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Classic ‘position-effect’ experiments repositioned genes near telomeres to demonstrate that the epigenetic landscape can dramatically alter gene expression. Here we show that systematic gene knockout collections provide an exceptional resource for interrogating position effects, not only near telomeres but at every single genetic locus. Because a single reporter gene replaces each deleted gene, interrogating this reporter provides a sensitive probe into different chromatin environments while controlling for genetic context. Using this approach we find that, whereas replacement of yeast genes with the kanMX marker does not perturb the chromatin landscape, chromatin differences associated with gene position account for over 35% of kanMX activity. We observe distinct chromatin influences, including a Set2/Rpd3-mediated antagonistic interaction between histone H3 lysine 36 trimethylation and the Rap1 transcriptional activation site in kanMX. These findings demonstrate that chromatin regulation is not governed by a uniform ‘histone code’, but by specific interactions between chromatin and genetic factors.
Transcription requires the precise coordination of genetic signals encoded in DNA with epigenetic signals such as modification of histones (Jaenisch and Bird, 2003; Rando and Winston, 2012). To elucidate which chromatin modification signals are most informative, powerful genome-scale methods have been applied to correlate profiles of histone modification state with profiles of gene expression measured over all genes (Schones and Zhao, 2008). These studies have identified a number of states that associate with transcriptional activity, such as trimethylation of lysine 4 in histone H3 (H3K4) which is found preferentially at the 5’ regions of highly-expressed genes (Santos-Rosa et al., 2002). Both histone states and gene expression state vary along a genome, however, making it difficult to discern which of these states is the cause and which is the effect. Moreover, methods based on genome-wide correlation identify only the most general chromatin effects and miss those that apply preferentially to subsets of genes or promoters, i.e., chromatin-genetic interactions. For example, the genome-wide positive association between H3K4me3 and transcription contradicts a previously-identified role for H3K4me3 in promoting gene silencing at telomeres, silent mating type loci, or rDNA regions (Briggs et al., 2001; Nislow et al., 1997). Such interactions are increasingly important for understanding human diseases such as cancer, in which both genetic and epigenetic alterations can enable onco- and tumor-suppressor genes (Chi et al., 2010; Feinberg et al., 2006).
Isolating the complete chromatin contribution to gene expression would mean controlling for the genetic sequence as the chromatin context was varied. This is precisely the means by which position effect variegation was first observed in Drosophila (reviewed by Henikoff, 1990). Gottschling et al. (1990) went on to establish the now classic “position-effect” in yeast, in which relocating genes from their wild-type loci to positions near telomeric heterochromatin revealed repressive effects on gene expression due to the distinct chromatin landscape.
Ideally, such position-effect experiments could be performed systematically by measuring the expression of the same gene positioned at each chromatin context, i.e., across all gene positions in the genome. Such a systematic screen has never been performed, perhaps because of the perceived difficulty of such a task. We reasoned that this task might be feasible, however, using the gene knockout library constructed in budding yeast by the Saccharomyces Genome Deletion Project (Winzeler et al., 1999). This project targeted each yeast open reading frame (ORF) for replacement with the kanMX cassette, which contains the TEF promoter from Ashbya gossypii upstream of the kanR gene conferring resistance to the antibiotic G418 (Wach et al., 1994). Deletion strains have been constructed for approximately 6,000 yeast genes representing >90% of known or suspected ORFs (Giaever et al., 2002). Although this deletion library was originally constructed to study gene function, it also possesses the critical feature needed for a systematic position-effect assay: each strain carries the same promoter and gene positioned over the range of chromatin environments presented by a genome.
Here, we show that the Saccharomyces Genome Deletion library indeed provides a foundation for systematic gene position experiments. These experiments, which effectively separate chromatin from genetic effects, permit estimates of the total genome-wide contribution of chromatin to gene transcription while preserving genetic and chromatin integrity far from the site of gene replacement. Integration of the resulting data with genome-wide maps of histone modifications leads us to propose a specific role for histone H3 lysine 36 tri-methylation (H3K36me3) in transcriptional control, via a chromatin-genetic interaction with the Rap1 transcriptional activation site in the TEF promoter.
To explore the use of gene deletion libraries for position-effect studies, we selected yeast strains from the heterozygous diploid collection corresponding to all kanMX-mediated gene replacements on Chromosome I. Heterozygous diploids retain one functional copy of the deleted gene and thus minimize unwanted effects of gene deletion on cell function (Deutschbauer et al., 2005). This assumption was supported by the finding that these strains have wild-type growth phenotypes and mRNA-expression profiles (Figure S1A-L). Next, we used quantitative reverse transcriptase Polymerase Chain Reaction (qPCR) to obtain sextuplicate measurements of kanMX expression in each of the Chromosome I deletion strains (Figure 1). As a group, the expression measurements showed significant variation from locus to locus (F-test, p < 2.04 × 10−11). This variation was due to at least nineteen loci that had significantly higher or lower expression (Figure 1B, C), with a four-fold dynamic range between the highest and lowest expressing loci. A comparison of expression variance at each position with variance across all measurements revealed that gene position accounts for approximately 35% of variation in kanMX expression (Experimental Procedures). In addition, decreased expression was observed at telomere-proximal loci (i.e., subtelomeric loci defined by Kellis et al., 2003), showing that our assay recapitulated well-established results (Figure S1M). In contrast, the two pericentric loci were expressed at near-average levels (Figure S1M), also consistent with previous observations that S. cerevisiae centromeric regions remain somewhat transcriptionally active (Perrod and Gasser, 2003). Since each kanMX insertion is directly downstream of the native wild-type gene promoter, it is possible that transcriptional machinery recruited by the native promoter directly influences kanMX expression. To assess this possibility, we compared our kanMX expression measurements to the expression levels of the wild-type genes being replaced and found no relationship between wild-type and kanMX expression, and no difference in kanMX expression between loci that are silenced versus actively expressed in wild type (Figure S1N). Although this result counters a direct influence of the native promoter on kanMX expression, it remains conceivable that the native promoter contributes to chromatin state at kanMX that then indirectly alters expression. We consider this a part of the position effect being examined in the approach.
Though it is assumed in position-effect assays that the inserted construct inherits the chromatin landscape of its new position, we sought to test this assumption directly by comparing the levels of different histone modifications along the kanMX cassette with their corresponding levels along the wild-type gene. The technique of chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR) was used to quantify levels of five different histone modifications, including trimethylation of histone H3 lysines 4, 36, and 79 (H3K4me3, H3K36me3, H3K79me3, respectively), and acetylation of histone H3 lysines 9 and 14 (H3K9ac and H3K14ac, respectively), and H3 for normalization to histone occupancy levels. Measurements were made at sites along the promoter and gene at each of ten different gene knockout positions on chromosome I, two of which had been observed to express kanMX at significantly higher or lower levels than average (Figure S2A; Table S1). For all histone modifications tested, the chromatin landscape was found to be very similar between the kanMX cassette and wild type (Figure 2A-J and S2). Correlations were particularly strong over the kanMX regulatory region and the corresponding 5’ region of the wild-type gene (Pearson r > 0.82, Figure 2A-E), suggesting that the insertion of kanMX does not significantly perturb the histone modification landscape in heterozygous diploid gene deletion strains.
Since the insertion and expression of kanMX does not appear to perturb histone modifications, we next sought to test the converse hypothesis, that histone modifications are predictive of kanMX expression. We used a sliding-window approach to compute the correlation between the kanMX expression levels we had measured along Chromosome I and the published occurrence at these loci of seven different histone modifications [H3K4me1, H3K4me2, H3K4me3, H3K36me3, H3K79me3, H3K9ac, and H3K14ac from (Pokholok et al., 2005), Figure S2D-F and Experimental Procedures]. Previous studies have shown that H3K4me3, H3K9ac, and H3K14ac are enriched at the 5’ region of yeast genes at levels that correlate with transcription, whereas H3K4me2 and H3K4me1 are enriched in the gene body and 3’ regions, respectively (Pokholok et al., 2005; Santos-Rosa et al., 2002). H3K36me3 is found over middle and 3’ regions of genes, where it is thought to repress spurious intragenic transcription (Carrozza et al., 2005). H3K79me3 is enriched within gene bodies, but its deposition is not closely linked with transcription (Pokholok et al., 2005).
Of the modifications examined, we identified strong anti-correlation between kanMX gene expression and H3K36me3 occupancy at the promoter (Figure 2K). Such an association was not identified previously in genome-wide histone profiling studies. In contrast, the expression profile of the wild-type genes along Chromosome I showed no correlation with H3K36me3 but was positively correlated with other chromatin states such as histone acetylation and H3K4me3 (Figure 2L), relationships that have been previously well-established (Millar and Grunstein, 2006). Thus, it appears that H3K36me3 has a negative association with expression of the kanMX gene but not with genes in general, which tend to be associated with a variety of other modifications (Figure 2M).
If the negative interaction we have identified between H3K36me3 and kanMX expression on chromosome I is general, we reasoned that levels of this histone modification should be predictive of kanMX expression on the other 15 yeast chromosomes (II – XVI). Among these chromosomes, ten loci were randomly selected from genomic regions with either reduced or elevated H3K36me3 occupancy. Measurements by qPCR revealed that kanMX expression levels were substantially higher when kanMX is positioned in regions of reduced H3K36me3 in comparison to regions of elevated H3K36me3 occupancy (Figure 3A). Therefore, the dependency of kanMX expression on the absence of H3K36me3, a relationship inferred from loci on Chromosome I, is indeed predictive of kanMX expression throughout the genome.
H3K36me3, a modification catalyzed by the Set2 methyltransferase (Krogan et al., 2003), is a known element contributing to the repression of spurious transcription initiation via recruitment of the Rpd3 histone deacetylase complex (Carrozza et al., 2005; Lickwar et al., 2009). To test the hypothesis that this mechanism of regulation may also play a role in relation to kanMX, we measured kanMX expression in strains without SET2 or RPD3. We observed increased kanMX expression compared to wild type at each of ten gene positions in an rpd3Δ background and eight out of nine positions in a set2Δ background (p < 0.003 and p < 0.05, respectively, paired t-test, see Figure 3B). These results suggest a causal role for H3K36me3 in the regulation of kanMX gene expression, and that this regulation is mediated through Set2 and Rpd3.
To further explore the connection to SET2 and RPD3, we looked for differences in chromatin organization that might co-occur with H3K36me3 to explain significantly higher or lower kanMX expression. We found additional support for a connection to the Set2-Rpd3 pathway by comparing histone acetylation levels (Kurdistani et al., 2004; O'Connor and Wyrick, 2007) between loci for which kanMX is expressed at either high or low levels. Five acetylated lysines (H2AK7, H2BK11, H2BK16, H4K12, H4K16) were significantly associated with kanMX expression (Mann-Whitney p < 0.05, Figure S3A-E) and significantly anti-correlated with H3K36me3 (Pearson r < −0.7, p < 0.05, Figure S3F-J, red dots). The anti-correlation between H3K36me3 and the acetylated lysines was particularly striking in comparison to the background correlation among all loci, which was insignificant in all five cases (Figure S3F-J, black dots). Notably, each of these lysine residues except H4K16 are known deacetylation targets of Rpd3 (Millar and Grunstein, 2006) and lend further support to a role for the Set2-Rpd3 pathway in kanMX expression.
The canonical mechanism for chromatin-mediated transcriptional regulation involves modulation of transcription-factor binding upstream of a gene (Rando and Chang, 2009). Since the kanMX cassette is activated by binding of the Rap1 transcription factor (TF) to an upstream activation sequence in the TEF promoter (Steiner and Philippsen, 1994), we hypothesized that the repressive interaction between H3K36me3 and kanMX might act through modulation of Rap1 binding. To test this idea, we used antibodies to either Rap1 or H3K36me3 to perform ChIPqPCR in five knockout strains. We found that Rap1 binding is indeed elevated at loci with low levels of H3K36me3 occupancy and depressed at loci with high levels of H3K36me3 (Pearson r = −0.97, Figure 4A). Thus, elevated levels of H3K36me3 are predictive not only of reduced kanMX expression but also of reduced binding of Rap1 to the kanMX promoter.
Another test of the apparent antagonism between H3K36me3 and Rap1 is to examine whether this interaction takes place not only at the kanMX locus but also at the numerous other Rap1 binding sites encoded across the genome. For this purpose, we compared the genome-wide binding profiles of Rap1 and H3K36me3, both of which have been published previously (Koerber et al., 2009; Pokholok et al., 2005). We found that the genomic regions associated with lower levels of H3K36me3 do indeed tend to be bound more frequently by Rap1 (Figure 4B).
Rap1 recognizes multiple cis-regulatory motifs in DNA (Pina et al., 2003), and it is known to take on different conformations depending on the sequence to which it is bound (Idrissi et al., 1998). Further investigation showed that the Rap1 / H3K36me3 association is strongest at promoters containing an identical Rap1 binding motif to the one carried in the kanMX cassette (GCCCATACAT, henceforth called the Rap-kan box). Indeed, among genes downstream of a Rap-kan box, expressed transcripts have lower occupancy of H3K36me3 relative to non-expressed transcripts (Mann-Whitney p < 5.4×10−4, Figure 4C, n = 30 expressed, 13 non-expressed), whereas H3K4me3 levels are no different (p = 0.89, Figure 4D). Interestingly, a slightly different histone distribution is observed when considering genes bearing a more general motif [ACACCCRYACAY, henceforth called the Rap-box (Lieb et al., 2001)]. In this more general set of genes (n = 130 expressed, 134 non-expressed), the distribution of H3K36me3 among non-expressed genes appears bimodal, with roughly half of the genes associated with high H3K36me3 occupancy and half of the genes associated with low H3K36me3 occupancy. Even for this expanded Rap-box motif, however, it is still the case that H3K36me3 is significantly elevated in non-expressed genes relative to expressed genes (p < 3.2 × 10−4) whereas H3K4me3 is significantly depressed (p < 5.9 × 10−3, Figure S4).
The Saccharomyces Genome Deletion Project constructed knockout strains covering many but not all genic positions throughout the genome. Of the 528 yeast ORFs that have not yet been included in the collection, 321 were attempted but did not yield successful transformants (Angela Chu, personal communication). Given the observed H3K36me3-mediated transcriptional repression of kanMX, we postulated that this interaction might explain why certain ORFs failed the deletion process. In support of this hypothesis, we observed that H3K36me3 is significantly enriched at ORFs that failed deletion (Figure 5, p < 2×10−16). Different ORF deletions were attempted different numbers of times, however, potentially introducing a sampling bias. To guard against such bias, we also examined the set of ‘Dubious ORFs’ for which deletion was attempted once and only once. Even in that restricted set, H3K36me3 remained significantly enriched at loci that failed deletion (Figure 5, p < 5×10−6).
To accommodate reduced kanMX expression during the gene deletion procedure, we developed a modified transformation protocol in which the drug-selection condition is more moderate than in the original (Experimental Procedures). Four ORFs were selected from loci with elevated H3K36me3 levels that were also unsuccessfully deleted in the Saccharomyces Genome Deletion Project. Using the modified protocol we successfully generated gene deletion strains for three of these four ORFs on our first attempt. To test whether these loci express kanMX at particularly low levels due to H3K36me3 occupancy, we measured kanMX expression in these new strains relative to a strain from Chromosome I that expresses kanMX at average levels (with low variance across replicates). We found that all three of the newly constructed strains expressed kanMX at significantly lower levels than average (Figure 5B, p < 0.01, one-sample t-test). All three kanMX transformants also had low expression relative to loci with elevated H3K36me3 that were nonetheless successfully targeted by the Saccharomyces Genome Deletion Project (Figure 3A). Thus H3K36me3-mediated suppression appears to explain, at least in part, why some ORFs failed in the systematic gene deletion process.
More than twenty years have passed since the classic position effect experiment in yeast, in which genes were repositioned to the telomere to show that the epigenetic landscape dramatically alters gene expression (Gottschling et al., 1990). Here, we have explored proof-of principle that gene knockout libraries can be ‘repurposed’ as a resource to study the effects of gene position not only at the telomere, but systematically across an entire eukaryotic chromosome. Using the Saccharomyces Gene Deletion collection in this mode, we have identified an antagonistic interaction involving a chromatin mark– the H3K36me3 histone modification– and a genetic element— the Rap1 binding site on the kanMX gene cassette.
Although the presence of H3K36me3 at the promoter does not generally repress gene expression, our results show that it is repressive in the context of a Rap1 binding site (Figure 2). In the same context, other marks such as H3K4me3 which correlate with expression in general are not correlated for a Rap1-driven gene. These differences point to specific chromatin effects on transcription that depend on the context of the gene being transcribed.
The idea that chromatin-genetic interactions can differ according to the identity of the bound TF has previously been explored (Guccione et al., 2006), and in one instance a Rap1 promoter was shown to be particularly sensitive to Rpd3-mediated repression relative to promoters driven by other TFs (Deckert and Struhl, 2002). Genome-wide studies have also identified chromatin-TF interactions that operate on only a subset of genes (Buck and Lieb, 2006). In support of distinct interactions within a cohort of genes bound by a common TF, Lickwar et al. (Lickwar et al., 2012) recently found that subsets of Rap1-bound genes with different binding motifs (one of which is a near-perfect match for the Rap1 motif in kanMX) are associated with different functional outcomes such as gene activation and local nucleosome positioning. Here we show that genes with an identical kanMX motif bear a distinct interaction with chromatin modifications not found when considering larger sets of genes (Figure 4C, D, and S4) and that the Set2-Rpd3 pathway is likely involved in modulating kanMX expression. Thus, it appears that H3K36me3 and Set2-Rpd3-mediated gene repression have a greater effect on kanMX expression relative to its effect on average genes, while effects from other histone modifications are diminished.
Recently, Henikoff and Shilatifard (Henikoff and Shilatifard, 2011) have countered the popular histone code hypothesis – whereby histone modifications play a causal role in regulating transcription – with the idea that the data equally support a ‘reverse model’ in which DNA-binding regulatory factors modulate the landscape of histone modifications. Under the reverse model, one would expect insertion of a genetic sequence such as kanMX to induce concurrent changes in the chromatin landscape. In this study we did not observe such changes: levels of histone modification at the kanMX gene cassette remained largely unchanged in comparison to wild type (Figure 2). Conversely, differences in levels of H3K36me3 at different gene positions were found to inversely correlate with kanMX expression. Finally, disruption of the genes whose protein products catalyze and interact with H3K36me3 (SET2 and RPD3, respectively) results in increased levels of kanMX expression (Figure 3B). The clearest interpretation of these results is that H3K36me3 plays a causal role in regulating kanMX gene expression, not vice versa.
It remains to be seen whether such a causal link can be generalized to expression of other genes, or whether it is specific to kanMX. Recent findings do suggest different models of chromatin regulation for different genes. A study of the GAL1/10 promoter exemplifies the argument that DNA sequence determines chromatin architecture (Floer et al., 2010). Studies of MYC1 TF binding in human B-cells demonstrates how a TF can induce specific histone modifications at its binding target (Guccione et al., 2006; Martinato et al., 2008). A study in yeast separates TFs into two groups: those that are histone-sensitive, and those that are histone-insensitive (Cheng et al., 2011). It is possible that the eukaryotic genome may take advantage of multiple modes of regulation, in which case systematic position-effect screening may provide a suitable method for establishing directionality in the chromatin-genetic relationship.
The demonstration that yeast knockout libraries can be used for position-effect screening opens the door for a cadre of future studies that we foresee falling along several lines. First, because the positioning of a single gene into many different chromosomal locations is a general feature of gene knockout collections for many eukaryotic organisms, including Schizosaccharomyces pombe (Spirek et al., 2010), Neurospora crassa (Dunlap et al., 2007), Caenorhabditis elegans (Vallin et al., 2012), Arabidopsis thaliana (Alonso et al., 2003), Drosophila melanogaster (Bellen et al., 2004; Thibault et al., 2004), and Mus musculus (Skarnes et al., 2011), a position-effect approach is readily adapted for analyses in other species. These other species present modes of epigenetic regulation not present in Saccharomyces, such as DNA methylation and RNAi targeting, which the gene knockout collections may help elucidate. Second, the relative ease of genetic manipulation in S. cerevisiae, as well as the growing use of zinc-finger and TALE nucleases for targeted genome editing in higher eukaryotes (Miller et al., 2011; Urnov et al., 2010), may allow the study of position effects involving other genes beyond that presented by the kanMX cassette. In yeast, employing well-established methods for exchanging the kanMX marker with an exogenous DNA sequence (Goldstein and McCusker, 1999; Romanos et al., 1992), one can envision screening for epigenetic interactions with well-conserved candidate human disease genes and promoters (Perocchi et al., 2008; Steinmetz et al., 2002) positioned at loci encompassing a wide array of epigenetic states. The resulting strains could be assayed for any desired output, such as candidate gene expression or interaction with regulatory factors. Third, we foresee novel uses of the molecular barcodes included in each knockout strain, which may enable position-effect assays in pooled cultures for parallel analysis. Whereas each barcode represents a missing gene in a functional genomics assay (Giaever et al., 2002), each barcode in a position-effect assay represents a distinct position in the genome. For example, analysis of individual barcodes following ChIP in pooled cultures might characterize how a TF-DNA interaction influences or is influenced by epigenetic context. Thus, the wide availability of gene knockout libraries will, in turn, enable researchers to deploy a variety of position-effect analyses and to develop innovative position-effect techniques.
All strains are from the Saccharomyces cerevisiae heterozygous diploid gene deletion collection in the BY4743 background (Open Biosystems). Constant growth rates were observed for all heterozygous gene deletion strains regardless of chromosomal position (not shown). Strains were grown to saturation in a 96 deep well plate (Nunc) in rich medium overnight before transferring to a new 96-well plate on the day of measurement. Cultures were grown to mid-log phase (1 × 107 cells/mL), and ~2 × 106 cells were harvested in each sample. Confirmations of kanMX positioning via PCR were performed for a selection of strains, including those exhibiting the most extreme expression levels. To guard against genetic mutations that may have arisen to produce aberrant expression, we performed two tests to validate extreme-expressing strains. First, we sequenced each promoter to look for significant mutations. Second, each strain was remade, and expression in the remade strain was compared to the strain used in this study. One extremely low-expressing strain, yal040cΔ, failed both tests and was therefore excluded from our analysis. rpd3Δ and set2Δ strains were created using standard yeast transformation techniques with the natMX gene cassette, and selected using rich media supplemented with 50 mg/L of clonNAT. Each deletion was confirmed via primers that flank the targeted natMX insertion site, and for set2, was further confirmed by protein immunoblot using an antibody to H3K36me3. Each of these two strains was then crossed with the ten strains in Figure 3A to produce 19 strains that are each homozygous for deletion of either SET2 or RPD3, and heterozygous for gene deletion by kanMX (one strain could not be recovered in a set2Δ background).
mRNA-Seq was performed in four different strains representing different positions along Chromosome I. Total RNA was isolated as described by Wong et al. (Wong et al., 2004), yielding RNA with an Integrity Number of at least 7. mRNA was purified and fragmented to an average of 300-bp as described by Yoon and Brem (Yoon and Brem, 2010). First-strand cDNA was then reverse-transcribed using Superscript III, followed by RNase H digestion and second-strand synthesis. Libraries were then prepared for analysis on an Illumina HiSeq2000 sequencer. Data were filtered to eliminate clonal reads, and aligned using Bowtie (Langmead et al., 2009) to the S. cerevisiae genome. Coordinates for each ORF were downloaded from Saccharomyces Genome Database, and counts for each ORF were computed as the median number of reads aligned to the last 200-bp of each ORF. Differential expression was determined using the “edgeR” package in R (Robinson et al., 2010).
To minimize batch effects, mRNA for each replicate of the Chromosome I data was isolated and reverse-transcribed into cDNA in parallel in a 96-well plate format. Cultures were treated with zymolyase (Seikagaku) for 30 minutes at 30°C, and total RNA was isolated and reverse transcribed in 96-well format using a Cells-2-Ct kit (Ambion), with the following modifications. Lysis Buffer with DNase I was briefly warmed to 25°C immediately before use, and incubation time in lysis buffer was extended from 5 minutes to 8 minutes. qPCR was conducted with a Bio-Rad iCycler using Bio-Rad SYBR-Green I Supermix. Primers used to quantify expression are listed in Table S1. Quantitative PCR measurements were analyzed using the Pfaffl method (Pfaffl, 2001), with kanMX transcripts quantified relative to ACT1. Results for each of six replicates were log2-transformed and plate- and median-normalized. Centromeric loci were defined as positions within 1-kb of the centromere. To produce Figure 1C, we constructed an empirical null model without position effects by sampling, with replacement, 1000 datasets of equal size (90 sets of 6 measurements) from all measurements. Each dataset was then ranked. The values displayed in Figure 1C summarize the distribution of expression observed at each rank across the null dataset. 79% (71 / 90) of the observed measurements were more extreme than the 99% confidence intervals defined in our null model without position effects. The contribution of position effects to expression variance was computed as 100 * (1 − r), where r is the ratio of the within-locus variance (6 replicates per locus, variance averaged over 90 loci) to the total variance over all 540 measurements. We also assessed whether essentiality of the replaced gene or proximity to a native binding site for Rap1 may have influenced kanMX expression. We found that neither correlated significantly with kanMX expression (data not shown).
Each immunoprecipitation (IP) was performed as previously described by Lee et al. (2002), with the following modifications. For each replicate, 300mL of yeast were prepared for cell lysis and sonication. Following formaldehyde treatment, crosslinking was quenched with addition of glycine to a final concentration of 400 mM. Cell lysate was collected into a 14mL tube, and sonicated using a Misonix 3000 (power 8, 6 cycles, 30 sec per cycle) to obtain fragments in the range 300 – 600 bp. Whole cell extract was collected for multiple IPs using different antibodies on aliquots of the same lysate. The antibodies used were specific to endogenous H3K4me3 (ab8580, Abcam), H3K36me3 (ab9050, Abcam), H3K79me3 (ab2621, Abcam), H3K9ac (ab10812, Abcam), H3K14ac (39137, Active Motif), histone H3 (ab1791, Abcam), or Rap1 (y-300, Santa Cruz Biotechnology).
At each gene knockout position, qPCR primers were designed to amplify five loci representing one position upstream of the kanMX insertion site, one position with primers flanking the insertion site, and three positions in the kanMX promoter, the 5’ region, and the gene body, respectively (Figure S2A and Table S1). To compare these measurements with wild type, three additional primer pairs were designed for use on wild-type ChIP extracts, to measure the corresponding histone modification enrichments on the native gene sequence. The wild-type primers were positioned at the insertion site, in the 5’ region of the gene, and in the body of the gene. The quality of each IP was assessed by evaluating the enrichment of a DNA sequence known to be bound to each protein (positive control) relative to mitochondrial DNA (negative control) (Table S1). Immunoprecipitated DNA samples with at least 20-fold enrichment were selected for further analysis. In these samples, enrichments for the kanMX sequence were quantified relative to whole-cell extract using positive control primers as a reference and expressed as a log2 ratio of enrichment. Normalization using a positive control accounts for experimental differences between replicates (i.e., how well non-specifically bound DNA was washed away), as well as differences in protein abundance that may arise in different strains. Enrichments for each antibody were normalized separately. Each set of replicate measurements was quantile normalized before subtracting histone H3 enrichments.
To calculate a value representing histone modification levels at the kanMX promoter, we averaged previously-published histone measurements within a 500-bp window centered at the transcription start site (TSS). A 500 bp window size recapitulated known genome-wide correlations with native gene expression most faithfully. Pokholok et al. (Pokholok et al., 2005) examined chromatin sheared randomly by sonication, and thus introduces the possibility that measurements may include modifications from other regions on random, long DNA fragments. To guard against such noise, we employed an approach that examined histone modifications within a 500-bp sliding window centered at positions from 2 kb upstream of the TSS to 2 kb downstream (Figure S2D-F). We then searched for peaks of correlation between expression and histone modification that localized over the promoter and transcription start site.
Transformation to produce new yeast strains was performed as described by the Saccharomyces Genome Deletion Consortium [a derivative of the method developed in (Gietz and Schiestl, 2007)] with the following modifications. First, we added a short incubation (5 – 15 minutes) in 5mM calcium chloride following heat shock (Pan et al., 2007). Next, whereas the cited protocol calls for strong selection with G418 (300 µg/mL) after 3 hours of recovery post heat-shock, we plated transformants directly onto rich medium post-heat shock, and allowed for recovery overnight at 30°C in order to allow transformants to generate sufficient kanMX gene product to promote G418 resistance. Transformants were then exposed to a graded selection procedure, in which cells were first replica-plated onto rich media bearing 50 µg/mL of G418 antibiotic, followed by replica-plating 2 days later onto rich media bearing 200 µg/mL of G418 and growth at 30°C for two more days. Colonies larger than 1 mm in diameter were assayed for correct integration of the kanMX cassette via PCR (Giaever et al., 2002).
We thank L. Clark and F. Zhang for technical assistance, R. Srivas for critical reading of the manuscript, R. Deconde for helpful discussions regarding statistics, A. Shah for laboratory assistance, A. Chu for detailed information about the Saccharomyces Genome Deletion Project, and J. Boeke for helpful comments. This research was supported by grants R21HG005252, R01GM084279, and P50GM085764 from the National Institutes of Health.
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Accession numbers. All mRNA-Seq data are deposited in GEO under accession number GSE42554.