Genetics: Published Articles Ahead of Print, published on February 1, 2008 as 10.1534/genetics.107.084103

Heterozygous Screen in Identifies Dosage Sensitive

that Impact Stability

Erin D. Strome*,† , Xiaowei Wu‡, Marek Kimmel‡and Sharon E. Plon†, §

Cell and Molecular Biology *, Texas Children’s Cancer Center†, Department of

Pediatrics§, Baylor College of Medicine; Department of Statistics, Rice University‡; All

in Houston, TX

1 Running Head: Yeast Chromosome Stability Screen

Key Words/Phrases: Haploinsufficiency, Chromosome Stability, Low-penetrance and

Modifier Alleles, Cancer Susceptibility, COMA kinetochore complex

Contact Information: [email protected]

Corresponding author: Dr. Sharon Plon MC3-3320 6621 Fannin Street Houston, TX 77030 832-824-2451 832-825-4726 [email protected]

2 ABSTRACT

Current techniques for identifying mutations that convey small increased cancer risk or those that modify cancer risk in carriers of highly penetrant mutations are limited by the statistical power of epidemiologic studies, which require screening of large populations and candidate genes. To identify dosage sensitive genes that mediate genomic stability, we performed a genome-wide screen in Saccharomyces cerevisiae for heterozygous mutations which increase chromosome instability in a checkpoint-deficient diploid strain. We used two genome stability assays sensitive enough to detect the impact of heterozygous mutations and identified 172 heterozygous disruptions which effected chromosome fragment (CF) loss, 45% of which also conferred modest but statistically significant instability of endogenous . Analysis of heterozygous deletion of 65 of these genes demonstrated increased genomic instability in both checkpoint deficient and wild-type backgrounds. Strains heterozygous for COMA kinetochore complex genes were particularly unstable. Over 50% of the genes identified in this screen have putative human homologs including CHEK2, ERCC4, and TOPBP1 which are already associated with inherited cancer susceptibility. These findings encourage the incorporation of this orthologous gene list into cancer epidemiology studies and suggest further analysis of heterozygous phenotypes in yeast as models of human disease resulting from haploinsufficiency.

3 INTRODUCTION

Cancers are commonly characterized as having an abnormal number of chromosomes, termed aneuploidy, which arises due to genomic instability. Aneuploidy has been proposed as a mutagenic mechanism and a driving force of tumor progression and not just a phenotype of the disease (WEAVER and CLEVELAND 2006). Many of the genes whose disruption results in aneuploidy were first identified in budding yeast based on analysis of haploid strains containing null mutations. Aneuploidy can be caused by inherited or somatic mutations in genes that function in the maintenance of genomic stability, such as those involved in centrosome formation, chromosome metabolism and cell cycle checkpoints. Among these, cell cycle checkpoint pathways play an especially important role in maintaining genomic integrity when cells are challenged with genotoxic agents or other stressors (ZHOU and ELLEDGE 2000).

Mutations in checkpoint genes including, BRCA1, PTEN, ATM and CHEK2, lead to increases in breast cancer susceptibility (LI et al. 1997; NATHANSON and WEBER 2001;

MEIJERS-HEIJBOER et al. 2002; KING et al. 2003). Women who inherit BRCA1 mutations have an increased lifetime breast cancer risk of 50-80% (12% risk in the general population) and an ovarian cancer risk of 15-65% (1.5% risk in the general population).

However, the age of cancer onset, type and number of cancers can vary, even among women carrying the same mutation. One mechanism for this variation is the presence of unlinked genetic loci, which modify this risk (REBBECK 2002). For instance, ovarian cancer risk in BRCA1 carriers is influenced by specific alleles of a VNTR (Variable Number of

Tandem Repeats) polymorphism in HRAS1 (PHELAN et al. 1996).

4 Current methods to identify genetic modifiers and low-penetrant alleles for cancer susceptibility require large patient cohorts and are limited by the statistical power of epidemiologic studies (CHENEVIX-TRENCH et al. 2007). New approaches that are unbiased and comprehensive in their search for genes modulating genomic stability and putatively cancer development are needed.

Conservation of the spindle, DNA replication and DNA damage pathways between humans and Saccharomyces cerevisiae has been well documented allowing for use of this model organism in studies focused on control of genomic stability (ELLEDGE

1996). However, the majority of yeast genetic screens have focused on null mutations in haploid strains, restricting analysis to nonessential genes. In contrast, cancer susceptibility is often seen in heterozygous mutation carriers; however screens for the impact of haploinsufficiency in a diploid setting have not been extensively explored.

Here we perform a genome-wide heterozygous screen in S. cerevisiae in order to identify haploinsufficient mutations that result in modest increases in genomic instability, as a novel strategy for the identification of candidate cancer susceptibility and modifier loci in humans.

5 MATERIALS AND METHODS

Strains and Assay Markers: Parental strains were made by mating DVL142-35B to

HKY965-12B, kind gifts from Vicki Lundblad and Hannah Klein respectively, and followed by dissection, genotyping and recreation of desired strains (KLEIN 2001). The chromosome fragment (CF) used in this screen was originally created and provided by

Phil Hieter (personal communication). ES75: rad9∆/rad9∆, leu2-3/leu2-3, his3-

∆200/his3-∆200, trp1-∆1/trp1-∆1, lys2-801/LYS2, ura3-52/ura3-52, can1-100/CAN1, ade2-101/ade2-101, 2X (CF:[ura3::TRP1, SUP11, CEN4, D8B]) ES76: leu2-3/leu2-3, his3-∆200/his3-∆200, trp1-∆1/trp1-∆1, lys2-801/LYS2, ura3-52/ura3-52, can1-

100/CAN1, ade2-101/ade2-101, 2X (CF:[ura3::TRP1, SUP11, CEN4, D8B]).

Insertional Mutagenesis: Heterozygous mutations were created using the mTn- lacZ/LEU2-mutagenized library (KUMAR et al. 2002). Briefly, the mTn-lacZ/LEU2 library was received as DNA pools which were amplified using E. coli and then NotI excised from the bacterial vector and transformed into ES75 yeast cultures via the lithium acetate

+ method (GIETZ and WOODS 2006). Leu transformants were then struck-out onto 1/8 of a low adenine concentration plate (6ug/ml) which allowed visualization of ~185 single colonies per insertionally mutagenized strain. After growth for 3 days at 30o and 1 night at 4o (for color development) colonies were examined for the appearance of pink/red sectors by one observer. Sectors arise due to loss of a chromosome fragment (CF), which harbors a SUP11 ochre suppressing tRNA responsible for suppression of the homozygous ade2-101 ochre mutation that causes yeast to be red due to build-up of adenine precursors. S. cerevisiae containing two copies of the CF are white, one copy pink and

6 zero copies red. The use of 2 CFs in the parental strain enabled us to more easily identify pink and red sectors on a white colony background. A positive sectoring phenotype was set at four or more sectors among the ~185 colonies inspected compared with on average

0.5 sectors in a similar number of the rad9∆⁄rad9∆ parental strain (p value of < 0.001 compared with parental rate). Fully pink or red colonies were not counted as sectored colonies.

Fluctuation Analysis: Estimation of Chromosome V instability rate via Method of the Median: Chromosome V instability rate was measured as conversion of a heterozygous can1-100/CAN1 strain to canavanine resistance using a modification of the method described in Klein (KLEIN 2001). Strains were struck-out so that colonies arose from single cells and were allowed to grow for 3 days at 30o. Twenty-four separate colonies per strain were then chosen and dispersed in 200 µl of water each in 96 well plates. Absorbance was measured using the Tecan Spectroflour Plus at 620 nm, and the fifteen colonies with the closest optical densities were used for analysis. The canavanine resistant (k) and viable numbers of cells (N) in each colony were determined by plating the appropriate dilution on SC-Arg- plus canavanine at 60 µg/ml and non-selective (YPD) plates respectively. Plates were grown for 3 days at 30o, and then colonies were counted using the aCOLyte SuperCount Colony Counter. Chromosome V instability rates were calculated using fluctuation analysis and a modification of the Lea and Couslon Method of the Median (LEA and COULSON 1949). To accommodate variations in N, chromosome V instability rate estimates were separately computed for the 15 colonies setting the initial cell count N0=1, and utilizing individual N and k values for each colony. A median of

7 these estimates was accepted as a final estimate. Independently, estimates were computed using the Maximum Likelihood Method (ZHENG 2005) modified to accommodate variation in N; estimates from both methods showed less than 10% difference.

Statistical Analysis of Chromosome V Instability Rates: To determine if estimated chromosome V instability rates of mutant strains were different from the parental strain rate, we performed one-sided unequal Behrens-Fisher (LIX et al. 2005) variance t-tests for the estimate chromosome V instability rate of each strain (using the estimated mutation rate data from all parallel cultures) against the estimated parental chromosome V instability rate to test if this rate was smaller.

Transposon Insertion Site Identification: Vectorette PCR and Inverse PCR:

Identification of the site of insertion of the transposon in 300 strains was performed using two different methods, Vectorette PCR and Inverse PCR. The remaining 98 insertional mutants were unidentifiable through extensive rounds of Vectorette and Inverse PCR with different individual restriction enzymes and combinations, and thus were not pursued further. Vectorette PCR methods utilizing RsaI, AluI, and DraI in different experiments were carried out. Briefly genomic DNA was isolated from strains of interest and digested. Anchor bubbles were ligated onto the blunt ends created by use of frequent blunt end cutter restriction enzymes, and PCR was performed utilizing a primer to the anchor bubble and a primer to the mTn-lacZ/LEU2 transposon. 80 µl of the PCR reaction were electrophoresed on a 0.7% TAE gel, and unique bands were gel purified

8 and sequenced using a primer from the transposon. Inverse PCR techniques were then carried out on the remaining strains utilizing RsaI, AluI, DraI, Taq1, HpaII, AciI and

HaeIII restriction enzymes. Genomic DNA was isolated from strains of interest and digested with a single restriction enzyme, ligated at low density, precipitated and used as template DNA for PCR with opposing primers from within the mTn-lacZ/LEU2 transposon. Unique bands were again gel purified, sequenced, and then analyzed against the S. cerevisiae genomic sequence to identify the transposon insertion site.

Gene Ontology Analysis and Interactome Mapping: Annotations were analyzed using the Generic Gene Ontology (GO) Term Mapper

(http://go.princeton.edu/cgi-bin/GOTermMapper) from the Lewis-Sigler Institute for

Integrated Genomics at Princeton University and the S. cerevisiae GO slim gene association files. The p values were calculated using standard Chi-squared tests.

An interactome map of the network of genetic and physical interactions among the 172 unique genes identified was created utilizing the Osprey Visualization System

(BREITKREUTZ et al. 2003). Node colors depict biological process gene ontologies, while edge colors denote the genetic or physical interaction identified.

Creation of Precise Heterozygous Mutations Utilizing KAN-MX Cassette: Precise heterozygous deletions were created for a subset of the genes utilizing the KAN-MX cassette homologous recombination switch-out method (WACH et al. 1994). KAN-MX module deletions for each gene were amplified using PCR on DNA isolated from individual strains from the haploid deletion collection or by Long Flanking Homology

9 techniques. Primers were designed 500-800 bp upstream and downstream of the KAN-

MX cassette to create large areas of homology to facilitate recombination between the deletion cassette and endogenous gene. After amplification, the PCR generated products were transformed into ES75 and ES76 strains, and positive transformants were selected on 200 µg/ml G418 plates. Positive transformants were then checked for proper integration via PCR with a forward primer upstream of the Gene of Interest (GOI) and a reverse primer within the KAN-MX cassette.

Genotoxic Stress Assays: Precise heterozygous deletion strains were tested for sensitivity to phleomycin, MMS (Methyl Methane Sulfanate), hydroxyurea (HU),

Ultraviolet light (UV) and benomyl. Cultures for each strain were grown overnight at 30o to saturation in 96 well plates and then diluted down to 0.2 OD and allowed to double twice. Each assay plate contained two parental controls and 6 tester strains and was spotted in duplicate. Five five-fold serial dilutions were performed, and equal aliquots of each dilution were transferred (frogged) onto three plates per genotoxic stress agent;

Phleomycin 0.1 µg/ml, 0.5 µg/ml and 1 µg/ml; Benomyl 10 µg/ml, 20 µg/ml, and 30

µg/ml; MMS 0.0075%, 0.015% and 0.030%; HU 25 mM, 50 mM and 75 mM; and YPD plates for exposure to UV at 20 J/m2/sec, 30 J/m2/sec and 40 J/m2/sec. After several hours (to allow drying) the plates were inverted and placed at 30o for 3 days. Each plate was photographed and visually analyzed for changes in sensitivity.

10 RESULTS

A genome-wide yeast genetic screen for heterozygous mutations enhancing genome instability: The S. cerevisiae RAD9 gene encodes a putative functional ortholog of mammalian BRCA1, NFBD1 (MDC1) and 53BP1 . All of these proteins contain two BRCT functional domains and function as mediators of the DNA damage checkpoint

(WEINERT and HARTWELL 1990; BORK et al. 1997; RAPPOLD et al. 2001; PENG and CHEN 2003;

PENG and CHEN 2005). We developed this screen in a diploid rad9∆/rad9∆ deficient background to model mammalian checkpoint deficient cells which could potentially lead to identification of specific genetic modifiers of cancer predisposition. In addition, use of the rad9∆/rad9∆ strain background increases the baseline instability of S. cerevisiae strains approximately five to tenfold (WEINERT and HARTWELL 1990; KLEIN 2001). For our specific sectoring assay use of the rad9∆/rad9∆ background raised the absolute instability of the starting strain allowing identification of insertional mutants with only a 3-10 fold increase in sectors. This would not be feasible in a wild-type background where the starting strain demonstrates only 1 sector per 1500 colonies on average.

In order to focus on heterozygous mutations that increase chromosome loss, we developed a diploid parental strain, ES75, which includes the features required for a primary qualitative assay based on the spontaneous loss of a non-essential linear chromosome, referred to as a chromosome fragment (CF), and a secondary quantitative assay which determines the rate of loss or mitotic recombination of a natural endogenous chromosome. The overall screen strategy is depicted in Figure 1. The initial assay measured genome instability through visual assessment of the loss of one or two copies

11 of the CF resulting in pink or red sectors on white colonies due to an inability to synthesize adenine (HIETER et al. 1985).

At the initiation of this study, use of the diploid heterozygous deletion collection was not feasible since this collection did not carry the reporters for chromosome instability or the homozygous rad9 deletion necessary for our screen. Therefore, we decided to use an insertional mutagenesis technique based on the Snyder mTn- lacZ/LEU2-mutagenized library (KUMAR et al. 2002) to create heterozygous insertions potentially disrupting non-essential, essential and novel/uncharacterized genes. As recommended by Snyder, in order to cover approximately 95% of yeast genes with insertions, we visually inspected 30,000 Leu+ mutant strains for a sectoring phenotype.

In the initial screen 1,225 of 30,000 mutant strains met our threshold of having four or more sectors in approximately 185 colonies. To test for reproducibility of the sectoring phenotype, these 1,225 mutant strains were then restruck three additional times.

The mutant strains were then categorized into three groups: 1) 398 insertional mutants, which had four or more sectors in at least three of the four streak-outs; this increased CF loss group represents 1.33% of the 30,000 mutant strains and was carried forward to the next step of the screen; 2) 761 mutant strains which consistently sectored but below the threshold level; and 3) 66 strains which only had sectored colonies on the initial screen.

The increased CF loss group typically demonstrated 4-10 sectors per ~185 colonies, compared with 0-1 in the parental ES75 strain, see Figure 1. This small but significant increase in the number of sectored colonies (p value of <0.001 over parental strain) supports the hypothesis that heterozygous mutations may convey modest changes in genomic stability.

12

Mutant strains with increased chromosome fragment loss also demonstrate instability of an endogenous chromosome: The second assay for genomic instability monitored the endogenous chromosome Vs, one containing the wild-type CAN1 gene conferring sensitivity to canavanine and the second containing the can1-100 recessive allele conferring resistance. Quantitative assessment of conversion to canavanine resistance assessed the combined effects of loss of the endogenous chromosome V containing the wild-type CAN1 gene, mitotic recombination of the CAN1 locus to can1-

100 or point mutation in the CAN1 gene. However, spontaneous point mutations account for only 1-2% of the canavanine resistant mutants (OHNISHI et al. 2004) and thus do not significantly contribute to this assay.

Chromosome V instability was measured by fluctuation analysis using a modification of the Lea and Coulson method of the median (see Materials and Methods)

Five independent estimations of chromosome V instability for the rad9∆/rad9∆ and wild- type strains were performed to show reproducibility of the assay with estimated mutation rates of 3.37E-05 and 7.86E-06 respectively (see Figure 2A). To confirm that the mutant strains exhibiting increased CF loss also had increased instability of chromosome V, we performed fluctuation analysis on 40 of the 398 increased CF loss strains and 10 mutagenized strains which did not show sectored colonies. We performed one-sided unequal variance t-tests (WELCH 1938) on the estimated chromosome V instability rate of each of the strains compared to the estimated rate of the rad9∆/rad9∆ parental strain (see

Figure 2B). We found that 29/40 (72.5%) of the strains from the increased CF loss group showed statistically increased chromosome V instability rates, while none of the ten

13 strains from the non-sectoring group were statistically different from the parental strain.

These data demonstrate that the heterozygous mutants identified in the screen based on increased CF loss are highly enriched for strains that exhibit increased instability of endogenous chromosomes.

Identification of the site of transposon insertion in 300 high CF loss strains: The transposon insertion sites in 300 of the 398 increased CF loss strains were identified using Vectorette and Inverse PCR techniques (see Materials and Methods). Analysis of the 300 insertion sites revealed 172 insertions within previously defined gene coding sequences, which likely disrupt or modify activity of the encoded proteins, 53 insertions in regions that do not contain a previously annotated ORF, and 75 sites that are replicas of those in the previous two groups. See Supplemental Data Table 1, for all identified transposon insertion sites.

We performed analysis of the chromosomal coordinates of the 106 genes with the potential to have promoter regions disrupted by transposon insertions in non-annotated regions. We find that 64 of these genes are in an orientation with their 5’ region adjacent to the insertion site. We searched the limited S. cerevisiae promoter database (ZHU and

ZHANG 1999) for insertions within the promoter region. However, only five of the 64 genes in the correct orientation have documented promoter regions and in only two cases do the insertion sites fall between the promoter region and the transcription start site

(TSS); STE2 and FAS1. However, by mapping the distance to the TSS (basepair 0) for the insertions not in documented promoters, we found that in 28.6% of these cases the

14 insertion site of the transposon was within 250 basepairs of the TSS and may be expected to disrupt transcription (see data in Supplemental Data Table 2).

Notably of the 172 unique gene disruptions, 20% were in essential genes or genes identified only as hypothetical ORFs. Since these two groups are not included in the haploid deletion collection (WINZELER et al. 1999), a substantial portion of genes identified in this screen have not been phenotypically characterized by other investigators employing this collection.

Gene Ontology (GO) annotations and interactome mapping to characterize the 172 unique gene disruptions: We focused on the 172 strains containing unique gene- disrupting insertions given the possible varying impact of the other insertions on gene expression. In order to characterize this large set of insertions, we used Gene Ontology

(GO), a vocabulary of annotated gene assignments into ontologies based on their known biological process, compartment location, or molecular function (ASHBURNER et al. 2000).

We characterized the 172 genes by comparing their ontology representation against the ontology of the entire budding yeast genome. Using GO processes at the 3rd level of complexity, the groups that were statistically significantly over-represented in the biological process division included cell cycle and meiosis; the only under-represented group was biosynthesis (Figure 3A). Of note, all of the genes identified in the meiosis group are also contained in the cell cycle group. The analysis of gene ontology by cellular compartment revealed that chromosome location was over-represented

(Figure 3B). Thus, the non-random nature of this list as well as the over-representation in

15 genes known to be involved in genomic stability further supports the validity of this screen.

For further analysis of the gene list we created an interactome map of the known genetic and physical interactions (Figure 4). Notably 69 of 172 genes had identified interactions with at least one other gene from our list, with the majority of these being genes that mapped to cell cycle, metabolism and DNA repair ontologies. We included

RAD9 on the map and 8 of the genes identified in the screen have previously established genetic or biochemical interactions with RAD9. The YHR135C node shows interactions with 14 other genes/proteins within our list, 13 of which are biochemical activity interactions; however further inquiry shows that YHR135C has biochemical interactions with a total of 285 proteins (Saccharomyces Genome Database http://www.yeastgenome.org/), suggesting it may just represent a “sticky” protein.

Quantifying the genomic instability of increased CF loss mutant strains:

Chromosome V instability assays (as previously described), were performed for all 172 unique gene disruptions found in our set of increased CF loss strains (see Supplemental

Data Table 3). We again performed one-sided unequal variance t-tests for the estimated rate of each unique locus compared to the estimated chromosome V instability rate of the rad9∆/rad9∆ parental strain. In this larger sample we found that 45% of the tested strains have a significantly increased chromosome V instability rate compared to the rad9∆/rad9∆ parental rate of 3.37E-05 and these increases ranged from 3-14 fold.

16 Assays of chromosome instability and rad9-dependence in strains with precise heterozygous deletions of genes identified in the screen: A subset of 65 of the 172 genes with insertions in a coding region were chosen for further characterization based on one of the following criteria: 1) member of over-represented groups from the GO analysis; 2) the seven insertional mutant strains with the highest chromosome V instability rate; 3) novel or newly annotated genes; and 4) essential genes. We used directed gene targeting to make precise heterozygous gene deletions of the coding region in non-mutagenized backgrounds in order to 1) test reproducibility of the phenotype in a non-mutagenized background, 2) eliminate potential hypomorphic effects of the insertion, and 3) test the impact of heterozygous precise deletions in both wild-type and rad9-deficient backgrounds.

Chromosome V instability was determined by fluctuation analysis on these 130 strains (65 precise deletions in both wild-type and rad9∆/rad9∆ backgrounds). As shown in Table 1, the chromosome V instability phenotype was reproducible, with 80% of the reconstructed deletions in a rad9∆/rad9∆ background having an equal (within two-fold) or greater rate then the original insertional mutant strain isolated in the screen.

Surprisingly, 85% of the heterozygous deletions resulted in greater then a two-fold increase in chromosome V instability in a wild-type ES76 background. Thus, these deletions identify dosage sensitive genes that mediate genomic stability independent of

RAD9 status. We further characterized the type of effect with regard to rad9-specificity in

Table 1. Heterozygous deletion of only three genes, sam1∆/SAM1, tma17∆/TMA17 and dml1∆/DML1 demonstrated increases in chromosome V instability rates that were completely rad9–dependent. There were eight heterozygous gene deletions where the

17 impact of combining rad9∆/rad9∆ and the heterozygous deletion resulted in increased instability above a multiplicative effect, and twelve where the level met what would be expected for a simple multiplicative effect. The former group may represent genes that have a synergistic effect on genome instability when combined with a checkpoint deficiency, and the latter group of genes likely causes instability independent of checkpoint deficiencies. The remaining 45 of 65 tested heterozygous gene deletions demonstrated a larger impact in a wild-type versus a rad9∆/rad9∆ parental background.

Unexpectedly, a small group of these genes had significantly more instability in wild- type compared with rad9∆/rad9∆ backgrounds. Notably, a mcm21∆/MCM21 strain has a

500-fold increase in chromosome V instability rate (4.03E-03 chromosome V instability rate, standard deviation 3.49E-03) over the wild-type parental strain. This rate was derived from performing replicate fluctuation analyses of four mcm21∆/MCM21 strains created from independent transformations with the deletion cassette. In contrast, the rad9∆/rad9∆ mcm21∆/MCM21 strain has a rate close to a wild-type level (4.21E-06 chromosome V instability rate, standard deviation 3.48E-06). CF loss results were similar where the sectoring of the mcm21∆/MCM21 strain was much higher than in the rad9∆/rad9∆ mcm21∆/MCM21 strain, although some increase in sectoring still occurred compared to the rad9-deficient starting strain as expected based on the original identification of the insertional mutant in this screen. Thus, although the initial screen was carried out in a rad9∆/rad9∆ strain background, 62 of 65 heterozygous deletions also significantly increased chromosome instability in checkpoint proficient strains.

18 The majority of the heterozygous gene deletion strains do not show changes in the response to exogenous genotoxic stress: The original sectoring and canavanine resistance assays measured spontaneous events. We wanted to determine if these heterozygous mutations also had an impact on the response to exogenous damage.

Sensitivity of the wild-type and rad9∆/rad9∆ strains containing the 65 reconstructed heterozygous deletions to a variety of different genotoxic stresses was tested by exposure to agents including Methyl Methane Sulfonate (MMS), Hydroxyurea (HU), Ultraviolet

Light (UV), Phleomycin, and Benomyl, a microtubule depolymerizing agent. The strains were exposed to three doses of each drug or UV radiation, and viability was measured in a semiquantitative assay.

The majority (65%) of heterozygous mutant strains did not show a change in sensitivity to any of the agents tested. The minority of strains that had altered growth in response to agents is shown in Table 2. This group includes strains with deletions of several genes in which null mutations in haploid or homozygous strains have been previously shown to be sensitive. For example, rad52∆/RAD52 and rad52∆ strains show sensitivity to MMS and UV and both dun1∆/DUN1 and dun1∆ strains are sensitive to

MMS (Table 2 and (BEGLEY et al. 2004)). Our results demonstrate dosage sensitivity of heterozygous mutations for these genes. However, the finding that the majority of heterozygous mutant strains do not demonstrate increased sensitivity to genotoxic stress reinforces that our screen predominantly identified heterozygous mutations that impact spontaneous genomic events distinct from pathways that mediate damage sensitivity.

Most of the agents we tested result in DNA damage; however, we also included benomyl in this study due to its impact on the mitotic spindle and chromosome

19 segregation. Although a few heterozygous strains showed benomyl sensitivity (Table 2), we also identified a group of seven heterozygous deletions, e.g. atg11∆/ATG11, which demonstrated relative resistance to benomyl in a rad9-deficient state and sensitivity in a wild-type background (see Figure 5 and Discussion).

Heterozygous mutations of MCM21 and the genes encoding other members of the

COMA kinetochore complex are very unstable in a wild-type background: The mcm21∆/MCM21 heterozygous strains showed the greatest instability with a 500-fold increase in a wild-type background. mcm21 was originally identified as

Minichromosome Maintenance mutant number 21 in a haploid EMS mutagenesis screen for instability of a monocentric circular minichromosome (MAINE et al. 1984). This gene was later identified to be part of the COMA complex involved in binding the kinetochore to centromeric regions (ORTIZ et al. 1999). We further determined the dosage sensitivity of mcm21 mutants as well as the other COMA complex members (Table 3). The mcm21∆/mcm21∆ homozygous null strain had an even further increase in instability compared with the heterozygous counterpart increasing from 4.03E-03 to 1.94E-02 with loss of the second copy of MCM21.

The COMA complex is named for its four member proteins, Ctf19, Okp1, Mcm21 and Ame1, which are encoded by two non-essential genes, CTF19 and MCM21, and two essential genes, OKP1 and AME1. The ctf19∆/CTF19 and ctf19∆/ctf19∆ strains are also very unstable with chromosome V instability rates of 2.5E-04 and 1.8E-02, respectively, similar to the mcm21 mutant strains. Heterozygous deletion of the essential genes, OKP1 and AME1, results in increased instability but not to the high level seen with deletion of

20 the non-essential members of this complex. Similar to mcm21∆/MCM21 mutant strain, the combined rad9∆/rad9∆ okp1∆/OKP1 strain was more stable than okp1∆/OKP1 alone.

21 DISCUSSION

In this study, we performed a genome-wide screen in S. cerevisiae to successfully identify heterozygous mutations that cause a modest increase in genome instability in a checkpoint deficient strain. The genes identified in this screen differ from prior screens which were carried out in haploid strains and which typically identify mutant strains with much greater degrees of genomic instability (BEGLEY et al. 2004; YUEN et al. 2007). We identified 398 heterozygous mutant strains with increased loss of a non-essential artificial chromosome, resulting from insertions into at least 172 different coding regions in this collection. Approximately 45% of these insertions also resulted in a statistically significant 3-14 fold increased instability of the endogenous chromosome V. Assays of genomic instability conducted in precise heterozygous deletions in non-mutagenized backgrounds demonstrated 80% reproducibility of the instability phenotype. These findings lend further support to the analysis of other heterozygous phenotypes in yeast as a potential model of human diseases that result from haploinsufficiency.

Yuen et al. recently published work identifying 293 null mutant strains (either hemizygous deletions in haploids or homozygous deletions in diploids) in an otherwise wild-type background which affected maintenance of genome structure (YUEN et al.

2007). They utilized three different assays to identify these genes, one of which was similar to our initial assay using CF inheritance and colony sectoring to measure instability. When we compare our gene list with those 89 genes identified from this portion of their screen, we find seven genes in both lists. Although we do not know the severity of sectoring required to be included in the Yuen et al. data set, as their scoring ranged from 1-3 (from subtle to prominent), the lack of significant overlap in the genes

22 identified in the two screens may result from 1) our use of a rad9-deficient background and 2) the inability to a priori predict which genes will demonstrate both a null and heterozygous or dosage sensitive phenotype.

Gene Ontology analysis demonstrated that we identified insertions into genes implicated in a wide variety of functions but the list had statistically significant overrepresentations of groups such as cell cycle that have members known to participate in maintenance of genome stability. Further analysis of the genes in the cell cycle group revealed a predominance of G2, G2/M and mitotic checkpoint genes and an absence of G1 cell cycle specific genes. The interactome demonstrated that many of these genes also genetically or biochemically interact with RAD9. However, we did not identify the genes encoding the checkpoint kinases MEC1, TEL1 or CHK1 presumably because enzymes are less likely to be dosage sensitive. Instead we identified genes whose products are proposed to play more structural roles in the checkpoint response such as MRC1 and

DBP11 (KAMIMURA et al. 1998; OSBORN and ELLEDGE 2003).

Further assays for sensitivity to genotoxic stress demonstrated that the majority of heterozygous deletions that increased spontaneous genomic instability did not significantly increase sensitivity to exogenous damage. Thus, the results of this screen are distinct from those that focused on mutants with increased sensitivity to specific agents

(BIRRELL et al. 2001; CHANG et al. 2002; AOUIDA et al. 2004). Most interesting was the observation that for seven different deletions, the heterozygous strains were more resistant to the microtubule depolymerizing agent benomyl in a rad9-deficient background and were more sensitive to benomyl in the wild-type background. In these strains, the heterozygous mutation may result in slowing during mitosis. In the wild-type

23 case, this slowing could accentuate the mitotic delay that is induced by exposure to benomyl and result in poorer colony growth. In fact, experiments performed in conditions inducing slow growth, either growth at 18o or on low nutrient plates, further accentuated sensitivity to benomyl (data not shown). Conversely, in the rad9-deficient background, this mitotic delay may compensate for the RAD9 checkpoint deficiency and result in relative resistance to benomyl. Consistent with this model, the rad9∆/rad9∆ strain itself is more sensitive to benomyl exposure. Overlapping roles of Rad9p in both the DNA damage and spindle checkpoints has been previously reported by our lab and others (GARBER and RINE 2002; MIKHAILOV et al. 2002; SCOTT and PLON 2003).

Although the initial screen was performed in a rad9∆/rad9∆ background, additional testing of 65 precise gene deletions revealed that 85% of them were not exclusively RAD9 dependent and also increased genomic instability of strains in a wild- type background. However, the absolute sectoring rate of the majority of these heterozygous mutations in a wild-type background was still less then the rad9∆/rad9∆ parental strain. Thus, use of the rad9∆/rad9∆ background was necessary in order to bring the absolute instability of the strains to a visible level for the sectoring assay used in our initial screen. The majority of the genes identified demonstrate dosage sensitive genomic stability independent of checkpoint status and heterozygous mutations in homologous human genes might impact cancer susceptibility in the general population

Twenty of the 65 precise deletions tested did increase genomic instability of a rad9∆/rad9∆ strain at or above a multiplicative effect. The human orthologs of this set of genes would be good candidates for modifiers of the cancer phenotype in carriers of

BRCA1 or other checkpoint mutations.

24 Included in the group of potential BRCA1 specific modifiers are the three genes that showed rad9-specificity for genome instability, SAM1, TMA17 and DML1. This rad9-specificity may reflect heterozygous mutations that induce instability through an intermediate that is normally detected and compensated for by the Rad9 checkpoint pathway and thus don’t show instability in a wild-type background.

The budding yeast SAM1 gene encodes an enzyme required for production of S- adenosyl-L-methionine (SAM), availability of which has been associated with development of cancer. Consistent with our findings in yeast, exogenous addition of

SAM to primary human foreskin fibroblasts has recently been shown to prevent aneuploidy (RAMIREZ et al. 2007). While alterations in levels of SAM may be affected by diet or exposure to chemical agents, variation in levels may also result from polymorphisms in methyl metabolism genes.

The TMA17 gene was named for its Translational Machinery Association

(FLEISCHER et al. 2006), but further functional studies have not been performed. It is of particular interest that Mcm21 was one of five proteins found to interact with Tma17 through a two-hybrid analysis (ITO et al. 2001). Given this interaction, and our finding of a CF and chromosome V instability phenotype for the heterozygous tma17 deletion strain we hypothesize Tma17p impacts chromosome segregation as well as any putative function in translation.

DML1 was identified as the ortholog of the Drosophila melanogaster Misato gene which functions in chromosome segregation (MIKLOS et al. 1997). Analysis of the haploid deletion of dml1 in S. cerevisiae by Gurvitz et al. revealed that it was an essential gene, although their work specifically implicated a defect in mitochondrial DNA inheritance

25 but not chromosome segregation effects (GURVITZ et al. 2002). In contrast, similar to the

Drosophila work, our study of heterozygous dml1∆ strains demonstrates a role for Dml1 in chromosome segregation in checkpoint deficient cells. Although recent studies of human Misato demonstrate a role in mitochondrial fusion (KIMURA and OKANO 2007), based on our results in S. cerevisiae and the work in D. melanogaster, further analysis of the role of human Misato in maintenance of chromosome stability is warranted.

The mcm21∆ heterozygous deletion caused the greatest increase (~500 fold) in genomic instability in a wild-type background. We also found that strains mutant for the other nonessential member of the COMA kinetochore complex, CTF19, have similar phenotypes. Thus, deficiency of either Mcm21 or Ctf19 (the nonessental COMA complex members) results in very high levels of chromosome instability. This is consistent with the results of synthetic lethal screens which demonstrated that combining mcm21∆ or ctf19∆ deletions with spindle checkpoint gene deletions results in lethality (LEE and

SPENCER 2004; TONG et al. 2004; MEASDAY et al. 2005; DANIEL et al. 2006). Heterozygous mutant strains for okp1 and ame1, the two essential members of the COMA complex, showed increases in genome instability but not to the level seen in the two non-essential members. We propose that when either of the nonessential members (Mcm21 or Ctf19) are deficient, Okp1 and Ame1 perform their essential kinetochore function very inefficiently resulting in very high levels of chromosome instability. Thus, the COMA complex appears to play a critical role in maintaining chromosome segregation fidelity and is encoded by dosage sensitive genes.

Work ongoing at the time of this study identified a human homolog to Mcm21, called Mcm21R or hMcm21 or CENPO (MERALDI et al. 2006). Similar to our analysis,

26 depletion of Mcm21R by siRNA in HeLa cells showed chromosome congression defects

(MCAINSH et al. 2006). Depletion of Mcm21R was also shown to allow bypass of mitotic arrest by preventing Mad2 binding to kinetochores, thus inactivating the spindle checkpoint. Interestingly, in our experiments homozygous deletion of RAD9 reduced sectoring and chromosome V instability of the MCM21 heterozygous strains. Similar results were seen for OKP1 heterozygous strains. These phenotypes in yeast and human cells suggest that in the presence of defective mitotic and spindle checkpoints the apparent relative chromosome V stability may be due to reduced viability of the cells that mis-segregate chromosomes or chromosome fragments.

Evolutionary conservation of genes and/or pathways is paramount to the effective use of yeast to model human disease states. Therefore, extensive searches for homologs to the 172 unique genes identified in this screen were conducted using multiple algorithims including: Inparanoid, HomoloGene, OrthoMCL, BLASTP and Pubmed literature searches. This combined approach yielded a candidate human homolog for

50% of the yeast genes isolated from our screen (Table 4).

Consistent with our goal to use this screen to identify potential cancer predisposition loci, mutations or polymorphisms in human genes homologous to 15% of our mutants have already been associated with increased cancer risk including TOPBP1,

TXN, ERCC4, and CHEK2 (MEIJERS-HEIJBOER et al. 2002; STAALESEN et al. 2004; KARPPINEN et al. 2006; CEBRIAN et al. 2006; MILNE et al. 2006). For example, Karppinen et al. recently investigated TOPBP1’s influence on hereditary predisposition to breast and/or ovarian cancer based on its role in DNA damage and replication checkpoints, and described a novel heterozygous variant in TOPBP1 associated with an increased breast

27 and/or ovarian cancer risk (KARPPINEN et al. 2006). Similarly, a single nucleotide polypmorphism in the TXN gene has been associated with susceptibility to breast cancer by Cebrian et al. and surmised to account for 0.32% of the excess familial risk of breast cancer (CEBRIAN et al. 2006).

Based on their dosage sensitive impact on genome instability, we believe that the human homologs of genes identified in our screen should be included in ongoing epidemiologic studies for cancer susceptibility loci as well as modifiers of cancer susceptibility in mutation carriers. The impact of haploinsufficiency of the mammalian orthologs could also be tested in heterozygous mouse models including their impact on genome instability and cancer.

28 ACKNOWLEDGEMENTS

This work was supported by Department of Defense grant DAMD17-03-1-0464 to SEP; EDS and XW received support from the Dan L. Duncan Cancer Center at Baylor

College of Medicine. Special thanks to Drs. Hannah Klein, Vicki Lundblad and Phil

Hieter for donation of strains. We extend thanks to Drs. Kenneth Scott, Chad Shaw and

Albert Ribes Zamora for technical support and helpful discussions.

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38 Figure 1. - Screen strategy. 1) The rad9∆/rad9∆ strain ES75 was mutagenized by transformation with the Not1-digested mTn-lacz/Leu2 insertional library and positive transformants were selected on leucine-deficient plates. 2) Approximately 185 colonies from each mutant strain were then struck-out on low adenine media and monitored for sectoring colonies as a measure of chromosome fragment (CF) loss. Strains that met the sectoring threshold were restruck three times and strains that consistently showed increased CF loss were carried forward. 3) The transposon insertion site was then identified in mutagenized strains that showed increased CF loss. 4) The rate of chromosome V loss or recombination as quantitatively measured by conversion to canavanine resistance was estimated using fluctuation analysis for those strains that demonstrated increased CF loss.

Figure 2. – Validation of chromosome V instability rate estimates and enrichment of increased CF loss strains for increases in chromosome V instability. A. Fluctuation analysis experiments were performed on five wild-type and five rad9-deficient yeast strains to test reproducibility of the chromosome V instability rate estimations. These data are shown in a combined box and whisker plot where each box represents summary statistics of instability rate estimates in the 15 parallel cultures of each strain. The box has lines at the lower quartile, median, and upper quartile of the data. The whiskers are lines extending from each end of the box to show the extent of the rest of the data. The whiskers indicate the minimum and maximum data values, unless outliers (marked using

+) are present in which case the whiskers extend to a maximum of 1.5 times the inter- quartile range. B. We measured the chromsome V instability rates of 40 mutant strains

39 from the increased CF loss category and 10 mutant strains from the non-sectoring category. One-sided unequal variance t-tests were performed on the estimated rate of chromosome V instability of each of the 50 strains compared to the rad9∆/rad9∆ parental strain (3.37E-05 by summation of 5 separate rad9∆/rad9∆ estimations). Strains which were statistically increased as determined by the t-test are shown as solid diamonds; strains not significantly increased are shown as open diamonds. Seventy percent of the strains from the high CF loss group showed statistically increased chromosome V instability rates, while zero of the strains from the no CF loss group were statistically different.

Figure 3. - Gene ontology analysis of biological processes and cellular component categories for Saccharomyces cerevisiae. This graphical representation shows the percentage usage in the gene ontology at the 3rd level of both biological process (A) and cellular component (B). Black bars show observed percent representation in list of genes isolated in the screen, white bars show representation observed in the yeast genome, and demonstrate the expected rate in the list of genes if the list is random. The boxed ontologies, cell cycle and meiosis process and chromosome location are statistically significantly over-represented while the boxed ontology of protein biosynthesis is under- represented.

Figure 4. - Network interactome of 69 genes identified by coding region disruptions.

This graphical representation shows the 69 of 172 genes, identified by transposon insertion into their coding region, which had been previously identified to physically or

40 genetically interact with another member of this group or with RAD9. The node color indicates the primary biological process gene ontology the gene is classified into. The edge color indicates the identified physical or genetic interaction.

Figure 5. - Altered benomyl sensitivity and resistance of a subset of mutant strains.

Wild-type and rad9∆/rad9∆ strains with heterozygous deletions in atg11, bfr2, elg1, mrc1, trx1, and ydr066c were grown on rich media (YPD) without or with 10ug/ml

Benomyl. Although atg11∆/ATG11, mrc1∆/MRC1, trx1∆/TRX1 and ydr066c∆/YDR066C strains are sensitive to benomyl compared to wild-type strains, the heterozygous mutation confers relative resistance to benomyl in a rad9∆/rad9∆ background. The rad9∆/rad9∆ strain itself shows an increased sensitivity to benomyl versus the wild-type counterpart.

41 Table 1. Chromosome V Instability Rate of Mutant Strains for 65 Genes Identified

in the Screen

1 2 3 4 5 6 7 8

Gene of Mutation µ - Precise ratio A = ratio µ (goi∆/ B = ratio ratio

Interest (GOI) Rate (µ) Deletion µ (rad9∆/ µ (rad9∆/ GOI) µ A

Insertional (rad9∆ rad9∆ rad9∆ (goi∆/GOI) B

Mutant /rad9∆, goi∆/GOI) goi∆/GOI) µ (wild-

(ISM) goi∆/GOI) µ (ISM) µ (rad9∆ type)

/rad9∆)

WT 7.86E-06 rad9∆/rad9∆ 3.37E-05

SAM1A 4.36E-04 2.12E-04 0.49 6.29 8.67E-06 1.1 5.72

TMA17B 1.15E-04 9.87E-05 0.86 2.93 6.90E-06 0.88 3.33

ARO4 A 9.56E-05 5.14E-05 0.54 1.53 3.99E-06 0.51 3

DML1 A 7.59E-05 1.35E-04 1.78 4.01 1.08E-05 1.37 2.93

MSH5 A 4.01E-05 1.79E-04 4.46 5.32 2.48E-05 3.16 1.68

YBL104C B 1.91E-04 8.17E-05 0.43 2.42 1.13E-05 1.44 1.68

DPB11 A 2.67E-05 1.69E-04 6.33 5 2.54E-05 3.23 1.55

SPP2C 6.33E-04 2.07E-04 0.33 6.13 3.33E-05 4.24 1.45

CHS3 A 6.06E-05 8.19E-05 1.35 2.43 1.51E-05 1.92 1.27

TUB2 A 5.73E-05 2.85E-04 4.97 8.44 6.48E-05 8.24 1.02

TOM1 A 1.99E-04 9.79E-05 0.49 2.91 2.27E-05 2.89 1.01

RRN3 A 2.49E-05 6.00E-05 2.41 1.78 1.44E-05 1.83 0.97

42 YLR307C-A B 1.77E-04 9.16E-05 0.52 2.72 2.21E-05 2.81 0.97

MNN4 A 1.76E-04 6.86E-05 0.39 2.03 1.72E-05 2.19 0.93

NDD1 A 2.42E-06 7.97E-05 32.93 2.36 2.11E-05 2.68 0.88

HOP1 A 1.60E-04 1.21E-04 0.76 3.6 3.25E-05 4.13 0.87

REV7 A 1.58E-04 8.95E-05 0.57 2.66 2.52E-05 3.21 0.83

RLI1 C 1.90E-04 1.36E-04 0.72 4.02 3.83E-05 4.87 0.83

HAC1 A 5.12E-05 9.18E-05 1.79 2.72 2.65E-05 3.37 0.81

CDC26 A 3.38E-05 9.59E-05 2.84 2.84 2.97E-05 3.78 0.75

DUN1 A 5.06E-05 1.51E-04 2.98 4.48 5.14E-05 6.54 0.69

TSC11 C 9.44E-05 1.05E-04 1.11 3.11 3.72E-05 4.73 0.66

SDC25D 8.31E-05 1.32E-04 1.59 3.9 4.72E-05 6.01 0.65

ATG13 D 9.77E-05 6.60E-05 0.68 1.96 2.44E-05 3.1 0.63

CDC9 A 4.08E-06 7.00E-05 17.16 2.08 2.72E-05 3.46 0.6

SWE1 A 9.25E-05 8.45E-05 0.91 2.51 3.44E-05 4.38 0.57

LEU3 A 8.54E-05 5.60E-05 0.66 1.66 2.31E-05 2.94 0.56

YIR035C B 6.75E-05 6.43E-05 0.95 1.91 2.76E-05 3.51 0.54

ACK1 B 1.33E-04 1.23E-04 0.92 3.66 5.39E-05 6.86 0.53

SSK1 D 1.18E-04 9.87E-05 0.84 2.93 4.50E-05 5.73 0.51

DST1 A 1.89E-04 8.61E-05 0.46 2.55 3.92E-05 4.99 0.51

YKL044W B 7.20E-05 1.08E-04 1.5 3.19 5.01E-05 6.37 0.5

IME2 A 3.12E-05 5.22E-05 1.67 1.55 2.52E-05 3.21 0.48

SEC6 C 1.33E-04 1.21E-04 0.91 3.59 5.89E-05 7.49 0.48

GDA1 D 1.54E-04 1.49E-04 0.97 4.41 7.73E-05 9.83 0.45

43 FOB1 A 5.99E-05 6.47E-05 1.08 1.92 3.48E-05 4.43 0.43

ECM16 C 5.65E-05 1.16E-04 2.05 3.46 6.49E-05 8.26 0.42

SYF1 A 3.31E-06 5.63E-05 17.01 1.67 3.16E-05 4.02 0.42

SPO12 A 7.20E-05 5.68E-05 0.79 1.69 3.59E-05 4.57 0.37

BFR2 C 9.86E-04 6.78E-05 0.07 2.01 4.48E-05 5.7 0.35

MSC1 A 4.22E-05 5.68E-05 1.35 1.68 3.87E-05 4.92 0.34

SPE4 A 2.98E-06 4.99E-05 16.74 1.48 3.48E-05 4.43 0.33

DBR1 A 5.76E-05 1.10E-04 1.91 3.26 7.79E-05 9.91 0.33

SIR4 A 1.76E-04 1.22E-04 0.69 3.62 8.66E-05 11.02 0.33

DIP5 A 1.06E-04 9.95E-05 0.94 2.95 7.31E-05 9.3 0.32

TEA1 A 1.36E-04 3.93E-05 0.29 1.17 2.91E-05 3.7 0.32

STU2 A 1.60E-04 5.34E-05 0.33 1.58 3.98E-05 5.06 0.31

ELG1 A 5.10E-05 6.85E-05 1.34 2.03 5.12E-05 6.51 0.31

LHS1 A 2.34E-04 6.27E-05 0.27 1.86 4.98E-05 6.34 0.29

RAD55 A 8.48E-05 8.52E-05 1 2.53 7.84E-05 9.97 0.25

NGR1 A 1.37E-04 2.29E-06 0.02 0.07 2.29E-06 0.29 0.24

RAD1 A 2.51E-04 7.43E-05 0.3 2.2 7.17E-05 9.12 0.24

NMD2 D 1.47E-04 1.03E-05 0.07 0.31 1.03E-05 1.31 0.24

PPH21 A 2.01E-05 2.30E-05 1.14 0.68 2.30E-05 2.93 0.23

PTC3 A 9.81E-05 4.76E-05 0.49 1.41 4.89E-05 6.22 0.23

UTP22 C 9.52E-05 4.69E-05 0.49 1.39 5.00E-05 6.37 0.22

RFC4 A 1.78E-04 6.64E-05 0.37 1.97 7.33E-05 9.33 0.21

HIR3 A 1.72E-04 4.45E-05 0.26 1.32 6.96E-05 8.85 0.15

44 MRC1 A 4.42E-05 2.89E-05 0.65 0.86 7.37E-05 9.38 0.09

YDR066C B 6.18E-05 3.13E-05 0.51 0.93 9.13E-05 11.62 0.08

ATG11 D 1.61E-04 2.22E-05 0.14 0.66 7.70E-05 9.8 0.07

TRX1 A 1.22E-04 3.78E-05 0.31 1.12 1.44E-04 18.32 0.06

SPE1 D 1.69E-04 1.18E-04 0.7 3.5 6.87E-04 87.4 0.04

YAL066W B 6.74E-05 1.33E-04 1.97 3.95 7.83E-04 99.62 0.04

MCM21 A 8.63E-05 4.21E-06 0.04 0.12 4.03E-03 512.72 0

Column 1 identifies the gene of interest (GOI) isolated in the mutagenesis screen by

transposon insertion (ISM) and selected for construction of a precise heterozygous

deletion (goi∆/GOI) in both rad9-deficient and wild-type backgrounds. Basis for

inclusion of this gene in this subset is denoted by the superscript letter after the gene

name, A: Gene Ontology Statistically Significantly Overrepresented Group, B:

Hypothetical Open Reading Frame, C: Essential, D: High Chromosome V instability rate

(µ). Column 2 shows µ (events/cell/generation) as measured by conversion to canvanine

resistance, of the insertionally mutagenized strains in a rad9∆/rad9∆ background; column

3 shows the µ of the precise heterozygous deletion in the rad9-deficient background;

column 4 shows the ratio between the two to determine the reproducibility of the

instability phenotype. Column 5 shows the ratio (A) of the µ of the heterozygous gene

deletion in the rad9∆/rad9∆ background to µ of the rad9∆/rad9∆ parental strain. Column

6 shows the µ of the heterozygous deletion in a wild-type background. Column 7 shows

the ratio (B) of the µ of the heterozygous gene deletion in the wild-type background to

the wild-type parental strain. Column 8, the calculated A/B ratio, shows the fold change

45 between the increases in µ due to the heterozygous gene deletion in the rad9∆/rad9∆ vs. wild-type backgrounds. Column 8 was then used to categorize these chromosome V instability rates based on whether the fold change due to the heterozygous deletion was larger or smaller in the rad9∆/rad9∆ or wild-type backgrounds. The first boxed section

(A>B) represents 8 strains where the heterozygous deletion of the GOI appears to have a larger effect in a rad9∆/rad9∆ background then in wild-type background. The second boxed section (A≈B) represents 12 strains where heterozygous deletion of the GOI has a similar effect in both backgrounds. The third boxed section (A

46 Table 2. Genotoxic stress phenotypes for precise heterozygous gene deletions

Heterozygous Strain UV MMS Benomyl Phleomycin HU

Deletion Background

ATG11 WT All

ATG11 rad9∆/rad9∆ R R

ARO4 WT All

ARO4 rad9∆/rad9∆ All mild R mild

ACK1 rad9∆/rad9∆ mild

CHS3 WT All All All All All

DUN1 WT All-mild mild All All

GDA1 WT All

GDA1 rad9∆/rad9∆ All mild R All

HIR3 rad9∆/rad9∆ R R mild

HOP1 WT All

HOP1 rad9∆/rad9∆ All mild R

MRC1 WT All

MRC1 rad9∆/rad9∆ R

MCM21 WT All mild R mild

NDD1 WT All mild mild

NGR1 WT mild mild R

NGR1 rad9∆/rad9∆ All mild R

PPH21 WT mild

RAD1 WT All

47 RAD55 WT All All All All

RRN3 WT mild

SAM1 WT R R R

SAM1 rad9∆/rad9∆ R

SIR4 WT All

SPE1 WT R R R

TMA17 WT R R

TRX1 WT All

TRX1 rad9∆/rad9∆ R

YAL066W WT R R

YAL066W rad9∆/rad9∆ R

YBL104C WT All All

YDR066C WT All

YCR066C rad9∆/rad9∆ R R

Sixty-five precise heterozygous deletions in rad9∆/rad9∆ and wild-type backgrounds, as described in Table 1, were tested for response to genotoxic stress. 41 of the 65 tested heterozygous gene deletions were not sensitive to any of the agents tested in either background. Strains that showed an altered response to any agent are shown. Exposures to Ultraviolet Light (UV) doses of 20 J/m2/sec, 30 J/m2/sec and 40 J/m2/sec, Methyl

Methane Sulfonate doses of 0.0075%, 0.015% and 0.03%, Benomyl doses at 10 µg/ml,

20 µg/ml and 30 µg/ml, Phleomycin doses at 0.1 µg/ml, 0.5 µg/ml and 1 µg/ml and

Hydroxyurea (HU) doses at 25 mM, 50 mM and 75 mM were tested. R-Resistant, All-

48 sensitive to all doses, mild- sensitive only at high doses, or All-mild: slight decreases in growth seen at every dose.

49 Table 3. Impact on Genome Stability due to Deletions in COMA Complex Genes

COMA Mutation Strain Sectoring Chromosome V Fold Change

Background Instability Rate over

events/cell/generation Parental

Strain

--- WT 0.07% 7.86E-06

--- rad9∆/rad9∆ 0.27% 3.37E-05 mcm21∆/MCM21 WT 4.10% 4.03E-03 512.72 mcm21∆/MCM21 rad9∆/rad9∆ 0.65% 4.21E-06 0.12 mcm21∆/mcm21∆ WT 0.00% 1.94E-02 2468.19 mcm21∆/mcm21∆ rad9∆/rad9∆ 0.00% 1.87E-02 554.90

ctf19∆/CTF19 WT 6.80% 2.54E-04 32.32

ctf19∆/CTF19 rad9∆/rad9∆ 8.60% 1.64E-04 4.87

ctf19∆/ctf19∆ WT 0.00% 1.81E-02 2302.80

ctf19∆/ctf19∆ rad9∆/rad9∆ 0.00% 1.64E-02 486.65

okp1∆/OKP1 WT 5.00% 2.72E-05 3.46

okp1∆/OKP1 rad9∆/rad9∆ 3.33% 1.29E-06 0.04

ame1∆/AME1 WT 6.60% 1.47E-05 1.87

ame1∆/AME1 rad9∆/rad9∆ 6.60% 3.08E-05 0.91

Sectoring and chromosome V instability rates are shown for heterozygous and homozygous deletion strains for the four members of the COMA complex. Sectoring is shown as a percentage of the total number of sectors in approximately 500 colonies.

50 Chromosome V instability rate (events/cell/generation) as measured by conversion to canavanine resistant cells is estimated via fluctuation analysis. The fold change in chromosome V instability rate for the indicated strain compared to the respective parental strain rate is shown in column 4. OKP1 and AME1 are essential genes and data is only available for heterozygous strains.

51 Table 4. Identification of Human Homologs for 172 Gene Insertions Identified in the Screen

Yeast Human Yeast Human Yeast Human

Protein Homolog Protein Homolog Protein Homolog

Ack1p SEL1LD Mcm21 MCM21RE Sec15p SEC15L2A,B,C

p EXOC6D

Ape2p NPEPPSA,B,C,D Mes1p MARSA,B,C Sec6p SEC6L1A

SYMPKD EXOC3B,D

Apl4p AP1G1A,C,D Mia40p CHCHD4A,C,D Smc4p SMC4A,B,C,D

,E

Atg26p UGT3A2D Mnn4p ANP32EA Smy2p TNNT1A

PERQ1D

Aus1p ABCG2D Mrc1p CLSPNE Snf3p GTR2D

Bfr2p AATFA,B,C Mrs6p CHMB,C,E Snt2p AF17D

GDI1D

Bph1p NSMAFA Msh5p MSH5A,B,C,D,E Snu66p SART1A,C

WDFY4C

ABCC1D

Bpt1p ABCC6C Muc1p MUC5BA Sor1p SORDA,C,D

WDFY3D MUC16C

Cdc9p LIG1A,B,C,E Nab2p ZC3H14D Spe1p ODC1A,B,C,D

DNL1D

Chs3p HAS3D Nft1p MRP2D Spe4p SRMC,D

52 Cox13p COX6A1A,C,D Ngr1p TIAL1A,D Spp2p GPKOWC

TRSPAP1C

Dbp5p DDX19AA,B,C, Nmd2p UPF2A,B,C,D,E Srv2p CAP2A,D

D CAP1B,C,E

Dbp6p DDX51A,B,C,D Npp1p ENPP5A,B Stu2p CKAP5A,C,D

ENPP3C,D,E

Dbr1p DBR1A,B,C,D,E Nup133 hNUP133E Swe1p PKMYT1C,D

p

Did4p CHMP2AA,B,C, Oac1p SLC25A34A,B, Swh1p OSBPA,B,C,D

D C,D

Dip5p SLC7A4A Otu2 p OTUD6BA,B,C, Swi1p AR15BD

D

Dml1p MSTO1C,D Pdc1p HPCLD Syf1p XAB2A,C,D

Dpb11p TopBP1E Pet191 MGC52110C Tom1p HUWE1C,D

p

Dst1p TCEA1A,B,C,D Pfa4p ZDHHC6C,D Tpm2p TPM3A

Dun1p CHEK2B,C,D,E Ppa2p IPYRD Trx1p TXNA,B,D

Ecm16 DHX37A,B,C,D,E Pph21p PPP2CBA, D Tsc11p RICTORC,D

p PPP2CA B,C

Elg1p FRAG1E Prc1p PPGBA,C,D Tub2p TUBB2CA,B,C

TBB2D

Emi2p HKDC1C,D Pry1p GAPR1B,C,D Ubp11p UBP21D

Ena1p ATP2C1D Ptc3p PPM1GA,C Urm1p C9orf74A,C,D

D

53 PP2CAD

Ena2p ATP2C1D Pus9p RPUSD2A,C,D Utp22p NOL6A,B,C,D

Ena5p AT2A1D Pyc2p PCA,C,D Vma2p ATP6V1B2A,B

ATP6V1B1C,D

Eug1p P4HBA,C Rad1p ERCC4A,B,C,D, Ybl104 FLJ20323A,C,D

PDIA3D E Cp

Gda1p ENTPD6A,C,D Rev7p hREV7E Ydr066 C1orf82A

ENTPD5B Cp

Hac1p XBP1E Rfc4p RFC2A,B,C,D Yel077 LOC642662B

Cp

Hop1p HORMAD2A Rli1p ABCE1A,B,C,D, Yfr044 CNDP2A,B,D

HORMAD1C,D, E Cp

E

Ime2p ICKA,C,D Rpl12B RPL12A,C,D Ygl059 PDK4 A

p Wp BCKDKD

Lcb4p SPHK2A,C Rpo21p POLR2AA,B,C, Yhr135 CSNK1G1A,C,D

SPHK1D D Cp

Lhs1p SH3KBP1A Rrm3p C15orf20A,C,D Yir035 HSD11B1A,D

HYOU1B,C,D Cp

Lsb1p GRB2C Sam1p MAT1AA,D Ypk1p SGK2A,B,C,D

SH3D19D MAT2AB,C

Mch2p SLC16A6A,D Sdc25p SOS1D

54 Searches for human homologs to the 172 proteins encoded by the genes identified in the primary screen for CF loss were carried out using; InparanoidA, HomoloGeneB,

OrthoMCLC, BLASTPD and PubmedE. Any protein with an identified homolog is listed and the search program(s) which identified the human homolog are denoted by the superscript letter.

55 SUPPLEMENTAL DATA

Screen Design: A diploid rad9∆/rad9∆ strain homozygous for the ade2-101 ochre mutation and carrying two chromosome fragments each with one copy of the SUP11 ochre suppressing tRNA gene was engineered to also carry an endogenously marked chromosome V carrying the mutant can1-100 gene. This strain was then insertionally mutagenized utilizing the Snyder mTn-lacZ/LEU2 insertional mutagenesis library to create a comprehensive set of heterozygous mutants selected as leu2+ transformants.

Thirty thousand heterozygous mutant strains were struck-out onto 1/8 of a low adenine plate and scored by visual inspection for reproducibly demonstrating increased red or pink sectors due to loss of one or both of the CFs resulting in loss of suppression of the ade2-101 mutation. Mutagenized strains with increased CF loss above a threshold level were then quantified for their chromosome V instability, using fluctuation analysis and a modified method of the median, and the insertion site of the transposon was identified.

Supplementary Data Table 1. 300 Transposon Insertion Sites Identified with

Vectorette and Inverse PCR. Transposon Insertion Site Identification; single gene names denote insertion of transposon into coding region of named gene, two gene names separated by a hyphen denote the transposon inserted between these two genes. Gene name repetitions indicate the number of times this gene was identified in the screen.

Supplementary Data Table 2. Transposon Insertion Sites in Non-Annotated

Regions. 53 insertions into non-annotated coding regions were identified. Column 2 lists

56 the closest upstream gene and closest downstream gene; repetitions of identified insertions are listed by reciprocal numbering in column 1. Column 3 identifies the annotated coding region of the upstream gene; column 4 identifies the annotated coding region of the downstream gene. The chromosomal coordinate of the transposon insertion is listed in column 5. Columns 6 and 7 show the number of basepairs between the transposon insertion site and the upstream and downstream genes. Column 8 lists the coordinates of all promotor regions identified through the S. cerevisie Promotor

Database.

Supplementary Data Table 3. Mean Chromosome V Instability Rate for all 172

Unique Gene-Disrupting Insertions. The transposon insertion site is identified in column 1 and the chromosome V instability rate estimated by one trial of fluctuation analysis as conversion to canavaine resistance is shown in column 2.

57