Assistant Professor of Genetics, Genomics and DevelopmentLab Homepage: http://blogs.ls.berkeley.edu/bremlab/
Individuals within and between species differ in many ways, from eye color to disease susceptibility. Much of this variation is controlled by sequence differences in genomic DNA. Recent successes in quantitative genetics have made clear that most such sequence variants give rise to subtle regulatory changes rather than to qualitative gains or losses. How these changes propagate through the regulatory network and manifest phenotypically is not well understood. Despite the elegance and power of general principles that have emerged from systems biology research, in most cases we cannot predict how subtle genetic changes lead to dramatic cellular consequences, let alone design therapeutics that interfere with these effects in human genetic disease.
The work in our lab is based on the idea that many sequence differences between outbred individuals affect regulatory cascades quantitatively—their RNA and protein output, their sensitivity to input signal, kinetics of output production, stochastic noise, adaptation, and other fine-scale parameters. Sequence variants affecting quantitative behavior can be identified by forward-genetic methods for any circuit, even when the total molecular parts list of the circuit is unknown. Their mapping allows us to discover novel circuit components, and their effects tell us how changes in these components can perturb the circuit yet be tolerated in the wild. We aim to understand the mechanisms by which our mapped alleles exert their effects: how they alter biomolecule structure, function, expression and abundance, and how these changes perturb the network. We also want to know how many variants impinge on a given pathway, and we want to assess the selective pressure on these variants in outbred populations.
Our lab group uses genetically distinct strains of budding yeast, other fungi, and human cell lines as models for the study of natural variation in RNA expression and quantitative regulatory biochemistry. We assay these parameters experimentally, and we develop statistical genetics software to identify the sequence variants that underlie phenotypic differences, as well as their importance in evolution.
Pathway evolution. Detecting ancient events of natural selection is critical for an understanding of the evolutionary origin of modern species. In the molecular study of evolution, a key limitation of most analysis methods is their reliance on a simple genetic model, in which one or a few mutations of strong effect confer a fitness advantage. Our lab is developing new approaches to move beyond this assumption: we seek to understand when and how natural selection can involve sequence changes in many genes, each of which contributes to a final advantageous phenotype. We have developed powerful methods to detect patterns of polygenic evolution across genes in pathways, using gene expression measurements across species as well as DNA sequences from individuals in populations. Current applications include fungal and metazoan systems.
The genetics of alternative polyadenylation. Extending beyond the protein-coding sequence of a messenger RNA is an additional stretch of sequence that harbors signals governing transcript fate. The use of alternative 3' transcript ends for a given gene can have dramatic consequences on the translation, half-life, or localization of the final gene product. In a few cases, human diseases have been associated with naturally occurring genetic variants at 3' gene ends; in general, how alternative polyadenylation differs among genetically distinct individuals is almost completely unknown. Our lab is dissecting the genetic basis of naturally occurring variation in 3' transcript ends and its the impact on gene expression, with the ultimate goal of understanding sequence signals that drive alternative polyadenylation in individual genes as well as the master regulatory proteins that carry out 3' RNA processing. Current work involves both human and fungal populations.
Natural variation in expression of noncoding RNAs and their function. Noncoding RNA expression is widespread in genomes from bacteria to human. Landmark studies have dissected the regulatory function of individual noncoding RNAs, but for the vast majority of noncoding transcripts, the potential for function remains unknown. We are dissecting the genetic differences across genetically distinct fungal strains and species in noncoding RNA expression, in order to discover principles of biogenesis and signatures of function among uncharacterized noncoding transcripts.
Natural variation in N. crassa. The filamentous fungi represent a clade of tens of thousands of eukaryotic species that includes many human and plant pathogens, as well as hosts for industrial bioproduction of pharmaceuticals and fuels. In even the best-annotated of these fungal species, almost half of the genes are of unknown function. As such, for the vast majority of biomedically and industrially relevant phenotypes in filamentous fungi, the genetic basis remains unknown. In collaboration with UCB mycologists John Taylor and Louise Glass, we are surveying naturally occurring genetic variation in gene expression between strains of the filamentous fungus Neurospora crassa; we use these genetic changes as a tool to discover regulatory networks, infer functions of uncharacterized genes, and elucidate the evolutionary history of wild fungi.
Yoon OK, Hsu TY, Im JH, Brem RB. Genetics and regulatory impact of alternative polyadenylation in human B-lymphoblastoid cells. PLoS Genetics, in press, 2012.
Zhu J, Sova P, Xu Q, Dombek KM, Xu EY, Vu H, Tu Z, Brem RB, Bumgarner RE, Schadt EE. Stitching together multiple data dimensions reveals interacting metabolic and transcriptomic networks that modulate cell regulation. PLoS Biology 10(4)e1001301, 2012.
Denby CM, Im JH, Yu RC, Pesce G, Brem RB. Negative feedback confers mutational robustness in yeast transcription factor regulation. Proc Natl Acad Sci USA 109(10):3874-8, 2012.
Martin HC, Roop JI, Schraiber JG, Hsu TY, Brem RB. Evolution of a membrane protein regulon in Saccharomyces. Molecular Biology and Evolution 29(7):1747-1756, 2012.
Lee HN, Magwene PM, Brem RB. Natural variation in CDC28 underlies morphological phenotypes in an environmental yeast isolate. Genetics, 188:723-730, 2011.
Ellison CE, Hall C, Kowbel D, Welch J, Brem RB, Glass NG, Taylor JW. Population genomics and local adaptation in wild isolates of a model microbial eukaryote. Proc Natl Acad Sci USA, 108(7):2831-36, 2011.
Yoon OK, Brem RB. Non-canonical transcript forms in yeast and their regulation during environmental stress. RNA, 16(6):1256-67, 2010.
Bullard JH, Mostovoy Y, Dudoit S, Brem RB. Polygenic and directional regulatory evolution across pathways in Saccharomyces. Proc Natl Acad Sci USA, 107(11):5058-63, 2010.
Zhu J, Zhang B, Smith EN, Drees B, Brem RB, Kruglyak L, Bumgarner RE, Schadt EE. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nat Genet. 40(7):854-61, 2008.
Ronald J, Tang H, Brem RB. Genome-wide evolutionary rates in laboratory and wild yeast. Genetics 174(1):541-4, 2006.
Ronald J, Brem RB, Whittle J, Kruglyak L. Local Regulatory Variation in Saccharomyces cerevisiae. PLoS Genet. 1(2):e25, 2005.
Brem RB, Storey JD, Whittle J, Kruglyak L. Genetic interactions between polymorphisms that affect gene expression in yeast. Nature 436(7051):701-3, 2005.
Brem RB, Kruglyak L. The landscape of genetic complexity across 5,700 gene expression traits in yeast. Proc Natl Acad Sci U S A. 102(5):1572-7, 2005.
Yvert G, Brem RB, Whittle J, Akey JM, Foss E, Smith EN, Mackelprang R, Kruglyak L. Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factors. Nat Genet. 35(1):57-64, 2003.
Brem RB, Yvert G, Clinton R, Kruglyak L. Genetic dissection of transcriptional regulation in budding yeast. Science 296(5568):752-5, 2002.
Last Updated 2012-08-14