Multiple large-scale analyses in yeast implicate SUMO chain function in the maintenance of higher-order chromatin structure and transcriptional repression of environmental stress response genes.
Like ubiquitin, the small ubiquitin-related modifier (SUMO) proteins can form oligomeric “chains,” but the biological functions of these superstructures are not well understood. Here, we created mutant yeast strains unable to synthesize SUMO chains (smt3allR) and subjected them to high-content microscopic screening, synthetic genetic array (SGA) analysis, and high-density transcript profiling to perform the first global analysis of SUMO chain function. This comprehensive assessment identified 144 proteins with altered localization or intensity in smt3allR cells, 149 synthetic genetic interactions, and 225 mRNA transcripts (primarily consisting of stress- and nutrient-response genes) that displayed a >1.5-fold increase in expression levels. This information-rich resource strongly implicates SUMO chains in the regulation of chromatin. Indeed, using several different approaches, we demonstrate that SUMO chains are required for the maintenance of normal higher-order chromatin structure and transcriptional repression of environmental stress response genes in budding yeast.
Synthetic genetic array (SGA) analysis automates yeast genetics, enabling high-throughput construction of ordered arrays of double mutants. Quantitative colony sizes derived from SGA analysis can be used to measure cellular fitness and score for genetic interactions, such as synthetic lethality. Here we show that SGA colony sizes also can be used to obtain global maps of meiotic recombination because recombination frequency affects double-mutant formation for gene pairs located on the same chromosome and therefore influences the size of the resultant double-mutant colony. We obtained quantitative colony size data for ~1.2 million double mutants located on the same chromosome and constructed a genome-scale genetic linkage map at ~5 kb resolution. We found that our linkage map is reproducible and consistent with previous global studies of meiotic recombination. In particular, we confirmed that the total number of crossovers per chromosome tends to follow a simple linear model that depends on chromosome size. In addition, we observed a previously unappreciated relationship between the size of linkage regions surrounding each centromere and chromosome size, suggesting that crossovers tend to occur farther away from the centromere on larger chromosomes. The pericentric regions of larger chromosomes also appeared to load larger clusters of meiotic cohesin Rec8, and acquire fewer Spo11-catalyzed DNA double-strand breaks. Given that crossovers too near or too far from centromeres are detrimental to homolog disjunction and increase the incidence of aneuploidy, our data suggest that chromosome size may have a direct role in regulating the fidelity of chromosome segregation during meiosis.
synthetic genetic array (SGA); genomics; meiosis; recombination; centromere; genetic linkage; chromosome size; double strand breaks; Rec8; Spo11; yeast; Saccharomyces cerevisiae
The mechanisms that dictate nuclear shape are largely unknown. Here we screened the budding yeast deletion collection for mutants with abnormal nuclear shape. A common phenotype was the appearance of a nuclear extension, particularly in mutants in DNA repair and chromosome segregation genes. Our data suggest that these mutations led to the abnormal nuclear morphology indirectly, by causing a checkpoint-induced cell cycle delay. Indeed, delaying cells in mitosis by other means also led to the appearance of nuclear extensions, while inactivating the DNA damage checkpoint pathway in a DNA repair mutant reduced the fraction of cells with nuclear extensions. Formation of a nuclear extension was specific to a mitotic delay, as cells arrested in S or G2 had round nuclei. Moreover, the nuclear extension always coincided with the nucleolus, while the morphology of DNA mass remained largely unchanged. Finally, we found that phospholipid synthesis continues unperturbed when cells delay in mitosis, and inhibiting phospholipid synthesis abolished the formation of nuclear extensions. Our data suggest a mechanism that promotes nuclear envelope expansion during mitosis. When mitotic progression is delayed, cells sequester the added membrane to the nuclear envelope associated with the nucleolus, possibly to avoid disruption of intra-nuclear organization.
Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images. Our analysis is based on 7 biologically interpretable features which are evaluated on automatically identified cells, and whose cell-stage dependency is captured by a continuous model for cell growth. We show that it is possible to identify most previously identified localization patterns in a cluster analysis based on these features and that similarities between the inferred expression patterns contain more information about protein function than can be explained by a previous manual categorization of subcellular localization. Furthermore, the inferred cell-stage associated to each fluorescence measurement allows us to visualize large groups of proteins entering the bud at specific stages of bud growth. These correspond to proteins localized to organelles, revealing that the organelles must be entering the bud in a stereotypical order. We also identify and organize a smaller group of proteins that show subtle differences in the way they move around the bud during growth. Our results suggest that biologically interpretable features based on explicit models of cell morphology will yield unprecedented power for pattern discovery in high-resolution, high-throughput microscopy images.
The location of a particular protein in the cell is one of the most important pieces of information that cell biologists use to understand its function. Fluorescent tags are a powerful way to determine the location of a protein in living cells. Nearly a decade ago, a collection of yeast strains was introduced, where in each strain a single protein was tagged with green fluorescent protein (GFP). Here, we show that by training a computer to accurately identify the buds of growing yeast cells, and then making simple fluorescence measurements in context of cell shape and cell stage, the computer could automatically discover most of the localization patterns (nucleus, cytoplasm, mitochondria, etc.) without any prior knowledge of what the patterns might be. Because we made the same, simple measurements for each yeast cell, we could compare and visualize the patterns of fluorescence for the entire collection of strains. This allowed us to identify large groups of proteins moving around the cell in a coordinated fashion, and to identify new, complex patterns that had previously been difficult to describe.
Screening genome-wide sets of mutants for fitness defects provides a simple but powerful approach for exploring gene function, mapping genetic networks and probing mechanisms of drug action. For yeast and other microorganisms with global mutant collections, genetic or chemical-genetic interactions can be effectively quantified by growing an ordered array of strains on agar plates as individual colonies, and then scoring the colony size changes in response to a genetic or environmental perturbation. To do so, requires efficient tools for the extraction and analysis of quantitative data. Here, we describe SGAtools (http://sgatools.ccbr.utoronto.ca), a web-based analysis system for designer genetic screens. SGAtools outlines a series of guided steps that allow the user to quantify colony sizes from images of agar plates, correct for systematic biases in the observations and calculate a fitness score relative to a control experiment. The data can also be visualized online to explore the colony sizes on individual plates, view the distribution of resulting scores, highlight genes with the strongest signal and perform Gene Ontology enrichment analysis.
The Bck2 protein is a potent genetic regulator of cell-cycle-dependent gene expression in budding yeast. To date, most experiments have focused on assessing a potential role for Bck2 in activation of the G1/S-specific transcription factors SBF (Swi4, Swi6) and MBF (Mbp1, Swi6), yet the mechanism of gene activation by Bck2 has remained obscure. We performed a yeast two-hybrid screen using a truncated version of Bck2 and discovered six novel Bck2-binding partners including Mcm1, an essential protein that binds to and activates M/G1 promoters through Early Cell cycle Box (ECB) elements as well as to G2/M promoters. At M/G1 promoters Mcm1 is inhibited by association with two repressors, Yox1 or Yhp1, and gene activation ensues once repression is relieved by an unknown activating signal. Here, we show that Bck2 interacts physically with Mcm1 to activate genes during G1 phase. We used chromatin immunoprecipitation (ChIP) experiments to show that Bck2 localizes to the promoters of M/G1-specific genes, in a manner dependent on functional ECB elements, as well as to the promoters of G1/S and G2/M genes. The Bck2-Mcm1 interaction requires valine 69 on Mcm1, a residue known to be required for interaction with Yox1. Overexpression of BCK2 decreases Yox1 localization to the early G1-specific CLN3 promoter and rescues the lethality caused by overexpression of YOX1. Our data suggest that Yox1 and Bck2 may compete for access to the Mcm1-ECB scaffold to ensure appropriate activation of the initial suite of genes required for cell cycle commitment.
Cell-cycle-dependent gene expression is a universal feature of cell cycles, with clear transcriptional programs in yeast, bacteria, and metazoans. At the M/G1 transition, many of the up-regulated genes encode key regulators of DNA replication (CDC6) and cyclins that initiate the events of cell cycle commitment (PCL9, CLN3). The promoters of genes activated at M/G1 contain a cis-regulatory sequence called the early cell cycle box (ECB), which is bound by the MADS-box transcription factor Mcm1, as well as the repressor Yox1 or Yhp1. The ECB cluster of genes defines a crucial cell cycle window during which a cell may change its fate; yet how the regulators that appear to act at ECBs are linked to cell cycle position is unclear, and coregulators, which experience tells us must exist, were unknown. Here, we describe our discovery that Bck2, a potent cell-cycle-regulator whose function has remained obscure, functions as a cofactor for Mcm1, to induce ECB–dependent gene expression. We also show that Bck2 has a role in promoting expression of late G1 and M/G2 genes. Our genetic and biochemical experiments reveal a new pathway for regulating gene expression associated with early cell cycle commitment, a process that is highly conserved.
Systematic analysis of gene overexpression phenotypes provides an insight into gene function, enzyme targets, and biological pathways. Here, we describe a novel functional genomics platform that enables a highly parallel and systematic assessment of overexpression phenotypes in pooled cultures. First, we constructed a genome-level collection of ~5100 yeast barcoder strains, each of which carries a unique barcode, enabling pooled fitness assays with a barcode microarray or sequencing readout. Second, we constructed a yeast open reading frame (ORF) galactose-induced overexpression array by generating a genome-wide set of yeast transformants, each of which carries an individual plasmid-born and sequence-verified ORF derived from the Saccharomyces cerevisiae full-length EXpression-ready (FLEX) collection. We combined these collections genetically using synthetic genetic array methodology, generating ~5100 strains, each of which is barcoded and overexpresses a specific ORF, a set we termed “barFLEX.” Additional synthetic genetic array allows the barFLEX collection to be moved into different genetic backgrounds. As a proof-of-principle, we describe the properties of the barFLEX overexpression collection and its application in synthetic dosage lethality studies under different environmental conditions.
barFLEX array; gene overexpression; barcoders; synthetic dosage lethality
In parallel with evolutionary developments, the Hsp90 molecular chaperone system shifted from a simple prokaryotic factor into an expansive network that includes a variety of cochaperones. We have taken high-throughput genomic and proteomic approaches to better understand the abundant yeast p23 cochaperone Sba1. Our work revealed an unexpected p23 network that displayed considerable independence from known Hsp90 clients. Additionally, our data uncovered a broad nuclear role for p23, contrasting with the historical dogma of restricted cytosolic activities for molecular chaperones. Validation studies demonstrated that yeast p23 was required for proper Golgi function, ribosome biogenesis and was necessary for efficient DNA repair from a wide range of mutagens. Notably, mammalian p23 had conserved roles in these pathways as well as being necessary for proper cell mobility. Taken together, our work demonstrates that the p23 chaperone serves a broad physiological network and functions both in conjunction with and sovereign to Hsp90.
Synthetic genetic interactions have recently been mapped on a genome scale in the budding yeast Saccharomyces cerevisiae, providing a functional view of the central processes of eukaryotic life. Currently, comprehensive genetic interaction networks have not been determined for other species, and we therefore sought to model conserved aspects of genetic interaction networks in order to enable the transfer of knowledge between species.
Using a combination of physiological and evolutionary properties of genes, we built models that successfully predicted the genetic interaction degree of S. cerevisiae genes. Importantly, a model trained on S. cerevisiae gene features and degree also accurately predicted interaction degree in the fission yeast Schizosaccharomyces pombe, suggesting that many of the predictive relationships discovered in S. cerevisiae also hold in this evolutionarily distant yeast. In both species, high single mutant fitness defect, protein disorder, pleiotropy, protein-protein interaction network degree, and low expression variation were significantly predictive of genetic interaction degree. A comparison of the predicted genetic interaction degrees of S. pombe genes to the degrees of S. cerevisiae orthologs revealed functional rewiring of specific biological processes that distinguish these two species. Finally, predicted differences in genetic interaction degree were independently supported by differences in co-expression relationships of the two species.
Our findings show that there are common relationships between gene properties and genetic interaction network topology in two evolutionarily distant species. This conservation allows use of the extensively mapped S. cerevisiae genetic interaction network as an orthology-independent reference to guide the study of more complex species.
We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future.
Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (~45%) of the 1,101 essential yeast genes, with ~30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)–based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes.
Intense experimental and theoretical efforts have been made to globally map genetic interactions, yet we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we: i) quantitatively measure genetic interactions between ~185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii) superpose the data on a detailed systems biology model of metabolism, and iii) introduce a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigate the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy, and gene dispensability. Last, we demonstrate the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments.
The clathrin light-chain (LC) N-terminal region interacts with the Sla2/Hip1/Hip1R family of ANTH/talin–like proteins. In vivo evidence shows that LC–Sla2 binding is important for releasing Sla2 attachments to actin in the endocytic coat. Loss of this regulation can suppress major actin defects during endocytosis.
The role of clathrin light chain (CLC) in clathrin-mediated endocytosis is not completely understood. Previous studies showed that the CLC N-terminus (CLC-NT) binds the Hip1/Hip1R/Sla2 family of membrane/actin–binding factors and that overexpression of the CLC-NT in yeast suppresses endocytic defects of clathrin heavy-chain mutants. To elucidate the mechanistic basis for this suppression, we performed synthetic genetic array analysis with a clathrin CLC-NT deletion mutation (clc1-Δ19-76). clc1-Δ19-76 suppressed the internalization defects of null mutations in three late endocytic factors: amphiphysins (rvs161 and rvs167) and verprolin (vrp1). In actin sedimentation assays, CLC binding to Sla2 inhibited Sla2 interaction with F-actin. Furthermore, clc1-Δ19-76 suppression of the rvs and vrp phenotypes required the Sla2 actin-binding talin-Hip1/R/Sla2 actin-tethering C-terminal homology domain, suggesting that clc1-Δ19-76 promotes internalization by prolonging actin engagement by Sla2. We propose that CLC directs endocytic progression by pruning the Sla2-actin attachments in the clathrin lattice, providing direction for membrane internalization.
The coordination of cell-cycle events with developmental processes is essential for the reproductive success of organisms. In Drosophila melanogaster, meiosis is tightly coupled to oocyte development, and early embryos undergo specialized S-M mitoses that are supported by maternal products. We previously showed that the small phosphoprotein α-endosulfine (Endos) is required for normal oocyte meiotic maturation and early embryonic mitoses in Drosophila. In this study, we performed a genetic screen for dominant enhancers of endos00003 and identified several genomic regions that, when deleted, lead to impaired fertility of endos00003/+ heterozygous females. We uncovered matrimony (mtrm), which encodes a Polo kinase inhibitor, as a strong dominant enhancer of endos. mtrm126 +/+ endos00003 females are sterile because of defects in early embryonic mitoses, and this phenotype is reverted by removal of one copy of polo. These results provide compelling genetic evidence that excessive Polo activity underlies the strong functional interaction between endos00003 and mtrm126. Moreover, we show that endos is required for the increased expression of Mtrm in mature oocytes, which is presumably loaded into early embryos. These data are consistent with the model that maternal endos antagonizes Polo function in the early embryo to ensure normal mitoses through its effects on Mtrm expression during late oogenesis. Finally, we also identified genomic deletions that lead to loss of viability of endos00003/+ heterozygotes, consistent with recently published studies showing that endos is required zygotically to regulate the cell cycle during development.
α-endosulfine; matrimony; polo; early embryonic cell cycle; Drosophila
Two types of drug synergy, genetic and promiscuous, are explored in S. cerevisiae. The results suggest that promiscuous synergy predominates, and that propensity to synergize is an intrinsic drug property with the potential to accelerate the search for synergistic drug combinations.
Discovered 37 synergistic interactions among antifungal chemicalsPromiscuous synergy is the predominant form of drug synergyRate of synergy is an intrinsic property of drugs that can guide searches for drug synergy
Drug synergy allows a therapeutic effect to be achieved with lower doses of component drugs. Drug synergy can result when drugs target the products of genes that act in parallel pathways (‘specific synergy'). Such cases of drug synergy should tend to correspond to synergistic genetic interaction between the corresponding target genes. Alternatively, ‘promiscuous synergy' can arise when one drug non-specifically increases the effects of many other drugs, for example, by increased bioavailability. To assess the relative abundance of these drug synergy types, we examined 200 pairs of antifungal drugs in S. cerevisiae. We found 38 antifungal synergies, 37 of which were novel. While 14 cases of drug synergy corresponded to genetic interaction, 92% of the synergies we discovered involved only six frequently synergistic drugs. Although promiscuity of four drugs can be explained under the bioavailability model, the promiscuity of Tacrolimus and Pentamidine was completely unexpected. While many drug synergies correspond to genetic interactions, the majority of drug synergies appear to result from non-specific promiscuous synergy.
chemical genetics; drug combinations; drug discovery; genetic interactions
About one-fifth of the genes in the budding yeast are essential for haploid viability and cannot be functionally assessed using standard genetic approaches such as gene deletion. To facilitate genetic analysis of essential genes, we and others have assembled collections of yeast strains expressing temperature-sensitive (ts) alleles of essential genes. To explore the phenotypes caused by essential gene mutation we used a panel of genetically engineered fluorescent markers to explore the morphology of cells in the ts strain collection using high-throughput microscopy. Here, we describe the design and implementation of an online database, PhenoM (Phenomics of yeast Mutants), for storing, retrieving, visualizing and data mining the quantitative single-cell measurements extracted from micrographs of the ts mutant cells. PhenoM allows users to rapidly search and retrieve raw images and their quantified morphological data for genes of interest. The database also provides several data-mining tools, including a PhenoBlast module for phenotypic comparison between mutant strains and a Gene Ontology module for functional enrichment analysis of gene sets showing similar morphological alterations. The current PhenoM version 1.0 contains 78 194 morphological images and 1 909 914 cells covering six subcellular compartments or structures for 775 ts alleles spanning 491 essential genes. PhenoM is freely available at http://phenom.ccbr.utoronto.ca/.
Classical forward genetics has been foundational to modern biology, and has been the paradigm for characterizing the role of genes in shaping phenotypes for decades. In recent years, reverse genetics has been used to identify the functions of genes, via the intentional introduction of variation and subsequent evaluation in physiological, molecular, and even population contexts. These approaches are complementary and whole genome analysis serves as a bridge between the two. We report in this article the whole genome sequencing of eighteen classical mutant strains of Neurospora crassa and the putative identification of the mutations associated with corresponding mutant phenotypes. Although some strains carry multiple unique nonsynonymous, nonsense, or frameshift mutations, the combined power of limiting the scope of the search based on genetic markers and of using a comparative analysis among the eighteen genomes provides strong support for the association between mutation and phenotype. For ten of the mutants, the mutant phenotype is recapitulated in classical or gene deletion mutants in Neurospora or other filamentous fungi. From thirteen to 137 nonsense mutations are present in each strain and indel sizes are shown to be highly skewed in gene coding sequence. Significant additional genetic variation was found in the eighteen mutant strains, and this variability defines multiple alleles of many genes. These alleles may be useful in further genetic and molecular analysis of known and yet-to-be-discovered functions and they invite new interpretations of molecular and genetic interactions in classical mutant strains.
single nucleotide polymorphism; SNP; indel; comparative genomics; classical mutant
The quantification of spontaneous mutation rates is crucial for a mechanistic understanding of the evolutionary process. In bacteria, traditional estimates using experimental or comparative genetic methods are prone to statistical uncertainty and consequently estimates vary by over one order of magnitude. With the advent of next-generation sequencing, more accurate estimates are now possible. We sequenced 19 Escherichia coli genomes from a 40,000-generation evolution experiment and directly inferred the point-mutation rate based on the accumulation of synonymous substitutions. The resulting estimate was 8.9 × 10−11 per base-pair per generation, and there was a significant bias toward increased AT-content. We also compared our results with published genome sequence datasets for other bacterial evolution experiments. Given the power of our approach, our estimate represents the most accurate measure of bacterial base-substitution rates available to date.
genomic base-substitution rate; experimental evolution; molecular evolution; mutation pressure; next-generation sequencing
In telomerase-deficient yeast cells, like equivalent mammalian cells, telomeres shorten over many generations until a period of senescence/crisis is reached. After this, a small fraction of cells can escape senescence, principally using recombination-dependent mechanisms. To investigate the pathways that affect entry into and recovery from telomere-driven senescence, we combined a gene deletion disrupting telomerase (est1Δ) with the systematic yeast deletion collection and measured senescence characteristics in high-throughput assays. As expected, the vast majority of gene deletions showed no strong effects on entry into/exit from senescence. However, around 200 gene deletions behaving similarly to a rad52Δest1Δ archetype (rad52Δ affects homologous recombination) accelerated entry into senescence, and such cells often could not recover growth. A smaller number of strains similar to a rif1Δest1Δ archetype (rif1Δ affects proteins that bind telomeres) accelerated entry into senescence but also accelerated recovery from senescence. Our genome-wide analysis identifies genes that affect entry into and/or exit from telomere-initiated senescence and will be of interest to those studying telomere biology, replicative senescence, cancer, and ageing. Our dataset is complementary to other high-throughput studies relevant to telomere biology, genetic stability, and DNA damage responses.
telomere; Saccharomyces cerevisiae; senescence; crisis
Despite the ecological and economic importance of lignin and other wood chemical components, there are few studies of the natural genetic variation that exists within plant species and its adaptive significance. We used models developed from near infra-red spectroscopy to study natural genetic variation in lignin content and monomer composition (syringyl-to-guaiacyl ratio [S/G]) as well as cellulose and extractives content, using a 16-year-old field trial of an Australian tree species, Eucalyptus globulus. We sampled 2163 progenies of 467 native trees from throughout the native geographic range of the species. The narrow-sense heritability of wood chemical traits (0.25–0.44) was higher than that of growth (0.15), but less than wood density (0.51). All wood chemical traits exhibited significant broad-scale genetic differentiation (QST = 0.34–0.43) across the species range. This differentiation exceeded that detected with putatively neutral microsatellite markers (FST = 0.09), arguing that diversifying selection has shaped population differentiation in wood chemistry. There were significant genetic correlations among these wood chemical traits at the population and additive genetic levels. However, population differentiation in the S/G ratio of lignin in particular was positively correlated with latitude (R2 = 76%), which may be driven by either adaptation to climate or associated biotic factors.
tree improvement; wood chemicals; adaptation; lignin; cellulose; extractives; syringyl; guaiacyl
Plant root systems must grow in a manner that is dictated by endogenous genetic pathways, yet sensitive to environmental input. This allows them to provide the plant with water and nutrients while navigating a heterogeneous soil environment filled with obstacles, toxins, and pests. Gravity and touch, which constitute important cues for roots growing in soil, have been shown to modulate root architecture by altering growth patterns. This is illustrated by Arabidopsis thaliana roots growing on tilted hard agar surfaces. Under these conditions, the roots are exposed to both gravity and touch stimulation. Consequently, they tend to skew their growth away from the vertical and wave along the surface. This complex growth behavior is believed to help roots avoid obstacles in nature. Interestingly, A. thaliana accessions display distinct growth patterns under these conditions, suggesting the possibility of using this variation as a tool to identify the molecular mechanisms that modulate root behavior in response to their mechanical environment. We have used the Cvi/Ler recombinant inbred line population to identify quantitative trait loci that contribute to root skewing on tilted hard agar surfaces. A combination of fine mapping for one of these QTL and microarray analysis of expression differences between Cvi and Ler root tips identifies a region on chromosome 2 as contributing to root skewing on tilted surfaces, potentially by modulating cell wall composition.
Arabidopsis; root; skewing; waving; cis-prenyltransferase