Dataset Information

Prospects for proteomics Directed Genomic and Genetic Analyses in Disease Discoveries.

ABSTRACT: Proteomic discoveries are usually made using database searches for identification of proteins in a given protein sample derived from cells or tissues. High throughput searches leave a number of peptides not analyzed for a variety of reasons, such as posttranslational modification or a mutation that results changes in the peptide that is not present in databases. Such mutations may be critically important in causing disease conditions. Accounts from ocular diseases are presented where the search provided results often from non-conventional databases (such as structural database instead of protein database) due to the presence of information about a mutant peptide. We contemplate that better algorithms and the ability to determine probabilities of different amino acids in the available sequence may permit combinatorial analysis with genomics which may help identify new disease associated mutations directly from the sequence of the captured peptides. In addition, the de novo analysis of spectra of the unidentified peptides may provide mutation or polymorphism information enabling additional insight about the disease association of a mutation or posttranslational modification.

SUBMITTER: Bhattacharya SK

PROVIDER: S-EPMC2899679 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

prospects for proteomics Directed Genomic and Genetic Analyses in Disease Discoveries.

Bhattacharya Sanjoy K SK

Proteomics insights 20090901

Proteomic discoveries are usually made using database searches for identification of proteins in a given protein sample derived from cells or tissues. High throughput searches leave a number of peptides not analyzed for a variety of reasons, such as posttranslational modification or a mutation that results changes in the peptide that is not present in databases. Such mutations may be critically important in causing disease conditions. Accounts from ocular diseases are presented where the search ...[more]

PMID: 20622924

Similar Datasets

Project description:Reproductive performance is a key indicator of the long-term sustainability of any livestock production system. Testicular hypoplasia (TH) is a morphological and functional reproductive disorder that affects bulls around the world and consequently causes major economic losses due to reduced fertility rates. Despite the improvements in management practices to enhance performance of affected animals, the use of hypoplastic animals for reproduction might contribute to expand the prevalence of this disorder. The aim of this study was to identify genomic regions that are associated with TH in Nellore cattle by performing a genome-wide association study (GWAS) and functional analyses. Phenotypic and pedigree data from 47,563 animals and genotypes (500,689 Single Nucleotide Polymorphism, SNPs) from 265 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. The estimated breeding values (EBVs) were calculated by fitting a single-trait threshold animal model using a Bayesian approach. The SNP effects were estimated using the Bayes C method and de-regressed EBVs for TH as the response variable (pseudo-phenotype). The top-15 ranking windows (5-adjacent SNPs) that explained the highest proportion of variance were identified for further functional and biological network analyses. The posterior mean (95% highest posterior density) of the heritability for TH was 0.16 (0.08; 0.23). The most important genomic windows were located on BTA1, BTA3, BTA4, BTA5, BTA9, BTA22, BTA23, and BTA25. These windows explained together 22.69% of the total additive genetic variance for TH. Strong candidate genes associated with metabolism and synthesis of steroids, cell survival, spermatogenesis process and sperm motility were identified, which might play an important role in the expression of TH. Our findings contribute to a better biological understanding of TH and future characterization of causal variants might enable improved genomic prediction of this trait in beef cattle.

Dataset Information

Prospects for proteomics Directed Genomic and Genetic Analyses in Disease Discoveries.

Publications

prospects for proteomics Directed Genomic and Genetic Analyses in Disease Discoveries.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets