Analysis and functional annotation of an expressed sequence tag collection for tropical crop sugarcane

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST),program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged.

Gene expression profiling reveals molecular marker candidates of laryngeal squamous cell carcinoma

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

Differentially expressed genes in giant cell tumor of bone

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

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

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise da expressão gênica no tumor ósseo de células gigantes

Pós-graduação em Genética - IBILCE

Assinaturas de seleção na linhagem de trabalho de equinos da raça quarto de milha

Pós-graduação em Genética e Melhoramento Animal - FCAV

Post-partum anoestrus in tropical beef cattle: A systems approach combining gene expression and genome-wide association results

The length of the post-partum anoestrous interval affects reproductive efficiency in many tropical beef cattle herds. In this study, results from genome-wide association studies (Experiment 1: GWAS) and gene expression (Experiment 2: microarray) were combined in a systems approach to reveal genetic markers, genes and pathways underlying the physiology of post-partum anoestrus in tropically adapted cattle. The microarray study measured the expression of 13,964 genes in the hypothalamus of Brahman cows. A total of 366 genes were differentially expressed (DE) in the post-partum period, when acyclic cows were compared to cows that had resumed ovarian cycles. Associated markers (P < 0.05) from a high density GWAS pointed to 2829 genes that were associated with post-partum anoestrous interval (PPAI) in two populations of beef cattle: Brahman and Tropical composite. Together the experiments provided evidence for 63 genes that are likely to influence the resumption of ovulation post-partum in tropically adapted beef cattle. Functional annotation analysis revealed that some of the 63 genes have known roles in hormonal activity, energy balance and neuronal synapse plasticity. Polymorphisms within candidate genes identified by this systems approach could have biological significance in post-partum anoestrus and help select Zebu (Bos indicus) influenced cattle with genetic potential for shorter post-partum anoestrus. Crown Copyright (C) 2014 Published by Elsevier B.V. All rights reserved.

Genetic analysis of feet and legs in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Prospection of genomic regions divergently selected in cutting line of quarter horses in relation to racing line

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

Using Amino Acid Correlation and Community Detection Algorithms to Identify Functional Determinants in Protein Families

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

Automatic classification of enzyme family in protein annotation

Most of the tasks in genome annotation can be at least partially automated. Since this annotation is time-consuming, facilitating some parts of the process - thus freeing the specialist to carry out more valuable tasks - has been the motivation of many tools and annotation environments. In particular, annotation of protein function can benefit from knowledge about enzymatic processes. The use of sequence homology alone is not a good approach to derive this knowledge when there are only a few homologues of the sequence to be annotated. The alternative is to use motifs. This paper uses a symbolic machine learning approach to derive rules for the classification of enzymes according to the Enzyme Commission (EC). Our results show that, for the top class, the average global classification error is 3.13%. Our technique also produces a set of rules relating structural to functional information, which is important to understand the protein tridimensional structure and determine its biological function. © 2009 Springer Berlin Heidelberg.