81 resultados para Genomic imprinting


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A significant proportion (up to 62) of oral squamous cell carcinomas (OSCCs) may arise from oral potential malignant lesions (OPMLs), such as leukoplakia. Patient outcomes may thus be improved through detection of lesions at a risk for malignant transformation, by identifying and categorizing genetic changes in sequential, progressive OPMLs. We conducted array comparative genomic hybridization analysis of 25 sequential, progressive OPMLs and same-site OSCCs from five patients. Recurrent DNA copy number gains were identified on 1p in 20/25 cases (80) with minimal, high-level amplification regions on 1p35 and 1p36. Other regions of gains were frequently observed: 11q13.4 (68), 9q34.13 (64), 21q22.3 (60), 6p21 and 6q25 (56) and 10q24, 19q13.2, 22q12, 5q31.2, 7p13, 10q24 and 14q22 (48). DNA losses were observed in 20 of samples and mainly detected on 5q31.2 (35), 16p13.2 (30), 9q33.1 and 9q33.29 (25) and 17q11.2, 3p26.2, 18q21.1, 4q34.1 and 8p23.2 (20). Such copy number alterations (CNAs) were mapped in all grades of dysplasia that progressed, and their corresponding OSCCs, in 70 of patients, indicating that these CNAs may be associated with disease progression. Amplified genes mapping within recurrent CNAs (KHDRBS1, PARP1, RAB1A, HBEGF, PAIP2, BTBD7) were selected for validation, by quantitative real-time PCR, in an independent set of 32 progressive leukoplakia, 32 OSSCs and 21 non-progressive leukoplakia samples. Amplification of BTBD7, KHDRBS1, PARP1 and RAB1A was exclusively detected in progressive leukoplakia and corresponding OSCC. BTBD7, KHDRBS1, PARP1 and RAB1A may be associated with OSCC progression. Proteinprotein interaction networks were created to identify possible pathways associated with OSCC progression.

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The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.

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

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

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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The evolution of eusociality is one of the major transitions in evolution, but the underlying genomic changes are unknown. We compared the genomes of 10 bee species that vary in social complexity, representing multiple independent transitions in social evolution, and report three major findings. First, many important genes show evidence of neutral evolution as a consequence of relaxed selection with increasing social complexity. Second, there is no single road map to eusociality; independent evolutionary transitions in sociality have independent genetic underpinnings. Third, though clearly independent in detail, these transitions do have similar general features, including an increase in constrained protein evolution accompanied by increases in the potential for gene regulation and decreases in diversity and abundance of transposable elements. Eusociality may arise through different mechanisms each time, but would likely always involve an increase in the complexity of gene networks.

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