Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model.

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F2 hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.

Regularized quantile regression for SNP marker estimation of pig growth curves.

BACKGROUND: Genomic growth curves are generally defined only in terms of population mean; an alternative approach that has not yet been exploited in genomic analyses of growth curves is the Quantile Regression (QR). This methodology allows for the estimation of marker effects at different levels of the variable of interest. We aimed to propose and evaluate a regularized quantile regression for SNP marker effect estimation of pig growth curves, as well as to identify the chromosome regions of the most relevant markers and to estimate the genetic individual weight trajectory over time (genomic growth curve) under different quantiles (levels). RESULTS: The regularized quantile regression (RQR) enabled the discovery, at different levels of interest (quantiles), of the most relevant markers allowing for the identification of QTL regions. We found the same relevant markers simultaneously affecting different growth curve parameters (mature weight and maturity rate): two (ALGA0096701 and ALGA0029483) for RQR(0.2), one (ALGA0096701) for RQR(0.5), and one (ALGA0003761) for RQR(0.8). Three average genomic growth curves were obtained and the behavior was explained by the curve in quantile 0.2, which differed from the others. CONCLUSIONS: RQR allowed for the construction of genomic growth curves, which is the key to identifying and selecting the most desirable animals for breeding purposes. Furthermore, the proposed model enabled us to find, at different levels of interest (quantiles), the most relevant markers for each trait (growth curve parameter estimates) and their respective chromosomal positions (identification of new QTL regions for growth curves in pigs). These markers can be exploited under the context of marker assisted selection while aiming to change the shape of pig growth curves.

Regularized quantile regression applied to genome-enabled prediction of quantitative traits.

Genomic selection (GS) is a variant of marker-assisted selection, in which genetic markers covering the whole genome predict individual genetic merits for breeding. GS increases the accuracy of breeding values (BV) prediction. Although a variety of statistical models have been proposed to estimate BV in GS, few methodologies have examined statistical challenges based on non-normal phenotypic distributions, e.g., skewed distributions. Traditional GS models estimate changes in the phenotype distribution mean, i.e., the function is defined for the expected value of trait-conditional on markers, E(Y|X). We proposed an approach based on regularized quantile regression (RQR) for GS to improve the estimation of marker effects and the consequent genomic estimated BV (GEBV). The RQR model is based on conditional quantiles, Qτ(Y|X), enabling models that fit all portions of a trait probability distribution. This allows RQR to choose one quantile function that "best" represents the relationship between the dependent and independent variables. Data were simulated for 1000 individuals. The genome included 1500 markers; most had a small effect and only a few markers with a sizable effect were simulated. We evaluated three scenarios according to symmetrical, positively, and negatively skewed distributions. Analyses were performed using Bayesian LASSO (BLASSO) and RQR considering three quantiles (0.25, 0.50, and 0.75). The use of RQR to estimate GEBV was efficient; the RQR method achieved better results than BLASSO, at least for one quantile model fit for all evaluated scenarios. The gains in relation to BLASSO were 86.28 and 55.70% for positively and negatively skewed distributions, respectively.

Genomic prediction for additive and dominance effects of censored traits in pigs.

Age at the time of slaughter is a commonly used trait in animal breeding programs. Since studying this trait involves incomplete observations (censoring), analysis can be performed using survival models or modified linear models, for example, by sampling censored data from truncated normal distributions. For genomic selection, the greatest genetic gains can be achieved by including non-additive genetic effects like dominance. Thus, censored traits with effects on both survival models have not yet been studied under a genomic selection approach. We aimed to predict genomic values using the Cox model with dominance effects and compare these results with the linear model with and without censoring. Linear models were fitted via the maximum likelihood method. For censored data, sampling through the truncated normal distribution was used, and the model was called the truncated normal linear via Gibbs sampling (TNL). We used an F2 pig population; the response variable was time (days) from birth to slaughter. Data were previously adjusted for fixed effects of sex and contemporary group. The model predictive ability was calculated based on correlation of predicted genomic values with adjusted phenotypic values. The results showed that both with and without censoring, there was high agreement between Cox and linear models in selection of individuals and markers. Despite including the dominance effect, there was no increase in predictive ability. This study showed, for the first time, the possibility of performing genomic prediction of traits with censored records while using the Cox survival model with additive and dominance effects.

Using artificial neural networks to select upright cowpea (Vigna unguiculata) genotypes with high productivity and phenotypic stability.

Cowpea (Vigna unguiculata) is grown in three Brazilian regions: the Midwest, North, and Northeast, and is consumed by people on low incomes. It is important to investigate the genotype x environment (GE) interaction to provide accurate recommendations for farmers. The aim of this study was to identify cowpea genotypes with high adaptability and phenotypic stability for growing in the Brazilian Cerrado, and to compare the use of artificial neural networks with the Eberhart and Russell (1966) method. Six trials with upright cowpea genotypes were conducted in 2005 and 2006 in the States of Mato Grosso do Sul and Mato Grosso. The data were subjected to adaptability and stability analysis by the Eberhart and Russell (1966) method and artificial neural networks. The genotypes MNC99-537F-4 and EVX91-2E-2 provided grain yields above the overall environment means, and exhibited high stability according to both methods. Genotype IT93K-93-10 was the most suitable for unfavorable environments. There was a high correlation between the results of both methods in terms of classifying the genotypes by their adaptability and stability. Therefore, this new approach would be effective in quantifying the GE interaction in upright cowpea breeding programs.

New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program.

Genomic selection is the main force driving applied breeding programs and accuracy is the main measure for evaluating its efficiency. The traditional estimator (TE) of experimental accuracy is not fully adequate. This study proposes and evaluates the performance and efficiency of two new accuracy estimators, called regularized estimator (RE) and hybrid estimator (HE), which were applied to a practical cassava breeding program and also to simulated data. The simulation study considered two individual narrow sense heritability levels and two genetic architectures for traits. TE, RE, and HE were compared under four validation procedures: without validation (WV), independent validation, ten-fold validation through jacknife allowing different markers, and with the same markers selected in each cycle. RE presented accuracies closer to the parametric ones and less biased and more precise ones than TE. HE proved to be very effective in the WV procedure. The estimators were applied to five traits evaluated in a cassava experiment, including 358 clones genotyped for 390 SNPs. Accuracies ranged from 0.67 to 1.12 with TE and from 0.22 to 0.51 with RE. These results indicated that TE overestimated the accuracy and led to one accuracy estimate (1.12) higher than one, which is outside of the parameter space. Use of RE turned the accuracy into the parameter space. Cassava breeding programs can be more realistically implemented using the new estimators proposed in this study, providing less risky practical inferences.

Genome wide selection in Citrus breeding.

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_seqTM (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.

Factor analysis applied to genome prediction for high-dimensional phenotypes in pigs.

The aim of the present study was to propose and evaluate the use of factor analysis (FA) in obtaining latent variables (factors) that represent a set of pig traits simultaneously, for use in genome-wide selection (GWS) studies. We used crosses between outbred F2 populations of Brazilian Piau X commercial pigs. Data were obtained on 345 F2 pigs, genotyped for 237 SNPs, with 41 traits. FA allowed us to obtain four biologically interpretable factors: "weight", "fat", "loin", and "performance". These factors were used as dependent variables in multiple regression models of genomic selection (Bayes A, Bayes B, RR-BLUP, and Bayesian LASSO). The use of FA is presented as an interesting alternative to select individuals for multiple variables simultaneously in GWS studies; accuracy measurements of the factors were similar to those obtained when the original traits were considered individually. The similarities between the top 10% of individuals selected by the factor, and those selected by the individual traits, were also satisfactory. Moreover, the estimated markers effects for the traits were similar to those found for the relevant factor.

Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs.

A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is much larger than the number of genotyped individuals, and such markers are highly correlated, special statistical methods are widely required. Among these methods, independent component regression, principal component regression, partial least squares, and partial principal components stand out. Thus, the aim of this study was to propose an application of the methods of dimensionality reduction to GWS of carcass traits in an F2 (Piau x commercial line) pig population. The results show similarities between the principal and the independent component methods and provided the most accurate genomic breeding estimates for most carcass traits in pigs.

Genomic selection for slaughter age in pigs using the Cox frailty model.

The aim of this study was to compare genomic selection methodologies using a linear mixed model and the Cox survival model. We used data from an F2 population of pigs, in which the response variable was the time in days from birth to the culling of the animal and the covariates were 238 markers [237 single nucleotide polymorphism (SNP) plus the halothane gene]. The data were corrected for fixed effects, and the accuracy of the method was determined based on the correlation of the ranks of predicted genomic breeding values (GBVs) in both models with the corrected phenotypic values. The analysis was repeated with a subset of SNP markers with largest absolute effects. The results were in agreement with the GBV prediction and the estimation of marker effects for both models for uncensored data and for normality. However, when considering censored data, the Cox model with a normal random effect (S1) was more appropriate. Since there was no agreement between the linear mixed model and the imputed data (L2) for the prediction of genomic values and the estimation of marker effects, the model S1 was considered superior as it took into account the latent variable and the censored data. Marker selection increased correlations between the ranks of predicted GBVs by the linear and Cox frailty models and the corrected phenotypic values, and 120 markers were required to increase the predictive ability for the characteristic analyzed.

Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information.

Knowledge of dominance effects should improve ge-netic evaluations, provide the accurate selection of purebred animals, and enable better breeding strategies, including the exploitation of het-erosis in crossbreeds. In this study, we combined genomic and pedi-gree data to study the relative importance of additive and dominance genetic variation in growth and carcass traits in an F2 pig population. Two GBLUP models were used, a model without a polygenic effect (ADM) and a model with a polygenic effect (ADMP). Additive effects played a greater role in the control of growth and carcass traits than did dominance effects. However, dominance effects were important for all traits, particularly in backfat thickness. The narrow-sense and broad-sense heritability estimates for growth (0.06 to 0.42, and 0.10 to 0.51, respectively) and carcass traits (0.07 to 0.37, and 0.10 to 0.76, respec-tively) exhibited a wide variation. The inclusion of a polygenic effect in the ADMP model changed the broad-sense heritability estimates only for birth weight and weight at 21 days of age.

Estudo farmacobotânico de partes aéreas vegetativas de aroeira-vermelha (Schinus terebinthifolius Raddi, Anacardiaceae) / Pharmacobotanical study of the aerial parts of Brazilian pepper (Schinus terebinthifolius Raddi)

Schinus terebinthifolius Raddi (Anacardiaceae), conhecida como aroeira-vermelha é uma espécie nativa do Brasil, perenifólia e pioneira, sendo muito utilizada para combater diversas doenças, pois apresenta, entre outras, propriedades anti-inflamatórias e cicatrizantes. O objetivo desta pesquisa foi realizar um estudo morfoanatômico do caule e da folha de S. terebinthifolius, descrevendo a organização dos tecidos e suas possíveis variações. As análises macro e microscópicas foram realizadas com material selecionado de partes vegetativas de um espécime localizado na cidade de Campina Grande - PB. A aroeira-vermelha é um vegetal arbóreo e dióico, que apresenta caule cilíndrico e simpodial, com casca rugosa e estriada. A folha é perene, alterna, coriácea e composta. As análises microscópicas evidenciaram epiderme caulinar e foliar uniestratificadas, exceto na face adaxial da folha, que é bisseriada. No caule e no pecíolo são visualizados muitos tricomas tectores unicelulares, curtos, cônicos e agudos no ápice. Encontram-se canais secretores arredondados e bem desenvolvidos na região do floema em todos os órgãos estudados, bem como cutícula revestindo as células epidérmicas e grande quantidade de drusas de oxalato de cálcio. Os feixes vasculares são circundados por células esclerenquimáticas e apresentam o floema seguido por xilema helicoidal bem desenvolvido. No caule, pecíolo e nervura central da folha, o xilema é interno e o floema, externo. A aroeira-vermelha apresenta alguns aspectos estruturais característicos de plantas xerófilas, como camada múltipla da epiderme da face adaxial foliar, que protegem o mesofilo de excessiva dessecação; presença de cutícula espessa e grande quantidade de pêlos e de estômatos; além de sistema vascular bem desenvolvido, com abundância de esclerênquima, dando sustentação ao feixe.

Schinus terebinthifolius Raddi (Anacardiaceae), popularly known as Brazilian pepper, is an evergreen, pioneer and indigenous plant from Brazil, and it is used to combat various diseases, as it presents anti-inflammatory and wound healing properties. The aim of this research was to study the morpho-anatomical features of the stem and leaf of S. terebinthifolius, describing the organization of the tissues and their variations. The macroscopic and microscopic analyses were performed with material selected from vegetative parts of a specimen collected in the city of Campina Grande - state of Paraíba, Brazil. The Brazilian pepper is a dioecious plant with cylindrical and sympodial stem and rough and striated bark. The leaves are evergreen, alternate, leathery and compound. The microscopic analysis showed uniseriate epidermis in the stem and leaf, except in the adaxial leaf, which is biseriate. In the stem and petiole, many unicellular, short, conical tector trichomes with acute apex are observed. In the phloem of all studied organs, we found rounded and well-developed secretory ducts, as well as cuticle covering the epidermal cells and a large amount of calcium oxalate druses. The vascular bundles are surrounded by sclerenchyma cells and present phloem followed by well-developed spiral xylem. In the stem, petiole and leaf's central vein, the xylem is internal and the phloem is external. The Brazilian pepper has some structural features characteristic of xerophilous plants, such as multiple layers of the epidermis in adaxial leaf, which protects the mesophyll from excessive drying, thick cuticle and a large quantity of hairs and stomata, well-developed vascular system with plenty of sclerenchyma, giving support to the bundle.

Supervised independent component analysis as an alternative method for genomic selection in pigs.

The objective of this work was to evaluate the efficiency of the supervised independent component regression (SICR) method for the estimation of genomic values and the SNP marker effects for boar taint and carcass traits in pigs. The methods were evaluated via the agreement between the predicted genetic values and the corrected phenotypes observed by cross-validation. These values were also compared with other methods generally used for the same purposes, such as RR-BLUP, SPCR, SPLS, ICR, PCR and PLS. The SICR method was found to have the most accurate prediction values.

Aspectos anatômicos de plântulas Foeniculum vulgare Mill / Anatomical aspects of the Foeniculum vulgare Mill. seedling

A erva-doce, Foeniculum vulgare Mill. (Apiaceae), é uma erva entouceirada, aromática que apresenta propriedades condimentares e medicinais; tem origem Européia e é amplamente cultivada em todo o Brasil. Devido à deficiência de informações relativas à organização estrutural de plântulas de espécies medicinais, o presente estudo teve como objetivo fornecer informações sobre a anatomia e o desenvolvimento de plântulas de F. vulgare. As sementes de erva-doce foram semeadas em areia e mantidas em casa de vegetação por 25 dias, sendo realizadas regas diárias. Foram selecionadas plântulas normais e de padrão uniforme, que tiveram raiz, zona de transição, caule, cotilédones e primeiras folhas seccionados à mão livre. Este material foi corado e montado em lâminas com glicerina para observação em microscópio. Em todos os órgãos da plântula de erva-doce a epiderme é unisseriada, cuticularizada e com estômatos; sendo que as duas últimas estruturas não são encontradas na raiz, porém esta apresenta pêlos unicelulares e cônicos. Os cotilédones e as folhas apresentam funções fotossintéticas e nutricionais, indicadas pela presença de grande quantidade de estômatos, cloroplastos e amido. A caracterização anatômica de plântulas de F. vulgare auxilia na identificação da espécie e no conhecimento da organização celular, fornecendo informações que auxiliam em estudos fisiológicos, taxonômicos e ecológicos.

Fennel, Foeniculum vulgare Mill. (Apiaceae), is a forming clumps herb and presents aromatic, medicinal and condimental properties. It has European origin and is widely cultivated and used in Brazil. Due to lack of information concerning the structural organization of seedlings of medicinal species, this study aimed to provide information about the anatomy and development of F. vulgare seedlings. The seeds fennel was sowed in sand and maintained in greenhouse for 25 days, with daily waterings. Were selected normal seedlings and with patterns uniforms, for freehand seccion of root, transition zone, stem, cotyledons and first leaves. This material was stained and mounted on slides with glycerol for observation under microscope. In all the parts of seedling fennel the epidermis is uniseriate, with a cuticle and stomata, and the two latter structures are not found in the root, but has tapered hairs unicellular. The cotyledons and the leaves have photosynthetic and nutrition functions, as indicated by the presence of large numbers of stomata, chloroplast and starch. The anatomical characterization of the F. vulgare seedling aids in specie identification and knowledge of cellular organization, providing information that assists in physiological, taxonomic and ecological studies.

Efeito de sistemas de consórcio e inseticida na formação dos estômatos em plântulas de erva-doce (Foeniculum vulgare Mill. ) / Effects of intercropping systems and insecticide in formation of stomata in fennel seedlings

Foeniculum vulgare Mill., pertencente à família Apiacea, é conhecida como erva-doce e apresenta grande importância medicinal e comercial, tanto no Brasil como em vários outros países. Objetivou-se com esta pesquisa, estudar o desenvolvimento dos estômatos em plântulas de F. vulgare oriundas de sementes produzidas em sistemas de consórcio erva-doce X algodão e com aplicação do inseticida monocrotofós. A erva-doce foi cultivada em consórcio com algodão colorido cultivar BRS Safira, sendo utilizados os seguintes tratamentos: 1A2E, uma fileira de algodão e duas de erva-doce; 2A1E, duas fileiras de algodão e uma de erva-doce; ES, erva-doce solteira; onde foram distribuídos com e sem aplicação de inseticida, totalizando seis tratamentos. As sementes colhidas foram semeadas em areia e mantidas em casa de vegetação por 25 dias. Partes das plântulas (zona de transição, caule, cotilédones e folhas) foram seccionadas à mão livre, coradas e montadas em lâminas com glicerina para observação em microscópio. Foram avaliadas as seguintes características: número de estômatos, diâmetro polar e equatorial dos estômatos e número de cloroplastos nas células-guarda. Os dados foram analisados em delineamento inteiramente casualizado e distribuídos em arranjo fatorial 3X2; sendo realizado teste de Tukey a 5% de probabilidade. Na zona de transição e no caule observou-se aumento do número e do diâmetro polar dos estômatos quando foram utilizados sistemas de consórcio. Nos cotilédones, a erva-doce solteira proporcionou maior número de estômatos, porém com menor diâmetro e com menor quantidade de cloroplastos. Já na folha, os consórcios influenciaram positivamente o número de estômatos e de cloroplastos. De forma geral, os sistemas de consórcio e o inseticida influenciaram positivamente o desenvolvimento dos estômatos das plântulas de erva-doce.

Foeniculum vulgare Mill., belonging to the family Apiaceae, is known as fennel and has great medicinal and commercial importance, both in Brazil and in several other countries. The objective of this research was to study the development of stomata of F. vulgare seedlings grown from seeds produced in intercropping systems fennel and cotton, with application of insecticide monocrotophos. The fennel was grown in association with colored cotton BRS Safira, with the following treatments: 1A2E, one rows of cotton and two fennel; 2A1E, two rows of cotton and one fennel; ES, fennel single; were distributed with and without application of insecticide, total six treatments. The seeds were sown in sand and kept in a greenhouse for 25 days. Parts of seedlings (transition zone, stem, cotyledons and leaves) were cut freehand, stained and mounted on slides with glycerol for observation under microscope. Were evaluated the following characteristics: stomata number, polar and equatorial diameter of the stomata and chloroplasts number in guard cells. The data were analyzed in completely randomized and distributed in factorial 3x2, being conducted Tukey test at 5% probability. The transition zone and stem showed an increase of the stomata number and polar diameter the when consortium systems were used. In cotyledons, fennel single provided the highest stomata number, but with smaller diameter and fewer chloroplasts. In leaf, the consortia have positively influenced the stomata and chloroplasts number. In general, the intercropping systems and insecticide positively influenced the development of stomata in fennel plants.