Universal Epistasis Analysis
NEWS AND VIEWS
lates many processes (including planar cell The finding that the primary cilia–basal 5. Morgan, D. et al. Hum. Genet. 110, 377–384 (2002). polarity, cell migration and mitotic spindle body–centrosomal complex regulates non- 6. Nurnberger, J., Bacallao, R.L. & Phillips, C.L. Mol. orientation) whose coordinated activity is likely canonical Wnt signaling might explain how Biol. Cell 13, 3096–3106 (2002). to be essential for proper tubular morphol- the various genes implicated in cystic kidney 7. Logan, C.Y. & Nusse, R. Ann. Rev. Cell Dev. Biol. 20, 781–810 (2004). ogy. Therefore, it is tempting to speculate that disease regulate tubular morphology. Although 8. Veeman, M.T., Axelrod, J.D. & Moon, R.T. Dev. Cell 5, noncanonical Wnt signaling helps to ensure many key elements remain to be discovered, 367–377 (2003). 9. Perantoni, A.O. Sem. Cell Dev. Biol. 14, 201–208 that renal tubules (and perhaps other tubular Simons et al. have written an exciting chapter (2003). structures) lengthen along their longitudinal in this rapidly evolving story. 10. Schwarz-Romond, T. et al. Genes Dev. 16, 2073–2084 axis rather than expand circumferentially dur- (2002). 11. Praetorius, H.A. & Spring, K.R. J. Membr. Biol. 184, ing development (Fig. 2). In postdevelopmen- 1. Simons, M. et al. Nat. Genet. 37, 537–543 71–79 (2001). tal tissues, this pathway might help to maintain (2005). 12. Watanabe, D. et al. Development 130, 1725–1734 2. Mochizuki, T. et al. Nature 395, 177–181 (1998). (2003). the cellular orientation of individual cells in the 3. Morgan, D. et al. Nat. Genet. 20, 149–155 (1998). 13. Maretto, S. et al. Proc. Natl. Acad. Sci. USA 100, tubule. 4. Otto, E.A. et al. Nat. Genet. 34, 413–420 (2003). 3299–3304 (2003).
Universal epistasis analysis
Timothy R Hughes
http://www.nature.com/naturegenetics Epistasis analysis is a foundation in the analysis of genetic networks, but in complex or poorly defined processes, defining the phenotype can be an insurmountable hurdle. A new study shows that microarray expression profiles can be used as a ‘phenotype’ for epistasis analysis of the development of a multicellular organism, offering a potentially universal solution to this problem.
The concept of epistasis was introduced a series of such studies. In more complicated physiological roles. The question arises: nearly 100 years ago1 and today underpins pathways, however, evaluation of epistasis what is the relevant assay to gauge epistatic our interpretation of genetic pathways. If a can be more difficult. For instance, in devel- interactions? On page 471 of this issue3, Van mutation in one gene masks the effects of a opment of multicellular organisms, there Driessche et al. provide a possible solution by mutation in a second gene, then the first gene are many mutations with pleiotropic effects, presenting evidence that global gene expres- is said to be epistatic to the second. Because some of which are hard to quantify objec- sion measurements can serve as a generic 2005 Nature Publishing Group Group 2005 Nature Publishing
© individual gene products often have discrete tively, and many genes with poorly defined phenotype for epistasis analysis. functions in a sequential process or pathway, the simplest interpretation is that the prod- uct of the first gene acts downstream of the #ELL SURFACE ' PROTEIN 3CAFFOLD 4RANSCRIPTION A +INASE +INASE product of the second gene. For example, RECEPTOR B SUBUNIT PROTEIN FACTOR the budding yeast mating response (Fig. 1a) is determined by a pathway of hormones, 3TE 3TE 3TE 3TE 3TE 3TE receptors, adaptors and kinases that culmi- nates in the activation of a program of gene expression. The sterile or STE mutants have defects in the mating pathway, and all have B "INDS AND INHIBITS a similar sterile phenotype. A constitutively +INASE THAT NEGATIVELY TRANSLATION OF PKA# active allele of STE11 is epistatic to STE4 REGULATES CELL GROWTH and STE5 mutants, implying that STE11 is AND PUF! PUF! downstream of STE4 and STE5. In contrast, YAK! mutations in STE7 and STE12 are epistatic to !DENYLATE CYCLASE PKA# $EVELOPMENT STE11, implying that they are downstream of PROMOTES DEVELOPMENT ACA! #ATALYTIC SUBUNIT OF STE11 (ref. 2; Fig. 1a). The order of the entire BY SYNTHESIZING C!-0 PKA2 PROTEIN KINASE ! signaling pathway was largely determined by REG! "INDS AND INACTIVATES PKA# 0HOSPHODIESTERASE Timothy R. Hughes is at the Banting and DISSOCATED BY C!-0 DEGRADES C!-0 Best Department of Medical Research at the Katie Ris University of Toronto, Toronto, Ontario M5G Figure 1 Ordering pathways using epistasis analysis. Schematic representations of (a) the yeast mating 1L6, Canada. pathway and (b) the D. discoideum PKA developmental pathway (modified from refs. 2, 3, 7 and 8). e-mail: [email protected] Comparisons of double and versus single mutants made by Van Driessche et al. are circled.
NATURE GENETICS | VOLUME 37 | NUMBER 5 | MAY 2005 457 NEWS AND VIEWS
Expression patterns as phenotypes double versus single mutants are presented: allel functions in addition to the epistatic Microarray expression profiles have been used one (yakA and pufA) is essentially a positive relation, a theme that is not uncommon in previously as a generic surrogate phenotype. control, another (pufA and pkaC) is a pre- signaling pathways. This will undoubtedly In yeast, expression patterns can distinguish dicted epistatic interaction based on biochem- be a complication for future analyses: if the mutants in different functional categories4, istry and a third (regA and pkaR) illustrates microarray is measuring multiple simultane- and in certain types of cancer, the transcript that pathway orientation can be resolved even ous overlapping transcriptional phenotypes, profile can be predictive of clinical proper- when phenotypes of the single mutants are Euclidean distance will defer to the one with ties5. This probably works because the cells very similar. In all three cases, the Euclidean the largest amount of gene activity, which mount specific transcriptional responses to distance (taken over all genes over 13 develop- may differ from one mutant pair to another. the specific defects caused by mutations; in mental time points for each mutant) is closest A related issue is that epistasis is not an entirely cancer, the phenotypes probably result from between the double mutant and the mutant in foolproof method for determining the order mutations that directly perturb transcription the known or expected downstream gene, pro- of gene action, particularly when partial-func- factors. In the case of signaling pathways with viding evidence that the microarray expression tion alleles, branching pathways or cell-cell a transcriptional output, expression analysis profile faithfully replicates known epistasis interactions are involved11. has been used to dissect signaling circuitry. In relationships. Perhaps the most important outcome of the the yeast mating pathway, the entire transcrip- Van Driessche et al. study, regardless of techni- tional response to mating factor is completely Challenges ahead cal considerations, is that it opens the door to dependent on STE2 (the receptor) and STE12 The study by Van Driessche et al. also high- similar analyses in other organisms. The cas- (the transcription factor), whereas deletion lights challenges in dissecting genetic networks. cade of events that results in development of of FAR1 (a cell-cycle inhibitor) abrogates the One is that the number of crosses required to mice and humans involves thousands of gene repression of G1 cell-cycle related transcripts fully resolve all pathway relationships is large: products working in concert, many of which but not induction of mating genes, showing in the six-gene PKA network, there are fifteen seem to be transcription factors. These are
http://www.nature.com/naturegenetics that it is downstream of STE12 (ref. 6). possible double-mutant combinations. Only almost certainly arranged into pathways that The study by Van Driessche et al. represents three were analyzed, and consequently, the full can begin to be dissected by epistasis analysis an advance in that it uses transcription profiles epistatic network cannot be recreated auto- with a microarray readout. to produce a series of phenotypic comparisons matically, although it can now be inferred by 1. Bateson, W. Mendel’s Principles of Heredity (Cambridge of single versus double mutants in a signal- conventional reasoning and incorporation of University Press, Cambridge, 1909). ing pathway. Moreover, it shows that epistasis existing knowledge. Presumably, the complete 2. Cairns, B.R., Ramer, S.W. & Kornberg, R.D. Genes Dev. analysis using microarray expression profiling structure could be determined automatically 6, 1305–1318 (1992). 3. Van Driessche, N. et al. Nat. Genet. 37, 471–477 as the phenotype can be applied to analyze with fewer than fifteen crosses, if the appro- (2005). the development of a multicellular organism priate alleles were available. The authors have 4. Hughes, T.R. et al. Cell 102, 109–126 (2000). (Dictoystelium discoideum). The study focuses published automated approaches for inter- 5. Liotta, L. & Petricoin, E. Nat. Rev. Genet. 1, 48–56 (2000). on the protein kinase A (PKA) signaling path- pretation and design of conventional epistasis 6. Roberts, C.J. et al. Science 287, 873–880 (2000). way, required for a developmental program experiments9,10 and propose to do the same for 7. Loomis, W.F. Microbiol. Mol. Biol. Rev. 62, 684–694 that results in cell aggregation and formation microarray epistasis analysis. (1998). 2005 Nature Publishing Group Group 2005 Nature Publishing 8. Harwood, A.J. et al. Dev. Biol. 149, 90–99 (1992). 7,8
© of a fruiting body (Fig. 1b). The genetics of The authors also observed that the tran- 9. Zupan, B. et al. Artif. Intell. Med. 29, 107–130 the pathway have been studied previously, but scription profiles usually contained a subset (2003). 10. Zupan, B. et al. Bioinformatics 19, 383–389 (2003). not all of the pathway relationships have been of genes that defied the main epistatic trend. 11. Avery, L. & Wasserman, S. Trends Genet. 8, 312–316 completely resolved9. Three comparisons of They propose that these genes represent par- (1992).
Mutation accumulation of the transcriptome
Greg Gibson
A microarray-based study of the nematode Caenorhabditis elegans offers a first glimpse of the effect of mutation accumulation on transcriptional variation. One major conclusion is that stabilizing selection must constrain the divergence of gene expression profiles in natural populations.
Mutation is the quantum force of genetics. ary trajectories. The classical approach to gene expression) leads to direct estimation of Its effects are too small to measure by direct measuring the effect of mutation is the study the per-generation impact of mutations, and observation, yet it is one of the two or three of mutation accumulation lines1. A highly comparison with natural populations allows most potent forces contributing to evolution- inbred, genetically uniform isogenic line is inference of the impact of stabilizing selec- split into tens of replicate lines, and these are tion on phenotypic constraint (Fig. 1). On Greg Gibson is in the Department of Genetics, allowed to diverge genetically owing to the page 544 of this issue, Dee Denver and col- North Carolina State University, Raleigh, North input of new mutations for several hundred leagues2 describe mutational accumulation in Carolina 27695-7614, USA. generations. Monitoring the rate of genetic the transcriptome and its implications for the e-mail: [email protected] divergence among lines for a trait (such as evolution of gene expression.
458 VOLUME 37 | NUMBER 5 | MAY 2005 | NATURE GENETICS