Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Multiple-trait genomic evaluation for milk yield and milk quality traits using genomic and phenotypic data in buffalo in Brazil

The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.

Marker-trait association and epistasis for brown rust resistance in sugarcane

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quantitative trait loci with sex-specific effects for internal organs weights and hematocrit value in a broiler-layer cross

Rapid growth in broilers is associated with susceptibility to metabolic disorders such as pulmonary hypertension syndrome (ascites) and sudden death. This study describes a genome search for QTL associated with relative weight of cardio respiratory and metabolically important organs (heart, lungs, liver and gizzard), and hematocrit value in a Brazilian broiler-layer cross. QTL with similar or different effects across sexes were investigated. At 42 days of age after fasted for 6 h, the F2 chickens were weighed and slaughtered. Weights and percentages of the weight relative to BW42 of gizzard, heart, lungs, liver and hematocrit were used in the QTL search. Parental, F1 and F2 individuals were genotyped with 128 genetic markers (127 microsatellites and 1 SNP) covering 22 linkage groups. QTL mapping analyses were carried out using mixed models. A total of 11 genome-wide significant QTL and five suggestive linkages were mapped. Thus, genome-wide significant QTL with similar effects across sexes were mapped to GGA2, 4 and 14 for heart weight, and to GGA2, 8 and 12 for gizzard %. Additionally, five genome-wide significant QTL with different effects across sexes were mapped to GGA 8, 19 and 26 for heart weight; GGA26 for heart % and GGA3 for hematocrit value. Five QTL were detected in chromosomal regions where QTL for similar traits were previously mapped in other F2 chicken populations. Seven novel genome-wide significant QTL are reported here, and 21 positional candidate genes in QTL regions were identified.

Selection for Increased Starvation Resistance Using Drosophila melanogaster: Investigating Physiological and Life History Trait Responses to Starvation and Dietary Supplementation in the Context of an Obese Phenotype

Artificial selection for starvation resistance provided insight into the relationships between evolved physiological and life history trait responses following exposure to biologically induced stress. Investigations of alterations to body composition, metabolic rate, movement, and life history traits including development time, female egg production, and longevity in response to brief periods of starvation were conducted on genetically based starvation-resistant and control lines of Drosophila melanogaster. Analysis of the starvation-resistant lines indicated increased energy storage with increased triglyceride deposition and conversion of carbohydrates to lipid, as identified by respiratory quotient values. Correlations between reductions in metabolic rates and movement in the starvation-resistant lines, suggested the presence of an evolved physiological response resulting in energy conservation. Investigations of life history traits in the starvation-resistant lines indicated no significant differences in development time or reproduction between the selected and control lines. Measurements of longevity, however, indicated a significant reduction in starvation-resistant D. melanogaster lifespan. These results suggested that elevated lipid concentrations, similar to that observed with obesity, were correlated with premature mortality. Exposure of the starvation-resistant and control lines to diets supplemented with glucose, palmitic acid, and a 2:1 mixture of casein to albumin were used to investigate alterations in body composition, movement, and life history traits. Results obtained from this study indicated that increased sugar in the diet led to increased carbohydrate, glycogen, total sugar, trehalose, and triglyceride concentrations, while increased fat and protein in the diet resulted in increased soluble protein, carbohydrate, glycogen, total sugar, and trehalose concentrations. Examination of life history trait responses indicated reduced fecundity in females exposed to increased glucose concentrations. Increased supplementations of palmitic acid was consistently correlated with an overall reduction in lifespan in both the starvation-resistant and control Drosophila lines, while measurements of movement indicated increased female activity levels in flies exposed to diets supplemented with fat and protein. Analyses of the physiological and life history trait responses to starvation and dietary supplementation on Drosophila melanogaster used in the present study has implications for investigating the mechanisms underlying the development and persistence of human obesity and associated metabolic disorders.

QUANTITATIVE TRAIT LOCI FOR AGRONOMIC AND END-USE QUALITY PERFORMANCE AND THE EFFECT OF SOILBORNE WHEAT MOSAIC VIRUS IN A HARD WINTER WHEAT POPULATION IN NEBRASKA

To better understand agronomic and end-use quality in wheat (Triticum aestivum L.) we developed a population containing 154 F6:8 recombinant inbred lines (RILs) from the cross TAM107-R7/Arlin. The parental lines and RILs were phenotyped at six environments in Nebraska and differed for resistance to Wheat soilborne mosaic virus (WSBMV), morphological, agronomic, and end-use quality traits. Additionally, a 2300 cM genome-wide linkage map was created for quantitative trait loci (QTL) analysis. Based on our results across multiple environments, the best RILs could be used for cultivar improvement. The population and marker data are publicly available for interested researchers for future research. The population was used to determine the effect of WSBMV on agronomic and end-use quality and for the mapping of a resistance locus. Results from two infected environments showed that all but two agronomic traits were significantly affected by the disease. Specifically, the disease reduced grain yield by 30% of susceptible RILs and they flowered 5 d later and were 11 cm shorter. End-use quality traits were not negatively affected but flour protein content was increased in susceptible RILs. The resistance locus SbmTmr1 mapped to 27.1 cM near marker wPt-5870 on chromosome 5DL using ELISA data. Finally, we investigated how WSBMV affected QTL detection in the population. QTLs were mapped at two WSBMV infected environments, four uninfected environments, and in the resistant and susceptible RIL subpopulations in the infected environments. Fifty-two significant (LOD≥3) QTLs were mapped in RILs at uninfected environments. Many of the QTLs were pleiotropic or closely linked at 6 chromosomal regions. Forty-seven QTLs were mapped in RILs at WSBMV infected environments. Comparisons between uninfected and infected environments identified 20 common QTLs and 21 environmentally specific QTLs. Finally, 24 QTLs were determined to be affected by WSBMV by comparing the subpopulations in QTL analyses within the same environment. The comparisons were statistically validated using marker by disease interactions. These results showed that QTLs can be affected by WSBMV and careful interpretation of QTL results is needed where biotic stresses are present. Finally, beneficial QTLs not affected by WSBMV or the environment are candidates for marker-assisted selection.

Genetic Mapping of Quantitative Trait Loci Associated with Bioenergy Traits, and The Assessment of Genetic Variability in Sweet Sorghum (Sorghum bicolor (L.). Moench)

Sweet sorghum, a botanical variety of sorghum is a potential source of bioenergy because high sugar levels accumulate in its stalks. The objectives of this study were to explore the global diversity of sweet sorghum germplasm, and map the genomic regions that are associated with bioenergy traits. In assessing diversity, 142 sweet sorghum accessions were evaluated with three marker types (SSR, SRAP, and morphological markers) to determine the degree of relatedness among the accessions. The traits measured (anthesis date [AD], plant height [PH], biomass yield [BY], and moisture content [MC]) were all significantly different (P<0.05) among accessions. Morphological marker clustered the accessions into five groups based on PH, MC and AD. The three traits accounted for 92.5% of the variation. There were four and five groups based on SRAP and SSR data respectively classifying accessions mainly on their origin or breeding history. The observed difference between SSR and SRAP based clusters could be attributed to the difference in marker type. SSRs amplify any region of the genome whereas SRAP amplify the open reading frames and promoter regions. Comparing the three marker-type clusters, the markers complimented each other in grouping accessions and would be valuable in assisting breeders to select appropriate lines for crossing. In evaluating QTLs that are associated with bioenergy traits, 165 recombinant inbred lines (RILs) were planted at four environments in Nebraska. A genetic linkage map constructed spanned a length of 1541.3 cM, and generated 18 linkage groups that aligned to the 10 sorghum chromosomes. Fourteen QTLs (6 for brix, 3 for BY, 2 each for AD and MC, and 1 for PH) were mapped. QTLs for the traits that were significantly correlated, colocalized in two clusters on linkage group Sbi01b. Both parents contributed beneficial alleles for most of traits measured, supporting the transgressive segregation in this population. Additional work is needed on exploiting the usefulness of chromosome 1 in breeding sorghum for bioenergy.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Genome wide scan for quantitative trait loci affecting tick resistance in cattle (Bos taurus × Bos indicus)

Abstract Background In tropical countries, losses caused by bovine tick Rhipicephalus (Boophilus) microplus infestation have a tremendous economic impact on cattle production systems. Genetic variation between Bos taurus and Bos indicus to tick resistance and molecular biology tools might allow for the identification of molecular markers linked to resistance traits that could be used as an auxiliary tool in selection programs. The objective of this work was to identify QTL associated with tick resistance/susceptibility in a bovine F2 population derived from the Gyr (Bos indicus) × Holstein (Bos taurus) cross. Results Through a whole genome scan with microsatellite markers, we were able to map six genomic regions associated with bovine tick resistance. For most QTL, we have found that depending on the tick evaluation season (dry and rainy) different sets of genes could be involved in the resistance mechanism. We identified dry season specific QTL on BTA 2 and 10, rainy season specific QTL on BTA 5, 11 and 27. We also found a highly significant genome wide QTL for both dry and rainy seasons in the central region of BTA 23. Conclusions The experimental F2 population derived from Gyr × Holstein cross successfully allowed the identification of six highly significant QTL associated with tick resistance in cattle. QTL located on BTA 23 might be related with the bovine histocompatibility complex. Further investigation of these QTL will help to isolate candidate genes involved with tick resistance in cattle.

Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: identification of a novel QTL in rat chromosome 5

Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.

Heterosis in maize (Zea mays, L.): characterization of heterotic quantitative trait loci (QTL) for agronomic traits in near isogenic lines (NILs) and their testcrosses

In a previous study on maize (Zea mays, L.) several quantitative trait loci (QTL) showing high dominance-additive ratio for agronomic traits were identified in a population of recombinant inbred lines derived from B73 × H99. For four of these mapped QTL, namely 3.05, 4.10, 7.03 and 10.03 according to their chromosome and bin position, families of near-isogenic lines (NILs) were developed, i.e., couples of homozygous lines nearly identical except for the QTL region that is homozygote either for the allele provided by B73 or by H99. For two of these QTL (3.05 and 4.10) the NILs families were produced in two different genetic backgrounds. The present research was conducted in order to: (i) characterize these QTL by estimating additive and dominance effects; (ii) investigate if these effects can be affected by genetic background, inbreeding level and environmental growing conditions (low vs. high plant density). The six NILs’ families were tested across three years and in three Experiments at different inbreeding levels as NILs per se and their reciprocal crosses (Experiment 1), NILs crossed to related inbreds B73 and H99 (Experiment 2) and NILs crossed to four unrelated inbreds (Experiment 3). Experiment 2 was conducted at two plant densities (4.5 and 9.0 plants m-2). Results of Experiments 1 and 2 confirmed previous findings as to QTL effects, with dominance-additive ratio superior to 1 for several traits, especially for grain yield per plant and its component traits; as a tendency, dominance effects were more pronounced in Experiment 1. The QTL effects were also confirmed in Experiment 3. The interactions involving QTL effects, families and plant density were generally negligible, suggesting a certain stability of the QTL. Results emphasize the importance of dominance effects for these QTL, suggesting that they might deserve further studies, using NILs’ families and their crosses as base materials.

Trait emotional intelligence: Evidence from italian adolescents and adults

Emotional intelligence (EI) represents an attribute of contemporary attractiveness for the scientific psychology community. Of particular interest for the present thesis are the conundrum related to the representation of this construct conceptualized as a trait (i.e., trait EI), which are in turn reflected in the current lack of agreement upon its constituent elements, posing significant challenges to research and clinical progress. Trait EI is defined as an umbrella personality-alike construct reflecting emotion-related dispositions and self-perceptions. The Trait Emotional Intelligence Questionnaire (TEIQue) was chosen as main measure, given its strong theoretical and psychometrical basis, including superior predictive validity when compared to other trait EI measures. Studies 1 and 2 aimed at validating the Italian 153-items forms of the TEIQue devoted to adolescents and adults. Analyses were done to investigate the structure of the questionnaire, its internal consistencies and gender differences at the facets, factor, and global level of both versions. Despite some low reliabilities, results from Studies 1 and 2 confirm the four-factor structure of the TEIQue. Study 3 investigated the utility of trait EI in a sample of adolescents over internalizing conditions (i.e., symptoms of anxiety and depression) and academic performance (grades at math and Italian language/literacy). Beyond trait EI, concurrent effects of demographic variables, higher order personality dimensions and non-verbal cognitive ability were controlled for. Study 4a and Study 4b addressed analogue research questions, through a meta-analysis and new data in on adults. In the latter case, effects of demographics, emotion regulation strategies, and the Big Five were controlled. Overall, these studies showed the incremental utility of the TEIQue in different domains beyond relevant predictors. Analyses performed at the level of the four-TEIQue factors consistently indicated that its predictive effects were mainly due to the factor Well-Being. Findings are discussed with reference to potential implication for theory and practice.

Interaction between serotonin 5-HT2A receptor gene and dopamine transporter (DAT1) gene polymorphisms influences personality trait of persistence in Austrian Caucasians

We examined 89 normal volunteers using Cloninger's Temperament and Character Inventory (TCI). Genotyping the 102T/C polymorphism of the serotonin 5HT2A receptor gene and the ser9gly polymorphism in exon 1 of the dopamine D3 receptor (DRD3) gene was performed using PCR-RFLP, whereas the dopamine transporter (DAT1) gene variable number of tandem repeats (VNTR) polymorphism was investigated using PCR amplification followed by electrophoresis in an 8% acrylamide gel with a set of size markers. We found a nominally significant association between gender and harm avoidance (P=0.017; women showing higher scores). There was no association of either DAT1, DRD3 or 5HT2A alleles or genotypes with any dimension of the TCI applying Kruskal-Wallis rank-sum tests. Comparing homozygote and heterozygote DAT1 genotypes, we found higher novelty seeking scores in homozygotes (P=0.054). We further found a nominally significant interaction between DAT1 and 5HT2A homo-/heterozygous gene variants (P=0.0071; DAT1 and 5HT2A genotypes P value of 0.05), performing multivariate analysis of variance (MANOVA). Examining the temperamental TCI subscales, this interaction was associated with persistence (genotypes: P=0.004; homo-/heterozygous gene variants: P=0.0004). We conclude that an interaction between DAT1 and 5HT2A genes might influence the temperamental personality trait persistence.

No evidence for a genetic association between female mating preference and male secondary sexual trait in a Lake Victoria cichlid fish

Sexual selection by female mating preference for male nuptial coloration has been suggested as a driving force in the rapid speciation of Lake Victoria cichlid fish. This process could have been facilitated or accelerated by genetic associations between female preference loci and male coloration loci. Preferences, as well as coloration, are heritable traits and are probably determined by more than one gene. However, little is known about potential genetic associations between these traits. In turbid water, we found a population that is variable in male nuptial coloration from blue to yellow to red. Males at the extreme ends of the phenotype distribution resemble a reproductively isolated species pair in clear water that has diverged into one species with blue-grey mates and one species with bright red males. Females of the turbid water population vary in mating preference coinciding with the male phenotype distribution. For the current study, these females were mated to blue males. We measured the coloration of the sires and male offspring. Parents-offspring regression showed that the sires did not affect male offspring coloration, which confirms earlier findings that the blue species breeds true. In contrast, male offspring coloration was determined by the identity of the dams, which suggests that there is heritable variation in male color genes between females. However, we found that mating preferences of the dams were not correlated with male offspring coloration. Thus, there is no evidence for strong genetic linkage between mating preference and the preferred trait in this population [Current Zoology 56 (1): 57-64 2010].