dCas9 chromatin opening enables adjacent RAR binding and RA-dependent gene activation.

<p><b>a</b>. Anti-retinoic acid receptor (RAR) ChIP followed by qPCR at three loci (RAR1-3, x-axis) in the presence of sgRNAs targeting each locus (blue, red, and green). ChIP-qPCR values are normalized to the average of two of the strongest genomic RAR binding sites. Three replicates were performed for all experiments, and a two-tailed Student’s t-test was used to calculate significance, and values with P<0.01 are denoted with a *. <b>b.</b> The Tol2 transposon-based reporter system involves stable integration of a 2x RAR motif, a minimal promoter, and GFP. dCas9 was recruited through sgRNA sequences upstream (sgRAR Up, red) or downstream (sgRAR Down, blue) of the 2x RAR motif. <b>c</b>. Average flow cytometric GFP induction by RA in the presence of control sgRNA (black), sgRAR Up (red), or sgRAR Down (blue) sgRNAs. <b>d</b>. dCas9 is able to bind to sgRNA sequences in inaccessible chromatin and induce accessibility, which directly enables the settler factor RAR to bind to previously obscured motifs.</p

DNase-seq and DNase-capture appear concordant.

<p>A one kilobase capture region in chromosome 10, starting at base 127508639. The reads are smoothed in a 5bp window, and only the forward reads are shown for visualization purpose. The DNase-capture reads counts were scaled so they could be shown on the same plot as the DNase-seq reads. The data pre-correction was used here.</p

Corrected DNase-capture and DNase-seq appear concordant.

<p>A one kilobase capture region in chromosome 10, starting at base 127508639. The reads are smoothed in a 5bp window, and only the forward reads are shown for visualization purpose. The DNase-capture reads counts were scaled so they could be shown on the same plot as the DNase-seq reads. Data normalization was used here.</p

DNase-capture has more reads per base.

<p>Reads per base, excluding bases with no reads, for the forward reads. The x- and y-axes are in log 10 scale. The DNase-capture reads were truncated at 1000 reads for visualization purposes. Reads from all tiling densities were aggregated in this plot.</p

dCas9 induces chromatin accessibility at previously inaccessible genomic loci.

<p><b>a</b>. mESCs were co-transfected with a Tol2 transposase (TPase), a Tol2 transposon-flanked dCas9 expression cassette, and a Tol2 transposon-flanked sgRNA cassette to yield stable expression of dCas9 and a sgRNA targeted to a region with inaccessible chromatin. <b>b</b>. 16/16 loci in previously inaccessible chromatin had statistically significant increases in DNase hypersensitivity (y-axis) upon sgRNA targeting as measured by DNase-qPCR (gray dots). DNase hypersensitivity at each locus is normalized to its level in the absence of sgRNA (blue dot), and the average normalized DNase hypersensitivity in the presence of gRNA for all loci is shown (red dot), which is statistically significantly increased over–sgRNA control. At least two replicates were performed for all conditions, and a two-tailed Student’s t-test used to calculate significance. <b>c</b>. DNase-qPCR measurement of DNase hypersensitivity (y-axis) is shown +/-150 bp from the sgRNA site (x-axis) at four targeted loci. DNase-qPCR values at each datapoint are normalized to hypersensitivity in the absence of sgRNA, and all loci are oriented such that the 20 bp sgRNA sequence is immediately to the left of 0 and the NGG PAM sequence is immediately to the right of 0. Three replicates were performed for all experiments.</p

DNase-capture protocol.

<p>This figure shows the stages of the DNase-capture protocol.</p

Increased tiling density produces more coverage.

<p>Log enrichment of the DNase-capture reads at a given tiling density compared to the number of DNase-seq reads over the same regions. Data pre-normalization data was used.</p

Correlation of DNase-capture and DNase-seq.

<p>Correlation coefficient values of the DNase-capture vs the DNase-seq data at various smoothing window sizes in the pre-selected genomic loci. Data pre-normalization was used.</p

Aggregate plots of two ChIP-seq CTCF clusters.

<p>The plots show raw ChIP-seq read counts over the two CTCF clusters. The ChIP-seq profiles are consistent with the DNase-seq profiles of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0187046#pone.0187046.g010" target="_blank">Fig 10</a>.</p

Constructing a proteomic growth model.

<p>(<b>A</b>) The average % growth rate difference relative to the ‘wt’ strain in each pair (figure produced using previously published data) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0075320#B4" target="_blank">4</a>]. Error bars show +/- one standard deviation. (<b>B</b>) Log relative protein abundance measurements vs. growth rate for 3 example proteins. ‘NDE1’ is repressed in strains with decreased growth rate. ‘RPP2A’ is unresponsive to changing relative growth rates. ‘HSP82’ is induced in strains with decreased growth rate. Colors correspond to strain pairs in (<b>A</b>). Error bars show +/- one standard deviation. (<b>C</b>) Slopes for three example proteins from (<b>B</b>) multiplied by a conversion factor (see Methods S1) to allow direct comparison between our slopes (across relative % growth differences; grey) and slopes found previously (across absolute growth differences; black) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0075320#B6" target="_blank">6</a>]. We use unconverted slopes to predict growth differences. Error bars display +/- standard error on the slope.</p