Integrating Gene Ontology and Blast to predict gene functions

A GoBlast system was built to predict gene function by integrating Blast search and Gene Ontology (GO) annotations together. The operation system was based on Debian Linux 3.1, with Apache as the web server and Mysql database as the data storage system. FASTA files with GO annotations were taken as the sequence source for blast alignment, which were formatted by wu-formatdb program. The GoBlast system includes three Bioperl modules in Perl:a data input module, a data process module and a data output module. A GoBlast query starts with an amino acid or nucleotide sequence. It ends with an output in an html page, presenting high scoring gene products which are of a high homology to the queried sequence and listing associated GO terms beside respective gene poducts. A simple click on a GO term leads to the detailed explanation of the specific gene function. This avails gene function prediction by Blast. GoBlast can be a very useful tool for functional genome research and is available for free at http://bioq.org/goblast.

Gene Expression Versus Sequence for Predicting Function: Glia Maturation Factor Gamma Is Not A Glia Maturation Factor

It is standard practice, whenever a researcher finds a new gene, to search databases for genes that have a similar sequence. It is not standard practice, whenever a researcher finds a new gene, to search for genes that have similar expression (co-expression). Failure to perform co-expression searches has lead to incorrect conclusions about the likely function of new genes, and has lead to wasted laboratory attempts to confirm functions incorrectly predicted. We present here the example of Glia Maturation Factor gamma (GMF-gamma). Despite its name, it has not been shown to participate in glia maturation. It is a gene of unknown function that is similar in sequence to GMF-beta. The sequence homology and chromosomal location led to an unsuccessful search for GMF-gamma mutations in glioma. We examined GMF-gamma expression in 1432 human cDNA libraries. Highest expression occurs in phagocytic, antigen-presenting and other hematopoietic cells. We found GMF-gamma mRNA in almost every tissue examined, with expression in nervous tissue no higher than in any other tissue. Our evidence indicates that GMF-gamma participates in phagocytosis in antigen presenting cells. Searches for genes with similar sequences should be supplemented with searches for genes with similar expression to avoid incorrect predictions.

Identifcation of Immunity-related Genes in Arabidopsis and Cassava Using Genomic Data

Recent advances in genomic and post-genomic technologies have provided the opportu- nity to generate a previously unimaginable amount of information. However, biological knowledge is still needed to improve the understanding of complex mechanisms such as plant immune responses. Better knowledge of this process could improve crop production and management. Here, we used holistic analysis to combine our own microarray and RNA-seq data with public genomic data from Arabidopsis and cassava in order to acquire biological knowledge about the relationships between proteins encoded by immunity-related genes （IRGs） and other genes. This approach was based on a kernel method adapted for the construction of gene networks. The obtained results allowed us to propose a list of new IRGs. A putative function in the immunity pathway was predicted for the new IRGs. The analysis of networks revealed that our predicted IRGs are either well documented or recognized in previous co-expression studies. In addition to robust relationships between IRGs, there is evidence suggesting that other cellular processes may be also strongly related to immunity.