Analysis of genetic correlations of hip height with selection indices and mature weight in Nelore cattle

Body size is directly related to the productive and reproductive performance of beef cattle raised under free-range conditions. In an attempt to better plan selection criteria, avoiding extremes in body size, this study estimated the heritabilities and genetic correlations of yearling hip height (YH) and mature hip height (MH) with selection indices obtained at weaning (WI) and yearling (YI) and mature weight (MW). Data from 102,373 Nelore animals born between 1984 and 2010, which belong to 263 farms that participate in genetic evaluation programmes of beef cattle conducted in Brazil and Paraguay, were used. The (co)variance components and genetic parameters were estimated by Bayesian inference in multi-trait analysis using an animal model. The mean heritabilities for YH, MH and MW were 0. 56 ± 0. 06, 0. 47 ± 0. 02 and 0. 42 ± 0. 02, respectively. The genetic correlation of YH with WI (0. 13 ± 0. 01) and YI (0. 11 ± 0. 01) was practically zero, whereas a higher correlation was observed with MW (0. 22 ± 0. 03). Positive genetic correlations of medium magnitude were estimated between MH and WI and YI (0. 23 ± 0. 01 and 0. 43 ± 0. 02, respectively). On the other hand, a high genetic correlation (0. 68 ± 0. 03) was observed between the indicator traits of mature body size (MH and MW). Considering the top 20 % of sire (896 sires) in terms of breeding values for the yearling index, the rank sire correlations between breeding values for MH and MW was 0. 62. In general, the results indicate that selection based on WI and YI should not lead to important changes in YH. However, an undesired correlated response in mature cow height is expected, particularly when selection is performed using YI. Therefore, changes in the body structure of Nelore females can be obtained when MH and MW is used as a selection criterion for cows. © 2012 Institute of Plant Genetics, Polish Academy of Sciences, Poznan.

Genetic parameters for test-day milk yield, 305-day milk yield, and lactation length in Guzerat cows

Milk production in tropical environments requires the use of crossbreeding systems including breeds well adapted to harsh conditions, but with lower productivities when compared to specialized breeds. Besides the genetic improvement for milk production, lactation lengths also need to be studied for most of these breeds. Accordingly, genetic parameters were estimated for 305-day cumulative milk yield (MY305), test-day milk yield (TDMY), and lactation length (LL) using information from the first lactations of 2816 Guzerat cows selected for milk production in 28 herds in Brazil. Contemporary groups were defined as herd, year and season of the test for TDMY, and as herd, year and season of calving for MY305 and LL. Variance components were estimated with the restricted maximum likelihood method under a multi-trait animal model. Heritabilities estimated for TDMY ranged from 0.16 to 0.24, and were 0.24 and 0.12 for MY305 and LL, respectively. Genetic correlations were high and positive, ranging from 0.51 to 0.99 among TDMY records, from 0.81 to 0.98 between each TDMY and MY305, and from 0.71 to 0.94 between each TDMY and LL. Genetic parameters obtained in this study indicated the possibility of using test-day records for the prediction of breeding values for milk yield in this population of the Guzerat breed. The use of TDMY as selection criteria would result in indirect gains in MY305 and LL. However, the highest response to selection for MY305 would be obtained by direct selection for this trait. © 2012 Elsevier B.V.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

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.

Programação de horários usando um algoritmo genético especializado

Pós-graduação em Engenharia Elétrica - FEIS

Genetic Correlation for Pre-Weaning and Post-Weaning Traits of Mediterranean Buffaloes from Brazil, Estimated By Bayesian Inference

The aim of this study was to estimate genetic, environmental and phenotypic correlation between birth weight (BW) and weight at 205 days age (W205), BW and weight at 365 days age (W365) and W205-W365, using Bayesian inference. The Brazilian Program for Genetic Improvement of Buffaloes provided the data that included 3,883 observations from Mediterranean breed buffaloes. With the purpose to estimate variance and covariance, bivariate analyses were performed using Gibbs sampler that is included in the MTGSAM software. The model for BW, W205 and W365 included additive direct and maternal genetic random effects, maternal environmental random effect and contemporary group as fixed effect. The convergence diagnosis was achieved using Geweke, a method that uses an algorithm implemented in R software through the package Bayesian Output Analysis. The calculated direct genetic correlations were 0.34 (BW-W205), 0.25 (BW-W365) and 0.74 (W205-W365). The environmental correlations were 0.12, 0.11 and 0.72 between BW-W205, BW-W365 and W205-W365, respectively. The phenotypic correlations were low for BW-W205 (0.01) and BW-W365 (0.04), differently than the obtained for W205-W365 with a value of 0.67. The results indicate that BW trait have low genetic, environmental and phenotypic association with the two others traits. The genetic correlation between W205 and W365 was high and suggests that the selection for weight at around 205 days could be beneficial to accelerate the genetic gain.

Genetic Parameters for Growth Traits of Mediterranean Buffaloes from Brazil, Estimated By Bayesian Inference

Quantitative analysis of growth genetic parameters is not available for many breeds of buffaloes making selection and breeding decisions an empirical process that lacks robustness. The objective of this study was to estimate heritability for birth weight (BW), weight at 205 days (W205) and 365 days (W365) of age using Bayesian inference. The Brazilian Program for Genetic Improvement of Buffaloes provided the data. For the traits BW, W205 and W365 of Brazilian Mediterranean buffaloes 5169, 3792 and 3883 observations have been employed for the analysis, respectively. In order to obtain the estimates of variance, univariate analyses were conducted using the Gibbs sampler included in the MTGSAM software. The model for BW, W205 and W365 included additive direct and maternal genetic random effects, random maternal permanent environmental effect and contemporary group that was treated as a fixed effect. The convergence diagnosis was performed employing Geweke, a method that uses an algorithm from the Bayesian Output Analysis package that was implemented using R software environment. The average values for weight traits were 37.6 +/- 4.7 kg for BW, 192.7 +/- 40.3 kg for W205 and 298.6 +/- 67.4 kg for W365. The heritability posterior distributions for direct and maternal effects were symmetric and close to those expected in a normal distribution. Direct heritability estimates obtained using the modes were 0.30 (BW), 0.52 (W205) and 0.54 (W365). The maternal heritability coefficient estimates were 0.31, 0.19 and 0.21 for BW, W205 and W365, respectively. Our data suggests that all growth traits and mainly W205 and W365, have clear potential for yield improvement through direct genetic selection.

Genetic Parameters for Milk Yield and Lactation Length of Crossbred Buffaloes from Brazil by Bayesian Inference

The objective of the study was to estimate heritability and repeatability for milk yield (MY) and lactation length (LL) in buffaloes using Bayesian inference. The Brazilian genetic improvement program of buffalo provided the data that included 628 females, from four herds, born between 1980 and 2003. In order to obtain the estimates of variance, univariate analyses were performed with the Gibbs sampler, using the MTGSAM software. The model for MY and LL included direct genetic additive and permanent environment as random effects, and contemporary groups, milking frequency and calving number as fixed effects. The convergence diagnosis was performed with the Geweke method using an algorithm implemented in R software through the package Bayesian Output Analysis. Average for milk yield and lactation length was 1,546.1 +/- 483.8 kg and 252.3 +/- 42.5 days, respectively. The heritability coefficients were 0.31 (mode), 0.35 (mean) and 0.34 (median) for MY and 0.11 (mode), 0.10 (mean) and 0.10 (median) for LL. The repeatability coefficient (mode) were 0.50 and 0.15 for MY and LL, respectively. Milk yield is the only trait with clear potential for genetic improvement by direct genetic selection. The repeatability for MY indicates that selection based on the first lactation could contribute for an improvement in this trait.

Genetic variation of the Ananas genus with ornamental potential

Brazil is one of the main centers of origin of pineapple species presenting the largest genetic variation of the Ananas genus. Embrapa Cassava and Fruits is a Brazilian Agricultural Research Corporation and has an ex-situ collection of 678 accessions of the Ananas genus and some other Bromeliaceae. The use of ornamental pineapple has increased in the last years demanding new varieties, mainly for the external market, due to the originality and colors of its tiny fruits. The main aim of the present study was describing accessions from the pineapple gene bank in order to quantify their genetic variation and identify possible progenitors to be used in breeding programs of ornamental pineapples. Eighty-nine accessions of Ananas comosus var. comosus, A. comosus var. bracteatus (Lindl.) Coppens et Leal, A. comosus var. ananassoides (Baker) Coppens et Leal, A. comosus var. erectifolius (L. B. Smith) Coppens et Leal, A. comosus var. parguasensis (Camargo et L. B. Smith) Coppens et Leal and A. macrodontes Morren were evaluated with 25 morphological descriptors. According to the results, the evaluated accessions were separated into the following categories: landscape plants, cut flower, potted plants, minifruits, foliage and hedge. The genetic distance among accessions was determined using the combined qualitative and quantitative data by the Gower algorithm. The pre-selected accessions presented genetic variation and ornamental potential for different uses. The multicategory analysis formed seven clusters through a classification method based on the average Euclidean distance between all accessions using the cut-point of genetic dissimilarity (D dg = 0.35). The genotypes A. comosus var. erectifolius were selected to be used as landscape plants, cut flower, minifruits and potted plants. Accessions of A. comosus var. bracteatus and A. macrodontes were selected as landscape plants and hedge. The highest variation was observed in A. comosus var. ananassoides genotypes, which presented high potential for use as cut flowers.

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.

Genetic and environmental factors associated with the risk of cognitive decline and dementia

AD is the most common age related neurodegenerative disease in the industrialized world. Clinically AD is defined as a progressing decline of cognitive functions. Neuropathologically, AD is characterized by the aggregation of b-amyloid (Ab) peptide in the form of extracellular senile plaques, and hyperphosphorlylated tau protein in the form of intracellular neurofibrillary tangles. These neuropathological hallmarks are often accompanied by abundant microvascular damage and pronounced inflammation of the affected brain regions. In this thesis we investigated several aspects of AD focusing on the genetic aspect. We confirmed that Alpha 1 antichymotrypsin (ACT), an acute phase protein, was associated to AD subjects, being plasma levels higher in AD cases than controls. In addition, in a GWA study we demonstrated that two different gene, Clusterin and CR1 were strongly associated to AD. A single gene association not explain such a complex disease like AD. The goal should be to created a network of genetic, phenotypic and clinical data associated to AD. We used a new algorithm, the ANNs, aimed to map variables and search for connectivity among variables. We found specific variables associated to AD like cholesterol levels, the presence of variation in HMGCR enzyme and the age. Other factors such as the BMI, the amount of HDL and blood folate levels were also associated with AD. Pathogen infections, above all viral infections, have been previously associated to AD. The hypothesis suggests that virus and in particular herpes virus could enter the brain when an individual becomes older, perhaps because of a decline in the immune system. Our new hypothesis is that the presence of SNPs in our GWA gene study results in a genetic signature that might affect individual brain susceptibility to infection by herpes virus family during aging.

Genetic evidence supporting the association of protease and protease inhibitor genes with inflammatory bowel disease: a systematic review

As part of the European research consortium IBDase, we addressed the role of proteases and protease inhibitors (P/PIs) in inflammatory bowel disease (IBD), characterized by chronic mucosal inflammation of the gastrointestinal tract, which affects 2.2 million people in Europe and 1.4 million people in North America. We systematically reviewed all published genetic studies on populations of European ancestry (67 studies on Crohn's disease [CD] and 37 studies on ulcerative colitis [UC]) to identify critical genomic regions associated with IBD. We developed a computer algorithm to map the 807 P/PI genes with exact genomic locations listed in the MEROPS database of peptidases onto these critical regions and to rank P/PI genes according to the accumulated evidence for their association with CD and UC. 82 P/PI genes (75 coding for proteases and 7 coding for protease inhibitors) were retained for CD based on the accumulated evidence. The cylindromatosis/turban tumor syndrome gene (CYLD) on chromosome 16 ranked highest, followed by acylaminoacyl-peptidase (APEH), dystroglycan (DAG1), macrophage-stimulating protein (MST1) and ubiquitin-specific peptidase 4 (USP4), all located on chromosome 3. For UC, 18 P/PI genes were retained (14 proteases and 4 protease inhibitors), with a considerably lower amount of accumulated evidence. The ranking of P/PI genes as established in this systematic review is currently used to guide validation studies of candidate P/PI genes, and their functional characterization in interdisciplinary mechanistic studies in vitro and in vivo as part of IBDase. The approach used here overcomes some of the problems encountered when subjectively selecting genes for further evaluation and could be applied to any complex disease and gene family.

Spatial isolation and genetic differentiation in naturally fragmented plant populations of the Swiss Alps

Aims The effect Of anthropogenic landscape fragmentation on the genetic diversity and adaptive potential of plant populations is a major issue in conservation biology. However, little is known about the partitioning of genetic diversity in alpine species, which occur in naturally fragmented habitats. Here, we, investigate molecular patterns of three alpine plants (Epilobium fleischeri, Geum reptans and Campanula thyrsoides) across Switzerland and ask whether Spatial isolation has led to high levels of populations differentiation, increasing over distance, and a decrease of within-population variability. We further hypothesize that file contrasting potential for long-distance dispersal (LDD) of Seed in these Species will considerably influence and explain diversity partitioning. Methods For each study species, we Sampled 20-23 individuals from each of 20-32 populations across entire Switzerland. We applied Random Amplified Polymorphic Dimorphism markers to assess genetic diversity within (Nei's expected heterozygosity, H-e; percentage of polymorphic hands, P-P) and among (analysis of molecular variance, Phi(st)) populations and correlated population size and altitude with within-populalion diversity. Spatial patterns of genetic relatedness were investigated using Mantel tests and standardized major axis regression as well as unweighted pair group method with arithmetic mean cluster analyses and Monmonier's algorithm. To avoid known biases, We standardized the numbers of populations, individuals and markers using multiple random reductions. We modelled LDD with a high alpine wind data set using the terminal velocity and height of seed release as key parameters. Additionally, we assessed a number of important life-history traits and factors that potentially influence genetic diversity partitioning (e.g. breeding system, longevity and population size). Important findings For all three species, We found a significant isolation-by-distance relationship but only a moderately high differentiation among populations (Phi(st): 22.7, 48 and 16.8%, for E. fleischeri, G. reptans and C. thyrsoides, respectively). Within-population diversity (H-c: 0.19-0.21, P-p: 62-75%) was not reduced in comparison to known results from lowland species and even small populations with < 50 reproductive individuals contained high levels of genetic diversity. We further found no indication that a high long-distance seed dispersal potential enhances genetic connectivity among populations. Gene flow seems to have a strong stochastic component causing large dissimilarity between population pairs irrespective of the spatial distance. Our results suggest that other life-history traits, especially the breeding System, may play an important role in genetic diversity partitioning. We conclude that spatial isolation in the alpine environment has a strong influence on population relatedness but that a number of factors can considerably influence the strength of this relationship.

Role of {\it ERCC1\/} in DNA repair and genetic recombination

The ERCC1 (Excision Repair Cross-Complementing-1) gene is the presumptive mammalian homolog of the Saccharomyces cerevisiae RAD10 gene. In mammalian NER, the Ercc1/XpF complex functions as an endonuclease that specifically recognizes 5$\sp\prime$ double-strand-3$\sp\prime$ single-strand structures. In yeast, the analogous function is performed by the Rad1/Rad10 complex. These observations and the conservation of amino acid homology between the Rad1 and XpF and the Rad10 and Ercc1 proteins has led to a general assumption of functional homology between these genes.^ In addition to NER, the Rad1/Rad10 endonuclease complex is also required in certain specialized mitotic recombination pathways in yeast. However, a similiar requirement for the endonuclease function of the Ercc1/XpF complex during genetic recombination in mammalian cells has not been directly demonstrated. The experiments performed in these studies were designed to determine if ERCC1 deficiency would produce recombination-deficient phenotypes in CHO cells similar to those observed in RAD10 deletion mutants, including: (1) decreased single-reciprocal exchange recombination, and (2) inability to process 5$\sp\prime$ sequence heterology in recombination intermediates.^ Specifically, these studies describe: (1) The isolation and characterization of the ERCC1 locus of Chinese hamster ovary cells; (2) The production of an ERCC1 null mutant cell line by targeted knock-out of the endogenous ERCC1 gene in a Chinese hamster ovary cell line, CHO-ATS49tg, which contains an endogenous locus, APRT, suitable as a chromosomal target for homologous recombination; (3) The characterization of mutant ERCC1 alleles from a panel of Chinese hamster ovary cell ERCC1 mutants derived by conventional mutagenesis; (4) An investigation of the effects of ERCC1 mutation on mitotic recombination through targeting of the APRT locus in an ERCC1 null background.^ The results of these studies strongly suggest that the role of ERCC1 in homologous recombination in mammalian cells is analogous to that of the yeast RAD10 gene. ^

Identification, quantification, spatiotemporal distribution and genetic variation of major latex secondary metabolites in the common dandelion (Taraxacum officinale agg.)

The secondary metabolites in the roots, leaves and flowers of the common dandelion (Taraxacum officinale agg.) have been studied in detail. However, little is known about the specific constituents of the plant’s highly specialized laticifer cells. Using a combination of liquid and gas chromatography, mass spectrometry and nuclear magnetic resonance spectrometry, we identified and quantified the major secondary metabolites in the latex of different organs across different growth stages in three genotypes, and tested the activity of the metabolites against the generalist root herbivore Diabrotica balteata. We found that common dandelion latex is dominated by three classes of secondary metabolites: phenolic inositol esters (PIEs), triterpene acetates (TritAc) and the sesquiterpene lactone taraxinic acid β-d-glucopyranosyl ester (TA-G). Purification and absolute quantification revealed concentrations in the upper mg g−1 range for all compound classes with up to 6% PIEs, 5% TritAc and 7% TA-G per gram latex fresh weight. Contrary to typical secondary metabolite patterns, concentrations of all three classes increased with plant age. The highest concentrations were measured in the main root. PIE profiles differed both quantitatively and qualitatively between plant genotypes, whereas TritAc and TA-G differed only quantitatively. Metabolite concentrations were positively correlated within and between the different compound classes, indicating tight biosynthetic co-regulation. Latex metabolite extracts strongly repelled D. balteata larvae, suggesting that the latex constituents are biologically active.