web-based self-education modules with monthly traditional face-to-face lectures by genetics experts. The course was pilot tested by 186 healthcare providers from various disciplines with 69% (n=129) of the class registrants enrolling in a pre-post evaluation trial. Outcome measures included critical thinking knowledge items and a Web-based Learning Environment Inventory (WEBLEI). Results indicated a significant (p<0.001) change in knowledge scores. WEBLEI scores indicated program effectiveness particularly in the area of convenience, access and the course structure and design. Although significant increases in overall knowledge scores were achieved, scores in content areas surrounding genetic risk identification and ethical issues regarding genetic testing reflected continued gaps in knowledge. Web-based genetics education may help overcome genetics knowledge deficits by providing access for health professionals with diverse schedules in a variety of national and international settings. Published by Elsevier Ltd.

Genetic progress in homogeneous regions of wheat cultivation in Rio Grande do Sul State, Brazil.

PubMed

Follmann, D N; Cargnelutti Filho, A; Lúcio, A D; de Souza, V Q; Caraffa, M; Wartha, C A

2017-03-30

The State of Rio Grande do Sul (RS) stands out as the largest wheat producer in Brazil. Wheat is the most emphasized winter cereal in RS, attracting public and private investments directed to wheat genetic breeding. The study of genetic progress should be performed routinely at breeding programs to study the behavior of cultivars developed for homogeneous regions of cultivation. The objectives of this study were: 1) to evaluate the genetic progress of wheat grain yield in RS; 2) to evaluate the influence of cultivar competition trial stratification in homogeneous regions of cultivation on the study of genetic progress. Grain yield data of 122 wheat cultivars evaluated in 137 trials arranged in randomized block design with three or four replications were used. Field trials were carried out in 23 locations in RS divided into two homogeneous regions during the period from 2002 to 2013. Genetic progress for RS and homogeneous regions was studied utilizing the method proposed by Vencovsky. Annual genetic progress for wheat grain yield during the period of 12 years in the State of RS was 2.86%, oscillating between homogeneous regions of cultivation. The difference of annual genetic progress in region 1 (1.82%) in relation to region 2 (4.38%) justifies the study of genetic progress by homogeneous regions of cultivation.

Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis

DTIC Science & Technology

2015-10-01

AWARD NUMBER: W81XWH-10-1-0469 TITLE: Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis...31Jul2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER "Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis." 5b...ABSTRACT Dystrophic or non-dystrophic forms of scoliosis are skeletal manifestations of Neurofibromatosis type 1 (NF1). Dystrophic scoliosis has a more

Media Exposure and Genetic Literacy Skills to Evaluate Angelina Jolie's Decision for Prophylactic Mastectomy.

PubMed

Abrams, Leah R; Koehly, Laura M; Hooker, Gillian W; Paquin, Ryan S; Capella, Joseph N; McBride, Colleen M

2016-01-01

To examine public preparedness to evaluate and respond to Angelina Jolie's well-publicized decision to have a prophylactic mastectomy. A consumer panel (n = 1,008) completed an online survey in November 2013, reporting exposure to Jolie's story, confidence applying genomic knowledge to evaluate her decision, and ability to interpret provided genetic risk information (genetic literacy skills). Linear and logistic regressions tested mediating/moderating models of these factors in association with opinions regarding mastectomies. Confidence with genomics was associated with increased genetic literacy skills and increased media exposure, with a significant interaction between the two. Confidence was also associated with favoring mastectomies for women with BRCA mutations, mediating the relationship with media exposure. Respondents were more likely to form opinions about mastectomies if they had high genetic literacy skills. These findings suggest that having higher genetic literacy skills may increase the public's ability to form opinions about clinical applications of genomic discovery. However, repeated media exposure to high-profile stories may artificially inflate confidence among those with low genetic literacy. © 2016 S. Karger AG, Basel.

Genetics educational needs in China: physicians' experience and knowledge of genetic testing.

PubMed

Li, Jing; Xu, Tengda; Yashar, Beverly M

2015-09-01

The aims of this study were to explore the relationship between physicians' knowledge and utilization of genetic testing and to explore genetics educational needs in China. An anonymous survey about experience, attitudes, and knowledge of genetic testing was conducted among physicians affiliated with Peking Union Medical College Hospital during their annual health evaluation. A personal genetics knowledge score was developed and predictors of personal genetics knowledge score were evaluated. Sixty-four physicians (33% male) completed the survey. Fifty-eight percent of them had used genetic testing in their clinical practice. Using a 4-point scale, mean knowledge scores of six common genetic testing techniques ranged from 1.7 ± 0.9 to 2.4 ± 1.0, and the average personal genetics knowledge score was 2.1 ± 0.8. In regression analysis, significant predictors of higher personal genetics knowledge score were ordering of genetic testing, utilization of pedigrees, higher medical degree, and recent genetics training (P < 0.05). Sixty-six percent of physicians indicated a desire for specialized genetic services, and 84% reported a desire for additional genetics education. This study demonstrated a sizable gap between Chinese physicians' knowledge and utilization of genetic testing. Participants had high self-perceived genetics educational needs. Development of genetics educational platforms is both warranted and desired in China.Genet Med 17 9, 757-760.

Evolving hard problems: Generating human genetics datasets with a complex etiology.

PubMed

Himmelstein, Daniel S; Greene, Casey S; Moore, Jason H

2011-07-07

A goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models. Here we develop and evaluate a model free evolution strategy to generate datasets which display a complex relationship between individual genotype and disease susceptibility. We show that this model free approach is capable of generating a diverse array of datasets with distinct gene-disease relationships for an arbitrary interaction order and sample size. We specifically generate eight-hundred Pareto fronts; one for each independent run of our algorithm. In each run the predictiveness of single genetic variation and pairs of genetic variants have been minimized, while the predictiveness of third, fourth, or fifth-order combinations is maximized. Two hundred runs of the algorithm are further dedicated to creating datasets with predictive four or five order interactions and minimized lower-level effects. This method and the resulting datasets will allow the capabilities of novel methods to be tested without pre-specified genetic models. This allows researchers to evaluate which methods will succeed on human genetics problems where the model is not known in advance. We further make freely available to the community the entire Pareto-optimal front of datasets from each run so that novel methods may be rigorously evaluated. These 76,600 datasets are available from http://discovery.dartmouth.edu/model_free_data/.

Sensitivity to Peer Evaluation and Its Genetic and Environmental Determinants: Findings from a Population-Based Twin Study.

PubMed

Klippel, Annelie; Reininghaus, Ulrich; Viechtbauer, Wolfgang; Decoster, Jeroen; Delespaul, Philippe; Derom, Cathérine; de Hert, Marc; Jacobs, Nele; Menne-Lothmann, Claudia; Rutten, Bart; Thiery, Evert; van Os, Jim; van Winkel, Ruud; Myin-Germeys, Inez; Wichers, Marieke

2018-02-23

Adolescents and young adults are highly focused on peer evaluation, but little is known about sources of their differential sensitivity. We examined to what extent sensitivity to peer evaluation is influenced by interacting environmental and genetic factors. A sample of 354 healthy adolescent twin pairs (n = 708) took part in a structured, laboratory task in which they were exposed to peer evaluation. The proportion of the variance in sensitivity to peer evaluation due to genetic and environmental factors was estimated, as was the association with specific a priori environmental risk factors. Differences in sensitivity to peer evaluation between adolescents were explained mainly by non-shared environmental influences. The results on shared environmental influences were not conclusive. No impact of latent genetic factors or gene-environment interactions was found. Adolescents with lower self-rated positions on the social ladder or who reported to have been bullied more severely showed significantly stronger responses to peer evaluation. Not genes, but subjective social status and past experience of being bullied seem to impact sensitivity to peer evaluation. This suggests that altered response to peer evaluation is the outcome of cumulative sensitization to social interactions.

Predictive genetic testing for complex diseases: a public health perspective

PubMed Central

Marzuillo, C.; De Vito, C.; D’Andrea, E.; Rosso, A.

2014-01-01

From a public health perspective, systematic, evidence-based technology assessments and economic evaluations are needed to guide the incorporation of genomics into clinical and public health practice. However, scientific evidence on the effectiveness of predictive genetic tests is difficult to obtain. This review first highlights the similarities and differences between traditional screening tests and predictive genetic testing for complex diseases and goes on to describe frameworks for the evaluation of genetic testing that have been developed in recent years providing some evidence that currently genetic tests are not used in an appropriate way. Nevertheless, evidence-based recommendations are already available for some genomic applications that can reduce morbidity and mortality and many more are expected to emerge over the next decade. The time is now ripe for the introduction of a range of genetic tests into healthcare practice, but this will require the development of specific health policies, proper public health evaluations, organizational changes within the healthcare systems, capacity building among the healthcare workforce and the education of the public. PMID:24049051

Impact of Genetic Counseling and Connexin-26 and Connexin-30 Testing on Deaf Identity and Comprehension of Genetic Test Results in a Sample of Deaf Adults: A Prospective, Longitudinal Study

PubMed Central

Palmer, Christina G. S.; Boudreault, Patrick; Baldwin, Erin E.; Sinsheimer, Janet S.

2014-01-01

Using a prospective, longitudinal study design, this paper addresses the impact of genetic counseling and testing for deafness on deaf adults and the Deaf community. This study specifically evaluated the effect of genetic counseling and Connexin-26 and Connexin-30 genetic test results on participants' deaf identity and understanding of their genetic test results. Connexin-26 and Connexin-30 genetic testing was offered to participants in the context of linguistically and culturally appropriate genetic counseling. Questionnaire data collected from 209 deaf adults at four time points (baseline, immediately following pre-test genetic counseling, 1-month following genetic test result disclosure, and 6-months after result disclosure) were analyzed. Four deaf identity orientations (hearing, marginal, immersion, bicultural) were evaluated using subscales of the Deaf Identity Development Scale-Revised. We found evidence that participants understood their specific genetic test results following genetic counseling, but found no evidence of change in deaf identity based on genetic counseling or their genetic test results. This study demonstrated that culturally and linguistically appropriate genetic counseling can improve deaf clients' understanding of genetic test results, and the formation of deaf identity was not directly related to genetic counseling or Connexin-26 and Connexin-30 genetic test results. PMID:25375116

High burden of genetic conditions diagnosed in a cardiac neurodevelopmental clinic.

PubMed

Goldenberg, Paula C; Adler, Betsy J; Parrott, Ashley; Anixt, Julia; Mason, Karen; Phillips, Jannel; Cooper, David S; Ware, Stephanie M; Marino, Bradley S

2017-04-01

There is a known high prevalence of genetic and clinical syndrome diagnoses in the paediatric cardiac population. These disorders often have multisystem effects, which may have an important impact on neurodevelopmental outcomes. Taken together, these facts suggest that patients and families may benefit from consultation by genetic specialists in a cardiac neurodevelopmental clinic. This study assessed the burden of genetic disorders and utility of genetics evaluation in a cardiac neurodevelopmental clinic. A retrospective chart review was conducted of patients evaluated in a cardiac neurodevelopmental clinic from 6 December, 2011 to 16 April, 2013. All patients were seen by a cardiovascular geneticist with genetic counselling support. A total of 214 patients were included in this study; 64 of these patients had a pre-existing genetic or syndromic diagnosis. Following genetics evaluation, an additional 19 were given a new clinical or laboratory-confirmed genetic diagnosis including environmental such as teratogenic exposures, malformation associations, chromosomal disorders, and single-gene disorders. Genetic testing was recommended for 112 patients; radiological imaging to screen for congenital anomalies for 17 patients; subspecialist medical referrals for 73 patients; and non-genetic clinical laboratory testing for 14 patients. Syndrome-specific guidelines were available and followed for 25 patients with known diagnosis. American Academy of Pediatrics Red Book asplenia guideline recommendations were given for five heterotaxy patients, and family-based cardiac screening was recommended for 23 families affected by left ventricular outflow tract obstruction. Genetics involvement in a cardiac neurodevelopmental clinic is helpful in identifying new unifying diagnoses and providing syndrome-specific care, which may impact the patient's overall health status and neurodevelopmental outcome.

Role of Genetic Testing for Inherited Prostate Cancer Risk: Philadelphia Prostate Cancer Consensus Conference 2017.

PubMed

Giri, Veda N; Knudsen, Karen E; Kelly, William K; Abida, Wassim; Andriole, Gerald L; Bangma, Chris H; Bekelman, Justin E; Benson, Mitchell C; Blanco, Amie; Burnett, Arthur; Catalona, William J; Cooney, Kathleen A; Cooperberg, Matthew; Crawford, David E; Den, Robert B; Dicker, Adam P; Eggener, Scott; Fleshner, Neil; Freedman, Matthew L; Hamdy, Freddie C; Hoffman-Censits, Jean; Hurwitz, Mark D; Hyatt, Colette; Isaacs, William B; Kane, Christopher J; Kantoff, Philip; Karnes, R Jeffrey; Karsh, Lawrence I; Klein, Eric A; Lin, Daniel W; Loughlin, Kevin R; Lu-Yao, Grace; Malkowicz, S Bruce; Mann, Mark J; Mark, James R; McCue, Peter A; Miner, Martin M; Morgan, Todd; Moul, Judd W; Myers, Ronald E; Nielsen, Sarah M; Obeid, Elias; Pavlovich, Christian P; Peiper, Stephen C; Penson, David F; Petrylak, Daniel; Pettaway, Curtis A; Pilarski, Robert; Pinto, Peter A; Poage, Wendy; Raj, Ganesh V; Rebbeck, Timothy R; Robson, Mark E; Rosenberg, Matt T; Sandler, Howard; Sartor, Oliver; Schaeffer, Edward; Schwartz, Gordon F; Shahin, Mark S; Shore, Neal D; Shuch, Brian; Soule, Howard R; Tomlins, Scott A; Trabulsi, Edouard J; Uzzo, Robert; Vander Griend, Donald J; Walsh, Patrick C; Weil, Carol J; Wender, Richard; Gomella, Leonard G

2018-02-01

Purpose Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-driven working framework for comprehensive genetic evaluation of inherited PCA in the multigene testing era addressing genetic counseling, testing, and genetically informed management. Methods An expert consensus conference was convened including key stakeholders to address genetic counseling and testing, PCA screening, and management informed by evidence review. Results Consensus was strong that patients should engage in shared decision making for genetic testing. There was strong consensus to test HOXB13 for suspected hereditary PCA, BRCA1/2 for suspected hereditary breast and ovarian cancer, and DNA mismatch repair genes for suspected Lynch syndrome. There was strong consensus to factor BRCA2 mutations into PCA screening discussions. BRCA2 achieved moderate consensus for factoring into early-stage management discussion, with stronger consensus in high-risk/advanced and metastatic setting. Agreement was moderate to test all men with metastatic castration-resistant PCA, regardless of family history, with stronger agreement to test BRCA1/2 and moderate agreement to test ATM to inform prognosis and targeted therapy. Conclusion To our knowledge, this is the first comprehensive, multidisciplinary consensus statement to address a genetic evaluation framework for inherited PCA in the multigene testing era. Future research should focus on developing a working definition of familial PCA for clinical genetic testing, expanding understanding of genetic contribution to aggressive PCA, exploring clinical use of genetic testing for PCA management, genetic testing of African American males, and addressing the value framework of genetic evaluation and testing men at risk for PCA-a clinically heterogeneous disease.

Genetics Evaluation Guidelines for the Etiologic Diagnosis of Congenital Hearing Loss

PubMed Central

2002-01-01

The advent of hearing screening in newborns in many states has led to an increase in the use of genetic testing and related genetic services in the follow-up of infants with hearing loss. A significant proportion of those with congenital hearing loss have genetic etiologies underlying their hearing loss. To ensure that those identified with congenital hearing loss receive the genetic services appropriate to their conditions, the Maternal and Child Health Bureau of the Health Resources and Services Administration funded the American College of Medical Genetics to convene an expert panel to develop guidelines for the genetic evaluation of congential hearing loss. After a brief overview of the current knowledge of hearing loss, newborn screening, and newborn hearing screening, we provide an overview of genetic services and a guideline that describes how best to ensure that patients receive appropriate genetic services. The significant contribution of genetic factors to these conditions combined with the rapid evolution of knowledge about the genetics of these conditions overlaid with the inherently multidisciplinary nature of genetic services provides an example of a condition for which a well-integrated multidisciplinary approach to care is clearly needed. PMID:12180152

Genetic algorithm for nuclear data evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arthur, Jennifer Ann

These are slides on genetic algorithm for nuclear data evaluation. The following is covered: initial population, fitness (outer loop), calculate fitness, selection (first part of inner loop), reproduction (second part of inner loop), solution, and examples.

Measuring informed choice in population-based reproductive genetic screening: a systematic review

PubMed Central

Ames, Alice Grace; Metcalfe, Sylvia Ann; Archibald, Alison Dalton; Duncan, Rony Emily; Emery, Jon

2015-01-01

Genetic screening and health-care guidelines recommend that programmes should facilitate informed choice. It is therefore important that accurate measures of informed choice are available to evaluate such programmes. This review synthesises and appraises measures used to evaluate informed choice in population-based genetic screening programmes for reproductive risk. Databases were searched for studies offering genetic screening for the purpose of establishing reproductive risk to an adult population sample, in which aspects of informed choice were measured. Studies were included if, at a minimum, measures of uptake of screening and knowledge were used. Searches identified 1462 citations and 76 studies were reviewed in full text; 34 studies met the inclusion criteria. Over 20 different measures of informed choice were used. Many measures lacked adequate validity and reliability data. This systematic review will inform future evaluation of informed choice in population genetic screening programmes. PMID:24848746

Divergent selection on 63-day body weight in the rabbit: response on growth, carcass and muscle traits

PubMed Central

Larzul, Catherine; Gondret, Florence; Combes, Sylvie; de Rochambeau, Hubert

2005-01-01

The effects of selection for growth rate on weights and qualitative carcass and muscle traits were assessed by comparing two lines selected for live body weight at 63 days of age and a cryopreserved control population raised contemporaneously with generation 5 selected rabbits. The animals were divergently selected for five generations for either a high (H line) or a low (L line) body weight, based on their BLUP breeding value. Heritability (h2) was 0.22 for 63-d body weight (N = 4754). Growth performance and quantitative carcass traits in the C group were intermediate between the H and L lines (N = 390). Perirenal fat proportion (h2 = 0.64) and dressing out percentage (h2 = 0.55) ranked in the order L < H = C (from high to low). The weight and cross-sectional area of the Semitendinosus muscle, and the mean diameter of the constitutive myofibres were reduced in the L line only (N = 140). In the Longissimus muscle (N = 180), the ultimate pH (h2 = 0.16) and the maximum shear force reached in the Warner-Braztler test (h2 = 0.57) were slightly modified by selection. PMID:15588570

A geostatistical approach to data harmonization - Application to radioactivity exposure data

NASA Astrophysics Data System (ADS)

Baume, O.; Skøien, J. O.; Heuvelink, G. B. M.; Pebesma, E. J.; Melles, S. J.

2011-06-01

Environmental issues such as air, groundwater pollution and climate change are frequently studied at spatial scales that cross boundaries between political and administrative regions. It is common for different administrations to employ different data collection methods. If these differences are not taken into account in spatial interpolation procedures then biases may appear and cause unrealistic results. The resulting maps may show misleading patterns and lead to wrong interpretations. Also, errors will propagate when these maps are used as input to environmental process models. In this paper we present and apply a geostatistical model that generalizes the universal kriging model such that it can handle heterogeneous data sources. The associated best linear unbiased estimation and prediction (BLUE and BLUP) equations are presented and it is shown that these lead to harmonized maps from which estimated biases are removed. The methodology is illustrated with an example of country bias removal in a radioactivity exposure assessment for four European countries. The application also addresses multicollinearity problems in data harmonization, which arise when both artificial bias factors and natural drifts are present and cannot easily be distinguished. Solutions for handling multicollinearity are suggested and directions for further investigations proposed.

Sampling scheme on genetic structure of tree species in fragmented tropical dry forest: an evaluation from landscape genetic simulations

Treesearch

Yessica Rico; Marie-Stephanie Samain

2017-01-01

Investigating how genetic variation is distributed across the landscape is fundamental to inform forest conservation and restoration. Detecting spatial genetic discontinuities has value for defining management units, germplasm collection, and target sites for reforestation; however, inappropriate sampling schemes can misidentify patterns of genetic structure....

Genetic evaluation of mastitis liability and recovery through longitudinal analysis of transition probabilities

PubMed Central

2012-01-01

Background Many methods for the genetic analysis of mastitis use a cross-sectional approach, which omits information on, e.g., repeated mastitis cases during lactation, somatic cell count fluctuations, and recovery process. Acknowledging the dynamic behavior of mastitis during lactation and taking into account that there is more than one binary response variable to consider, can enhance the genetic evaluation of mastitis. Methods Genetic evaluation of mastitis was carried out by modeling the dynamic nature of somatic cell count (SCC) within the lactation. The SCC patterns were captured by modeling transition probabilities between assumed states of mastitis and non-mastitis. A widely dispersed SCC pattern generates high transition probabilities between states and vice versa. This method can model transitions to and from states of infection simultaneously, i.e. both the mastitis liability and the recovery process are considered. A multilevel discrete time survival model was applied to estimate breeding values on simulated data with different dataset sizes, mastitis frequencies, and genetic correlations. Results Correlations between estimated and simulated breeding values showed that the estimated accuracies for mastitis liability were similar to those from previously tested methods that used data of confirmed mastitis cases, while our results were based on SCC as an indicator of mastitis. In addition, unlike the other methods, our method also generates breeding values for the recovery process. Conclusions The developed method provides an effective tool for the genetic evaluation of mastitis when considering the whole disease course and will contribute to improving the genetic evaluation of udder health. PMID:22475575

Genetic testing in the European Union: does economic evaluation matter?

PubMed

Antoñanzas, Fernando; Rodríguez-Ibeas, R; Hutter, M F; Lorente, R; Juárez, C; Pinillos, M

2012-10-01

We review the published economic evaluation studies applied to genetic technologies in the EU to know the main diseases addressed by these studies, the ways the studies were conducted and to assess the efficiency of these new technologies. The final aim of this review was to understand the possibilities of the economic evaluations performed up to date as a tool to contribute to decision making in this area. We have reviewed a set of articles found in several databases until March 2010. Literature searches were made in the following databases: PubMed; Euronheed; Centre for Reviews and Dissemination of the University of York-Health Technology Assessment, Database of Abstracts of Reviews of Effects, NHS Economic Evaluation Database; and Scopus. The algorithm was "(screening or diagnosis) and genetic and (cost or economic) and (country EU27)". We included studies if they met the following criteria: (1) a genetic technology was analysed; (2) human DNA must be tested for; (3) the analysis was a real economic evaluation or a cost study, and (4) the articles had to be related to any EU Member State. We initially found 3,559 papers on genetic testing but only 92 articles of economic analysis referred to a wide range of genetic diseases matched the inclusion criteria. The most studied diseases were as follows: cystic fibrosis (12), breast and ovarian cancer (8), hereditary hemochromatosis (6), Down's syndrome (7), colorectal cancer (5), familial hypercholesterolaemia (5), prostate cancer (4), and thrombophilia (4). Genetic tests were mostly used for screening purposes, and cost-effectiveness analysis is the most common type of economic study. The analysed gene technologies are deemed to be efficient for some specific population groups and screening algorithms according to the values of their cost-effectiveness ratios that were below the commonly accepted threshold of 30,000€. Economic evaluation of genetic technologies matters but the number of published studies is still rather low as to be widely used for most of the decisions in different jurisdictions across the EU. Further, the decision bodies across EU27 are fragmented and the responsibilities are located at different levels of the decision process for what it is difficult to find out whether a given decision on genetic tests was somehow supported by the economic evaluation results.

FINE-SCALE GENETIC DIFFERENTIATION BETWEEN CONTAMINANT-TOLERANT AND CONTAMINANT SENSITIVE FISH POPULATIONS

EPA Science Inventory

Studies have suggested that environmental contaminants can act as selective forces on exposed populations of wildlife species. Chronically exposed populations have shown reduced genetic diversity and/or demonstrated other genetic changes. We evaluated the genetic structure of pop...

Genetic Diversity, Population Structure, and Resistance to Phytophthora capsici of a Worldwide Collection of Eggplant Germplasm

PubMed Central

Naegele, Rachel P.; Boyle, Samantha; Quesada-Ocampo, Lina M.; Hausbeck, Mary K.

2014-01-01

Eggplant (Solanum melongena L.) is an important solanaceous crop with high phenotypic diversity and moderate genotypic diversity. Ninety-nine genotypes of eggplant germplasm (species (S. melongena, S. incanum, S. linnaeanum and S. gilo), landraces and heirloom cultivars) from 32 countries and five continents were evaluated for genetic diversity, population structure, fruit shape, and disease resistance to Phytophthora fruit rot. Fruits from each line were measured for fruit shape and evaluated for resistance to two Phytophthora capsici isolates seven days post inoculation. Only one accession (PI 413784) was completely resistant to both isolates evaluated. Partial resistance to Phytophthora fruit rot was found in accessions from all four eggplant species evaluated in this study. Genetic diversity and population structure were assessed using 22 polymorphic simple sequence repeats (SSRs). The polymorphism information content (PIC) for the population was moderate (0.49) in the population. Genetic analyses using the program STRUCTURE indicated the existence of four genetic clusters within the eggplant collection. Population structure was detected when eggplant lines were grouped by species, continent of origin, country of origin, fruit shape and disease resistance. PMID:24819601

Singapore Cancer Network (SCAN) Guidelines for Referral for Genetic Evaluation of Common Hereditary Cancer Syndromes.

PubMed

2015-10-01

The SCAN cancer genetics workgroup aimed to develop Singapore Cancer Network (SCAN) clinical practice guidelines for referral for genetic evaluation of common hereditary cancer syndromes. The workgroup utilised a modified ADAPTE process to calibrate high quality international evidence-based clinical practice guidelines to our local setting. To formulate referral guidelines for the 3 most commonly encountered hereditary cancer syndromes to guide healthcare providers in Singapore who care for cancer patients and/or their family members, 7, 5, and 3 sets of international guidelines respectively for hereditary breast and ovarian cancer (HBOC) syndrome, Lynch syndrome (LS), and familial adenomatous polyposis (FAP) were evaluated. For each syndrome, the most applicable one was selected, with modifications made such that they would be appropriate to the local context. These adapted guidelines form the SCAN Guidelines 2015 for referral for genetic evaluation of common hereditary cancer syndromes.

Genetic Counseling

MedlinePlus

... Testing Evaluating Genomic Tests Epidemiology Pathogen Genomics Resources Genetic Counseling Recommend on Facebook Tweet Share Compartir In ... informed decisions about testing and treatment. Reasons for Genetic Counseling There are many reasons that people go ...

Genotype by environment interaction effects in genetic evaluation of preweaning gain for Line 1 Hereford cattle from Miles City, Montana

USDA-ARS?s Scientific Manuscript database

That genotype by environment interaction potentially influences genetic evaluation of beef cattle has long been recognized. However, this recognition has largely been ignored in systems for national cattle evaluation. The objective of this investigation was to determine if direct and maternal geneti...

International genetic evaluation of Holstein bulls for overall type traits and body condition score.

PubMed

Battagin, M; Forabosco, F; Jakobsen, J H; Penasa, M; Lawlor, T J; Cassandro, M

2012-08-01

The study documents the procedures used to estimate genetic correlations among countries for overall conformation (OCS), overall udder (OUS), overall feet and legs (OFL), and body condition score (BCS) of Holstein sires. Major differences in traits definition are discussed, in addition to the use of international breeding values (IBV) among countries involved in international genetic evaluations, and similarities among countries through hierarchical clustering. Data were available for populations from 20 countries for OCS and OUS, 18 populations for OFL, and 11 populations for BCS. The IBV for overall traits and BCS were calculated using a multi-trait across-country evaluation model. Distance measures, obtained from genetic correlations, were used as input values in the cluster analysis. Results from surveys sent to countries participating in international genetic evaluation for conformation traits showed that different ways of defining traits are used: the overall traits were either computed from linear or composite traits or defined as general characteristics. For BCS, populations were divided into 2 groups: one scored and evaluated BCS, and one used a best predictor. In general, populations were well connected except for Estonia and French Red Holstein. The average number of common bulls for the overall traits ranged from 19 (OCS and OUS of French Red Holstein) to 514 (OFL of United States), and for BCS from 17 (French Red Holstein) to 413 (the Netherlands). The average genetic correlation (range) across countries was 0.75 (0.35 to 0.95), 0.80 (0.41 to 0.95), and 0.68 (0.12 to 0.89) for OCS, OUS, and OFL, respectively. Genetic correlations among countries that used angularity as best predictor for BCS and countries that scored BCS were negative. The cluster analysis provided a clear picture of the countries distances; differences were due to trait definition, trait composition, and weights in overall traits, genetic ties, and genotype by environment interactions. Harmonization of trait definition and increasing genetic ties could improve genetic correlations across countries and reduce the distances. In each national selection index, all countries, except Estonia and New Zealand, included at least one overall trait, whereas none included BCS. Out of 18 countries, 9 have started genomic evaluation of conformation traits. The first were Canada, France, New Zealand, and United States in 2009, followed by Switzerland, Germany, and the Netherlands in 2010, and Australia and Denmark-Finland-Sweden (joint evaluation) in 2011. Six countries are planning to start soon. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic data and the listing of species under the U.S. Endangered Species Act.

PubMed

Fallon, Sylvia M

2007-10-01

Genetic information is becoming an influential factor in determining whether species, subspecies, and distinct population segments qualify for protection under the U.S. Endangered Species Act. Nevertheless, there are currently no standards or guidelines that define how genetic information should be used by the federal agencies that administer the act. I examined listing decisions made over a 10-year period (February 1996-February 2006) that relied on genetic information. There was wide variation in the genetic data used to inform listing decisions in terms of which genomes (mitochondrial vs. nuclear) were sampled and the number of markers (or genetic techniques) and loci evaluated. In general, whether the federal agencies identified genetic distinctions between putative taxonomic units or populations depended on the type and amount of genetic data. Studies that relied on multiple genetic markers were more likely to detect distinctions, and those organisms were more likely to receive protection than studies that relied on a single genetic marker. Although the results may, in part, reflect the corresponding availability of genetic techniques over the given time frame, the variable use of genetic information for listing decisions has the potential to misguide conservation actions. Future management policy would benefit from guidelines for the critical evaluation of genetic information to list or delist organisms under the Endangered Species Act.

Lessons from 25 years of genetic mapping in onion: where next?

USDA-ARS?s Scientific Manuscript database

Genetic maps are useful tools for both basic research and plant improvement. Close association of genetic markers with genes controlling economically important traits allows for indirect selection, avoiding often time-consuming and expensive phenotypic evaluations. As a result, detailed genetic maps...

Innovations in human genetics education. Incorporation of genetics into a problem-based medical school curriculum.

PubMed Central

Swinford, A E; McKeag, D B

1990-01-01

There has been recent interest in the development of problem-based human genetics curricula in U.S. medical schools. The College of Human Medicine at Michigan State University has had a problem-based curriculum since 1974. The vertical integration of genetics within the problem-based curriculum, called "Track II," has recently been revised. On first inspection, the curriculum appeared to lack a significant genetics component; however, on further analysis it was found that many genetics concepts were covered in the biochemistry, microbiology, pathology, and clinical science components. Both basic science concepts and clinical applications of genetics are covered in the curriculum by providing appropriate references for basic concepts and including inherited conditions within the differential diagnosis in the cases studied. Evaluations consist of a multiple-choice content exam and a modified essay exam based on a clinical case, allowing evaluation of both basic concepts and problem-solving ability. This curriculum prepares students to use genetics in a clinical context in their future careers. PMID:2220816

Provision of Genetic Services for Autism and Its Impact on Spanish Families

ERIC Educational Resources Information Center

Codina-Solà, Marta; Pérez-Jurado, Luis A.; Cuscó, Ivon; Serra-Juhé, Clara

2017-01-01

Although a genetic evaluation can identify the etiology in 15-30% of individuals with autism spectrum disorder, several studies show an underuse of genetic services by affected families. We have explored the access to genetic services and perception of genetics and recurrence risk in parents of autistic children in Spain. Despite the high interest…

Expanding maize genetic resources with predomestication alleles: maize-teosinte introgression populations

USDA-ARS?s Scientific Manuscript database

Teosinte (Zea mays ssp. parviglumis) has greater genetic diversity than maize inbreds and landraces (Z. mays ssp. mays). There are, however, limited genetic resources to efficiently evaluate and tap this diversity. To broaden resources for genetic diversity studies in maize, we developed and evaluat...

Supply of genetic information--amount, format, and frequency.

PubMed

Misztal, I; Lawlor, T J

1999-05-01

The volume and complexity of genetic information is increasing because of new traits and better models. New traits may include reproduction, health, and carcass. More comprehensive models include the test day model in dairy cattle or a growth model in beef cattle. More complex models, which may include nonadditive effects such as inbreeding and dominance, also provide additional information. The amount of information per animal may increase drastically if DNA marker typing becomes routine and quantitative trait loci information is utilized. In many industries, evaluations are run more frequently. They result in faster genetic progress and improved management and marketing opportunities but also in extra costs and information overload. Adopting new technology and making some organizational changes can help realize all the added benefits of the improvements to the genetic evaluation systems at an acceptable cost. Continuous genetic evaluation, in which new records are accepted and breeding values are updated continuously, will relieve time pressures. An online mating system with access to both genetic and marketing information can result in mating recommendations customized for each user. Such a system could utilize inbreeding and dominance information that cannot efficiently be accommodated in the current sire summaries or off-line mating programs. The new systems will require a new organizational approach in which the task of scientists and technicians will not be simply running the evaluations but also providing the research, design, supervision, and maintenance required in the entire system of evaluation, decision making, and distribution.

Early genetic evaluation of open-pollinated Douglas-fir families

Treesearch

Kurt H. Riitters; David A. Perry

1987-01-01

In a test of early genetic evaluation of the growth potential of 14 families of open-pollinated Douglas-fir (Pseudotsuga menziesii) [Mirb.] Franco), measures of growth and phenology of seedligns grown in a coldframe were correlated with height of saplings in evaluation plantations at 9, 12, and 15 years. fifteen-year height was most strongly...

Genetic evaluation of rapid height growth in pot- and nursery-grown Scotch pine

Treesearch

Maurice E., Jr. Demeritt; Henry D. Gerhold; Henry D. Gerhold

1985-01-01

Genetic and environmental components of variance for 2-year pot and nursery heights of offspring from inter- and intraprovenance matings in Scotch pine were studied to determine which provenances and selection methods should be used in an ornamental and Christmas tree improvement program. Nursery evaluation was preferred to pot evaluation because heritability estimates...

Which BRCA genetic testing programs are ready for implementation in health care? A systematic review of economic evaluations.

PubMed

D'Andrea, Elvira; Marzuillo, Carolina; De Vito, Corrado; Di Marco, Marco; Pitini, Erica; Vacchio, Maria Rosaria; Villari, Paolo

2016-12-01

There is considerable evidence regarding the efficacy and effectiveness of BRCA genetic testing programs, but whether they represent good use of financial resources is not clear. Therefore, we aimed to identify the main health-care programs for BRCA testing and to evaluate their cost-effectiveness. We performed a systematic review of full economic evaluations of health-care programs involving BRCA testing. Nine economic evaluations were included, and four main categories of BRCA testing programs were identified: (i) population-based genetic screening of individuals without cancer, either comprehensive or targeted based on ancestry; (ii) family history (FH)-based genetic screening, i.e., testing individuals without cancer but with FH suggestive of BRCA mutation; (iii) familial mutation (FM)-based genetic screening, i.e., testing individuals without cancer but with known familial BRCA mutation; and (iv) cancer-based genetic screening, i.e., testing individuals with BRCA-related cancers. Currently BRCA1/2 population-based screening represents good value for the money among Ashkenazi Jews only. FH-based screening is potentially very cost-effective, although further studies that include costs of identifying high-risk women are needed. There is no evidence of cost-effectiveness for BRCA screening of all newly diagnosed cases of breast/ovarian cancers followed by cascade testing of relatives, but programs that include tools for identifying affected women at higher risk for inherited forms are promising. Cost-effectiveness is highly sensitive to the cost of BRCA1/2 testing.Genet Med 18 12, 1171-1180.

Difficulties in diagnosing Marfan syndrome using current FBN1 databases.

PubMed

Groth, Kristian A; Gaustadnes, Mette; Thorsen, Kasper; Østergaard, John R; Jensen, Uffe Birk; Gravholt, Claus H; Andersen, Niels H

2016-01-01

The diagnostic criteria of Marfan syndrome (MFS) highlight the importance of a FBN1 mutation test in diagnosing MFS. As genetic sequencing becomes better, cheaper, and more accessible, the expected increase in the number of genetic tests will become evident, resulting in numerous genetic variants that need to be evaluated for disease-causing effects based on database information. The aim of this study was to evaluate genetic variants in four databases and review the relevant literature. We assessed background data on 23 common variants registered in ESP6500 and classified as causing MFS in the Human Gene Mutation Database (HGMD). We evaluated data in four variant databases (HGMD, UMD-FBN1, ClinVar, and UniProt) according to the diagnostic criteria for MFS and compared the results with the classification of each variant in the four databases. None of the 23 variants was clearly associated with MFS, even though all classifications in the databases stated otherwise. A genetic diagnosis of MFS cannot reliably be based on current variant databases because they contain incorrectly interpreted conclusions on variants. Variants must be evaluated by time-consuming review of the background material in the databases and by combining these data with expert knowledge on MFS. This is a major problem because we expect even more genetic test results in the near future as a result of the reduced cost and process time for next-generation sequencing.Genet Med 18 1, 98-102.

Unified method to integrate and blend several, potentially related, sources of information for genetic evaluation.

PubMed

Vandenplas, Jérémie; Colinet, Frederic G; Gengler, Nicolas

2014-09-30

A condition to predict unbiased estimated breeding values by best linear unbiased prediction is to use simultaneously all available data. However, this condition is not often fully met. For example, in dairy cattle, internal (i.e. local) populations lead to evaluations based only on internal records while widely used foreign sires have been selected using internally unavailable external records. In such cases, internal genetic evaluations may be less accurate and biased. Because external records are unavailable, methods were developed to combine external information that summarizes these records, i.e. external estimated breeding values and associated reliabilities, with internal records to improve accuracy of internal genetic evaluations. Two issues of these methods concern double-counting of contributions due to relationships and due to records. These issues could be worse if external information came from several evaluations, at least partially based on the same records, and combined into a single internal evaluation. Based on a Bayesian approach, the aim of this research was to develop a unified method to integrate and blend simultaneously several sources of information into an internal genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. This research resulted in equations that integrate and blend simultaneously several sources of information and avoid double-counting of contributions due to relationships and due to records. The performance of the developed equations was evaluated using simulated and real datasets. The results showed that the developed equations integrated and blended several sources of information well into a genetic evaluation. The developed equations also avoided double-counting of contributions due to relationships and due to records. Furthermore, because all available external sources of information were correctly propagated, relatives of external animals benefited from the integrated information and, therefore, more reliable estimated breeding values were obtained. The proposed unified method integrated and blended several sources of information well into a genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. The unified method can also be extended to other types of situations such as single-step genomic or multi-trait evaluations, combining information across different traits.

Evaluation of a Diverse, Worldwide Collection of Wild, Cultivated, and Landrace Pepper (Capsicum annuum) for Resistance to Phytophthora Fruit Rot, Genetic Diversity, and Population Structure.

PubMed

Naegele, R P; Tomlinson, A J; Hausbeck, M K

2015-01-01

Pepper is the third most important solanaceous crop in the United States and fourth most important worldwide. To identify sources of resistance for commercial breeding, 170 pepper genotypes from five continents and 45 countries were evaluated for Phytophthora fruit rot resistance using two isolates of Phytophthora capsici. Genetic diversity and population structure were assessed on a subset of 157 genotypes using 23 polymorphic simple sequence repeats. Partial resistance and isolate-specific interactions were identified in the population at both 3 and 5 days postinoculation (dpi). Plant introductions (PIs) 640833 and 566811 were the most resistant lines evaluated at 5 dpi to isolates 12889 and OP97, with mean lesion areas less than Criollo de Morelos. Genetic diversity was moderate (0.44) in the population. The program STRUCTURE inferred four genetic clusters with moderate to very great differentiation among clusters. Most lines evaluated were susceptible or moderately susceptible at 5 dpi, and no lines evaluated were completely resistant to Phytophthora fruit rot. Significant population structure was detected when pepper varieties were grouped by predefined categories of disease resistance, continent, and country of origin. Moderately resistant or resistant PIs to both isolates of P. capsici at 5 dpi were in genetic clusters one and two.

Incorporation of causative quantitative trait nucleotides in single-step GBLUP.

PubMed

Fragomeni, Breno O; Lourenco, Daniela A L; Masuda, Yutaka; Legarra, Andres; Misztal, Ignacy

2017-07-26

Much effort is put into identifying causative quantitative trait nucleotides (QTN) in animal breeding, empowered by the availability of dense single nucleotide polymorphism (SNP) information. Genomic selection using traditional SNP information is easily implemented for any number of genotyped individuals using single-step genomic best linear unbiased predictor (ssGBLUP) with the algorithm for proven and young (APY). Our aim was to investigate whether ssGBLUP is useful for genomic prediction when some or all QTN are known. Simulations included 180,000 animals across 11 generations. Phenotypes were available for all animals in generations 6 to 10. Genotypes for 60,000 SNPs across 10 chromosomes were available for 29,000 individuals. The genetic variance was fully accounted for by 100 or 1000 biallelic QTN. Raw genomic relationship matrices (GRM) were computed from (a) unweighted SNPs, (b) unweighted SNPs and causative QTN, (c) SNPs and causative QTN weighted with results obtained with genome-wide association studies, (d) unweighted SNPs and causative QTN with simulated weights, (e) only unweighted causative QTN, (f-h) as in (b-d) but using only the top 10% causative QTN, and (i) using only causative QTN with simulated weight. Predictions were computed by pedigree-based BLUP (PBLUP) and ssGBLUP. Raw GRM were blended with 1 or 5% of the numerator relationship matrix, or 1% of the identity matrix. Inverses of GRM were obtained directly or with APY. Accuracy of breeding values for 5000 genotyped animals in the last generation with PBLUP was 0.32, and for ssGBLUP it increased to 0.49 with an unweighted GRM, 0.53 after adding unweighted QTN, 0.63 when QTN weights were estimated, and 0.89 when QTN weights were based on true effects known from the simulation. When the GRM was constructed from causative QTN only, accuracy was 0.95 and 0.99 with blending at 5 and 1%, respectively. Accuracies simulating 1000 QTN were generally lower, with a similar trend. Accuracies using the APY inverse were equal or higher than those with a regular inverse. Single-step GBLUP can account for causative QTN via a weighted GRM. Accuracy gains are maximum when variances of causative QTN are known and blending is at 1%.

An Evaluation of Factors Associated With Pathogenic PRSS1, SPINK1, CTFR, and/or CTRC Genetic Variants in Patients With Idiopathic Pancreatitis.

PubMed

Jalaly, Niloofar Y; Moran, Robert A; Fargahi, Farshid; Khashab, Mouen A; Kamal, Ayesha; Lennon, Anne Marie; Walsh, Christi; Makary, Martin A; Whitcomb, David C; Yadav, Dhiraj; Cebotaru, Liudmila; Singh, Vikesh K

2017-08-01

We evaluated factors associated with pathogenic genetic variants in patients with idiopathic pancreatitis. Genetic testing (PRSS1, CFTR, SPINK1, and CTRC) was performed in all eligible patients with idiopathic pancreatitis between 2010 to 2015. Patients were classified into the following groups based on a review of medical records: (1) acute recurrent idiopathic pancreatitis (ARIP) with or without underlying chronic pancreatitis; (2) idiopathic chronic pancreatitis (ICP) without a history of ARP; (3) an unexplained first episode of acute pancreatitis (AP)<35 years of age; and (4) family history of pancreatitis. Logistic regression analysis was used to determine the factors associated with pathogenic genetic variants. Among 197 ARIP and/or ICP patients evaluated from 2010 to 2015, 134 underwent genetic testing. A total of 88 pathogenic genetic variants were found in 64 (47.8%) patients. Pathogenic genetic variants were identified in 58, 63, and 27% of patients with ARIP, an unexplained first episode of AP <35 years of age, and ICP without ARP, respectively. ARIP (OR: 18.12; 95% CI: 2.16-151.87; P=0.008) and an unexplained first episode of AP<35 years of age (OR: 2.46; 95% CI: 1.18-5.15; P=0.017), but not ICP, were independently associated with pathogenic genetic variants in the adjusted analysis. Pathogenic genetic variants are most likely to be identified in patients with ARIP and an unexplained first episode of AP<35 years of age. Genetic testing in these patient populations may delineate an etiology and prevent unnecessary diagnostic testing and procedures.

Genetic evaluation of Jatropha curcas: an important oilseed for biodiesel production.

PubMed

Freitas, R G; Missio, R F; Matos, F S; Resende, M D V; Dias, L A S

2011-01-01

Jatropha curcas, internationally and locally known, respectively, as physic nut and pinhão manso, is a highly promising species for biodiesel production in Brazil and other countries in the tropics. It is rustic, grows in warm regions and is easily cultivated. These characteristics and high-quality oil yields from the seeds have made this plant a priority for biodiesel programs in Brazil. Consequently, this species merits genetic investigations aimed at improving yields. Some studies have detected genetic variability in accessions in Africa and Asia. We have made the first genetic evaluation of J. curcas collected from Brazil. Our objective was to quantify genetic diversity and to estimate genetic parameters for growth and production traits and seed oil content. We evaluated 75 J. curcas progenies collected from Brazil and three from Cambodia. The mean oil content in the seeds was 31%, ranging from 16 to 45%. No genetic correlation between growth traits and seed oil content was found. However, high coefficients of genetic variation were found for plant height, number of branches, height of branches, and stem diameter. The highest individual narrow-sense heritabilities were found for leaf length (0.35) and width (0.34), stem diameter (0.24) and height of branches (0.21). We used a clustering algorithm to genetically identify the closest and most distant progenies, to assist in the development of new cultivars. Geographical diversity did not necessarily represent the genetic diversity among the accessions collected. These results are important for the continuity of breeding programs, aimed at obtaining cultivars with high grain yield and high oil content in seeds.

Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

PubMed Central

Canaza-Cayo, Ali William; Lopes, Paulo Sávio; da Silva, Marcos Vinicius Gualberto Barbosa; de Almeida Torres, Robledo; Martins, Marta Fonseca; Arbex, Wagner Antonio; Cobuci, Jaime Araujo

2015-01-01

A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre’s polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre’s polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from −0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from −0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits. PMID:26323397

The Genetic Drift Inventory: A Tool for Measuring What Advanced Undergraduates Have Mastered about Genetic Drift

ERIC Educational Resources Information Center

Price, Rebecca M.; Andrews, Tessa C.; McElhinny, Teresa L.; Mead, Louise S.; Abraham, Joel K.; Thanukos, Anna; Perez, Kathryn E.

2014-01-01

Understanding genetic drift is crucial for a comprehensive understanding of biology, yet it is difficult to learn because it combines the conceptual challenges of both evolution and randomness. To help assess strategies for teaching genetic drift, we have developed and evaluated the Genetic Drift Inventory (GeDI), a concept inventory that measures…

Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions

USDA-ARS?s Scientific Manuscript database

Information about genetic parameters is essential for selection decisions and genetic evaluation. Those estimates are population specific, but few studies are available for dairy cattle populations reared under tropical and subtropical conditions. Heritability and genetic correlations for milk yield...

Spatial and population genetic structure of microsatellites in white pine

Treesearch

Paula E. Marquardt; Bryan K. Epperson

2004-01-01

We evaluated the population genetic structure of seven microsatellite loci for old growth and second growth populations of eastern white pine (Pinus strobus). From each population, located within Hartwick Pines State Park, Grayling, Michigan, USA, 120-122 contiguous trees were sampled for genetic analysis. Within each population, genetic diversity...

Evaluation and characterization of a genetically diverse Musa germplasm core subset.

USDA-ARS?s Scientific Manuscript database

The USDA-ARS, Tropical Agriculture Research Station is responsible for curating germplasm of several regionally and internationally important agricultural crops. Evaluation and characterization of Musa (bananas) genetic resources are an important component of programmed research. In a global coll...

Portfolio Evaluation for Professional Competence: Credentialing in Genetics for Nurses.

ERIC Educational Resources Information Center

Cook, Sarah Sheets; Kase, Ron; Middelton, Lindsay; Monsen, Rita Black

2003-01-01

Describes the process used by the Credentialing Committee of the International Society of Nurses in Genetics to validate evaluation criteria for nursing portfolios using neural network programs. Illustrates how standards are translated into measurable competencies and provides a scoring guide. (SK)

Genetic Counseling and Evaluation for BRCA1/2 Testing

MedlinePlus

... counseling. If you do not have a personal history of breast or ovarian cancer BRCA genetic counseling, ... the USPSTF recommendation. If you have a personal history of ovarian cancer Genetic counseling and testing is ...

BIOTECHNOLOGY/ECORISK

EPA Science Inventory

This research effort is designed to provide the risk assessment community with modern genetic tools for evaluating long-term risks of genetically modified (GM) crops. Molecular population genetic data can potentially reveal information about long-term trends in both pest populat...

Developing education tailored to clinical roles: genetics education for haemophilia nurses.

PubMed

Burke, Sarah; Barker, Colin; Marshall, Dianne

2012-01-01

Genetics is an important component of the clinical work of haemophilia nurses, but little was known about the genetic education needs of haemophilia nurses. To develop, deliver and evaluate genetic education for haemophilia nurses, based on clinical roles. Perceived relevance of genetics to haemophilia nursing practice was explored using electronic voting (response rate 75%, 58/77). A follow-on questionnaire to a volunteer sample of participants explored educational preferences (response rate 41%, 17/41). Results informed development of a two-hour genetics workshop session, evaluated by questionnaire (response rate 67%, 47/70). Genetic competences were considered relevant to the clinical practice of haemophilia nurses, and learning needs were identified. Preference was expressed for education focused on practical skills. During the subsequent workshop, participant confidence ratings significantly increased in the four areas addressed. Planned changes to clinical care and training were reported. Within new areas of advanced nursing practice, learning needs can be addressed by: identifying relevant clinical activities and associated learning needs; creating a strategy and resources using preferred forms of delivery; implementing the strategy; and evaluating its effect. This will enable development of education that addresses the real needs of practising nurses, grounded in their daily clinical practice. Copyright © 2011 Elsevier Ltd. All rights reserved.

Genetic Evaluation of Children with Global Developmental Delay--Current Status of Network Systems in Taiwan.

PubMed

Foo, Yong-Lin; Chow, Julie Chi; Lai, Ming-Chi; Tsai, Wen-Hui; Tung, Li-Chen; Kuo, Mei-Chin; Lin, Shio-Jean

2015-08-01

This review article aims to introduce the screening and referral network of genetic evaluation for children with developmental delay in Taiwan. For these children, integrated systems provide services from the medical, educational, and social welfare sectors. All cities and counties in Taiwan have established a network for screening, detection, referral, evaluation, and intervention services. Increased awareness improves early detection and intervention. There remains a gap between supply and demand, especially with regard to financial resources and professional manpower. Genetic etiology has a major role in prenatal causes of developmental delay. A summary of reports on some related genetic disorders in the Taiwanese population is included in this review. Genetic diagnosis allows counseling with regard to recurrence risk and prevention. Networking with neonatal screening, laboratory diagnosis, genetic counseling, and orphan drugs logistics systems can provide effective treatment for patients. In Taiwan, several laboratories provide genetic tests for clinical diagnosis. Accessibility to advanced expensive tests such as gene chips or whole exome sequencing is limited because of funding problems; however, the service system in Taiwan can still operate in a relatively cost-effective manner. This experience in Taiwan may serve as a reference for other countries. Copyright © 2014. Published by Elsevier B.V.

Implementation of genetic conservation practices in a muskellunge propagation and stocking program

USGS Publications Warehouse

Jennings, Martin J.; Sloss, Brian L.; Hatzenbeler, Gene R.; Kampa, Jeffrey M.; Simonson, Timothy D.; Avelallemant, Steven P.; Lindenberger, Gary A.; Underwood, Bruce D.

2010-01-01

Conservation of genetic resources is a challenging issue for agencies managing popular sport fishes. To address the ongoing potential for genetic risks, we developed a comprehensive set of recommendations to conserve genetic diversity of muskellunge (Esox masquinongy) in Wisconsin, and evaluated the extent to which the recommendations can be implemented. Although some details are specific to Wisconsin's muskellunge propagation program, many of the practical issues affecting implementation are applicable to other species and production systems. We developed guidelines to restrict future broodstock collection operations to lakes with natural reproduction and to develop a set of brood lakes to use on a rotational basis within regional stock boundaries, but implementation will require considering lakes with variable stocking histories. Maintaining an effective population size sufficient to minimize the risk of losing alleles requires limiting broodstock collection to large lakes. Recommendations to better approximate the temporal distribution of spawning in hatchery operations and randomize selection of brood fish are feasible. Guidelines to modify rearing and distribution procedures face some logistic constraints. An evaluation of genetic diversity of hatchery-produced fish during 2008 demonstrated variable success representing genetic variation of the source population. Continued evaluation of hatchery operations will optimize operational efficiency while moving toward genetic conservation goals.

Implementation of genetic conservation practices in a muskellunge propagation and stocking program

USGS Publications Warehouse

Jennings, Martin J.; Sloss, Brian L.; Hatzenbeler, Gene R.; Kampa, Jeffrey M.; Simonson, Timothy D.; Avelallemant, Steven P.; Lindenberger, Gary A.; Underwood, Bruce D.

2010-01-01

Conservation of genetic resources is a challenging issue for agencies managing popular sport fishes. To address the ongoing potential for genetic risks, we developed a comprehensive set of recommendations to conserve genetic diversity of muskellunge (Esox masquinongy) in Wisconsin, and evaluated the extent to which the recommendations can be implemented. Although some details are specific to Wisconsin's muskellunge propagation program, many of the practical issues affecting implementation are applicable to other species and production systems. We developed guidelines to restrict future brood stock collection operations to lakes with natural reproduction and to develop a set of brood lakes to use on a rotational basis within regional stock boundaries, but implementation will require considering lakes with variable stocking histories. Maintaining an effective population size sufficient to minimize the risk of losing alleles requires limiting brood stock collection to large lakes. Recommendations to better approximate the temporal distribution of spawning in hatchery operations and randomize selection of brood fish are feasible. Guidelines to modify rearing and distribution procedures face some logistic constraints. An evaluation of genetic diversity of hatchery-produced fish during 2008 demonstrated variable success representing genetic variation of the source population. Continued evaluation of hatchery operations will optimize operational efficiency while moving toward genetic conservation goals.

How is genetic testing evaluated? A systematic review of the literature.

PubMed

Pitini, Erica; De Vito, Corrado; Marzuillo, Carolina; D'Andrea, Elvira; Rosso, Annalisa; Federici, Antonio; Di Maria, Emilio; Villari, Paolo

2018-05-01

Given the rapid development of genetic tests, an assessment of their benefits, risks, and limitations is crucial for public health practice. We performed a systematic review aimed at identifying and comparing the existing evaluation frameworks for genetic tests. We searched PUBMED, SCOPUS, ISI Web of Knowledge, Google Scholar, Google, and gray literature sources for any documents describing such frameworks. We identified 29 evaluation frameworks published between 2000 and 2017, mostly based on the ACCE Framework (n = 13 models), or on the HTA process (n = 6), or both (n = 2). Others refer to the Wilson and Jungner screening criteria (n = 3) or to a mixture of different criteria (n = 5). Due to the widespread use of the ACCE Framework, the most frequently used evaluation criteria are analytic and clinical validity, clinical utility and ethical, legal and social implications. Less attention is given to the context of implementation. An economic dimension is always considered, but not in great detail. Consideration of delivery models, organizational aspects, and consumer viewpoint is often lacking. A deeper analysis of such context-related evaluation dimensions may strengthen a comprehensive evaluation of genetic tests and support the decision-making process.

Logistics Distribution Center Location Evaluation Based on Genetic Algorithm and Fuzzy Neural Network

NASA Astrophysics Data System (ADS)

Shao, Yuxiang; Chen, Qing; Wei, Zhenhua

Logistics distribution center location evaluation is a dynamic, fuzzy, open and complicated nonlinear system, which makes it difficult to evaluate the distribution center location by the traditional analysis method. The paper proposes a distribution center location evaluation system which uses the fuzzy neural network combined with the genetic algorithm. In this model, the neural network is adopted to construct the fuzzy system. By using the genetic algorithm, the parameters of the neural network are optimized and trained so as to improve the fuzzy system’s abilities of self-study and self-adaptation. At last, the sampled data are trained and tested by Matlab software. The simulation results indicate that the proposed identification model has very small errors.

INHERITED NEUROPATHIES: CLINICAL OVERVIEW AND UPDATE

PubMed Central

KLEIN, CHRISTOPHER J.; DUAN, XIAOHUI; SHY, MICHAEL E.

2014-01-01

Inherited neuropathy is a group of common neurologic disorders with heterogeneous clinical presentations and genetic causes. Detailed neuromuscular evaluations, including nerve conduction studies, laboratory testing, and histopathologic examination, can assist in identification of the inherited component beyond family history. Genetic testing increasingly enables definitive diagnosis of specific inherited neuropathies. Diagnosis, however, is often complex, and neurologic disability may have both genetic and acquired components in individual patients. The decision of which genetic test to order or whether to order genetic tests is often complicated, and the strategies to maximize the value of testing are evolving. Apart from rare inherited metabolic neuropathies, treatment approaches remain largely supportive. We provide a clinical update of the various types of inherited neuropathies, their differential diagnoses, and distinguishing clinical features (where available). A framework is provided for clinical evaluations, including the inheritance assessment, electrophysiologic examinations, and specific genetic tests. PMID:23801417

Re-evaluating causal modeling with mantel tests in landscape genetics

Treesearch

Samuel A. Cushman; Tzeidle N. Wasserman; Erin L. Landguth; Andrew J. Shirk

2013-01-01

The predominant analytical approach to associate landscape patterns with gene flow processes is based on the association of cost distances with genetic distances between individuals. Mantel and partial Mantel tests have been the dominant statistical tools used to correlate cost distances and genetic distances in landscape genetics. However, the inherent high...

Refining and defining riverscape genetics: How rivers influence population genetic structure

Treesearch

Chanté D. Davis; Clinton W. Epps; Rebecca L. Flitcroft; Michael A. Banks

2018-01-01

Traditional analysis in population genetics evaluates differences among groups of individuals and, in some cases, considers the effects of distance or potential barriers to gene flow. Genetic variation of organisms in complex landscapes, seascapes, or riverine systems, however, may be shaped by many forces. Recent research has linked habitat heterogeneity and landscape...

Isozymes and the genetic resources of forest trees

Treesearch

A. H. D. Brown; G. F. Moran

1981-01-01

Genetic data are an essential prerequisite for analysing the genetic structure of tree populations. The isozyme technique is the best currently available method for obtaining such data. Despite several shortcomings, isozyme data directly evaluate the genetic resources of forest trees, and can thus be used to monitor and manipulate these resources. For example,...

Genetic parameters and prediction of breeding values in switchgrass bred for bioenergy

USDA-ARS?s Scientific Manuscript database

Estimating genetic parameters is an essential step in breeding by recurrent selection to maximize genetic gains over time. This study evaluated the effects of selection on genetic variation across two successive cycles (C1 and C2) of a ‘Summer’x‘Kanlow’ switchgrass (Panicum virgatum L.) population. ...

Identification of individuals at risk for Lynch syndrome using targeted evaluations and genetic testing: National Society of Genetic Counselors and the Collaborative Group of the Americas on Inherited Colorectal Cancer joint practice guideline.

PubMed

Weissman, Scott M; Burt, Randall; Church, James; Erdman, Steve; Hampel, Heather; Holter, Spring; Jasperson, Kory; Kalady, Matt F; Haidle, Joy Larsen; Lynch, Henry T; Palaniappan, Selvi; Wise, Paul E; Senter, Leigha

2012-08-01

Identifying individuals who have Lynch syndrome (LS) involves a complex diagnostic work up that includes taking a detailed family history and a combination of various genetic and immunohistochemical tests. The National Society of Genetic Counselors (NSGC) and the Collaborative Group of the Americas on Inherited Colorectal Cancer (CGA-ICC) have come together to publish this clinical practice testing guideline for the evaluation of LS. The purpose of this practice guideline is to provide guidance and a testing algorithm for LS as well as recommendations on when to offer testing. This guideline does not replace a consultation with a genetics professional. This guideline includes explanations in support of this and a summary of background data. While this guideline is not intended to serve as a review of LS, it includes a discussion of background information on LS, and cites a number of key publications which should be reviewed for a more in-depth understanding of LS. These guidelines are intended for genetic counselors, geneticists, gastroenterologists, surgeons, medical oncologists, obstetricians and gynecologists, nurses and other healthcare providers who evaluate patients for LS.

An exploratory study with preliminary results: The development and evaluation of a Genetics Concept Inventory

NASA Astrophysics Data System (ADS)

Hott, Adam M.

Modern science education reform includes the development of standards and recommendations for content as well as the development and evaluation of pedagogy, but demonstrates limited assessment of student knowledge. Student knowledge assessment is an important factor in measuring the scientific literacy of current students. Concept inventories have been developed and used for the past fourteen years to assess non-science major student conceptual understanding of a content area. Inventories have been developed in the fields of physics, astronomy, chemistry and biology. The development and evaluation of a Genetics Concept Inventory (GCI) is presented here. The reliability estimate of 0.62 is supported by a respected panel of genetics educators' revisions, no significant gender bias, and the ability of junior and senior biology majors to outperform the non-science majors. Pretest/Posttest comparisons show a significant increase in five of six genetics content areas as well as a 9% increase on the overall percent score for the instrument. Although the Genetics Concept Inventory presented here needs further modification and testing, it is the first step in the development of a quality assessment tool for genetics content.

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

PubMed

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic selection in autogamous crops, especially bringing long-term improvement.

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops

PubMed Central

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an “island model” inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic selection in autogamous crops, especially bringing long-term improvement. PMID:27115872

Genetic toxicology at the crossroads-from qualitative hazard evaluation to quantitative risk assessment.

PubMed

White, Paul A; Johnson, George E

2016-05-01

Applied genetic toxicology is undergoing a transition from qualitative hazard identification to quantitative dose-response analysis and risk assessment. To facilitate this change, the Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC) sponsored a workshop held in Lancaster, UK on July 10-11, 2014. The event included invited speakers from several institutions and the contents was divided into three themes-1: Point-of-departure Metrics for Quantitative Dose-Response Analysis in Genetic Toxicology; 2: Measurement and Estimation of Exposures for Better Extrapolation to Humans and 3: The Use of Quantitative Approaches in Genetic Toxicology for human health risk assessment (HHRA). A host of pertinent issues were discussed relating to the use of in vitro and in vivo dose-response data, the development of methods for in vitro to in vivo extrapolation and approaches to use in vivo dose-response data to determine human exposure limits for regulatory evaluations and decision-making. This Special Issue, which was inspired by the workshop, contains a series of papers that collectively address topics related to the aforementioned themes. The Issue includes contributions that collectively evaluate, describe and discuss in silico, in vitro, in vivo and statistical approaches that are facilitating the shift from qualitative hazard evaluation to quantitative risk assessment. The use and application of the benchmark dose approach was a central theme in many of the workshop presentations and discussions, and the Special Issue includes several contributions that outline novel applications for the analysis and interpretation of genetic toxicity data. Although the contents of the Special Issue constitutes an important step towards the adoption of quantitative methods for regulatory assessment of genetic toxicity, formal acceptance of quantitative methods for HHRA and regulatory decision-making will require consensus regarding the relationships between genetic damage and disease, and the concomitant ability to use genetic toxicity results per se. © Her Majesty the Queen in Right of Canada 2016. Reproduced with the permission of the Minister of Health.

Genetic potential of common bean progenies obtained by different breeding methods evaluated in various environments.

PubMed

Pontes Júnior, V A; Melo, P G S; Pereira, H S; Melo, L C

2016-09-02

Grain yield is strongly influenced by the environment, has polygenic and complex inheritance, and is a key trait in the selection and recommendation of cultivars. Breeding programs should efficiently explore the genetic variability resulting from crosses by selecting the most appropriate method for breeding in segregating populations. The goal of this study was to evaluate and compare the genetic potential of common bean progenies of carioca grain for grain yield, obtained by different breeding methods and evaluated in different environments. Progenies originating from crosses between lines and CNFC 7812 and CNFC 7829 were replanted up to the F 7 generation using three breeding methods in segregating populations: population (bulk), bulk within F 2 progenies, and single-seed descent (SSD). Fifteen F 8 progenies per method, two controls (BRS Estilo and Perola), and the parents were evaluated in a 7 x 7 simple lattice design, with plots of two 4-m rows. The tests were conducted in 10 environments in four States of Brazil and in three growing seasons in 2009 and 2010. Genetic parameters including genetic variance, heritability, variance of interaction, and expected selection gain were estimated. Genetic variability among progenies and the effect of progeny-environment interactions were determined for the three methods. The breeding methods differed significantly due to the effects of sampling procedures on the progenies and due to natural selection, which mainly affected the bulk method. The SSD and bulk methods provided populations with better estimates of genetic parameters and more stable progenies that were less affected by interaction with the environment.

Evaluation of genetic diversity and population structure of West-Central Indian cattle breeds.

PubMed

Shah, Tejas M; Patel, Jaina S; Bhong, Chandrakant D; Doiphode, Aakash; Umrikar, Uday D; Parmar, Shivnandan S; Rank, Dharamshibhai N; Solanki, Jitendra V; Joshi, Chaitanya G

2013-08-01

Evaluations of genetic diversity in domestic livestock populations are necessary to implement region-specific conservation measures. We determined the genetic diversity and evolutionary relationships among eight geographically and phenotypically diverse cattle breeds indigenous to west-central India by genotyping these animals for 22 microsatellite loci. A total of 326 alleles were detected, and the expected heterozygosity ranged from 0.614 (Kenkatha) to 0.701 (Dangi). The mean number of alleles among the cattle breeds ranged from 7.182 (Khillar) to 9.409 (Gaolao). There were abundant genetic variations displayed within breeds, and the genetic differentiation was also high between the Indian cattle breeds, which displayed 15.9% of the total genetic differentiation among the different breeds. The genetic differentiation (pairwise FST ) among the eight Indian breeds varied from 0.0126 for the Kankrej-Malvi pair to 0.2667 for Khillar-Kenkatha pair. The phylogeny, principal components analysis, and structure analysis further supported close grouping of Kankrej, Malvi, Nimari and Gir; Gaolao and Kenkatha, whereas Dangi and Khillar remained at distance from other breeds. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

Incorporation of genomic information into genetic evaluation: U. S. beef industry as a model

USDA-ARS?s Scientific Manuscript database

In his presentation, Dr. Kuehn described approaches for using information garnered through developments in genomics to improve the accuracy of genetic evaluation. He considered the history of these molecular-based techniques, including their strengths and potential weaknesses, and his experiences wi...

Study of parameter identification using hybrid neural-genetic algorithm in electro-hydraulic servo system

NASA Astrophysics Data System (ADS)

Moon, Byung-Young

2005-12-01

The hybrid neural-genetic multi-model parameter estimation algorithm was demonstrated. This method can be applied to structured system identification of electro-hydraulic servo system. This algorithms consist of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. To evaluate the proposed method, electro-hydraulic servo system was designed and manufactured. The experiment was carried out to figure out the hybrid neural-genetic multi-model parameter estimation algorithm. As a result, the dynamic characteristics were obtained such as the parameters(mass, damping coefficient, bulk modulus, spring coefficient), which minimize total square error. The result of this study can be applied to hydraulic systems in industrial fields.

Biobanking genetic material for agricultural animal species

USDA-ARS?s Scientific Manuscript database

Biobanking animal germplasm and tissues is a major component of conserving genetic resources. Effectively constructing such gene banks requires an understanding and evaluation of genetic resources, the ability to conserve various tissues through cryopreservation, and a robust information technology ...

An economic evaluation of second-trimester genetic ultrasonography for prenatal detection of down syndrome.

PubMed

Vintzileos, A M; Ananth, C V; Fisher, A J; Smulian, J C; Day-Salvatore, D; Beazoglou, T; Knuppel, R A

1998-11-01

The objective of this study was to perform an economic evaluation of second-trimester genetic ultrasonography for prenatal detection of Down syndrome. More specifically, we sought to determine the following: (1) the diagnostic accuracy requirements (from the cost-benefit point of view) of genetic ultrasonography versus genetic amniocentesis for women at increased risk for fetal Down syndrome and (2) the possible economic impact of second-trimester genetic ultrasonography for the US population on the basis of the ultrasonographic accuracies reported in previously published studies. A cost-benefit equation was developed from the hypothesis that the cost of universal genetic amniocentesis of patients at increased risk for carrying a fetus with Down syndrome should be at least equal to the cost of universal genetic ultrasonography with amniocentesis used only for those with abnormal ultrasonographic results. The main components of the equation included the diagnostic accuracy of genetic ultrasonography (sensitivity and specificity for detecting Down syndrome), the costs of the amniocentesis package and genetic ultrasonography, and the lifetime cost of Down syndrome cases not detected by the genetic ultrasonography. After appropriate manipulation of the equation a graph was constructed, representing the balance between sensitivity and false-positive rate of genetic ultrasonography; this was used to examine the accuracy of previously published studies from the cost-benefit point of view. Sensitivity analyses included individual risks for Down syndrome ranging from 1:261 (risk of a 35-year-old at 18 weeks' gestation) to 1:44 (risk of a 44-year-old at 18 weeks' gestation). This economic evaluation was conducted from the societal perspective. Genetic ultrasonography was found to be economically beneficial only if the overall sensitivity for detecting Down syndrome was >74%. Even then, the cost-benefit ratio depended on the corresponding false-positive rate. Of the 7 published studies that used multiple ultrasonographic markers for genetic ultrasonography, 6 had accuracies compatible with benefits. The required ultrasonographic accuracy (sensitivity and false-positive rate) varied according to the prevalence of Down syndrome in the population tested. The cost-benefit ratio of second-trimester genetic ultrasonography depends on its diagnostic accuracy, and it is beneficial only when its overall sensitivity for Down syndrome is >74%.

78 FR 25297 - Programmatic Environmental Assessment

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-30

... environmental assessment (PEA) to evaluate the effects of the cultivation and use of genetically modified crops... genetically modified crops (GMCs) on our Refuge System lands. Our PEA will concentrate on the refuges in our... lands are those that have been evaluated and deregulated by the Animal and Plant Health Inspection...

Predictive Heterosis in Multibreed Evaluations Using Quantitative and Molecular Approaches

USDA-ARS?s Scientific Manuscript database

Heterosis is the extra genetic boost in performance obtained by crossing two cattle breeds. It is an important tool for increasing the efficiency of beef production. It is also important to adjust data used to calculate genetic evaluations for differences in heterosis. Good estimates of heterosis...

Estimation of the Proportion of Genetic Variation Accounted for by DNA Tests

USDA-ARS?s Scientific Manuscript database

An increasingly relevant question in evaluating commercial DNA tests is "What proportion of the additive genetic variation in the target trait is accounted for by the test?" Therefore, several estimators of this quantity were evaluated by simulation of a population of 1000 animals with 100 sires, ea...

A prototype national cattle evaluation for feed intake and efficiency of Angus cattle

USDA-ARS?s Scientific Manuscript database

Recent development of technologies for measuring individual feed intake has made possible the collection of data suitable for breed-wide genetic evaluation. Goals of this research were to estimate genetic parameters for components of feed efficiency and develop a prototype system for conducting a ge...

Genetic Monitoring and Evaluation Program for Supplemented Populations of Salmon and Steelhead in the Snake River Basin, 1990-1991 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waples, Robin S.; Teel, David J.; Aebersold, Paul B.

This is the first report of research for an ongoing study to evaluate the genetic effects of using hatchery-reared fish to supplement natural populations of chinook salmon and steelhead in the Snake River Basin.

Effect of inclusion or non-inclusion of short lactations and cow and/or dam genetic group on genetic evaluation of Girolando dairy cattle.

PubMed

Canaza-Cayo, A W; Silva, M V G B; Cobuci, J A; Martins, M F; Lopes, P S

2016-04-04

The objective of this study was to evaluate the effects of inclusion or non-inclusion of short lactations and cow (CGG) and/or dam (DGG) genetic group on the genetic evaluation of 305-day milk yield (MY305), age at first calving (AFC), and first calving interval (FCI) of Girolando cows. Covariance components were estimated by the restricted maximum likelihood method in an animal model of single trait analyses. The heritability estimates for MY305, AFC, and FCI ranged from 0.23 to 0.29, 0.40 to 0.44, and 0.13 to 0.14, respectively, when short lactations were not included, and from 0.23 to 0.28, 0.39 to 0.43, and 0.13 to 0.14, respectively, when short lactations were included. The inclusion of short lactations caused little variation in the variance components and heritability estimates of traits, but their non-inclusion resulted in the re-ranking of animals. Models with CGG or DGG fixed effects had higher heritability estimates for all traits compared with models that consider these two effects simultaneously. We recommend using the model with fixed effects of CGG and inclusion of short lactations for the genetic evaluation of Girolando cattle.

Genetic variability of garlic accessions as revealed by agro-morphological traits evaluated under different environments.

PubMed

Hoogerheide, E S S; Azevedo Filho, J A; Vencovsky, R; Zucchi, M I; Zago, B W; Pinheiro, J B

2017-05-31

The cultivated garlic (Allium sativum L.) displays a wide phenotypic diversity, which is derived from natural mutations and phenotypic plasticity, due to dependence on soil type, moisture, latitude, altitude and cultural practices, leading to a large number of cultivars. This study aimed to evaluate the genetic variability shown by 63 garlic accessions belonging to Instituto Agronômico de Campinas and the Escola Superior de Agricultura "Luiz de Queiroz" germplasm collections. We evaluated ten quantitative characters in experimental trials conducted under two localities of the State of São Paulo: Monte Alegre do Sul and Piracicaba, during the agricultural year of 2007, in a randomized blocks design with five replications. The Mahalanobis distance was used to measure genetic dissimilarities. The UPGMA method and Tocher's method were used as clustering procedures. Results indicated significant variation among accessions (P < 0.01) for all evaluated characters, except for the percentage of secondary bulb growth in MAS, indicating the existence of genetic variation for bulb production, and germplasm evaluation considering different environments is more reliable for the characterization of the genotypic variability among garlic accessions, since it diminishes the environmental effects in the clustering of genotypes.

Computational Integration of Human Genetic and Toxicological Data to Evaluate AOP-Specific Susceptibility

EPA Science Inventory

Susceptibility to environmental chemicals can be modulated by genetic differences. Direct estimation of the genetic contribution to variability in susceptibility to environmental chemicals is only possible in special cases where there is an observed association between exposure a...

USE OF GENOTOXIC ACTIVITY PROFILES IN ASSESSMENT OF CARCINOGENESIS AND TRANSMISSIBLE GENETIC EFFECTS

EPA Science Inventory

A methodology has been developed to display and evaluate multiple test quantitative information on genetic toxicants for purposes of assessing carcinogenesis and transmissible genetic effects. ose Information is collected from the open literature: either the lowest effective dose...

Evaluation of LOINC for Representing Constitutional Cytogenetic Test Result Reports

PubMed Central

Heras, Yan Z.; Mitchell, Joyce A.; Williams, Marc S.; Brothman, Arthur R.; Huff, Stanley M.

2009-01-01

Genetic testing is becoming increasingly important to medical practice. Integrating genetics and genomics data into electronic medical records is crucial in translating genetic discoveries into improved patient care. Information technology, especially Clinical Decision Support Systems, holds great potential to help clinical professionals take full advantage of genomic advances in their daily medical practice. However, issues relating to standard terminology and information models for exchanging genetic testing results remain relatively unexplored. This study evaluates whether the current LOINC standard is adequate to represent constitutional cytogenetic test result reports using sample result reports from ARUP Laboratories. The results demonstrate that current standard terminology is insufficient to support the needs of coding cytogenetic test results. The terminology infrastructure must be developed before clinical information systems will be able to handle the high volumes of genetic data expected in the near future. PMID:20351857

Evaluation of LOINC for representing constitutional cytogenetic test result reports.

PubMed

Heras, Yan Z; Mitchell, Joyce A; Williams, Marc S; Brothman, Arthur R; Huff, Stanley M

2009-11-14

Genetic testing is becoming increasingly important to medical practice. Integrating genetics and genomics data into electronic medical records is crucial in translating genetic discoveries into improved patient care. Information technology, especially Clinical Decision Support Systems, holds great potential to help clinical professionals take full advantage of genomic advances in their daily medical practice. However, issues relating to standard terminology and information models for exchanging genetic testing results remain relatively unexplored. This study evaluates whether the current LOINC standard is adequate to represent constitutional cytogenetic test result reports using sample result reports from ARUP Laboratories. The results demonstrate that current standard terminology is insufficient to support the needs of coding cytogenetic test results. The terminology infrastructure must be developed before clinical information systems will be able to handle the high volumes of genetic data expected in the near future.

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

PubMed

Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

2013-09-01

Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P < 0.01). This algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P < 0.05), whereas it shows results not significantly different to 3D-COFFEE (P > 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

Benchmarking outcomes in the Neonatal Intensive Care Unit: Cytogenetic and molecular diagnostic rates in a retrospective cohort.

PubMed

Malam, Faheem; Hartley, Taila; Gillespie, Meredith K; Armour, Christine M; Bariciak, Erika; Graham, Gail E; Nikkel, Sarah M; Richer, Julie; Sawyer, Sarah L; Boycott, Kym M; Dyment, David A

2017-05-09

Genetic disease and congenital anomalies continue to be a leading cause of neonate mortality and morbidity. A genetic diagnosis in the neonatal intensive care unit (NICU) can be a challenge given the associated genetic heterogeneity and early stage of a disease. We set out to evaluate the outcomes of Medical Genetics consultation in the NICU in terms of cytogenetic and molecular diagnostic rates and impact on management. We retrospectively reviewed 132 charts from patients admitted to the NICU who received a Medical Genetics diagnostic evaluation over a 2 year period. Of the 132 patients reviewed, 26% (34/132) received a cytogenetic or molecular diagnosis based on the Medical Genetics diagnostic evaluation; only 10% (13/132) received a diagnosis during their admission. The additional 16% (21 patients) received their diagnosis following NICU discharge, but based on a genetic test initiated during hospital-stay. Mean time from NICU admission to confirmed diagnosis was 24 days. For those who received a genetic diagnosis, the information was considered beneficial for clinical management in all, and a direct change to medical management occurred for 12% (4/32). For those non-diagnosed infants seen in out-patient follow-up clinic, diagnoses were made in 8% (3/37). The diagnoses made post-discharge from the NICU comprised a greater number of Mendelian disorders and represent an opportunity to improve genetic care. The adoption of diagnostic tools, such as exome sequencing, used in parallel with traditional approaches will improve rate of diagnoses and will have a significant impact, in particular when the differential diagnosis is broad. © 2017 Wiley Periodicals, Inc.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling.

PubMed

Kochunov, Peter; Jahanshad, Neda; Sprooten, Emma; Nichols, Thomas E; Mandl, René C; Almasy, Laura; Booth, Tom; Brouwer, Rachel M; Curran, Joanne E; de Zubicaray, Greig I; Dimitrova, Rali; Duggirala, Ravi; Fox, Peter T; Hong, L Elliot; Landman, Bennett A; Lemaitre, Hervé; Lopez, Lorna M; Martin, Nicholas G; McMahon, Katie L; Mitchell, Braxton D; Olvera, Rene L; Peterson, Charles P; Starr, John M; Sussmann, Jessika E; Toga, Arthur W; Wardlaw, Joanna M; Wright, Margaret J; Wright, Susan N; Bastin, Mark E; McIntosh, Andrew M; Boomsma, Dorret I; Kahn, René S; den Braber, Anouk; de Geus, Eco J C; Deary, Ian J; Hulshoff Pol, Hilleke E; Williamson, Douglas E; Blangero, John; van 't Ent, Dennis; Thompson, Paul M; Glahn, David C

2014-07-15

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability. Copyright © 2014 Elsevier Inc. All rights reserved.

Exome Sequencing in the Clinical Diagnosis of Sporadic or Familial Cerebellar Ataxia

PubMed Central

Fogel, Brent L.; Lee, Hane; Deignan, Joshua L.; Strom, Samuel P.; Kantarci, Sibel; Wang, Xizhe; Quintero-Rivera, Fabiola; Vilain, Eric; Grody, Wayne W.; Perlman, Susan; Geschwind, Daniel H.; Nelson, Stanley F.

2015-01-01

IMPORTANCE Cerebellar ataxias are a diverse collection of neurologic disorders with causes ranging from common acquired etiologies to rare genetic conditions. Numerous genetic disorders have been associated with chronic progressive ataxia and this consequently presents a diagnostic challenge for the clinician regarding how to approach and prioritize genetic testing in patients with such clinically heterogeneous phenotypes. Additionally, while the value of genetic testing in early-onset and/or familial cases seems clear, many patients with ataxia present sporadically with adult onset of symptoms and the contribution of genetic variation to the phenotype of these patients has not yet been established. OBJECTIVE To investigate the contribution of genetic disease in a population of patients with predominantly adult- and sporadic-onset cerebellar ataxia. DESIGN, SETTING, AND PARTICIPANTS We examined a consecutive series of 76 patients presenting to a tertiary referral center for evaluation of chronic progressive cerebellar ataxia. MAIN OUTCOMES AND MEASURES Next-generation exome sequencing coupled with comprehensive bioinformatic analysis, phenotypic analysis, and clinical correlation. RESULTS We identified clinically relevant genetic information in more than 60% of patients studied (n = 46), including diagnostic pathogenic gene variants in 21% (n = 16), a notable yield given the diverse genetics and clinical heterogeneity of the cerebellar ataxias. CONCLUSIONS AND RELEVANCE This study demonstrated that clinical exome sequencing in patients with adult-onset and sporadic presentations of ataxia is a high-yield test, providing a definitive diagnosis in more than one-fifth of patients and suggesting a potential diagnosis in more than one-third to guide additional phenotyping and diagnostic evaluation. Therefore, clinical exome sequencing is an appropriate consideration in the routine genetic evaluation of all patients presenting with chronic progressive cerebellar ataxia. PMID:25133958

Microsatellite variation reveals weak genetic structure and retention of genetic variability in threatened Chinook salmon (Oncorhynchus tshawytcha) within a Snake River watershed

Treesearch

Helen Neville; Daniel Isaak; Russell Thurow; Jason Dunham; Bruce Rieman

2007-01-01

Pacific salmon (Oncorhynchus spp.) have been central to the development of management concepts associated with evolutionarily significant units (ESUs), yet there are still relatively few studies of genetic diversity within threatened and endangered ESUs for salmon or other species. We analyzed genetic variation at 10 microsatellite loci to evaluate...

Is the Child "Father of the Man"? Evaluating the Stability of Genetic Influences across Development

ERIC Educational Resources Information Center

Ronald, Angelica

2011-01-01

This selective review considers findings in genetic research that have shed light on how genes operate across development. We will address the question of whether the child is "father of the Man" from a genetic perspective. In other words, do the same genetic influences affect the same traits across development? Using a "taster menu" approach and…

Integration of population genetic structure and plant response to climate change: sustaining genetic resources through evaluation of projected threats

Treesearch

Bryce A. Richardson; Marcus V. Warwell; Mee-Sook Kim; Ned B. Klopfenstein; Geral I. McDonald

2010-01-01

To assess threats or predict responses to disturbances, or both, it is essential to recognize and characterize the population structures of forest species in relation to changing environments. Appropriate management of these genetic resources in the future will require (1) understanding the existing genetic diversity/variation and population structure of forest trees...

Genetic conservation and management of the California endemic, Torrey pine ( Pinus torreyana Parry): Implications of genetic rescue in a genetically depauperate species

Treesearch

Jill A. Hamilton; Raphaël Royauté; Jessica W. Wright; Paul Hodgskiss; F. Thomas Ledig

2017-01-01

Rare species present a challenge under changing environmental conditions as the genetic consequences of rarity may limit species ability to adapt to environmental change. To evaluate the evolutionary potential of a rare species, we assessed variation in traits important to plant fitness using multigenerational common garden experiments. Torrey pine, ...

Adaptive genetic potential of coniferous forest tree species under climate change: implications for sustainable forest management

NASA Astrophysics Data System (ADS)

Mihai, Georgeta; Birsan, Marius-Victor; Teodosiu, Maria; Dumitrescu, Alexandru; Daia, Mihai; Mirancea, Ionel; Ivanov, Paula; Alin, Alexandru

2017-04-01

Mountain ecosystems are extremely vulnerable to climate change. The real potential for adaptation depends upon the existence of a wide genetic diversity in trees populations, upon the adaptive genetic variation, respectively. Genetic diversity offers the guarantee that forest species can survive, adapt and evolve under the influence of changing environmental conditions. The aim of this study is to evaluate the genetic diversity and adaptive genetic potential of two local species - Norway spruce and European silver fir - in the context of regional climate change. Based on data from a long-term provenance experiments network and climate variables spanning over more than 50 years, we have investigated the impact of climatic factors on growth performance and adaptation of tree species. Our results indicate that climatic and geographic factors significantly affect forest site productivity. Mean annual temperature and annual precipitation amount were found to be statistically significant explanatory variables. Combining the additive genetic model with the analysis of nuclear markers we obtained different images of the genetic structure of tree populations. As genetic indicators we used: gene frequencies, genetic diversity, genetic differentiation, genetic variance, plasticity. Spatial genetic analyses have allowed identifying the genetic centers holding high genetic diversity which will be valuable sources of gene able to buffer the negative effects of future climate change. Correlations between the marginal populations and in the optimal vegetation, between the level of genetic diversity and ecosystem stability, will allow the assessment of future risks arising from current genetic structure. Therefore, the strategies for sustainable forest management have to rely on the adaptive genetic variation and local adaptation of the valuable genetic resources. This work was realized within the framework of the project GENCLIM (Evaluating the adaptive potential of the main coniferous species for a sustainable forest management in the context of climate change), financed by the Executive Agency for Higher Education, Research, Development and Innovation Funding, grant number PN-II-PC-PCCA-2013-4-0695.

Genetic conditions of joint Nordic genetic evaluations of lifetime competition performance in warmblood sport horses.

PubMed

Viklund, Å; Furre, S; Eriksson, S; Vangen, O; Philipsson, J

2015-08-01

Breeding programmes for warmblood sport horses are similar in the Nordic countries Sweden, Denmark, Finland and Norway, and stallions of same origin are used. The aim was to investigate whether a joint Nordic genetic evaluation based on lifetime competition performance is feasible and beneficial for breeding competitive sport horses in the Nordic countries. Results for almost 45,000 horses in show jumping and 30,000 horses in dressage were available. The larger populations in Sweden and Denmark contributed with 85% of the results. Heritabilities and genetic correlations between performances in the different countries were estimated, and comparisons of accuracies of estimated breeding values (EBVs) and number of stallions with EBVs based on national or joint data were studied. The heritabilities ranged between 0.25 and 0.42 for show jumping and between 0.14 and 0.55 for dressage. The genetic correlations between competition performances in the Nordic countries were estimated to 0.63-1.00. EBVs based on joint data increased accuracies for EBVs for stallions by 38-81% and increased the number of available stallions with EBVs by 40-288%, compared to EBVs based on national data only. A joint Nordic genetic evaluation for sport horses is recommended. © 2015 Blackwell Verlag GmbH.

Assessment of the value of a genetic risk score in improving the estimation of coronary risk

USDA-ARS?s Scientific Manuscript database

The American Heart Association has established criteria for the evaluation of novel markers of cardiovascular risk. In accordance with these criteria, we assessed the association between a multi-locus genetic risk score (GRS) and incident coronary heart disease (CHD), and evaluated whether this GRS ...

Multiple-trait multiple-country genetic evaluation of Holstein bulls for female fertility and milk production traits.

PubMed

Nilforooshan, M A; Jakobsen, J H; Fikse, W F; Berglund, B; Jorjani, H

2014-06-01

The aim of this study was to investigate the effect of including milk yield data in the international genetic evaluation of female fertility traits to reduce or eliminate a possible bias because of across-country selection for milk yield. Data included two female fertility traits from Great Britain, Italy and the Netherlands, together with milk yield data from the same countries and from the United States, because the genetic trends in other countries may be influenced by selection decisions on bulls in the United States. Potentially, female fertility data had been corrected nationally for within-country selection and management biases for milk yield. Using a multiple-trait multiple across-country evaluation (MT-MACE) for the analysis of female fertility traits with milk yield, across-country selection patterns both for female fertility and milk yield can be considered simultaneously. Four analyses were performed; one single-trait multiple across-country evaluation analysis including only milk yield data, one MT-MACE analysis including only female fertility traits, and one MT-MACE analysis including both female fertility and milk yield traits. An additional MT-MACE analysis was performed including both female fertility and milk yield traits, but excluding the United States. By including milk yield traits to the analysis, female fertility reliabilities increased, but not for all bulls in all the countries by trait combinations. The presence of milk yield traits in the analysis did not considerably change the genetic correlations, genetic trends or bull rankings of female fertility traits. Even though the predicted genetic merits of female fertility traits hardly changed by including milk yield traits to the analysis, the change was not equally distributed to the whole data. The number of bulls in common between the two sets of Top 100 bulls for each trait in the two analyses of female fertility traits, with and without the four milk yield traits and their rank correlations were low, not necessarily because of the absence of the US milk yield data. The joint international genetic evaluation of female fertility traits with milk yield is recommended to make use of information on several female fertility traits from different countries simultaneously, to consider selection decisions for milk yield in the genetic evaluation of female fertility traits for obtaining more accurate estimating breeding values (EBV) and to acquire female fertility EBV for bulls evaluated for milk yield, but not for female fertility.

Creation and Implementation of an Environmental Scan to Assess Cancer Genetics Services at Three Oncology Care Settings.

PubMed

Bednar, Erica M; Walsh, Michael T; Baker, Ellen; Muse, Kimberly I; Oakley, Holly D; Krukenberg, Rebekah C; Dresbold, Cara S; Jenkinson, Sandra B; Eppolito, Amanda L; Teed, Kelly B; Klein, Molly H; Morman, Nichole A; Bowdish, Elizabeth C; Russ, Pauline; Wise, Emaline E; Cooper, Julia N; Method, Michael W; Henson, John W; Grainger, Andrew V; Arun, Banu K; Lu, Karen H

2018-05-16

An environmental scan (ES) is an efficient mixed-methods approach to collect and interpret relevant data for strategic planning and project design. To date, the ES has not been used nor evaluated in the clinical cancer genetics setting. We created and implemented an ES to inform the design of a quality improvement (QI) project to increase the rates of adherence to national guidelines for cancer genetic counseling and genetic testing at three unique oncology care settings (OCS). The ES collected qualitative and quantitative data from reviews of internal processes, past QI efforts, the literature, and each OCS. The ES used a data collection form and semi-structured interviews to aid in data collection. The ES was completed within 6 months, and sufficient data were captured to identify opportunities and threats to the QI project's success, as well as potential barriers to, and facilitators of guideline-based cancer genetics services at each OCS. Previously unreported barriers were identified, including inefficient genetic counseling appointment scheduling processes and the inability to track referrals, genetics appointments, and genetic test results within electronic medical record systems. The ES was a valuable process for QI project planning at three OCS and may be used to evaluate genetics services in other settings.

Industry benefits from recent genetic progress in sheep and beef populations.

PubMed

Amer, P R; Nieuwhof, G J; Pollott, G E; Roughsedge, T; Conington, J; Simm, G

2007-11-01

An analytical model that evaluates the benefits from 10 years of genetic improvement over a 20-year time frame was specified. Estimates of recent genetic trends in recorded traits, industry statistics and published estimates of the economic values of trait changes were used to parameterise the model for the UK sheep and beef industries. Despite rates of genetic change in the relevant performance-recorded breeding populations being substantially less than theoretical predictions, the financial benefits of genetic change were substantial. Over 20 years, the benefits from 10 years of genetic progress at recently achieved rates in recorded hill sheep, sheep crossing sire and sheep terminal sire breeding programmes was estimated to be £5.3, £1.0 and £11.5 million, respectively. If dissemination of genetic material is such that these rates of change are also realised across the entire ram breeding industry, the combined benefits would be £110.8 million. For beef cattle, genetic evaluation systems have been operating within all the major breeds for some years with quite widespread use of performance recording, and so genetic trends within the beef breeds were used as predictors of industry genetic change. Benefits from 10 years of genetic progress at recent rates of change, considering a 20-year time frame, in terminal sire beef breeds are expected to be £4.9 million. Benefits from genetic progress for growth and carcass characters in dual-purpose beef breeds were £18.2 million after subtraction of costs associated with a deterioration in calving traits. These benefits may be further offset by unfavourable associated changes in maternal traits. Additional benefits from identification and use of the best animals available from the breeding sector for commercial matings through performance recording and genetic evaluation could not be quantified. When benefits of genetic improvement were expressed on an annual present value basis and compared with lagged annual investment costs to achieve it, the internal rate of return (IRR) on the combined investment in sheep and beef cattle was 32%. Despite a much higher rate of participation in performance recording, the present value of benefits and the IRR were lower for beef cattle than for sheep. The implications of these results for future national and industry investment in genetic improvement infrastructure were discussed.

Prediction of Breeding Values for Dairy Cattle Using Artificial Neural Networks and Neuro-Fuzzy Systems

PubMed Central

Shahinfar, Saleh; Mehrabani-Yeganeh, Hassan; Lucas, Caro; Kalhor, Ahmad; Kazemian, Majid; Weigel, Kent A.

2012-01-01

Developing machine learning and soft computing techniques has provided many opportunities for researchers to establish new analytical methods in different areas of science. The objective of this study is to investigate the potential of two types of intelligent learning methods, artificial neural networks and neuro-fuzzy systems, in order to estimate breeding values (EBV) of Iranian dairy cattle. Initially, the breeding values of lactating Holstein cows for milk and fat yield were estimated using conventional best linear unbiased prediction (BLUP) with an animal model. Once that was established, a multilayer perceptron was used to build ANN to predict breeding values from the performance data of selection candidates. Subsequently, fuzzy logic was used to form an NFS, a hybrid intelligent system that was implemented via a local linear model tree algorithm. For milk yield the correlations between EBV and EBV predicted by the ANN and NFS were 0.92 and 0.93, respectively. Corresponding correlations for fat yield were 0.93 and 0.93, respectively. Correlations between multitrait predictions of EBVs for milk and fat yield when predicted simultaneously by ANN were 0.93 and 0.93, respectively, whereas corresponding correlations with reference EBV for multitrait NFS were 0.94 and 0.95, respectively, for milk and fat production. PMID:22991575

The Case of the "Tainted" Taco Shells: A Case Study on Genetically Modified Foods

ERIC Educational Resources Information Center

Taylor, Ann T. S.

2004-01-01

This case study introduces students to the use of genetically modified foods. Students learn how genetically modified plants are made, and then they read primary literature papers to evaluate the environmental, economic, and health issues. (Contains 2 figures.)

Genetic diversity provides opportunities for improvement of fresh-cut pepper quality

USDA-ARS?s Scientific Manuscript database

Extensive genetic diversity present in the Capsicum genepool has been utilized extensively to improve pepper disease resistance, fruit quality and varied yield attributes. Little attention has been dedicated to genetic enhancement of pepper fresh-cut quality. We evaluated pepper accessions with dive...

A model of genetic guidance for hemoglobinopathy patients and laboratory diagnosis of family members as educational and preventive measures

PubMed Central

Ferreira, Tatiana Dela-Sávia; Freire, Adriana Sousa; Silveira-Lacerda, Elisângela de Paula; García-Zapata, Marco Túlio Antônio

2012-01-01

Background: The high frequency of hemoglobinopathies in Brazil constitutes a public health problem and thus educational and preventive measures are necessary to reduce the incidence. Genetic guidance, a modality of genetic counseling, and family screening are measures that can assist in reproductive decisions and mitigate clinical, psychological and social problems of families with these disorders. Objetive: The objective of the current study was to evaluate the effectiveness of educational and preventive measures for hemoglobinopathies using genetic guidance and laboratory screening of families. Methods: The diagnoses of patients with hemoglobinopathies were confirmed and then the level of knowledge about their disease was evaluated and genetic guidance was provided. Three months later, the level of assimilated information of these patients was evaluated. In addition, laboratory diagnosis of family members was carried out. Results: Diagnosis of sickle cell anemia was confirmed for most patients. Moreover, the majority of the patients who had a low level of knowledge before genetic guidance (68.8%) demonstrated a higher level of assimilated information after the process (81.8%). Almost 70% of the family members had hemoglobin changes and some had hemoglobinopathies(2.6%). They were duly informed about the results of the examinations, which made it possible to investigate further. Conclusion: Genetic guidance and family screening were effective preventive and educational measures that improved the quality of life of patients, preventing complications and sequels and allowed the referral of those who may transmit altered genes for clinical diagnosis and to genetic counseling services. PMID:23125541

Analysis of competition performance in dressage and show jumping of Dutch Warmblood horses.

PubMed

Rovere, G; Ducro, B J; van Arendonk, J A M; Norberg, E; Madsen, P

2016-12-01

Most Warmblood horse studbooks aim to improve the performance in dressage and show jumping. The Dutch Royal Warmblood Studbook (KWPN) includes the highest score achieved in competition by a horse to evaluate its genetic ability of performance. However, the records collected during competition are associated with some aspects that might affect the quality of the genetic evaluation based on these records. These aspects include the influence of rider, censoring and preselection of the data. The aim of this study was to quantify the impact of rider effect, censoring and preselection on the genetic analysis of competition data of dressage and show jumping of KWPN. Different models including rider effect were evaluated. To assess the impact of censoring, genetic parameters were estimated in data sets that differed in the degree of censoring. The effect of preselection on variance components was analysed by defining a binary trait (sport-status) depending on whether the horse has a competition record or not. This trait was included in a bivariate model with the competition trait and used all horses registered by KWPN since 1984. Results showed that performance in competition for dressage and show jumping is a heritable trait (h 2 ~ 0.11-0.13) and that it is important to account for the effect of rider in the genetic analysis. Censoring had a small effect on the genetic parameter for highest performance achieved by the horse. A moderate heritability obtained for sport-status indicates that preselection has a genetic basis, but the effect on genetic parameters was relatively small. © 2016 Blackwell Verlag GmbH.

Current practices of commercial cryobanks in screening prospective donors for genetic disease and reproductive risk.

PubMed

Conrad, E A; Fine, B; Hecht, B R; Pergament, E

1996-01-01

To determine how the screening practices of commercial semen banks vary from published guidelines, which factors influence cryobanks to exclude prospective semen donors for genetic reasons, and the current role of clinical geneticists/genetic counselors in evaluating prospective semen donors. The genetic screening of prospective donors by commercial semen banks was evaluated using written questionnaires completed by bank directors. Responses were analyzed to determine exclusion criteria, adherence to published guidelines, and contribution of genetic professionals. Semen banks were selected on the basis of membership in the American Association of Tissue Banks and commercial use of semen for artificial insemination by donor. Semen bank practices as reported by commercial semen bank directors. Of 37 eligible banks, 16 responded. All screen prospective donors by medical/family history and physical examination, 94% have upper age limits; 63% examine for minor physical defects; 56% routinely karyotype; 81% screen men of ethnic groups at risk for Tay Sachs disease, sickle cell disease and thalassemia; 19% screen all donors; 25% screen all donors for cystic fibrosis and 50% only screen if family history positive. Donor rejection was based on three criteria: mode of inheritance of familial disorder, severity of disease, and availability of carrier/confirmatory testing of donor genotype. Ten of 16 banks have no genetic professional on staff. Commercial semen banks primarily rely on family history as the major exclusion criterion in genetic screening of donors. Considerable differences exist among semen bank practices in accordance with guidelines published by national agencies. Genetic professionals have a minimal effect overall on evaluation of semen donors.

Genetic evaluations for growth heat tolerance in Angus cattle.

PubMed

Bradford, H L; Fragomeni, B O; Bertrand, J K; Lourenco, D A L; Misztal, I

2016-10-01

The objectives were to assess the impact of heat stress and to develop a model for genetic evaluation of growth heat tolerance in Angus cattle. The American Angus Association provided weaning weight (WW) and yearling weight (YW) data, and records from the Upper South region were used because of the hot climatic conditions. Heat stress was characterized by a weaning (yearling) heat load function defined as the mean temperature-humidity index (THI) units greater than 75 (70) for 30 (150) d prior to the weigh date. Therefore, a weaning (yearling) heat load of 5 units corresponded to 80 (75) for the corresponding period prior to the weigh date. For all analyses, 82,669 WW and 69,040 YW were used with 3 ancestral generations in the pedigree. Univariate models were a proxy for the Angus growth evaluation, and reaction norms using 2 B-splines for heat load were fit separately for weaning and yearling heat loads. For both models, random effects included direct genetic, maternal genetic, maternal permanent environment (WW only), and residual. Fixed effects included a linear age covariate, age-of-dam class (WW only), and contemporary group for both models and fixed regressions on the B-splines in the reaction norm. Direct genetic correlations for WW were strong for modest heat load differences but decreased to less than 0.50 for large differences. Reranking of proven sires occurred for only WW direct effects for the reaction norms with extreme heat load differences. Conversely, YW results indicated little effect of heat stress on genetic merit. Therefore, weaning heat tolerance was a better candidate for developing selection tools. Maternal heritabilities were consistent across heat loads, and maternal genetic correlations were greater than 0.90 for nearly all heat load combinations. No evidence existed for a genotype × environment interaction for the maternal component of growth. Overall, some evidence exists for phenotypic plasticity for the direct genetic effects of WW, but traditional national cattle evaluations are likely adequately ranking sires for nonextreme environmental conditions.

Diagnosing Autism in Individuals with Known Genetic Syndromes: Clinical Considerations and Implications for Intervention

PubMed Central

Hepburn, Susan L.; Moody, Eric J.

2015-01-01

Assessing symptoms of autism in persons with known genetic syndromes associated with intellectual and/or developmental disability is a complex clinical endeavor. We suggest that a developmental approach to evaluation is essential to reliably teasing apart global impairments from autism-specific symptomology. In this chapter, we discuss our assumptions about autism spectrum disorders, the process of conducting a family-focused, comprehensive evaluation with behaviorally complex children and some implications for intervention in persons with co-occurring autism and known genetic syndromes. PMID:26269783

Genetic evaluation of aspects of temperament in Nellore-Angus calves.

PubMed

Riley, D G; Gill, C A; Herring, A D; Riggs, P K; Sawyer, J E; Lunt, D K; Sanders, J O

2014-08-01

The objective of this work was to estimate heritability of each of 5 subjectively measured aspects of temperament of cattle and the genetic correlations of pairs of those traits. From 2003 to 2013, Nellore-Angus F2 and F3 calves (n = 1,816) were evaluated for aspects of temperament at an average 259 d of age, which was approximately 2 mo after weaning. Calves were separated from a group and subjectively scored from 1 (calm, good temperament) to 9 (wild, poor temperament) for aggressiveness (willingness to hit an evaluator), nervousness, flightiness, gregariousness (willingness to separate from the group), and a distinct overall score by 4 evaluators. Data were analyzed using threshold and linear models with additive genetic random effects. Two-trait animal models (nonthreshold) included the additive genetic covariance for pairs of traits and were used to estimate additive genetic correlations. Contemporary groups (n = 104) represented calves penned together for evaluation on given evaluation days. Heifers had greater (worse) means for all traits than steers (P < 0.05). The regression of score on age in days was included in final models for flightiness (P = 0.05; -0.006 ± 0.003) and gregariousness (P = 0.025; -0.007 ± 0.003). Estimates of heritability were large (0.51, 0.4, 0.45, 0.49, and 0.47 for aggressiveness, nervousness, flightiness, gregariousness, and overall temperament, respectively; SE = 0.07 for each). The ability to use this methodology to distinctly separate different aspects of calf temperament appeared to be limited, as estimates of additive genetic correlations were near unity for all pairs of traits; estimates of phenotypic correlation ranged from 0.88 ± 0.01 to 0.99 ± 0.002 for pairs of traits. Distinct subsequent analyses indicated a significant negative relationship of 4 of the various temperament scores with weight at weaning (regression coefficients ranged from -0.008 ± 0.002 for nervousness, flightiness, and gregariousness to -0.003 ± 0.002 for aggressiveness). In subsequent analyses, the regression of temperament trait on sequence of evaluation within a pen was highly significant and solutions ranged from 0.05 ± 0.007 for aggressiveness to 0.08 ± 0.007 for all other traits. The apparent large additive genetic variance for any one of these traits may be useful in identification of genes responsible for differences in cattle temperament.

Discordant genetic diversity and geographic patterns between Crassicutis cichlasomae (Digenea: Apocreadiidae) and its cichlid host, "Cichlasoma" urophthalmus (Osteichthyes: Cichlidae), in Middle-America.

PubMed

Razo-Mendivil, Ulises; Vázquez-Domínguez, Ella; de León, Gerardo Pérez-Ponce

2013-12-01

Genetic analyses of hosts and their parasites are key to understand the evolutionary patterns and processes that have shaped host-parasite associations. We evaluated the genetic structure of the digenean Crassicutis cichlasomae and its most common host, the Mayan cichlid "Cichlasoma" urophthalmus, encompassing most of their geographical range in Middle-America (river basins in southeastern Mexico, Belize, and Guatemala together with the Yucatan Peninsula). Genetic diversity and structure analyses were done based on 167 cytochrome c oxidase subunit 1 sequences (330 bp) for C. cichlasomae from 21 populations and 161 cytochrome b sequences (599 bp) for "C." urophthalmus from 26 populations. Analyses performed included phylogenetic tree estimation under Bayesian inference and maximum likelihood analysis, genetic diversity, distance and structure estimates, haplotype networks, and demographic evaluations. Crassicutis cichlasomae showed high genetic diversity values and genetic structuring, corresponding with 4 groups clearly differentiated and highly divergent. Conversely, "C." urophthalmus showed low levels of genetic diversity and genetic differentiation, defined as 2 groups with low divergence and with no correspondence with geographical distribution. Our results show that species of cichlids parasitized by C. cichlasomae other than "C." urophthalmus, along with multiple colonization events and subsequent isolation in different basins, are likely factors that shaped the genetic structure of the parasite. Meanwhile, historical long-distance dispersal and drought periods during the Holocene, with significant population size reductions and fragmentations, are factors that could have shaped the genetic structure of the Mayan cichlid.

A fine structure genetic analysis evaluating ecoregional adaptability of a Bos taurus breed (Hereford)

USDA-ARS?s Scientific Manuscript database

Ecoregional differences contribute to genetic environmental interactions and impact animal performance. These differences may become more important under climate change scenarios. Utilizing genetic diversity within a species to address such problems has not been fully explored. In this study Herefor...

QUANTITATIVE GENETIC ACTIVITY GRAPHICAL PROFILES FOR USE IN CHEMICAL EVALUATION

EPA Science Inventory

A graphic approach termed a Genetic Activity Profile (GAP) has been developed to display a matrix of data on the genetic and related effects of selected chemical agents. he profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each...

A Test of Genetic Algorithms in Relevance Feedback.

ERIC Educational Resources Information Center

Lopez-Pujalte, Cristina; Guerrero Bote, Vicente P.; Moya Anegon, Felix de

2002-01-01

Discussion of information retrieval, query optimization techniques, and relevance feedback focuses on genetic algorithms, which are derived from artificial intelligence techniques. Describes an evaluation of different genetic algorithms using a residual collection method and compares results with the Ide dec-hi method (Salton and Buckley, 1990…

Untapped genetic variability in Herefords: implications for climate change

USDA-ARS?s Scientific Manuscript database

Global climate change (CC) has the potential to significantly alter US cattle productivity. As a result, the creation of genetic resources for a specific environment may be necessary, given that genetic-environmental interactions are present and may become more important. Molecular evaluation of a s...

Genetic diversity in a Poincianella pyramidalis (Tul.) L.P. Queiroz population assessed by RAPD molecular markers.

PubMed

Belarmino, K S; Rêgo, M M; Bruno, R L A; Medeiros, G D A; Andrade, A P; Rêgo, E R

2017-08-31

Poincianella pyramidalis (Tul.) L.P. Queiroz is an endemic Caatinga (Brazilian savannah biome) species that has been exploited for different purposes, although information is necessary about still existing natural populations. The objective of this study was to evaluate the genetic diversity among 20 P. pyramidalis individuals occurring in a population localized in the Caatinga biome of Paraíba State, aiming at seed collection, using RAPD markers. For the DNA extraction, young shoots of the individuals were used, and amplification was carried out using 20 primers. The obtained markers were converted to a binary matrix, from which a genetic dissimilarity matrix was built using the arithmetic complement of Jaccard's coefficient, and the dendrogram was built by the UPGMA analysis. No amplified fragment was monomorphic, resulting in 100% polymorphism of the analyzed population. The mean genetic diversity among the matrices was 63.28%, ranging from 30.9 to 97.7%. Individuals 09 and 17 showed relevant genetic proximity, and thus planting their seedlings at close sites would not be indicated. The population evaluated in this study showed high genetic diversity, originating twelve groups from the UPGMA hierarchical cluster analysis. Based on the results, individuals 09 and 17 can provide plant material for the evaluation of the physiological performance of P. pyramidalis seeds, and the set of individuals of this population has a high genetic diversity that characterizes them as adequate matrices for projects of restoration and conservation of the seed species.

The Case against Preadoption Genetic Testing.

ERIC Educational Resources Information Center

Freundlich, Madelyn D.

1998-01-01

Examines the medical, psychosocial, and ethical considerations concerning presymptomatic genetic testing in evaluating children for adoption. Offers an ethical framework for rejecting such a practice. (JPB)

Dominance genetic and maternal effects for genetic evaluation of egg production traits in dual-purpose chickens.

PubMed

Jasouri, M; Zamani, P; Alijani, S

2017-10-01

1. A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared. 2. Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits. 3. Estimates of heritability (h 2 ) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28-32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d 2 ) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m 2 ) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c 2 ) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30. 4. Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and environmental) and, to a lesser extent, direct dominance genetic effect would improve the accuracy of genetic evaluation for early age body weights in dual-purpose chickens.

The knowledge value-chain of genetic counseling for breast cancer: an empirical assessment of prediction and communication processes.

PubMed

Amara, Nabil; Blouin-Bougie, Jolyane; Jbilou, Jalila; Halilem, Norrin; Simard, Jacques; Landry, Réjean

2016-01-01

The aim of this paper is twofold: to analyze the genetic counseling process for breast cancer with a theoretical knowledge transfer lens and to compare generalists, medical specialists, and genetic counselors with regards to their genetic counseling practices. This paper presents the genetic counseling process occurring within a chain of value-adding activities of four main stages describing health professionals' clinical practices: (1) evaluation, (2) investigation, (3) information, and (4) decision. It also presents the results of a cross-sectional study based on a Canadian medical doctors and genetic counselors survey (n = 176) realized between July 2012 and March 2013. The statistical exercise included descriptive statistics, one-way ANOVA and post-hoc tests. The results indicate that even though all types of health professionals are involved in the entire process of genetic counseling for breast cancer, genetic counselors are more involved in the evaluation of breast cancer risk, while medical doctors are more active in the decision toward breast cancer risk management strategies. The results secondly demonstrate the relevance and the key role of genetic counselors in the care provided to women at-risk of familial breast cancer. This paper presents an integrative framework to understand the current process of genetic counseling for breast cancer in Canada, and to shed light on how and where health professionals contribute to the process. It also offers a starting point for assessing clinical practices in genetic counseling in order to establish more clearly where and to what extent efforts should be undertaken to implement future genetic services.

News Media Use, Informed Issue Evaluation, and South Koreans' Support for Genetically Modified Foods

ERIC Educational Resources Information Center

Kim, Sei-Hill; Kim, Jeong-Nam; Choi, Doo-Hun; Jun, Sangil

2015-01-01

Analyzing survey data on the issue of genetically modified foods in South Korea, this study explores the role of news media in facilitating informed issue evaluation. Respondents who read a newspaper more often were more knowledgeable about the issue. Also, heavy newspaper readers were more able than light readers to hold "consistent"…

World distribution of female flight and genetic variation in Lymantria dispar (Lepidoptera: Lymantriidae)

Treesearch

M.A. Keena; M.-J. Cote; P.S. Grinberg; W.E. Wallner

2008-01-01

Female gypsy moths, Lymantria dispar L., from 46 geographic strains were evaluated for flight capability and related traits. Males from 31 of the same strains were evaluated for genetic diversity using two polymorphic cytochrome oxidase I mitochondrial DNA restriction sites, the nuclear FS1 marker, and four microsatellite loci. Females capable of...

CLINICAL APPROACH TO THE DIAGNOSTIC EVALUATION OF HERDITARY AND ACQUIRED NEUROMUSCULAR DISEASES

PubMed Central

McDonald, Craig M.

2012-01-01

SYNOPSIS In the context of a neuromuscular disease diagnostic evaluation, the clinician still must be able to obtain a relevant patient and family history and perform focused general, musculoskeletal, neurologic and functional physical examinations to direct further diagnostic evaluations. Laboratory studies for hereditary neuromuscular diseases include relevant molecular genetic studies. The EMG and nerve conduction studies remain an extension of the physical examination and help to guide further diagnostic studies such as molecular genetic studies, and muscle and nerve biopsies. All diagnostic information needs to be interpreted not in isolation, but within the context of relevant historical information, family history, physical examination findings, and laboratory data, electrophysiologic findings, pathologic findings, and molecular genetic findings if obtained. PMID:22938875

Evaluation of Genetic Algorithm Concepts using Model Problems. Part 1; Single-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge.

Spurious correlations and inference in landscape genetics

Treesearch

Samuel A. Cushman; Erin L. Landguth

2010-01-01

Reliable interpretation of landscape genetic analyses depends on statistical methods that have high power to identify the correct process driving gene flow while rejecting incorrect alternative hypotheses. Little is known about statistical power and inference in individual-based landscape genetics. Our objective was to evaluate the power of causalmodelling with partial...

Genetic analysis without replications: Model evaluation and application in spring wheat

USDA-ARS?s Scientific Manuscript database

Genetic data collected from plant breeding and genetic studies may not be replicated in field designs even though field variation is present. In this study, we addressed this problem using spring wheat (Triticum eastivum L.) trial data collected from two locations. There were no intra-location repl...

Genetic analysis of teosinte alleles for kernel composition traits in maize

USDA-ARS?s Scientific Manuscript database

Teosinte (Zea mays ssp. parviglumis) is the wild ancestor of modern maize (Zea mays ssp. mays). Teosinte contains greater genetic diversity compared to maize inbreds and landraces, but its use is limited by insufficient genetic resources to evaluate its value. A population of teosinte near isogenic ...

Genetic Analysis of Termite Colonies in Wisconsin

Treesearch

R.A. Arango; D.A. Marschalek; F. Green III; K.F. Raffa; M.E. Berres

2015-01-01

The objective of this study was to document current areas of subterranean termite activity in Wisconsin and to evaluate genetic characteristics of these northern, peripheral colonies. Here, amplified fragment-length polymorphism was used to characterize levels of inbreeding, expected heterozygosity, and percent polymorphism within colonies as well as genetic structure...

Low genetic diversity contrasts with high phenotypic variability in heptaploid Spartina densiflora populations invading the Pacific Coast of North America

USDA-ARS?s Scientific Manuscript database

Species can respond to environmental pressures through genetic and epigenetic changes and through phenotypic plasticity, but few studies have evaluated the relationships between genetic differentiation and phenotypic plasticity of plant species along changing environmental conditions such as through...

Genetic parameters and breeding strategies for high levels of iron and zinc in Phaseolus vulgaris L.

PubMed

Martins, S M; Melo, P G S; Faria, L C; Souza, T L P O; Melo, L C; Pereira, H S

2016-06-10

One of the current focus of common bean breeding programs in Brazil is to increase iron (FeC) and zinc content (ZnC) in grains. The objectives of this study were to estimate genetic parameters for FeC and ZnC in common bean, verify the need for conducting multi-site evaluation tests, identify elite lines that combine high FeC and ZnC with good adaptability, stability, and agronomic potential, and examine the genetic association between FeC and ZnC. Elite lines (140) were evaluated for important agronomic traits in multiple environments. In one trial, FeC and ZnC were evaluated and genetic parameters were estimated. Based on the high heritability estimates and significant selection gains obtained, the conditions for a successful selection was favorable. Of the 140 evaluated lines, 17 had higher FeC and ZnC, and were included in the validation test (2013, five environments), specifically for the evaluation of FeC and ZnC. The line by environment interaction for FeC and ZnC was detected, but it was predominantly simple. The environmental effect strongly influenced FeC and ZnC . The environment Brasília/rainy season was selected as the best evaluation site for preliminary tests for FeC and ZnC, because it resulted in similar conclusions as the mean of the five environments. The lines CNFP 15701 and CNFC 15865 had higher FeC and ZnC and were highly adaptable and stable, and are recommended for utilization in breeding programs. The lines CNFC 15833, CNFC 15703, and CNFP 15676 showed excellent combined agronomic and nutritional traits, and were selected for the development of biofortified cultivars. Additionally, the genetic association between FeC and ZnC was detected.

Utility of Post-Mortem Genetic Testing in Cases of Sudden Arrhythmic Death Syndrome.

PubMed

Lahrouchi, Najim; Raju, Hariharan; Lodder, Elisabeth M; Papatheodorou, Efstathios; Ware, James S; Papadakis, Michael; Tadros, Rafik; Cole, Della; Skinner, Jonathan R; Crawford, Jackie; Love, Donald R; Pua, Chee J; Soh, Bee Y; Bhalshankar, Jaydutt D; Govind, Risha; Tfelt-Hansen, Jacob; Winkel, Bo G; van der Werf, Christian; Wijeyeratne, Yanushi D; Mellor, Greg; Till, Jan; Cohen, Marta C; Tome-Esteban, Maria; Sharma, Sanjay; Wilde, Arthur A M; Cook, Stuart A; Bezzina, Connie R; Sheppard, Mary N; Behr, Elijah R

2017-05-02

Sudden arrhythmic death syndrome (SADS) describes a sudden death with negative autopsy and toxicological analysis. Cardiac genetic disease is a likely etiology. This study investigated the clinical utility and combined yield of post-mortem genetic testing (molecular autopsy) in cases of SADS and comprehensive clinical evaluation of surviving relatives. We evaluated 302 expertly validated SADS cases with suitable DNA (median age: 24 years; 65% males) who underwent next-generation sequencing using an extended panel of 77 primary electrical disorder and cardiomyopathy genes. Pathogenic and likely pathogenic variants were classified using American College of Medical Genetics (ACMG) consensus guidelines. The yield of combined molecular autopsy and clinical evaluation in 82 surviving families was evaluated. A gene-level rare variant association analysis was conducted in SADS cases versus controls. A clinically actionable pathogenic or likely pathogenic variant was identified in 40 of 302 cases (13%). The main etiologies established were catecholaminergic polymorphic ventricular tachycardia and long QT syndrome (17 [6%] and 11 [4%], respectively). Gene-based rare variants association analysis showed enrichment of rare predicted deleterious variants in RYR2 (p = 5 × 10 -5 ). Combining molecular autopsy with clinical evaluation in surviving families increased diagnostic yield from 26% to 39%. Molecular autopsy for electrical disorder and cardiomyopathy genes, using ACMG guidelines for variant classification, identified a modest but realistic yield in SADS. Our data highlighted the predominant role of catecholaminergic polymorphic ventricular tachycardia and long QT syndrome, especially the RYR2 gene, as well as the minimal yield from other genes. Furthermore, we showed the enhanced utility of combined clinical and genetic evaluation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A complex scenario of tuberculosis transmission is revealed through genetic and epidemiological surveys in Porto.

PubMed

Rito, Teresa; Matos, Carlos; Carvalho, Carlos; Machado, Henrique; Rodrigues, Gabriela; Oliveira, Olena; Ferreira, Eduarda; Gonçalves, Jorge; Maio, Lurdes; Morais, Clara; Ramos, Helena; Guimarães, João Tiago; Santos, Catarina L; Duarte, Raquel; Correia-Neves, Margarida

2018-01-25

Tuberculosis (TB) incidence is decreasing worldwide and eradication is becoming plausible. In low-incidence countries, intervention on migrant populations is considered one of the most important strategies for elimination. However, such measures are inappropriate in European areas where TB is largely endemic, such as Porto in Portugal. We aim to understand transmission chains in Porto through a genetic characterization of Mycobacterium tuberculosis strains and through a detailed epidemiological evaluation of cases. We genotyped the M. tuberculosis strains using the MIRU-VNTR system. We performed an evolutionary reconstruction of the genotypes with median networks, used in this context for the first time. TB cases from a period of two years were evaluated combining genetic, epidemiological and georeferencing information. The data reveal a unique complex scenario in Porto where the autochthonous population acts as a genetic reservoir of M. tuberculosis diversity with discreet episodes of transmission, mostly undetected using classical epidemiology alone. Although control policies have been successful in decreasing incidence in Porto, the discerned complexity suggests that, for elimination to be a realistic goal, strategies need to be adjusted and coupled with a continuous genetic characterization of strains and detailed epidemiological evaluation, in order to successfully identify and interrupt transmission chains.

Short communication: Estimates of genetic parameters for dairy fertility in New Zealand.

PubMed

Amer, P R; Stachowicz, K; Jenkins, G M; Meier, S

2016-10-01

Reproductive performance of dairy cows in a seasonal calving system is especially important as cows are required to achieve a 365-d calving interval. Prior research with a small data set has identified that the genetic evaluation model for fertility could be enhanced by replacing the binary calving rate trait (CR42), which gives the probability of a cow calving within the first 42d since the planned start of calving at second, third, and fourth calving, with a continuous version, calving season day (CSD), including a heifer calving season day trait expressed at first calving, removing milk yield, retaining a probability of mating trait (PM21) which gives the probability of a cow being mated within the first 21d from the planned start of mating, and first lactation body condition score (BCS), and including gestation length (GL). The aim of this study was to estimate genetic parameters for the proposed new model using a larger data set and compare these with parameters used in the current system. Heritability estimates for CSD and PM21 ranged from 0.013 to 0.019 and from 0.031 to 0.058, respectively. For the 2 traits that correspond with the ones used in the current genetic evaluation system (mating trait, PM21 and BCS) genetic correlations were lower in this study compared with previous estimates. Genetic correlations between CSD and PM21 across different parities were also lower than the correlations between CR42 and PM21 reported previously. The genetic correlation between heifer CSD and CSD in first parity was 0.66. Estimates of genetic correlations of BCS with CSD were higher than those with PM21. For GL, direct heritability was estimated to be 0.67, maternal heritability was 0.11, and maternal repeatability was 0.22. Direct GL had moderate to high and favorable genetic correlations with evaluated fertility traits, whereas corresponding residual correlations remain low, which makes GL a useful candidate predictor trait for fertility in a multiple trait evaluation. The superiority of direct GL genetic component over the maternal GL component for predicting fertility was demonstrated. Future work planned in this area includes the implementation and testing of this new model on national fertility data. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Evaluation of the Affymetrix CytoScan® Dx Assay for Developmental Delay

PubMed Central

Webb, Bryn D.; Scharf, Rebecca J.; Spear, Emily A.; Edelmann, Lisa J.; Stroustrup, Annemarie

2015-01-01

The goal of molecular cytogenetic testing for children presenting with developmental delay is to identify or exclude genetic abnormalities that are associated with cognitive, behavioral, and/or motor symptoms. Until 2010, chromosome analysis was the standard first-line genetic screening test for evaluation of patients with developmental delay when a specific syndrome was not suspected. In 2010, The American College of Medical Genetics and several other groups recommended chromosomal microarray (CMA) as the first-line test in children with developmental delays, multiple congenital anomalies, and/or autism. This test is able to detect regions of genomic imbalances at a much finer resolution than G-banded karyotyping. Until recently, no CMA testing had been approved by the United States Food and Drug Administration (FDA). This review will focus on the use of the Affymetrix CytoScan® Dx Assay, the first CMA to receive FDA approval for the genetic evaluation of individuals with developmental delay. PMID:25350348

Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

Development and Evaluation of Event-Specific Quantitative PCR Method for Genetically Modified Soybean MON87701.

PubMed

Tsukahara, Keita; Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Nishimaki-Mogami, Tomoko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2016-01-01

A real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event, MON87701. First, a standard plasmid for MON87701 quantification was constructed. The conversion factor (C f ) required to calculate the amount of genetically modified organism (GMO) was experimentally determined for a real-time PCR instrument. The determined C f for the real-time PCR instrument was 1.24. For the evaluation of the developed method, a blind test was carried out in an inter-laboratory trial. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr), respectively. The determined biases and the RSDr values were less than 30 and 13%, respectively, at all evaluated concentrations. The limit of quantitation of the method was 0.5%, and the developed method would thus be applicable for practical analyses for the detection and quantification of MON87701.

Regulatory science requirements of labeling of genetically modified food.

PubMed

Moghissi, A Alan; Jaeger, Lisa M; Shafei, Dania; Bloom, Lindsey L

2018-05-01

This paper provides an overview of the evolution of food labeling in the USA. It briefly describes the three phases of agricultural development consisting of naturally occurring, cross-bred, and genetically engineered, edited or modified crops, otherwise known as Genetically Modified Organisms (GMO). It uses the Best Available Regulatory Science (BARS) and Metrics for Evaluation of Regulatory Science Claims (MERSC) to evaluate the scientific validity of claims applicable to GMO and the Best Available Public Information (BAPI) to evaluate the pronouncements by public media and others. Subsequently claims on health risk, ecological risk, consumer choice, and corporate greed are evaluated based on BARS/MERSC and BAPI. The paper concludes by suggesting that labeling of food containing GMO should consider the consumer's choice, such as the food used by those who desire kosher and halal food. Furthermore, the consumer choice is already met by the exclusion of GMO in organic food.

Efficient genetic algorithms using discretization scheduling.

PubMed

McLay, Laura A; Goldberg, David E

2005-01-01

In many applications of genetic algorithms, there is a tradeoff between speed and accuracy in fitness evaluations when evaluations use numerical methods with varying discretization. In these types of applications, the cost and accuracy vary from discretization errors when implicit or explicit quadrature is used to estimate the function evaluations. This paper examines discretization scheduling, or how to vary the discretization within the genetic algorithm in order to use the least amount of computation time for a solution of a desired quality. The effectiveness of discretization scheduling can be determined by comparing its computation time to the computation time of a GA using a constant discretization. There are three ingredients for the discretization scheduling: population sizing, estimated time for each function evaluation and predicted convergence time analysis. Idealized one- and two-dimensional experiments and an inverse groundwater application illustrate the computational savings to be achieved from using discretization scheduling.

Routine Discovery of Complex Genetic Models using Genetic Algorithms

PubMed Central

Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.

2010-01-01

Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983

Restoration over time and sustainability of Schinus terebinthifolius Raddi.

PubMed

Álvares-Carvalho, S V; Silva-Mann, R; Gois, I B; Melo, M F V; Oliveira, A S; Ferreira, R A; Gomes, L J

2017-05-31

The success of recovery programs on degraded areas is dependent on the genetic material to be used, which should present heterozygosity and genetic diversity in native and recovered populations. This study was carried out to evaluate the model efficiency to enable the recovery of a degraded area of the Lower São Francisco, Sergipe, Brazil. The target species for this study was Schinus terebinthifolius Raddi. Three populations were analyzed, the recovered area, seed-tree source population, and native tree population border established to the recovered area. The random amplified polymorphic DNA (RAPD) markers were used for diversity analysis. Genetic structure was estimated to evaluate the level of genetic variability existent in each population. There was no correlation between the spatial distribution and the genetic distances for all trees of the recovered area. The heterozygosity present in the recovered population was higher than the native tree population. The seed-tree source population presents genetic bottlenecks. Three clusters were suggested (ΔK = 3) with non-genetic structure. High intra-population genetic variability and inter-population differentiation are present. However, gene flow may also introduce potentially adaptive alleles in the populations of the recovered area, and the native population is necessary to ensure the sustainability and maintenance of the populations by allelic exchange.

Using population genetic tools to develop a control strategy for feral cats (Felis catus) in Hawai'i

USGS Publications Warehouse

Hansen, H.; Hess, S.C.; Cole, D.; Banko, P.C.

2007-01-01

Population genetics can provide information about the demographics and dynamics of invasive species that is beneficial for developing effective control strategies. We studied the population genetics of feral cats on Hawai'i Island by microsatellite analysis to evaluate genetic diversity and population structure, assess gene flow and connectivity among three populations, identify potential source populations, characterise population dynamics, and evaluate sex-biased dispersal. High genetic diversity, low structure, and high number of migrants per generation supported high gene flow that was not limited spatially. Migration rates revealed that most migration occurred out of West Mauna Kea. Effective population size estimates indicated increasing cat populations despite control efforts. Despite high gene flow, relatedness estimates declined significantly with increased geographic distance and Bayesian assignment tests revealed the presence of three population clusters. Genetic structure and relatedness estimates indicated male-biased dispersal, primarily from Mauna Kea, suggesting that this population should be targeted for control. However, recolonisation seems likely, given the great dispersal ability that may not be inhibited by barriers such as lava flows. Genetic monitoring will be necessary to assess the effectiveness of future control efforts. Management of other invasive species may benefit by employing these population genetic tools. ?? CSIRO 2007.

Concerns about cancer risk and experiences with genetic testing in a diverse population of patients with breast cancer.

PubMed

Jagsi, Reshma; Griffith, Kent A; Kurian, Allison W; Morrow, Monica; Hamilton, Ann S; Graff, John J; Katz, Steven J; Hawley, Sarah T

2015-05-10

To evaluate preferences for and experiences with genetic testing in a diverse cohort of patients with breast cancer identified through population-based registries, with attention to differences by race/ethnicity. We surveyed women diagnosed with nonmetastatic breast cancer from 2005 to 2007, as reported to the SEER registries of metropolitan Los Angeles and Detroit, about experiences with hereditary risk evaluation. Multivariable models evaluated correlates of a strong desire for genetic testing, unmet need for discussion with a health care professional, and receipt of testing. Among 1,536 patients who completed the survey, 35% expressed strong desire for genetic testing, 28% reported discussing testing with a health care professional, and 19% reported test receipt. Strong desire for testing was more common in younger women, Latinas, and those with family history. Minority patients were significantly more likely to have unmet need for discussion (failure to discuss genetic testing with a health professional when they had a strong desire for testing): odds ratios of 1.68, 2.44, and 7.39 for blacks, English-speaking Latinas, and Spanish-speaking Latinas compared with whites, respectively. Worry in the long-term survivorship period was higher among those with unmet need for discussion (48.7% v 24.9%; P <.001). Patients who received genetic testing were younger, less likely to be black, and more likely to have a family cancer history. Many patients, especially minorities, express a strong desire for genetic testing and may benefit from discussion to clarify risks. Clinicians should discuss genetic risk even with patients they perceive to be at low risk, as this may reduce worry. © 2015 by American Society of Clinical Oncology.

Evaluation of Genetic Diversity and Development of a Core Collection of Wild Rice (Oryza rufipogon Griff.) Populations in China

PubMed Central

Bai, Lin; Lu, Zhenzhen; Chen, Yuhong; Jiang, Lan; Diao, Mengyang; Liu, Xiangdong; Lu, Yonggen

2015-01-01

Common wild rice (Oryza rufipogon Griff.), the progenitor of Asian cultivated rice (O. sativa L.), is endangered due to habitat loss. The objectives of this research were to evaluate the genetic diversity of wild rice species in isolated populations and to develop a core collection of representative genotypes for ex situ conservation. We collected 885 wild rice accessions from eight geographically distinct regions and transplanted these accessions in a protected conservation garden over a period of almost two decades. We evaluated these accessions for 13 morphological or phenological traits and genotyped them for 36 DNA markers evenly distributed on the 12 chromosomes. The coefficient of variation of quantitative traits was 0.56 and ranged from 0.37 to 1.06. SSR markers detected 206 different alleles with an average of 6 alleles per locus. The mean polymorphism information content (PIC) was 0.64 in all populations, indicating that the marker loci have a high level of polymorphism and genetic diversity in all populations. Phylogenetic analyses based on morphological and molecular data revealed remarkable differences in the genetic diversity of common wild rice populations. The results showed that the Zengcheng, Gaozhou, and Suixi populations possess higher levels of genetic diversity, whereas the Huilai and Boluo populations have lower levels of genetic diversity than do the other populations. Based on their genetic distance, 130 accessions were selected as a core collection that retained over 90% of the alleles at the 36 marker loci. This genetically diverse core collection will be a useful resource for genomic studies of rice and for initiatives aimed at developing rice with improved agronomic traits. PMID:26720755

Evaluation of Genetic Diversity and Development of a Core Collection of Wild Rice (Oryza rufipogon Griff.) Populations in China.

PubMed

Liu, Wen; Shahid, Muhammad Qasim; Bai, Lin; Lu, Zhenzhen; Chen, Yuhong; Jiang, Lan; Diao, Mengyang; Liu, Xiangdong; Lu, Yonggen

2015-01-01

Common wild rice (Oryza rufipogon Griff.), the progenitor of Asian cultivated rice (O. sativa L.), is endangered due to habitat loss. The objectives of this research were to evaluate the genetic diversity of wild rice species in isolated populations and to develop a core collection of representative genotypes for ex situ conservation. We collected 885 wild rice accessions from eight geographically distinct regions and transplanted these accessions in a protected conservation garden over a period of almost two decades. We evaluated these accessions for 13 morphological or phenological traits and genotyped them for 36 DNA markers evenly distributed on the 12 chromosomes. The coefficient of variation of quantitative traits was 0.56 and ranged from 0.37 to 1.06. SSR markers detected 206 different alleles with an average of 6 alleles per locus. The mean polymorphism information content (PIC) was 0.64 in all populations, indicating that the marker loci have a high level of polymorphism and genetic diversity in all populations. Phylogenetic analyses based on morphological and molecular data revealed remarkable differences in the genetic diversity of common wild rice populations. The results showed that the Zengcheng, Gaozhou, and Suixi populations possess higher levels of genetic diversity, whereas the Huilai and Boluo populations have lower levels of genetic diversity than do the other populations. Based on their genetic distance, 130 accessions were selected as a core collection that retained over 90% of the alleles at the 36 marker loci. This genetically diverse core collection will be a useful resource for genomic studies of rice and for initiatives aimed at developing rice with improved agronomic traits.

Genetic algorithms using SISAL parallel programming language

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tejada, S.

1994-05-06

Genetic algorithms are a mathematical optimization technique developed by John Holland at the University of Michigan [1]. The SISAL programming language possesses many of the characteristics desired to implement genetic algorithms. SISAL is a deterministic, functional programming language which is inherently parallel. Because SISAL is functional and based on mathematical concepts, genetic algorithms can be efficiently translated into the language. Several of the steps involved in genetic algorithms, such as mutation, crossover, and fitness evaluation, can be parallelized using SISAL. In this paper I will l discuss the implementation and performance of parallel genetic algorithms in SISAL.

Evaluating Secondary Students' Scientific Reasoning in Genetics Using a Two-Tier Diagnostic Instrument

NASA Astrophysics Data System (ADS)

Tsui, Chi-Yan; Treagust, David

2010-05-01

While genetics has remained as one key topic in school science, it continues to be conceptually and linguistically difficult for students with the concomitant debates as to what should be taught in the age of biotechnology. This article documents the development and implementation of a two-tier multiple-choice instrument for diagnosing grades 10 and 12 students' understanding of genetics in terms of reasoning. The pretest and posttest forms of the diagnostic instrument were used alongside other methods in evaluating students' understanding of genetics in a case-based qualitative study on teaching and learning with multiple representations in three Western Australian secondary schools. Previous studies have shown that a two-tier diagnostic instrument is useful in probing students' understanding or misunderstanding of scientific concepts and ideas. The diagnostic instrument in this study was designed and then progressively refined, improved, and implemented to evaluate student understanding of genetics in three case schools. The final version of the instrument had Cronbach's alpha reliability of 0.75 and 0.64, respectively, for its pretest and the posttest forms when it was administered to a group of grade 12 students (n = 17). This two-tier diagnostic instrument complemented other qualitative data collection methods in this research in generating a more holistic picture of student conceptual learning of genetics in terms of scientific reasoning. Implications of the findings of this study using the diagnostic instrument are discussed.

Genetic and demographic implications of aquaculture in white sturgeon (Acipenser transmontanus)conservation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jager, Yetta

2005-01-01

This study uses a genetic individual-based model of white sturgeon (Acipenser transmontanus) populations in a river to examine the genetic and demographic trade-offs associated with operating a conservation hatchery. Simulation experiments evaluated three management practices: (i) setting quotas to equalize family contributions in an effort to prevent genetic swamping, (ii) an adaptive management scheme that interrupts stocking when introgression exceeds a specified threshold, and (iii) alternative broodstock selection strategies that influence domestication. The first set of simulations, designed to evaluate equalizing the genetic contribution of families, did not show the genetic benefits expected. The second set of simulations showed thatmore » simulated adaptive management was not successful in controlling introgression over the long term, especially with uncertain feedback. The third set of simulations compared the effects of three alternative broodstock selection strategies on domestication for hypothetical traits controlling early density-dependent survival. Simulated aquaculture selected for a density-tolerant phenotype when broodstock were taken from a genetically connected population. Using broodstock from an isolated population (i.e., above an upstream barrier or in a different watershed) was more effective at preventing domestication than using wild broodstock from a connected population.« less

Impact of computer-assisted data collection, evaluation and management on the cancer genetic counselor's time providing patient care.

PubMed

Cohen, Stephanie A; McIlvried, Dawn E

2011-06-01

Cancer genetic counseling sessions traditionally encompass collecting medical and family history information, evaluating that information for the likelihood of a genetic predisposition for a hereditary cancer syndrome, conveying that information to the patient, offering genetic testing when appropriate, obtaining consent and subsequently documenting the encounter with a clinic note and pedigree. Software programs exist to collect family and medical history information electronically, intending to improve efficiency and simplicity of collecting, managing and storing this data. This study compares the genetic counselor's time spent in cancer genetic counseling tasks in a traditional model and one using computer-assisted data collection, which is then used to generate a pedigree, risk assessment and consult note. Genetic counselor time spent collecting family and medical history and providing face-to-face counseling for a new patient session decreased from an average of 85-69 min when using the computer-assisted data collection. However, there was no statistically significant change in overall genetic counselor time on all aspects of the genetic counseling process, due to an increased amount of time spent generating an electronic pedigree and consult note. Improvements in the computer program's technical design would potentially minimize data manipulation. Certain aspects of this program, such as electronic collection of family history and risk assessment, appear effective in improving cancer genetic counseling efficiency while others, such as generating an electronic pedigree and consult note, do not.

Evaluation of genetic diversity in Piper spp using RAPD and SRAP markers.

PubMed

Jiang, Y; Liu, J-P

2011-11-29

Random amplified polymorphic DNA (RAPD) and sequence-related amplified polymorphism (SRAP) analysis were applied to 74 individual plants of Piper spp in Hainan Island. The results showed that the SRAP technique may be more informative and more efficient and effective for studying genetic diversity of Piper spp than the RAPD technique. The overall level of genetic diversity among Piper spp in Hainan was relatively high, with the mean Shannon diversity index being 0.2822 and 0.2909, and the mean Nei's genetic diversity being 0.1880 and 0.1947, calculated with RAPD and SRAP data, respectively. The ranges of the genetic similarity coefficient were 0.486-0.991 and 0.520-1.000 for 74 individual plants of Piper spp (the mean genetic distance was 0.505 and 0.480) and the within-species genetic distance ranged from 0.063 to 0.291 and from 0.096 to 0.234, estimated with RAPD and SRAP data, respectively. These genetic indices indicated that these species are closely related genetically. The dendrogram generated with the RAPD markers was topologically different from the dendrogram based on SRAP markers, but the SRAP technique clearly distinguished all Piper spp from each other. Evaluation of genetic variation levels of six populations showed that the effective number of alleles, Nei's gene diversity and the Shannon information index within Jianfengling and Diaoluoshan populations are higher than those elsewhere; consequently conservation of wild resources of Piper in these two regions should have priority.

Valuing the benefits of genetic testing for retinitis pigmentosa: a pilot application of the contingent valuation method.

PubMed

Eden, Martin; Payne, Katherine; Combs, Ryan M; Hall, Georgina; McAllister, Marion; Black, Graeme C M

2013-08-01

Technological advances present an opportunity for more people with, or at risk of, developing retinitis pigmentosa (RP) to be offered genetic testing. Valuation of these tests using current evaluative frameworks is problematic since benefits may be derived from diagnostic information rather than improvements in health. This pilot study aimed to explore if contingent valuation method (CVM) can be used to value the benefits of genetic testing for RP. CVM was used to elicit willingness-to-pay (WTP) values for (1) genetic counselling and (2) genetic counselling with genetic testing. Telephone and face-to-face interviews with a purposive sample of individuals with (n=25), and without (n=27), prior experience of RP were used to explore the feasibility and validity of CVM in this context. Faced with a hypothetical scenario, the majority of participants stated that they would seek genetic counselling and testing in the context of RP. Between participant groups, respondents offered similar justifications for stated WTP values. Overall stated WTP was higher for genetic counselling plus testing (median=£524.00) compared with counselling alone (median=£224.50). Between-group differences in stated WTP were statistically significant; participants with prior knowledge of the condition were willing to pay more for genetic ophthalmology services. Participants were able to attach a monetary value to the perceived potential benefit that genetic testing offered regardless of prior experience of the condition. This exploratory work represents an important step towards evaluating these services using formal cost-benefit analysis.

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle.

PubMed

Santana, M L; Eler, J P; Bignardi, A B; Ferraz, J B S

2014-03-01

The objectives of the present study were: (1) to evaluate the importance of genotype × production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire × contemporary group interaction (S × CG) to model G × E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S × CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype × production environment interaction. Furthermore, the model including S × CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S × CG. Thus, the model that included S × CG can therefore be considered the best model on the basis of these criteria. The genotype × production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S × CG in the model is a feasible and plausible alternative to model the effects of G × E in the genetic evaluations.

Assessment of Genetic and Molecular Approaches for the Prediction of Wheat Quality

USDA-ARS?s Scientific Manuscript database

Assessment of genetic and molecular approaches for the prediction of wheat quality. R.A. Graybosch, USDA-ARS, Lincoln, NE, U.S.A. Over the past four decades, the field of plant breeding and genetics has been revolutionized by technological advances in the areas of DNA manipulation and evaluation. Fo...

The chloroplast psbK-psbI intergenic region, a potential genetic marker for broad sectional relationships in Anthurium

USDA-ARS?s Scientific Manuscript database

Nuclear and chloroplast genetic markers have been extensively used for plant identification and molecular taxonomy studies. The efficacy of genetic markers to be used as DNA barcodes is under constant evaluation and improvement, with identification of new barcodes that provide greater resolution an...

Evaluating realized genetic gains from tree improvement.

Treesearch

J.B. St. Clair

1993-01-01

Tree improvement has become an essential part of the management of forest lands for wood production, and predicting yields and realized gains from forests planted with genetically-improved trees will become increasingly important. This paper discusses concepts of tree improvement and genetic gain important to growth and yield modeling, and reviews previous studies of...

Effect of genetic selection on growth parameters and tonic immobility in Leghorn pullets.

USDA-ARS?s Scientific Manuscript database

Four genetic strains of leghorn pullets were evaluated for effects of genetic selection on growth and fearfulness behavior. Three strains were closed, random bred stocks from 1950, 1960, and 1972. The fourth strain was a 1993 commercial laying stock. Pullets were reared in a brood/grow poultry ho...

Drought genetics have varying influence on corn water stress under differing water availability

USDA-ARS?s Scientific Manuscript database

Irrigated corn (Zea mays L.) in the Great Plains will be increasingly grown under limited irrigation management and greater water stress. Hybrids with drought genetics may decrease the impacts of water stress on yield. The objective of this experiment was to evaluate the effect of drought genetics o...

Genetic architechture and biological basis for feed efficiency in dairy cattle

USDA-ARS?s Scientific Manuscript database

The genetic architecture of residual feed intake (RFI) and related traits was evaluated using a dataset of 2,894 cows. A Bayesian analysis estimated that markers accounted for 14% of the variance in RFI, and that RFI had considerable genetic variation. Effects of marker windows were small, but QTL p...

[Genetic predisposition to breast and ovarian cancer: importance of test results].

PubMed

Julian-Reynier, Claire

2011-01-01

Oncogenetic consultations and predictive BRCA1/2 testing are intertwined processes and the specific impact of these genetic tests if performed alone through direct-to-consumer offers remains unknown. Noteworthy, the expectations of patients vary with their own status, whether they are affected or not by breast cancer at the time genetic testing is performed. The prescription of genetic tests for BCRA mutations has doubled in France between 2003 and 2009. There is a consensus on the fact that genetic results disclosure led to a significant increase in the knowledge and understanding that the patients have of the genetic risk and also changed the medical follow-up of these patients. Evaluating the psychological burden of tests disclosure did not reveal any major distress in patients who are followed by high-quality multidisciplinary teams. Longitudinal cohorts studies have now evaluated the perception and behaviour of these patients, and observed sociodemographic as well as geographic and psychosocial differences both in the acceptation of prophylactic strategies such as surgery, and time to surgery. © 2011 médecine/sciences - Inserm / SRMS.

Genetic evaluation of the breeding population of a valuable reforestation conifer Platycladus orientalis (Cupressaceae)

NASA Astrophysics Data System (ADS)

Jin, Yuqing; Ma, Yongpeng; Wang, Shun; Hu, Xian-Ge; Huang, Li-Sha; Li, Yue; Wang, Xiao-Ru; Mao, Jian-Feng

2016-10-01

Platycladus orientalis, a widespread conifer with long lifespan and significant adaptability. It is much used in reforestation in north China and commonly planted in central Asia. With the increasing demand for plantation forest in central to north China, breeding programs are progressively established for this species. Efficient use of breeding resources requires good understanding of the genetic value of the founder breeding materials. This study investigated the distribution of genetic variation in 192 elite trees collected for the breeding program for the central range of the species. We developed first set of 27 polymorphic EST-derived SSR loci for the species from transcriptome/genome data. After examination of amplification quality, 10 loci were used to evaluate the genetic variation in the breeding population. We found moderate genetic diversity (average He = 0.348) and low population differentiation (Fst = 0.011). Extensive admixture and no significant geographic population structure characterized this set of collections. Our analyses of the diversity and population structure are important steps toward a long-term sustainable deployment of the species and provide valuable genetic information for conservation and breeding applications.

Using Multi-Objective Genetic Programming to Synthesize Stochastic Processes

NASA Astrophysics Data System (ADS)

Ross, Brian; Imada, Janine

Genetic programming is used to automatically construct stochastic processes written in the stochastic π-calculus. Grammar-guided genetic programming constrains search to useful process algebra structures. The time-series behaviour of a target process is denoted with a suitable selection of statistical feature tests. Feature tests can permit complex process behaviours to be effectively evaluated. However, they must be selected with care, in order to accurately characterize the desired process behaviour. Multi-objective evaluation is shown to be appropriate for this application, since it permits heterogeneous statistical feature tests to reside as independent objectives. Multiple undominated solutions can be saved and evaluated after a run, for determination of those that are most appropriate. Since there can be a vast number of candidate solutions, however, strategies for filtering and analyzing this set are required.

40 CFR 158.2110 - Microbial pesticides data requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

...: genetic engineering techniques used; the identity of the inserted or deleted gene segment (base sequence... evaluate genetic stability and exchange; and selected Tier II environmental expression and toxicology tests. ...

40 CFR 158.2110 - Microbial pesticides data requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

...: genetic engineering techniques used; the identity of the inserted or deleted gene segment (base sequence... evaluate genetic stability and exchange; and selected Tier II environmental expression and toxicology tests. ...

40 CFR 158.2110 - Microbial pesticides data requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

...: genetic engineering techniques used; the identity of the inserted or deleted gene segment (base sequence... evaluate genetic stability and exchange; and selected Tier II environmental expression and toxicology tests. ...

40 CFR 158.2110 - Microbial pesticides data requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

...: genetic engineering techniques used; the identity of the inserted or deleted gene segment (base sequence... evaluate genetic stability and exchange; and selected Tier II environmental expression and toxicology tests. ...

Frankenfoods: Values about Genetics Embedded in a Metaphor.

ERIC Educational Resources Information Center

Flores, Vanessa S.; Tobin, Allan J.

2002-01-01

Presents an assay on genetically modified (GM) foods, also called Frankenfoods, that demonstrates ways to evaluate a scientific metaphor and facilitate discussion on students' values regarding GM foods. (YDS)

Multilocus genetic risk scores for venous thromboembolism risk assessment.

PubMed

Soria, José Manuel; Morange, Pierre-Emmanuel; Vila, Joan; Souto, Juan Carlos; Moyano, Manel; Trégouët, David-Alexandre; Mateo, José; Saut, Noémi; Salas, Eduardo; Elosua, Roberto

2014-10-23

Genetics plays an important role in venous thromboembolism (VTE). Factor V Leiden (FVL or rs6025) and prothrombin gene G20210A (PT or rs1799963) are the genetic variants currently tested for VTE risk assessment. We hypothesized that primary VTE risk assessment can be improved by using genetic risk scores with more genetic markers than just FVL-rs6025 and prothrombin gene PT-rs1799963. To this end, we have designed a new genetic risk score called Thrombo inCode (TiC). TiC was evaluated in terms of discrimination (Δ of the area under the receiver operating characteristic curve) and reclassification (integrated discrimination improvement and net reclassification improvement). This evaluation was performed using 2 age- and sex-matched case-control populations: SANTPAU (248 cases, 249 controls) and the Marseille Thrombosis Association study (MARTHA; 477 cases, 477 controls). TiC was compared with other literature-based genetic risk scores. TiC including F5 rs6025/rs118203906/rs118203905, F2 rs1799963, F12 rs1801020, F13 rs5985, SERPINC1 rs121909548, and SERPINA10 rs2232698 plus the A1 blood group (rs8176719, rs7853989, rs8176743, rs8176750) improved the area under the curve compared with a model based only on F5-rs6025 and F2-rs1799963 in SANTPAU (0.677 versus 0.575, P<0.001) and MARTHA (0.605 versus 0.576, P=0.008). TiC showed good integrated discrimination improvement of 5.49 (P<0.001) for SANTPAU and 0.96 (P=0.045) for MARTHA. Among the genetic risk scores evaluated, the proportion of VTE risk variance explained by TiC was the highest. We conclude that TiC greatly improves prediction of VTE risk compared with other genetic risk scores. TiC should improve prevention, diagnosis, and treatment of VTE. © 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Multilocus Genetic Risk Scores for Venous Thromboembolism Risk Assessment

PubMed Central

Soria, José Manuel; Morange, Pierre‐Emmanuel; Vila, Joan; Souto, Juan Carlos; Moyano, Manel; Trégouët, David‐Alexandre; Mateo, José; Saut, Noémi; Salas, Eduardo; Elosua, Roberto

2014-01-01

Background Genetics plays an important role in venous thromboembolism (VTE). Factor V Leiden (FVL or rs6025) and prothrombin gene G20210A (PT or rs1799963) are the genetic variants currently tested for VTE risk assessment. We hypothesized that primary VTE risk assessment can be improved by using genetic risk scores with more genetic markers than just FVL‐rs6025 and prothrombin gene PT‐rs1799963. To this end, we have designed a new genetic risk score called Thrombo inCode (TiC). Methods and Results TiC was evaluated in terms of discrimination (Δ of the area under the receiver operating characteristic curve) and reclassification (integrated discrimination improvement and net reclassification improvement). This evaluation was performed using 2 age‐ and sex‐matched case–control populations: SANTPAU (248 cases, 249 controls) and the Marseille Thrombosis Association study (MARTHA; 477 cases, 477 controls). TiC was compared with other literature‐based genetic risk scores. TiC including F5 rs6025/rs118203906/rs118203905, F2 rs1799963, F12 rs1801020, F13 rs5985, SERPINC1 rs121909548, and SERPINA10 rs2232698 plus the A1 blood group (rs8176719, rs7853989, rs8176743, rs8176750) improved the area under the curve compared with a model based only on F5‐rs6025 and F2‐rs1799963 in SANTPAU (0.677 versus 0.575, P<0.001) and MARTHA (0.605 versus 0.576, P=0.008). TiC showed good integrated discrimination improvement of 5.49 (P<0.001) for SANTPAU and 0.96 (P=0.045) for MARTHA. Among the genetic risk scores evaluated, the proportion of VTE risk variance explained by TiC was the highest. Conclusions We conclude that TiC greatly improves prediction of VTE risk compared with other genetic risk scores. TiC should improve prevention, diagnosis, and treatment of VTE. PMID:25341889

Mutation extraction tools can be combined for robust recognition of genetic variants in the literature

PubMed Central

Jimeno Yepes, Antonio; Verspoor, Karin

2014-01-01

As the cost of genomic sequencing continues to fall, the amount of data being collected and studied for the purpose of understanding the genetic basis of disease is increasing dramatically. Much of the source information relevant to such efforts is available only from unstructured sources such as the scientific literature, and significant resources are expended in manually curating and structuring the information in the literature. As such, there have been a number of systems developed to target automatic extraction of mutations and other genetic variation from the literature using text mining tools. We have performed a broad survey of the existing publicly available tools for extraction of genetic variants from the scientific literature. We consider not just one tool but a number of different tools, individually and in combination, and apply the tools in two scenarios. First, they are compared in an intrinsic evaluation context, where the tools are tested for their ability to identify specific mentions of genetic variants in a corpus of manually annotated papers, the Variome corpus. Second, they are compared in an extrinsic evaluation context based on our previous study of text mining support for curation of the COSMIC and InSiGHT databases. Our results demonstrate that no single tool covers the full range of genetic variants mentioned in the literature. Rather, several tools have complementary coverage and can be used together effectively. In the intrinsic evaluation on the Variome corpus, the combined performance is above 0.95 in F-measure, while in the extrinsic evaluation the combined recall performance is above 0.71 for COSMIC and above 0.62 for InSiGHT, a substantial improvement over the performance of any individual tool. Based on the analysis of these results, we suggest several directions for the improvement of text mining tools for genetic variant extraction from the literature. PMID:25285203

Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

PubMed

García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

2018-01-01

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In conclusion, the Thurstonian approach is recommended for the routine genetic evaluations for ranking in endurance horses.

Genomic and Resistance Gene Homolog Diversity of the Dominant Tallgrass Prairie Species across the U.S. Great Plains Precipitation Gradient

PubMed Central

Rouse, Matthew N.; Saleh, Amgad A.; Seck, Amadou; Keeler, Kathleen H.; Travers, Steven E.; Hulbert, Scot H.; Garrett, Karen A.

2011-01-01

Background Environmental variables such as moisture availability are often important in determining species prevalence and intraspecific diversity. The population genetic structure of dominant plant species in response to a cline of these variables has rarely been addressed. We evaluated the spatial genetic structure and diversity of Andropogon gerardii populations across the U.S. Great Plains precipitation gradient, ranging from approximately 48 cm/year to 105 cm/year. Methodology/Principal Findings Genomic diversity was evaluated with AFLP markers and diversity of a disease resistance gene homolog was evaluated by PCR-amplification and digestion with restriction enzymes. We determined the degree of spatial genetic structure using Mantel tests. Genomic and resistance gene homolog diversity were evaluated across prairies using Shannon's index and by averaging haplotype dissimilarity. Trends in diversity across prairies were determined using linear regression of diversity on average precipitation for each prairie. We identified significant spatial genetic structure, with genomic similarity decreasing as a function of distance between samples. However, our data indicated that genome-wide diversity did not vary consistently across the precipitation gradient. In contrast, we found that disease resistance gene homolog diversity was positively correlated with precipitation. Significance Prairie remnants differ in the genetic resources they maintain. Selection and evolution in this disease resistance homolog is environmentally dependent. Overall, we found that, though this environmental gradient may not predict genomic diversity, individual traits such as disease resistance genes may vary significantly. PMID:21532756

Evaluation of the genetic structure present in natural populations of four subspecies of black cherry (Prunus serotina Ehrh.) from North America using SSR markers

USDA-ARS?s Scientific Manuscript database

Black cherry (Prunus serotina) is a fruit tree native to North America, and almost all parts of this plant have some use. This species is a complex of five subspecies with morphological differences and distinctive habitats. The genetic structure of 18 natural populations of black cherry was evaluate...

Comparison of molecular breeding values based on within- and across-breed training in beef cattle.

PubMed

Kachman, Stephen D; Spangler, Matthew L; Bennett, Gary L; Hanford, Kathryn J; Kuehn, Larry A; Snelling, Warren M; Thallman, R Mark; Saatchi, Mahdi; Garrick, Dorian J; Schnabel, Robert D; Taylor, Jeremy F; Pollak, E John

2013-08-16

Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of purebreds. However, comparable studies using beef cattle field data have not been reported. Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype. With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero. Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.

Results from six generations of selection for intramuscular fat in Duroc swine using real-time ultrasound. II. Genetic parameters and trends.

PubMed

Schwab, C R; Baas, T J; Stalder, K J

2010-01-01

Design of breeding programs requires knowledge of variance components that exist for traits included in specific breeding goals and the genetic relationships that exist among traits of economic importance. A study was conducted to evaluate direct and correlated genetic responses to selection for intramuscular fat (IMF) and to estimate genetic parameters for economically important traits in Duroc swine. Forty gilts were purchased from US breeders and randomly mated for 2 generations to boars available in regional boar studs to develop a base population of 56 litters. Littermate pairs of gilts from this population were randomly assigned to a select line (SL) or control line (CL) and mated to the same boar to establish genetic ties between lines. In the SL, the top 10 boars and 75 gilts were selected based on IMF EBV obtained from a bivariate animal model that included IMF evaluated on the carcass and IMF predicted via ultrasound. One boar from each sire family and 50 to 60 gilts representing all sire families were randomly selected to maintain the CL. Carcass and ultrasound IMF were both moderately heritable (0.31 and 0.38, respectively). Moderate to high genetic relationships were estimated among carcass backfat and meat quality measures of IMF, Instron tenderness, and objective loin muscle color. Based on estimates obtained in this study, more desirable genetic merit for pH is associated with greater genetic value for loin color, tenderness, and sensory characteristics. Intramuscular fat measures obtained on the carcass and predicted using ultrasound technology were highly correlated (r(g) = 0.86 from a 12-trait analysis; r(g) = 0.90 from a 5-trait analysis). Estimated genetic relationships among IMF measures and other traits evaluated were generally consistent. Intramuscular fat measures were also genetically associated with Instron tenderness and flavor score in a desirable direction. Direct genetic response in IMF measures observed in the SL corresponded to a significant decrease in EBV for carcass loin muscle area (-0.90 cm(2) per generation) and an increase in carcass backfat EBV (0.98 mm per generation). Selection for IMF has led to more desirable EBV for objective tenderness and has had an adverse effect on additive genetic merit for objective loin color.

Population dynamics of Aedes aegypti from a dengue hyperendemic urban setting in Colombia.

PubMed

Ocampo, Clara B; Wesson, Dawn M

2004-10-01

This study evaluated if the Aedes aegypti population in the city of Cali, Colombia was composed of genetically distinct local populations with different levels of insecticide resistance and dengue vector competence. Insecticide resistance was assayed biochemically and was associated with varying levels of mixed-function oxidases and non-specific esterases. The genes encoding those enzymes were under selective pressure from insecticides used to suppress Ae. aegypti populations. Vector competence showed heterogeneity among the vector populations ranging from 19% to 60%. Population genetic analysis of random amplified polymorphic DNA-polymerase chain reaction products, expressed as genetic distance, Wright's F(st), and migration rate (Nm), demonstrated moderate genetic differentiation among Ae. aegypti from four sites (F(st) = 0.085). The results from all characteristics evaluated in the study demonstrated spatial and temporal variation between Ae. aegypti populations. At any specific time, the local populations of Ae. aegypti were genetically differentiated and unique with respect to insecticide resistance and vector competence. Both characteristics changed independently.

Genetic Associations With White Matter Hyperintensities Confer Risk of Lacunar Stroke

PubMed Central

Rutten-Jacobs, Loes C.A.; Thijs, Vincent; Holliday, Elizabeth G.; Levi, Chris; Bevan, Steve; Malik, Rainer; Boncoraglio, Giorgio; Sudlow, Cathie; Rothwell, Peter M.; Dichgans, Martin; Markus, Hugh S.

2016-01-01

Background and Purpose— White matter hyperintensities (WMH) are increased in patients with lacunar stroke. Whether this is because of shared pathogenesis remains unknown. Using genetic data, we evaluated whether WMH-associated genetic susceptibility factors confer risk of lacunar stroke, and therefore whether they share pathogenesis. Methods— We used a genetic risk score approach to test whether single nucleotide polymorphisms associated with WMH in community populations were associated with magnetic resonance imaging–confirmed lacunar stroke (n=1,373), as well as cardioembolic (n=1,331) and large vessel (n=1,472) Trial of Org 10172 in Acute Stroke Treatment subtypes, against 9,053 controls. Second, we separated lacunar strokes into those with WMH (n=568) and those without (n=787) and tested for association with the risk score in these 2 groups. In addition, we evaluated whether WMH-associated single nucleotide polymorphisms are associated with lacunar stroke, or in the 2 groups. Results— The WMH genetic risk score was associated with lacunar stroke (odds ratio [OR; 95% confidence interval [CI

Sex-biased dispersal and spatial heterogeneity affect landscape resistance to gene flow in fisher

Treesearch

Jody M. Tucker; Fred W. Allendorf; Richard L. Truex; Michael K. Schwartz

2017-01-01

Genetic connectivity results from the dispersal and reproduction of individuals across landscapes. Mammalian populations frequently exhibit sex-biased dispersal, but this factor has rarely been addressed in individual-based landscape genetics research. In this study, we evaluate the effects of sexbiased dispersal and landscape heterogeneity on genetic connectivity in a...

Identification of a barrier height threshold where brook trout population genetic diversity, differentiation, and relatedness are affected

Treesearch

Anne Timm; Eric Hallerman; Andy Dolloff; Mark Hudy; Randall Kolka

2016-01-01

The overall goal of the study was to evaluate effects of landscape features, barriers, on Brook Trout Salvelinus fontinalis population genetics and to identify a potential barrier height threshold where genetic diversity was reduced upstream of the barrier and differentiation and relatedness increase. We screened variation at eight...

Simulating pattern-process relationships to validate landscape genetic models

Treesearch

A. J. Shirk; S. A. Cushman; E. L. Landguth

2012-01-01

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

DECOMPOSTION OF GENETICALLY ENGINEERED TOBACCO UNDER FIELD CONDITIONS: PERSISTENCE OF THE PROTEINASE INHIBITOR I PRODUCT AND EFFECTS OF SOIL MICROBIAL RESPIRATION AND PROTOZOA, NEMATODE AND MICROARTHR

EPA Science Inventory

1. To evaluate the potential effects of genetically engineered (transgenic) plants on soil ecosystems, litterbags containing leaves of non-engineered (parental) and transgenic tobacco plants were buried in field plots. The transgenic tobacco plants were genetically engineered to ...

Genetic structure, diversity, and inbreeding of eastern white pine under different management conditions

Treesearch

Paula E. Marquardt; Craig S. Echt; Bryan K. Epperson; Dan M. Pubanz

2007-01-01

Resource sustainability requires a thorough understanding of the influence of forest management programs on the conservation of genetic diversity in tree populations. To observe how differences in forest structure affect the genetic structure of eastern white pine (Pinus strobus L.), we evaluated six eastern white pine sites across the 234000 acre (1...

Genetic diversity revealed by single nucleotide polymorphism markers in a worldwide germplasm collection of durum wheat.

PubMed

Ren, Jing; Sun, Daokun; Chen, Liang; You, Frank M; Wang, Jirui; Peng, Yunliang; Nevo, Eviatar; Sun, Dongfa; Luo, Ming-Cheng; Peng, Junhua

2013-03-28

Evaluation of genetic diversity and genetic structure in crops has important implications for plant breeding programs and the conservation of genetic resources. Newly developed single nucleotide polymorphism (SNP) markers are effective in detecting genetic diversity. In the present study, a worldwide durum wheat collection consisting of 150 accessions was used. Genetic diversity and genetic structure were investigated using 946 polymorphic SNP markers covering the whole genome of tetraploid wheat. Genetic structure was greatly impacted by multiple factors, such as environmental conditions, breeding methods reflected by release periods of varieties, and gene flows via human activities. A loss of genetic diversity was observed from landraces and old cultivars to the modern cultivars released during periods of the Early Green Revolution, but an increase in cultivars released during the Post Green Revolution. Furthermore, a comparative analysis of genetic diversity among the 10 mega ecogeographical regions indicated that South America, North America, and Europe possessed the richest genetic variability, while the Middle East showed moderate levels of genetic diversity.

Genetic fidelity and variability of micropropagated cassava plants (Manihot esculenta Crantz) evaluated using ISSR markers.

PubMed

Vidal, Á M; Vieira, L J; Ferreira, C F; Souza, F V D; Souza, A S; Ledo, C A S

2015-07-14

Molecular markers are efficient for assessing the genetic fidelity of various species of plants after in vitro culture. In this study, we evaluated the genetic fidelity and variability of micropropagated cassava plants (Manihot esculenta Crantz) using inter-simple sequence repeat markers. Twenty-two cassava accessions from the Embrapa Cassava & Fruits Germplasm Bank were used. For each accession, DNA was extracted from a plant maintained in the field and from 3 plants grown in vitro. For DNA amplification, 27 inter-simple sequence repeat primers were used, of which 24 generated 175 bands; 100 of those bands were polymorphic and were used to study genetic variability among accessions of cassava plants maintained in the field. Based on the genetic distance matrix calculated using the arithmetic complement of the Jaccard's index, genotypes were clustered using the unweighted pair group method using arithmetic averages. The number of bands per primer was 2-13, with an average of 7.3. For most micropropagated accessions, the fidelity study showed no genetic variation between plants of the same accessions maintained in the field and those maintained in vitro, confirming the high genetic fidelity of the micropropagated plants. However, genetic variability was observed among different accessions grown in the field, and clustering based on the dissimilarity matrix revealed 7 groups. Inter-simple sequence repeat markers were efficient for detecting the genetic homogeneity of cassava plants derived from meristem culture, demonstrating the reliability of this propagation system.

Population genetics and evaluation of genetic evidence for subspecies in the Semipalmated Sandpiper (Calidris pusilla)

USGS Publications Warehouse

Miller, Mark P.; Gratto-Trevor, Cheri; Haig, Susan M.; Mizrahi, David S.; Mitchell, Melanie M.; Mullins, Thomas D.

2013-01-01

Semipalmated Sandpipers (Calidris pusilla) are among the most common North American shorebirds. Breeding in Arctic North America, this species displays regional differences in migratory pathways and possesses longitudinal bill length variation. Previous investigations suggested that genetic structure may occur within Semipalmated Sandpipers and that three subspecies corresponding to western, central, and eastern breeding groups exist. In this study, mitochondrial control region sequences and nuclear microsatellite loci were used to analyze DNA of birds (microsatellites: n = 120; mtDNA: n = 114) sampled from seven North American locations. Analyses designed to quantify genetic structure and diversity patterns, evaluate genetic evidence for population size changes, and determine if genetic data support the existence of Semipalmated Sandpiper subspecies were performed. Genetic structure based only on the mtDNA data was observed, whereas the microsatellite loci provided no evidence of genetic differentiation. Differentiation among locations and regions reflected allele frequency differences rather than separate phylogenetic groups, and similar levels of genetic diversity were noted. Combined, the two data sets provided no evidence to support the existence of subspecies and were not useful for determining migratory connectivity between breeding sites and wintering grounds. Birds from western and central groups displayed signatures of population expansions, whereas the eastern group was more consistent with a stable overall population. Results of this analysis suggest that the eastern group was the source of individuals that colonized the central and western regions currently utilized by Semipalmated Sandpipers.

Potential Genetic Risk Factors for Chronic TMD: Genetic Associations from the OPPERA Case Control Study

PubMed Central

Smith, Shad B.; Maixner, Dylan; Greenspan, Joel; Dubner, Ron; Fillingim, Roger; Ohrbach, Richard; Knott, Charles; Slade, Gary; Bair, Eric; Gibson, Dustin G.; Zaykin, Dmitri V.; Weir, Bruce; Maixner, William; Diatchenko, Luda

2011-01-01

Genetic factors play a role in the etiology of persistent pain conditions, putatively by modulating underlying processes such as nociceptive sensitivity, psychological well-being, inflammation, and autonomic response. However, to date, only a few genes have been associated with temporomandibular disorders (TMD). This study evaluated 358 genes involved in pain processes, comparing allelic frequencies between 166 cases with chronic TMD and 1442 controls enrolled in the OPPERA (Orofacial Pain: Prospective Evaluation and Risk Assessment) study cooperative agreement. To enhance statistical power, 182 TMD cases and 170 controls from a similar study were included in the analysis. Genotyping was performed using the Pain Research Panel, an Affymetrix gene chip representing 3295 single nucleotide polymorphisms, including ancestry-informative markers that were used to adjust for population stratification. Adjusted associations between genetic markers and TMD case status were evaluated using logistic regression. The OPPERA findings provided evidence supporting previously-reported associations between TMD and two genes: HTR2A and COMT. Other genes were revealed as potential new genetic risk factors for TMD, including NR3C1, CAMK4, CHRM2, IFRD1, and GRK5. While these findings need to be replicated in independent cohorts, the genes potentially represent important markers of risk for TMD and they identify potential targets for therapeutic intervention. PMID:22074755

Patient reported outcomes and patient empowerment in clinical genetics services.

PubMed

McAllister, M; Dearing, A

2015-08-01

Evaluation of clinical genetics services (CGS), including genetic counseling and genetic testing, has been problematic. Patient mortality and morbidity are unlikely to be directly improved by interventions offered in CGS. Patient-reported outcomes (PROs) are not routinely measured in CGS evaluation, but this may change as patient-reported outcome measures (PROMs) become a key part of how healthcare services are managed and funded across the world. However, there is no clear consensus about which PROMs are most useful for CGS evaluation. This review summarizes the published research on how PROs from CGS have been measured and how patients may benefit from using those services, with a focus on patient empowerment. Many patient benefits (PROs) identified repeatedly in the research literature can be re-interpreted within a patient empowerment framework. Other important PROs identified include family functioning, social functioning, altruism, sense of purpose, enabling development of future research and treatment/participating in research. Well-validated measures are available to capture (dimensions of) patient empowerment. Although generic measures of family functioning are available, suitable measures capturing social functioning, development of future treatments, and altruism were not identified in this review. Patient empowerment provides one useful approach to measuring PROs from CGS. © 2014 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Quantitative maps of genetic interactions in yeast - comparative evaluation and integrative analysis.

PubMed

Lindén, Rolf O; Eronen, Ville-Pekka; Aittokallio, Tero

2011-03-24

High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms. Using large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies. We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

Patterns of ancestry and genetic diversity in reintroduced populations of the slimy sculpin: Implications for conservation

USGS Publications Warehouse

Huff, David D.; Miller, Loren M.; Vondracek, Bruce C.

2010-01-01

Reintroductions are a common approach for preserving intraspecific biodiversity in fragmented landscapes. However, they may exacerbate the reduction in genetic diversity initially caused by population fragmentation because the effective population size of reintroduced populations is often smaller and reintroduced populations also tend to be more geographically isolated than native populations. Mixing genetically divergent sources for reintroduction purposes is a practice intended to increase genetic diversity. We documented the outcome of reintroductions from three mixed sources on the ancestral composition and genetic variation of a North American fish, the slimy sculpin (Cottus cognatus). We used microsatellite markers to evaluate allelic richness and heterozygosity in the reintroduced populations relative to computer simulated expectations. Sculpins in reintroduced populations exhibited higher levels of heterozygosity and allelic richness than any single source, but only slightly higher than the single most genetically diverse source population. Simulations intended to mimic an ideal scenario for maximizing genetic variation in the reintroduced populations also predicted increases, but they were only moderately greater than the most variable source population. We found that a single source contributed more than the other two sources at most reintroduction sites. We urge caution when choosing whether to mix source populations in reintroduction programs. Genetic characteristics of candidate source populations should be evaluated prior to reintroduction if feasible. When combined with knowledge of the degree of genetic distinction among sources, simulations may allow the genetic diversity benefits of mixing populations to be weighed against the risks of outbreeding depression in reintroduced and nearby populations.

Patterns of ancestry and genetic diversity in reintroduced populations of the slimy sculpin: Implications for conservation

USGS Publications Warehouse

Huff, D.D.; Miller, L.M.; Vondracek, B.

2010-01-01

Reintroductions are a common approach for preserving intraspecific biodiversity in fragmented landscapes. However, they may exacerbate the reduction in genetic diversity initially caused by population fragmentation because the effective population size of reintroduced populations is often smaller and reintroduced populations also tend to be more geographically isolated than native populations. Mixing genetically divergent sources for reintroduction purposes is a practice intended to increase genetic diversity. We documented the outcome of reintroductions from three mixed sources on the ancestral composition and genetic variation of a North American fish, the slimy sculpin (Cottus cognatus). We used microsatellite markers to evaluate allelic richness and heterozygosity in the reintroduced populations relative to computer simulated expectations. Sculpins in reintroduced populations exhibited higher levels of heterozygosity and allelic richness than any single source, but only slightly higher than the single most genetically diverse source population. Simulations intended to mimic an ideal scenario for maximizing genetic variation in the reintroduced populations also predicted increases, but they were only moderately greater than the most variable source population. We found that a single source contributed more than the other two sources at most reintroduction sites. We urge caution when choosing whether to mix source populations in reintroduction programs. Genetic characteristics of candidate source populations should be evaluated prior to reintroduction if feasible. When combined with knowledge of the degree of genetic distinction among sources, simulations may allow the genetic diversity benefits of mixing populations to be weighed against the risks of outbreeding depression in reintroduced and nearby populations. ?? 2010 US Government.

Genetic diversity, linkage disequilibrium, population structure and construction of a core collection of Prunus avium L. landraces and bred cultivars.

PubMed

Campoy, José Antonio; Lerigoleur-Balsemin, Emilie; Christmann, Hélène; Beauvieux, Rémi; Girollet, Nabil; Quero-García, José; Dirlewanger, Elisabeth; Barreneche, Teresa

2016-02-24

Depiction of the genetic diversity, linkage disequilibrium (LD) and population structure is essential for the efficient organization and exploitation of genetic resources. The objectives of this study were to (i) to evaluate the genetic diversity and to detect the patterns of LD, (ii) to estimate the levels of population structure and (iii) to identify a 'core collection' suitable for association genetic studies in sweet cherry. A total of 210 genotypes including modern cultivars and landraces from 16 countries were genotyped using the RosBREED cherry 6 K SNP array v1. Two groups, mainly bred cultivars and landraces, respectively, were first detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA). Further analyses identified nine subgroups using STRUCTURE and Discriminant Analysis of Principal Components (DAPC). Several sub-groups correspond to different eco-geographic regions of landraces distribution. Linkage disequilibrium was evaluated showing lower values than in peach, the reference Prunus species. A 'core collection' containing 156 accessions was selected using the maximum length sub tree method. The present study constitutes the first population genetics analysis in cultivated sweet cherry using a medium-density SNP (single nucleotide polymorphism) marker array. We provided estimations of linkage disequilibrium, genetic structure and the definition of a first INRA's Sweet Cherry core collection useful for breeding programs, germplasm management and association genetics studies.

An Efficient Functional Test Generation Method For Processors Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Hudec, Ján; Gramatová, Elena

2015-07-01

The paper presents a new functional test generation method for processors testing based on genetic algorithms and evolutionary strategies. The tests are generated over an instruction set architecture and a processor description. Such functional tests belong to the software-oriented testing. Quality of the tests is evaluated by code coverage of the processor description using simulation. The presented test generation method uses VHDL models of processors and the professional simulator ModelSim. The rules, parameters and fitness functions were defined for various genetic algorithms used in automatic test generation. Functionality and effectiveness were evaluated using the RISC type processor DP32.

Genetic diversity analysis of fruit characteristics of hawthorn germplasm.

PubMed

Su, K; Guo, Y S; Wang, G; Zhao, Y H; Dong, W X

2015-12-07

One hundred and six accessions of hawthorn intraspecific resources, from the National Germplasm Repository at Shenyang, were subjected to genetic diversity and principal component analysis based on evaluation data of 15 fruit traits. Results showed that the genetic diversity of hawthorn fruit traits varied. Among the 15 traits, the fruit shape variable coefficient had the most obvious evaluation, followed by fruit surface state, dot color, taste, weight of single fruit, sepal posture, peduncle form, and metula traits. These are the primary traits by which hawthorn could be classified in the future. The principal component demonstrated that these traits are the most influential factors of hawthorn fruit characteristics.

Potential for Incorporation of Genetic Polymorphism Data in Human Health Risk Assessment

EPA Science Inventory

This overview summarizes several EPA assessment publications evaluating the potential impact of genetic polymorphisms in ten metabolizing enzymes on the variability in enzyme function across ethnically diverse populations.

Prenatal Testing: Is It Right for You?

MedlinePlus

... to you. If you're concerned about prenatal testing, discuss the risks and benefits with your health care provider. You might also meet with a genetic counselor for a more thorough evaluation. A genetic ...

Genet-specific DNA methylation probabilities detected in a spatial epigenetic analysis of a clonal plant population.

PubMed

Araki, Kiwako S; Kubo, Takuya; Kudoh, Hiroshi

2017-01-01

In sessile organisms such as plants, spatial genetic structures of populations show long-lasting patterns. These structures have been analyzed across diverse taxa to understand the processes that determine the genetic makeup of organismal populations. For many sessile organisms that mainly propagate via clonal spread, epigenetic status can vary between clonal individuals in the absence of genetic changes. However, fewer previous studies have explored the epigenetic properties in comparison to the genetic properties of natural plant populations. Here, we report the simultaneous evaluation of the spatial structure of genetic and epigenetic variation in a natural population of the clonal plant Cardamine leucantha. We applied a hierarchical Bayesian model to evaluate the effects of membership of a genet (a group of individuals clonally derived from a single seed) and vegetation cover on the epigenetic variation between ramets (clonal plants that are physiologically independent individuals). We sampled 332 ramets in a 20 m × 20 m study plot that contained 137 genets (identified using eight SSR markers). We detected epigenetic variation in DNA methylation at 24 methylation-sensitive amplified fragment length polymorphism (MS-AFLP) loci. There were significant genet effects at all 24 MS-AFLP loci in the distribution of subepiloci. Vegetation cover had no statistically significant effect on variation in the majority of MS-AFLP loci. The spatial aggregation of epigenetic variation is therefore largely explained by the aggregation of ramets that belong to the same genets. By applying hierarchical Bayesian analyses, we successfully identified a number of genet-specific changes in epigenetic status within a natural plant population in a complex context, where genotypes and environmental factors are unevenly distributed. This finding suggests that it requires further studies on the spatial epigenetic structure of natural populations of diverse organisms, particularly for sessile clonal species.

Accelerating global optimization of aerodynamic shapes using a new surrogate-assisted parallel genetic algorithm

NASA Astrophysics Data System (ADS)

Ebrahimi, Mehdi; Jahangirian, Alireza

2017-12-01

An efficient strategy is presented for global shape optimization of wing sections with a parallel genetic algorithm. Several computational techniques are applied to increase the convergence rate and the efficiency of the method. A variable fidelity computational evaluation method is applied in which the expensive Navier-Stokes flow solver is complemented by an inexpensive multi-layer perceptron neural network for the objective function evaluations. A population dispersion method that consists of two phases, of exploration and refinement, is developed to improve the convergence rate and the robustness of the genetic algorithm. Owing to the nature of the optimization problem, a parallel framework based on the master/slave approach is used. The outcomes indicate that the method is able to find the global optimum with significantly lower computational time in comparison to the conventional genetic algorithm.

Evaluation of genetic diversity among soybean (Glycine max) genotypes using univariate and multivariate analysis.

PubMed

Oliveira, M M; Sousa, L B; Reis, M C; Silva Junior, E G; Cardoso, D B O; Hamawaki, O T; Nogueira, A P O

2017-05-31

The genetic diversity study has paramount importance in breeding programs; hence, it allows selection and choice of the parental genetic divergence, which have the agronomic traits desired by the breeder. This study aimed to characterize the genetic divergence between 24 soybean genotypes through their agronomic traits, using multivariate clustering methods to select the potential genitors for the promising hybrid combinations. Six agronomic traits evaluated were number of days to flowering and maturity, plant height at flowering and maturity, insertion height of the first pod, and yield. The genetic divergence evaluated by multivariate analysis that esteemed first the Mahalanobis' generalized distance (D 2 ), then the clustering using Tocher's optimization methods, and then the unweighted pair group method with arithmetic average (UPGMA). Tocher's optimization method and the UPGMA agreed with the groups' constitution between each other, the formation of eight distinct groups according Tocher's method and seven distinct groups using UPGMA. The trait number of days for flowering (45.66%) was the most efficient to explain dissimilarity between genotypes, and must be one of the main traits considered by the breeder in the moment of genitors choice in soybean-breeding programs. The genetic variability allowed the identification of dissimilar genotypes and with superior performances. The hybridizations UFU 18 x UFUS CARAJÁS, UFU 15 x UFU 13, and UFU 13 x UFUS CARAJÁS are promising to obtain superior segregating populations, which enable the development of more productive genotypes.

Public Health Genomics and Genetic Test Evaluation: The Challenge of Conducting Behavioural Research on the Utility of Lifestyle-Genetic Tests

PubMed Central

Sanderson, Saskia C.; Wardle, Jane; Humphries, Steve E.

2008-01-01

Human genetics research is increasingly concerned with multifactorial conditions such as diabetes and heart disease, which are influenced not only by genetic but also lifestyle factors such as diet and smoking. Although the results of ‘lifestyle-genetic’ tests using this information could conceivably motivate lifestyle changes in the future, companies are already selling such tests and related lifestyle advice commercially. Some academics and lobby groups have condemned the companies for selling these tests in advance of scientific support. Others are concerned that the tests may not motivate lifestyle improvements, instead causing distress in people receiving adverse test results and complacency in those receiving reassuring results. There is currently no regulatory oversight of genetic test utility, despite consensus in the Public Health Genomics community that clinical utility (including psychological and behavioural impact) of all emerging genetic tests should be evaluated before being introduced for individual use. Clearly, empirical data in this area is much needed, to inform understanding of the potential utility of these tests, and of whether stricter regulation of commercial exploitation is needed. In this article, we review the current situation regarding lifestyle-genetic tests, and discuss the challenges inherent in conducting this kind of behavioural research in the genomics era. PMID:19776630

Genetic diversity and population structure analysis of the tropical pasture grass Brachiaria humidicola based on microsatellites, cytogenetics, morphological traits, and geographical origin.

PubMed

Jungmann, L; Vigna, B B Z; Boldrini, K R; Sousa, A C B; do Valle, C B; Resende, R M S; Pagliarini, M S; Zucchi, M I; de Souza, A P

2010-09-01

Brachiaria humidicola (Rendle) Schweick. is a warm-season grass commonly used as forage in the tropics. Accessions of this species were collected in eastern Africa and massively introduced into South America in the 1980s. Several of these accessions form a germplasm collection at the Brazilian Agricultural Research Corporation. However, apomixis, ploidy, and limited knowledge of the genetic basis of this germplasm collection have constrained breeding activities. The objectives of this work were to identify genetic variability in the Brazilian B. humidicola germplasm collection using microsatellite markers and to compare the results with information on the following: (1) collection sites of the accessions; (2) reproductive mode and ploidy levels; and (3) genetic diversity revealed by morphological traits. The evaluated germplasm population is highly structured into four major groups. The sole sexual accession did not group with any of the clusters. Genetic dissimilarities did not correlate with either geographic distances or genetic distances inferred from morphological descriptors. Additionally, the genetic structure identified in this collection did not correspond to differences in ploidy level. Alleles exclusive to either sexual or apomictic accessions were identified, suggesting that further evaluation of the association of these loci with apospory should be carried out.

Evaluation of the genetic structure of sika deer (Cervus nippon) in Japan's Kanto and Tanzawa mountain areas, based on microsatellite markers.

PubMed

Konishi, Sayaka; Hata, Shoko; Matsuda, Sayumi; Arai, Kazushi; Mizoguchi, Yasushi

2017-11-01

The browsing habits of sika deer (Cervus nippon) in Japan have caused serious ecological problems. Appropriate management of sika deer populations requires understanding the different genetic structures of local populations. In the present study, we used 10 microsatellite polymorphisms to explore the genetic structures of sika deer populations (162 individuals) living in the Kanto region. The expected heterozygosity of the Tanzawa mountain range population (Group I) was lower than that of the populations in the Kanto mountain areas (Group II). Our results suggest that moderate gene flow has occurred between the sika deer populations in the Kanto mountain areas (Group II), but not to or from the Tanzawa mountain range population (Group I). Also, genetic structure analysis showed that the Tanzawa population was separated from the other populations. This is probably attributable to a genetic bottleneck that developed in the Tanzawa sika deer population in the 1950s. However, we found that the Tanzawa population has since recovered from the bottleneck situation and now exhibits good genetic diversity. Our results show that it is essential to periodically evaluate the genetic structures of deer populations to develop conservation strategies appropriate to the specific structures of individual populations at any given time. © 2017 Japanese Society of Animal Science.

Evaluation of offspring and maternal genetic effects on disease risk using a family-based approach: the "pent" design.

PubMed

Mitchell, Laura E; Weinberg, Clarice R

2005-10-01

Diseases that develop during gestation may be influenced by the genotype of the mother and the inherited genotype of the embryo/fetus. However, given the correlation between maternal and offspring genotypes, differentiating between inherited and maternal genetic effects is not straightforward. The two-step transmission disequilibrium test was the first, family-based test proposed for the purpose of differentiating between maternal and offspring genetic effects. However, this approach, which requires data from "pents" comprising an affected child, mother, father, and maternal grandparents, provides biased tests for maternal genetic effects when the offspring genotype is associated with disease. An alternative approach based on transmissions from grandparents provides unbiased tests for maternal and offspring genetic effects but requires genotype information for paternal grandparents in addition to pents. The authors have developed two additional, pent-based approaches for the evaluation of maternal and offspring genetic effects. One approach requires the assumption of genetic mating type symmetry (pent-1), whereas the other does not (pent-2). Simulation studies demonstrate that both of these approaches provide valid estimation and testing for offspring and maternal genotypic effects. In addition, the power of the pent-1 approach is comparable with that of the approach based on data using all four grandparents.

Multivariate analysis in a genetic divergence study of Psidium guajava.

PubMed

Nogueira, A M; Ferreira, M F S; Guilhen, J H S; Ferreira, A

2014-12-18

The family Myrtaceae is widespread in the Atlantic Forest and is well-represented in the Espírito Santo State in Brazil. In the genus Psidium of this family, guava (Psidium guajava L.) is the most economically important species. Guava is widely cultivated in tropical and subtropical countries; however, the widespread cultivation of only a small number of guava tree cultivars may cause the genetic vulnerability of this crop, making the search for promising genotypes in natural populations important for breeding programs and conservation. In this study, the genetic diversity of 66 guava trees sampled in the southern region of Espírito Santo and in Caparaó, MG, Brazil were evaluated. A total of 28 morphological descriptors (11 quantitative and 17 multicategorical) and 18 microsatellite markers were used. Principal component, discriminant and cluster analyses, descriptive analyses, and genetic diversity analyses using simple sequence repeats were performed. Discrimination of accessions using molecular markers resulted in clustering of genotypes of the same origin, which was not observed using morphological data. Genetic diversity was detected between and within the localities evaluated, regardless of the methodology used. Genetic differentiation among the populations using morphological and molecular data indicated the importance of the study area for species conservation, genetic erosion estimation, and exploitation in breeding programs.

Accuracy of genomic predictions in Gyr (Bos indicus) dairy cattle.

PubMed

Boison, S A; Utsunomiya, A T H; Santos, D J A; Neves, H H R; Carvalheiro, R; Mészáros, G; Utsunomiya, Y T; do Carmo, A S; Verneque, R S; Machado, M A; Panetto, J C C; Garcia, J F; Sölkner, J; da Silva, M V G B

2017-07-01

Genomic selection may accelerate genetic progress in breeding programs of indicine breeds when compared with traditional selection methods. We present results of genomic predictions in Gyr (Bos indicus) dairy cattle of Brazil for milk yield (MY), fat yield (FY), protein yield (PY), and age at first calving using information from bulls and cows. Four different single nucleotide polymorphism (SNP) chips were studied. Additionally, the effect of the use of imputed data on genomic prediction accuracy was studied. A total of 474 bulls and 1,688 cows were genotyped with the Illumina BovineHD (HD; San Diego, CA) and BovineSNP50 (50K) chip, respectively. Genotypes of cows were imputed to HD using FImpute v2.2. After quality check of data, 496,606 markers remained. The HD markers present on the GeneSeek SGGP-20Ki (15,727; Lincoln, NE), 50K (22,152), and GeneSeek GGP-75Ki (65,018) were subset and used to assess the effect of lower SNP density on accuracy of prediction. Deregressed breeding values were used as pseudophenotypes for model training. Data were split into reference and validation to mimic a forward prediction scheme. The reference population consisted of animals whose birth year was ≤2004 and consisted of either only bulls (TR1) or a combination of bulls and dams (TR2), whereas the validation set consisted of younger bulls (born after 2004). Genomic BLUP was used to estimate genomic breeding values (GEBV) and reliability of GEBV (R 2 PEV ) was based on the prediction error variance approach. Reliability of GEBV ranged from ∼0.46 (FY and PY) to 0.56 (MY) with TR1 and from 0.51 (PY) to 0.65 (MY) with TR2. When averaged across all traits, R 2 PEV were substantially higher (R 2 PEV of TR1 = 0.50 and TR2 = 0.57) compared with reliabilities of parent averages (0.35) computed from pedigree data and based on diagonals of the coefficient matrix (prediction error variance approach). Reliability was similar for all the 4 marker panels using either TR1 or TR2, except that imputed HD cow data set led to an inflation of reliability. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information. A reduced panel of ∼15K markers resulted in reliabilities similar to using HD markers. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

PubMed Central

Meseret, S.; Tamir, B.; Gebreyohannes, G.; Lidauer, M.; Negussie, E.

2015-01-01

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations. PMID:26194217

Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis Type I and Scoliosis

DTIC Science & Technology

2011-08-01

AWARD NUMBER: W81XWH-10-1-0469 TITLE: Genetic Evaluation for the Scoliosis Gene(s) in...Patients with Neurofibromatosis Type I and Scoliosis PRINCIPAL INVESTIGATOR: David W. Polly, Jr., M.D. CONTRACTING ORGANIZATION: University...for the Scoliosis Gene(s) in Patients with Neurofibromatosis Type I and Scoliosis 5b. GRANT NUMBER W81XWH-10-1-0469 5c. PROGRAM ELEMENT NUMBER 6

Obtaining genetic testing in pediatric epilepsy.

PubMed

Ream, Margie A; Patel, Anup D

2015-10-01

The steps from patient evaluation to genetic diagnosis remain complicated. We discuss some of the genetic testing methods available along with their general advantages and disadvantages. We briefly review common pediatric epilepsy syndromes with strong genetic association and provide a potentially useful algorithm for genetic testing in drug-resistant epilepsy. We performed an extensive literature review of available information as it pertains to genetic testing and genetics in pediatric epilepsy. If a genetic disorder is suspected as the cause of epilepsy, based on drug resistance, family history, or clinical phenotype, timely diagnosis may reduce overall cost, limit the diagnostic odyssey that can bring much anxiety to families, improve prognostic accuracy, and lead to targeted therapy. Interpretation of complicated results should be performed only in collaboration with geneticists and genetic counselors, unless the ordering neurologist has a strong background in and understanding of genetics. Genetic testing can play an important role in the care provided to patients with epilepsy. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

A Clinician's primer in human genetics: what nurses need to know.

PubMed

Lea, D H

2000-09-01

This article provides nurses with general information about the structure and function of genes, metabolic and chromosomal disorders, and the inheritance of genetic conditions in families. It serves as a foundation for the remainder of this issue, which addresses the clinical application of genetic principles, genetic counseling and evaluation, and emerging genetic technologies. Nurses are present in all health care settings and care for individuals and families throughout their patient's life span. Nurses must therefore have adequate knowledge of human genetics so that they can identify individuals who may have a genetic condition or predisposition, and ensure that those individuals have access to the most current genetic diagnostics, treatment, and management therapeutics. With this knowledge, nurses can collect appropriate family histories, provide current genetic information, and support patients, families, and communities as they integrate this new information and technology into their daily lives.

Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: meta-analysis of nine studies in the CHARGE consortium

USDA-ARS?s Scientific Manuscript database

Scope: Tissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated i...

Genetic and Morphological Differentiation of the Semiterrestrial Crab Armases angustipes (Brachyura: Sesarmidae) along the Brazilian Coast.

PubMed

Marochi, Murilo Zanetti; Masunari, Setuko; Schubart, Christoph D

2017-02-01

The genetic and morphometric population structures of the semiterrestrial crab Armases angustipes from along the Brazilian coast were examined. The influence of the Central South Equatorial Current on larval dispersal of A. angustipes also was evaluated. Six populations were sampled from estuarine areas in São Luis do Maranhão, Maranhão; Natal, Rio Grande do Norte; Maceió, Alagoas; Ilhéus, Bahia; Aracruz, Espírito Santo; and Guaratuba, Paraná. Patterns of genetic differentiation were assessed using DNA sequence data corresponding to parts of the mitochondrial cytochrome c oxidase subunit 1. Geometric morphometric techniques were used to evaluate morphological variation in shape and size of the carapace and right cheliped propodus. Our results revealed low genetic variability and lack of phylogeographic structure; geometric morphometrics showed statistically significant morphological differentiation and geographic structuring. Our data indicate the absence of possible barriers to gene flow for this mobile species, and no clear correlation of morphological or genetic variation with ocean currents and/or geographic distance. Our results also suggest that historical geological and climatological events and/or possible bottleneck effects influenced the current low genetic variability among the populations of A. angustipes.

Dilated Cardiomyopathy: Genetic Determinants and Mechanisms.

PubMed

McNally, Elizabeth M; Mestroni, Luisa

2017-09-15

Nonischemic dilated cardiomyopathy (DCM) often has a genetic pathogenesis. Because of the large number of genes and alleles attributed to DCM, comprehensive genetic testing encompasses ever-increasing gene panels. Genetic diagnosis can help predict prognosis, especially with regard to arrhythmia risk for certain subtypes. Moreover, cascade genetic testing in family members can identify those who are at risk or with early stage disease, offering the opportunity for early intervention. This review will address diagnosis and management of DCM, including the role of genetic evaluation. We will also overview distinct genetic pathways linked to DCM and their pathogenetic mechanisms. Historically, cardiac morphology has been used to classify cardiomyopathy subtypes. Determining genetic variants is emerging as an additional adjunct to help further refine subtypes of DCM, especially where arrhythmia risk is increased, and ultimately contribute to clinical management. © 2017 American Heart Association, Inc.

Landscape genetic approaches to guide native plant restoration in the Mojave Desert

USGS Publications Warehouse

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2016-01-01

Restoring dryland ecosystems is a global challenge due to synergistic drivers of disturbance coupled with unpredictable environmental conditions. Dryland plant species have evolved complex life-history strategies to cope with fluctuating resources and climatic extremes. Although rarely quantified, local adaptation is likely widespread among these species and potentially influences restoration outcomes. The common practice of reintroducing propagules to restore dryland ecosystems, often across large spatial scales, compels evaluation of adaptive divergence within these species. Such evaluations are critical to understanding the consequences of large-scale manipulation of gene flow and to predicting success of restoration efforts. However, genetic information for species of interest can be difficult and expensive to obtain through traditional common garden experiments. Recent advances in landscape genetics offer marker-based approaches for identifying environmental drivers of adaptive genetic variability in non-model species, but tools are still needed to link these approaches with practical aspects of ecological restoration. Here, we combine spatially-explicit landscape genetics models with flexible visualization tools to demonstrate how cost-effective evaluations of adaptive genetic divergence can facilitate implementation of different seed sourcing strategies in ecological restoration. We apply these methods to Amplified Fragment Length Polymorphism (AFLP) markers genotyped in two Mojave Desert shrub species of high restoration importance: the long-lived, wind-pollinated gymnosperm Ephedra nevadensis, and the short-lived, insect-pollinated angiosperm Sphaeralcea ambigua. Mean annual temperature was identified as an important driver of adaptive genetic divergence for both species. Ephedra showed stronger adaptive divergence with respect to precipitation variability, while temperature variability and precipitation averages explained a larger fraction of adaptive divergence in Sphaeralcea. We describe multivariate statistical approaches for interpolating spatial patterns of adaptive divergence while accounting for potential bias due to neutral genetic structure. Through a spatial bootstrapping procedure, we also visualize patterns in the magnitude of model uncertainty. Finally, we introduce an interactive, distance-based mapping approach that explicitly links marker-based models of adaptive divergence with local or admixture seed sourcing strategies, promoting effective native plant restoration.

Simulating Drosophila Genetics with the Computer.

ERIC Educational Resources Information Center

Small, James W., Jr.; Edwards, Kathryn L.

1979-01-01

Presents some techniques developed to help improve student understanding of Mendelian principles through the use of a computer simulation model by the genetic system of the fruit fly. Includes discussion and evaluation of this computer assisted program. (MA)

Genetic differentiation of the mitochondrial cytochrome oxidase C subunit I gene in genus Paramecium (Protista, Ciliophora).

PubMed

Zhao, Yan; Gentekaki, Eleni; Yi, Zhenzhen; Lin, Xiaofeng

2013-01-01

The mitochondrial cytochrome c oxidase subunit I (COI) gene is being used increasingly for evaluating inter- and intra-specific genetic diversity of ciliated protists. However, very few studies focus on assessing genetic divergence of the COI gene within individuals and how its presence might affect species identification and population structure analyses. We evaluated the genetic variation of the COI gene in five Paramecium species for a total of 147 clones derived from 21 individuals and 7 populations. We identified a total of 90 haplotypes with several individuals carrying more than one haplotype. Parsimony network and phylogenetic tree analyses revealed that intra-individual diversity had no effect in species identification and only a minor effect on population structure. Our results suggest that the COI gene is a suitable marker for resolving inter- and intra-specific relationships of Paramecium spp.

Genetic Differentiation of the Mitochondrial Cytochrome Oxidase c Subunit I Gene in Genus Paramecium (Protista, Ciliophora)

PubMed Central

Zhao, Yan; Gentekaki, Eleni; Yi, Zhenzhen; Lin, Xiaofeng

2013-01-01

Background The mitochondrial cytochrome c oxidase subunit I (COI) gene is being used increasingly for evaluating inter- and intra-specific genetic diversity of ciliated protists. However, very few studies focus on assessing genetic divergence of the COI gene within individuals and how its presence might affect species identification and population structure analyses. Methodology/Principal findings We evaluated the genetic variation of the COI gene in five Paramecium species for a total of 147 clones derived from 21 individuals and 7 populations. We identified a total of 90 haplotypes with several individuals carrying more than one haplotype. Parsimony network and phylogenetic tree analyses revealed that intra-individual diversity had no effect in species identification and only a minor effect on population structure. Conclusions Our results suggest that the COI gene is a suitable marker for resolving inter- and intra-specific relationships of Paramecium spp. PMID:24204730

Estimates of genetic parameters in turkeys. 3. Sexual dimorphism and its implications in selection procedures.

PubMed

Toelle, V D; Havenstein, G B; Nestor, K E; Bacon, W L

1990-10-01

Live, carcass, and skeletal data taken at 16 wk of age on 504 female and 584 male turkeys from 34 sires and 168 dams were utilized to evaluate sex differences in genetic parameter estimates. Data were transformed to common mean and variance to evaluate possible scaling effects. Genetic parameters were estimated from transformed and untransformed data. Further analyses were conducted with a model that included sire by sex and dams within sire by sex interactions, and the variance estimates were used to calculate genetic correlations between the sexes and genetic regression parameters. Heritability estimates from transformed and untransformed data were similar, indicating that sex differences were present in the genetic parameters, but scaling effects were not an important factor. Genetic correlation estimates from paternal (PHS) and maternal (MHS) half-sib estimates were close to unity for BW (1.14, PHS; 1.09, MHS), shank width (.99, PHS; .93, MHS), breast muscle weight (1.23, PHS; 1.04, MHS), and shank length (1.09, PHS; .97, MHS). However, abdominal fat (.79, PHS; .59 MHS), total drumstick muscle weight (.75, PHS; 1.14, MHS), rough cleaned shank weight (.78, PHS; not estimatable, MHS), and shank bone density (1.00, PHS; .53, MHS) estimates were somewhat lower. The estimates suggest that the measurement of these latter "traits" at the same age in the two sexes may, in fact, be measuring different genetic effects and that selection procedures in turkeys need to take these correlations into account in order to make optimum progress. The genetic regression parameters indicated that more intense selection in the sex that has the smaller genetic variation could be practiced to make greater gains in the opposite sex.

Utilization of Genetic Testing Prior to Subspecialist Referral for Cerebellar Ataxia

PubMed Central

Fogel, Brent L.; Vickrey, Barbara G.; Walton-Wetzel, Jenny; Lieber, Eli

2013-01-01

Objective: To evaluate the utilization of laboratory testing in the diagnosis of cerebellar ataxia, including the completeness of initial standard testing for acquired causes, the early use of genetic testing, and associated clinical and nonclinical factors, among a cohort referred for subspecialty consultation. Methods: Data were abstracted from records of 95 consecutive ataxia patients referred to one neurogenetics subspecialist from 2006–2010 and linked to publicly available data on characteristics of referral clinicians. Multivariable logistic and linear regression models were used to analyze unique associations of clinical and nonclinical factors with laboratory investigation of acquired causes and with early genetic testing prior to referral. Results: At referral, 27 of 95 patients lacked evidence of any of 14 laboratory studies suggested for initial work-up of an acquired cause for ataxia (average number of tests=4.5). In contrast, 92% of patients had undergone brain magnetic resonance imaging prior to referral. Overall, 41.1% (n=39) had genetic testing prior to referral; there was no association between family history of ataxia and obtaining genetic testing prior to referral (p=0.39). The level of early genetic testing was 31.6%, primarily due to genetic testing despite an incomplete laboratory evaluation for acquired causes and no family history. A positive family history was consistently associated with less extensive laboratory testing (p=0.004), and referral by a neurologist was associated with higher levels of early genetic testing. Conclusions: Among consecutive referrals to a single center, a substantial proportion of sporadic cases had genetic testing without evidence of a work-up for acquired causes. Better strategies to guide decision making and subspecialty referrals in rare neurologic disorders are needed, given the cost and consequences of genetic testing. PMID:23725007

Genetic variation among interconnected populations of Catostomus occidentalis: Implications for distinguishing impacts of contaminants from biogeographical structuring

USGS Publications Warehouse

Whitehead, A.; Anderson, S.L.; Kuivila, K.M.; Roach, J.L.; May, B.

2003-01-01

Exposure to contaminants can affect survivorship, recruitment, reproductive success, mutation rates and migration, and may play a significant role in the partitioning of genetic variation among exposed and nonexposed populations. However, the application of molecular population genetic data to evaluate such influences has been uncommon and often flawed. We tested whether patterns of genetic variation among native fish populations (Sacramento sucker, Catostomus occidentalis) in the Central Valley of California were consistent with long-term pesticide exposure history, or primarily with expectations based on biogeography. Field sampling was designed to rigorously test for both geographical and contamination influences. Fine-scale structure of these interconnected populations was detected with both amplified fragment length polymorphisms (AFLP) and microsatellite markers, and patterns of variation elucidated by the two marker systems were highly concordant. Analyses indicated that biogeographical hypotheses described the data set better than hypotheses relating to common historical pesticide exposure. Downstream populations had higher genetic diversity than upstream populations, regardless of exposure history, and genetic distances showed that populations from the same river system tended to cluster together. Relatedness among populations reflected primarily directions of gene flow, rather than convergence among contaminant-exposed populations. Watershed geography accounted for significant partitioning of genetic variation among populations, whereas contaminant exposure history did not. Genetic patterns indicating contaminant-induced selection, increased mutation rates or recent bottlenecks were weak or absent. We stress the importance of testing contaminant-induced genetic change hypotheses within a biogeographical context. Strategic application of molecular markers for analysis of fine-scale structure, and for evaluating contaminant impacts on gene pools, is discussed.

Genetic variability in Jatropha curcas L. from diallel crossing.

PubMed

Ribeiro, D O; Silva-Mann, R; Alvares-Carvalho, S V; Souza, E M S; Vasconcelos, M C; Blank, A F

2017-05-18

Physic nut (Jatropha curcas L.) presents high oilseed yield and low production cost. However, technical-scientific knowledge on this crop is still limited. This study aimed to evaluate and estimate the genetic variability of hybrids obtained from dialell crossing. Genetic variability was carried out using ISSR molecular markers. For genetic variability, nine primers were used, and six were selected with 80.7% polymorphism. Genetic similarity was obtained using the NTSYS pc. 2.1 software, and cluster analysis was obtained by the UPGMA method. Mean genetic similarity was 58.4% among hybrids; the most divergent pair was H1 and H10 and the most similar pair was H9 and H10. ISSR PCR markers provided a quick and highly informative system for DNA fingerprinting, and also allowed establishing genetic relationships of Jatropha hybrids.

Nuclear fuel management optimization using genetic algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeChaine, M.D.; Feltus, M.A.

1995-07-01

The code independent genetic algorithm reactor optimization (CIGARO) system has been developed to optimize nuclear reactor loading patterns. It uses genetic algorithms (GAs) and a code-independent interface, so any reactor physics code (e.g., CASMO-3/SIMULATE-3) can be used to evaluate the loading patterns. The system is compared to other GA-based loading pattern optimizers. Tests were carried out to maximize the beginning of cycle k{sub eff} for a pressurized water reactor core loading with a penalty function to limit power peaking. The CIGARO system performed well, increasing the k{sub eff} after lowering the peak power. Tests of a prototype parallel evaluation methodmore » showed the potential for a significant speedup.« less

A Lens for Evaluating Genetic Information Governance Models: Balancing Equity, Efficiency and Sustainability.

PubMed

Skorve, Espen; Vassilakopoulou, Polyxeni; Aanestad, Margunn; Grünfeld, Thomas

2017-01-01

This paper draws from the literature on collective action and the governance of the commons to address the governance of genetic data on variants of specific genes. Specifically, the data arrangements under study relate to the BRCA genes (BRCA1 and BRCA2) which are linked to breast and ovarian cancer. These data are stored in global genetic data repositories and accessed by researchers and clinicians, from both public and private institutions. The current BRCA data arrangements are fragmented and politicized as there are multiple tensions around data ownership and sharing. Three key principles are proposed for forming and evaluating data governance arrangements in the field. These principles are: equity, efficiency and sustainability.

Genetic horoscopes: is it all in the genes? Points for regulatory control of direct-to-consumer genetic testing

PubMed Central

Patch, Christine; Sequeiros, Jorge; Cornel, Martina C

2009-01-01

The development of tests for genetic susceptibility to common complex diseases has raised concerns. These concerns relate to evaluation of the scientific and clinical validity and utility of the tests, quality assurance of laboratories and testing services, advice and protection for the consumer and the appropriate regulatory and policy response. How these concerns are interpreted and addressed is an ongoing debate. If the possibility of using the discoveries from genomic science to improve health is to be realised without losing public confidence, then improvements in the evaluation and mechanisms for control of supply of tests may be as important as the science itself. PMID:19259126

Genetic horoscopes: is it all in the genes? Points for regulatory control of direct-to-consumer genetic testing.

PubMed

Patch, Christine; Sequeiros, Jorge; Cornel, Martina C

2009-07-01

The development of tests for genetic susceptibility to common complex diseases has raised concerns. These concerns relate to evaluation of the scientific and clinical validity and utility of the tests, quality assurance of laboratories and testing services, advice and protection for the consumer and the appropriate regulatory and policy response. How these concerns are interpreted and addressed is an ongoing debate. If the possibility of using the discoveries from genomic science to improve health is to be realised without losing public confidence, then improvements in the evaluation and mechanisms for control of supply of tests may be as important as the science itself.

Standards for the Reporting of Genetic Counseling Interventions in Research and Other Studies (GCIRS): an NSGC Task Force Report.

PubMed

Hooker, Gillian W; Babu, D; Myers, M F; Zierhut, H; McAllister, M

2017-06-01

As the demand for evidence to support the value of genetic counseling increases, it is critical that reporting of genetic counseling interventions in research and other types of studies (e.g. process improvement or service evaluation studies) adopt greater rigor. As in other areas of healthcare, the appraisal, synthesis, and translation of research findings into genetic counseling practice are likely to be improved if clear specifications of genetic counseling interventions are reported when studies involving genetic counseling are published. To help improve reporting practices, the National Society of Genetic Counselors (NSGC) convened a task force in 2015 to develop consensus standards for the reporting of genetic counseling interventions. Following review by the NSGC Board of Directors, the NSGC Practice Guidelines Committee and the editorial board of the Journal of Genetic Counseling, 23 items across 8 domains were proposed as standards for the reporting of genetic counseling interventions in the published literature (GCIRS: Genetic Counseling Intervention Reporting Standards). The authors recommend adoption of these standards by authors and journals when reporting studies involving genetic counseling interventions.

Genetic diversity of popcorn genotypes using molecular analysis.

PubMed

Resh, F S; Scapim, C A; Mangolin, C A; Machado, M F P S; do Amaral, A T; Ramos, H C C; Vivas, M

2015-08-19

In this study, we analyzed dominant molecular markers to estimate the genetic divergence of 26 popcorn genotypes and evaluate whether using various dissimilarity coefficients with these dominant markers influences the results of cluster analysis. Fifteen random amplification of polymorphic DNA primers produced 157 amplified fragments, of which 65 were monomorphic and 92 were polymorphic. To calculate the genetic distances among the 26 genotypes, the complements of the Jaccard, Dice, and Rogers and Tanimoto similarity coefficients were used. A matrix of Dij values (dissimilarity matrix) was constructed, from which the genetic distances among genotypes were represented in a more simplified manner as a dendrogram generated using the unweighted pair-group method with arithmetic average. Clusters determined by molecular analysis generally did not group material from the same parental origin together. The largest genetic distance was between varieties 17 (UNB-2) and 18 (PA-091). In the identification of genotypes with the smallest genetic distance, the 3 coefficients showed no agreement. The 3 dissimilarity coefficients showed no major differences among their grouping patterns because agreement in determining the genotypes with large, medium, and small genetic distances was high. The largest genetic distances were observed for the Rogers and Tanimoto dissimilarity coefficient (0.74), followed by the Jaccard coefficient (0.65) and the Dice coefficient (0.48). The 3 coefficients showed similar estimations for the cophenetic correlation coefficient. Correlations among the matrices generated using the 3 coefficients were positive and had high magnitudes, reflecting strong agreement among the results obtained using the 3 evaluated dissimilarity coefficients.

Scientific reporting is suboptimal for aspects that characterize genetic risk prediction studies: a review of published articles based on the Genetic RIsk Prediction Studies statement.

PubMed

Iglesias, Adriana I; Mihaescu, Raluca; Ioannidis, John P A; Khoury, Muin J; Little, Julian; van Duijn, Cornelia M; Janssens, A Cecile J W

2014-05-01

Our main objective was to raise awareness of the areas that need improvements in the reporting of genetic risk prediction articles for future publications, based on the Genetic RIsk Prediction Studies (GRIPS) statement. We evaluated studies that developed or validated a prediction model based on multiple DNA variants, using empirical data, and were published in 2010. A data extraction form based on the 25 items of the GRIPS statement was created and piloted. Forty-two studies met our inclusion criteria. Overall, more than half of the evaluated items (34 of 62) were reported in at least 85% of included articles. Seventy-seven percentage of the articles were identified as genetic risk prediction studies through title assessment, but only 31% used the keywords recommended by GRIPS in the title or abstract. Seventy-four percentage mentioned which allele was the risk variant. Overall, only 10% of the articles reported all essential items needed to perform external validation of the risk model. Completeness of reporting in genetic risk prediction studies is adequate for general elements of study design but is suboptimal for several aspects that characterize genetic risk prediction studies such as description of the model construction. Improvements in the transparency of reporting of these aspects would facilitate the identification, replication, and application of genetic risk prediction models. Copyright © 2014 Elsevier Inc. All rights reserved.

Genetic diversity and genetic structure of farmed and wild Chinese mitten crab (Eriocheir sinensis) populations from three major basins by mitochondrial DNA COI and Cyt b gene sequences.

PubMed

Zhang, Cheng; Li, Qingqing; Wu, Xugan; Liu, Qing; Cheng, Yongxu

2017-11-20

The Chinese mitten crab, Eriocheir sinensis, is one of the important native crab species in East Asian region, which has been widely cultured throughout China, particularly in river basins of Yangtze, Huanghe and Liaohe. This study was designed to evaluate the genetic diversity and genetic structure of cultured and wild E. sinensis populations from the three river basins based on mitochondrial DNA (mtDNA) cytochrome oxidase subunit I (COI) and cytochrome b (Cyt b). The results showed that there were 62 variable sites and 30 parsimony informative sites in the 647 bp of sequenced mtDNA COI from 335 samples. Similarly, a 637 bp segment of Cyt b provided 59 variable sites and 26 parsimony informative sites. AMOVA showed that the levels of genetic differentiation were low among six populations. Although the haplotype diversity and nucleotide diversity of Huanghe wild population had slightly higher than the other populations, there were no significant differences. There was no significant differentiation between the genetic and geographic distance of the six populations, and haplotype network diagram indicated that there may exist genetic hybrids of E. sinensis from different river basins. The results of clustering and neutrality tests revealed that the distance of geographical locations were not completely related to their genetic distance values for the six populations. In conclusion, these results have great significance for the evaluation and exploitation of germplasm resources of E. sinensis.

Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis

DTIC Science & Technology

2013-08-01

AD_________________ (Leave blank) Award Number: W81HWH-10-1-0469 TITLE: Genetic Evaluation for the Scoliosis Gene(s) in Patients with...Neurofibromatosis 1 and Scoliosis PRINCIPAL INVESTIGATOR: David W. Polly, Jr., MD CONTRACTING ORGANIZATION: UNIVERSITY OF MINNESOTA Minneapolis, MN 55455...the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis 5b. GRANT NUMBER W81HWH-10- -0469 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

The etiology of mathematical self-evaluation and mathematics achievement: understanding the relationship using a cross-lagged twin study from age 9 to 12

PubMed Central

Luo, Yu L.L.; Kovas, Yulia; Haworth, Claire M.A.; Plomin, Robert

2011-01-01

The genetic and environmental origins of individual differences in mathematical self-evaluation over time and its association with later mathematics achievement were investigated in a UK sample of 2138 twin pairs at ages 9 and 12. Self-evaluation indexed how good children think they are at mathematical activities and how much they like those activities. Mathematics achievement was assessed by teachers based on UK National Curriculum standards. At both ages self-evaluation was approximately 40% heritable, with the rest of the variance explained by non-shared environment. The results also suggested moderate reciprocal associations between self-evaluation and mathematics achievement across time, with earlier self-evaluation predicting later performance and earlier performance predicting later self-evaluation. These cross-lagged relationships were genetically rather than environmentally mediated. PMID:22102781

Morphoagronomic characterization and genetic diversity of a common bean RIL mapping population derived from the cross Rudá x AND 277.

PubMed

Silva, L C; Batista, R O; Anjos, R S R; Souza, M H; Carneiro, P C S; Souza, T L P O; Barros, E G; Carneiro, J E S

2016-07-29

Recombinant inbred lines (RILs) are a valuable resource for building genetic linkage maps. The presence of genetic variability in the RILs is essential for detecting associations between molecular markers and loci controlling agronomic traits of interest. The main goal of this study was to quantify the genetic diversity of a common bean RIL population derived from a cross between Rudá (Mesoamerican gene pool) and AND 277 (Andean gene pool). This population was developed by the single seed descent method from 500 F2 plants until the F10 generation. Seven quantitative traits were evaluated in the field in 393 RILs, the parental lines, and five control cultivars. The plants were grown using a randomized block design with additional controls and three replicates. Significant differences were observed among the RILs for all evaluated traits (P < 0.01). A comparison of the RILs and parental lines showed significant differences (P < 0.01) for the number of days to flowering (DFL) and to harvest (DH), productivity (PROD) and mass of 100 beans (M100); however, there were no significant differences for plant architecture, degree of seed flatness, or seed shape. These results indicate the occurrence of additive x additive epistatic interactions for DFL, DH, PROD, and M100. The 393 RILs were shown to fall into 10 clusters using Tocher's method. This RIL population clearly contained genetic variability for the evaluated traits, and this variability will be crucial for future studies involving genetic mapping and quantitative trait locus identification and analysis.

Evaluation of microsatellite loci from libraries derived from the wild diploid 'Calcutta 4' and 'Ouro' banana cultivars.

PubMed

Silva, P R O; Jesus, O N J; Creste, S; Figueira, A; Amorim, E P; Ferreira, C F

2015-09-25

Microsatellite markers have been widely used in the quantification of genetic variability and for genetic breeding in Musa spp. The objective of the present study was to evaluate the discriminatory power of microsatellite markers derived from 'Calcutta 4' and 'Ouro' genomic libraries, and to analyze the genetic variability among 30 banana accessions. Thirty-eight markers were used: 15 from the 'Ouro' library and 23 from the 'Calcutta 4' library. Genetic diversity was evaluated by considering SSR markers as both dominant markers because of the presence of triploid accessions, and co-dominant markers. For the dominant analysis, polymorphism information content (PIC) values for 44 polymorphic markers ranged from 0.063 to 0.533, with a mean value of 0.24. A dendrogram analysis separated the BGB-Banana accessions into 4 groups: the 'Ouro' and 'Muísa Tia' accessions were the most dissimilar (93% dissimilarity), while the most similar accessions were 'Pacovan' and 'Walha'. The mean genetic distance between samples was 0.74. For the analysis considering SSR markers as co-dominants, using only diploid accessions, two groups were separated based on their genome contents (A and B). The PIC values for the markers from the 'Calcutta 4' library varied from 0.4836 to 0.7886, whereas those from the 'Ouro' library ranged from 0.3800 to 0.7521. Given the high PIC values, the markers from both the libraries showed high discriminatory power, and can therefore be widely applied for analysis of genetic diversity, population structures, and linkage mapping in Musa spp.

Genetic variation in the prostaglandin E2 pathway is associated with primary graft dysfunction.

PubMed

Diamond, Joshua M; Akimova, Tatiana; Kazi, Altaf; Shah, Rupal J; Cantu, Edward; Feng, Rui; Levine, Matthew H; Kawut, Steven M; Meyer, Nuala J; Lee, James C; Hancock, Wayne W; Aplenc, Richard; Ware, Lorraine B; Palmer, Scott M; Bhorade, Sangeeta; Lama, Vibha N; Weinacker, Ann; Orens, Jonathan; Wille, Keith; Crespo, Maria; Lederer, David J; Arcasoy, Selim; Demissie, Ejigayehu; Christie, Jason D

2014-03-01

Biologic pathways with significant genetic conservation across human populations have been implicated in the pathogenesis of primary graft dysfunction (PGD). The evaluation of the role of recipient genetic variation in PGD has thus far been limited to single, candidate gene analyses. We sought to identify genetic variants in lung transplant recipients that are responsible for increased risk of PGD using a two-phase large-scale genotyping approach. Phase 1 was a large-scale candidate gene association study of the multicenter, prospective Lung Transplant Outcomes Group cohort. Phase 2 included functional evaluation of selected variants and a bioinformatics screening of variants identified in phase 1. After genetic data quality control, 680 lung transplant recipients were included in the analysis. In phase 1, a total of 17 variants were significantly associated with PGD, four of which were in the prostaglandin E2 family of genes. Among these were a coding variant in the gene encoding prostaglandin E2 synthase (PTGES2; P = 9.3 × 10(-5)) resulting in an arginine to histidine substitution at amino acid position 298, and three variants in a block containing the 5' promoter and first intron of the PTGER4 gene (encoding prostaglandin E2 receptor subtype 4; all P < 5 × 10(-5)). Functional evaluation in regulatory T cells identified that rs4434423A in the PTGER4 gene was associated with differential suppressive function of regulatory T cells. Further research aimed at replication and additional functional insight into the role played by genetic variation in prostaglandin E2 synthetic and signaling pathways in PGD is warranted.

GENETIC BASIS OF MURINE ANTIBACTERIAL DEFENSE TO STREPTOCOCCAL LUNG INFECTION

EPA Science Inventory

To evaluate the effect of genetic background and toll-like receptor 2 on antibacterial defense to streptococcal infection, eight genetically diverse strains of mice (A/J, DBA/2J, CAST/Ei, FVB/NJ, BALB/cJ, C57BL/6J, 129/SvImJ, and C3H/HeJ) and tlr2-deficient mice (C57BL/6

Development and evaluation of 200 novel SNP assays for population genetic studies of westslope cutthroat trout and genetic identification of related taxa

Treesearch

N. R. Campbell; S. J. Amish; V. L. Prichard; K. M. McKelvey; M. K. Young; M. K. Schwartz; J. C. Garza; G. Luikart; S. R. Narum

2012-01-01

DNA sequence data were collected and screened for single nucleotide polymorphisms (SNPs) in westslope cutthroat trout (Oncorhynchus clarki lewisi) and also for substitutions that could be used to genetically discriminate rainbow trout (O. mykiss) and cutthroat trout, as well as several cutthroat trout subspecies. In total, 260 expressed sequence tag-derived loci were...

Evaluation of genetic divergence among clones of conilon coffee after scheduled cycle pruning.

PubMed

Dalcomo, J M; Vieira, H D; Ferreira, A; Lima, W L; Ferrão, R G; Fonseca, A F A; Ferrão, M A G; Partelli, F L

2015-11-30

Coffea canephora genotypes from the breeding program of Instituto Capixaba de Pesquisa e Extensão Rural were evaluated, and genetic diversity was estimated with the aim of future improvement strategies. From an initial group of 55 genotypes, 18 from the region of Castelo, ES, were selected, and three clones of the cultivars "Vitória" and "robusta tropical." Upon completion of the scheduled cycle pruning, 17 morphoagronomic traits were measured in the 22 genotypes selected. The principal components method was used to evaluate the contributions relative to the traits. The genetic dissimilarity matrix was obtained through Mahalanobis generalized distance, and genotypes were grouped using the hierarchical method based on the mean of the distances. The most promising clones of Avaliação Castelo were AC02, AC03, AC12, AC13, AC22, AC24, AC26, AC27, AC28, AC29, AC30, AC35, AC36, AC37, AC39, AC40, AC43, and AC46. These methods detected high genetic variability, grouping, by similarity, the genotypes in five groups. The trait that contributed the least to genetic divergence was the number of leaves in plagiotropic branches; however, this was not eliminated, because discarding it altered the groups. There are superior genotypes with potential for use in the next stages of the breeding program, aimed at both the composition of clonal variety and hybridizations.

Can environmental pollution by metals change genetic diversity? Ucides cordatus (Linnaeus, 1763) as a study case in Southeastern Brazilian mangroves.

PubMed

Banci, Karina Rodrigues da Silva; Mori, Gustavo Maruyama; Oliveira, Marcos Antonio de; Paganelli, Fernanda Laroza; Pereira, Mariana Rangel; Pinheiro, Marcelo Antonio Amaro

2017-03-15

Industrial areas on estuarine systems are commonly affected by heavy metals, affecting all local biota. Random Amplified Polymorphic DNA (RAPD) was used to evaluate genetic diversity of Ucides cordatus at mangroves in southeastern Brazil (Juréia, J; São Vicente, SV; and Cubatão, C), with distinct pollution levels by metals. The genetic diversity of this species was compared with concentrations of metals (Cd, Pb, Cu, Cr and Hg) in the environment. A pollution gradient was confirmed (SV>C>J), with low levels detected in water, except for mercury in SV. All metals in the sediment samples were below Threshold Effect Level (TEL), without an apparent biological risk to the biota. Genetic distance was very similar between J and C, with SV occurring as an out-group. RAPD was a powerful tool to investigate the effect of metal pollution on genetic diversity of this mangrove crab, and to evaluate the conservation status of the mangrove ecosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

PubMed

Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-02-01

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme. Copyright © 2016 Elsevier Inc. All rights reserved.

Using Next-Generation Sequencing to Explore Genetics and Race in the High School Classroom

PubMed Central

Yang, Xinmiao; Hartman, Mark R.; Harrington, Kristin T.; Etson, Candice M.; Fierman, Matthew B.; Slonim, Donna K.; Walt, David R.

2017-01-01

With the development of new sequencing and bioinformatics technologies, concepts relating to personal genomics play an increasingly important role in our society. To promote interest and understanding of sequencing and bioinformatics in the high school classroom, we developed and implemented a laboratory-based teaching module called “The Genetics of Race.” This module uses the topic of race to engage students with sequencing and genetics. In the experimental portion of this module, students isolate their own mitochondrial DNA using standard biotechnology techniques and collect next-generation sequencing data to determine which of their classmates are most and least genetically similar to themselves. We evaluated the efficacy of this module by administering a pretest/posttest evaluation to measure student knowledge related to sequencing and bioinformatics, and we also conducted a survey at the conclusion of the module to assess student attitudes. Upon completion of our Genetics of Race module, students demonstrated significant learning gains, with lower-performing students obtaining the highest gains, and developed more positive attitudes toward scientific research. PMID:28408407

Notification: Evaluation of Office of Pesticide Programs’ Genetically Engineered Corn Insect Resistance Management

EPA Pesticide Factsheets

Project #OPE-FY15-0055, July 09, 2015. The EPA OIG plans to begin preliminary research on the EPA's ability to manage and prevent increased insect resistance to genetically engineered Bacillus thuringiensis (Bt) corn.

GENETIC ACTIVITY PROFILES AND HAZARD ASSESSMENT

EPA Science Inventory

A methodology has been developed to display and evaluate multiple test quantitative information on genetic toxicants for purposes of hazard/risk assessment. ose information is collected from the open literature: either the lowest effective dose (LED) or the highest ineffective do...

Genotype by environment interaction effects in genetic evaluation of preweaning gain for Line 1 Hereford cattle from Miles City, Montana.

PubMed

MacNeil, M D; Cardoso, F F; Hay, E

2017-09-01

It has long been recognized that genotype × environment interaction potentially influences genetic evaluation of beef cattle. However, this recognition has largely been ignored in systems for national cattle evaluation. The objective of this investigation was to determine if direct and maternal genetic effects on preweaning gain would be reranked depending on an environmental gradient as determined by year effects. Data used were from the 76-yr selection experiment with the Line 1 Hereford cattle raised at Miles City, MT. The data comprised recorded phenotypes from 7,566 animals and an additional 1,862 ancestral records included in the pedigree. The presence of genotype × environment interaction was examined using reaction norms wherein year effects on preweaning gain were hypothesized to linearly influence the EBV. Estimates of heritability for direct and maternal effects, given the average environment, were 10 ± 2 and 26 ± 3%, respectively. In an environment that is characterized by the 5th (95th) percentile of the distribution of year effects, the corresponding estimates of heritability were 18 ± 3 (22 ± 3%) and 30 ± 3% (30 ± 3%), respectively. Rank correlations of direct and maternal EBV appropriate to the 5th and 95th percentiles of the year effects were 0.67 and 0.92, respectively. In the average environment, the genetic trends were 255 ± 1 g/yr for direct effects and 557 ± 3 g/yr for maternal effects. In the fifth percentile environment, the corresponding estimates of genetic trend were 271 ± 1 and 540 ± 3 g/yr, respectively, and in the 95th percentile environment, they were 236 ± 1 and 578 ± 3 g/yr, respectively. Linear genetic trends in environmental sensitivity were observed for both the direct (-8.06 × 10 ± 0.49 × 10) and maternal (8.72 × 10 ± 0.43 × 10) effects. Therefore, changing systems of national cattle evaluation to more fully account for potential genotype × environment interaction would improve the assessment of breeding stock, particularly for direct effects. Estimates of environmental sensitivity parameters could also facilitate identification of genetic limitations to production.

Immunotoxicological evaluation of wheat genetically modified with TaDREB4 gene on BALB/c mice.

PubMed

Liang, Chun Lai; Zhang, Xiao Peng; Song, Yan; Jia, Xu Dong

2013-08-01

To evaluate the immunotoxicological effects of genetically modified wheat with TaDREB4 gene in female BALB/c mice. Female mice weighing 18-22 g were divided into five groups (10 mice/group), which were set as negative control group, common wheat group, parental wheat group, genetically modified wheat group and cyclophosphamide positive control group, respectively. Mice in negative control group and positive control group were fed with AIN93G diet, mice in common wheat group, non-genetically modified parental wheat group and genetically modified wheat group were fed with feedstuffs added corresponding wheat (the proportion is 76%) for 30 days, then body weight, absolute and relative weight of spleen and thymus, white blood cell count, histological examination of immune organ, peripheral blood lymphocytes phenotyping, serum cytokine, serum immunoglobulin, antibody plaque-forming cell, serum half hemolysis value, mitogen-induced splenocyte proliferation, delayed-type hypersensitivity reaction and phagocytic activities of phagocytes were detected. No immunotoxicological effects related to the consumption of the genetically modified wheat were observed in BALB/c mice when compared with parental wheat group, common wheat group and negative control group. From the immunotoxicological point of view, results from this study demonstrate that genetically modified wheat with TaDREB4 gene is as safe as the parental wheat. Copyright © 2013 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

Genetic evaluation of weekly body weight in Japanese quail using random regression models.

PubMed

Karami, K; Zerehdaran, S; Tahmoorespur, M; Barzanooni, B; Lotfi, E

2017-02-01

1. A total of 11 826 records from 2489 quails, hatched between 2012 and 2013, were used to estimate genetic parameters for BW (body weight) of Japanese quail using random regression models. Weekly BW was measured from hatch until 49 d of age. WOMBAT software (University of New England, Australia) was used for estimating genetic and phenotypic parameters. 2. Nineteen models were evaluated to identify the best orders of Legendre polynomials. A model with Legendre polynomial of order 3 for additive genetic effect, order 3 for permanent environmental effects and order 1 for maternal permanent environmental effects was chosen as the best model. 3. According to the best model, phenotypic and genetic variances were higher at the end of the rearing period. Although direct heritability for BW reduced from 0.18 at hatch to 0.12 at 7 d of age, it gradually increased to 0.42 at 49 d of age. It indicates that BW at older ages is more controlled by genetic components in Japanese quail. 4. Phenotypic and genetic correlations between adjacent periods except hatching weight were more closely correlated than remote periods. The present results suggested that BW at earlier ages, especially at hatch, are different traits compared to BW at older ages. Therefore, BW at earlier ages could not be used as a selection criterion for improving BW at slaughter age.

Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions.

PubMed

Petrini, J; Iung, L H S; Rodriguez, M A P; Salvian, M; Pértille, F; Rovadoscki, G A; Cassoli, L D; Coutinho, L L; Machado, P F; Wiggans, G R; Mourão, G B

2016-10-01

Information about genetic parameters is essential for selection decisions and genetic evaluation. These estimates are population specific; however, there are few studies with dairy cattle populations reared under tropical and sub-tropical conditions. Thus, the aim was to obtain estimates of heritability and genetic correlations for milk yield and quality traits using pedigree and genomic information from a Holstein population maintained in a tropical environment. Phenotypic records (n = 36 457) of 4203 cows as well as the genotypes for 57 368 single nucleotide polymorphisms from 755 of these cows were used. Covariance components were estimated using the restricted maximum likelihood method under a mixed animal model, considering a pedigree-based relationship matrix or a combined pedigree-genomic matrix. High heritabilities (around 0.30) were estimated for lactose and protein content in milk whereas moderate values (between 0.19 and 0.26) were obtained for percentages of fat, saturated fatty acids and palmitic acid in milk. Genetic correlations ranging from -0.38 to -0.13 were determined between milk yield and composition traits. The smaller estimates compared to other similar studies can be due to poor environmental conditions, which may reduce genetic variability. These results highlight the importance in using genetic parameters estimated in the population under evaluation for selection decisions. © 2016 Blackwell Verlag GmbH.

Anorexia Nervosa, Major Depression, and Suicide Attempts: Shared Genetic Factors

PubMed Central

Thornton, Laura M.; Welch, Elisabeth; Munn-Chernoff, Melissa A.; Lichtenstein, Paul; Bulik, Cynthia M.

2015-01-01

We evaluated the extent to which genetic and environmental factors influenced anorexia nervosa (AN), major depressive disorder (MDD), and suicide attempts (SA). Participants were 6,899 women from the Swedish Twin study of Adults Genes and Environment. A Cholesky decomposition assessed independent and overlapping genetic and environmental contributions to AN, MDD, and SA. Genetic factors accounted for a substantial amount of liability to all three traits; unique environmental factors accounted for most of the remaining liability. Shared genetic factors may underlie the co-expression of these traits. Results underscore the importance of assessing for signs of suicide among individuals with AN. PMID:26916469

Anorexia Nervosa, Major Depression, and Suicide Attempts: Shared Genetic Factors.

PubMed

Thornton, Laura M; Welch, Elisabeth; Munn-Chernoff, Melissa A; Lichtenstein, Paul; Bulik, Cynthia M

2016-10-01

The extent to which genetic and environmental factors influenced anorexia nervosa (AN), major depressive disorder (MDD), and suicide attempts (SA) were evaluated. Participants were 6,899 women from the Swedish Twin Study of Adults: Genes and Environment. A Cholesky decomposition assessed independent and overlapping genetic and environmental contributions to AN, MDD, and SA. Genetic factors accounted for a substantial amount of liability to all three traits; unique environmental factors accounted for most of the remaining liability. Shared genetic factors may underlie the coexpression of these traits. Results underscore the importance of assessing for signs of suicide among individuals with AN. © 2016 The American Association of Suicidology.

Genetics on the World Wide Web.

PubMed

Trangenstein, P A; Hetteberg, C

1998-11-01

Since 1990, when the Human Genome Project was initiated, the amount of genetic information on the World Wide Web (WWW) has grown substantially. The WWW has become an important resource for current, accurate, and reliable genetic information for health care professionals and the general public. The purpose of this article is to provide a variety of genetics-related WWW sites that are useful for all levels of practitioners interested in genetics. In selecting sites to be included in this article, a number of evaluation tools were reviewed. The primary concern was that these sites be reputable and provide accurate, timely information. A table of the WWW sites is included for quick easy reference.

Comparison of molecular breeding values based on within- and across-breed training in beef cattle

PubMed Central

2013-01-01

Background Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of purebreds. However, comparable studies using beef cattle field data have not been reported. Methods Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype. Results With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero. Conclusions Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set. PMID:23953034

Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

USGS Publications Warehouse

Safner, T.; Miller, M.P.; McRae, B.H.; Fortin, M.-J.; Manel, S.

2011-01-01

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

Monogenic and chromosomal causes of isolated speech and language impairment.

PubMed

Barnett, C P; van Bon, B W M

2015-11-01

The importance of a precise molecular diagnosis for children with intellectual disability, autism spectrum disorder and epilepsy has become widely accepted and genetic testing is an integral part of the diagnostic evaluation of these children. In contrast, children with an isolated speech or language disorder are not often genetically evaluated, despite recent evidence supporting a role for genetic factors in the aetiology of these disorders. Several chromosomal copy number variants and single gene disorders associated with abnormalities of speech and language have been identified. Individuals without a precise genetic diagnosis will not receive optimal management including interventions such as early testosterone replacement in Klinefelter syndrome, otorhinolaryngological and audiometric evaluation in 22q11.2 deletion syndrome, cardiovascular surveillance in 7q11.23 duplications and early dietary management to prevent obesity in proximal 16p11.2 deletions. This review summarises the clinical features, aetiology and management options of known chromosomal and single gene disorders that are associated with speech and language pathology in the setting of normal or only mildly impaired cognitive function. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Genetic diversity of the Arctic fox using SRAP markers.

PubMed

Zhang, M; Bai, X J

2013-12-04

Sequence-related amplified polymorphism (SRAP) is a recently developed molecular marker technique that is stable, simple, reliable, and achieves moderate to high numbers of codominant markers. This study is the first to apply SRAP markers in a mammal, namely the Arctic fox. In order to investigate the genetic diversity of the Arctic fox and to provide a reference for use of its germplasm, we analyzed 7 populations of Arctic fox by SRAP. The genetic similarity coefficient, genetic distance, proportion of polymorphic loci, total genetic diversity (Ht), genetic diversity within populations (Hs), and genetic differentiation (Gst) were calculated using the Popgene software package. The results indicated abundant genetic diversity among the different populations of Arctic fox studied in China. The genetic similarity coefficient ranged from 0.1694 to 0.0417, genetic distance ranged from 0.8442 to 0.9592, and the proportion of polymorphic loci was smallest in the TS group. Genetic diversity ranged from 0.2535 to 0.3791, Ht was 0.3770, Hs was 0.3158, Gst was 0.1624, and gene flow (Nm) was estimated at 2.5790. Thus, a high level of genetic diversity and many genetic relationships were found in the populations of Arctic fox evaluated in this study.

Cancer genetics education in a low- to middle-income country: evaluation of an interactive workshop for clinicians in Kenya.

PubMed

Hill, Jessica A; Lee, Su Yeon; Njambi, Lucy; Corson, Timothy W; Dimaras, Helen

2015-01-01

Clinical genetic testing is becoming an integral part of medical care for inherited disorders. While genetic testing and counseling are readily available in high-income countries, in low- and middle-income countries like Kenya genetic testing is limited and genetic counseling is virtually non-existent. Genetic testing is likely to become widespread in Kenya within the next decade, yet there has not been a concomitant increase in genetic counseling resources. To address this gap, we designed an interactive workshop for clinicians in Kenya focused on the genetics of the childhood eye cancer retinoblastoma. The objectives were to increase retinoblastoma genetics knowledge, build genetic counseling skills and increase confidence in those skills. The workshop was conducted at the 2013 Kenyan National Retinoblastoma Strategy meeting. It included a retinoblastoma genetics presentation, small group discussion of case studies and genetic counseling role-play. Knowledge was assessed by standardized test, and genetic counseling skills and confidence by questionnaire. Knowledge increased significantly post-workshop, driven by increased knowledge of retinoblastoma causative genetics. One-year post-workshop, participant knowledge had returned to baseline, indicating that knowledge retention requires more frequent reinforcement. Participants reported feeling more confident discussing genetics with patients, and had integrated more genetic counseling into patient interactions. A comprehensive retinoblastoma genetics workshop can increase the knowledge and skills necessary for effective retinoblastoma genetic counseling.

Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis

DTIC Science & Technology

2014-08-01

Genetic Evaluation for the Scoliosis Gene(s) in Patients with Neurofibromatosis 1 and Scoliosis PRINCIPAL INVESTIGATOR: David W. Polly, Jr... Neurofibromatosis 1 and Scoliosis 5b. GRANT NUMBER W81XWH-10-1-0469 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) David. W. Polly Jr., MD 5d. PROJECT...dystrophic scoliosis is one of most common skeletal manifestations of Neurofibromatosis type 1. Dystrophic scoliosis has a more progressive and

Learning about an Undiagosed Condition in an Adult

MedlinePlus

... of the public with current information on clinical research studies. For example, the study entitled "Studies of Children with Metabolic and Other Genetic Diseases" evaluates individuals of all ages (despite its title) with known or suspected genetic diseases. You can ...

Notification: Evaluation of EPA's Management of Resistance Issues Related to Herbicide Tolerant Genetically Engineered Crops

EPA Pesticide Factsheets

Project #OPE-FY16-0023, March 25, 2016. The EPA OIG plans to begin preliminary research to assess the EPA's management and oversight of resistance issues related to herbicide tolerant genetically engineered crops.

Accuracies of univariate and multivariate genomic prediction models in African cassava.

PubMed

Okeke, Uche Godfrey; Akdemir, Deniz; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2017-12-04

Genomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for crop species such as cassava that have long breeding cycles. Practically, to implement GS in cassava breeding, it is necessary to evaluate different GS models and to develop suitable models for an optimized breeding pipeline. In this paper, we compared (1) prediction accuracies from a single-trait (uT) and a multi-trait (MT) mixed model for a single-environment genetic evaluation (Scenario 1), and (2) accuracies from a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model to a multivariate (ME) multi-environment mixed model that accounts for genotype-by-environment interaction for multi-environment genetic evaluation (Scenario 2). For these analyses, we used 16 years of public cassava breeding data for six target cassava traits and a fivefold cross-validation scheme with 10-repeat cycles to assess model prediction accuracies. In Scenario 1, the MT models had higher prediction accuracies than the uT models for all traits and locations analyzed, which amounted to on average a 40% improved prediction accuracy. For Scenario 2, we observed that the ME model had on average (across all locations and traits) a 12% improved prediction accuracy compared to the uE model. We recommend the use of multivariate mixed models (MT and ME) for cassava genetic evaluation. These models may be useful for other plant species.

Genetic grouping strategies in selection efficiency of composite beef cattle ( × ).

PubMed

Petrini, J; Pertile, S F N; Eler, J P; Ferraz, J B S; Mattos, E C; Figueiredo, L G G; Mourão, G B

2015-02-01

The inclusion of genetic groups in sire evaluation has been widely used to represent genetic differences among animals not accounted for by the absence of parentage data. However, the definition of these groups is still arbitrary, and studies assessing the effects of genetic grouping strategies on the selection efficiency are rare. Therefore, the aim in this study was to compare genetic grouping strategies for animals with unknown parentage in prediction of breeding values (EBV). The total of 179,302 records of weaning weight (WW), 29,825 records of scrotal circumference (SC), and 70,302 records of muscling score (MUSC) from Montana Tropical animals, a Brazilian composite beef cattle population, were used. Genetic grouping strategies involving year of birth, sex of the unknown parent, birth farm, breed composition, and their combinations were evaluated. Estimated breeding values were predicted for each approach simulating a loss of genealogy data. Thereafter, these EBV were compared to those obtained in an analysis involving a real relationship matrix to estimate selection efficiency and correlations between EBV and animal rankings. The analysis model included the fixed effects of contemporary groups and class of the dam age at calving, the covariates of additive and nonadditive genetic effects, and age, and the additive genetic effect of animal as random effects. A second model also included the fixed effects of genetic group. The use of genetic groups resulted in means of selection efficiency and correlation of 70.4 to 97.1% and 0.51 to 0.94 for WW, 85.8 to 98.8% and 0.82 to 0.98 for SC, and 85.1 to 98.6% and 0.74 to 0.97 for MUSC, respectively. High selection efficiencies were observed for year of birth and breed composition strategies. The maximum absolute difference in annual genetic gain estimated through the use of complete genealogy and genetic groups were 0.38 kg for WW, 0.02 cm for SC, and 0.01 for MUSC, with lower differences obtained when year of birth was adopted as a genetic group criterion. Grouping strategy must consider selection decisions and the number of genetic groups formed, in the way that genetic groups represent the genetic differences in population and allow an adequate prediction of EBV.

Critical roles for a genetic code alteration in the evolution of the genus Candida.

PubMed

Silva, Raquel M; Paredes, João A; Moura, Gabriela R; Manadas, Bruno; Lima-Costa, Tatiana; Rocha, Rita; Miranda, Isabel; Gomes, Ana C; Koerkamp, Marian J G; Perrot, Michel; Holstege, Frank C P; Boucherie, Hélian; Santos, Manuel A S

2007-10-31

During the last 30 years, several alterations to the standard genetic code have been discovered in various bacterial and eukaryotic species. Sense and nonsense codons have been reassigned or reprogrammed to expand the genetic code to selenocysteine and pyrrolysine. These discoveries highlight unexpected flexibility in the genetic code, but do not elucidate how the organisms survived the proteome chaos generated by codon identity redefinition. In order to shed new light on this question, we have reconstructed a Candida genetic code alteration in Saccharomyces cerevisiae and used a combination of DNA microarrays, proteomics and genetics approaches to evaluate its impact on gene expression, adaptation and sexual reproduction. This genetic manipulation blocked mating, locked yeast in a diploid state, remodelled gene expression and created stress cross-protection that generated adaptive advantages under environmental challenging conditions. This study highlights unanticipated roles for codon identity redefinition during the evolution of the genus Candida, and strongly suggests that genetic code alterations create genetic barriers that speed up speciation.

Chemical and Biological Defense Test and Evaluation (T&E) Future Challenges

DTIC Science & Technology

2012-07-01

considerations. For example, while chimeric organisms, which comprise genetic material, metabolic pathways, and capabilities of two or more organisms, may be...they would become a concern to T&E efforts. Chimeric organisms are those that have been genetically manipulated to include genes or entire...Even in the absence of intentional genetic engineering, on average, we see one new emerging disease per year just as a result of natural

Estimates of epistatic and pleiotropic effects of casein alpha s1 (CSN1S1) and thyroglobulin (TG) genetic markers on beef heifer performance traits enhanced by selection

USDA-ARS?s Scientific Manuscript database

Genetic marker effects and type of inheritance are estimated with poor precision when minor marker allele frequencies are low. A stable composite population (MARC II) was subjected to marker assisted selection for two years to equalize CSN1S1 and TG genetic marker frequencies to evaluate the epista...

Effective communication of molecular genetic test results to primary care providers.

PubMed

Scheuner, Maren T; Edelen, Maria Orlando; Hilborne, Lee H; Lubin, Ira M

2013-06-01

We evaluated a template for molecular genetic test reports that was developed as a strategy to reduce communication errors between the laboratory and ordering clinician. We surveyed 1,600 primary care physicians to assess satisfaction, ease of use, and effectiveness of genetic test reports developed using our template and reports developed by clinical laboratories. Mean score differences of responses between the reports were compared using t-tests. Two-way analysis of variance evaluated the effect of template versus standard reports and the influence of physician characteristics. There were 396 (24%) respondents. Template reports had higher scores than the standard reports for each survey item. The gender and specialty of the physician did not influence scores; however, younger physicians gave higher scores regardless of report type. There was significant interaction between report type and whether physicians ordered or reviewed any genetic tests (none versus at least one) in the past year, P = 0.005. For each survey item assessing satisfaction, ease of use, and effectiveness, physicians gave higher ratings to genetic test reports developed with the template than standard reports used by clinical laboratories. Physicians least familiar with genetic test reports, and possibly having the greatest need for better communication, were best served by the template reports.

Genetic diversity among Korean bermudagrass (Cynodon spp.) ecotypes characterized by morphological, cytological and molecular approaches.

PubMed

Kang, Si-Yong; Lee, Geung-Joo; Lim, Ki Byung; Lee, Hye Jung; Park, In Sook; Chung, Sung Jin; Kim, Jin-Baek; Kim, Dong Sub; Rhee, Hye Kyung

2008-04-30

The genus Cynodon comprises ten species. The objective of this study was to evaluate the genetic diversity of Korean bermudagrasses at the morphological, cytological and molecular levels. Morphological parameters, the nuclear DNA content and ploidy levels were observed in 43 bermudagrass ecotypes. AFLP markers were evaluated to define the genetic diversity, and chromosome counts were made to confirm the inferred cytotypes. Nuclear DNA contents were in the ranges 1.42-1.56, 1.94-2.19, 2.54, and 2.77-2.85 pg/2C for the triploid, tetraploid, pentaploid, and hexaploid accessions, respectively. The inferred cytotypes were triploid (2n = 3x = 27), tetraploid (2n = 4x = 36), pentaploid (2n = 5x = 45), and hexaploid (2n = 6x = 54), but the majority of the collections were tetraploid (81%). Mitotic chromosome counts verified the corresponding ploidy levels. The fast growing fine-textured ecotypes had lower ploidy levels, while the pentaploids and hexaploids were coarse types. The genetic similarity ranged from 0.42 to 0.94 with an average of 0.64. UPGMA cluster analysis and principle coordinate analysis separated the ecotypes into 6 distinct groups. The genetic similarity suggests natural hybridization between the different cytotypes, which could be useful resources for future breeding and genetic studies.

Alternate Service Delivery Models in Cancer Genetic Counseling: A Mini-Review.

PubMed

Buchanan, Adam Hudson; Rahm, Alanna Kulchak; Williams, Janet L

2016-01-01

Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models, such as telephone counseling, telegenetics, and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology.

Multiplex Polymerase Chain Reaction for Identification of Shigellae and Four Shigella Species Using Novel Genetic Markers Screened by Comparative Genomics.

PubMed

Kim, Hyun-Joong; Ryu, Ji-Oh; Song, Ji-Yeon; Kim, Hae-Yeong

2017-07-01

In the detection of Shigella species using molecular biological methods, previously known genetic markers for Shigella species were not sufficient to discriminate between Shigella species and diarrheagenic Escherichia coli. The purposes of this study were to screen for genetic markers of the Shigella genus and four Shigella species through comparative genomics and develop a multiplex polymerase chain reaction (PCR) for the detection of shigellae and Shigella species. A total of seven genomic DNA sequences from Shigella species were subjected to comparative genomics for the screening of genetic markers of shigellae and each Shigella species. The primer sets were designed from the screened genetic markers and evaluated using PCR with genomic DNAs from Shigella and other bacterial strains in Enterobacteriaceae. A novel Shigella quintuplex PCR, designed for the detection of Shigella genus, S. dysenteriae, S. boydii, S. flexneri, and S. sonnei, was developed from the evaluated primer sets, and its performance was demonstrated with specifically amplified results from each Shigella species. This Shigella multiplex PCR is the first to be reported with novel genetic markers developed through comparative genomics and may be a useful tool for the accurate detection of the Shigella genus and species from closely related bacteria in clinical microbiology and food safety.

Spatial working memory function in twins with schizophrenia and bipolar disorder.

PubMed

Pirkola, Tiia; Tuulio-Henriksson, Annamari; Glahn, David; Kieseppä, Tuula; Haukka, Jari; Kaprio, Jaakko; Lönnqvist, Jouko; Cannon, Tyrone D

2005-12-15

Family studies are in conflict as to whether schizophrenia and bipolar disorder have independent genetic etiologies. Given the relatively low prevalence (approximately 1%) of these disorders, the use of quantitative endophenotypic markers of genetic liability might provide a more sensitive strategy for evaluating their genetic overlap. We have previously demonstrated that spatial working memory deficits increase in a dose-dependent fashion with increasing genetic proximity to a proband among the unaffected co-twins of schizophrenic patients. Here, we evaluated whether such deficits might also mark genetic susceptibility to bipolar disorder. The Wechsler Memory Scale-Revised Visual Memory Span and Digit Span subtests were administered to 46 schizophrenic patients, 32 of their unaffected co-twins, 22 bipolar patients, 16 of their unaffected co-twins, and 100 control twins, representing unselectively nationwide twin samples. Schizophrenic patients and their unaffected co-twins performed significantly worse than control subjects on the spatial working memory task, whereas only the schizophrenic patients performed significantly below the control subjects on the verbal working memory task. Neither bipolar patients nor their unaffected co-twins differed from control subjects on these measures. Our findings support the hypothesis that impairment in spatial working memory might effectively reflect an expression of genetic liability to schizophrenia but less clearly to bipolar disorder.

Genetic differentiation of spring-spawning and fall-spawning male Atlantic sturgeon in the James River, Virginia

PubMed Central

Balazik, Matthew T.; Farrae, Daniel J.; Darden, Tanya L.; Garman, Greg C.

2017-01-01

Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus, Acipenseridae) populations are currently at severely depleted levels due to historic overfishing, habitat loss, and pollution. The importance of biologically correct stock structure for effective conservation and management efforts is well known. Recent improvements in our understanding of Atlantic sturgeon migrations, movement, and the occurrence of putative dual spawning groups leads to questions regarding the true stock structure of this endangered species. In the James River, VA specifically, captures of spawning Atlantic sturgeon and accompanying telemetry data suggest there are two discrete spawning groups of Atlantic sturgeon. The two putative spawning groups were genetically evaluated using a powerful microsatellite marker suite to determine if they are genetically distinct. Specifically, this study evaluates the genetic structure, characterizes the genetic diversity, estimates effective population size, and measures inbreeding of Atlantic sturgeon in the James River. The results indicate that fall and spring spawning James River Atlantic sturgeon groups are genetically distinct (overall FST = 0.048, F’ST = 0.181) with little admixture between the groups. The observed levels of genetic diversity and effective population sizes along with the lack of detected inbreeding all indicated that the James River has two genetically healthy populations of Atlantic sturgeon. The study also demonstrates that samples from adult Atlantic sturgeon, with proper sample selection criteria, can be informative when creating reference population databases. The presence of two genetically-distinct spawning groups of Atlantic sturgeon within the James River raises concerns about the current genetic assignment used by managers. Other nearby rivers may also have dual spawning groups that either are not accounted for or are pooled in reference databases. Our results represent the second documentation of genetically distinct dual spawning groups of Atlantic sturgeon in river systems along the U.S. Atlantic coast, suggesting that current reference population database should be updated to incorporate both new samples and our increased understanding of Atlantic sturgeon life history. PMID:28686610

Evaluation: A Qualitative Pilot Study of Novel Information Technology Infrastructure to Communicate Genetic Variant Updates.

PubMed

Klinkenberg-Ramirez, Stephanie; Neri, Pamela M; Volk, Lynn A; Samaha, Sara J; Newmark, Lisa P; Pollard, Stephanie; Varugheese, Matthew; Baxter, Samantha; Aronson, Samuel J; Rehm, Heidi L; Bates, David W

2016-01-01

Partners HealthCare Personalized Medicine developed GeneInsight Clinic (GIC), a tool designed to communicate updated variant information from laboratory geneticists to treating clinicians through automated alerts, categorized by level of variant interpretation change. The study aimed to evaluate feedback from the initial users of the GIC, including the advantages and challenges to receiving this variant information and using this technology at the point of care. Healthcare professionals from two clinics that ordered genetic testing for cardiomyopathy and related disorders were invited to participate in one-hour semi-structured interviews and/ or a one-hour focus group. Using a Grounded Theory approach, transcript concepts were coded and organized into themes. Two genetic counselors and two physicians from two treatment clinics participated in individual interviews. Focus group participants included one genetic counselor and four physicians. Analysis resulted in 8 major themes related to structuring and communicating variant knowledge, GIC's impact on the clinic, and suggestions for improvements. The interview analysis identified longitudinal patient care, family data, and growth in genetic testing content as potential challenges to optimization of the GIC infrastructure. Participants agreed that GIC implementation increased efficiency and effectiveness of the clinic through increased access to genetic variant information at the point of care. Development of information technology (IT) infrastructure to aid in the organization and management of genetic variant knowledge will be critical as the genetic field moves towards whole exome and whole genome sequencing. Findings from this study could be applied to future development of IT support for genetic variant knowledge management that would serve to improve clinicians' ability to manage and care for patients.

Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values.

PubMed

Přibyl, J; Bauer, J; Čermák, V; Pešek, P; Přibylová, J; Šplíchal, J; Vostrá-Vydrová, H; Vostrý, L; Zavadilová, L

2015-10-01

Estimated breeding values (EBVs) and genomic enhanced breeding values (GEBVs) for milk production of young genotyped Holstein bulls were predicted using a conventional BLUP - Animal Model, a method fitting regression coefficients for loci (RRBLUP), a method utilizing the realized genomic relationship matrix (GBLUP), by a single-step procedure (ssGBLUP) and by a one-step blending procedure. Information sources for prediction were the nation-wide database of domestic Czech production records in the first lactation combined with deregressed proofs (DRP) from Interbull files (August 2013) and domestic test-day (TD) records for the first three lactations. Data from 2627 genotyped bulls were used, of which 2189 were already proven under domestic conditions. Analyses were run that used Interbull values for genotyped bulls only or that used Interbull values for all available sires. Resultant predictions were compared with GEBV of 96 young foreign bulls evaluated abroad and whose proofs were from Interbull method GMACE (August 2013) on the Czech scale. Correlations of predictions with GMACE values of foreign bulls ranged from 0.33 to 0.75. Combining domestic data with Interbull EBVs improved prediction of both EBV and GEBV. Predictions by Animal Model (traditional EBV) using only domestic first lactation records and GMACE values were correlated by only 0.33. Combining the nation-wide domestic database with all available DRP for genotyped and un-genotyped sires from Interbull resulted in an EBV correlation of 0.60, compared with 0.47 when only Interbull data were used. In all cases, GEBVs had higher correlations than traditional EBVs, and the highest correlations were for predictions from the ssGBLUP procedure using combined data (0.75), or with all available DRP from Interbull records only (one-step blending approach, 0.69). The ssGBLUP predictions using the first three domestic lactation records in the TD model were correlated with GMACE predictions by 0.69, 0.64 and 0.61 for milk yield, protein yield and fat yield, respectively.

Using simulation models to predict feed intake: phenotypic and genetic relationships between observed and predicted values in cattle.

PubMed

Williams, C B; Bennett, G L; Jenkins, T G; Cundiff, L V; Ferrell, C L

2006-06-01

The objectives of this study were to evaluate the accuracy of the Decision Evaluator for the Cattle Industry (DECI) and the Cornell Value Discovery System (CVDS) in predicting individual DMI and to assess the feasibility of using predicted DMI data in genetic evaluations of cattle. Observed individual animal data on the average daily DMI (OFI), ADG, and carcass measurements were obtained from postweaning records of 504 steers from 52 sires (502 with complete data). The experimental data and daily temperature and wind speed data were used as inputs to predict average daily feed DMI (kg) required (feed required; FR) for maintenance, cold stress, and ADG; maintenance and cold stress; ADG; maintenance and ADG; and maintenance alone, with CVDS (CFRmcg, CFRmc, CFRg, CFRmg, and CFRm, respectively) and DECI (DFRmcg, DFRmc, DFRg, DFRmg, and DFRm, respectively). Genetic parameters were estimated by REML using an animal model with age on test as a covariate and with genotype, age of dam, and year as fixed effects. Regression equations for observed on predicted DMI were OFI = 1.27 (SE = 0.27) + 0.83 (SE = 0.04) x CFRmcg [R2 = 0.44, residual SD (s(y.x)) = 0.669 kg/d] and OFI = 1.32 (SE = 0.22) + 0.8 (SE = 0.03) x DFRmcg (R2 = 0.53, s(y.x) = 0.612 kg/d). Heritability of OFI was 0.27 +/- 0.12, and heritabilities ranged from 0.33 +/- 0.12 to 0.41 +/- 0.13 for predicted measures of DMI. Phenotypic and genetic correlations between OFI and CFRmcg, CFRmc, CFRg, CFRmg, CFRm, DFRmcg, DFRmc, DFRg, DFRmg, and DFRm were 0.67, 0.73, 0.41, 0.63, 0.78, 0.73, 0.82, 0.45, 0.77, and 0.86 (P < 0.001 for all phenotypic correlations); and 0.95 +/- 0.07, 0.82 +/- 0.13, 0.89 +/- 0.09, 0.95 +/- 0.07, 0.91 +/- 0.09, 0.96 +/- 0.07, 0.89 +/- 0.09, 0.88 +/- 0.09, 0.96 +/- 0.06, and 0.96 +/- 0.07, respectively. Phenotypic and genetic correlations between CFRmcg and DFRmcg, CFRmc and DFRmc, CFRg and DFRg, CFRmg and DFRmg, and CFRm and DFRm were 0.98, 0.94, 0.99, 0.98, and 0.95 (P < 0.001 for all phenotypic correlations), and 0.99 +/- 0.004, 0.98 +/- 0.017, 0.99 +/- 0.004, 0.99 +/- 0.005, and 0.97 +/- 0.021, respectively. The strong genetic relationships between OFI and CFRmcg, CFRmg, DFRmcg, and DFRmg indicate that these predicted measures of DMI may be used in genetic evaluations and that DM requirements for cold stress may not be needed, thus reducing model complexity. However, high genetic correlations for final weight with OFI, CFRmcg, and DFRmcg suggest that the technology needs to be further evaluated in populations with genetic variance in feed efficiency.

Application of active learning modalities to achieve medical genetics competencies and their learning outcome assessments

PubMed Central

Hagiwara, Nobuko

2017-01-01

The steadily falling costs of genome sequencing, coupled with the growing number of genetic tests with proven clinical validity, have made the use of genetic testing more common in clinical practice. This development has necessitated nongeneticist physicians, especially primary care physicians, to become more responsible for assessing genetic risks for their patients. Providing undergraduate medical students a solid foundation in genomic medicine, therefore, has become all the more important to ensure the readiness of future physicians in applying genomic medicine to their patient care. In order to further enhance the effectiveness of instructing practical skills in medical genetics, the emphasis of active learning modules in genetics curriculum at medical schools has increased in recent years. This is because of the general acceptance of a better efficacy of active learner-centered pedagogy over passive lecturer-centered pedagogy. However, an objective standard to evaluate students’ skill levels in genomic medicine achieved by active learning is currently missing. Recently, entrustable professional activities (EPAs) in genomic medicine have been proposed as a framework for developing physician competencies in genomic medicine. EPAs in genomic medicine provide a convenient guideline for not only developing genomic medicine curriculum but also assessing students’ competency levels in practicing genomic medicine. In this review, the efficacy of different types of active learning modules reported for medical genetics curricula is discussed using EPAs in genomic medicine as a common evaluation standard for modules’ learning outcomes. The utility of the EPAs in genomic medicine for designing active learning modules in undergraduate medical genetics curricula is also discussed. PMID:29276425

Effects of Cancer Genetic Panel Testing on at-Risk Individuals.

PubMed

Frost, Anja S; Toaff, Miriam; Biagi, Tara; Stark, Elizabeth; McHenry, Allison; Kaltman, Rebecca

2018-06-01

To evaluate the role of screening patients at increased risk for hereditary cancer syndromes with an extended panel of cancer predisposition genes to identify actionable genetic mutations. A retrospective chart review was conducted of all patients presenting to a multidisciplinary cancer program for genetic counseling and testing from January 2015 to December 2016. Individuals presenting to the program were identified as at-risk by a personal or family history of cancer, by their health care provider, or by self-referral. All participants met current National Comprehensive Cancer Network criteria for genetic risk evaluation for hereditary cancer. The results of testing and its implications for management, based on National Comprehensive Cancer Network guidelines, were recorded. Of 670 at-risk patients who underwent genetic testing, 66 (9.9%) had BRCA-limited testing; of these, 26 of 670 (3.9%) had a deleterious or likely pathogenic mutation. Expanded panel testing was done for 560 of the 670 patients (83.4%), and abnormal results were found in 65 of 670 (9.7%); non-BRCA mutations (predominantly CHEK2) were found in 49 of the 65 (75%). Abnormal genetic testing was associated with increased surveillance in 96% of those with deleterious mutations, whereas negative testing for a known familial mutation in 45 patients was associated with a downgrade of their risk and reduction of subsequent surveillance and management. Guideline-based management is frequently altered by genetic testing, including panel testing, in patients at risk for cancer. We recommend that obstetrics and gynecology providers routinely refer at-risk patients for genetic counseling and testing when clinically appropriate.

Application of active learning modalities to achieve medical genetics competencies and their learning outcome assessments.

PubMed

Hagiwara, Nobuko

2017-01-01

The steadily falling costs of genome sequencing, coupled with the growing number of genetic tests with proven clinical validity, have made the use of genetic testing more common in clinical practice. This development has necessitated nongeneticist physicians, especially primary care physicians, to become more responsible for assessing genetic risks for their patients. Providing undergraduate medical students a solid foundation in genomic medicine, therefore, has become all the more important to ensure the readiness of future physicians in applying genomic medicine to their patient care. In order to further enhance the effectiveness of instructing practical skills in medical genetics, the emphasis of active learning modules in genetics curriculum at medical schools has increased in recent years. This is because of the general acceptance of a better efficacy of active learner-centered pedagogy over passive lecturer-centered pedagogy. However, an objective standard to evaluate students' skill levels in genomic medicine achieved by active learning is currently missing. Recently, entrustable professional activities (EPAs) in genomic medicine have been proposed as a framework for developing physician competencies in genomic medicine. EPAs in genomic medicine provide a convenient guideline for not only developing genomic medicine curriculum but also assessing students' competency levels in practicing genomic medicine. In this review, the efficacy of different types of active learning modules reported for medical genetics curricula is discussed using EPAs in genomic medicine as a common evaluation standard for modules' learning outcomes. The utility of the EPAs in genomic medicine for designing active learning modules in undergraduate medical genetics curricula is also discussed.

Improved performance of epidemiologic and genetic risk models for rheumatoid arthritis serologic phenotypes using family history

PubMed Central

Sparks, Jeffrey A.; Chen, Chia-Yen; Jiang, Xia; Askling, Johan; Hiraki, Linda T.; Malspeis, Susan; Klareskog, Lars; Alfredsson, Lars; Costenbader, Karen H.; Karlson, Elizabeth W.

2014-01-01

Objective To develop and validate rheumatoid arthritis (RA) risk models based on family history, epidemiologic factors, and known genetic risk factors. Methods We developed and validated models for RA based on known RA risk factors, among women in two cohorts: the Nurses’ Health Study (NHS, 381 RA cases and 410 controls) and the Epidemiological Investigation of RA (EIRA, 1244 RA cases and 971 controls). Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in logistic regression models for the study population and for those with positive family history. The joint effect of family history with genetics, smoking, and body mass index (BMI) was evaluated using logistic regression models to estimate odds ratios (OR) for RA. Results The complete model including family history, epidemiologic risk factors, and genetics demonstrated AUCs of 0.74 for seropositive RA in NHS and 0.77 for anti-citrullinated protein antibody (ACPA)-positive RA in EIRA. Among women with positive family history, discrimination was excellent for complete models for seropositive RA in NHS (AUC 0.82) and ACPA-positive RA in EIRA (AUC 0.83). Positive family history, high genetic susceptibility, smoking, and increased BMI had an OR of 21.73 for ACPA-positive RA. Conclusions We developed models for seropositive and seronegative RA phenotypes based on family history, epidemiologic and genetic factors. Among those with positive family history, models utilizing epidemiologic and genetic factors were highly discriminatory for seropositive and seronegative RA. Assessing epidemiological and genetic factors among those with positive family history may identify individuals suitable for RA prevention strategies. PMID:24685909

Is the child 'father of the man'? evaluating the stability of genetic influences across development.

PubMed

Ronald, Angelica

2011-11-01

This selective review considers findings in genetic research that have shed light on how genes operate across development. We will address the question of whether the child is 'father of the Man' from a genetic perspective. In other words, do the same genetic influences affect the same traits across development? Using a 'taster menu' approach and prioritizing newer findings on cognitive and behavioral traits, examples from the following genetic disciplines will be discussed: (a) developmental quantitative genetics (such as longitudinal twin studies), (b) neurodevelopmental genetic syndromes with known genetic causes (such as Williams syndrome), (c) developmental candidate gene studies (such as those that link infant and adult populations), (d) developmental genome-wide association studies (GWAS), and (e) DNA resequencing. Evidence presented here suggests that there is considerable genetic stability of cognitive and behavioral traits across development, but there is also evidence for genetic change. Quantitative genetic studies have a long history of assessing genetic continuity and change across development. It is now time for the newer, more technology-enabled fields such as GWAS and DNA resequencing also to take on board the dynamic nature of human behavior. 2011 Blackwell Publishing Ltd.

Evaluation of the contribution of D9S1120 to anthropological studies in Native American populations.

PubMed

Aguilar-Velázquez, J A; Martínez-Sevilla, V Manuel; Sosa-Macías, M; González-Martin, A; Muñoz-Valle, J F; Rangel-Villalobos, H

2017-12-01

The D9S1120 locus exhibits a population-specific allele of 9 repeats (9RA) in all Native American and two Siberian populations currently studied, but it is absent in other worldwide populations. Although this feature has been used in anthropological genetic studies, its impact on the evaluation of the structure and genetic relations among Native American populations has been scarcely assessed. Consequently, the aim of this study was to evaluate the anthropological impact of D9S1120 when it was added to STR population datasets in Mexican Native American groups. We analyzed D9S1120 by PCR and capillary electrophoresis (CE) in 1117 unrelated individuals from 13 native groups from the north and west of Mexico. Additional worldwide populations previously studied with D9S1120 and/or 15 autosomal STRs (Identifier kit) were included for interpopulation analyses. We report statistical results of forensic importance for D9S1120. On average, the modal alleles were the Native American-specific allele 9RA (0.3254) and 16 (0.3362). Genetic distances between Native American and worldwide populations were estimated. When D9S1120 was included in the 15 STR population dataset, we observed improvements for admixture estimation in Mestizo populations and for representing congruent genetic relationships in dendrograms. Analysis of molecular variance (AMOVA) based on D9S1120 confirms that most of the genetic variability in the Mexican population is attributable to their Native American backgrounds, and allows the detection of significant intercontinental differentiation attributed to the exclusive presence of 9RA in America. Our findings demonstrate the contribution of D9S1120 to a better understanding of the genetic relationships and structure among Mexican Native groups. Copyright © 2017 Elsevier GmbH. All rights reserved.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

PubMed

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

A universal genetic testing initiative for patients with high-grade, non-mucinous epithelial ovarian cancer and the implications for cancer treatment.

PubMed

Bednar, Erica M; Oakley, Holly D; Sun, Charlotte C; Burke, Catherine C; Munsell, Mark F; Westin, Shannon N; Lu, Karen H

2017-08-01

Genetic counseling (GC) and germline genetic testing (GT) for BRCA1 and BRCA2 are considered standard of care for patients with high-grade, non-mucinous epithelial ovarian, fallopian tube, and primary peritoneal cancers (HGOC). We describe a universal genetic testing initiative to increase the rates of recommendation and acceptance of GC and GT to >80% for patients with HGOC at our institution. Data from a consecutive cohort of patients seen in our gynecologic oncology clinics between 9/1/2012 and 8/31/2015 for evaluation of HGOC were retrospectively analyzed. Data were abstracted from the tumor registry, medical records, and research databases. Descriptive statistics were used to evaluate patient characteristics and GC, GT, and PARP inhibitor use. Various clinic interventions were developed, influenced by the Plan-Do-Study-Act cycle method, which included physician-coordinated GT, integrated GC, and assisted GC referrals. A cohort of 1636 patients presented to the gynecologic oncology clinics for evaluation of HGOC during our study period, and 1423 (87.0%) were recommended to have GC and GT. Of these, 1214 (85.3%) completed GT and 217 (17.9%) were found to have a BRCA1 or BRCA2 mutation. Among BRCA-positive patients, 167 had recurrent or progressive disease, and 56 of those received PARP inhibitor therapy. The rates of GC and GT recommendation and completion among patients with HGOC at our institution exceeded 80% following the implementation of a universal genetic testing initiative. Universal genetic testing of patients with HGOC is one strategy to identify those who may benefit from PARP inhibitor therapy. Copyright © 2017. Published by Elsevier Inc.

A fine structure genetic analysis evaluating ecoregional adaptability of a Bos taurus breed (Hereford)

PubMed Central

Krehbiel, B.; Ericsson, S. A.; Wilson, C.; Caetano, A. R.; Paiva, S. R.

2017-01-01

Ecoregional differences contribute to genetic environmental interactions and impact animal performance. These differences may become more important under climate change scenarios. Utilizing genetic diversity within a species to address such problems has not been fully explored. In this study Hereford cattle were genotyped with 50K Bead Chip or 770K Bovine Bead Chip to test the existence of genetic structure in five U.S. ecoregions characterized by precipitation, temperature and humidity and designated: cool arid (CA), cool humid (CH), transition zone (TZ), warm arid (WA), and warm humid (WH). SNP data were analyzed in three sequential analyses. Broad genetic structure was evaluated with STRUCTURE, and ADMIXTURE software using 14,312 SNPs after passing quality control variables. The second analysis was performed using principal coordinate analysis with 66 Tag SNPs associated in the literature with various aspects of environmental stressors (e.g., heat tolerance) or production (e.g., milk production). In the third analysis TreeSelect was used with the 66 SNPs to evaluate if ecoregional allelic frequencies deviated from a central frequency and by so doing are indicative of directional selection. The three analyses suggested subpopulation structures associated with ecoregions from where animals were derived. ADMIXTURE and PCA results illustrated the importance of temperature and humidity and confirm subpopulation assignments. Comparisons of allele frequencies with TreeSelect showed ecoregion differences, in particular the divergence between arid and humid regions. Patterns of genetic variability obtained by medium and high density SNP chips can be used to acclimatize a temperately derived breed to various ecoregions. As climate change becomes an important factor in cattle production, this study should be used as a proof of concept to review future breeding and conservation schemes aimed at adaptation to climatic events. PMID:28459870

Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution.

PubMed

Boueiz, Adel; Lutz, Sharon M; Cho, Michael H; Hersh, Craig P; Bowler, Russell P; Washko, George R; Halper-Stromberg, Eitan; Bakke, Per; Gulsvik, Amund; Laird, Nan M; Beaty, Terri H; Coxson, Harvey O; Crapo, James D; Silverman, Edwin K; Castaldi, Peter J; DeMeo, Dawn L

2017-03-15

Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe-predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. To identify the genetic influences of emphysema distribution in non-alpha-1 antitrypsin-deficient smokers. A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism-, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic approaches in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.

PubMed

Ovenden, Ben; Milgate, Andrew; Wade, Len J; Rebetzke, Greg J; Holland, James B

2018-05-31

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat under field conditions. A panel of 358 varieties and breeding lines constrained for maturity was evaluated under rainfed and irrigated treatments across two locations and two years. Whole-genome marker profiles and factor analytic mixed models were used to generate genomic estimated breeding values (GEBVs) for specific environments and environment groups. Additive genetic variance was smaller than residual genetic variance for WSCC, such that genotypic values were dominated by residual genetic effects rather than additive breeding values. As a result, GEBVs were not accurate predictors of genotypic values of the extant lines, but GEBVs should be reliable selection criteria to choose parents for intermating to produce new populations. The accuracy of GEBVs for untested lines was sufficient to increase predicted genetic gain from genomic selection per unit time compared to phenotypic selection if the breeding cycle is reduced by half by the use of GEBVs in off-season generations. Further, genomic prediction accuracy depended on having phenotypic data from environments with strong correlations with target production environments to build prediction models. By combining high-density marker genotypes, stress-managed field evaluations, and mixed models that model simultaneously covariances among genotypes and covariances of complex trait performance between pairs of environments, we were able to train models with good accuracy to facilitate genetic gain from genomic selection. Copyright © 2018 Ovenden et al.

Genetic Variation in the Prostaglandin E2 Pathway Is Associated with Primary Graft Dysfunction

PubMed Central

Akimova, Tatiana; Kazi, Altaf; Shah, Rupal J.; Cantu, Edward; Feng, Rui; Levine, Matthew H.; Kawut, Steven M.; Meyer, Nuala J.; Lee, James C.; Hancock, Wayne W.; Aplenc, Richard; Ware, Lorraine B.; Palmer, Scott M.; Bhorade, Sangeeta; Lama, Vibha N.; Weinacker, Ann; Orens, Jonathan; Wille, Keith; Crespo, Maria; Lederer, David J.; Arcasoy, Selim; Demissie, Ejigayehu; Christie, Jason D.

2014-01-01

Rationale: Biologic pathways with significant genetic conservation across human populations have been implicated in the pathogenesis of primary graft dysfunction (PGD). The evaluation of the role of recipient genetic variation in PGD has thus far been limited to single, candidate gene analyses. Objectives: We sought to identify genetic variants in lung transplant recipients that are responsible for increased risk of PGD using a two-phase large-scale genotyping approach. Methods: Phase 1 was a large-scale candidate gene association study of the multicenter, prospective Lung Transplant Outcomes Group cohort. Phase 2 included functional evaluation of selected variants and a bioinformatics screening of variants identified in phase 1. Measurements and Main Results: After genetic data quality control, 680 lung transplant recipients were included in the analysis. In phase 1, a total of 17 variants were significantly associated with PGD, four of which were in the prostaglandin E2 family of genes. Among these were a coding variant in the gene encoding prostaglandin E2 synthase (PTGES2; P = 9.3 × 10−5) resulting in an arginine to histidine substitution at amino acid position 298, and three variants in a block containing the 5′ promoter and first intron of the PTGER4 gene (encoding prostaglandin E2 receptor subtype 4; all P < 5 × 10−5). Functional evaluation in regulatory T cells identified that rs4434423A in the PTGER4 gene was associated with differential suppressive function of regulatory T cells. Conclusions: Further research aimed at replication and additional functional insight into the role played by genetic variation in prostaglandin E2 synthetic and signaling pathways in PGD is warranted. PMID:24467603

Landscape-scale evaluation of genetic structure among barrier-isolated populations of coastal cutthroat trout, Oncorhynchus clarkii clarkii

USGS Publications Warehouse

Guy, T.J.; Gresswell, R.E.; Banks, M.A.

2008-01-01

Relationships among landscape structure, stochastic disturbance, and genetic diversity were assessed by examining interactions between watershed-scale environmental factors and genetic diversity of coastal cutthroat trout (Oncorhynchus clarkii clarkii) in 27 barrier-isolated watersheds from western Oregon, USA. Headwater populations of coastal cutthroat trout were genetically differentiated (mean FST = 0.33) using data from seven microsatellite loci (2232 individuals), but intrapopulation microsatellite genetic diversity (mean number of alleles per locus = 5, mean He = 0.60) was only moderate. Genetic diversity of coastal cutthroat trout was greater (P = 0.02) in the Coast Range ecoregion (mean alleles = 47) than in the Cascades ecoregion (mean alleles = 30), and differences coincided with indices of regional within-watershed complexity and connectivity. Furthermore, regional patterns of diversity evident from isolation-by-distance plots suggested that retention of within-population genetic diversity in the Coast Range ecoregion is higher than that in the Cascades, where genetic drift is the dominant factor influencing genetic patterns. Thus, it appears that physical landscape features have influenced genetic patterns in these populations isolated from short-term immigration. ?? 2008 NRC.

[Study on tests of genetics experiments in universities].

PubMed

Jie, He; Hao, Zhang; Lili, Zhang

2015-03-01

Based on the present situation and the development of experiment tests in universities, we introduced a reform in tests of genetics experiments. According to the teaching goals and course contents of genetics experiment, the tests of genetics experiments contain four aspects on the performance of students: the adherence to the experimental procedures, the depth of participation in experiment, the quality of experiment report, and the mastery of experiment principles and skills, which account for 10 %, 20 %, 40 % and 30 % in the total scores, respectively. All four aspects were graded quantitatively. This evaluation system has been tested in our experiment teaching. The results suggest that it has an effect on the promotion of teaching in genetics experiments.

Genetic variation in polyploid forage grass: Assessing the molecular genetic variability in the Paspalum genus

PubMed Central

2013-01-01

Background Paspalum (Poaceae) is an important genus of the tribe Paniceae, which includes several species of economic importance for foraging, turf and ornamental purposes, and has a complex taxonomical classification. Because of the widespread interest in several species of this genus, many accessions have been conserved in germplasm banks and distributed throughout various countries around the world, mainly for the purposes of cultivar development and cytogenetic studies. Correct identification of germplasms and quantification of their variability are necessary for the proper development of conservation and breeding programs. Evaluation of microsatellite markers in different species of Paspalum conserved in a germplasm bank allowed assessment of the genetic differences among them and assisted in their proper botanical classification. Results Seventeen new polymorphic microsatellites were developed for Paspalum atratum Swallen and Paspalum notatum Flüggé, twelve of which were transferred to 35 Paspalum species and used to evaluate their variability. Variable degrees of polymorphism were observed within the species. Based on distance-based methods and a Bayesian clustering approach, the accessions were divided into three main species groups, two of which corresponded to the previously described Plicatula and Notata Paspalum groups. In more accurate analyses of P. notatum accessions, the genetic variation that was evaluated used thirty simple sequence repeat (SSR) loci and revealed seven distinct genetic groups and a correspondence of these groups to the three botanical varieties of the species (P. notatum var. notatum, P. notatum var. saurae and P. notatum var. latiflorum). Conclusions The molecular genetic approach employed in this study was able to distinguish many of the different taxa examined, except for species that belong to the Plicatula group, which has historically been recognized as a highly complex group. Our molecular genetic approach represents a valuable tool for species identification in the initial assessment of germplasm as well as for characterization, conservation and successful species hybridization. PMID:23759066

Recent developments in genetics and medically assisted reproduction: from research to clinical applications.

PubMed

Harper, J C; Aittomäki, K; Borry, P; Cornel, M C; de Wert, G; Dondorp, W; Geraedts, J; Gianaroli, L; Ketterson, K; Liebaers, I; Lundin, K; Mertes, H; Morris, M; Pennings, G; Sermon, K; Spits, C; Soini, S; van Montfoort, A P A; Veiga, A; Vermeesch, J R; Viville, S; Macek, M

2018-01-01

Two leading European professional societies, the European Society of Human Genetics and the European Society for Human Reproduction and Embryology, have worked together since 2004 to evaluate the impact of fast research advances at the interface of assisted reproduction and genetics, including their application into clinical practice. In September 2016, the expert panel met for the third time. The topics discussed highlighted important issues covering the impacts of expanded carrier screening, direct-to-consumer genetic testing, voiding of the presumed anonymity of gamete donors by advanced genetic testing, advances in the research of genetic causes underlying male and female infertility, utilisation of massively parallel sequencing in preimplantation genetic testing and non-invasive prenatal screening, mitochondrial replacement in human oocytes, and additionally, issues related to cross-generational epigenetic inheritance following IVF and germline genome editing. The resulting paper represents a consensus of both professional societies involved.

Evidence of a genetic link between endometriosis and ovarian cancer.

PubMed

Lee, Alice W; Templeman, Claire; Stram, Douglas A; Beesley, Jonathan; Tyrer, Jonathan; Berchuck, Andrew; Pharoah, Paul P; Chenevix-Trench, Georgia; Pearce, Celeste Leigh

2016-01-01

To evaluate whether endometriosis-associated genetic variation affects risk of ovarian cancer. Pooled genetic analysis. University hospital. Genetic data from 46,176 participants (15,361 ovarian cancer cases and 30,815 controls) from 41 ovarian cancer studies. None. Endometriosis-associated genetic variation and ovarian cancer. There was significant evidence of an association between endometriosis-related genetic variation and ovarian cancer risk, especially for the high-grade serous and clear cell histotypes. Overall we observed 15 significant burden statistics, which was three times more than expected. By focusing on candidate regions from a phenotype associated with ovarian cancer, we have shown a clear genetic link between endometriosis and ovarian cancer that warrants further follow-up. The functional significance of the identified regions and SNPs is presently uncertain, though future fine mapping and histotype-specific functional analyses may shed light on the etiologies of both gynecologic conditions. Copyright © 2016. Published by Elsevier Inc.

Endemic insular and coastal Tunisian date palm genetic diversity.

PubMed

Zehdi-Azouzi, Salwa; Cherif, Emira; Guenni, Karim; Abdelkrim, Ahmed Ben; Bermil, Aymen; Rhouma, Soumaya; Salah, Mohamed Ben; Santoni, Sylvain; Pintaud, Jean Christophe; Aberlenc-Bertossi, Frédérique; Hannachi, Amel Salhi

2016-04-01

The breeding of crop species relies on the valorisation of ancestral or wild varieties to enrich the cultivated germplasm. The Tunisian date palm genetic patrimony is being threatened by diversity loss and global climate change. We have conducted a genetic study to evaluate the potential of spontaneous coastal resources to improve the currently exploited Tunisian date palm genetic pool. Eighteen microsatellite loci of Phoenix dactylifera L. were used to compare the genetic diversity of coastal accessions from Kerkennah, Djerba, Gabès and continental date palm accessions from Tozeur. A collection of 105 date palms from the four regions was analysed. This study has provided us with an extensive understanding of the local genetic diversity and its distribution. The coastal date palm genotypes exhibit a high and specific genetic diversity. These genotypes are certainly an untapped reservoir of agronomically important genes to improve cultivated germplasm in continental date palm.

Automated discovery of structural features of the optic nerve head on the basis of image and genetic data

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2014-03-01

Evaluation of optic nerve head (ONH) structure is a commonly used clinical technique for both diagnosis and monitoring of glaucoma. Glaucoma is associated with characteristic changes in the structure of the ONH. We present a method for computationally identifying ONH structural features using both imaging and genetic data from a large cohort of participants at risk for primary open angle glaucoma (POAG). Using 1054 participants from the Ocular Hypertension Treatment Study, ONH structure was measured by application of a stereo correspondence algorithm to stereo fundus images. In addition, the genotypes of several known POAG genetic risk factors were considered for each participant. ONH structural features were discovered using both a principal component analysis approach to identify the major modes of variance within structural measurements and a linear discriminant analysis approach to capture the relationship between genetic risk factors and ONH structure. The identified ONH structural features were evaluated based on the strength of their associations with genotype and development of POAG by the end of the OHTS study. ONH structural features with strong associations with genotype were identified for each of the genetic loci considered. Several identified ONH structural features were significantly associated (p < 0.05) with the development of POAG after Bonferroni correction. Further, incorporation of genetic risk status was found to substantially increase performance of early POAG prediction. These results suggest incorporating both imaging and genetic data into ONH structural modeling significantly improves the ability to explain POAG-related changes to ONH structure.

SSR-based genetic diversity and structure of garlic accessions from Brazil.

PubMed

da Cunha, Camila Pinto; Resende, Francisco Vilela; Zucchi, Maria Imaculada; Pinheiro, José Baldin

2014-10-01

Garlic is a spice and a medicinal plant; hence, there is an increasing interest in 'developing' new varieties with different culinary properties or with high content of nutraceutical compounds. Phenotypic traits and dominant molecular markers are predominantly used to evaluate the genetic diversity of garlic clones. However, 24 SSR markers (codominant) specific for garlic are available in the literature, fostering germplasm researches. In this study, we genotyped 130 garlic accessions from Brazil and abroad using 17 polymorphic SSR markers to assess the genetic diversity and structure. This is the first attempt to evaluate a large set of accessions maintained by Brazilian institutions. A high level of redundancy was detected in the collection (50 % of the accessions represented eight haplotypes). However, non-redundant accessions presented high genetic diversity. We detected on average five alleles per locus, Shannon index of 1.2, HO of 0.5, and HE of 0.6. A core collection was set with 17 accessions, covering 100 % of the alleles with minimum redundancy. Overall FST and D values indicate a strong genetic structure within accessions. Two major groups identified by both model-based (Bayesian approach) and hierarchical clustering (UPGMA dendrogram) techniques were coherent with the classification of accessions according to maturity time (growth cycle): early-late and midseason accessions. Assessing genetic diversity and structure of garlic collections is the first step towards an efficient management and conservation of accessions in genebanks, as well as to advance future genetic studies and improvement of garlic worldwide.

Evaluating Changes in Omega-3 Fatty Acid Intake after Receiving Personal FADS1 Genetic Information: A Randomized Nutrigenetic Intervention.

PubMed

Roke, Kaitlin; Walton, Kathryn; Klingel, Shannon L; Harnett, Amber; Subedi, Sanjeena; Haines, Jess; Mutch, David M

2017-03-06

Nutrigenetics research is anticipated to lay the foundation for personalized dietary recommendations; however, it remains unclear if providing individuals with their personal genetic information changes dietary behaviors. Our objective was to evaluate if providing information for a common variant in the fatty acid desaturase 1 ( FADS1 ) gene changed omega-3 fatty acid (FA) intake and blood levels in young female adults (18-25 years). Participants were randomized into Genetic (intervention) and Non-Genetic (control) groups, with measurements taken at Baseline and Final (12 weeks). Dietary intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) was assessed using an omega-3 food frequency questionnaire. Red blood cell (RBC) FA content was quantified by gas chromatography. Implications of participation in a nutrigenetics study and awareness of omega-3 FAs were assessed with online questionnaires. Upon completion of the study, EPA and DHA intake increased significantly ( p = 1.0 × 10 -4 ) in all participants. This change was reflected by small increases in RBC %EPA. Participants in the Genetic group showed increased awareness of omega-3 terminology by the end of the study, reported that the dietary recommendations were more useful, and rated cost as a barrier to omega-3 consumption less often than those in the Non-Genetic group. Providing participants FADS1 genetic information did not appear to influence omega-3 intake during the 12 weeks, but did change perceptions and behaviors related to omega-3 FAs in this timeframe.

Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data

PubMed Central

Lopes, Marcos S.; Bastiaansen, John W. M.; Janss, Luc; Knol, Egbert F.; Bovenhuis, Henk

2015-01-01

Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases. PMID:26438289

Evaluating Changes in Omega-3 Fatty Acid Intake after Receiving Personal FADS1 Genetic Information: A Randomized Nutrigenetic Intervention

PubMed Central

Roke, Kaitlin; Walton, Kathryn; Klingel, Shannon L.; Harnett, Amber; Subedi, Sanjeena; Haines, Jess; Mutch, David M.

2017-01-01

Nutrigenetics research is anticipated to lay the foundation for personalized dietary recommendations; however, it remains unclear if providing individuals with their personal genetic information changes dietary behaviors. Our objective was to evaluate if providing information for a common variant in the fatty acid desaturase 1 (FADS1) gene changed omega-3 fatty acid (FA) intake and blood levels in young female adults (18–25 years). Participants were randomized into Genetic (intervention) and Non-Genetic (control) groups, with measurements taken at Baseline and Final (12 weeks). Dietary intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) was assessed using an omega-3 food frequency questionnaire. Red blood cell (RBC) FA content was quantified by gas chromatography. Implications of participation in a nutrigenetics study and awareness of omega-3 FAs were assessed with online questionnaires. Upon completion of the study, EPA and DHA intake increased significantly (p = 1.0 × 10−4) in all participants. This change was reflected by small increases in RBC %EPA. Participants in the Genetic group showed increased awareness of omega-3 terminology by the end of the study, reported that the dietary recommendations were more useful, and rated cost as a barrier to omega-3 consumption less often than those in the Non-Genetic group. Providing participants FADS1 genetic information did not appear to influence omega-3 intake during the 12 weeks, but did change perceptions and behaviors related to omega-3 FAs in this timeframe. PMID:28272299

Promoting Utilization of Saccharum spp. Genetic Resources through Genetic Diversity Analysis and Core Collection Construction

PubMed Central

Pathak, Bhuvan; Ayala-Silva, Tomas; Yang, Xiping; Todd, James; Glynn, Neil C.; Kuhn, David N.; Glaz, Barry; Gilbert, Robert A.; Comstock, Jack C.; Wang, Jianping

2014-01-01

Sugarcane (Saccharum spp.) and other members of Saccharum spp. are attractive biofuel feedstocks. One of the two World Collections of Sugarcane and Related Grasses (WCSRG) is in Miami, FL. This WCSRG has 1002 accessions, presumably with valuable alleles for biomass, other important agronomic traits, and stress resistance. However, the WCSRG has not been fully exploited by breeders due to its lack of characterization and unmanageable population. In order to optimize the use of this genetic resource, we aim to 1) genotypically evaluate all the 1002 accessions to understand its genetic diversity and population structure and 2) form a core collection, which captures most of the genetic diversity in the WCSRG. We screened 36 microsatellite markers on 1002 genotypes and recorded 209 alleles. Genetic diversity of the WCSRG ranged from 0 to 0.5 with an average of 0.304. The population structure analysis and principal coordinate analysis revealed three clusters with all S. spontaneum in one cluster, S. officinarum and S. hybrids in the second cluster and mostly non-Saccharum spp. in the third cluster. A core collection of 300 accessions was identified which captured the maximum genetic diversity of the entire WCSRG which can be further exploited for sugarcane and energy cane breeding. Sugarcane and energy cane breeders can effectively utilize this core collection for cultivar improvement. Further, the core collection can provide resources for forming an association panel to evaluate the traits of agronomic and commercial importance. PMID:25333358

Relationships Between Oases and Germplasm Collections

USDA-ARS?s Scientific Manuscript database

Traditional date palm oases have served as conservators of date palm genetic resources. There have been only a few studies on the population structure of these oases or evaluations of non-fruit-related characteristics. A system is needed in which regional germplasm repositories for date palm genetic...

COMPARATIVE EVALUATION OF RISK FACTORS FOR CARDIOVASCULAR DISEASE (CVD) IN GENETICALLY PREDISPOSED RATS

EPA Science Inventory

Rodent CVD models are increasingly used for understanding individual differences in susceptibility to environmental stressors such as air pollution. We characterized pathologies and a number of known human risk factors of CVD in genetically predisposed, male young adult Spontaneo...

Role of genetic improvement in the Short Rotation Woody Crops Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Layton, P.A.; Wright, L.L.

1986-01-01

A major effort in the Short Rotation Woody Crops Program (SRWCP) is species screening and genetic improvement of selected species. Of the 125 species initially evaluated for SRIC, 20 are being seriously considered with most of emphasis on 16 hardwood species. Range-wide seed collections of 12 species were provenance tested; these include Platanus occidentalis (sycamore), Alnus glutinosa (European black alder), and Robinia pseudoacacia (black locust). Based on the results of these tests, highly productive, site-specific seed sources are being chosen for several geographic regions. Three of these species re currently being bred for increased productivity in SRIC systems. Genetic improvementmore » is viewed as a tool for increasing productivity, having anticipated gains of 40 to 50%. The techniques of somaclonal screening and genetic engineering are being evaluated for their usefulness in the SRIC improvement program. Currently, salt-tolerant Atriplex canescens (four-wing saltbush) and herbicide-resistant Populus spp. are being sought via somaclonal screening. 35 refs., 4 figs., 3 tabs.« less

Methodological issues in genetic association studies of inherited thrombophilia: original report of recent practice.

PubMed

Simundic, Ana-Maria; Nikolac, Nora; Topic, Elizabeta

2009-01-01

The aims of this article are to evaluate the methodological quality of genetic association studies on the inherited thrombophilia published during 2003 to 2005, to identify the most common mistakes made by authors of those studies, and to examine if overall quality of the article correlates with the quality of the journal. Articles were evaluated by 2 independent reviewers using the checklist of 16 items. A total of 58 eligible studies were identified. Average total score was 7.59 +/- 1.96. Total article score did not correlate with the journal impact factor (r = 0.3971; 95% confidence interval [CI], 0.1547-0.5944, P = .002). Total score did not differ across years (P = .624). Finally, it is concluded that methodological quality of genetic association studies is not optimal, and it does not depend on the quality of the journal. Journals should adopt methodological criteria for reporting the genetic association studies, and editors should encourage authors to strictly adhere to those criteria.

Genetic analysis of the Venezuelan Criollo horse.

PubMed

Cothran, E G; Canelon, J L; Luis, C; Conant, E; Juras, R

2011-10-07

Various horse populations in the Americas have an origin in Spain; they are remnants of the first livestock introduced to the continent early in the colonial period (16th and 17th centuries). We evaluated genetic variability within the Venezuelan Criollo horse and its relationship with other horse breeds. We observed high levels of genetic diversity within the Criollo breed. Significant population differentiation was observed between all South American breeds. The Venezuelan Criollo horse showed high levels of genetic diversity, and from a conservation standpoint, there is no immediate danger of losing variation unless there is a large drop in population size.

Palmar dermatoglyphic patterns in twins.

PubMed

Jacques, S M; Salzano, F M; Penña, H F

1977-01-01

The role of genetic factors in the determination of palmar dermatoglyphic patterns was investigated in a series of 49 MZ and 51 DZ twins, using Spearman's rank correlation and analysis of variance. Both methods indicated that the genetic effect in the distribution of patterns is highest in the interdigital III and lowest in the interdigital IV regions, the hypothenar and thenar showing intermediate values. As for interdigital II, no evaluation of genetic effects was possible using the nonparametric test, but the estimates of genetic variance indicate that inherited factors may play a relatively minor role in the pattern distribution of this area.

Contribution of genetics to ecological restoration.

PubMed

Mijangos, Jose Luis; Pacioni, Carlo; Spencer, Peter B S; Craig, Michael D

2015-01-01

Ecological restoration of degraded ecosystems has emerged as a critical tool in the fight to reverse and ameliorate the current loss of biodiversity and ecosystem services. Approaches derived from different genetic disciplines are extending the theoretical and applied frameworks on which ecological restoration is based. We performed a search of scientific articles and identified 160 articles that employed a genetic approach within a restoration context to shed light on the links between genetics and restoration. These articles were then classified on whether they examined association between genetics and fitness or the application of genetics in demographic studies, and on the way the studies informed restoration practice. Although genetic research in restoration is rapidly growing, we found that studies could make better use of the extensive toolbox developed by applied fields in genetics. Overall, 41% of reviewed studies used genetic information to evaluate or monitor restoration, and 59% provided genetic information to guide prerestoration decision-making processes. Reviewed studies suggest that restoration practitioners often overlook the importance of including genetic aspects within their restoration goals. Even though there is a genetic basis influencing the provision of ecosystem services, few studies explored this relationship. We provide a view of research gaps, future directions and challenges in the genetics of restoration. © 2014 John Wiley & Sons Ltd.

Feasibility of pedigree recording and genetic selection in village sheep flocks of smallholder farmers.

PubMed

Gizaw, Solomon; Goshme, Shenkute; Getachew, Tesfaye; Haile, Aynalem; Rischkowsky, Barbara; van Arendonk, Johan; Valle-Zárate, Anne; Dessie, Tadelle; Mwai, Ally Okeyo

2014-06-01

Pedigree recording and genetic selection in village flocks of smallholder farmers have been deemed infeasible by researchers and development workers. This is mainly due to the difficulty of sire identification under uncontrolled village breeding practices. A cooperative village sheep-breeding scheme was designed to achieve controlled breeding and implemented for Menz sheep of Ethiopia in 2009. In this paper, we evaluated the reliability of pedigree recording in village flocks by comparing genetic parameters estimated from data sets collected in the cooperative village and in a nucleus flock maintained under controlled breeding. Effectiveness of selection in the cooperative village was evaluated based on trends in breeding values over generations. Heritability estimates for 6-month weight recorded in the village and the nucleus flock were very similar. There was an increasing trend over generations in average estimated breeding values for 6-month weight in the village flocks. These results have a number of implications: the pedigree recorded in the village flocks was reliable; genetic parameters, which have so far been estimated based on nucleus data sets, can be estimated based on village recording; and appreciable genetic improvement could be achieved in village sheep selection programs under low-input smallholder farming systems.

Genetic value of herd life adjusted for milk production.

PubMed

Allaire, F R; Gibson, J P

1992-05-01

Cow herd life adjusted for lactational milk production was investigated as a genetic trait in the breeding objective. Under a simple model, the relative economic weight of milk to adjusted herd life on a per genetic standard deviation basis was equal to CVY/dCVL where CVY and CVL are the genetic coefficients of variation of milk production and adjusted herd life, respectively, and d is the depreciation per year per cow divided by the total fixed costs per year per cow. The relative economic value of milk to adjusted herd life at the prices and parameters for North America was about 3.2. An increase of 100-kg milk was equivalent to 2.2 mo of adjusted herd life. Three to 7% lower economic gain is expected when only improved milk production is sought compared with a breeding objective that included both production and adjusted herd life for relative value changed +/- 20%. A favorable economic gain to cost ratio probably exists for herd life used as a genetic trait to supplement milk in the breeding objective. Cow survival records are inexpensive, and herd life evaluations from such records may not extend the generation interval when such an evaluation is used in bull sire selection.

CAP/ACMG proficiency testing for biochemical genetics laboratories: a summary of performance.

PubMed

Oglesbee, Devin; Cowan, Tina M; Pasquali, Marzia; Wood, Timothy C; Weck, Karen E; Long, Thomas; Palomaki, Glenn E

2018-01-01

PurposeTesting for inborn errors of metabolism is performed by clinical laboratories worldwide, each utilizing laboratory-developed procedures. We sought to summarize performance in the College of American Pathologists' (CAP) proficiency testing (PT) program and identify opportunities for improving laboratory quality. When evaluating PT data, we focused on a subset of laboratories that have participated in at least one survey since 2010.MethodsAn analysis of laboratory performance (2004 to 2014) on the Biochemical Genetics PT Surveys, a program administered by CAP and the American College of Medical Genetics and Genomics. Analytical and interpretive performance was evaluated for four tests: amino acids, organic acids, acylcarnitines, and mucopolysaccharides.ResultsSince 2010, 150 laboratories have participated in at least one of four PT surveys. Analytic sensitivities ranged from 88.2 to 93.4%, while clinical sensitivities ranged from 82.4 to 91.0%. Performance was higher for US participants and for more recent challenges. Performance was lower for challenges with subtle findings or complex analytical patterns.ConclusionUS clinical biochemical genetics laboratory proficiency is satisfactory, with a minority of laboratories accounting for the majority of errors. Our findings underscore the complex nature of clinical biochemical genetics testing and highlight the necessity of continuous quality management.

Genetic Modification of the Relationship between Parental Rejection and Adolescent Alcohol Use.

PubMed

Stogner, John M; Gibson, Chris L

2016-07-01

Parenting practices are associated with adolescents' alcohol consumption, however not all youth respond similarly to challenging family situations and harsh environments. This study examines the relationship between perceived parental rejection and adolescent alcohol use, and specifically evaluates whether youth who possess greater genetic sensitivity to their environment are more susceptible to negative parental relationships. Analyzing data from the National Longitudinal Study of Adolescent Health, we estimated a series of regression models predicting alcohol use during adolescence. A multiplicative interaction term between parental rejection and a genetic index was constructed to evaluate this potential gene-environment interaction. Results from logistic regression analyses show a statistically significant gene-environment interaction predicting alcohol use. The relationship between parental rejection and alcohol use was moderated by the genetic index, indicating that adolescents possessing more 'risk alleles' for five candidate genes were affected more by stressful parental relationships. Feelings of parental rejection appear to influence the alcohol use decisions of youth, but they do not do so equally for all. Higher scores on the constructed genetic sensitivity measure are related to increased susceptibility to negative parental relationships. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Transition of genomic evaluation from a research project to a production system

USDA-ARS?s Scientific Manuscript database

Genomic data began to be included in official USDA genetic evaluations of dairy cattle in January 2009. Numerous changes to the evaluation system were made to enable efficient management of genomic information, to incorporate it in official evaluations, and to distribute evaluations. Artificial-inse...

Genetic testing in heritable cardiac arrhythmia syndromes: differentiating pathogenic mutations from background genetic noise.

PubMed

Giudicessi, John R; Ackerman, Michael J

2013-01-01

In this review, we summarize the basic principles governing rare variant interpretation in the heritable cardiac arrhythmia syndromes, focusing on recent advances that have led to disease-specific approaches to the interpretation of positive genetic testing results. Elucidation of the genetic substrates underlying heritable cardiac arrhythmia syndromes has unearthed new arrhythmogenic mechanisms and given rise to a number of clinically meaningful genotype-phenotype correlations. As such, genetic testing for these disorders now carries important diagnostic, prognostic, and therapeutic implications. Recent large-scale systematic studies designed to explore the background genetic 'noise' rate associated with these genetic tests have provided important insights and enhanced how positive genetic testing results are interpreted for these potentially lethal, yet highly treatable, cardiovascular disorders. Clinically available genetic tests for heritable cardiac arrhythmia syndromes allow the identification of potentially at-risk family members and contribute to the risk-stratification and selection of therapeutic interventions in affected individuals. The systematic evaluation of the 'signal-to-noise' ratio associated with these genetic tests has proven critical and essential to assessing the probability that a given variant represents a rare pathogenic mutation or an equally rare, yet innocuous, genetic bystander.

Patterns of genetic diversity in the polymorphic ground snake (Sonora semiannulata).

PubMed

Cox, Christian L; Chippindale, Paul T

2014-08-01

We evaluated the genetic diversity of a snake species with color polymorphism to understand the evolutionary processes that drive genetic structure across a large geographic region. Specifically, we analyzed genetic structure of the highly polymorphic ground snake, Sonora semiannulata, (1) among populations, (2) among color morphs (3) at regional and local spatial scales, using an amplified fragment length polymorphism dataset and multiple population genetic analyses, including FST-based and clustering analytical techniques. Based upon these methods, we found that there was moderate to low genetic structure among populations. However, this diversity was not associated with geographic locality at either spatial scale. Similarly, we found no evidence for genetic divergence among color morphs at either spatial scale. These results suggest that despite dramatic color polymorphism, this phenotypic diversity is not a major driver of genetic diversity within or among populations of ground snakes. We suggest that there are two mechanisms that could explain existing genetic diversity in ground snakes: recent range expansion from a genetically diverse founder population and current or recent gene flow among populations. Our findings have further implications for the types of color polymorphism that may generate genetic diversity in snakes.

Genetic effects on gene expression across human tissues

PubMed Central

2017-01-01

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease. PMID:29022597

Genetic predisposition increases the tic severity, rate of comorbidities, and psychosocial and educational difficulties in children with Tourette syndrome.

PubMed

Eysturoy, Absalon Niclas; Skov, Liselotte; Debes, Nanette Mol

2015-03-01

This study aimed to examine whether there are differences in tic severity, comorbidities, and psychosocial and educational consequences in children with Tourette syndrome and genetic predisposition to Tourette syndrome compared with children with Tourette syndrome without genetic predisposition to Tourette syndrome. A total of 314 children diagnosed with Tourette syndrome participated in this study. Validated diagnostic tools were used to assess tic severity, comorbidities, and cognitive performance. A structured interview was used to evaluate psychosocial and educational consequences related to Tourette syndrome. The children with Tourette syndrome and genetic predisposition present with statistically significant differences in terms of severity of tics, comorbidities, and a range of psychosocial and educational factors compared with the children with Tourette syndrome without genetic predisposition. Professionals need to be aware of genetic predisposition to Tourette syndrome, as children with Tourette syndrome and genetic predisposition have more severe symptoms than those children with Tourette syndrome who are without genetic predisposition. © The Author(s) 2014.

Genetic effects on gene expression across human tissues.

PubMed

Battle, Alexis; Brown, Christopher D; Engelhardt, Barbara E; Montgomery, Stephen B

2017-10-11

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

Interactive genetic counseling role-play: a novel educational strategy for family physicians.

PubMed

Blaine, Sean M; Carroll, June C; Rideout, Andrea L; Glendon, Gord; Meschino, Wendy; Shuman, Cheryl; Telner, Deanna; Van Iderstine, Natasha; Permaul, Joanne

2008-04-01

Family physicians (FPs) are increasingly involved in delivering genetic services. Familiarization with aspects of genetic counseling may enable FPs to help patients make informed choices. Exploration of interactive role-play as a means to raise FPs' awareness of the process and content of genetic counseling. FPs attending two large Canadian family medicine conferences in 2005 were eligible -- 93 participated. FPs discussed a case during a one-on-one session with a genetic counselor. Evaluation involved pre and post intervention questionnaires FPs' baseline genetic knowledge was self-rated as uniformly poor. Baseline confidence was highest in eliciting family history and providing psychosocial support and lowest in discussing risks/benefits of genetic testing and counseling process. Post-intervention, 80% of FPs had better appreciation of family history and 97% indicated this was an effective learning experience. Role-play with FPs is effective in raising awareness of the process and content of genetic counseling and may be applied to other health disciplines.

A comprehensive global genotype-phenotype database for rare diseases.

PubMed

Trujillano, Daniel; Oprea, Gabriela-Elena; Schmitz, Yvonne; Bertoli-Avella, Aida M; Abou Jamra, Rami; Rolfs, Arndt

2017-01-01

The ability to discover genetic variants in a patient runs far ahead of the ability to interpret them. Databases with accurate descriptions of the causal relationship between the variants and the phenotype are valuable since these are critical tools in clinical genetic diagnostics. Here, we introduce a comprehensive and global genotype-phenotype database focusing on rare diseases. This database (CentoMD ® ) is a browser-based tool that enables access to a comprehensive, independently curated system utilizing stringent high-quality criteria and a quickly growing repository of genetic and human phenotype ontology (HPO)-based clinical information. Its main goals are to aid the evaluation of genetic variants, to enhance the validity of the genetic analytical workflow, to increase the quality of genetic diagnoses, and to improve evaluation of treatment options for patients with hereditary diseases. The database software correlates clinical information from consented patients and probands of different geographical backgrounds with a large dataset of genetic variants and, when available, biomarker information. An automated follow-up tool is incorporated that informs all users whenever a variant classification has changed. These unique features fully embedded in a CLIA/CAP-accredited quality management system allow appropriate data quality and enhanced patient safety. More than 100,000 genetically screened individuals are documented in the database, resulting in more than 470 million variant detections. Approximately, 57% of the clinically relevant and uncertain variants in the database are novel. Notably, 3% of the genetic variants identified and previously reported in the literature as being associated with a particular rare disease were reclassified, based on internal evidence, as clinically irrelevant. The database offers a comprehensive summary of the clinical validity and causality of detected gene variants with their associated phenotypes, and is a valuable tool for identifying new disease genes through the correlation of novel genetic variants with specific, well-defined phenotypes.

Statistical tests for detecting associations with groups of genetic variants: generalization, evaluation, and implementation

PubMed Central

Ferguson, John; Wheeler, William; Fu, YiPing; Prokunina-Olsson, Ludmila; Zhao, Hongyu; Sampson, Joshua

2013-01-01

With recent advances in sequencing, genotyping arrays, and imputation, GWAS now aim to identify associations with rare and uncommon genetic variants. Here, we describe and evaluate a class of statistics, generalized score statistics (GSS), that can test for an association between a group of genetic variants and a phenotype. GSS are a simple weighted sum of single-variant statistics and their cross-products. We show that the majority of statistics currently used to detect associations with rare variants are equivalent to choosing a specific set of weights within this framework. We then evaluate the power of various weighting schemes as a function of variant characteristics, such as MAF, the proportion associated with the phenotype, and the direction of effect. Ultimately, we find that two classical tests are robust and powerful, but details are provided as to when other GSS may perform favorably. The software package CRaVe is available at our website (http://dceg.cancer.gov/bb/tools/crave). PMID:23092956

Genetic progress in multistage dairy cattle breeding schemes using genetic markers.

PubMed

Schrooten, C; Bovenhuis, H; van Arendonk, J A M; Bijma, P

2005-04-01

The aim of this paper was to explore general characteristics of multistage breeding schemes and to evaluate multistage dairy cattle breeding schemes that use information on quantitative trait loci (QTL). Evaluation was either for additional genetic response or for reduction in number of progeny-tested bulls while maintaining the same response. The reduction in response in multistage breeding schemes relative to comparable single-stage breeding schemes (i.e., with the same overall selection intensity and the same amount of information in the final stage of selection) depended on the overall selection intensity, the selection intensity in the various stages of the breeding scheme, and the ratio of the accuracies of selection in the various stages of the breeding scheme. When overall selection intensity was constant, reduction in response increased with increasing selection intensity in the first stage. The decrease in response was highest in schemes with lower overall selection intensity. Reduction in response was limited in schemes with low to average emphasis on first-stage selection, especially if the accuracy of selection in the first stage was relatively high compared with the accuracy in the final stage. Closed nucleus breeding schemes in dairy cattle that use information on QTL were evaluated by deterministic simulation. In the base scheme, the selection index consisted of pedigree information and own performance (dams), or pedigree information and performance of 100 daughters (sires). In alternative breeding schemes, information on a QTL was accounted for by simulating an additional index trait. The fraction of the variance explained by the QTL determined the correlation between the additional index trait and the breeding goal trait. Response in progeny test schemes relative to a base breeding scheme without QTL information ranged from +4.5% (QTL explaining 5% of the additive genetic variance) to +21.2% (QTL explaining 50% of the additive genetic variance). A QTL explaining 5% of the additive genetic variance allowed a 35% reduction in the number of progeny tested bulls, while maintaining genetic response at the level of the base scheme. Genetic progress was up to 31.3% higher for schemes with increased embryo production and selection of embryos based on QTL information. The challenge for breeding organizations is to find the optimum breeding program with regard to additional genetic progress and additional (or reduced) cost.

Genetic characterization of three varieties of Astragalus lentiginosus (Fabaceae).

Treesearch

Brian J. Knaus; Rich C. Cronn; Aaron Liston

2005-01-01

Astragalus lentiginosus is a polymorphic species that occurs in geologically young habitats and whose varietal circumscription implies active morphological and genetic differentiation. In this preliminary study, we evaluate the potential of amplified fragment length polymorphism (AFLP) markers to resolve infraspecific taxa in three varieties of...

An Evaluation of the Navy’s Health Promotion Videotapes

DTIC Science & Technology

1990-04-30

1263. Fisher, L., Rowley, P. T., & Lipkin. M. (1981). Genetic counseling for beta- thalassemia trait following health screening in a health maintenence...counseling for x, ta- thalassemia trait in a population unselected for interest: Effects on knowledge and m ,ood. American Journal of Human Genetics

Reasonable Foreseeability and Liability in Relation to Genetically Modified Organisms

ERIC Educational Resources Information Center

Khoury, Lara; Smyth, Stuart

2007-01-01

This article examines problems that may arise when addressing liability resulting from the genetic modification of microbes, animals, and plants. More specifically, it evaluates how uncertainties relating to the outcomes of these biotechnological innovations affect--or may affect--the courts' application of the reasonable foreseeability…

Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent.

PubMed

Guo, Yan; Warren Andersen, Shaneda; Shu, Xiao-Ou; Michailidou, Kyriaki; Bolla, Manjeet K; Wang, Qin; Garcia-Closas, Montserrat; Milne, Roger L; Schmidt, Marjanka K; Chang-Claude, Jenny; Dunning, Allison; Bojesen, Stig E; Ahsan, Habibul; Aittomäki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Bogdanova, Natalia V; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Casey, Graham; Chenevix-Trench, Georgia; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Dumont, Martine; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gammon, Marilie; Giles, Graham G; Guénel, Pascal; Haiman, Christopher A; Hamann, Ute; Hooning, Maartje J; Hopper, John L; Jakubowska, Anna; Jasmine, Farzana; Jenkins, Mark; John, Esther M; Johnson, Nichola; Jones, Michael E; Kabisch, Maria; Kibriya, Muhammad; Knight, Julia A; Koppert, Linetta B; Kosma, Veli-Matti; Kristensen, Vessela; Le Marchand, Loic; Lee, Eunjung; Li, Jingmei; Lindblom, Annika; Luben, Robert; Lubinski, Jan; Malone, Kathi E; Mannermaa, Arto; Margolin, Sara; Marme, Frederik; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Olson, Janet E; Perez, Jose I A; Perkins, Barbara; Peterlongo, Paolo; Phillips, Kelly-Anne; Pylkäs, Katri; Rudolph, Anja; Santella, Regina; Sawyer, Elinor J; Schmutzler, Rita K; Seynaeve, Caroline; Shah, Mitul; Shrubsole, Martha J; Southey, Melissa C; Swerdlow, Anthony J; Toland, Amanda E; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Ursin, Giske; Van Der Luijt, Rob B; Verhoef, Senno; Whittemore, Alice S; Winqvist, Robert; Zhao, Hui; Zhao, Shilin; Hall, Per; Simard, Jacques; Kraft, Peter; Pharoah, Paul; Hunter, David; Easton, Douglas F; Zheng, Wei

2016-08-01

Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases  =  46,325, controls  =  42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]  =  0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10). The associations were similar for both premenopausal (OR   =   0.44, 95% CI:0.31-0.62, p  =  9.91 × 10-8) and postmenopausal breast cancer (OR  =  0.57, 95% CI: 0.46-0.71, p  =  1.88 × 10-8). This association was replicated in the data from the DRIVE consortium (OR  =  0.72, 95% CI: 0.60-0.84, p   =   1.64 × 10-7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p < 0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.

Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent

PubMed Central

Guo, Yan; Warren Andersen, Shaneda; Shu, Xiao-Ou; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Garcia-Closas, Montserrat; Milne, Roger L.; Schmidt, Marjanka K.; Chang-Claude, Jenny; Dunning, Allison; Bojesen, Stig E.; Ahsan, Habibul; Aittomäki, Kristiina; Andrulis, Irene L.; Anton-Culver, Hoda; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Bogdanova, Natalia V.; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Casey, Graham; Chenevix-Trench, Georgia; Couch, Fergus J.; Cross, Simon S.; Czene, Kamila; Dörk, Thilo; Dumont, Martine; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gammon, Marilie; Giles, Graham G.; Guénel, Pascal; Haiman, Christopher A.; Hamann, Ute; Hooning, Maartje J.; Hopper, John L.; Jakubowska, Anna; Jasmine, Farzana; Jenkins, Mark; John, Esther M.; Johnson, Nichola; Jones, Michael E.; Kabisch, Maria; Knight, Julia A.; Koppert, Linetta B.; Kosma, Veli-Matti; Kristensen, Vessela; Le Marchand, Loic; Lee, Eunjung; Li, Jingmei; Lindblom, Annika; Lubinski, Jan; Malone, Kathi E.; Mannermaa, Arto; Margolin, Sara; McLean, Catriona; Meindl, Alfons; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Olson, Janet E.; Perez, Jose I. A.; Perkins, Barbara; Phillips, Kelly-Anne; Pylkäs, Katri; Rudolph, Anja; Santella, Regina; Sawyer, Elinor J.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shrubsole, Martha J.; Southey, Melissa C.; Swerdlow, Anthony J.; Toland, Amanda E.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Ursin, Giske; Van Der Luijt, Rob B.; Verhoef, Senno; Whittemore, Alice S.; Winqvist, Robert; Zhao, Hui; Zhao, Shilin; Hall, Per; Simard, Jacques; Kraft, Peter; Hunter, David; Easton, Douglas F.; Zheng, Wei

2016-01-01

Background Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. Methods We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases  =  46,325, controls  =  42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. Results In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]  =  0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56–0.75, p = 3.32 × 10−10). The associations were similar for both premenopausal (OR   =   0.44, 95% CI:0.31–0.62, p  =  9.91 × 10−8) and postmenopausal breast cancer (OR  =  0.57, 95% CI: 0.46–0.71, p  =  1.88 × 10−8). This association was replicated in the data from the DRIVE consortium (OR  =  0.72, 95% CI: 0.60–0.84, p   =   1.64 × 10−7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p < 0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. Conclusions BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer. PMID:27551723

Genetic analyses of linear profiling data on 3-year-old Swedish Warmblood horses.

PubMed

Viklund, Å; Eriksson, S

2018-02-01

A linear profiling protocol was introduced in 2013 at tests for 3-year-old Swedish Warmblood horses. In this protocol, traits are subjectively described on a nine-point linear scale from one biological extreme to the other. This complements the traditional scoring where horses are evaluated in relation to the breeding objective. This study aimed to investigate the suitability of the linear information for genetic evaluation. Data on 22 conformation traits, 17 movement traits, 14 jumping traits and one temperament trait from 3,410 horses tested between 2013 and 2016 were analysed using an animal model. For conformation traits, the heritabilities ranged from 0.10 for description of hock joint from behind to 0.52 for shape of the neck. For movement traits, the highest heritability (0.54) was estimated for elasticity in trot and the lowest (0.08) for energy in walk. The heritabilities for jumping traits ranged from 0.05 for the ability to focus on the assignment to 0.57 for scope. Genetic correlations between linear traits and corresponding traditionally scored traits were strong (-0.37 to in many cases <-0.9). The results show that the linear information is suitable for genetic evaluation and can be a useful tool for breeders. © 2018 Blackwell Verlag GmbH.

Familial Hypercholesterolaemia in the Era of Genetic Testing.

PubMed

Hughes, D P; Viljoen, A; Wierzbicki, A S

2016-05-01

Familial hypercholesterolaemia (FH) is a relatively common autosomal dominant genetic condition leading to premature ischaemic vascular disease and mortality if left untreated. Currently, a universal consensus on the diagnostic criteria of FH does not exist but the diagnosis of FH largely relies on the evaluation of low density lipoprotein-cholesterol (LDL-C) levels, a careful documentation of family history, and the identification of clinical features. Diagnosis based purely on lipid levels remains common but there are several limitations to this method of diagnosis both practically and in the proportion of false-negatives and false-positives detected, resulting in substantial under-diagnosis of FH. In some countries, diagnostic algorithms are supplemented with genetic testing of the index case as well as genetic and lipid testing of relatives of the index case. Such "cascade" screening of families following identification of index cases appears to not only improve the rate of diagnosis but is also cost-effective. Currently, we observe a great variation in the excess mortality among patients with FH, which likely reflects a combination of additional genetic and environmental effects on risk overlaid on the risk associated with FH. Current accepted drug therapies for FH include statins and PSCK9 inhibitors. Further work is required to evaluate the cardiovascular disease risk in patients with genetically diagnosed FH and to determine whether a risk-based approach to the treatment of FH is appropriate.

The use of genetically modified Saccharomyces cerevisiae strains in the wine industry.

PubMed

Schuller, Dorit; Casal, Margarida

2005-08-01

In recent decades, science and food technology have contributed at an accelerated rate to the introduction of new products to satisfy nutritional, socio-economic and quality requirements. With the emergence of modern molecular genetics, the industrial importance of Saccharomyces cerevisiae, is continuously extended. The demand for suitable genetically modified (GM) S. cerevisiae strains for the biofuel, bakery and beverage industries or for the production of biotechnological products (e.g. enzymes, pharmaceutical products) will continuously grow in the future. Numerous specialised S. cerevisiae wine strains were obtained in recent years, possessing a wide range of optimised or novel oenological properties, capable of satisfying the demanding nature of modern winemaking practise. The unlocking of transcriptome, proteome and metabolome complexities will contribute decisively to the knowledge about the genetic make-up of commercial yeast strains and will influence wine strain improvement via genetic engineering. The most relevant advances regarding the importance and implications of the use of GM yeast strains in the wine industry are discussed in this mini-review. In this work, various aspects are considered including the strategies used for the construction of strains with respect to current legislation requirements, the environmental risk evaluations concerning the deliberate release of genetically modified yeast strains, the methods for detection of recombinant DNA and protein that are currently under evaluation, and the reasons behind the critical public perception towards the application of such strains.

Genetic diversity among Puccinia melanocephala isolates from Brazil assessed using simple sequence repeat markers.

PubMed

Peixoto-Junior, R F; Creste, S; Landell, M G A; Nunes, D S; Sanguino, A; Campos, M F; Vencovsky, R; Tambarussi, E V; Figueira, A

2014-09-26

Brown rust (causal agent Puccinia melanocephala) is an important sugarcane disease that is responsible for large losses in yield worldwide. Despite its importance, little is known regarding the genetic diversity of this pathogen in the main Brazilian sugarcane cultivation areas. In this study, we characterized the genetic diversity of 34 P. melanocephala isolates from 4 Brazilian states using loci identified from an enriched simple sequence repeat (SSR) library. The aggressiveness of 3 isolates from major sugarcane cultivation areas was evaluated by inoculating an intermediately resistant and a susceptible cultivar. From the enriched library, 16 SSR-specific primers were developed, which produced scorable alleles. Of these, 4 loci were polymorphic and 12 were monomorphic for all isolates evaluated. The molecular characterization of the 34 isolates of P. melanocephala conducted using 16 SSR loci revealed the existence of low genetic variability among the isolates. The average estimated genetic distance was 0.12. Phenetic analysis based on Nei's genetic distance clustered the isolates into 2 major groups. Groups I and II included 18 and 14 isolates, respectively, and both groups contained isolates from all 4 geographic regions studied. Two isolates did not cluster with these groups. It was not possible to obtain clusters according to location or state of origin. Analysis of disease severity data revealed that the isolates did not show significant differences in aggressiveness between regions.

How Oxytocin Receptor (OXTR) Single Nucleotide Polymorphisms Act on Prosociality: The Mediation Role of Moral Evaluation.

PubMed

Shang, Siyuan; Wu, Nan; Su, Yanjie

2017-01-01

Prosociality is related to numerous positive outcomes, and mechanisms underlying individual differences in prosociality have been widely discussed. Recently, research has found converging evidence on the influence of the oxytocin receptor ( OXTR ) gene on prosociality. Meanwhile, moral reasoning, a key precursor for social behavior, has also been associated with variability in OXTR gene, thus the relationship between OXTR and prosociality is assumed to be mediated by moral evaluation. The current study examines the relationship in question, and includes gender as a potential moderator. Self-reported prosociality on Prosocial Tendencies Measure and evaluation on the moral acceptability of behaviors in stories from 790 Chinese adolescents (32.4% boys) were analyzed for the influence of their OXTR single nucleotide polymorphisms (SNPs). Results showed that SNP at site rs2254298 was indirectly associated with prosocial behaviors via moral evaluation of behaviors, and this effect was moderated by gender. Our findings suggest an indirect association between genetic variations in OXTR and prosociality through moral evaluation, indicating the potential pathway from genetic variability to prosociality through level of moral development. We also provide some evidence that the role of oxytocin system may to some extent depend on gender. These findings may promote our understanding of the genetic and biological roots of prosociality and morality.

Improved performance of epidemiologic and genetic risk models for rheumatoid arthritis serologic phenotypes using family history.

PubMed

Sparks, Jeffrey A; Chen, Chia-Yen; Jiang, Xia; Askling, Johan; Hiraki, Linda T; Malspeis, Susan; Klareskog, Lars; Alfredsson, Lars; Costenbader, Karen H; Karlson, Elizabeth W

2015-08-01

To develop and validate rheumatoid arthritis (RA) risk models based on family history, epidemiologic factors and known genetic risk factors. We developed and validated models for RA based on known RA risk factors, among women in two cohorts: the Nurses' Health Study (NHS, 381 RA cases and 410 controls) and the Epidemiological Investigation of RA (EIRA, 1244 RA cases and 971 controls). Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in logistic regression models for the study population and for those with positive family history. The joint effect of family history with genetics, smoking and body mass index (BMI) was evaluated using logistic regression models to estimate ORs for RA. The complete model including family history, epidemiologic risk factors and genetics demonstrated AUCs of 0.74 for seropositive RA in NHS and 0.77 for anti-citrullinated protein antibody (ACPA)-positive RA in EIRA. Among women with positive family history, discrimination was excellent for complete models for seropositive RA in NHS (AUC 0.82) and ACPA-positive RA in EIRA (AUC 0.83). Positive family history, high genetic susceptibility, smoking and increased BMI had an OR of 21.73 for ACPA-positive RA. We developed models for seropositive and seronegative RA phenotypes based on family history, epidemiological and genetic factors. Among those with positive family history, models using epidemiologic and genetic factors were highly discriminatory for seropositive and seronegative RA. Assessing epidemiological and genetic factors among those with positive family history may identify individuals suitable for RA prevention strategies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Reduced Genetic Diversity and Increased Structure in American Mink on the Swedish Coast following Invasive Species Control.

PubMed

Zalewski, Andrzej; Zalewska, Hanna; Lunneryd, Sven-Gunnar; André, Carl; Mikusiński, Grzegorz

2016-01-01

Eradication and population reductions are often used to mitigate the negative impacts of non-native invasive species on native biodiversity. However, monitoring the effectiveness of non-native species control programmes is necessary to evaluate the efficacy of these measures. Genetic monitoring could provide valuable insights into temporal changes in demographic, ecological, and evolutionary processes in invasive populations being subject to control programmes. Such programmes should cause a decrease in effective population size and/or in genetic diversity of the targeted non-native species and an increase in population genetic structuring over time. We used microsatellite DNA data from American mink (Neovison vison) to determine whether the removal of this predator on the Koster Islands archipelago and the nearby Swedish mainland affected genetic variation over six consecutive years of mink culling by trappers as part of a population control programme. We found that on Koster Islands allelic richness decreased (from on average 4.53 to 3.55), genetic structuring increased, and effective population size did not change. In contrast, the mink population from the Swedish coast showed no changes in genetic diversity or structure, suggesting the stability of this population over 6 years of culling. Effective population size did not change over time but was higher on the coast than on the islands across all years. Migration rates from the islands to the coast were almost two times higher than from the coast to the islands. Most migrants leaving the coast were localised on the southern edge of the archipelago, as expected from the direction of the sea current between the two sites. Genetic monitoring provided valuable information on temporal changes in the population of American mink suggesting that this approach can be used to evaluate and improve control programmes of invasive vertebrates.

Genetic variability within and among populations of an invasive, exotic orchid

PubMed Central

Ueno, Sueme; Rodrigues, Jucelene Fernandes; Alves-Pereira, Alessandro; Pansarin, Emerson Ricardo; Veasey, Elizabeth Ann

2015-01-01

Despite the fact that invasive species are of great evolutionary interest because of their success in colonizing and spreading into new areas, the factors underlying this success often remain obscure. In this sense, studies on population genetics and phylogenetic relationships of invasive species could offer insights into mechanisms of invasions. Originally from Africa, the terrestrial orchid Oeceoclades maculata, considered an invasive plant, is the only species of the genus throughout the Americas. Considering the lack of information on population genetics of this species, the aim of this study was to evaluate the genetic diversity and structure of Brazilian populations of O. maculata. We used 13 inter-simple sequence repeat primers to assess the genetic diversity of 152 individuals of O. maculata distributed in five sampled sites from three Brazilian states (São Paulo, Mato Grosso and Paraná). Low diversity was found within samples, with estimates of the Shannon index (H) ranging from 0.0094 to 0.1054 and estimates of Nei's gene diversity (He) ranging from 0.0054 to 0.0668. However, when evaluated together, the sampling locations showed substantially higher diversity estimates (H = 0.3869, He = 0.2556), and most of the genetic diversity was found among populations (ΦST = 0.933). Both clustering and principal coordinate analysis indicate the existence of five distinct groups, corresponding to the sampled localities, and which were also recovered in the Bayesian analysis. A substructure was observed in one of the localities, suggesting a lack of gene flow even between very small distances. The patterns of genetic structure found in this study may be understood considering the interaction of several probable reproductive strategies with its history of colonization involving possible genetic drift, selective pressures and multiple introductions. PMID:26162896

Evaluating the role of Pleistocene refugia, rivers and environmental variation in the diversification of central African duikers (genera Cephalophus and Philantomba).

PubMed

Ntie, Stephan; Davis, Anne R; Hils, Katrin; Mickala, Patrick; Thomassen, Henri A; Morgan, Katy; Vanthomme, Hadrien; Gonder, Mary K; Anthony, Nicola M

2017-09-06

This study aims to assess the role that Pleistocene refugia, rivers and local habitat conditions may have played in the evolutionary diversification of three central African duiker species (Cephalophus dorsalis, C. callipygus and Philantomba monticola). Genetic data from geo-referenced feces were collected from a wide range of sites across Central Africa. Historical patterns of population genetic structure were assessed using a ~ 650 bp fragment of the mitochondrial control region and contemporary patterns of genetic differentiation were evaluated using 12 polymorphic microsatellite loci. Mitochondrial analyses revealed that populations of C. callipygus and P. monticola in the Gulf of Guinea refugium are distinct from other populations in west central Africa. All three species exhibit signatures of past population expansion across much of the study area consistent with a history of postglacial expansion. There was no strong evidence for a riverine barrier effect in any of the three species, suggesting that duikers can readily cross major rivers. Generalized dissimilarity models (GDM) showed that environmental variation explains most of the nuclear genetic differentiation in both C. callipygus and P. monticola. The forest-savanna transition across central Cameroon and the Plateaux Batéké region in southeastern Gabon show the highest environmentally-associated turnover in genetic variability. A pattern of genetic differentiation was also evident between the coast and forest interior that may reflect differences in precipitation and/or vegetation. Findings from this study highlight the historical impact of Pleistocene fragmentation and current influence of environmental variation on genetic structure in duikers. Conservation efforts should therefore target areas that harbor as much environmentally-associated genetic variation as possible in order to maximize species' capacity to adapt to environmental change.