Steven E. Brenner

Associate Professor
Ph.D.  Biological Sciences    University of Cambridge, MRC Laboratory of Molecular Biology, 1997
A.B.   Biochemical Sciences    Harvard University, 1992

461 Koshland Hall
Berkeley, California 94720-3102
brenner@compbio.berkeley.edu
office: 510-643-9131   lab: 510-642-9614   fax:  510-666-2505

Web site         Recent publications      People

Nonsense-mediated mRNA decay (NMD) is a cellular RNA surveillance system that recognizes transcripts with premature termination codons and degrades them. Several years ago, we discovered large numbers of natural alternative splice forms that appear to be targets for NMD, and we speculated that this might be a mode of gene regulation which we termed RUST (regulated unproductive splicing and translation). This seems to be confirmed by our finding that all conserved members of the SR family of splice regulators have an unproductive alternative mRNA isoform targeted for NMD. Strikingly, the splice pattern for each is conserved in mouse and always associated with an ultraconserved or highly-conserved region of ~100 or more nucleotides of perfect identity between human and mouse. Remarkably, this seems to have evolved independently in every one of the genes, suggesting that this is a natural mode of regulation. We are using microarray data to explore the pervasiveness of NMD in humans and in Drosophila, in collaboration with Don Rio. As part of a modENCODE consortium, we plan to discover the repertoire of cis-reglatory sites for alternative splicing in insects. Future directions include detailing the regulators in the SR family and exploring the evolution of this gene-expression regulation mechanism.

Reference: Lareau LF, Inada M, Green RE, Wengrod JC, Brenner SE. 2007. Unproductive splicing of human SR genes associated with ultraconserved DNA elements. Nature in press.

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Unfortunately, these predictions have littered the databases with erroneous information, for a variety of reasons including the propagation of errors and the systematic flaws in BLAST and related methods. In collaboration with Michael Jordan's group, we have developed a statistical approach to predicting protein function that uses a protein family's phylogenetic tree, as the natural structure for representing protein relationships. We overlay on this all known protein functions in the family. We use a model of function evolution to then infer the functions of all other protein functions. Even our initial implementations of this method, called SIFTER (statistical inference of function through evolutionary relationships) have performed better than other methods in widespread use. We are presently making numerous improvements to the underlying SIFTER algorithm and enhancing its ability to work on a wide range of data. We are collaborating with the Joint Genome Institute and numerous protein databases to improve annotation on a large scale. In collaboration with Jack Kirsch, we are also experimentally validating the function predictions, with a focus on the Nudix family.

Reference: Engelhardt BE, Jordan MI, Muratore KE, Brenner SE. 2005. Protein molecular function prediction by Bayesian phylogenomics. PLoS Comput Biol 1:432-445.

The Sorcerer II global ocean sampling project revealed the sequences millions of new putative protein sequences, arguably doubling the known repertoire of proteins. We collaborated with the Venter Institute in the analysis of these proteins, understanding how they differ from those previously seen, and discovering ancient relationships amongst them. We are developing a new binning method that will help assign individual sequence reads and contigs to clades, and we are collaborating with Jill Banfield to apply this to the acid mine drainage community. Our initial medical metagenomics project is a collaboration with Daniel Present and Maria Abreu at Mt. Sinai Hospital (NYC) to understand the role of gut microbiota in Crohn's disease. Crohn's disease has long been known to be associated with microbial communities in the intestine, but the exact etiology has been unclear. By explicitly sampling these communities we aim to better understand how they cause disease. In addition, by studying how gut flora change during the withdrawal of long-term antibiotics, we hope to gain insight into the action of these drugs on the intestinal microbiota.

Reference: Yooseph S et al. 2007. The Sorcerer II Global Ocean Sampling expedition: expanding the universe of protein families. PLoS Biology in press.

Structural genomics ultimately aims to provide an experimental structure or a high-quality model for every protein. We are involved in maintaining the SCOP: Structural Classification of Proteins and ASTRAL databases which are key resources for accessing and understanding protein structure data. We therefore analyze structural genomics efforts and guide their future directions. Using kernel methods and selected features, we are building systems to recognize ancient protein evolutionary relationships. We are also involved in the Protein Complex Analysis Project, which uses mass-spectrometry, electron microscopy, and electron tomography to understand protein complexes and their cellular distribution.

Reference: Chandonia JM, Brenner SE. 2006. The impact of structural genomics: expectations and outcomes. Science 311:347-351.

Full list of publications

Selected Publications:

Chandonia JM, Brenner SE. 2006. The impact of structural genomics: expectations and outcomes. Science 311:347-351. doi:10.1126/science.1121018 [PDF .2M] [supporting material 1.2M]

Soergel DAW, Lareau LF, Brenner SE. 2005. Regulation of gene expression by the coupling of alternative splicing and nonsense-mediated mRNA decay. in Maquat L, ed., Nonsense-mediated mRNA decay. Landes Bioscience. 175-196. [PDF .27M]

Engelhardt BE, Jordan MI, Muratore KE, Brenner SE. 2005. Protein molecular function prediction by Bayesian phylogenomics. PLoS Computational Biology 1: e45. doi: 10.1371/journal.pcbi.0010045 [PDF 1.4M]

Chandonia JM, Brenner SE. 2005. Implications of structural genomics target selection strategies: Pfam5000, whole genome, and random approaches. Proteins: Structure, Function, and Bioinformatics 58:166-179. doi: 10.1002/prot.20298 [PDF .64M]

Crooks GE, Wolfe J, Brenner SE. 2004. Measurements of protein sequence-structure correlations. Proteins: Structure, Function, and Bioinformatics 57:804-810. doi: 10.1002/prot.20262 [PDF .18M]

Lareau LF, Green RE, Bhatnagar RS, Brenner SE. 2004. The evolving roles of alternative splicing. Current Opinion in Structural Biology 14:273-282. doi: 10.1016/j.sbi.2004.05.002 [PDF .18M]

Hillman RT, Green RE, Brenner SE. 2004. An unappreciated role for RNA surveillance. Genome Biology 5:R8.1-R8.16 [PDF .36M]

Lewis BP, Green RE, Brenner SE. 2003. Evidence for the widespread coupling of alternative splicing and nonsense-mediated mRNA decay in humans. Proceedings of the National Academy of Sciences of the United States of America 100:189-192. doi: 10.1073/pnas.0136770100 [PDF .25M]

Green RE, Brenner SE. 2002. Bootstrapping and normalization for enhanced evaluations of pairwise sequence comparison. Proceedings of the IEEE 9:1834-47. doi: 10.1109/JPROC.2002.805303 [PDF 1.6M]

Klosterman PS, Holbrook SR, Brenner SE. 2002. SCOR: a structural classification of RNA database. Nucleic Acids Research 30:392-394. [PDF .1M]

Brenner SE. 2001. A tour of structural genomics. Nature Reviews Genetics 2:801-9. [PDF 2.3M]

Brenner SE, Levitt M. 2000. Expectations from structural genomics. Protein Science. 9:197-200. [PDF .26M]

Brenner SE. 1999. Errors in genome annotation. Trends in Genetics 15:132-133. [PDF .16M]

Brenner SE, Hubbard T, Murzin A, Chothia C. 1995. Gene duplications in the H. influenzae genome. Nature 378:140. [OCR PDF 1.43M]