Department of Molecular & Cell Biology

Home Faculty and Research Faculty by Name Rachel Brem

Rachel Brem

Assistant Professor of Genetics, Genomics and Development

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Research Interests

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.

Current Projects

Pathway evolution.  When natural selection drives a population to acquire a new phenotype, the genetic response may involve sequence changes in many genes, each of which contributes to the final trait gain.  Classical molecular evolution methods often are not well-suited to detect these cases of complex, polygenic evolution, and our lab is developing new approaches to fill the power gap.  In one expression-based method, we first survey the genes subject to cis-regulatory change between populations; we then identify groups of genes of common function in which cis-regulatory alleles from a given population all affect expression in the same direction, which is unlikely under a neutral model.  A second, complementary method harnesses population genomic sequence data; here we use phylogenetic inference to find groups of genes whose phylogenetic trees all look the same but are distinct from the genomic average, providing evidence for coherent sequence changes in response to selection.  Current applications include fungal and metazoan systems.

Natural variation in expression of noncoding RNAs and their function.  We have developed a short-read sequencing procedure that improves quantitation of non-canonical, uncharacterized forms of coding transcripts and noncoding RNAs in parallel with well-studied mRNAs.  We are using this procedure to study the variation between genetically distinct individuals in expression of uncharacterized RNAs, and to use these expression differences to make and test predictions about RNA function.

Natural variation in the yeast unfolded protein response (UPR).  The UPR is a signaling cascade that protects cells from overwhelming loads of unfolded, unprocessed polypeptides in the endoplasmic reticulum.  This pathway is associated with cell death in mammalian neurodegenerative disease and also acts in many normal physiological processes.  Using yeast as a model, we are studying the genetic differences between individuals in the quantitative behaviors of the pathway.  Our ultimate goal is to understand how evolution tunes the kinetics, dose-response, and stochastic noise of UPR output.

Natural variation in gene expression in N. crassa.  We are collaborating with UCB mycologists John Taylor and Louise Glass to study genetic variation between strains of the filamentous fungus, Neurospora crassa.  We have uncovered two recently diverged Caribbean populations of this unicelluar eukaryote, and we are investigating the Caribbean system as a model of incipient speciation mediated by differences in DNA sequence and gene expression.  More broadly, we aim to use genetic variation between strains, in gene expression and in macroscopic phenotypes, in massively parallel annotation of the thousands of uncharacterized Neurospora genes.

The prevalence of feedback loops in the yeast genome.   Using high-throughput biochemical assays for regulatory feedback, we are surveying yeast DNA-binding proteins for their ability to regulate their own abundance.  Our goal is to gauge the prevalence of feedback in natural networks and understand the systems properties it confers.

Selected Publications

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, in press.

Martin HC, Roop JI, Schraiber JG, Hsu TY, Brem RB.  Evolution of a membrane protein regulon in Saccharomyces.  Molecular Biology and Evolution, in press.

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 2012-01-31