A New Adaptive Hungarian Mating Scheme in Genetic Algorithms

In genetic algorithms, selection or mating scheme is one of the important operations. In this paper, we suggest an adaptive mating scheme using previously suggested Hungarian mating schemes. Hungarian mating schemes consist of maximizing the sum of mating distances, minimizing the sum, and random matching. We propose an algorithm to elect one of these Hungarian mating schemes. Every mated pair of solutions has to vote for the next generation mating scheme. The distance between parents and the distance between parent and offspring are considered when they vote. Well-known combinatorial optimization problems, the traveling salesperson problem, and the graph bisection problem are used for the test bed of our method. Our adaptive strategy showed better results than not only pure and previous hybrid schemes but also existing distance-based mating schemes

Communal or Separate Rearing of Families in Selective Breeding of Common Carp (Cyprinus carpio L.)

This study reports on investigation of ways of improving the breeding programme for growth-related traits in common carp in Vietnam. The base population was synthesized following a single pair mating scheme from six carp stocks: (1) 2nd generation of family selection; (2) Hungarian 6th generation of mass selection; (3) Hungarian scaled carp; (4) Indonesian yellow 6th generation of mass selection; (5) Indonesian yellow carp; and (6) Vietnamese 6th generation of mass selection. The next two selected generations were produced using a partial factorial mating scheme, with each family being split and reared using communal early rearing (CER) or separate early rearing (SER) methods. The second generation (G2) was produced from selected fish from the CER G1 group. The total number of selection, control and reference families was 135 in the G1 and 101 in the G2 respectively. The control and reference (Hungarian P33 line) families were produced by single pair mating (reference families with the G2 only). Seven microsatellite loci were used for parentage assignment in the CER groups: 96.8% of the offspring (1284 individuals) and 96.2% offspring (1341 individuals) were unambiguously assigned to 113 families (selection, control) in the G1 and 99 families (selection, control and reference) in the G2 generations, respectively. Restricted maximum likelihood in the individual model was used to estimate phenotypic and genetic parameters. In CER, the estimated heritability values of common carp were from 0.20 ± 0.04 to 0.29 ± 0.05 for both weight and length at final harvest, indicating substantial additive genetic variation for selection on growth-related traits. The overall obtained maternal and common environmental effects were consistently close to zero. The average of direct response to selection for body weight was 15.0% per generation. In SER, the number of families in the G1 and G2 were 135 (selection and control) and 101 (selection, control and reference), respectively. The heritability estimates were from 0.20 ± 0.07 to 0.31 ± 0.08 at final measurement. Common environmental (full-sib family) effect were all lower at tagging and slightly higher at last measurement, ranging from 0.05 to 0.22. The response in each generation of selection as the difference between the selection and control lines was 8.1% on average for weight at final harvest, lower than under CER. The high genetic correlations of growth-related traits between the third (one year old, mature) and second (7 months old) measurements could allow selection to be based on the earlier assessment, reducing handling stress close to spawning. The benefits of using microsatellite markers to ascertain parentage, achieve greater growth rate (close to farming systems), shorten time to maturity and selection, and the overall relative merits of using CER v’s SER in this genetic improvement programme are discussed

Genetic diversity and population structure of six autochthonous pig breeds from Croatia, Serbia, and Slovenia

Background: The importance of local breeds as genetic reservoirs of valuable genetic variation is well established. Pig breeding in Central and South-Eastern Europe has a long tradition that led to the formation of several local pig breeds. In the present study, genetic diversity parameters were analysed in six autochthonous pig breeds from Slovenia, Croatia and Serbia (Banija spotted, Black Slavonian, Turopolje pig, Swallow-bellied Mangalitsa, Moravka and Krskopolje pig). Animals from each of these breeds were genotyped using microsatellites and single nucleotide polymorphisms (SNPs). The results obtained with these two marker systems and those based on pedigree data were compared. In addition, we estimated inbreeding levels based on the distribution of runs of homozygosity (ROH) and identified genomic regions under selection pressure using ROH islands and the integrated haplotype score (iHS). Results: The lowest heterozygosity values calculated from microsatellite and SNP data were observed in the Turopolje pig. The observed heterozygosity was higher than the expected heterozygosity in the Black Slavonian, Moravka and Turopolje pig. Both types of markers allowed us to distinguish clusters of individuals belonging to each breed. The analysis of admixture between breeds revealed potential gene flow between the Mangalitsa and Moravka, and between the Mangalitsa and Black Slavonian, but no introgression events were detected in the Banija spotted and Turopolje pig. The distribution of ROH across the genome was not uniform. Analysis of the ROH islands identified genomic regions with an extremely high frequency of shared ROH within the Swallow-bellied Mangalitsa, which harboured genes associated with cholesterol biosynthesis, fatty acid metabolism and daily weight gain. The iHS approach to detect signatures of selection revealed candidate regions containing genes with potential roles in reproduction traits and disease resistance. Conclusions: Based on the estimation of population parameters obtained from three data sets, we showed the existence of relationships among the six pig breeds analysed here. Analysis of the distribution of ROH allowed us to estimate the level of inbreeding and the extent of homozygous regions in these breeds. The iHS analysis revealed genomic regions potentially associated with phenotypic traits and allowed the detection of genomic regions under selection pressure

Insights into Genetic Diversity, Runs of Homozygosity and Heterozygosity-Rich Regions in Maremmana Semi-Feral Cattle Using Pedigree and Genomic Data

Semi-feral local livestock populations, like Maremmana cattle, are the object of renewed interest for the conservation of biological diversity and the preservation and exploitation of unique and potentially relevant genetic material. The aim of this study was to estimate genetic diversity parameters in semi-feral Maremmana cattle using both pedigree- and genomic-based approaches (FIS and FROH), and to detect regions of homozygosity (ROH) and heterozygosity (ROHet) in the genome. The average heterozygosity estimates were in the range reported for other cattle breeds (HE=0.261, HO=0.274). Pedigree-based average inbreeding (F) was estimated at 4.9%. The correlation was low between F and genomic-based approaches (r=0.03 with FIS, r=0.21 with FROH), while it was higher between FIS and FROH (r=0.78). The low correlation between F and FROH coefficients may be the result of the limited pedigree depth available for the animals involved in this study. The ROH islands identified in Maremmana cattle included candidate genes associated with climate adaptation, carcass traits or the regulation of body weight, fat and energy metabolism. The ROHet islands contained candidate genes associated with nematode resistance and reproduction traits in livestock. The results of this study confirm that genome-based measures like FROH may be useful estimators of individual autozygosity, and may provide insights on pedigree-based inbreeding estimates in cases when animals’ pedigree data are unavailable, thus providing a more detailed picture of the genetic diversity

Insights into genetic diversity, runs of homozygosity and heterozygosity-rich regions in maremmana semi-feral cattle using pedigree and genomic data

Semi-feral local livestock populations, like Maremmana cattle, are the object of renewed interest for the conservation of biological diversity and the preservation and exploitation of unique and potentially relevant genetic material. The aim of this study was to estimate genetic diversity parameters in semi-feral Maremmana cattle using both pedigree-and genomic-based approaches (FIS and FROH), and to detect regions of homozygosity (ROH) and heterozygosity (ROHet) in the genome. The average heterozygosity estimates were in the range reported for other cattle breeds (HE = 0.261, HO = 0.274). Pedigree-based average inbreeding (F) was estimated at 4.9%. The correlation was low between F and genomic-based approaches (r = 0.03 with FIS, r = 0.21 with FROH), while it was higher between FIS and FROH (r = 0.78). The low correlation between F and FROH coefficients may be the result of the limited pedigree depth available for the animals involved in this study. The ROH islands identified in Maremmana cattle included candidate genes associated with climate adaptation, carcass traits or the regulation of body weight, fat and energy metabolism. The ROHet islands contained candidate genes associated with nematode resistance and reproduction traits in livestock. The results of this study confirm that genome-based measures like FROH may be useful estimators of individual autozygosity, and may provide insights on pedigree-based inbreeding estimates in cases when animals’ pedigree data are unavailable, thus providing a more detailed picture of the genetic diversity

A Multi-objective Evolutionary Algorithm to solve Complex Optimization Problems

Multi-objective optimization problem formulations reflect pragmatic modeling of several real-life complex optimization problems. In many of them the considered objectives are competitive with each other; emphasizing only one of them during solution generation and evolution incurs high probability of producing a one-sided solution, which is unacceptable with respect to other objectives. An appropriate solution to the multi-objective optimization problem is to investigate a set of solutions that satisfy all of the competing objectives to an acceptable extent, where no solution in the solution set is dominated by others in terms of objective optimization. In this work, we investigate well known Non-dominated Sorting Genetic Algorithm (NSGA-II), and Strength Pareto Evolutionary Algorithm (SPEA-II), to find Pareto optimal solutions for two real-life problems: Task-based Sailor Assignment Problem (TSAP) and Coverage and Lifetime Optimization Problem in Wireless Sensor Networks (CLOP). Both of these problems are multi-objective problems. TSAP constitutes five multi-directional objectives, whereas CLOP is composed of two competing objectives. To validate the special operators developed, these two test bed problems have been used. Finally, traditional NSGA-II and SPEA-II have been blended with these special operators to generate refined solutions of these multi-objective optimization problems

Molecular Anthropology in the genomic era

Molecular Anthropology is a relatively young field of research. In fact, less than 50 years have passed since the symposium ''Classification and Human Evolution'' ( 1962, Burg Wartenstein, Austria), where the term was formally introduced by Emil Zuckerkandl. In this time, Molecular Anthropology has developed both methodologically and theoretically and extended its applications, so covering key aspects of human evolution such as the reconstruction of the history of human populations and peopling processes, the characterization of DNA in extinct humans and the role of adaptive processes in shaping the genetic diversity of our species. In the current scientific panorama, molecular anthropologists have to face a double challenge. As members of the anthropological community, we are strongly committed to the integration of biological findings and other lines of evidence (e.g. linguistic and archaeological), while keeping in line with methodological innovations which are moving the approach from the genetic to the genomic level. In this framework, the meeting "DNA Polymorphisms in Human Populations: Molecular Anthropology in the Genomic Era" ( Rome, December 3-5, 2009) offered an opportunity for discussion among scholars from different disciplines, while paying attention to the impact of recent methodological innovations. Here we present an overview of the meeting and discuss perspectives and prospects of Molecular Anthropology in the genomic era