81 resultados para Genomic imprinting


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Multiple primary tumors (MPT) are a major cause of mortality and morbidity among patients that have survived after the treatment of a first cancer. It has been proposed that after the first primary tumor, high risk of a subsequent tumor could be associated with radiotherapy used as treatment for the first cancer. Other potential risk factors include unhealthy lifestyle, genetic predisposition, aging, environmental determinants or an interaction between these factors. However, an association between the presence of MPT and family history of cancer in cases without clinical and molecular evidence of a known hereditary cancer syndrome is rarely described. Genomic DNA from 12 patients with at least two primary tumors and without mutations on TP53 was evaluated by CytoScan HD Array (Affymetrix). Chromosome Analysis Suite (ChAS) software v.2.0.1 was used considering at least 50 markers for gains; 25 for losses and a minimum of 5Mb for cnLOHs. Data from 1038 phenotypically healthy individuals (Affymetrix) and from Database of Genomic Variants were used as reference. Only alterations found in <1% (rare) or never described (new rare) in the reference population were considered. All cases, except one, presented a family history of cancer. Five cases developed MTP after radiotherapy and only one was located in the same treated area. It was detected 67 rare and 15 new rare genomic alterations encompassing 5.906 genes: 17 losses, 29 gains, and 36 cnLOH. X chromosome presented the higher number of alterations. Two patients with breast cancer presented a large deletion/cnLOH on 7q21. Enrichment analysis revealed 1275 genes associated with breast cancer (p= 0.001), which was diagnosed in 6 patients and their family members (all negative for BRCA1/2 or TP53 mutations). cnLOHs accounted for 44% of all the alterations. A significant proportion of cases (11/12) presented family history of cancer and the patients were not submitted to radiotherapy (7/12). We demonstrated the presence of rare genomic alterations in patients with MPT suggesting their involvement in the MPT development. cnLOH may arise as a new mechanism associated with the risk to develop MPT. All authors have declared no conflicts of interest.

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The bovine species have witnessed and played a major role in the drastic socio-economical changes that shaped our culture over the last 10,000 years. During this journey, cattle hitchhiked on human development and colonized the world, facing strong selective pressures such as dramatic environmental changes and disease challenge. Consequently, hundreds of specialized cattle breeds emerged and spread around the globe, making up a rich spectrum of genomic resources. Their DNA still carry the scars left from adapting to this wide range of conditions, and we are now empowered with data and analytical tools to track the milestones of past selection in their genomes. In this review paper, we provide a summary of the reconstructed demographic events that shaped cattle diversity, offer a critical synthesis of popular methodologies applied to the search for signatures of selection (SS) in genomic data, and give examples of recent SS studies in cattle. Then, we outline the potential and challenges of the application of SS analysis in cattle, and discuss the future directions in this field.

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Analysis of genomic data is increasingly becoming part of the livestock industry. Therefore, the routine collection of genomic information would be an invaluable resource for effective management of breeding programs in small, endangered populations. The objective of the paper was to demonstrate how genomic data could be used to analyse (1) linkage disequlibrium (LD), LD decay and the effective population size (NeLD); (2) Inbreeding level and effective population size (NeROH) based on runs of homozygosity (ROH); (3) Prediction of genomic breeding values (GEBV) using small within-breed and genomic information from other breeds. The Tyrol Grey population was used as an example, with the goal to highlight the potential of genomic analyses for small breeds. In addition to our own results we discuss additional use of genomics to assess relatedness, admixture proportions, and inheritance of harmful variants. The example data set consisted of 218 Tyrol Grey bull genotypes, which were all available AI bulls in the population. After standard quality control restrictions 34,581 SNPs remained for the analysis. A separate quality control was applied to determine ROH levels based on Illumina GenCall and Illumina GenTrain scores, resulting into 211 bulls and 33,604 SNPs. LD was computed as the squared correlation coefficient between SNPs within a 10 mega base pair (Mb) region. ROHs were derived based on regions covering at least 4, 8, and 16 Mb, suggesting that animals had common ancestors approximately 12, 6, and 3 generations ago, respectively. The corresponding mean inbreeding coefficients (F ROH) were 4.0% for 4 Mb, 2.9% for 8 Mb and 1.6% for 16 Mb runs. With an average generation interval of 5.66 years, estimated NeROH was 125 (NeROH>16 Mb), 186 (NeROH>8 Mb) and 370 (NeROH>4 Mb) indicating strict avoidance of close inbreeding in the population. The LD was used as an alternative method to infer the population history and the Ne. The results show a continuous decrease in NeLD, to 780, 120, and 80 for 100, 10, and 5 generations ago, respectively. Genomic selection was developed for and is working well in large breeds. The same methodology was applied in Tyrol Grey cattle, using different reference populations. Contrary to the expectations, the accuracy of GEBVs with very small within breed reference populations were very high, between 0.13-0.91 and 0.12-0.63, when estimated breeding values and deregressed breeding values were used as pseudo-phenotypes, respectively. Subsequent analyses confirmed the high accuracies being a consequence of low reliabilities of pseudo-phenotypes in the validation set, thus being heavily influenced by parent averages. Multi-breed and across breed reference sets gave inconsistent and lower accuracies. Genomic information may have a crucial role in management of small breeds, even if its primary usage differs from that of large breeds. It allows to assess relatedness between individuals, trends in inbreeding and to take decisions accordingly. These decisions would be based on the real genome architecture, rather than conventional pedigree information, which can be missing or incomplete. We strongly suggest the routine genotyping of all individuals that belong to a small breed in order to facilitate the effective management of endangered livestock populations.

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The aim of this study was to identify candidate genes and genomic regions associated with ultrasound-derived measurements of the rib-eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.

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The dog can spontaneously develop prostate cancer and consequently can be used as an experimental model for prostatic diseases associated with aging, including benign prostate hyperplasia (BPH) and prostate carcinoma (PCa). DNA copy number variations (CNVs) have been used to identify genes associated with cancer development and progression. DNA microarray based comparative genomic hybridization (aCGH) is a technique that allows to identify copy number of thousands of genes throughout the genome. aCGH was used to identify genomic regions with significantly different DNA copy number in three benign prostatic hyperplasia (BPH), four proliferative inflammatory atrophy (PIA), and 14 canine prostate carcinoma (PCa). Five histologically normal prostate tissue were used as reference. Genomic DNA was extracted from formalin fixed and paraffin embedded samples and CNVs data was evaluated in Canine Genome CGH Microarray 4x44K (G2519F, Design ID021193, Agilent). Data analysis was performed using Genomic Workbench Standard Edition 5.0.14 (Agilent). PCa showed higher number of altered genes related to canonical diseases process, cellular functions and molecular pathways as well as greater inter-relationship between genes, compared with PIA and BPH. In conclusion, PCa showed a more complex genotype, being losses the most frequent genomic changes. Some discrepancies between genomic alterations in human and canine carcinomas may indicate the different clinical behavior of these tumors in these two species. In addition, it was observed was an ascending pattern of genomic complexity in BPH, PIA and CA consistent with a model of multistep tumor progression.