03 Combinatorial patterns of histone acetylations and methylations in the human genome
Combinatorial patterns of histone acetylations and methylations in the human genome
Zhibin Wang 1,5,Chongzhi Zang 2,5,Jeffrey A Rosenfeld 3–5,Dustin E Schones 1,Artem Barski 1,
Suresh Cuddapah 1,Kairong Cui 1,Tae-Young Roh 1,Weiqun Peng 2,Michael Q Zhang 3&Keji Zhao 1
Histones are characterized by numerous posttranslational modi?cations that in?uence gene transcription 1,2.However,because of the lack of global distribution data in higher eukaryotic systems 3,the extent to which gene-speci?c
combinatorial patterns of histone modi?cations exist remains to be determined.Here,we report the patterns derived from the analysis of 39histone modi?cations in human CD4+T cells.Our data indicate that a large number of patterns are associated with promoters and enhancers.In particular,we identify a common modi?cation module consisting of 17modi?cations detected at 3,286promoters.These modi?cations tend to colocalize in the genome and correlate with each other at an individual nucleosome level.Genes associated with this module tend to have higher expression,and addition of more modi?cations to this module is associated with further increased expression.Our data suggest that these histone modi?cations may act cooperatively to prepare chromatin for transcriptional activation.
Histones are subject to numerous covalent modi?cations,including methylation and acetylation,that occur mainly at their N-terminal tails and that can affect transcription of genes 1,2,4,5.Extensive studies have established that histone acetylation is primarily associated with gene activation,whereas methylation,depending on its position and state,is associated with either repression or activation 5–10.Various models,including the histone code,the signaling network and the charge neutralization model,have been proposed to account for the function of histone modi?cations 11–14.The histone code hypothesis suggests that multiple histone modi?cations act in a combinatorial fashion to specify distinct chromatin states.However,the extent to which combinatorial patterns of histone modi?cations exist in the genome is unknown.We have now produced genome-wide maps of 18histone acetylations (H2AK5ac,H2AK9ac,H2BK5ac,H2BK12ac,H2BK20ac,H2BK120ac,H3K4ac,H3K9ac,H3K14ac,H3K18ac,H3K23ac,H3K27ac,H3K36ac,H4K5ac,H4K8ac,H4K12ac,H4K16ac and H4K91ac)at an individual nucleosome
level (see Methods section for data deposition),and analyzed these together with the H2A.Z and 19histone methylation maps we generated previously 15.
We ?rst systematically evaluated the speci?cities of the acetylation antibodies used in this study (Supplementary Methods ,Supplemen-tary Table 1and Supplementary Fig.1online).Competition assays using modi?ed and unmodi?ed peptides indicated that most anti-bodies showed speci?city for the desired acetylation (Supplementary Fig.1).The H4K5ac and H3K4ac antibodies demonstrated some crossreactivity toward H4K12ac and H3K9ac,respectively,in a con-dition with excess competitor peptides (Supplementary Fig.1d ,j ),and the H4K91ac antibody did not work in protein blotting.Thus,the results for these modi?cations should be interpreted with caution.Of note,H2AK9ac has not been reported previously,and H3K4ac has only been identi?ed by mass-spectrometry analysis and has not been previously characterized functionally 16.Protein blotting indicated that these acetylations indeed exist in human CD4+T cells (Supplemen-tary Fig.1j ,o ).We previously analyzed the genome-wide distribution of H2BK5me1(ref.15),and protein blotting data in this study indicated that this methylation exists in human cells and that the H2BK5me1antibody is speci?c (Supplementary Fig.1p ).
Next,we determined the genomic distribution patterns of these histone acetylations using the ChIP-Seq technique 15,which we pre-viously con?rmed yields H3K4me3distribution patterns similar to those generated by the ChIP-SAGE (GMAT)strategy 15,17.T o validate the histone acetylation data,we compared the genomic distribution patterns of the K9/K14-diacetylated histone H3from ChIP-SAGE 18with the separately examined patterns of H3K9ac and H3K14ac in this study (Supplementary Fig.2online).We found that the ChIP-Seq acetylation data are reliable and that the previously observed H3K9/K14diacetylation patterns could be primarily attributed to H3K9acetylation.
T o examine the distribution of the histone acetylations at different functional regions,we generated composite pro?les for the region spanning the transcription start sites (TSSs;Fig.1a –c and Supple-mentary Fig.3online)or the entire gene bodies and extending 5kb
Received 19December 2007;accepted 1April 2008;published online 15June 2008;doi:10.1038/ng.154
1Laboratory
of Molecular Immunology,National Heart,Lung,and Blood Institute,US National Institutes of Health,Bethesda,Maryland 20892,USA.2Department of
Physics,The George Washington University,Washington,D.C.20052,USA.3Cold Spring Harbor Laboratory,Cold Spring Harbor,New York 11724,USA.4Department of Biology,New York University,New York,New York 10003,USA.5These authors contributed equally to this work.Correspondence should be addressed to K.Z.(zhaok@https://www.sodocs.net/doc/1c16128467.html,).
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upstream and 5kb downstream for groups of 1,000genes according to their expression (Fig.1d –f and Supplementary Fig.4online).We found that all acetylations positively correlated with gene expression,consistent with their involvement in tran-scriptional activation.However,our data
indicate that different acetylations may target
different regions of genes.For example,H2AK9ac,H2BK5ac,H3K9ac,H3K18ac,H3K27ac,H3K36ac and H4K91ac are mainly
located in the region surrounding the TSS
(Fig.1d and Supplementary Fig.4),whereas
H2BK12ac,H2BK20ac,H2BK120ac,H3K4ac,
H4K5ac,H4K8ac,H4K12ac and H4K16ac are elevated in the promoter and transcribed regions of active genes (Fig.1f and Supplementary Fig.4).These results are consistent with previous reports that speci?c
*
H3K4me3*
H3K4me2*
H3K4me1
*
H3K4ac H3K27me3H3K27me2*
H3K27me1*
H3K27ac H3K9me3H3K9me2
*
H3K9me1
*
H3K9ac *
H3K79me3*
H3K79me2*
H3K79me1H3R2me2
H3R2me1
H3K36me3H3K36me1
*
H3K36ac H4K20me3
H4K20me1H2BK5me1*
H2BK5ac *
H3K14ac *
H3K18ac *
H3K23ac
*
H4K5ac *
H4K8ac *
H4K12ac *
H4K16ac
*
H4K91ac *
H2BK12ac *
H2BK20ac *
H2BK120ac H2AK5ac H2AK9ac
*
H2A.Z H4R3me2H3K9ac
H3K9ac
N o r m a l i z e d c o u n t s
N o r m a l i z e d c o u n t s
N o r m a l i z e d c o u n t s
Position relative to TSS
Position relative to TSS
N o r m a l i z e d c o u n t s
N o r m a l i z e d c o u n t s
N o r m a l i z e d c o u n t s
H4K12ac
H4K12ac
High Medium Low Silent
High Medium Low Silent
High Medium Low Silent
a
d
g
e
1.2E–07
1E–07
8E–086E–084E–082E–08
–2,000–1,000
1,0002,000
00
c
f
1.6E–081.4E–081E–081.2E–088E–096E–092E–09
4E–09–10,000–5,0005,00010,000
00
Position relative to TSS
H3K23ac
b
1.4E–081.2E–088E–091E–086E–092E–09
4E–09–10,000
–5,000
5,000
10,000
H3K23ac
High Silent
High Silent
High Silent
96Chr20:
3461186515543
532213125136625
61642935415547104647812359222410
439
45250000
45300000
45350000
45400000
45450000
ZMYND8
5 k b u p 2.5 k b u p t x S t a r t 0.10.20.30.40.500.600.700.800.90t x E n d 2.5 k b d o w n 5 k b d o w n
5 k b u p 2.5 k b u p t x S t a r t 0.10.20.30.40.500.600.700.800.90t x E n d 2.5 k b d o w n 5 k b d o w n
5 k b u p 2.5 k b u p t x S t a r t 0.10.20.30.40.500.600.700.800.90t x E n d 2.5 k b d o w n 5 k b d o w n
Figure 1Three distribution patterns of histone acetylations.(a –c )Normalized tag counts of histone acetylation signals
surrounding the TSS were indicated for highly active,intermediately active (two levels)and silent genes.Each group represents 1,000genes with similar expression,as described in Methods.(d –f )Normalized tag counts of histone acetylation signals of 1,000highly active or silent genes across the gene bodies.The plots extend 5kb 5￠and 3￠of the genic regions (see Methods).txStart,transcription start site;txEnd,transcription end.(g )Chromatin modi?cation patterns at the ZMYND8(PRKCBP1)gene locus.Signi?cant modi?cations in the –1kb to +1kb region surrounding the TSS (P o 10à7;highlighted in red)are indicated by asterisks on the left.
10,000
10,0001,0001,00010010090807060504030201010
100
1,00010,000
1
0100
10
101N u m b
e r o
f c o m b i n a t o r i a l p a t t e r n s
P e r c e n t a g e o f g e n e s w i t h h i g h e r e x p r e s s i o n
F o l d c h a n g e i n e x p r e s s i o n (l o g 2)
B,H2AK9ac,H2BK5me1,H3K79me1,me2,me3,H4K12ac,H4K16ac,H4K20me1:62
B,H2AK9ac,H2BK5me1,H3K79me1,me2,me3,H4K16ac,H4K20me1:68
B,H2BK5me1,H3K79me1,me2,me3,H4K16ac,H4K20me1:74
B,H4K16ac:67
B:64
H3K36me3:135
H2AZ,H3K4me1,me2,me3,H3K9me1,H3K27me3:77
H2AZ,H3K4me2,me3,H3K9me1,H3K27me3:70
H2AZ,H3K4me3,H3K27me3:74
H3K4me3,H3K27me3:167
H3K4me3:85H3K27me3:630No modification:2007
All genes:12541
21.510.50–0.5–1–1.5
H 2A K 5a c H 2B K 5a c H 2B K 5m e 1H 2B K 12a c H 2B K 20a c H 2B K 120a c H 3K 4a c H 3K 4m e 1H 3K 4m e 2H 3K 4m e 3H 3K 9a c H 3K 9m e 1H 3K 9m e 2H 3K 9m e 3H 3K 14a c H 3K 18a c H 3K 23a c H 3K 27a c H 3K 27m e 1H 3K 27m e 2H 3K 27m e 3H 3K 36a c H 3K 36m e 1H 3K 36m e 3H 3K 79m e 1H 3K 79m e 2H 3K 79m e 3H 3R 2m e 1H 3R 2m e 2H 4K 5a c H 4K 8a c H 4K 12a c H 4K 16a c H 4K 20m e 1H 4K 20m e 3H 4K 91a c
H 2A K 9a c H 2A .Z 1
Number of genes associated
with the same pattern
Gene expression
a b
c
Figure 2Patterns of histone modi?cations
associated with promoters.(a )Patterns of histone modi?cations at promoters.The y axis indicates the number of patterns of 39histone
modi?cations (see Methods),and the x axis indicates the number of promoters associated with each pattern.(b )Correlation of gene expression with the thirteen most prevalent modi?cation patterns.B,the 17-modi?cation backbone;All,all genes.The number of
promoters within each pattern is also indicated.The gene expression is determined using DNA microarrays.See Figure 4a for the composition of ‘backbone’.(c )Correlation of each modi?cation with gene expression.The changes in gene
expression (log 2)are calculated by comparing the average expression of the subsets of genes with or without a particular modi?cation.
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histone acetyl transferases (HATs)can associate with different regions of genes.For example,PCAF associates with the elongation-competent RNA Pol II,whereas p300interacts with the initiation-competent RNA Pol II (ref.19).Additionally,depletion of GCN5or PCAF,but not CBP or p300,affects H4K8ac and H3K14ac 20.The distribution patterns of these histone acetylations and histone methylations are exempli?ed by the genomic locus for ZMYND8(also
known as PRKCBP1),which is expressed in CD4+T cells (Fig.1g ).The promoter region (highlighted in red),which was de?ned as a 2-kb region surrounding the TSS,is associated with 25modi?cations (P o 10à7).
T o identify the patterns of histone modi?cations in an unbiased way,we examined each of the 12,541gene promoters for association with each of the 18acetylations,19methylations and H2A.Z.Of the possible patterns,only a small fraction exists at promoters.Of 4,339detected patterns,1,174are associated with
multiple genes and 3,165with only one gene each (Fig.2a ).The 13most prevalent patterns are each associated with more than 62genes.We next examined the expression of genes in these patterns,using the mean expression of
all genes as a reference (Fig.2b ).It seems that we can roughly classify these top patterns into three classes (I,II and III in Fig.2b )accord-ing to expression.Four of six patterns in class I contain H3K27me3and correlate with low expression.These patterns also contain
H3K4me1/2/3,H3K9me1and H2A.Z but
no acetylations.The patterns containing only H3K4me3or no modi?cation also belong to this class.Class II contains H3K36me3or a modi?cation backbone con-sisting of 17modi?cations (as discussed below),or the backbone plus H4K16ac,which correlates with intermediate gene expression.Class III shows the highest expres-sion,and it includes H2BK5me1,H4K16ac,H4K20me1and H3K79me1/2/3in addition to the modi?cation backbone (Fig.2b ).Our Gene Ontology analysis suggests that genes
involved in cellular physiology and metabolism are enriched in the active class III patterns,consistent with their house-keeping roles (data not shown).In contrast,many genes involved in development,cell–cell signaling and synaptic transmission are enriched in the inactive class I patterns,consistent with their not being required for mature T-cell function.
T o correlate each modi?cation with gene expression,we compared the average gene expression with or without each modi?cation
(Fig.2c ).H3K27me3was among a group of repressive marks also including H3K27me2,H3K9me2,H3K9me3and H4K20me3,whereas
most other modi?cations correlated with activation.Although the modi?cation patterns do not uniquely determine the extent of expression,the H3K79me3and H2BK5ac modi?cations showed weak correlation with expression within a modi?cation pattern (Supplementary Fig.5
online).
Chr10:
6145000
6150000
6155000
6160000
66810000
66830000
66850000
184153984510233151376554783691555178847610612141231632H3K4me3H3K4me2*
H3K4me1IL2RA
CD28RE
CNS22
IFNG
H3K27me3H3K27me2*
H3K27me1H3K27ac H3K9me3H3K9me2*
H3K9me1H3K79me3H3K79me2H3K79me1H3R2me2H3R2me1H3K36me3H3K36me1H4K20me3H4K20me1*
H2BK5me1H2BK5ac H4R3me2H3K14ac *
H3K18ac *
H3K23ac *
H4K5ac *
H4K8ac H4K12ac H4K16ac *
H4K91ac H2BK12ac H2BK20ac *
H2BK120ac *
H2AK5ac H2AK9ac *
H2A.Z H3K36ac H3K9ac
H3K4ac
Chr12:251130445617512322351155
435
63791610174647578323
45*
H3K4me3H3K4me2*
H3K4me1H3K27me3H3K27me2*
H3K27me1*H3K27ac H3K9me3H3K9me2*
H3K9me1H3K79me3H3K79me2H3K79me1H3R2me2H3R2me1H3K36me3H3K36me1H4K20me3H4K20me1H2BK5me1*
H2BK5ac
H4R3me2
H3K14ac
*
H3K18ac
*
H3K23ac
*
H4K5ac
*
H4K8ac
H4K12ac
* H4K16ac * H4K91ac * H2BK12ac * H2BK20ac *
H2BK120ac H2AK5ac
H2AK9ac
*
H2A.Z
*
H3K36ac
H3K9ac *
H3K4ac a
c d e b
0.35F r a c t i o n s o f e n h a n c e r s
0.300.250.200.150.10
0.05
10,000
10,0001,0001,000Number of enhancers associated with one pattern Enhancers-associated gene expression
P e r c e n t a g e o f e n h a n c e r s w i t h h i g h e r e x p r e s s i o n
N u m b e r o f c o m b i n a t o r i a l p a t t e r n s
10010010
10110
H 2A K 5a c H 2A K 9a c H 2B K 5a c H 2B K 5m e 1H 2B K 12a c H 2B K 20a c H 2B K 120a c H 3K 4a c H 3K 4m e 1H 3K 4m e 2H 3K 4m e 3H 3K 9m e 1H 3K 9m e 2H 3K 9m e 3H 3K 14a c H 3K 18a c H 3K 23a c H 3K 27a c H 3K 27m e 1H 3K 27m e 2H 3K 36m e 1H 3K 36m e 3H 3K 79m e 1H 3K 79m e 2H 3K 79m e 3H 3R 2m e 1H 3R 2m e 2H 4K 5a c H 4K 8a c H 4K 12a c H 4K 16a c H 4K 91a c
H 4K 20m e 1H 4K 20m e 3H 3K 27m e 3H 3K 36a c H 3K 9a c H 2A .Z 100908070
60
50403020
10
1101001,00010,000H2AZ, H3K4me1, H3K4me2, H3K4me3, H3K9me1: 21
H2AZ, H3K4me2, H3K4me3, H3K9me1: 37
H2AZ, H3K4me1: 36 H3K4me1, H4K20me1: 21H3K4me1: 64
H3K4me3: 34
H3K27me3: 65
H3K36me3: 41
H4K20me1: 42H2AK5ac: 63
No modification: 1,817
All enhancers: 4,179
H2AZ: 67
H2AZ, H3K4me3: 20Figure 3Patterns of histone modi?cations at
enhancers.(a )The histone modi?cation pattern at the CD28RE enhancer (highlighted in red)of the IL2RA gene.Signi?cant modi?cations are indicated by asterisks on the left.(b )Histone modi?cation patterns at the IFNG gene and its downstream enhancer,CNS22,are shown.
Signi?cant modi?cations at CNS22are indicated by asterisks on the left.(c )The fractions of enhancers associated with each of the 38modi?cations.(d )Patterns of histone
modi?cations at 4,179DNase hypersensitive
sites.The y axis indicates the number of patterns,and x axis indicates the number of hypersensitive sites associated with each pattern.(e )Correlation analysis of gene expression with the ten largest modi?cation patterns by assigning an enhancer to the TSS of the nearest known gene.All,all DNase I hypersensitive sites.The number of hypersensitive sites associated with each pattern is indicated.
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Enhancers of transcription have been identi?ed using modi?cation patterns 15,18,21,22.We previously found that all three H3K4methyla-tion states and H2A.Z were detected at enhancers 15.However,others identi?ed enhancers associated with high H3K4me1but very low H3K4me3(refs.21,23).These results suggest that there are distinctive modi?cation patterns at different enhancers.Indeed,the CD28response element (CD28RE)enhancer 24of the IL2RA gene is asso-ciated with 12modi?cations (P o 10à7),whereas 18modi?cations are detected at the CNS22enhancer 25of the IFNG gene (Fig.3a ,b ).We next examined histone modi?cation patterns at 4,179intergenic DNase I hypersensitive sites 26,excluding those in promoter regions and miRNA genes,as a set of putative enhancers.As compared to the whole genome,these putative enhancer regions showed an elevated sum of all modi?cations (Supplementary Fig.6a online).Each of H2A.Z,H3K4me1,H3K4me2,H3K4me3,H3K9me1and H3K18ac associated with more than 20%of enhancers (Fig.3c ).Several modi?cations were associated with very few enhancers,including both repressive marks (H3K9me2,H3K9me3and H3K27me2)and activating marks (H2AK9ac and H3K14ac)(Fig.3c ).Among the total of 1,389patterns,195are associated with multiple hypersensitive sites and 1,194associated with a distinct hypersensitive site (Fig.3d ).The top 12patterns include those associated with only one modi?cation or combinations of H3K4me1,H3K4me2,H3K4me3,H3K9me1,H3K36me3,H4K20me1and H2A.Z (Fig.3e ).No modi?cations were detected at 1,817hypersensitive sites,perhaps indicating nucleo-some-free regions or insuf?cient sequencing.These data suggest that there are multiple patterns associated with enhancers.However,we did not ?nd signi?cant correlations between modi?cation patterns at enhancers and gene expression (Fig.3e and Methods).
These results suggest that multiple histone modi?cations can associate with critical regulatory elements of transcription.T o identify modi?cations that may function together to modify chromatin,we searched for robust modi?cation features at promoter regions.This analysis revealed a modi?cation ‘backbone’consisting of 17modi?ca-tions (H2A.Z,H2BK5ac,H2BK12ac,H2BK20ac,H2BK120ac,H3K4ac,H3K4me1,H3K4me2,H3K4me3,H3K9ac,H3K9me1,H3K18ac,H3K27ac,H3K36ac,H4K5ac,H4K8ac and H4K91ac)that were present in 821different patterns and associated with a total of 3,286genes.T o examine whether the modi?cations in this group tend to coexist,we counted the promoters missing one of these modi?ca-tions.Notably,only a small number of promoters (0–393)were identi?ed as missing one of these 17modi?cations,as compared to 3,286promoters that had all 17modi?cations (Fig.4a ).This back-bone of modi?cations is robust against perturbations (Supplementary Fig.6b ).Furthermore,none of the promoters possessing the backbone had signi?cant levels of the repressive mark H3K27me3.We veri?ed the existence of the ‘backbone’modi?cation by principal component analysis,which revealed that 16of the 17modi?cations are highly clustered in the ?rst principal component (Supplementary Fig.7online)and provided further evidence that the modi?cations in the backbone can be classi?ed in the same group.Genes with this backbone seem to have higher expression than the genes with no modi?cations (Fig.2b ,class II).
The tendency of the 17modi?cations to coexist suggests that some of these modi?cations may be present at the same nucleosome.We tested this hypothesis by carrying out a pairwise correlation analysis at a single-nucleosome level of 18histone acetylations,18histone methylations,CTCF,Pol II and H2A.Z using 200-bp windows for the entire genome (see Supplementary Table 2online for the top correlated pairs (r 40.4;P o 0.01)).A heat map based on the mean correlation coef?cients indicates that a cluster of strong positively correlated pairs was observed at the lower-right corner (Fig.4b ).All 14modi?cations within this cluster (r 40.4;P o 0.01)belong to the 17-modi?cation backbone module found at promoters.Another cluster of positively correlated pairs contains modi?cations enriched in transcribed regions of genes,including H4K20me1,H2BK5me1,H3K9me1,H3K4me1/2and H3K79me1/2/3.Pol II clustered together with these modi?cations rather than the promoter-centric modi?ca-tions.Modi?cations related to gene silencing,including H3K27me2,H3K27me3,H3K9me2and H3K9me3,were clustered together (Fig.4b ).Many correlated pairs,including H3K4me1-H3K9me1(r ?0.51;P o 0.01),H3K9me1-H3K27me1(r ?0.31;P o 0.01)
Present
Absent
Value
H 3K 9m e 2H 3K 9m e 3H 3K 27m e 2H 3K 27m e 3H 3K 14a c H 2A K 9a c H 3K 23a c H 3K 36m e 3H 3K 27m e 1H 3R 2m e 1H 3R 2m e 2H 4R 3m e 2H 4K 20m e 3H 2A K 5a c H 4K 16a c H 4K 12a c C T C F P o l I I H 3K 79m e 1H 3K 79m e 2H 3K 79m e 3H 4K 20m e 1H 2B K 5m e 1H 3K 4m e 1H 3K 4m e 2H 3K 9m e 1H 4K 8a c H 4K 5a c H 2A Z H 3K 4m e 3H 2B K 12a c H 3K 9a c H 3K 18a c H 3K 27a c H 2B K 5a c H 3K 36a c H 3K 4a c H 2B K 20a c H 4K 91a c H 2B K 120a c
H2BK120ac
H4K91ac H2BK20ac H3K4ac H3K36ac H2BK5ac H3K27ac H3K18ac H3K9ac H2BK12ac H3K4me3H2AZ H4K5ac H4K8ac H3K9me1H3K4me2H3K4me1H2BK5me1H4K20me1H3K79me3H3K79me2H3K79me1PolII
CTCF H4K12ac H4K16ac H2AK5ac H4K20me3H4R3me2H3R2me2H3R2me1H3K27me1H3K36me3H3K23ac H2AK9ac H3K14ac H3K27me3H3K27me2H3K9me3H3K9me2a
b
Figure 4Correlation of histone modi?cations in the genome.(a )A group of 17modi?cations,the ‘backbone’in Figure 2b ,tend to coexist.The numbers of promoters associated with all the 17modi?cations or missing any one modi?cation (the blue rectangle)are indicated on the right.(b )Tags are binned into nonoverlapping 200-bp bins along the https://www.sodocs.net/doc/1c16128467.html,ing the tallies for each bin,we calculated a pairwise Spearman correlation coef?cient for each pair of modi?cations to create a correlation coef?cient matrix.A heat map was then generated from this matrix.
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and H3K9me2-H3K27me2(r ?0.28;P o 0.01),identi?ed in this study have been detected in one single modi?ed peptide using a mass spectrometry strategy 16.Mutually exclusive acetylation and methylation are detectable at several lysines,including H2BK5,H3K4,H3K9,H3K27and H3K36.However,except for the H3K9acetylation and methylation,little is known about the functional and spatial differences of modi?cation variance at other lysines.Our data indicate that all acetylations of these ?ve lysines are
enriched in the promoter regions of active genes (Fig.5),whereas the predominant
region of enrichment for the various methyla-tions depends on the speci?c lysine.H3K4me1and H3K4me2were elevated in the vicinity of promoters,whereas mono-methylated H2BK5,H3K9and H3K27were elevated throughout the transcribed regions of active genes (Fig.5).Localization in different regions of genes suggests that these modi?ca-tions have different functions.For example,H3K9ac was elevated in promoter regions,consistent with a role in transcriptional initia-tion 20,whereas H4K12ac was detected at high levels in transcribed regions,suggesting a role in transcriptional elongation 19,27.It has been proposed that histone modi?ca-tions can cross-talk 28and that multiple mod-i?cations with similar functions can reinforce the robustness of a chromatin state 14.In this
report,we identify a large number of histone modi?cation patterns at promoters and potential enhancers.In particular,we identify a back-bone module consisting of 17modi?cations that is found at 25%of human promoters.These modi?cations tend to colocalize at gene promoters,and most of them are correlated with each other at an individual nucleosome level.Although the genes associated with these modi?cations tend to have higher expression,the histone modi?cations
Chr19:
a c
e
g
i b
d
f
h
j 9
1964500019650000H2BK5me1
H2K36me3
H3K36me1
H3K4me3
H3K4me2
H3K4me1
H3K27me3
H3K27me2
H3K27me1
H3K9me3H3K9me2
H3K9me1H3K9ac
H3K27ac H3K4ac
H2BK5ac
H3K36ac
ZNF101
ZNF101
SMAP
SMAP
SMAP 1965500019660000
19645000
19650000
19655000
19660000
167160001671650016717000167175001671800016718500
16720000
16730000
16740000
16715000167200001672500016750000
16760000
1411
Chr19:52
151143Chr11:911142131321
Chr11:
5
16
171
411Chr11:221
1221
481 1.6E–07
Ac
Me1Ac Me3
Ac Me1
Ac Me3
Ac Me2Ac Me1Ac Me3
Ac Me2
Ac Me1Ac Me3Ac
Me2Ac Me1H 2B K 5 t a g d e n s i t y
H 3K 36 t a g d e n s i t y
H 3K 4 t a g d e n s i t y
H 3K 27 t a g d e n s i t y
H 3K 9 t a g d e n s i t y
1.4E–071.2E–071E–078E–086E–084E–082E–08
–4,000–2,00002,0004,000
–4,000–2,0000
2,0004,000
–4,000–2,000–1,000
–2,0002,000
1,000
00
–1,000–2,0002,000
1,0000–1,000
–2,0002,000
1,0000–2,000–4,0002,0004,0000–2,000–4,0002,0004,0000–2,000–4,0002,0004,0000–2,000–4,0002,0004,0000–2,000–4,0002,0004,000
0–2,000–4,0002,0004,000
02,0004,000
1.4E–071.2E–071E–078E–086E–084E–082E–08
1.4E–071.2E–071E–078E–086E–084E–082E–08
1.4E–071.2E–071E–078E–086E–08
4E–082E–080
1E–088E–096E–094E–092E–0901E–088E–096E–094E–092E–090
1.8E–081.6E–081.4E–081.2E–081E–088E–097E–086E–085E–084E–083E–082E–081E–08
07E–086E–085E–084E–083E–082E–081E–08
07E–088E–086E–085E–084E–083E–082E–081E–08
7E–088E–086E–085E–084E–083E–082E–081E–08
2.5E–072E–071.5E–071E–07
5E–08
6E–094E–092E–091.2E–081E–088E–096E–094E–092E–090
1.2E–081E–088E–096E–094E–092E–090
1.2E–081E–08
8E–096E–094E–092E–0905E–094E–09
3E–092E–091E–0905E–094E–093E–09
2.5E–082E–081.5E–081E–085E–0902E–091E–0901.2E–071E–078E–086E–08
4E–08
2E–0801.2E–071E–078E–086E–084E–08
2E–080
1.2E–071E–078E–086E–08
4E–08
2E–08
0Figure 5Characteristic spatial distribution of mutually exclusive modi?cations.(a )The
distribution of H2BK5me1(upper)and H2BK5ac (lower)surrounding the ZNF101gene.(b )The composite pro?les of H2BK5me1(green)and H2BK5ac (red)surround the TSS regions of
1,000active genes.(c )The distribution patterns of H3K36me3(upper),H3K36me1(middle)and H3K36ac (lower)surrounding the ZNF101gene.(d )The composite pro?les of H3K36ac (red)are compared with the two states of H3K36methylation (H3K36me1and H3K36me3)surrounding the TSS regions of 1,000active genes.(e )The distribution patterns of H3K4ac and the three states of H3K4methylation surrounding the promoter region of the SMAP gene.(f )The composite pro?les of H3K4ac (red)are compared with the three states of H3K4methylation (H3K4me1,H3K4me2and
H3K4me3)surrounding the TSS regions of 1,000active genes.(g )The distribution patterns of H3K27ac and the three states of H3K27
methylation surrounding the SMAP gene.(h )The composite pro?les of H3K27ac (red)are compared with the three states of H3K27methylation (H3K27me1,H3K27me2and H3K27me3)surrounding the TSS regions of 1,000active genes.(i )The distribution patterns of H3K9ac and the three states of H3K9
methylation surrounding the SMAP gene.(j )The composite ?les of H3K9ac (red)are compared with the three states of H3K9methylation (H3K9me1,H3K9me2and H3K9me3)surrounding the TSS regions of 1,000active genes.
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themselves do not uniquely determine expression but may function cooperatively to prepare chromatin for transcriptional activation.As with the ?ndings of other genome-wide ChIP analyses,our results rely on antibody speci?city.Many of the antibodies that we used are well characterized,but some need to be improved further.We also cannot exclude the possibility of antibody occlusion between adjacent modi?cations because of steric interference.Finally,because the ChIP step requires a population of hundreds of thousands or even millions of cells,the pattern obtained for each modi?cation is an average ‘snapshot’,containing contributions from heterogeneous modi?cation states of different cells.
METHODS
T-cell puri?cation,antibodies,ChIP and ChIP-Seq.Human CD4+T cell puri?cation and ChIP-Seq analysis for histone acetylations were done as previously described 15.The ChIP-Seq analysis for histone methylations was reported previously 15except for that of H3K79me1,H3K79me2and H3K79me3,which was done using an improved ChIP procedure 29.The raw sequence tags for histone acetylations and H3K79methylations in human CD4+T cells have been deposited in the Short Read Archive (see Accession codes section below).We have also generated 5.5million additional sequence reads for H3K27me3in human CD4+T cells and deposited them in the Short Read Archive.The histone acetylation maps and BED ?les can be found online (see URLs section below).
The validation of antibodies is described in Supplementary Methods ,Supplementary Table 1and Supplementary Figure 1.The expression infor-mation for CD4+T cells was obtained from the GNF SymAtlas gene expression atlas 30.GNF expression probes were mapped to UCSC Known Genes to obtain expression information in CD4+T cells for 12,726known genes.These genes were ranked by expression and broken up into 12sets of 1,000genes,starting with the most expressed set.The normalized tag counts were obtained by normalizing the tag counts in 5-bp windows (Fig.1a–c )or in 2-kb windows (Fig.1d–f )by the total base pairs.
Identi?cation of patterns and modules of histone modi?cations.The cover-age was examined by scaling analysis (Supplementary Methods ).We de?ned a promoter region as a region of 2kb around TSS with 1kb upstream and 1kb downstream.For each modi?cation and promoter region,we counted the tags located within the promoter region for that modi?cation.The modi?cation on a promoter under consideration was deemed signi?cant when the tag count was higher than a threshold,which was determined by a P value taken from a background model of Poisson distribution parameterized by the genome-wide tag density.In order to ensure high con?dence in each of our designations of a signi?cant promoter,we chose a very stringent threshold requiring a P value of 10à7.The P value of 10à7was a result of using a P value of 10à3on a single call along with the Bonferroni correction for simultaneous multiple calls.This method was applied to every promoter for each modi?cation.Hence,each promoter was given a binary string to represent the presence or absence of each modi?cation.A similar method was applied to the analysis of combinatorial patterns at a set of putative enhancers,which were de?ned as a DNase hypersensitive region with extensions of 200bp both upstream and downstream.T o examine if correlations between histone modi?cations at enhancers and gene expression exist,we assigned an enhancer to the TSS of the nearest known gene.However,we cannot exclude the possibility that the enhancer may not act as a major determinant of the expression of the gene under the assay condition,that the assigned gene is not the true target of the enhancer,or both.
We identi?ed the modi?cation backbone by ?nding the common features of the top patterns (that is,those associated with the largest number of genes)and by using the ‘single-mutation’analysis.In ‘single-mutation’analysis,we considered the size of the gene set for patterns that differ from the constructed backbone by only one modi?cation.We carried out principal component analysis using the tag counts for nonoverlapping 200-bp windows in the 2-kb region surrounding the TSS.
Pairwise correlation analysis.In order to assign tags to the centers of the nucleosomes to which they correspond,we shifted the sequence tag locations +65bp for hits on the positive strand and –65bp for hits on the negative
https://www.sodocs.net/doc/1c16128467.html,ing these locations,we placed tags into nonoverlapping 200-bp bins along the genome,with the bin for each tag determined by the middle of the tag.
T o determine the correlation between a pair of modi?cations,we divided the genome into 100windows of these 200-bp bins and determined the correlation for each window.We calculated the mean correlation and the s.d.of the correlation from all of the windows of bins using a Pearson correlation coef?cient.Resampling was then used to determine a signi?cance P value for each correlation coef?cient.This empirical calculation was necessary because the count data does not directly ?t any distribution that could be used to produce an analytic P value.T o illustrate the P -value calculation,we take the pair of modi?cations A and B as an example.For the modi?cations,the counts in 200-bp bins produced colinear arrays of integers that correspond to locations on the genome.These arrays were then shuf?ed so that for each location in the array,the bin for modi?cation A was taken from a different location than the bin for modi?cation B.We took this shuf?ed genome to represent the null background from which we determined the signi?cance.We then divided the shuf?ed genome into 100windows and determined the correlation for each window.The comparison of the mean correlation to the correlations from the shuf?ed genome was used to determine signi?cance.We carried out a t -test to compare the actual correlation and the correlations between the shuf?ed genomes.From the t -test results,we calculated a P value using a Gaussian assumption for the distribution of t -test scores.A heat map was then produced from the mean correlation coef?cients.For this analysis,we excluded any bins in the genome that lacked histone modi?cations,because the addition of paired 0s skews the calculation of a Pearson correlation coef?cient.
URLs.Histone acetylation maps and BED ?les,https://www.sodocs.net/doc/1c16128467.html,/papers/lmi/epigenomes/hgtcellacetylation.html.
Accession codes.NCBI Short Read Archive:raw sequence tags for histone acetylations and H3K79methylations in human CD4+T cells have been deposited with accession code SRA000287.
Note:Supplementary information is available on the Nature Genetics website.ACKNOWLEDGMENTS
We thank W.Leonard for comments.This work was supported by the Intramural Research Program of the US National Institutes of Health,National Heart,Lung,and Blood Institute (K.Z.)and by an NIH grant HG001696(M.Q.Z.).J.A.R.is supported by an NIH training grant to New Y ork University and a New Y ork University McCracken Fellowship.
AUTHOR CONTRIBUTIONS
Z.W.and K.Z.designed the study;Z.W.performed the experiments;A.B.,S.C.,K.C.and T.-Y .R.contributed to the study;C.Z.,J.A.R,D.E.S.,W.P .and M.Q.Z.analyzed the data;Z.W.,J.A.R.,W.P .,M.Q.Z.and K.Z.wrote the paper.
Published online at https://www.sodocs.net/doc/1c16128467.html,/naturegenetics/
Reprints and permissions information is available online at https://www.sodocs.net/doc/1c16128467.html,/reprintsandpermissions/
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常用宝钢钢材标准
常用宝钢钢材标准 一、无间隙原子高强度冷连轧钢板及钢带（Q/BQB 413-2009） 本标准适用于宝山钢铁股份有限公司生产的厚度为0.50mm～2.50mm的无间隙原子高强度冷连轧钢板及钢带。 通过控制钢中的化学成分来改善钢的塑性应变比（r值）和应变硬化指数（n 值）。由于钢中元素的固溶强化和无间隙原子的微观结构，这种钢既具有高强度，又具有非常好的冷成型性能，通常用来制作需要深冲压的复杂部件。 钢板及钢带按用途区分应符合下表的规定。 二、加磷高强度冷连轧钢板及钢带（Q/BQB 411-2009） 本标准适用于宝山钢铁股份有限公司生产的厚度为0.50mm～2.5mm的加磷高强度冷连轧钢板及钢带（以下简称钢板及钢带）。 在低碳钢或超低碳钢中，主要通过添加最大不超过0.12%的磷等固溶强化元素来提高钢强度。这种钢具有高强度和良好的冷成形性能，且具备良好的耐冲击和抗疲劳性能，通常用于汽车覆盖件和结构件制作。 钢板及钢带按用途区分应符合下表的规定。 三、冷连轧低碳钢板及钢带（Q/BQB 403-2009）等同于GB/T5213-20008冷轧低碳钢板及钢带 本标准适用于宝山钢铁股份有限公司生产的厚度为0.17mm～3.5mm的冷连轧低碳钢板及钢带 钢板及钢带按用途区分应符合下表的规定
室温储存条件下，对于表面质量要求为FC和FD的钢板及钢带，拉伸应变痕应符合下表的规定。 钢板及钢带各表面质量级别的特征应符合下表的规定。 四、冷连轧碳素钢板及钢带（Q/BQB 402-2009） 本标准适用于宝山钢铁股份有限公司生产的厚度为0.17mm～3.5mm的冷连轧碳素钢板及钢带 钢板及钢带按用途区分应符合下表的规定
宝钢DC01标准
1 范围 本标准规定了冷连轧低碳钢板及钢带的分类和代号、尺寸、外形、重量、技术要求、检验和试验、包装、标志及质量证明书等。 本标准适用于宝山钢铁股份有限公司生产的厚度为0.30mm～3.5mm的冷连轧低碳钢板及钢带（以下简称钢板及钢带）。 2 规范性引用文件 下列文件中的条款通过本标准的引用而成为本标准的条款。凡是注日期的引用文件，其随后所有的修改单（不包括勘误的内容）或修订版均不适用于本标准，然而，鼓励根据本标准达成协议的各方研究是否可使用这些文件的最新版本。凡是不注日期的引用文件，其最新版本适用于本标准。 GB/T 222－1984 钢的化学分析用试样取样法及成品化学成分允许偏差 GB/T 223 钢铁及合金化学分析方法 GB/T 228－2002 金属材料室温拉伸试验方法 GB/T 2975－1998 钢及钢产品力学性能试验取样位置及试样制备 GB/T 5027－1999 金属薄板和薄带塑性应变比（值）试验方法 GB/T 5028－1999 金属薄板和薄带拉伸应变硬化指数（值）试验方法 GB/T 8170－1987 数值修约规则 Q/BQB 400－2003 冷轧产品的包装、标志及质量证明书 Q/BQB 401－2003 冷连轧钢板及钢带的尺寸、外形、重量及允许偏差 SAE J911－1998 冷轧钢板表面粗糙度和峰值数测量方法 3 分类和代号 钢板及钢带按用途区分如表1的规定。 表 1
宝山钢铁股份有限公司2003－06－04 发布 2003－12－15 实施表2 表3 4 订货所需信息 订货时用户应提供如下信息： a) 产品名称 b) 本产品标准号
宝 钢 企 业 标 准
二者没有必然的联系，根据材料和工艺不同而不同。屈服强度就是材料进入屈服阶段的临界应力，材料过了屈服阶段后还会出现一个强化阶段，然后才断裂，而拉伸强度指的就是那个开始出现明显的颈缩的临界值。简单的理解，一旦应力超过拉伸强度，材料就会断裂，而应力超过屈服强度，只会导致材料发生塑性变形，而不一定会断裂。拉伸强度一般由材料直接决定，而屈服强度除材料外，还可以利用加工工艺做一定的提高。所有二者之间是没有什么换算关系的，二者多是材料的基本性能参数，多是需要靠实验测量的。 宝钢企业标准 （一）冷连轧碳素钢板、钢带（二）冷连轧低碳钢板及钢带 宝钢标准：Q/BQB402-2003 宝钢标准：Q/BQB403-2003 1、分类、代号： 一般用SPCC 一般用DCO1 （St12） 冲压用SPCD 冲压用DCO3 （St13） 深冲用SPCE 、SPCN 深冲用DCO4 （St14、St15） 特深冲用DCO5 （BSC2） 超深冲用DCO6 （St16、St14-T、BSC3）2、表面质量代号： 较高级精整表面FB（O3）较高级精整表面FB（O3） 高级精整表面FC（O4）高级精整表面FC （O4） 超高级精整表面FD（O5）超高级精整表面FD（O5） 3、表面结构代号： 光亮表面 B 光亮表面 B 麻面 D 麻面 D 4、热处理代号： 退火+平整S 1/8硬质8 1/4硬质 4 硬质 1 5、标记示例： 标准号；Q/BQB402-2003 Q/BQB403-2003 牌号：SPCC DCO5 表面质量：FB（较高级精整）FC（高级精整） 表面结构：D（麻面） B （光亮表面） 厚度：1.5 1.5 规格：1000 ×2000 1000 ×2000 Q/BQB402-2003 SPCC – FB Q/BQB403-2003 DCO5 – FC - B - 1.5 ×1000 ×2000 - 1.5 ×1000 ×2000
宝钢酸洗钢板标准
宝钢酸洗钢板及钢带标准 1 范围 本标准规定了冷成型用热连轧钢板及钢带的尺寸、外形、技术要求、检验和试验、包装、标志及质量证明书等。 本标准适用于宝山钢铁股份有限公司生产的冷成型用热连轧钢带以及由此横切成的钢板及纵切成的纵切钢带，以下简称钢板及钢带。 2 规范性引用文件 下列文件中的条款通过本标准的引用而成为本标准的条款。凡是注日期的引用文件，其随后所有的修改单（不包括勘误的内容）或修订版均不适用于本标准，然而，鼓励根据本标准达成协议的各方研究是否可使用这些文件的最新版本。凡是不注日期的引用文件，其最新版本适用于本标准。 GB/T 222－1984 钢的化学分析用试样取样法及成品化学成分允许偏差 GB/T 223 钢铁及合金化学分析方法 GB/T 228－2002 金属材料室温拉伸试验方法 GB/T 232－1999 金属材料弯曲试验方法 GB/T 2975－1998 钢及钢产品力学性能试验取样位置及试样制备 GB/T 8170－1987 数值修约规则 Q/BQB 300－2003 热连轧钢板及钢带的包装、标志及质量证明书的一般规定 Q/BQB 301－2003 热连轧钢板及钢带的尺寸、外形、重量及允许偏差 3 分类和代号 3.1 钢板及钢带的牌号、公称厚度、用途如表1所示。 表1 牌号公称厚度a mm 用途 SPHC ≤16.0 一般用DD11（StW22）≤8.0 SPHD ≤16.0 冲压用DD12（StW23）≤8.0 SPHE ≤8.0 深冲用
DD13（StW24）≤8.0 注：括号内的牌号可使用至2005年年底。 a对于热轧酸洗表面钢板及钢带，公称厚度≤6.0mm。 3.2 按边缘状态分为： 切边EC 不切边EM 3.3 按表面处理方式分为： 酸洗表面 非酸洗表面 3.4 按表面质量级别分为: 普通级表面FA 较高级表面FB 3.5 按产品类别分为： 热轧钢带 热轧钢板 热轧纵切钢带 4 订货所需信息 4.1 订货时用户需提供下列信息： a) 本企业标准号； b) 产品类别； c) 牌号、表面处理方式及表面质量级别； d) 规格及尺寸（厚度）精度； e) 边缘状态。 如在订货合同中： 未说明表面处理方式时，以非酸洗表面交货。 对于热轧非酸洗表面钢板及钢带，未说明尺寸精度时，以普通厚度精度交货；未说明边缘状态时，钢带以不切边状态交货，钢板以切边状态交货。 对于热轧酸洗表面钢板及钢带，未说明尺寸精度、边缘状态、表面质量级别和是否涂油时，以较高厚度精度、切边状态、较高级表面和涂油交货；未说明钢卷内
宝钢DC01标准
宝山钢铁股份有限公司企业标准 Q/BQB 403－2003 冷连轧低碳钢板及钢带代替Q/BQB 403-1999 BZJ 407-1999 1 范围 本标准规定了冷连轧低碳钢板及钢带的分类和代号、尺寸、外形、重量、技术要求、检验和试验、包装、标志及质量证明书等。 本标准适用于宝山钢铁股份有限公司生产的厚度为0.30mm～3.5mm的冷连轧低碳钢板及钢带（以下简称钢板及钢带）。 2 规范性引用文件 下列文件中的条款通过本标准的引用而成为本标准的条款。凡是注日期的引用文件，其随后所有的修改单（不包括勘误的内容）或修订版均不适用于本标准，然而，鼓励根据本标准达成协议的各方研究是否可使用这些文件的最新版本。凡是不注日期的引用文件，其最新版本适用于本标准。 GB/T 222－1984 钢的化学分析用试样取样法及成品化学成分允许偏差 GB/T 223 钢铁及合金化学分析方法 GB/T 228－2002 金属材料室温拉伸试验方法 GB/T 2975－1998 钢及钢产品力学性能试验取样位置及试样制备 GB/T 5027－1999 金属薄板和薄带塑性应变比（值）试验方法 GB/T 5028－1999 金属薄板和薄带拉伸应变硬化指数（值）试验方法 GB/T 8170－1987 数值修约规则 Q/BQB 400－2003 冷轧产品的包装、标志及质量证明书 Q/BQB 401－2003 冷连轧钢板及钢带的尺寸、外形、重量及允许偏差 SAE J911－1998 冷轧钢板表面粗糙度和峰值数测量方法 3 分类和代号 钢板及钢带按用途区分如表1的规定。 宝山钢铁股份有限公司2003－06－04 发布2003－12－15 实施