Cattle farming is one of the most important activities of Brazilian agribusiness. Brazil is the world's largest beef exporter, holds the world's largest commercial herd, and is the world's third largest producer and consumer of beef and the world's seventh largest milk producer, with about 4% of the world's total. In spite of its large overall production, Brazilian cattle farming remains low in productivity, indicating a great potential for improvement and expansion of this sector of the economy. In a globalized economy, market achievement and preservation are conditioned by the maintenance of the competitiveness of the quality and quantity characteristics of products of animal origin. Only with advanced research can it be possible to guarantee the maintenance and increase of the competitiveness of the national cattle farming. The identification of genes responsible for the phenotypic variation of characteristics of economic interest is an important step for the development of ancillary methods for the selection of superior genotypes and for the manipulation of the genome via transgenesis or interference RNA. Genomics has provided a basis for the identification of many of these genes, particularly by the study of molecular markers. However, with marker approaches, one often reaches a region that potentially contains several genes that could affect the characteristic of interest. Even when using the candidate gene strategy, it is difficult to safely state that the observed effect is related to the variations of the candidate gene being studied and not resulting from binding to another gene next to it. One of the possibilities to find an answer to these questions is to evaluate the relation between phenotype and gene expression. The comparison of the expression between individuals representing extreme phenotypic values for the trait under study is one of the frequently used strategies. The application of methods that allow the profiling of gene expression on a large scale, such as microarrays, in which the expression of thousands of genes can be simultaneously analyzed, is a strategy that is independent of assumptions in the choice of the genes to be analyzed and generates an infinity of data that can be analyzed under different aspects (such as metabolic pathways, physiological processes, sequence homology, non-allelic interactions, etc.). This strategy can be applied to the different characteristics under study, allowing to elucidate questions about resistance to diseases, product quality and reproductive efficiency, using essentially the same methodology for data generation and analysis, among which the present project addresses: resistance to infectious and parasitic diseases, reproductive characteristics and meat quality. In general, the strategy of analysis of gene expression was previously used in several projects conducted by the teams of this network, however in a specific and isolated way. In the research network conducted in this project, similar themes (eg, resistance to parasites) were approached in different conditions and localities, and could be confronted with each other. The differential expression information related to the determined phenotype within the present network can be compared with the studies of association of this same phenotype and point mutations (SNPs) predicted in another Embrapa project, offering an overview of the genome's functioning.