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    Worthington Biochemical nucleosomal dna isolation
    Abundance and genomic distribution of Single Nucleosome Epi-Polymorphisms. (A) The fraction of nucleosomes that were called SNEP at FDR = 0.0001 was computed in every 1Kb-segment along each chromosome. Density ranged from 0 (white) to 100% (red). Grey denotes regions where nucleosomes could not be aligned. (B) Enrichment of H3K14ac SNEPs upstream Ty insertions and rDNA repeats. The fraction of BYac SNEPs among all nucleosomes was counted in 10 kb intervals upstream the rDNA region (brown triangles). The 7 fold enrichment of BYac SNEPs in the first 10 kb was significant (grey area, Chi-square test P = 0.01). Upstream regions of all Ty insertions present in BY and absent from RM were analyzed similarly (black points), and their fractions of BYac SNEPs were averaged. The 1.3 fold enrichment in the 10 kb interval directly upstream the insertions was significant (grey area, Chi-square test P = 0.014). (C) Local correlation between H3K14ac SNEPs. Ten nucleosomes were interrogated upstream and downstream each SNEP (x-axis). For each one, cases where the nucleosome was a SNEP similar to the centered one (either BYac or RMac) were counted and divided by the total number of nucleosomes interrogated at that position (brown histogram). Control values were obtained from the same procedure applied after re-assigning SNEPs to random nucleosomes (grey histogram). (D) Density of H3K14 acetylation and SNEPs relative to gene position. Every gene was divided by segmenting the coding sequence in 10 bins (average bin size of 160 bp) and its upstream and downstream regions in 100 bp bins. For every gene and every bin, log(acBY/nucBY) was averaged across replicated experiments and across all probes matching <t>intra-nucleosomal</t> <t>DNA</t> to produce the top green profile. Similarly, averaged log(acRM/nucRM) values generated the top black profile. Here acBY and acRM refer to H3K14ac ChIP-CHIP experiments on BY and RM samples, respectively, while nucBY and nucRM refer to nucleosomal mapping experiments on BY and RM samples, respectively. Note that probes matching inter-nucleosome linkers do not contribute to the profiles, which are therefore corrected for nucleosome abundance. Bottom profiles were obtained by counting the fraction of BYac SNEPs (green) and RMac SNEPs (black) among all nucleosomes that overlapped at least partially the bin, and averaging these fractions across all genes.
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    1) Product Images from "Natural Single-Nucleosome Epi-Polymorphisms in Yeast"

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast

    Journal: PLoS Genetics

    doi: 10.1371/journal.pgen.1000913

    Abundance and genomic distribution of Single Nucleosome Epi-Polymorphisms. (A) The fraction of nucleosomes that were called SNEP at FDR = 0.0001 was computed in every 1Kb-segment along each chromosome. Density ranged from 0 (white) to 100% (red). Grey denotes regions where nucleosomes could not be aligned. (B) Enrichment of H3K14ac SNEPs upstream Ty insertions and rDNA repeats. The fraction of BYac SNEPs among all nucleosomes was counted in 10 kb intervals upstream the rDNA region (brown triangles). The 7 fold enrichment of BYac SNEPs in the first 10 kb was significant (grey area, Chi-square test P = 0.01). Upstream regions of all Ty insertions present in BY and absent from RM were analyzed similarly (black points), and their fractions of BYac SNEPs were averaged. The 1.3 fold enrichment in the 10 kb interval directly upstream the insertions was significant (grey area, Chi-square test P = 0.014). (C) Local correlation between H3K14ac SNEPs. Ten nucleosomes were interrogated upstream and downstream each SNEP (x-axis). For each one, cases where the nucleosome was a SNEP similar to the centered one (either BYac or RMac) were counted and divided by the total number of nucleosomes interrogated at that position (brown histogram). Control values were obtained from the same procedure applied after re-assigning SNEPs to random nucleosomes (grey histogram). (D) Density of H3K14 acetylation and SNEPs relative to gene position. Every gene was divided by segmenting the coding sequence in 10 bins (average bin size of 160 bp) and its upstream and downstream regions in 100 bp bins. For every gene and every bin, log(acBY/nucBY) was averaged across replicated experiments and across all probes matching intra-nucleosomal DNA to produce the top green profile. Similarly, averaged log(acRM/nucRM) values generated the top black profile. Here acBY and acRM refer to H3K14ac ChIP-CHIP experiments on BY and RM samples, respectively, while nucBY and nucRM refer to nucleosomal mapping experiments on BY and RM samples, respectively. Note that probes matching inter-nucleosome linkers do not contribute to the profiles, which are therefore corrected for nucleosome abundance. Bottom profiles were obtained by counting the fraction of BYac SNEPs (green) and RMac SNEPs (black) among all nucleosomes that overlapped at least partially the bin, and averaging these fractions across all genes.
    Figure Legend Snippet: Abundance and genomic distribution of Single Nucleosome Epi-Polymorphisms. (A) The fraction of nucleosomes that were called SNEP at FDR = 0.0001 was computed in every 1Kb-segment along each chromosome. Density ranged from 0 (white) to 100% (red). Grey denotes regions where nucleosomes could not be aligned. (B) Enrichment of H3K14ac SNEPs upstream Ty insertions and rDNA repeats. The fraction of BYac SNEPs among all nucleosomes was counted in 10 kb intervals upstream the rDNA region (brown triangles). The 7 fold enrichment of BYac SNEPs in the first 10 kb was significant (grey area, Chi-square test P = 0.01). Upstream regions of all Ty insertions present in BY and absent from RM were analyzed similarly (black points), and their fractions of BYac SNEPs were averaged. The 1.3 fold enrichment in the 10 kb interval directly upstream the insertions was significant (grey area, Chi-square test P = 0.014). (C) Local correlation between H3K14ac SNEPs. Ten nucleosomes were interrogated upstream and downstream each SNEP (x-axis). For each one, cases where the nucleosome was a SNEP similar to the centered one (either BYac or RMac) were counted and divided by the total number of nucleosomes interrogated at that position (brown histogram). Control values were obtained from the same procedure applied after re-assigning SNEPs to random nucleosomes (grey histogram). (D) Density of H3K14 acetylation and SNEPs relative to gene position. Every gene was divided by segmenting the coding sequence in 10 bins (average bin size of 160 bp) and its upstream and downstream regions in 100 bp bins. For every gene and every bin, log(acBY/nucBY) was averaged across replicated experiments and across all probes matching intra-nucleosomal DNA to produce the top green profile. Similarly, averaged log(acRM/nucRM) values generated the top black profile. Here acBY and acRM refer to H3K14ac ChIP-CHIP experiments on BY and RM samples, respectively, while nucBY and nucRM refer to nucleosomal mapping experiments on BY and RM samples, respectively. Note that probes matching inter-nucleosome linkers do not contribute to the profiles, which are therefore corrected for nucleosome abundance. Bottom profiles were obtained by counting the fraction of BYac SNEPs (green) and RMac SNEPs (black) among all nucleosomes that overlapped at least partially the bin, and averaging these fractions across all genes.

    Techniques Used: Sequencing, Generated, Chromatin Immunoprecipitation

    SNEPs are not associated with transcriptional differences but are enriched at conserved regulatory sites. (A) Display from microarray data directly. Density plots representing the distribution of genes with respect to H3K14 acetylation differences (y-axis) and gene expression differences (x-axis). For every gene, three regions were considered as indicated above the panels. For each region, H3K14ac inter-strain difference was estimated as log(acBY/nucBY)−log(acRM/nucRM) (as defined in legend of Figure 2D ), averaged across replicated experiments and across all probes interrogating nucleosomal DNA of the region. Gene expression inter-strain differences are represented by their t -statistic computed from data of Brem et al. [20] . ρ, Pearson correlation coefficient. A similar picture was obtained when using fold change of expression instead of t -statistics ( Figure S10 ). (B) Display from SNEP locations. For every gene, the fraction of H3K14ac SNEPs correlated to expression was defined as the number of SNEPs acetylated in the strain with highest expression, divided by the total number of nucleosomes in the region. Curves represent the density distribution of genes according to this measure, from actual data (colored) and data where indexes of expression ratios were permuted (black). Colored curves are not significantly shifted to the right (as compared to black curves), ruling out association between SNEP and gene expression differences. (C) BYac but not RMac SNEPs are more abundant at conserved regulatory sites. Nucleosomes were divided in three categories: nucleosomes that covered entirely a conserved regulatory site from the list of MacIsaac et al. [35] , nucleosomes that did not contain such sites but were located in highly conserved non-coding sequences (see Methods ), and nucleosomes excluded from the first two categories. The fraction of SNEPs within each category is presented. Error bars, 95% C.I. The 3.2 and 2.6 fold enrichment at regulatory sites and other conserved regions, respectively, were highly significant ( P
    Figure Legend Snippet: SNEPs are not associated with transcriptional differences but are enriched at conserved regulatory sites. (A) Display from microarray data directly. Density plots representing the distribution of genes with respect to H3K14 acetylation differences (y-axis) and gene expression differences (x-axis). For every gene, three regions were considered as indicated above the panels. For each region, H3K14ac inter-strain difference was estimated as log(acBY/nucBY)−log(acRM/nucRM) (as defined in legend of Figure 2D ), averaged across replicated experiments and across all probes interrogating nucleosomal DNA of the region. Gene expression inter-strain differences are represented by their t -statistic computed from data of Brem et al. [20] . ρ, Pearson correlation coefficient. A similar picture was obtained when using fold change of expression instead of t -statistics ( Figure S10 ). (B) Display from SNEP locations. For every gene, the fraction of H3K14ac SNEPs correlated to expression was defined as the number of SNEPs acetylated in the strain with highest expression, divided by the total number of nucleosomes in the region. Curves represent the density distribution of genes according to this measure, from actual data (colored) and data where indexes of expression ratios were permuted (black). Colored curves are not significantly shifted to the right (as compared to black curves), ruling out association between SNEP and gene expression differences. (C) BYac but not RMac SNEPs are more abundant at conserved regulatory sites. Nucleosomes were divided in three categories: nucleosomes that covered entirely a conserved regulatory site from the list of MacIsaac et al. [35] , nucleosomes that did not contain such sites but were located in highly conserved non-coding sequences (see Methods ), and nucleosomes excluded from the first two categories. The fraction of SNEPs within each category is presented. Error bars, 95% C.I. The 3.2 and 2.6 fold enrichment at regulatory sites and other conserved regions, respectively, were highly significant ( P

    Techniques Used: Microarray, Expressing

    Nucleosome positioning in two unrelated natural S. cerevisiae strains. (A) Example of raw signals and nucleosome positioning inference in the region of the PER1 gene. Nucleosomal DNA was purified from each strains in triplicate, amplified linearly and hybridized to whole genome oligonucleotide Tiling arrays. Data were log-transformed and normalized using the quantile-quantile method and averaged across replicates to produce the probe-level signal intensities shown on the top panels. A Hidden Markov Model (HMM) similar to the one previously described [25] was applied to each strain independently to infer nucleosomal positioning (blue rectangles). Faded and plain colors represent ‘delocalized’ and ‘well-positioned’ nucleosomes, respectively, as defined previously [24] . Signal intensities are colored according to the HMM posterior probability to be within a nucleosome (cumulating delocalized and well-positioned). Nucleosome positions from the published atlas of Lee et al. [24] , who used a strain isogenic to BY, are indicated by green rectangles and are also faded when reported as ‘delocalized’. (B) Genes (rows) were clustered based on profiles of nucleosome occupancy at their promoter in the BY strain (see Methods ). Their order was then used to plot heatmaps of nucleosome occupancy around transcriptional start site in BY and RM, respectively, as well as expression divergence between the two strains (according to statistical significance at FDR 5% from the dataset of Brem et al. [20] ). Left curves represent mean occupancy profiles of the six main classes of promoters. (C) Absence of correlation between promoter occupancy and expression divergence. Each dot represents one gene. X-axis: inter-strain difference in expression measured as log2(RM/BY) from Brem et al. [20] . Y-axis: inter-strain dissimilarity of promoter occupancy profiles. For each promoter region, the RM/BY dissimilarity was estimated as 1 - R, where R is the Spearman correlation coefficient between the BY and RM occupancy profiles shown in (B). ρ: Spearman correlation between the resulting X and Y data.
    Figure Legend Snippet: Nucleosome positioning in two unrelated natural S. cerevisiae strains. (A) Example of raw signals and nucleosome positioning inference in the region of the PER1 gene. Nucleosomal DNA was purified from each strains in triplicate, amplified linearly and hybridized to whole genome oligonucleotide Tiling arrays. Data were log-transformed and normalized using the quantile-quantile method and averaged across replicates to produce the probe-level signal intensities shown on the top panels. A Hidden Markov Model (HMM) similar to the one previously described [25] was applied to each strain independently to infer nucleosomal positioning (blue rectangles). Faded and plain colors represent ‘delocalized’ and ‘well-positioned’ nucleosomes, respectively, as defined previously [24] . Signal intensities are colored according to the HMM posterior probability to be within a nucleosome (cumulating delocalized and well-positioned). Nucleosome positions from the published atlas of Lee et al. [24] , who used a strain isogenic to BY, are indicated by green rectangles and are also faded when reported as ‘delocalized’. (B) Genes (rows) were clustered based on profiles of nucleosome occupancy at their promoter in the BY strain (see Methods ). Their order was then used to plot heatmaps of nucleosome occupancy around transcriptional start site in BY and RM, respectively, as well as expression divergence between the two strains (according to statistical significance at FDR 5% from the dataset of Brem et al. [20] ). Left curves represent mean occupancy profiles of the six main classes of promoters. (C) Absence of correlation between promoter occupancy and expression divergence. Each dot represents one gene. X-axis: inter-strain difference in expression measured as log2(RM/BY) from Brem et al. [20] . Y-axis: inter-strain dissimilarity of promoter occupancy profiles. For each promoter region, the RM/BY dissimilarity was estimated as 1 - R, where R is the Spearman correlation coefficient between the BY and RM occupancy profiles shown in (B). ρ: Spearman correlation between the resulting X and Y data.

    Techniques Used: Purification, Amplification, Transformation Assay, Expressing

    Related Articles

    DNA Extraction:

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast
    Article Snippet: .. We followed the protocol of Liu et al. for both nucleosomal DNA isolation and ChIP, except that incubation time with micrococcal nuclease (Worthington Biochemical) prior to immunopurification was increased to 30 min at 37°C to obtain mononucleosomes. .. ChIP was performed using 3 µl of anti-H3K14Ac polyclonal antibody (Upstate, 07–353).

    Incubation:

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast
    Article Snippet: .. We followed the protocol of Liu et al. for both nucleosomal DNA isolation and ChIP, except that incubation time with micrococcal nuclease (Worthington Biochemical) prior to immunopurification was increased to 30 min at 37°C to obtain mononucleosomes. .. ChIP was performed using 3 µl of anti-H3K14Ac polyclonal antibody (Upstate, 07–353).

    Chromatin Immunoprecipitation:

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast
    Article Snippet: .. We followed the protocol of Liu et al. for both nucleosomal DNA isolation and ChIP, except that incubation time with micrococcal nuclease (Worthington Biochemical) prior to immunopurification was increased to 30 min at 37°C to obtain mononucleosomes. .. ChIP was performed using 3 µl of anti-H3K14Ac polyclonal antibody (Upstate, 07–353).

    Immu-Puri:

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast
    Article Snippet: .. We followed the protocol of Liu et al. for both nucleosomal DNA isolation and ChIP, except that incubation time with micrococcal nuclease (Worthington Biochemical) prior to immunopurification was increased to 30 min at 37°C to obtain mononucleosomes. .. ChIP was performed using 3 µl of anti-H3K14Ac polyclonal antibody (Upstate, 07–353).

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    Worthington Biochemical nucleosomal dna isolation
    Abundance and genomic distribution of Single Nucleosome Epi-Polymorphisms. (A) The fraction of nucleosomes that were called SNEP at FDR = 0.0001 was computed in every 1Kb-segment along each chromosome. Density ranged from 0 (white) to 100% (red). Grey denotes regions where nucleosomes could not be aligned. (B) Enrichment of H3K14ac SNEPs upstream Ty insertions and rDNA repeats. The fraction of BYac SNEPs among all nucleosomes was counted in 10 kb intervals upstream the rDNA region (brown triangles). The 7 fold enrichment of BYac SNEPs in the first 10 kb was significant (grey area, Chi-square test P = 0.01). Upstream regions of all Ty insertions present in BY and absent from RM were analyzed similarly (black points), and their fractions of BYac SNEPs were averaged. The 1.3 fold enrichment in the 10 kb interval directly upstream the insertions was significant (grey area, Chi-square test P = 0.014). (C) Local correlation between H3K14ac SNEPs. Ten nucleosomes were interrogated upstream and downstream each SNEP (x-axis). For each one, cases where the nucleosome was a SNEP similar to the centered one (either BYac or RMac) were counted and divided by the total number of nucleosomes interrogated at that position (brown histogram). Control values were obtained from the same procedure applied after re-assigning SNEPs to random nucleosomes (grey histogram). (D) Density of H3K14 acetylation and SNEPs relative to gene position. Every gene was divided by segmenting the coding sequence in 10 bins (average bin size of 160 bp) and its upstream and downstream regions in 100 bp bins. For every gene and every bin, log(acBY/nucBY) was averaged across replicated experiments and across all probes matching <t>intra-nucleosomal</t> <t>DNA</t> to produce the top green profile. Similarly, averaged log(acRM/nucRM) values generated the top black profile. Here acBY and acRM refer to H3K14ac ChIP-CHIP experiments on BY and RM samples, respectively, while nucBY and nucRM refer to nucleosomal mapping experiments on BY and RM samples, respectively. Note that probes matching inter-nucleosome linkers do not contribute to the profiles, which are therefore corrected for nucleosome abundance. Bottom profiles were obtained by counting the fraction of BYac SNEPs (green) and RMac SNEPs (black) among all nucleosomes that overlapped at least partially the bin, and averaging these fractions across all genes.
    Nucleosomal Dna Isolation, supplied by Worthington Biochemical, used in various techniques. Bioz Stars score: 85/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/nucleosomal dna isolation/product/Worthington Biochemical
    Average 85 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    nucleosomal dna isolation - by Bioz Stars, 2020-08
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    Abundance and genomic distribution of Single Nucleosome Epi-Polymorphisms. (A) The fraction of nucleosomes that were called SNEP at FDR = 0.0001 was computed in every 1Kb-segment along each chromosome. Density ranged from 0 (white) to 100% (red). Grey denotes regions where nucleosomes could not be aligned. (B) Enrichment of H3K14ac SNEPs upstream Ty insertions and rDNA repeats. The fraction of BYac SNEPs among all nucleosomes was counted in 10 kb intervals upstream the rDNA region (brown triangles). The 7 fold enrichment of BYac SNEPs in the first 10 kb was significant (grey area, Chi-square test P = 0.01). Upstream regions of all Ty insertions present in BY and absent from RM were analyzed similarly (black points), and their fractions of BYac SNEPs were averaged. The 1.3 fold enrichment in the 10 kb interval directly upstream the insertions was significant (grey area, Chi-square test P = 0.014). (C) Local correlation between H3K14ac SNEPs. Ten nucleosomes were interrogated upstream and downstream each SNEP (x-axis). For each one, cases where the nucleosome was a SNEP similar to the centered one (either BYac or RMac) were counted and divided by the total number of nucleosomes interrogated at that position (brown histogram). Control values were obtained from the same procedure applied after re-assigning SNEPs to random nucleosomes (grey histogram). (D) Density of H3K14 acetylation and SNEPs relative to gene position. Every gene was divided by segmenting the coding sequence in 10 bins (average bin size of 160 bp) and its upstream and downstream regions in 100 bp bins. For every gene and every bin, log(acBY/nucBY) was averaged across replicated experiments and across all probes matching intra-nucleosomal DNA to produce the top green profile. Similarly, averaged log(acRM/nucRM) values generated the top black profile. Here acBY and acRM refer to H3K14ac ChIP-CHIP experiments on BY and RM samples, respectively, while nucBY and nucRM refer to nucleosomal mapping experiments on BY and RM samples, respectively. Note that probes matching inter-nucleosome linkers do not contribute to the profiles, which are therefore corrected for nucleosome abundance. Bottom profiles were obtained by counting the fraction of BYac SNEPs (green) and RMac SNEPs (black) among all nucleosomes that overlapped at least partially the bin, and averaging these fractions across all genes.

    Journal: PLoS Genetics

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast

    doi: 10.1371/journal.pgen.1000913

    Figure Lengend Snippet: Abundance and genomic distribution of Single Nucleosome Epi-Polymorphisms. (A) The fraction of nucleosomes that were called SNEP at FDR = 0.0001 was computed in every 1Kb-segment along each chromosome. Density ranged from 0 (white) to 100% (red). Grey denotes regions where nucleosomes could not be aligned. (B) Enrichment of H3K14ac SNEPs upstream Ty insertions and rDNA repeats. The fraction of BYac SNEPs among all nucleosomes was counted in 10 kb intervals upstream the rDNA region (brown triangles). The 7 fold enrichment of BYac SNEPs in the first 10 kb was significant (grey area, Chi-square test P = 0.01). Upstream regions of all Ty insertions present in BY and absent from RM were analyzed similarly (black points), and their fractions of BYac SNEPs were averaged. The 1.3 fold enrichment in the 10 kb interval directly upstream the insertions was significant (grey area, Chi-square test P = 0.014). (C) Local correlation between H3K14ac SNEPs. Ten nucleosomes were interrogated upstream and downstream each SNEP (x-axis). For each one, cases where the nucleosome was a SNEP similar to the centered one (either BYac or RMac) were counted and divided by the total number of nucleosomes interrogated at that position (brown histogram). Control values were obtained from the same procedure applied after re-assigning SNEPs to random nucleosomes (grey histogram). (D) Density of H3K14 acetylation and SNEPs relative to gene position. Every gene was divided by segmenting the coding sequence in 10 bins (average bin size of 160 bp) and its upstream and downstream regions in 100 bp bins. For every gene and every bin, log(acBY/nucBY) was averaged across replicated experiments and across all probes matching intra-nucleosomal DNA to produce the top green profile. Similarly, averaged log(acRM/nucRM) values generated the top black profile. Here acBY and acRM refer to H3K14ac ChIP-CHIP experiments on BY and RM samples, respectively, while nucBY and nucRM refer to nucleosomal mapping experiments on BY and RM samples, respectively. Note that probes matching inter-nucleosome linkers do not contribute to the profiles, which are therefore corrected for nucleosome abundance. Bottom profiles were obtained by counting the fraction of BYac SNEPs (green) and RMac SNEPs (black) among all nucleosomes that overlapped at least partially the bin, and averaging these fractions across all genes.

    Article Snippet: We followed the protocol of Liu et al. for both nucleosomal DNA isolation and ChIP, except that incubation time with micrococcal nuclease (Worthington Biochemical) prior to immunopurification was increased to 30 min at 37°C to obtain mononucleosomes.

    Techniques: Sequencing, Generated, Chromatin Immunoprecipitation

    SNEPs are not associated with transcriptional differences but are enriched at conserved regulatory sites. (A) Display from microarray data directly. Density plots representing the distribution of genes with respect to H3K14 acetylation differences (y-axis) and gene expression differences (x-axis). For every gene, three regions were considered as indicated above the panels. For each region, H3K14ac inter-strain difference was estimated as log(acBY/nucBY)−log(acRM/nucRM) (as defined in legend of Figure 2D ), averaged across replicated experiments and across all probes interrogating nucleosomal DNA of the region. Gene expression inter-strain differences are represented by their t -statistic computed from data of Brem et al. [20] . ρ, Pearson correlation coefficient. A similar picture was obtained when using fold change of expression instead of t -statistics ( Figure S10 ). (B) Display from SNEP locations. For every gene, the fraction of H3K14ac SNEPs correlated to expression was defined as the number of SNEPs acetylated in the strain with highest expression, divided by the total number of nucleosomes in the region. Curves represent the density distribution of genes according to this measure, from actual data (colored) and data where indexes of expression ratios were permuted (black). Colored curves are not significantly shifted to the right (as compared to black curves), ruling out association between SNEP and gene expression differences. (C) BYac but not RMac SNEPs are more abundant at conserved regulatory sites. Nucleosomes were divided in three categories: nucleosomes that covered entirely a conserved regulatory site from the list of MacIsaac et al. [35] , nucleosomes that did not contain such sites but were located in highly conserved non-coding sequences (see Methods ), and nucleosomes excluded from the first two categories. The fraction of SNEPs within each category is presented. Error bars, 95% C.I. The 3.2 and 2.6 fold enrichment at regulatory sites and other conserved regions, respectively, were highly significant ( P

    Journal: PLoS Genetics

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast

    doi: 10.1371/journal.pgen.1000913

    Figure Lengend Snippet: SNEPs are not associated with transcriptional differences but are enriched at conserved regulatory sites. (A) Display from microarray data directly. Density plots representing the distribution of genes with respect to H3K14 acetylation differences (y-axis) and gene expression differences (x-axis). For every gene, three regions were considered as indicated above the panels. For each region, H3K14ac inter-strain difference was estimated as log(acBY/nucBY)−log(acRM/nucRM) (as defined in legend of Figure 2D ), averaged across replicated experiments and across all probes interrogating nucleosomal DNA of the region. Gene expression inter-strain differences are represented by their t -statistic computed from data of Brem et al. [20] . ρ, Pearson correlation coefficient. A similar picture was obtained when using fold change of expression instead of t -statistics ( Figure S10 ). (B) Display from SNEP locations. For every gene, the fraction of H3K14ac SNEPs correlated to expression was defined as the number of SNEPs acetylated in the strain with highest expression, divided by the total number of nucleosomes in the region. Curves represent the density distribution of genes according to this measure, from actual data (colored) and data where indexes of expression ratios were permuted (black). Colored curves are not significantly shifted to the right (as compared to black curves), ruling out association between SNEP and gene expression differences. (C) BYac but not RMac SNEPs are more abundant at conserved regulatory sites. Nucleosomes were divided in three categories: nucleosomes that covered entirely a conserved regulatory site from the list of MacIsaac et al. [35] , nucleosomes that did not contain such sites but were located in highly conserved non-coding sequences (see Methods ), and nucleosomes excluded from the first two categories. The fraction of SNEPs within each category is presented. Error bars, 95% C.I. The 3.2 and 2.6 fold enrichment at regulatory sites and other conserved regions, respectively, were highly significant ( P

    Article Snippet: We followed the protocol of Liu et al. for both nucleosomal DNA isolation and ChIP, except that incubation time with micrococcal nuclease (Worthington Biochemical) prior to immunopurification was increased to 30 min at 37°C to obtain mononucleosomes.

    Techniques: Microarray, Expressing

    Nucleosome positioning in two unrelated natural S. cerevisiae strains. (A) Example of raw signals and nucleosome positioning inference in the region of the PER1 gene. Nucleosomal DNA was purified from each strains in triplicate, amplified linearly and hybridized to whole genome oligonucleotide Tiling arrays. Data were log-transformed and normalized using the quantile-quantile method and averaged across replicates to produce the probe-level signal intensities shown on the top panels. A Hidden Markov Model (HMM) similar to the one previously described [25] was applied to each strain independently to infer nucleosomal positioning (blue rectangles). Faded and plain colors represent ‘delocalized’ and ‘well-positioned’ nucleosomes, respectively, as defined previously [24] . Signal intensities are colored according to the HMM posterior probability to be within a nucleosome (cumulating delocalized and well-positioned). Nucleosome positions from the published atlas of Lee et al. [24] , who used a strain isogenic to BY, are indicated by green rectangles and are also faded when reported as ‘delocalized’. (B) Genes (rows) were clustered based on profiles of nucleosome occupancy at their promoter in the BY strain (see Methods ). Their order was then used to plot heatmaps of nucleosome occupancy around transcriptional start site in BY and RM, respectively, as well as expression divergence between the two strains (according to statistical significance at FDR 5% from the dataset of Brem et al. [20] ). Left curves represent mean occupancy profiles of the six main classes of promoters. (C) Absence of correlation between promoter occupancy and expression divergence. Each dot represents one gene. X-axis: inter-strain difference in expression measured as log2(RM/BY) from Brem et al. [20] . Y-axis: inter-strain dissimilarity of promoter occupancy profiles. For each promoter region, the RM/BY dissimilarity was estimated as 1 - R, where R is the Spearman correlation coefficient between the BY and RM occupancy profiles shown in (B). ρ: Spearman correlation between the resulting X and Y data.

    Journal: PLoS Genetics

    Article Title: Natural Single-Nucleosome Epi-Polymorphisms in Yeast

    doi: 10.1371/journal.pgen.1000913

    Figure Lengend Snippet: Nucleosome positioning in two unrelated natural S. cerevisiae strains. (A) Example of raw signals and nucleosome positioning inference in the region of the PER1 gene. Nucleosomal DNA was purified from each strains in triplicate, amplified linearly and hybridized to whole genome oligonucleotide Tiling arrays. Data were log-transformed and normalized using the quantile-quantile method and averaged across replicates to produce the probe-level signal intensities shown on the top panels. A Hidden Markov Model (HMM) similar to the one previously described [25] was applied to each strain independently to infer nucleosomal positioning (blue rectangles). Faded and plain colors represent ‘delocalized’ and ‘well-positioned’ nucleosomes, respectively, as defined previously [24] . Signal intensities are colored according to the HMM posterior probability to be within a nucleosome (cumulating delocalized and well-positioned). Nucleosome positions from the published atlas of Lee et al. [24] , who used a strain isogenic to BY, are indicated by green rectangles and are also faded when reported as ‘delocalized’. (B) Genes (rows) were clustered based on profiles of nucleosome occupancy at their promoter in the BY strain (see Methods ). Their order was then used to plot heatmaps of nucleosome occupancy around transcriptional start site in BY and RM, respectively, as well as expression divergence between the two strains (according to statistical significance at FDR 5% from the dataset of Brem et al. [20] ). Left curves represent mean occupancy profiles of the six main classes of promoters. (C) Absence of correlation between promoter occupancy and expression divergence. Each dot represents one gene. X-axis: inter-strain difference in expression measured as log2(RM/BY) from Brem et al. [20] . Y-axis: inter-strain dissimilarity of promoter occupancy profiles. For each promoter region, the RM/BY dissimilarity was estimated as 1 - R, where R is the Spearman correlation coefficient between the BY and RM occupancy profiles shown in (B). ρ: Spearman correlation between the resulting X and Y data.

    Article Snippet: We followed the protocol of Liu et al. for both nucleosomal DNA isolation and ChIP, except that incubation time with micrococcal nuclease (Worthington Biochemical) prior to immunopurification was increased to 30 min at 37°C to obtain mononucleosomes.

    Techniques: Purification, Amplification, Transformation Assay, Expressing