PubMed Health⌕ Search

Biomedical subjects

Xiang Jia Min

Publications and source records attributed to Xiang Jia Min.

3 recordsLinked to original sources

Generation, annotation, and analysis of an extensive Aspergillus niger EST collection.

BACKGROUND: Aspergillus niger, a saprophyte commonly found on decaying vegetation, is widely used and studied for industrial purposes. Despite its place as one of the most important organisms for commercial applications, the lack of available information about its genetic makeup limits research with this filamentous fungus. RESULTS: We present here the analysis of 12,820 expressed sequence tags (ESTs) generated from A. niger cultured under seven different growth conditions. These ESTs identify about 5,108 genes of which 44.5% code for proteins sharing similarity (E < or = 1e(-5)) with GenBank entries of known function, 38% code for proteins that only share similarity with GenBank entries of unknown function and 17.5% encode proteins that do not have a GenBank homolog. Using the Gene Ontology hierarchy, we present a first classification of the A. niger proteins encoded by these genes and compare its protein repertoire with other well-studied fungal species. We have established a searchable web-based database that includes the EST and derived contig sequences and their annotation. Details about this project and access to the annotated A. niger database are available. CONCLUSION: This EST collection and its annotation provide a significant resource for fundamental and applied research with A. niger. The gene set identified in this manuscript will be highly useful in the annotation of the genome sequence of A. niger, the genes described in the manuscript, especially those encoding hydrolytic enzymes will provide a valuable source for researchers interested in enzyme properties and applications.

Aspergillus niger↗

OrfPredictor: predicting protein-coding regions in EST-derived sequences.

OrfPredictor is a web server designed for identifying protein-coding regions in expressed sequence tag (EST)-derived sequences. For query sequences with a hit in BLASTX, the program predicts the coding regions based on the translation reading frames identified in BLASTX alignments, otherwise, it predicts the most probable coding region based on the intrinsic signals of the query sequences. The output is the predicted peptide sequences in the FASTA format, and a definition line that includes the query ID, the translation reading frame and the nucleotide positions where the coding region begins and ends. OrfPredictor facilitates the annotation of EST-derived sequences, particularly, for large-scale EST projects. OrfPredictor is available at https://fungalgenome.concordia.ca/tools/OrfPredictor.html.

Algorithms↗

TargetIdentifier: a webserver for identifying full-length cDNAs from EST sequences.

TargetIdentifier is a webserver that identifies full-length cDNA sequences from the expressed sequence tag (EST)-derived contig and singleton data. To accomplish this TargetIdentifier uses BLASTX alignments as a guide to locate protein coding regions and potential start and stop codons. This information is then used to determine whether the EST-derived sequences include their translation start codons. The algorithm also uses the BLASTX output to assign putative functions to the query sequences. The server is available at https://fungalgenome.concordia.ca/tools/TargetIdentifier.html.

Algorithms↗