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Molecular Genetics in the Post-Genome-Sequence Era
The genomic sequences of humans, several eukaryotic model organisms, and numerous bacteria have opened up new opportunities and challenges for molecular genetics. Now one can study all the genes of an organism at once, promising a level of biological inference at the "system level", beyond that possible from studying separate, individual genes, gene assemblies or pathways. A major challenge is the analysis and display of huge volumes of information in ways that allow biologists to fully interpret them.
Research areas: (1) genome-wide studies of gene expression through the life cycle and experimental evolution of budding yeast (Saccharomyces cerevisiae), (2) mechanisms by which yeast maintain metabolic homeostasis in the face of environmental and genetic perturbations, and (3) quantitative analysis and intuitive display of genome-scale biological information in the context of genomic databases.
Genome-Scale Studies of Metabolic Homeostasis in Yeast
We are studying the ability of yeast to maintain metabolic homeostasis under a variety of steady-state (chemostat) and changing (perturbation of chemostat cultures or batch cultures) growth environments. We have found that many features of growth regulation are shared among chemostat cultures regardless of the nature of the nutrient limitation, whereas other general features (e.g. cell cycle arrest in starving batch cultures) vary according to the nature of the limitation. We have found a way to avoid a stress response after temperature shifts and are exploiting this to study transcriptional responses in response to limitations imposed by conditional lethal mutations in essential genes (e.g. those encoding actin and the tubulins). We have already found that different actin alleles with different phenotypes show characteristically different patters of transcriptional response in this system. In this way we are beginning to learn how cells respond to specific defects in essential intracellular functions.
Genome-Wide Gene Expression During Experimental Evolution in Yeast
When cultures of Saccharomyces cerevisiae are exposed to persistent strong selection in a constant environment, such as a limiting nutrient in continuous culture, fitter variant strains arise that “sweep” the culture. Based on the repeated observation of similar changes in patterns of genome-wide gene expression and underlying genomic rearrangements found in strains that have “evolved” independently under these conditions, it appears that yeast can adapt to glucose limitation in chemostats in only a small number of ways, in part by characteristic rearrangements of their genomes. We infer from these results that there must be constraints in the relevant regulatory networks that limit the ways in which gene expression can be altered in a way that improves fitness.
Both the evolution and homeostasis studies aim to define the many interactions of metabolic regulatory networks in yeast. Ultimately we hope to amass a body of data sufficient to support realistic mathematical and computational models of these networks. The methods we are developing should also provide the means for experimental tests of such models.
Analysis and Display of Genome-Scale Biological Data
The full value of highly parallel, genome-scale data acquisition methods such as DNA microarray hybridization can only be realized if there are comparably powerful analytical facilities in place, namely ways of storing, searching, recovering, analyzing and displaying the data. To this end we have established a microarray database at the Lewis-Sigler Institute that integrates these functions, and have moved some of the functionalities of the Saccharomyces Genome Database to Princeton. Essential to any useful display of results from genome-wide studies is an efficient system and intuitively understood linkages of genetic data with biological annotation for the bacterial, yeast, human or mouse genes under study. To this end we plan to establish and develop representation of genome-scale results that can be computationally parsed (using the Gene Ontology) and used in the interpretation and display of new data.
Genome wide copy number in 8 independently evolved strains. Genes are plotted by coordinate along each chromosome. A measurement was colored red or green if the running average of nine genes centered at the query gene was beyond 99.9% of the data in the control experiment. Copy number scale ranges from 0 to 6.
Selected Publications
Lang GI, Murray AW, Botstein D. (2009) The cost of gene expression underlies a fitness trade-off in yeast. Proc Natl Acad Sci. 106: 5755-5760. PubMed
Airoldi EM, Huttenhower C, Gresham D, Lu C, Caudy AA, Dunham MJ, Broach JR, Botstein D, Troyanskaya OG. (2009) Predicting cellular growth from gene expression signatures. PLoS Comput Biol. 5: e1000257. PubMed
Gresham D, Desai MM, Tucker CM, Jenq HT, Pai DA, Ward A, DeSevo CG, Botstein D, Dunham MJ. (2008) The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast. PLoS Genet. 4: e1000303. PubMed
Lu C, Brauer MJ, Botstein D. (2008) Slow growth induces heat shock resistance in normal and respiratory-deficient yeast. Mol Biol Cell. 20: 891-903. PubMed
Boer VM, Amini S, Botstein D. (2008) Influence of genotype and nutrition on survival and metabolism of starving yeast. Proc Natl Acad Sci USA. 105: 6930-6935. PubMed
Gresham D, Dunham MJ, Botstein D. (2008) Comparing whole genomes using DNA microarrays. Nat Rev Genet. 9: 291-302. PubMed
Hong EL, Balakrishnan R, Dong Q, Christie KR, Park J, Binkley G, Costanzo MC, Dwight SS, Engel SR, Fisk DG, Hirschman JE, Hitz BC, Krieger CJ, Livstone MS, Miyasato SR, Nash RS, Oughtred R, Skrzypek MS, Weng S, Wong ED, Zhu KK, Dolinski K, Botstein D, Cherry JM. (2007) Gene Ontology annotations at SGD: new data sources and annotation methods. Nucleic Acids Res 36(Database issue): D577-581. PubMed
Brauer MJ, Huttenhower C, Airoldi EM, Rosenstein R, Matese JC, Gresham D, Boer VM, Troyanskaya OG, Botstein D. (2007) Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. Mol Biol Cell 19: 352-367. PubMed
Dolinski K, Botstein D. (2007) Orthology and functional conservation in eukaryotes. Annu Rev Genet 41: 465-507. PubMed
Heinicke S, Livstone MS, Lu C, Oughtred R, Kang F, Angiuoli SV, White O, Botstein D, Dolinski K. (2007) The Princeton Protein Orthology Database (P-POD): A comparative genomics analysis tool for biologists. PLoS ONE 2: e766. PubMed
Pelham RJ, Rodgers L, Hall I, Lucito R, Nguyen KC, Navin N, Hicks J, Mu D, Powers S, Wigler M, Botstein D. (2006) Identification of alterations in DNA copy number in host stromal cells during tumor progression. Proc Natl Acad Sci 103: 19848-19853. PubMed
Hess DC, Lu W, Rabinowitz JD, Botstein D. (2006) Ammonium toxicity and potassium limitation in yeast. Ammonium toxicity and potassium limitation in yeast. PLoS Biol 4: e351. PubMed
Brauer MJ, Yuan J, Bennett BD, Lu W, Kimball E, Botstein D, Rabinowitz JD. (2006) Conservation of the metabolomic response to starvation across two divergent microbes. Proc Natl Acad Sci 103: 19302-19307. PubMed
Wingreen N, Botstein D. (2006) Back to the future: education for systems-level biologists. Nat Rev Mol Cell Biol 7: 829-832. PubMed
Dolinski K, Botstein D. (2006) Changing perspectives in yeast research nearly a decade after the genome sequence. Genome Res 15: 1611-1619. PubMed
Wang W, Cherry JM, Nochomovitz Y, Jolly E, Botstein D, Li H. (2005) Inference of combinatorial regulation in yeast transcriptional networks: a case study of sporulation. Proc Natl Acad Sci USA 102: 1998-2003. PubMed
Brauer MJ, Saldanha AJ, Dolinski K, Botstein D. (2005) Homeostatic adjustment and metabolic remodeling in glucose-limited yeast cultures. Mol Biol Cell 16: 2503-2517. PubMed
Saldanha AJ, Brauer MJ, Botstein D. (2004) Nutritional homeostasis in batch and steady-state culture of yeast. Mol Biol Cell 15: 4089-4104. PubMed
Bialek W, Botstein D. (2004) Introductory science and mathematics education for 21st-Century biologists. Science 303: 788-790. PubMed
Botstein D, Risch N. (2003) Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat Genet 33 Suppl: 228-237. PubMed
Alter O, Brown PO, Botstein D. (2003) Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms. Proc Natl Acad Sci USA 100: 3351-3356. PubMed
Whitfield ML, Sherlock G, Saldanha AJ, Murray JI, Ball CA, Alexander KE, Matese JC, Perou CM, Hurt MM, Brown PO, Botstein D. (2002) Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell 13: 1977-2000. PubMed
Dunham MJ, Badrane H, Ferea T, Adams J, Brown PO, et al. (2002) Characteristic genome rearrangements in experimental evolution of Saccharomyces cerevisiae. Proc Natl Acad Sci 99: 16144-16149. PubMed