Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The evolutionary capacitor HSP90 buffers the regulatory effects of mammalian endogenous retroviruses

Nature Structural & Molecular Biology volume 24, pages 234–242 (2017)Cite this article

Subjects

Abstract

Understanding how genotypes are linked to phenotypes is important in biomedical and evolutionary studies. The chaperone heat-shock protein 90 (HSP90) buffers genetic variation by stabilizing proteins with variant sequences, thereby uncoupling phenotypes from genotypes. Here we report an unexpected role of HSP90 in buffering cis-regulatory variation affecting gene expression. By using the tripartite-motif-containing 28 (TRIM28; also known as KAP1)-mediated epigenetic pathway, HSP90 represses the regulatory influence of endogenous retroviruses (ERVs) on neighboring genes that are critical for mouse development. Our data based on natural variations in the mouse genome show that genes respond to HSP90 inhibition in a manner dependent on their genomic location with regard to strain-specific ERV-insertion sites. The evolutionary-capacitor function of HSP90 may thus have facilitated the exaptation of ERVs as key modifiers of gene expression and morphological diversification. Our findings add a new regulatory layer through which HSP90 uncouples phenotypic outcomes from individual genotypes.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: HSP90 inhibition causes misregulation of TEs in different mouse cell types.
Figure 2: HSP90 inhibition affects expression of genes in the vicinity of ERVs.
Figure 3: HSP90 represses cell-type-specific genes and ERVs through the KAP1–SETDB1 pathway.
Figure 4: Genetic variation caused by preexisting ERV insertions is buffered by HSP90.
Figure 5: The role of HSP90 and stress in genotype–phenotype mapping through buffering gene-expression variation caused by ERVs.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

Referenced accessions

Gene Expression Omnibus

References

  1. Wray, G.A. The evolutionary significance of cis-regulatory mutations. Nat. Rev. Genet. 8, 206–216 (2007).

    CAS  PubMed  Google Scholar 

  2. Mackay, T.F.C. et al. The Drosophila melanogaster Genetic Reference Panel. Nature 482, 173–178 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  3. Kilpinen, H. et al. Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription. Science 342, 744–747 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  4. Waddington, C. Canalization of development and the inheritance of acquired characters. Nature 150, 563–656 (1942).

    Google Scholar 

  5. Jarosz, D.F. & Lindquist, S. Hsp90 and environmental stress transform the adaptive value of natural genetic variation. Science 330, 1820–1824 (2010).

    CAS  PubMed Central  PubMed  Google Scholar 

  6. Queitsch, C., Sangster, T.A. & Lindquist, S. Hsp90 as a capacitor of phenotypic variation. Nature 417, 618–624 (2002).

    CAS  PubMed  Google Scholar 

  7. Rutherford, S.L. & Lindquist, S. Hsp90 as a capacitor for morphological evolution. Nature 396, 336–342 (1998).

    CAS  PubMed  Google Scholar 

  8. Rohner, N. et al. Cryptic variation in morphological evolution: HSP90 as a capacitor for loss of eyes in cavefish. Science 342, 1372–1375 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  9. Jarosz, D.F., Taipale, M. & Lindquist, S. Protein homeostasis and the phenotypic manifestation of genetic diversity: principles and mechanisms. Annu. Rev. Genet. 44, 189–216 (2010).

    CAS  PubMed  Google Scholar 

  10. Sawarkar, R., Sievers, C. & Paro, R. Hsp90 globally targets paused RNA polymerase to regulate gene expression in response to environmental stimuli. Cell 149, 807–818 (2012).

    CAS  PubMed  Google Scholar 

  11. Greer, C.B. et al. Histone deacetylases positively regulate transcription through the elongation machinery. Cell Rep. 13, 1444–1455 (2015).

    CAS  PubMed Central  PubMed  Google Scholar 

  12. Sawarkar, R. & Paro, R. Hsp90@chromatin.nucleus: an emerging hub of a networker. Trends Cell Biol. 23, 193–201 (2013).

    CAS  PubMed  Google Scholar 

  13. Sollars, V. et al. Evidence for an epigenetic mechanism by which Hsp90 acts as a capacitor for morphological evolution. Nat. Genet. 33, 70–74 (2003).

    CAS  PubMed  Google Scholar 

  14. Nellåker, C. et al. The genomic landscape shaped by selection on transposable elements across 18 mouse strains. Genome Biol. 13, R45 (2012).

    PubMed Central  PubMed  Google Scholar 

  15. Friedli, M. & Trono, D. The developmental control of transposable elements and the evolution of higher species. Annu. Rev. Cell Dev. Biol. 31, 429–451 (2015).

    CAS  PubMed  Google Scholar 

  16. Weick, E.M. & Miska, E.A. piRNAs: from biogenesis to function. Development 141, 3458–3471 (2014).

    CAS  PubMed  Google Scholar 

  17. Xiol, J. et al. A role for Fkbp6 and the chaperone machinery in piRNA amplification and transposon silencing. Mol. Cell 47, 970–979 (2012).

    CAS  PubMed  Google Scholar 

  18. Olivieri, D., Senti, K.A., Subramanian, S., Sachidanandam, R. & Brennecke, J. The cochaperone shutdown defines a group of biogenesis factors essential for all piRNA populations in Drosophila. Mol. Cell 47, 954–969 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  19. Specchia, V. et al. Hsp90 prevents phenotypic variation by suppressing the mutagenic activity of transposons. Nature 463, 662–665 (2010).

    CAS  PubMed  Google Scholar 

  20. Dolinoy, D.C. The agouti mouse model: an epigenetic biosensor for nutritional and environmental alterations on the fetal epigenome. Nutr. Rev. 66 (Suppl. 1), S7–S11 (2008).

    PubMed  Google Scholar 

  21. Gifford, W.D., Pfaff, S.L. & Macfarlan, T.S. Transposable elements as genetic regulatory substrates in early development. Trends Cell Biol. 23, 218–226 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  22. Lynch, V.J. et al. Ancient transposable elements transformed the uterine regulatory landscape and transcriptome during the evolution of mammalian pregnancy. Cell Rep. 10, 551–561 (2015).

    CAS  PubMed Central  PubMed  Google Scholar 

  23. Prescott, S.L. et al. Enhancer divergence and cis-regulatory evolution in the human and chimp neural crest. Cell 163, 68–83 (2015).

    CAS  PubMed Central  PubMed  Google Scholar 

  24. Eccles, S.A. et al. NVP-AUY922: a novel heat shock protein 90 inhibitor active against xenograft tumor growth, angiogenesis, and metastasis. Cancer Res. 68, 2850–2860 (2008).

    CAS  PubMed  Google Scholar 

  25. Trepel, J., Mollapour, M., Giaccone, G. & Neckers, L. Targeting the dynamic HSP90 complex in cancer. Nat. Rev. Cancer 10, 537–549 (2010).

    CAS  PubMed Central  PubMed  Google Scholar 

  26. Rebollo, R., Romanish, M.T. & Mager, D.L. Transposable elements: an abundant and natural source of regulatory sequences for host genes. Annu. Rev. Genet. 46, 21–42 (2012).

    CAS  PubMed  Google Scholar 

  27. Dewannieux, M. & Heidmann, T. Endogenous retroviruses: acquisition, amplification and taming of genome invaders. Curr. Opin. Virol. 3, 646–656 (2013).

    CAS  PubMed  Google Scholar 

  28. Faulkner, G.J. Retrotransposons: mobile and mutagenic from conception to death. FEBS Lett. 585, 1589–1594 (2011).

    CAS  PubMed  Google Scholar 

  29. Ferrari, K.J. et al. Polycomb-dependent H3K27me1 and H3K27me2 regulate active transcription and enhancer fidelity. Mol. Cell 53, 49–62 (2014).

    CAS  PubMed  Google Scholar 

  30. Karimi, M.M. et al. DNA methylation and SETDB1/H3K9me3 regulate predominantly distinct sets of genes, retroelements, and chimeric transcripts in mESCs. Cell Stem Cell 8, 676–687 (2011).

    CAS  PubMed Central  PubMed  Google Scholar 

  31. Bulut-Karslioglu, A. et al. Suv39h-dependent H3K9me3 marks intact retrotransposons and silences LINE elements in mouse embryonic stem cells. Mol. Cell 55, 277–290 (2014).

    CAS  PubMed  Google Scholar 

  32. Franci, G. et al. The class I-specific HDAC inhibitor MS-275 modulates the differentiation potential of mouse embryonic stem cells. Biol. Open 2, 1070–1077 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  33. Maksakova, I.A. et al. Distinct roles of KAP1, HP1 and G9a/GLP in silencing of the two-cell-specific retrotransposon MERVL in mouse ES cells. Epigenetics Chromatin 6, 15 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  34. Mozzetta, C. et al. The histone H3 lysine 9 methyltransferases G9a and GLP regulate polycomb repressive complex 2-mediated gene silencing. Mol. Cell 53, 277–289 (2014).

    CAS  PubMed  Google Scholar 

  35. Macfarlan, T.S. et al. Embryonic stem cell potency fluctuates with endogenous retrovirus activity. Nature 487, 57–63 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  36. Rowe, H.M. et al. TRIM28 repression of retrotransposon-based enhancers is necessary to preserve transcriptional dynamics in embryonic stem cells. Genome Res. 23, 452–461 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

  37. Lu, F. et al. Role of Tet proteins in enhancer activity and telomere elongation. Genes Dev. 28, 2103–2119 (2014).

    CAS  PubMed Central  PubMed  Google Scholar 

  38. Schultz, D.C., Ayyanathan, K., Negorev, D., Maul, G.G. & Rauscher, F.J. III. SETDB1: a novel KAP-1-associated histone H3, lysine 9-specific methyltransferase that contributes to HP1-mediated silencing of euchromatic genes by KRAB zinc-finger proteins. Genes Dev. 16, 919–932 (2002).

    CAS  PubMed Central  PubMed  Google Scholar 

  39. Moulick, K. et al. Affinity-based proteomics reveal cancer-specific networks coordinated by Hsp90. Nat. Chem. Biol. 7, 818–826 (2011).

    CAS  PubMed Central  PubMed  Google Scholar 

  40. Rowe, H.M. et al. KAP1 controls endogenous retroviruses in embryonic stem cells. Nature 463, 237–240 (2010).

    CAS  PubMed  Google Scholar 

  41. Sangster, T.A., Lindquist, S. & Queitsch, C. Under cover: causes, effects and implications of Hsp90-mediated genetic capacitance. BioEssays 26, 348–362 (2004).

    CAS  PubMed  Google Scholar 

  42. Zhang, Y., Maksakova, I.A., Gagnier, L., van de Lagemaat, L.N. & Mager, D.L. Genome-wide assessments reveal extremely high levels of polymorphism of two active families of mouse endogenous retroviral elements. PLoS Genet. 4, e1000007 (2008).

    PubMed Central  PubMed  Google Scholar 

  43. Sangster, T.A. et al. HSP90-buffered genetic variation is common in Arabidopsis thaliana. Proc. Natl. Acad. Sci. USA 105, 2969–2974 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Chuong, E.B., Elde, N.C. & Feschotte, C. Regulatory evolution of innate immunity through co-option of endogenous retroviruses. Science 351, 1083–1087 (2016).

    CAS  PubMed Central  PubMed  Google Scholar 

  45. Ichiyanagi, T. et al. HSP90α plays an important role in piRNA biogenesis and retrotransposon repression in mouse. Nucleic Acids Res. 42, 11903–11911 (2014).

    CAS  PubMed Central  PubMed  Google Scholar 

  46. Gangaraju, V.K. et al. Drosophila Piwi functions in Hsp90-mediated suppression of phenotypic variation. Nat. Genet. 43, 153–158 (2011).

    CAS  PubMed  Google Scholar 

  47. Iyengar, S. & Farnham, P.J. KAP1 protein: an enigmatic master regulator of the genome. J. Biol. Chem. 286, 26267–26276 (2011).

    CAS  PubMed Central  PubMed  Google Scholar 

  48. Taipale, M. et al. Quantitative analysis of HSP90-client interactions reveals principles of substrate recognition. Cell 150, 987–1001 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  49. Chelmicki, T. et al. MOF-associated complexes ensure stem cell identity and Xist repression. eLife 3, e02024 (2014).

    PubMed Central  PubMed  Google Scholar 

  50. Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).

    PubMed Central  PubMed  Google Scholar 

  51. Wang, L., Wang, S. & Li, W. RSeQC: quality control of RNA-seq experiments. Bioinformatics 28, 2184–2185 (2012).

    CAS  PubMed  Google Scholar 

  52. Liao, Y., Smyth, G.K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    CAS  PubMed  Google Scholar 

  53. Love, M.I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNAseq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed Central  PubMed  Google Scholar 

  54. Huang, S., Holt, J., Kao, C.Y., McMillan, L. & Wang, W. A novel multi-alignment pipeline for high-throughput sequencing data. Database (Oxford) 2014, bau057 (2014).

    Google Scholar 

  55. Kolde, R. pheatmap: Pretty Heatmaps. R package v. 1.0.8. (2015).

  56. Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  57. Quinlan, A.R. & Hall, I.M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    CAS  PubMed Central  PubMed  Google Scholar 

  58. Wickham, H. ggplot2: Elegant Graphics for Data Analysis. (Springer, 2009).

  59. Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W1, W160-5 (2016).

    Google Scholar 

  60. Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).

    PubMed Central  PubMed  Google Scholar 

  61. Arrigoni, L. et al. Standardizing chromatin research: a simple and universal method for ChIP-seq. Nucleic Acids Res. 44, e67 (2016).

    PubMed  Google Scholar 

  62. Baubec, T., Ivánek, R., Lienert, F. & Schübeler, D. Methylation-dependent and -independent genomic targeting principles of the MBD protein family. Cell 153, 480–492 (2013).

    CAS  PubMed  Google Scholar 

  63. Dow, L.E. et al. A pipeline for the generation of shRNA transgenic mice. Nat. Protoc. 7, 374–393 (2012).

    CAS  PubMed Central  PubMed  Google Scholar 

  64. Ran, F.A. et al. Genome engineering using the CRISPR-Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).

    CAS  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

We thank A. Akhtar, U. Bönisch, T. Jenuwein, T. Lämmermann, T. Manke and E. Trompouki (Max Planck Institute of Immunobiology and Epigenetics) for valuable input, cells and reagents; and E. Heard (Institut Curie, France), D. Trono (EPFL), G. Chiosis (Memorial Sloan Kettering Cancer Center) and D. Schübeler (FMI) for kindly providing cells and reagents. We are grateful to R. Rebollo for insightful discussions. This work was financially supported by the Max Planck Society, German Research Foundation (DFG) through the collaborative research center 'Medical Epigenetics' and the Ambizione grant from the Swiss National Foundation (R.S.).

Author information

Authors and Affiliations

  1. Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany

    Barbara Hummel, Barbara Hummel, Erik C Hansen, Erik C Hansen, Aneliya Yoveva, Aneliya Yoveva, Fernando Aprile-Garcia, Fernando Aprile-Garcia, Rebecca Hussong, Rebecca Hussong, Ritwick Sawarkar & Ritwick Sawarkar

  2. Faculty of Biology, University of Freiburg, Freiburg, Germany

    Barbara Hummel & Aneliya Yoveva

Authors
  1. Barbara Hummel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Erik C Hansen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aneliya Yoveva
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fernando Aprile-Garcia
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rebecca Hussong
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ritwick Sawarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

R.S. conceived the project; B.H. and R.S. designed the study; all authors performed experiments and interpreted the results; B.H. and R.S. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Ritwick Sawarkar.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Effect of HSP90 inhibition on expression of endogenous retroviruses.

(a) Inducible shRNA-mediated Hsp90 silencing in mouse ESCs. Immunoblots of total cell extract expressing the indicated constructs are shown. Two independent cell clones were analyzed. (b-f) A genome browser snapshot of genomic loci with indicated ERVs. RNAseq read counts under control and HSP90 inhibition conditions are plotted on the Y-axis. Mouse genomic co-ordinates from the genome build mm10 are as follows: (b) chr16: 57,805,060-57,812,042; (c) chr3: 35,413,307-35,419,237; (d) chr9:25,854,570-25,864,259. (e) chr3: 26,346,706-26,354,408; (f) chr13: 98,985,649-98,996,505. (g) The effect of HSP90 inhibition on expression of TEs in indicated cell types. The numbers of up- and down-regulated TEs (absolute fold change >2, adjusted p-value < 0.01) as annotated by RepeatMasker are indicated. (h) The effect of heat shock and two different HSP90 inhibitor concentrations (50nM and 75nM) on the expression of heat shock genes in ESCs. The same two HSP90 inhibitor concentrations were used to test the expression changes of IAPEz and MERV-L in ESCs. Fold change is shown as a mean of three independent cell-culture replicates (± SEM).

Supplementary Figure 2 Expression of genes close to ERVs is affected by HSP90 inhibition.

(a) HSP90 inhibition-induced changes in expression of genes located within 200kb region around ERV insertions in NPCs. The analyzed subtypes of ERVs are shown in different colors as indicated. (b) A table showing the fold change in three selected ERVs upon HSP90 inhibition, the number of genes adjacent to these ERVs and the mean/median distance between ERVs and adjacent genes. (c,d) HSP90 inhibition-induced changes in expression of all genes in the genome (black box) in comparison with genes close to IAPEz (blue boxes in c) and close to MERVL (red boxes in d) either closer or more distant than 25kb to the closest ERV type in ESCs. Consistent with previous observations (Fig. 2a), the effect of Hsp90 inhibition on gene expression of adjacent genes trails-off with distance. (e,f) Cumulative distributions of the distance between genes and adjacent IAPEz (e) or MERVL(f). Almost 60% of the adjacent genes are within 25kB of ERV. (g) Sashimi plot of a chimeric transcript originating in an adjacent MT2B2 LTR region and continuing transcription in the Ei24 gene region. (h-k) Validation of two chimeric transcripts, Clvs1 and Rimklb, by quantitative PCR (h,i) and PCR (j,k). For qPCR, fold change is shown as a mean of three independent cell-culture replicates (± SEM).

Supplementary Figure 3 Cell-type-specific genes are misregulated after HSP90 inhibition.

(a,b) Highly tissue-specific genes are ectopically activated in NPCs (a) and macrophages (b) upon HSP90 inhibition due to their neighborhood to ERVs. The heat maps were generated using RNAseq data from ENCODE detailing gene expression patterns in each of the individual mouse tissues. (c,d) Genes in (a) and (b) respectively are clustered together by common gene ontology terms as depicted.

Supplementary Figure 4 Comparison of genes upregulated in SETDB1 KO, KAP1 KO and HSP90 inhibition.

(a) A venn diagram comparing genes upregulated in KAP1 KO and SETDB1 KO. Genes that are upregulated in both KOs or only one of the two KOs were then compared with genes upregulated upon HSP90 inhibition (bottom). The P-value estimated by the hypergeometric test is shown. (b,c) HSP90 inhibition affects expression of genes in the vicinity of ERVs similar to KAP1 KO and SETDB1 KO. Changes in expression of genes located within 200kb region around ERV insertions in ESCs upon KAP1 KO (b) and SETDB1 KO (c). The analyzed subtypes of ERVs are shown in different colors as indicated. (d) A Sashimi plot of the indicated locus showing chimeric reads between an ERV and an adjacent gene (co-ordinates correspond to genome build mm10). The number of chimeric reads increases upon HSP90 inhibition, and upon KAP1 deletion, buttressing the claim that HSP90 and KAP1 act in the same pathway.

Supplementary Figure 5 HSP90 inhibition upregulates genes adjacent to ERVs that are repressed by KAP1-mediated H3K9me3 and SETDB1.

(a,b) A genome browser view of two loci showing an ERV and an adjacent gene, with ChIPseq and RNAseq profiles from mouse ES cells with indicated treatments and genotypes. The indicated coordinates correspond to mouse genome build mm10. At both loci, the ERV (IAPEz, green) is bound by KAP1 and shows the repressive mark H3K9me3 (brown box). The repressive mark is KAP1-dependent as the ChIPseq signal of H3K9me3 is reduced in KAP1 deletion. The adjacent gene is de-repressed in HSP90 inhibition, KAP1 deletion and for (b) also in SETDB1 deletion (RNAseq profiles in green and red).

Supplementary Figure 6 H3K9me3 and KAP1 occupancy at HSP90-target ERVs and the effect of stress on ERV transcription

(a) ChIP-qPCR for HSP90 in ESCs. Enrichment is shown as the mean (± SEM). (b) ChIP-qPCR for Kap1 and H3K9me3 in control ESCs and ESCs treated with HSP90 inhibitor. Enrichment is shown as the mean of three independent cell-culture replicates (± SEM) relative to control conditions. The red dotted line indicates the signal intensity in cells not treated with HSP90 inhibitor (c,d) Effect of Kap1 knock-out on H3K9me3 modification at and around HSP90-targeted ERVs, namely IAPEz (c) and MERV-L (d). (e) Experimental design to study the effect of HSP90 inhibition on genes with different strain-specific upstream ERV elements. All genes tested have an ERV either in 129S1 or CASTEiJ strain or both, but no ERV in C57BL6. Effect of HSP90 inhibitor on gene expression was analyzed by quantitative reverse transcription-PCR. Fold Change is shown as a mean of three independent cell-culture experiments (± SEM). (f) Different conditions mimicking environmental stresses upregulate IAPEz and MERV-L in ESC as shown by quantitative PCR. Fold change is shown as means of three independent cell-culture experiments (±SEM).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6 (PDF 1141 kb)

Supplementary Table 1

Gene Ontology Analysis of misregulated genes upon HSP90 inhibition (XLSX 401 kb)

Supplementary Table 2

List of fold changes for all repetitive elements upon HSP90 inhibition (XLSX 549 kb)

Supplementary Table 3

List of differentially expressed genes upon HSP90 inhibition and their fold changes upon Kap1 knock-out and Setdb1 knock-out (XLSX 1712 kb)

Supplementary Table 4

Chimeric transcripts in embryonic stem cells upon HSP90 inhibition, Kap1 knock-out and Setdb1 knock-out (XLSX 19 kb)

Supplementary Table 5

Primer sequences used for PCR, RT-qPCR and ChIP-qPCR (XLSX 12 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hummel, B., Hansen, E., Yoveva, A. et al. The evolutionary capacitor HSP90 buffers the regulatory effects of mammalian endogenous retroviruses. Nat Struct Mol Biol 24, 234–242 (2017). https://doi.org/10.1038/nsmb.3368

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nsmb.3368

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing