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High-temporal-resolution view of transcription and chromatin states across distinct metabolic states in budding yeast

Nature Structural & Molecular Biology volume 21, pages 854–863 (2014)Cite this article

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Abstract

Under continuous, glucose-limited conditions, budding yeast exhibit robust metabolic cycles associated with major oscillations of gene expression. How such fluctuations are linked to changes in chromatin status is not well understood. Here we examine the correlated genome-wide transcription and chromatin states across the yeast metabolic cycle at unprecedented temporal resolution, revealing a 'just-in-time supply chain' by which components from specific cellular processes such as ribosome biogenesis become available in a highly coordinated manner. We identify distinct chromatin and splicing patterns associated with different gene categories and determine the relative timing of chromatin modifications relative to maximal transcription. There is unexpected variation in the chromatin modification and expression relationship, with histone acetylation peaks occurring with varying timing and 'sharpness' relative to RNA expression both within and between cycle phases. Chromatin-modifier occupancy reveals subtly distinct spatial and temporal patterns compared to those of the modifications themselves.

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Figure 1: High-temporal-resolution analysis of gene expression reveals meticulous temporal compartmentalization in yeast.
Figure 2: RNA-seq analysis at introns reveals transient accumulation of pre-mRNAs during OX phase.
Figure 3: Dynamic chromatin states across the YMC.
Figure 4: Temporal patterns of H3K56ac.
Figure 5: Temporal combinatorial patterns of chromatin states and gene expression define functionally related genes.
Figure 6: Spatiotemporal patterns of chromatin modifiers and corresponding modifications.
Figure 7: Similar but not identical temporal patterns of chromatin modifiers and corresponding modifications.
Figure 8: O2-consumption traces of histone point mutants.

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Acknowledgements

We dedicate this paper to the memory of our colleague, Yu-yi Lin. We thank L. Huang for general data-analysis advice; J. Dai for advice on histone mutants; L. Shi, S. Uplekar and G. Rao for help with fermentor and YMC experiments; and S. Taverna, B. Cormack, J. Bader, P. Meluh, Y. Lin and members of the Boeke laboratory for helpful discussion. This work was supported by US National Institutes of Health grants R01HG006841 to H.J., R01GM094314 to B.P.T. and U54GM103520 to J.D.B.

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Authors and Affiliations

  1. High Throughput Biology Center, Johns Hopkins University, Baltimore, Maryland, USA

    Zheng Kuang & Jef D Boeke

  2. Department of Molecular Biology & Genetics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    Zheng Kuang & Jef D Boeke

  3. Institute for Systems Genetics, NYU Langone Medical Center, New York, New York, USA

    Zheng Kuang & Jef D Boeke

  4. Department of Biochemistry and Molecular Pharmacology, NYU Langone Medical Center, New York, New York, USA

    Zheng Kuang & Jef D Boeke

  5. Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas, USA

    Ling Cai & Benjamin P Tu

  6. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA

    Xuekui Zhang & Hongkai Ji

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  1. Zheng Kuang
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Contributions

Z.K., L.C., B.P.T. and J.D.B. designed experiments; Z.K. and L.C. collected ChIP-seq and RNA-seq data; Z.K., X.Z. and H.J. performed the analysis; Z.K. made histone mutants and analyzed growth and YMC phenotypes; Z.K. wrote the manuscript with help from all other authors; all authors reviewed the manuscript.

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Correspondence to Benjamin P Tu or Jef D Boeke.

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Integrated supplementary information

Supplementary Figure 1 Dynamics of gene expression in YMC.

(a, b) RNA-seq experiment reveals the same three clusters (OX, RB and RC) discovered by previous microarray experiments. 3 cycles of microarray data are plotted in the first three joint columns, each containing 12 time points. 16 time-point RNA-seq data are plotted in the last joint column. (a) Enriched GO terms are labeled on the right. (b) 537 “non-cycling” genes defined previously show clearly elevated expression level in OX phase. Algorithm previously used to define cycling genes required highest expression of 2 or more time points and highest expression in all three cycle periods. As can be seen, these 537 genes form very sharp peaks with only one high time point and/or are represented in only one or two cycles. (c) Average 16 time-point RNA-seq data across genes in subclusters from Figure 1 (b-d). (d) Expression level of RTT109 and HST3 across 16 time points extracted from the RNA-seq experiment.

Supplementary Figure 2 Temporal patterns of RNA-seq signals at RP introns.

89 RP genes from Intron1 cluster were included in the analysis. (a) The ratio of intron to exon was calculated for every gene in the cluster and the means are displayed across 16 time points in the top panel. The bottom panel is total numbers of junction reads spanning the 3’ end of RP introns at 16 time points. Note that the numbers of 3' junction reads are consistently higher than the numbers of 5′ junction reads (Figure 2c), consistent with an arrest of splicing at the “2/3 intermediate” stage of splicing. Heat maps show the temporal patterns of junction reads spanning the 5’ end (b) and the 3’ end (c) of RP introns and exon-exon junctions (d) of RP genes. Data is centered to mean zero. “T4” or “T5” mark the time point where signals reach the peak. (e) The RNA levels of CK2 subunits, catalytic subunits CKA1 and CKA2, and regulatory subunits CKB1 and CKB2, are plotted across the 16 time points. Time point 4 and 5 are labeled by “T4” and “T5”. (f) RT-qPCRs of 4 Ribi (top panel), 4 RP (middle panel) and 4 RP intron (bottom panel) transcripts across 16 ultra-dense OX time points (1.5~2 min intervals). Signals are normalized by the level at time point 1. 16 values of each transcript are plotted in a smoothed line. The vertical lines in each panel mark the mean peak time of the 4 transcripts and the estimation values are labeled at the right side of the lines.

Supplementary Figure 3 Dynamic chromatin modifications across the YMC.

H3K9ac, H3K14ac, H4K5ac and H3K4me3 ChIP-seq signals at chrVII: 340669-389335 are displayed in cisgenome browser. 16 tracks represent 16 time points from top to bottom consecutively. 3-color bars on the left of each panel mark the three phases. The boxes with the same 3 colors in the last track mark the phases of expression of corresponding genes. Black boxes represent non-cycling genes.

Supplementary Figure 4 Temporal patterns of chromatin modifications at OX genes.

H3K9ac, H3K14ac, H4K5ac and H3K4me3 ChIP-seq signals at FUR1, RPL42B, RPS11B, RRB1, MET5 and LYS1 are displayed in CisGenome browser screenshots. 16 tracks represent 16 time points from top to bottom consecutively. 3-color bars on the left of each panel mark the three phases.

Supplementary Figure 5 Temporal association between chromatin states and gene expression.

(a) Spatial distribution of chromatin markers. ChIP-seq reads are averaged from -1000 to +1000 bp of TSSs across the genome. (b) 14 clusters were determined for the whole genome, revealing complex combinatorial temporal patterns of H3K9ac, H3K14ac, H4K5ac, H3K56ac, H4K16ac, H3K4me3, H3K36me3 and H3. Each row represents centered signals of one gene and each column represents one time-point ChIP-seq corresponding to the indicated chromatin mark. We calculated reads at the 5′ end as gene-specific signals of H3K4me3, H3K9ac, H3K4ac, H4K5ac and H3K56ac, and reads across the full gene as signals of H3K36me3, H4K16ac and H3. (c) Estimation of time in YMC when RNA and histone modifications in “RNA_H3”, “RNA_H4”, “RNA_H5”, “RNA_H6”, “RNA_H7” reach the maximum. The middle of the horizontal colored lines on the O2 curves represent the mean peak value of genes in each cluster and the lengths represent standard deviations for genes in theses clusters.

Supplementary Figure 6 Dynamic analysis of chromatin modifiers and corresponding modifications.

(a) shows the numbers of binding sites and annotated genes by MACS for Gcn5, Esa1 and Set1. Areas of overlap among the three enzymes and numbers of annotated genes in each subset are labeled inside the Venn diagram. (b) 4 distinct patterns of the 1035 genes to which all three enzymes bind show the temporal combinatorial recruitment of the chromatin modifiers. Overrepresented GO terms for each cluster are listed on the right. (c) Gcn5-3FLAG 6HA-Set1 cells were collected at 8 time points from late RC to RB phase in YMC for ChIP-qPCR. (d) ChIP-qPCR of H3K9ac, H3K14ac, H4K5ac and H3K4me3 at examples of OX phase genes. RPS11b and RPL33b are two RP genes and MET5 and LYS1 are aa genes. H3K14ac and H4K5ac were detected earlier than H3K9ac on aa genes but not on RP genes. (e) ChIP-qPCR of Gcn5, Set1 and Esa1 at RPS11b and RPL33b. Esa1 and Set1 binding increase before Gcn5 binding.

Supplementary Figure 7 Analysis of histone-mutant O2 oscillation.

(a) Strains were plated (1:10 serial dilutions) on YPD plates and grown at 30°C. H3 mutants represent H3K9R, H3K(9,14,18)R, H3K(9,14,18,23)R, H3K(9,14,18,23,27)R, H3K(9,14,18,23,27)A, H3K(9,14,18,23,27)Q. H4 mutants represent H4K5R, H4K(5,8)R, H4K(5,8,12)R, H4K(5,8,12)A, H4K(5,8,12)Q. (b) O2 oscillation curves of H3K(9,14,18,23,27)A and H4K(5,8,12)A.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7 and Supplementary Note (PDF 8185 kb)

Supplementary Table 1

Analysis of the RNA-seq experiments in YMC (XLSX 4859 kb)

Supplementary Table 2

Clustering analysis of the RNA-seq reads at intron-containing genes (XLSX 253 kb)

Supplementary Table 3

Clustering analysis of histone-modification ChIP-seq experiments (XLSX 9794 kb)

Supplementary Table 4

Analysis of combinatorial histone modifications and RNA level (XLSX 160 kb)

Supplementary Table 5

Analysis of the chromatin-modifier ChIP-seq experiments (XLSX 795 kb)

Supplementary Table 6

Primers used in this study (XLSX 56 kb)

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Kuang, Z., Cai, L., Zhang, X. et al. High-temporal-resolution view of transcription and chromatin states across distinct metabolic states in budding yeast. Nat Struct Mol Biol 21, 854–863 (2014). https://doi.org/10.1038/nsmb.2881

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