Genetic algorithm of chu and beasley for static and multistage transmission expansion planning

In this paper the genetic algorithm of Chu and Beasley (GACB) is applied to solve the static and multistage transmission expansion planning problem. The characteristics of the GACB, and some modifications that were done, to efficiently solve the problem described above are also presented. Results using some known systems show that the GACB is very efficient. To validate the GACB, we compare the results achieved using it with the results using other meta-heuristics like tabu-search, simulated annealing, extended genetic algorithm and hibrid algorithms. © 2006 IEEE.

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co)variances with age adequately and larger breeding value accuracies can be expected using this model. © South African Society for Animal Science.

Application of molecular markers on genetic improvement and reproduction in the post-genomic Era: Emerging biotechnologies and perspectives in livestock

Background: New challenges are rising in the animal protein market, and one of the main world challenges is to produce more in shorter time, with better quality and in a sustainable way. Brazil is the largest beef exporter in volume hence the factors affecting the beef meat chain are of major concern in countrýs economy. An emerging class of biotechnological approaches, the molecular markers, is bringing new perspectives to face these challenges, particularly after the publication of the first complete livestock genome (bovine), which has triggered a massive initiative to put in practice the benefits of the so called the Post-Genomic Era. Review: This article aimed at showing the directions and insights in the application of molecular markers on livestock genetic improvement and reproduction as well at organizing the progress so far, pointing some perspectives of these emerging technologies in Brazilian ruminant production context. An overview on the nature of the main molecular markers explored in ruminant production is provided, which describes the molecular bases and detection approaches available for microsatellites (STR) and single nucleotide polymorphisms (SNP). A topic is dedicated to review the history of association studies between markers and important trait variation in livestock, showing the timeline starting on quantitative trait loci (QTL) identification using STR markers and ending in high resolution SNP panels to proceed whole genome scans for phenotype/genotype association. Also the article organizes this information to reveal how QTL prospection using STR could open ground to the feasibility of marker-assisted selection and why this approach is quickly being replaced by studies involving the application of genome-wide association using SNP research in a new concept called genomic selection. Conclusion: The world's scientific community is dedicating effort and resources to apply SNP information in livestock selection through the development of high density panels for genomic association studies, connecting molecular genetic data with phenotypes of economic interest. Once generated, this information can be used to take decisions in genetic improvement programs by selecting animals with the assistance of molecular markers.

Optimal trajectory and solution of the inverse kinematics of a robotic manipulator by genetic algorithms

This paper presents the generation of optimal trajectories by genetic algorithms (GA) for a planar robotic manipulator. The implemented GA considers a multi-objective function that minimizes the end-effector positioning error together with the joints angular displacement and it solves the inverse kinematics problem for the trajectory. Computer simulations results are presented to illustrate this implementation and show the efficiency of the used methodology producing soft trajectories with low computing cost. © 2011 Springer-Verlag Berlin Heidelberg.

Treatments to optimize the use of artificial insemination and reproductive efficiency in beef cattle under tropical environments

Bos indicus cattle, the preferred genetic group in tropical climates, are characterized by having a lower reproductive efficiency than Bos taurus. The reasons for the poorer reproductive efficiency of the Bos indicus cows include longer lengths of gestation and postpartum anestrus, a short length of estrous behavior with a high incidence of estrus occurring during the dark hours, and puberty at older age and at a higher percentage of body weight relative to mature body weight. Moreover, geography, environment, economics, and social traditions are factors contributing for a lower use of reproductive biotechnologies in tropical environments. Hormonal protocols have been developed to resolve some of the reproductive challenges of the Bos indicus cattle and allow artificial insemination, which is the main strategy to hasten genetic improvement in commercial beef ranches. Most of these treatments use exogenous sources of progesterone associated with strategies to improve the final maturation of the dominant follicle, such as temporary weaning and exogenous gonadotropins. These treatments have caused large impacts on reproductive performance of beef cattle reared under tropical areas. Copyright © 2011 O. G. Sá Filho and J. L. M. Vasconcelos.

Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle

Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.

An enhanced genetic algorithm to solve the static and multistage transmission network expansion planning

An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1) generation of an initial population using fast, efficient heuristic algorithms, (2) better implementation of the local improvement phase and (3) efficient solution of linear programming problems (LPs). Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem. Copyright © 2012 Luis A. Gallego et al.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Physiology and endocrinology symposium: Influence of cattle genotype (Bos indicus vs. Bos taurus) on oocyte and preimplantation embryo resistance to increased temperature

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

Study of whole genome linkage disequilibrium in Nellore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detecting Loci under Recent Positive Selection in Dairy and Beef Cattle by Combining Different Genome-Wide Scan Methods

As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP) data generated from dairy and beef cattle (taurine and indicine). The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10-7) population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3) in Brown Swiss (P = 3.82×10-12), and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection.

Expression of genes related to quality of Longissimus dorsi muscle meat in Nellore (Bos indicus) and Canchim (5/8 Bos taurus×3/8 Bos indicus) cattle

This study was performed to compare CAPN1, CAPN2, CAST, TG, DGAT1 and LEP gene expressions and correlate them with meat quality traits in two genetic groups (Nellore and Canchim) in order to assess their expression profile and use their expression profile as genetic markers. We analyzed 30 young bulls (1. year old), 15 of each genetic group. Samples of the Longissimus dorsi muscle were collected for analysis of: total lipids (TL) and meat tenderness measured as Warner-Bratzler shear force (SF) and myofibrillar fragmentation (MFI) at day of slaughter and 7. days of aging. Gene expression profiles were obtained via RT-qPCR. TL and MFI showed differences between breeds, higher MFI in Canchim and higher TL in Nellore. Calpains showed no differential expression between groups, as did DGAT1, TG, and LEP. CAST was expressed more in the Nellore cattle. The only significant within-breed correlation (0.79) between gene expression and meat traits was found for DGAT1 and MFI in Canchim breed. Although the number of animals used in this study was small, the results indicate that the increased expression of CAST in Nellore may reflect tougher meat, but the lack of correlations with the meat traits indicates it is not a promising genetic marker. © 2013 Elsevier Ltd.

Genetic and non-genetic effects on calf vigor at birth and preweaning mortality in nellore calves

The objective of the present study was to evaluate the genetic and non-genetic effects that influencevigor at birth and preweaning mortality in Nellore calves. A total of 11,727 records of births that occurred between 1978 and 2006, offspring of 363 sires, were analyzed. Poor calf vigor at birth (VB) and preweaning mortality divided into stillbirth (SB), early mortality (EM) and total mortality (TM) were analyzed as binary variables. Generalized linear models were used for the evaluation of non-genetic effects and generalized linear mixed models for genetic effects (sire and animal models). The incidences were 4.75% for VB, 2.66% for SB, 5.28% for EM, and 7.99% for TM. Birth weight was the effect that most influenced the traits studied. Calves weighing less than 22kg(females) and less than 24kg (males) were at a higher risk of low vigor and preweaning mortality. Preweaning mortality was higher among calves born from cows aged .3 and .11 years at calving compared with cows aged 7 to 10 years. Male calves presented less vigor and higher preweaning mortality than female calves. Selection for postweaning weight did not influence preweaning mortality. The heritability estimates ranged between 0.01 and 0.09 for VB, 0.00 and 0.27 for SB, 0.03 and 0.17 for EM and 0.02 and 0.10 for TM. Stillbirth should be included as a selection criterion in breeding programs of Nellore cattle, alone or as part of a selection index, aiming to reduce preweaning mortality. © 2013 Sociedade Brasileira de Zootecnia.

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach

Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. © 2013 Mokry et al.; licensee BioMed Central Ltd.

Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height

Background: Birth weight (BW) is an economically important trait in beef cattle, and is associated with growth- and stature-related traits and calving difficulty. One region of the cattle genome, located on Bos primigenius taurus chromosome 14 (BTA14), has been previously shown to be associated with stature by multiple independent studies, and contains orthologous genes affecting human height. A genome-wide association study (GWAS) for BW in Brazilian Nellore cattle (Bos primigenius indicus) was performed using estimated breeding values (EBVs) of 654 progeny-tested bulls genotyped for over 777,000 single nucleotide polymorphisms (SNPs).Results: The most significant SNP (rs133012258, PGC = 1.34 × 10-9), located at BTA14:25376827, explained 4.62% of the variance in BW EBVs. The surrounding 1 Mb region presented high identity with human, pig and mouse autosomes 8, 4 and 4, respectively, and contains the orthologous height genes PLAG1, CHCHD7, MOS, RPS20, LYN, RDHE2 (SDR16C5) and PENK. The region also overlapped 28 quantitative trait loci (QTLs) previously reported in literature by linkage mapping studies in cattle, including QTLs for birth weight, mature height, carcass weight, stature, pre-weaning average daily gain, calving ease, and gestation length.Conclusions: This study presents the first GWAS applying a high-density SNP panel to identify putative chromosome regions affecting birth weight in Nellore cattle. These results suggest that the QTLs on BTA14 associated with body size in taurine cattle (Bos primigenius taurus) also affect birth weight and size in zebu cattle (Bos primigenius indicus). © 2013 Utsunomiya et al.; licensee BioMed Central Ltd.