- Rachel Brem
- Fungi as a model system for the study of genetic variation and evolution
- Adjunct Associate Professor
- 312F Energy Biosciences Building
- Berkeley, CA 94720
- Phone 415.209.2093
Ph.D. Biophysics, UC San Francisco, 2000
B.S. Biochemistry, Brown University, 1994
Polygenic evolution. When evolutionary biologists say a species has adapted to a new niche, the classic model is that one or a few mutations of strong effect have arisen in the genome, conferred a fitness advantage, and swept through the population. But in many cases, adaptation may be the result of multiple, subtly acting variants that work together to give rise to a new phenotype. Recognizing these cases of polygenic evolution remains a primary roadblock in the field. In our lab, we have met this challenge with novel methods to detect polygenic evolution in transcriptional profiling data, using Saccharomyces yeast as a testbed. We first pioneered a test for directional regulatory evolution, in which the genes of a pathway harbor cis-regulatory changes that predominantly drive expression up, or drive expression down, in one species relative to another (Bullard et al., 2010). We next established methods to integrate expression-based and sequence-based tests for natural selection, detecting strong signal in a set of yeast membrane protein genes (Martin et al., 2012). We then developed a phylogenetic analysis method for expression data that identifies evidence for polygenic regulatory evolution in a pathway even if the changes are not directional—that is, if some genes are upregulated and others downregulated in a particular species (Schraiber et al., 2013). And in a case study in yeast focused on galactose metabolism, we found and validated the organism-level traits that result from regulatory differences between species (Roop et al., 2016).
Mapping genotype to phenotype using variation in wild fungi. Most fungal genomes are poorly annotated, and many fungal traits of industrial and biomedical relevance are not well-suited to classical genetic screens. Assigning genes to phenotypes on a genomic scale thus remains an urgent need in the field. We have sought to fill this analysis gap with strategies that make use of the standing genetic variation in fungal populations. This work complements our research on genes under natural selection (see Polygenic evolution above). Here, as we pursue a given phenotypic difference between fungi, our main interest is in the underlying genes themselves, rather than their importance for fitness in the wild—the “how” instead of the “why” of naturally occurring genetic variation. Following this paradigm, our surveys of wild yeast isolates mapped unusual morphologies in mitotically dividing cells in liquid culture and on solid medium, and in meiotic spore sacs, to the causal genes CDC28 and IRA1/2 (Lee et al., 2011; Roop and Brem, 2012). In Neurospora crassa, with John Taylor and Louise Glass in PMB, our large-scale sequencing effort delineated North and Central American populations (Ellison et al., 2010), which we used in a genome-wide association study mapping the Golgi gene cse-1 and eight other components of a secretion pathway required for cell-cell communication in fungal germlings (Palma-Guerrero et al., 2013). And transcriptome analyses of these populations identified hbc-1 (hyperbranching and cytoskeleton-1), a novel gene involved in hyphal architecture, as well as novel determinants of nitrogen and amino acid starvation (Ellison et al., 2014). In Zymoseptoria tritici, a wheat pathogen, with Eva Stukenbrock at the Max Planck Institute in Marburg, Germany, our transcriptional profiling study identified genomic clusters of genes only expressed during infection of wheat and not during infection of other plant hosts. These loci were strikingly divergent from their orthologs in Zymoseptoria species specialized to other plants, implicating them as novel, candidate pathogenicity islands involved in host-specific functions (Kellner et al., 2014). Our next projects, now in progress, are focused on variation in lifespan across Saccharomyces strains (with our collaborators at the Buck Institute for Research on Aging); and strain variation in virulence and stress resistance traits in the human pathogens Cryptococcus and Coccidioides.
Natural variation in 3’-end RNA processing. Untranslated regions at the 3’ ends of mRNAs are rich in cis-acting elements that can influence transcript half-life, translation, and localization. Little is known about the contribution of 3’ RNA processing to genetic differences between individuals. To investigate this potential mechanism of regulatory and phenotypic change, we developed a 3’-end RNA-seq protocol and peak-finding methods to detect transcription termination events from the sequencing data. In yeast, our approach found signatures of regulatory function at hundreds of genes with premature termination in the middle of the open reading frame (Yoon & Brem, 2010). In a study of genetically distinct human individuals (Yoon et al., 2012), we identified cases of 3’-end processing variation between humans at loci implicated in disease. In ongoing work, we ask whether and how natural variation in 3’ UTRs underlies macroscopic traits, using yeast as a model.
Cross-phenotype association tests uncover genes mediating nutrient response in Drosophila. Nelson CS, Beck JN, Wilson KA, Pilcher ER, Kapahi P, Brem RB. BMC Genomics 17(1):867, 2016.
Vitamin D Promotes Protein Homeostasis and Longevity via the Stress Response Pathway Genes skn-1, ire-1, and xbp-1. Mark KA, Dumas KJ, Bhaumik D, Schilling B, Davis S, Oron TR, Sorensen DJ, Lucanic M, Brem RB, Melov S, Ramanathan A, Gibson BW, Lithgow GJ. Cell Reports 17(5):1226-1237.
The role of transcription factors at antisense-expressing gene pairs in yeast. Mostovoy Y, Thiemicke A, Hsu TY, Brem RB. Genome Biology and Evolution 8(6):1748-61, 2016.
Polygenic evolution of a sugar specialization tradeoff in yeast. Roop JI, Chung KC, Brem RB. Nature 530(7590):336-9, 2016.
Katewa SD, Akagi K, Bose N, Rakshit K, Camarella T, Zheng X, Hall D, Davies S, Nelson C, Brem RB, Ramanathan A, Sehgal A, Giebultowicz JM, Kapahi P. Peripheral Circadian Clocks Mediate Dietary Restriction-Dependent Changes in Lifespan and Fat Metabolism in Drosophila. Cell Metabolism 23(1):143-54, 2016.
McCormick M, … Brem RB, … Kennedy BK. A comprehensive analysis of replicative lifespan in 4,698 single-gene deletion strains uncovers novel mechanisms of aging. Cell Metabolism 22(5):895-906, 2015.
Morita T, McClain SP, Batia LM, Pellegrino M, Wilson SR, Kienzler MA, Lyman K, Olsen ASB, Wong JF, Brem RB, Bautista DM. HTR7 is a transducer of serotonergic acute and chronic itch. Neuron 87(1):124-38, 2015.
Kellner R, Bhattacharyya A, Poppe S, Hsu TY, Brem RB, Stukenbrock E. Transcriptome sequencing at early-stage infection of the wheat pathogen Z. tritici reveals chromosome differences in transcription patterns and host-specific gene expression. Genome Biology and Evolution 6(6):1353-65, 2014.
Ellison CE, Kowbel D, Glass NL, Taylor JW, Brem RB. Discovering functions of unannotated genes from a transcriptome survey of wild fungal isolates. mBio 5(2):e01046-13, 2014.
Schraiber JG, Mostovoy Y, Hsu TY, Brem RB. Inferring pathway evolutionary histories from transcriptional profiling data. PLoS Computational Biology 9(10):e1003255, 2013.
Palma-Guerrero J, Hall CR, Kowbel D, Welch J, Taylor JW, Brem RB, Glass NL. Genome-wide association identifies novel loci involved in fungal communication. PLoS Genetics 9(8):e1003669, 2013.
Lee HN, Mostovoy Y, Hsu TY, Chang A, Brem RB. Divergence of iron metabolism in wild Malaysian yeast. G3: Genes|Genomes|Genetics 3(12):2187-94, 2013.
Roop JI, Brem RB. Rare variants in hypermutable genes underlie common morphology and growth traits in wild S. paradoxus yeasts. Genetics 195(2):513-525, 2013. Cover article, July 2014 issue; featured paper, October 2013 issue highlights.
Yoon OK, Hsu TY, Im JH, Brem RB. Genetics and regulatory impact of alternative polyadenylation in human B-lymphoblastoid cells. PLoS Genetics 8(8):e1002882, 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.
Denby CM, Im JH, Yu RC, Pesce CG, Brem RB. Negative feedback confers mutational robustness in yeast transcription factor regulation. PNAS 109(10):3874-8, 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.
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. PNAS 108(7):2831-6, 2011. Faculty of 1000 Must Read/Recommended Paper.
Lee HN, Magwene PM, Brem RB. Natural variation in CDC28 underlies morphological phenotypes in an environmental yeast isolate. Genetics 188(3):723-30, 2011.
Bullard JH, Mostovoy J, Dudoit S, Brem RB. Polygenic and directional regulatory evolution across pathways in Saccharomyces. PNAS 107(11):5058-5063, 2010.
Yoon OK, Brem RB. Non-canonical transcript forms in yeast and their regulation during environmental stress. RNA 16(6):1256-67, 2010. Faculty of 1000 Recommended Paper.