SIZE AS A LINE OF LEAST RESISTANCE II: DIRECT SELECTION ON SIZE OR CORRELATED RESPONSE DUE TO CONSTRAINTS?

Evolutionary change in New World Monkey (NWM) skulls occurred primarily along the line of least resistance defined by size (including allometric) variation (g(max)). Although the direction of evolution was aligned with this axis, it was not clear whether this macroevolutionary pattern results from the conservation of within population genetic covariance patterns (long-term constraint) or long-term selection along a size dimension, or whether both, constraints and selection, were inextricably involved. Furthermore, G-matrix stability can also be a consequence of selection, which implies that both, constraints embodied in g(max) and evolutionary changes observed on the trait averages, would be influenced by selection Here, we describe a combination of approaches that allows one to test whether any particular instance of size evolution is a correlated by-product due to constraints (g(max)) or is due to direct selection on size and apply it to NWM lineages as a case study. The approach is based on comparing the direction and amount of evolutionary change produced by two different simulated sets of net-selection gradients (beta), a size (isometric and allometric size) and a nonsize set. Using this approach it is possible to distinguish between the two hypotheses (indirect size evolution due to constraints or direct selection on size), because although both may produce an evolutionary response aligned with g(max), the amount of change produced by random selection operating through the variance/covariance patterns (constraints hypothesis) will be much smaller than that produced by selection on size (selection hypothesis). Furthermore, the alignment of simulated evolutionary changes with g(max) when selection is not on size is not as tight as when selection is actually on size, allowing a statistical test of whether a particular observed case of evolution along the line of least resistance is the result of selection along it or not. Also, with matrix diagonalization (principal components [PC]) it is possible to calculate directly the net-selection gradient on size alone (first PC [PC1]) by dividing the amount of phenotypic difference between any two populations by the amount of variation in PC1, which allows one to benchmark whether selection was on size or not

Validation of microsatellite markers for assisted selection of soybean genotypes resistant to powdery mildew

Powdery mildew is one of the most serious diseases of soybean and is found in all producing countries. The purpose of this study was to validate microsatellite markers previously identified as associated with resistance to powdery mildew in soybean. The study was conducted in two F, parent populations with contrasting resistance to powdery mildew, In the analysis 10 SSR primers were used for the populations. and tour polymorphic markers were identified for cross I (MGBR95-20937 x IAC-Foscarin 31) and three for cross 2 (MGBR-46 x Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) 48). The Chi-square analysis of the phenotypic evaluation confirmed the expected segregation (3: 1) of a dominant gene related to resistance. The polymorphic markers also segregated as expected (1:2:1). The markers Sat 366 and Sat 393 in the crosses 1 and 2. respectively, located at 9.41 and 12.45 cM from the gene. were considered promising for marker-assisted selection for resistance to powdery mildew in soybean. at a selection efficiency of 92.7% and 60.3% respectively.

Phenotypic and genetic parameters compared during repeated measures of longissimus muscle area and subcutaneous fat thickness in Nelore cattle

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

Selection for higher body weight in Nelore cattle is effective in achieving an increase of longissimus muscle area without reducing subcutaneous fat thickness

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

Two-Way Selection for Daily Gain and Feed Conversion in a Composite Rabbit Population

We conducted a two-way selection experiment in a composite rabbit population to investigate the responses to selection for postweaning ADG and feed conversion (FC). Two generations of crossing, followed by four generations of random pair matings, preceded three generations of selection. Selection was practiced within four lines: high-feed conversion (HFC), low-feed conversion (LFC), high gain (HG), and low gain (LG). Data on 1,446 rabbits from the random mating and selection generations were fitted to an animal model to estimate heritabilities of and the genetic correlation between ADG and FC. The two-trait model included rabbit and common litter random effects and line, generation, and sex fixed effects. Estimates of heritability of ADG and FC were .48 and .29, respectively, and the genetic correlation between them was -.82. Common litter environmental effects accounted for a proportion of .11 and . 13 of the phenotypic variation of the two traits, respectively. For ADG (in g/d) the regressions of mean breeding values on generation number during the selection period were 1.23 ± .12 (P < .01) in the HG line and -.86 ± .12 (P < .01) in the LG line; the regressions for FC (in g feed/g gain) were -.07 ± .01 (P < .01) in the HFC line and .03 ± .01 (P < .05) in the LFC line. Selection for ADG was effective in improving ADG and FC.

Phenotypic plasticity of composite beef cattle performance using reaction norms model with unknown covariate

The objective of the present study was to determine the presence of genotype by environment interaction (G × E) and to characterize the phenotypic plasticity of birth weight (BW), weaning weight (WW), postweaning weight gain (PWG) and yearling scrotal circumference (SC) in composite beef cattle using the reaction norms model with unknown covariate. The animals were born between 1995 and 2008 on 33 farms located throughout all Brazilian biomes between latitude -7 and -31, longitude -40 and -63. The contemporary group was chosen as the environmental descriptor, that is, the environmental covariate of the reaction norms. In general, higher estimates of direct heritability were observed in extreme favorable environments. The mean of direct heritability across the environmental gradient ranged from 0.05 to 0.51, 0.09 to 0.43, 0.01 to 0.43 and from 0.12 to 0.26 for BW, WW, PWG and SC, respectively. The variation in direct heritability observed indicates a different response to selection according to the environment in which the animals of the population are evaluated. The correlation between the level and slope of the reaction norm for BW and PWG was high, indicating that animals with higher average breeding values responded better to improvement in environmental conditions, a fact characterizing a scale of G × E. Low correlation between the intercept and slope was obtained for WW and SC, implying re-ranking of animals in different environments. Genetic variation exists in the sensitivity of animals to the environment, a fact that permits the selection of more plastic or robust genotypes in the population studied. Thus, the G × E is an important factor that should be considered in the genetic evaluation of the present population of composite beef cattle. © The Animal Consortium 2012.

Genomic and phenotypic profiles of two Brazilian breast cancer cell lines derived from primary human tumors

Breast cancer is the most common type of cancer among women worldwide. Research using breast cancer cell lines derived from primary tumors may provide valuable additional knowledge regarding this type of cancer. Therefore, the aim of this study was to investigate the phenotypic profiles of MACL-1 and MGSO-3, the only Brazilian breast cancer cell lines available for comparative studies. We evaluated the presence of hormone receptors, proliferation, differentiation and stem cell markers, using immunohistochemical staining of the primary tumor, cultured cells and xenografts implanted in immunodeficient mice. We also investigated the ability of the cell lines to form colonies and copy number alterations by array comparative genomic hybridization. Histopathological analysis showed that the invasive primary tumor from which the MACL-1 cell line was derived, was a luminal A subtype carcinoma, while the ductal carcinoma in situ (DCIS) that gave rise to the MGSO-3 cell line was a HER2 subtype tumor, both showing different proliferation levels. The cell lines and the tumor xenografts in mice preserved their high proliferative potential, but did not maintain the expression of the other markers assessed. This shift in expression may be due to the selection of an 'establishment' phenotype in vitro. Whole-genome DNA evaluation showed a large amount of copy number alterations (CNAs) in the two cell lines. These findings render MACL-1 and MGSO-3 the first characterized Brazilian breast cancer cell lines to be potentially used for comparative research. © 2013 Spandidos Publications Ltd. All rights reserved.

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.

Phenotypic and genetic variability for body weight of ostriches (Struthio camelus)

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

Genetic parameters and trends of morphometric traits of GIFT tilapia under selection for weight gain

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic and phenotypic parameters of carcass and organ traits of broiler chickens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Phenotypic, genetic and environmental parameters for traits related to femur bone integrity and body weight at 42 days of age in a broiler population

Intense selection among broilers, especially for performance and carcass traits, currently favors locomotion problems and bone resistance. Conducting studies relating to development and growth of bone tissue in broilers is necessary to minimize losses. Thus, genetic parameters were estimated for a broiler population's phenotypic traits such as BW at 42 d of age (BW42), chilled femur weight (CFW) and its yield (CFY), and femur measurements: calcium, DM, magnesium, phosphorus, and zinc content; breaking strength; rigidity; length; and thickness. Variance components were estimated through multitrait analyses using the restricted maximum likelihood method. The model included a fixed group effect (sex and hatch) and additive and residual genetic random effects. The heritability estimates we obtained ranged from 0.10 ± 0.05 to 0.50 ± 0.08 for chilled femur yield and BW42, respectively, and indicated that the traits can respond to the selection process, except for CFY, which presented low-magnitude heritability coefficients. Genetic correlation estimates between breaking strength, rigidity, and traits related to mineral content indicated that selection that aims to improve the breaking strength resistance of the femur is highly correlated with mineral content. Given the genetic correlation estimates between BW42 and minerals, it is suggested that in this population, selection for BW42 can be performed with greater intensity without affecting femoral integrity.

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Selection of early-maturing sweet orange cultivars by performance indexes

The objective of this work was to select adequate early-maturing sweet orange cultivars for the fresh fruit market and for industrial processing using performance indexes. Performance indexes for citrus were established from data collected in an experiment carried out in the southwest region of the state of Sao Paulo, involving 12 early-maturing sweet orange cultivars. New results were obtained by identifying cultivars with superior characteristics. In a comparison with 'Hamlin' sweet orange, a standard early-maturing cultivar, 'Valencia 2' and 'Salustiana' were considered better materials for the fresh fruit market, whereas 'Westin' sweet orange was identified as a superior cultivar for orange juice processing.

MODULARITY, NOISE, AND NATURAL SELECTION

Most biological systems are formed by component parts that are to some degree interrelated. Groups of parts that are more associated among themselves and are relatively autonomous from others are called modules. One of the consequences of modularity is that biological systems usually present an unequal distribution of the genetic variation among traits. Estimating the covariance matrix that describes these systems is a difficult problem due to a number of factors such as poor sample sizes and measurement errors. We show that this problem will be exacerbated whenever matrix inversion is required, as in directional selection reconstruction analysis. We explore the consequences of varying degrees of modularity and signal-to-noise ratio on selection reconstruction. We then present and test the efficiency of available methods for controlling noise in matrix estimates. In our simulations, controlling matrices for noise vastly improves the reconstruction of selection gradients. We also perform an analysis of selection gradients reconstruction over a New World Monkeys skull database to illustrate the impact of noise on such analyses. Noise-controlled estimates render far more plausible interpretations that are in full agreement with previous results.