6 resultados para Governo Luiz Inácio Lula da Silva (2003 - )


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Background: Copy number variations (CNVs) have been shown to account for substantial portions of observed genomic variation and have been associated with qualitative and quantitative traits and the onset of disease in a number of species. Information from high-resolution studies to detect, characterize and estimate population-specific variant frequencies will facilitate the incorporation of CNVs in genomic studies to identify genes affecting traits of importance. Results: Genome-wide CNVs were detected in high-density single nucleotide polymorphism (SNP) genotyping data from 1,717 Nelore (Bos indicus) cattle, and in NGS data from eight key ancestral bulls. A total of 68,007 and 12,786 distinct CNVs were observed, respectively. Cross-comparisons of results obtained for the eight resequenced animals revealed that 92 % of the CNVs were observed in both datasets, while 62 % of all detected CNVs were observed to overlap with previously validated cattle copy number variant regions (CNVRs). Observed CNVs were used for obtaining breed-specific CNV frequencies and identification of CNVRs, which were subsequently used for gene annotation. A total of 688 of the detected CNVRs were observed to overlap with 286 non-redundant QTLs associated with important production traits in cattle. All of 34 CNVs previously reported to be associated with milk production traits in Holsteins were also observed in Nelore cattle. Comparisons of estimated frequencies of these CNVs in the two breeds revealed 14, 13, 6 and 14 regions in high (>20 %), low (<20 %) and divergent (NEL > HOL, NEL < HOL) frequencies, respectively. Conclusions: Obtained results significantly enriched the bovine CNV map and enabled the identification of variants that are potentially associated with traits under selection in Nelore cattle, particularly in genome regions harboring QTLs affecting production traits.

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2016

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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.

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Visando fornecer subsídios para programas de manejo de plantas daninhas em culturas agrícolas, foi realizado o presente estudo. Assim, foi conduzido um experimento de campo em Botucatu (Sao Paulo), com o objetivo de determinar, através do procedimento estatístico de análise de regressão, o período crítico para prevenção da interferência (PCPI) de plantas daninhas de folha larga na produtividade da cultura de soja. Foi utilizado o delineamento experimental em blocos casualizados. A cultura foi mantida na presença das plantas daninhas de folha larga por diferentes períodos. O período crítico determinado foi de 21 a 30 dias após a emergência da cultura, segundo ajuste dos dados de produtividade ao modelo "Broken-stick". No entanto, o período crítico determinado apresentou-se de modo que permite o controle através do uso, uma única vez, de método momentâneo, sem efeito residual.

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Aspectos básicos do Pampalus; Como participar do Pampaplus; Sistema Pampaplusnet. Autores: Antônio do Nascimento Rosa, Fernando Flores Cardoso, Joal Brazzale Leal, Luiz Otávio Campos da Silva, Marcos Jun-Iti Yokoo, Maurício Morgado de Oliveira, Paulo Roberto Costa Nobre, Roberto Augusto de Almeida Torres Júnior, Thaís Maria Bento Pires Lopa.