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.