Genetic association study between Interleukin 10 gene and dental implant loss

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

A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data

Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.

Genome-Wide Analysis of Differentially Expressed Genes During the Early Stages of Tomato Infection by a Potyvirus

Plant responses against pathogens cause up-and downward shifts in gene expression. To identify differentially expressed genes in a plant-virus interaction, susceptible tomato plants were inoculated with the potyvirus Pepper yellow mosaic virus (PepYMV) and a subtractive library was constructed from inoculated leaves at 72 h after inoculation. Several genes were identified as upregulated, including genes involved in plant defense responses (e. g., pathogenesis-related protein 5), regulation of the cell cycle (e. g., cytokinin-repressed proteins), signal transduction (e. g., CAX-interacting protein 4, SNF1 kinase), transcriptional regulators (e. g., WRKY and SCARECROW transcription factors), stress response proteins (e. g., Hsp90, DNA-J, 20S proteasome alpha subunit B, translationally controlled tumor protein), ubiquitins (e. g., polyubiquitin, ubiquitin activating enzyme 2), among others. Downregulated genes were also identified, which likewise display identity with genes involved in several metabolic pathways. Differential expression of selected genes was validated by macroarray analysis and quantitative real-time polymerase chain reaction. The possible roles played by some of these genes in the viral infection cycle are discussed.

A Genome-wide Screen for Neurospora crassa Transcription Factors Regulating Glycogen Metabolism

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

Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle

Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.

Associação entre polimorfismos de base única e precocidade sexual em fêmeas da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Identificação de assinaturas de seleção e anotação do genoma em bovinos da raça Nelore

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genome-Wide Mapping of Loci Explaining Variance in Scrotal Circumference in Nellore Cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identificação de regiões genômicas selecionadas de forma divergente em equinos quarto de milha de corrida e trabalho

Pós-graduação em Genética e Melhoramento Animal - FCAV

Linkage disequilibrium and haplotype block structure in a composite beef cattle breed

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genetic analysis of feet and legs in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Effect of IGF1, GH, and PIT1 markers on the genetic parameters of growth and reproduction traits in Canchim cattle

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

Gene polymorphisms and increased DNA damage in morbidly obese women

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

Polymorphisms in TOX and NCOA2 genes and their associations with reproductive traits in cattle

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

Efeito da utilização de diferentes critérios de controle de qualidade dos genótipos em estudos de associação e seleção genômica ampla

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