The University of Texas at Austin
ORCID: 0000-0001-8808-180XPublishes on Bioinformatics and Genomic Networks, Advanced Proteomics Techniques and Applications, RNA and protein synthesis mechanisms. 453 papers and 39.6k citations.
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Neurospora crassa is a central organism in the history of twentieth-century genetics, biochemistry and molecular biology. Here, we report a high-quality draft sequence of the N. crassa genome. The approximately 40-megabase genome encodes about 10,000 protein-coding genes--more than twice as many as in the fission yeast Schizosaccharomyces pombe and only about 25% fewer than in the fruitfly Drosophila melanogaster. Analysis of the gene set yields insights into unexpected aspects of Neurospora biology including the identification of genes potentially associated with red light photobiology, genes implicated in secondary metabolism, and important differences in Ca2+ signalling as compared with plants and animals. Neurospora possesses the widest array of genome defence mechanisms known for any eukaryotic organism, including a process unique to fungi called repeat-induced point mutation (RIP). Genome analysis suggests that RIP has had a profound impact on genome evolution, greatly slowing the creation of new genes through genomic duplication and resulting in a genome with an unusually low proportion of closely related genes.
A computational method is proposed for inferring protein interactions from genome sequences on the basis of the observation that some pairs of interacting proteins have homologs in another organism fused into a single protein chain. Searching sequences from many genomes revealed 6809 such putative protein-protein interactions in Escherichia coli and 45,502 in yeast. Many members of these pairs were confirmed as functionally related; computational filtering further enriches for interactions. Some proteins have links to several other proteins; these coupled links appear to represent functional interactions such as complexes or pathways. Experimentally confirmed interacting pairs are documented in a Database of Interacting Proteins.
Determining protein functions from genomic sequences is a central goal of bioinformatics. We present a method based on the assumption that proteins that function together in a pathway or structural complex are likely to evolve in a correlated fashion. During evolution, all such functionally linked proteins tend to be either preserved or eliminated in a new species. We describe this property of correlated evolution by characterizing each protein by its phylogenetic profile, a string that encodes the presence or absence of a protein in every known genome. We show that proteins having matching or similar profiles strongly tend to be functionally linked. This method of phylogenetic profiling allows us to predict the function of uncharacterized proteins.
Cellular states are determined by differential expression of the cell's proteins. The relationship between protein and mRNA expression levels informs about the combined outcomes of translation and protein degradation which are, in addition to transcription and mRNA stability, essential contributors to gene expression regulation. This review summarizes the state of knowledge about large-scale measurements of absolute protein and mRNA expression levels, and the degree of correlation between the two parameters. We summarize the information that can be derived from comparison of protein and mRNA expression levels and discuss how corresponding sequence characteristics suggest modes of regulation.
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