Reverse Engineering of Modified Genes by Bayesian Network Analysis Defines Molecular Determinants Critical to the Development of Glioblastoma

In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I–IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors.

Model updating using genetic algorithms with sequential niche technique

The authors would like to express their gratitude to organizations and people that supported this research. Piotr Omenzetter’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research. Ben Ryder of Aurecon and Graeme Cummings of HEB Construction assisted in obtaining access to the bridge and information for modelling. Luke Williams and Graham Bougen, undergraduate research students, assisted with testing.

Girolando breed genetic improvement program - Genetic evaluation of cows - June/2016.

The Girolando breed progeny test was established in 1997, as a result of the partnership between Girolando and Embrapa Dairy Cattle. In 2007, the Programa de Melhoramento Genético da Raça Girolando? PMGG (Genetic Improvement Program of the Girolando Breed) was implemented. Besides interacting with previously existing initiatives of the Girolando Breeders Association, such as the genealogical register service, the progeny test and the dairy control service, the PMGG launched the Linear Evaluation System (SLAG). The main objectives of the PMGG comprises identification of genetically superior individuals, the technically-oriented multiplication of genetics, the evaluation of economic traits and the promotion of sustainable dairy activities. The program have yielded impressive results. The Girolando breed semen sales increases faster than any other breed in Brazil.

Assessment of genetic diversity of zoonotic Brucella spp. recovered from livestock in Egypt using multiple locus VNTR analysis

Brucellosis is endemic in most parts of Egypt, where it is caused mainly by Brucella melitensis biovar 3, and affects cattle and small ruminants in spite of ongoing efforts devoted to its control. Knowledge of the predominant Brucella species/strains circulating in a region is a prerequisite of a brucellosis control strategy. For this reason a study aiming at the evaluation of the phenotypic and genetic heterogeneity of a panel of 17 Brucella spp. isolates recovered from domestic ruminants (cattle, buffalo, sheep, and goat) from four governorates during a period of five years (2002-2007) was carried out using microbiological tests and molecular biology techniques (PCR, MLVA-15, and sequencing). Thirteen strains were identified as B. melitensis biovar 3 while all phenotypic and genetic techniques classified the remaining isolates as B. abortus (n = 2) and B. suis biovar 1 (n = 2). MLVA-15 yielded a high discriminatory power (h = 0.801), indicating a high genetic diversity among the B. melitensis strains circulating among domestic ruminants in Egypt. This is the first report of the isolation of B. suis from cattle in Egypt which, coupled with the finding of B. abortus, suggests a potential role of livestock as reservoirs of several zoonotic Brucella species in the region.

Optimizing time delay feedback for active vibration control of a cantilever beam using a genetic algorithm

Active vibration control using time delay for a cantilever beam is developed in this paper. The equation of motion of the system is developed using the discrete standard formulation, and the discrete quadratic function is used to design the controller. The original contribution in this paper is using a genetic algorithm to determine the optimal time delay feedback for active vibration control of a cantilever beam. Simulations of the beam demonstrated that the genetic algorithm correctly identified the time delay which produced the quickest attenuation of unwanted vibrations for both mode one and mode two. In terms of frequency response, the optimal time delay for both modes reduced the resonant amplitude. In a mixed mode situation, the simulation demonstrated that an optimal time delay could be identified.

Evaluation of breeding strategies for polledness in dairy cattle using a newly developed simulation framework for quantitative and Mendelian traits

Background: Intensified selection of polled individuals has recently gained importance in predominantly horned dairy cattle breeds as an alternative to routine dehorning. The status quo of the current polled breeding pool of genetically-closely related artificial insemination sires with lower breeding values for performance traits raises questions regarding the effects of intensified selection based on this founder pool. Methods: We developed a stochastic simulation framework that combines the stochastic simulation software QMSim and a self-designed R program named QUALsim that acts as an external extension. Two traits were simulated in a dairy cattle population for 25 generations: one quantitative (QMSim) and one qualitative trait with Mendelian inheritance (i.e. polledness, QUALsim). The assignment scheme for qualitative trait genotypes initiated realistic initial breeding situations regarding allele frequencies, true breeding values for the quantitative trait and genetic relatedness. Intensified selection for polled cattle was achieved using an approach that weights estimated breeding values in the animal best linear unbiased prediction model for the quantitative trait depending on genotypes or phenotypes for the polled trait with a user-defined weighting factor. Results: Selection response for the polled trait was highest in the selection scheme based on genotypes. Selection based on phenotypes led to significantly lower allele frequencies for polled. The male selection path played a significantly greater role for a fast dissemination of polled alleles compared to female selection strategies. Fixation of the polled allele implies selection based on polled genotypes among males. In comparison to a base breeding scenario that does not take polledness into account, intensive selection for polled substantially reduced genetic gain for this quantitative trait after 25 generations. Reducing selection intensity for polled males while maintaining strong selection intensity among females, simultaneously decreased losses in genetic gain and achieved a final allele frequency of 0.93 for polled. Conclusions: A fast transition to a completely polled population through intensified selection for polled was in contradiction to the preservation of high genetic gain for the quantitative trait. Selection on male polled genotypes with moderate weighting, and selection on female polled phenotypes with high weighting, could be a suitable compromise regarding all important breeding aspects.

Genetic Algorithms for Parameter Estimation in Circadian Model

This paper proposes an algorithm to estimate two parameter values vs, transcription of frq gene, and vd, maximum rate of FRQ protein degradation for an existing 3rd order Neurospora model in literature. Details of the algorithm with simulation results are shown in this paper.

Genomic structure and marker-derived gene networks for growth and meat quality traits of brazilian nelore beef cattle.

Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.

Genome-wide detection of CNVs and their association with meat tenderness in Nelore cattle.

Brazil is one of the largest beef producers and exporters in the world with the Nelore breed representing the vast majority of Brazilian cattle (Bos taurus indicus). Despite the great adaptability of the Nelore breed to tropical climate, meat tenderness (MT) remains to be improved. Several factors including genetic composition can influence MT. In this article, we report a genome-wide analysis of copy number variation (CNV) inferred from Illumina1 High Density SNP-chip data for a Nelore population of 723 males. We detected >2,600 CNV regions (CNVRs) representing 6.5% of the genome. Comparing our results with previous studies revealed an overlap in 1400 CNVRs (>50%). A total of 1,155 CNVRs (43.6%) overlapped 2,750 genes. They were enriched for processes involving guanosine triphosphate (GTP), previously reported to influence skeletal muscle physiology and morphology. Nelore CNVRs also overlapped QTLs for MT reported in other breeds (8.9%, 236 CNVRs) and from a previous study with this population (4.1%, 109 CNVRs). Two CNVRs were also proximal to glutathione metabolism genes that were previously associated with MT. Genome-wide association study of CN state with estimated breeding values derived from meat shear force identified 6 regions, including a region on BTA3 that contains genes of the cAMP and cGMP pathway. Ten CNVRs that overlapped regions associated with MT were successfully validated by qPCR. Our results represent the first comprehensive CNV study in Bos taurus indicus cattle and identify regions in which copy number changes are potentially of importance for the MT phenotype.