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STR mutations on chromosome 15q cause thyrotropin resistance by activating a primate-specific enhancer of MIR7-2/MIR1179

Nature Genetics volume 56, pages 877–888 (2024)Cite this article

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Abstract

Thyrotropin (TSH) is the master regulator of thyroid gland growth and function. Resistance to TSH (RTSH) describes conditions with reduced sensitivity to TSH. Dominantly inherited RTSH has been linked to a locus on chromosome 15q, but its genetic basis has remained elusive. Here we show that non-coding mutations in a (TTTG)4 short tandem repeat (STR) underlie dominantly inherited RTSH in all 82 affected participants from 12 unrelated families. The STR is contained in a primate-specific Alu retrotransposon with thyroid-specific cis-regulatory chromatin features. Fiber-seq and RNA-seq studies revealed that the mutant STR activates a thyroid-specific enhancer cluster, leading to haplotype-specific upregulation of the bicistronic MIR7-2/MIR1179 locus 35 kb downstream and overexpression of its microRNA products in the participants’ thyrocytes. An imbalance in signaling pathways targeted by these micro-RNAs provides a working model for this cause of RTSH. This finding broadens our current knowledge of genetic defects altering pituitary–thyroid feedback regulation.

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Fig. 1: STR variants in a primate-specific region of chr15.
Fig. 2: Pedigrees of families with STR mutations showing genotype–phenotype correlation.
Fig. 3: Etiology of familial RTSH and thyroid phenotype in individuals with STRmut.
Fig. 4: STRmut is associated with the activation of a codependent thyroid-specific enhancer cluster.
Fig. 5: STRmut stabilizes TF-binding occupancy.
Fig. 6: Allele-specific overexpression of a miRNA locus downstream of STRmut in the participants’ thyroid glands.
Fig. 7: Overexpression of MIR7-5P in STRmut thyroids is linked to altered proliferative signaling pathways.

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Data availability

All sequence data from the RNA-seq studies are available from the NCBI Sequence Read Archive (BioProject PRJNA972324) at http://www.ncbi.nlm.nih.gov/sra/PRJNA972324. In situ Hi-C contact matrix of the human Embryonic Stem Cell line H1 (ref. 93) was obtained from the 4D Nucleome Data Portal at http://data.4dnucleome.org/. The thyroid-specific ChIP-chip data for histone modifications were from the International Human Epigenome Consortium (IHEC) data portal (http://epigenomesportal.ca/ihec/grid.html), as well as ENCODE (http://www.encodeproject.org/; entries ENCSR033KMZ, ENCSR749MUH, ENCSR203KCB, ENCSR906YES, ENCSR975NOU and ENCSR432GAO). snATAC-Seq data57 were downloaded from the Human Cell Atlas data portal at http://data.humancellatlas.org/explore/projects/c31fa434-c9ed-4263-a9b6-d9ffb9d44005. RNA-seq and microRNA-seq data was downloaded from ENCODE (ENCSR687HJY and ENCSR566RDG). Gene sets for GSEA were obtained from the Molecular Signature Database at http://data.broadinstitute.org/gsea-msigdb/msigdb/release/2022.1.Hs/. miRNA target gene sets were obtained from miRDB (v6.0; http://mirdb.org/download.html)88 and MicroT-CDS (http://dianalab.e-ce.uth.gr/tools)94. Restrictions apply to the availability of Fiber-seq, WGS and patient-specific data generated or analyzed during this study to preserve participants’ confidentiality. The corresponding author will on request detail the restrictions and any conditions under which access to some data may be provided. Source data are provided with this paper.

Code availability

All software used in the study are publicly available as described in the Methods and Reporting Summary. All custom codes used to analyze the Fiber-seq data and generate plots for this study have been deposited in an open repository69,70,74,95.

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Acknowledgements

We thank the families for their participation and invaluable contributions to this research. We thank the following physicians for the referral of families with RTSH that turned out to have mutations in the STR on chromosome 15: I. Rosenthal, The University of Illinois in Chicago, IL, USA (deceased); R. Ruvalcaba, University of Washington, Seattle, WA, USA; M. Christine Vantyghem, Centre Hospitalier Universitaire de Lille, France; M. Abramowicz, Université Libre de Bruxelles, Belgium; G. Van Vliet, Université de Montréal, Quebec, Canada; H. Abdul-Latif, Johns Hopkins University School of Medicine, Baltimore MD, USA; D. L. Metzger, University of British Columbia, Vancouver, BC, Canada and W. Patrick Zeller, Academic Endocrine, Metabolism and Nutrition Group, Wheaton, IL, USA. We also thank S. Cheroux for help with the analysis of WGS data generated by Macrogen, S. Neph for help with the analysis of the Fiber-seq data and T. Karrison for assistance with the statistical analyses. We also thank the Great Ape Information Network, Primate Research Institute and the Wildlife Research Center of Kyoto University, JMC Kyoto City Zoo, and Ueno Zoological Gardens for providing Gorilla samples. This work was supported by the Cooperative Research Program of Primate Research Institute, Kyoto University (2020-C-12). This work was supported in part by grants from the National Institutes of Health (DK15070 (to S.R.), DK134486 (to H.G.), 1DP5OD029630 (to A.B.S.), U01 HG011744 and UM1 HG006493 (to M.B.)), the Belgian Kids Fund (to G.S.) and not for profit Association Recherche Biomedicale et Diagnostic (to G.V. and S.C.). A.B.S. holds a Career Award for Medical Scientists from the Burroughs Wellcome Fund and is a Pew Biomedical Scholar.

Author information

Authors and Affiliations

  1. Department of Internal Medicine, Medical School, University of Michigan, Ann Arbor, MI, USA

    Helmut Grasberger

  2. Department of Medicine, The University of Chicago, Chicago, IL, USA

    Alexandra M. Dumitrescu, Xiao-Hui Liao, Panudda Srichomkwun, Theodora Pappa, Monica Malheiros França, Kazumichi Onigata & Samuel Refetoff

  3. Committee on Molecular Metabolism and Nutrition, The University of Chicago, Chicago, IL, USA

    Alexandra M. Dumitrescu

  4. Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA

    Elliott G. Swanson, Jane Ranchalis, Mitchell R. Vollger, Andrew B. Stergachis, Jessica X. Chong & Michael J. Bamshad

  5. Department of Genome Sciences, University of Washington, Seattle, WA, USA

    Elliott G. Swanson, Andrew B. Stergachis & Michael J. Bamshad

  6. Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA

    Roy E. Weiss

  7. Institute of Transformative Bio-Molecules (WPI-ITbM) and Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan

    Junfeng Chen & Takashi Yoshimura

  8. Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium

    Phillip Hoffmann & Guillaume Smits

  9. Michigan Medicine BRCF Bioinformatics Core, University of Michigan, Ann Arbor, MI, USA

    Rebecca Tagett

  10. Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles, Brussels, Belgium

    Sabine Costagliola & Gilbert Vassart

  11. Brotman-Baty Institute for Precision Medicine, Seattle, WA, USA

    Andrew B. Stergachis, Jessica X. Chong & Michael J. Bamshad

  12. Center of Human Genetics, Hôpital Erasme, Hôpital Universitaire de Bruxelles, and Department of Genetics, Hôpital Universitaire des Enfants Reine Fabiola, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium

    Guillaume Smits

  13. Committee on Genetics, The University of Chicago, Chicago, IL, USA

    Samuel Refetoff

  14. Department of Pediatrics, The University of Chicago, Chicago, IL, USA

    Samuel Refetoff

Authors
  1. Helmut Grasberger
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  2. Alexandra M. Dumitrescu
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  3. Xiao-Hui Liao
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  4. Elliott G. Swanson
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  5. Roy E. Weiss
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  6. Panudda Srichomkwun
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  7. Theodora Pappa
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  8. Junfeng Chen
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  9. Takashi Yoshimura
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  10. Phillip Hoffmann
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  11. Monica Malheiros França
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  12. Rebecca Tagett
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  13. Kazumichi Onigata
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  14. Sabine Costagliola
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  15. Jane Ranchalis
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  16. Mitchell R. Vollger
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  17. Andrew B. Stergachis
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  18. Jessica X. Chong
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  19. Michael J. Bamshad
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  20. Guillaume Smits
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  21. Gilbert Vassart
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  22. Samuel Refetoff
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Contributions

H.G. and S.R. conceptualized the study, organized the data, prepared the figures and cowrote the original draft of the paper. S.R. and G.V. identified the first families, and advised and helped in devising all studies. S.R., A.M.D. and R.E.W. recruited, examined and followed participants and family members. G.S. analyzed the initial WGS data and identified the STR variant in humans with RTSH. He was assisted by P.H. H.G. and X.-H.L. designed and performed the laboratory studies. H.G. and R.T. analyzed the RNA-seq data. P.S., T.P., M.M.F. and K.O. performed gene sequencing and analyzed the results. J.C. and T.Y. obtained tissues, and sequenced and analyzed the Gorilla DNA samples. J.X.C. and M.J.B. performed WGS, analyzed the results and wrote parts of the paper. J.R. and A.B.S. performed the Fiber-seq reaction. M.R.V., E.G.S. and A.B.S. performed the Fiber-seq data analysis. S.C. advised and planned some of the studies. All authors reviewed and edited the paper.

Corresponding author

Correspondence to Samuel Refetoff.

Ethics declarations

Competing interests

A.B.S. is a co-inventor on a patent relating to the Fiber-seq method. The other authors declare no competing interests.

Peer review

Peer review information

Nature Genetics thanks Andrea Cortese, Luca Persani, Val Sheffield and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Alignment of the human STR (TTTG)4 with homolog sequences from other primates.

We searched 86 nonhuman primate genomes available in the NCBI databank (refseq_genomes; accessed 09/2023) by BLAST search with a 278 bp human sequence centered around the STR. Of 49 Old World Primates, 47 had a single match over the full sequence that was confirmed to be syntenic (that is, upstream of the MIR7-2 locus). All of these had a TTTG repeat sequence within the T-rich sequence (corresponding to the poly(A) tail of the AluSx1 retrotransposon). For the remaining two Old World Primate genomes (Rhinopithecus strykeri and Rhinopithecus bieti), we were not able to ascertain a clear homolog, although the homolog was present in another member of the same genus (R. roxellana). For the 37 other nonhuman primate genomes (including 13 New World Primates, 2 Tarsiiformes, 1 Chyromyiformes, 16 Lemuriformes, 5 Lorisiformes), only 4 of the New World Primate genomes (Cebus albifrons, Sapajus apella, Sanguinus midas, Aotus nancymaae) had a detectable syntenic homolog of the STR encompassing region, but their T-rich sequence was notably devoid of TTTG repeats. These data place the insertion of the AluSx1 retrotransposon into this locus before the split between New and Old World Primates, that is about 40 million years ago. This finding is consistent with data showing that the AluS subfamily arose from AluJ after the split between Strepsirrhini (Lemuriformes and Lorisiformes) from the common ancestors of Old and New World Primates96,97. Since essentially all extant members of the Old World Primate lineage seem to carry a TTTG repeat sequence in this interval, we postulate that it first evolved in the common ancestor of Old World Primates. Note that for genera with multiple representatives with virtually identical sequences, only a subset of species is shown.

Extended Data Fig. 2 Thyroid-specificity of the STR-associated cis-regulatory element.

Shown are snATAC-Seq peak data57 for different cell types. The STR maps to a predicted cis-regulatory element specifically active in thyroid follicular cells.

Extended Data Fig. 3 Fiber-seq chromatin accessibility at the STR site and miRNA locus.

a, Fiber-seq chromatin accessibility tracks showing the FIRE scores at the enhancer cluster surrounding the STR site in thyroid tissue from two individuals with RTSH, thyroid tissue from a healthy control individual, and MNG thyroid tissue. For the individuals with RTSH, FIRE signal is separated by haplotype. b, Bar plots showing the mean FIRE scores within the elements highlighted above across the samples shown in a. Of note, multi-nodular goiter (MNG) tissue showed selective activation of element 5 within this enhancer cluster, with elements 1–3 remaining silenced. c, DNase-seq signal at the miRNA locus from ENCODE, as well as haplotype-specific Fiber-seq chromatin accessibility in this region. Note that the miRNA promoter region selectively demonstrates haplotype-specific chromatin accessibility.

Source data

Extended Data Fig. 4 Relationship between CpG methylation and chromatin accessibility at the STR enhancer cluster.

For each Fiber-seq sequencing read at this site, shown is the per-molecule m6A-marked chromatin accessibility stencils (left), as well as the per-molecule methylation status of CpG dinucleotides (right) for the same reads. CpG methylation status is indicated using a color gradient from blue to red, with blue indicating unmethylated CpGs, and red indicating methylated CpGs, and the shading according to the precision of the methylation calls according to Primrose. Reads are separated out by sample, as well as by haplotype within the RTSH samples. Reads are then ranked based on the CpG methylation status surrounding the STR site, with hypo-CpG methylated reads being on top. This reveals that individual chromatin fibers harboring chromatin accessibility at this enhancer cluster similarly had hypo-CpG methylation of the surrounding CpG dinucleotides. However, hypo-CpG methylation of the surrounding CpGs was similarly observed on fibers lacking chromatin accessibility at elements 1–3, indicating that hypo-CpG methylation is necessary, but not sufficient for actuating this codependent enhancer cluster.

Extended Data Fig. 5 Tissue-specific DNA hypomethylation of the STRmut allele.

a, Upper panel depicts selected CpG sites hypomethylated on the STRmut haplotype in thyroid (compare Fig. 5a). The tissue-specific methylation profiles of the STRwt allele were established by allele-specific amplification from bisulfite treated DNA from either thyroid tissue (from n = 10 individuals per CpG site), skin fibroblasts (n = 7) or leukocytes (n = 6), and the methylation status (%methylated; mean±SEM) of six CpG sites (m1, m3, m6, m7, m8, m9) quantified following digestion with methylation-sensitive restriction endonucleases. Three CpG sites (m7, m8, m9) close to the STRwt sequence were hypomethylated in thyroid compared to fibroblasts and leukocytes suggesting their relevance for thyroid-specific expression under normal conditions. b, Tissue-specific relative methylation of STRmut (vs STRwt) in thyroid tissue (from n = 2 participants with RTSH), cultured fibroblasts (n = 3), and leukocytes (n = 4). On the chromosome harboring STRmut, m7 and m8 appear to be hypomethylated in fibroblasts albeit to lesser degree than in thyroid. In contrast, for the m9 site, hypomethylation of STRmut chromosomes appears to be restricted to thyroid. The latter site locates to a binding motif of C/EBPB and is hypermethylated in fibroblasts (both, STRwt and STRmut). These results could indicate that in fibroblasts, binding of a forkhead domain TF (other than FOXE1) at the STR region produces a limited increase in accessibility that does not extend to m9. In thyroid, FOXE1 produces more extensive accessibility followed by hypomethylation and binding of an additional TF, that is, C/EBPB.

Source data

Extended Data Fig. 6 Transcriptional activity of the MIR7-2/MIR1179 locus indicating high thyroid specificity of mature miRNA expression.

a, Top panel: Sashimi plot visualizing coverage and splice junctions from aligned RNA-seq data from Pt1. The acute absence of reads overlapping with the localization of the miRNA stem loop sequences suggests efficient processing of the pri-MIR by the Microprocessor complex. Lower panel: annotation track showing the relative positions of relevant features including the MIR7-2 and MIR1179 stem loops, the major polyA site where most pri-MIR transcripts terminate, and spliced readthrough transcripts that connect to the first coding exon of AEN. LINC0158 is expressed on the opposite strand and overlaps with pri-MIR transcripts within the core of the bidirectional promoter (containing a CpG island). b, Tissue expression profiling of products from the miRNA locus. For each tissue, total RNA pooled from at least 3 individual donors was utilized (Ambion). Data (mean±SD; 3 replicate amplifications) were obtained by real-time reverse transcription PCR assays, normalized for either RNU44 (MIR7-5P and MIR1179) or UBE2D3 (spliced readthrough transcript, unprocessed MIR7-2 stem loop, LINC01586, AEN)85, and expressed relative to the expression detected in thyroid tissue (set to 100%).

Source data

Extended Data Fig. 7 Data supporting activated EGF(-like) signaling activity.

a, Subset of DEGs (n = 2 STRmut vs n = 5 NL STRwt thyroids) that were directionally consistent with EGF signaling activity (from the analysis shown in Fig. 7e). b, Expression values of DEGs shown in a. Gene expression profile of an STRwt (nontoxic) MNG is shown for comparison. c, Downregulation of HPN encoding an EGFR-inactivating protease. Specific suppression of HPN expression in STRmut thyroid glands by RNA-seq (n = 2 thyroids with STRmut and 5 NL with STRwt) and RT-qPCR. For RT-PCR, samples included n = 4 NL thyroids (2 distinct from RNAseq samples), n = 3 with AITD, n = 2 with PTC, and one with MNG (all STRwt). For both Pt1 and Pt2 with STRmut, two separate specimens from their excised thyroid glands were analyzed by qPCR. ****, FDR = 2 × 10−21 (DESeq2). d, Alignment of MIR7-5P to predicted 3′-UTR target sites94 of HPN. Watson–Crick pairings are shown as vertical dashes and G:U wobble pairings by dots. TPM, transcripts per million.

Source data

Extended Data Table 1 Genetic variants in gnomAD that alter the (TTTG)4 repeat or the immediately flanking sequence
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Supplementary information

Supplementary Information

Supplementary Figs. 1–11.

Reporting Summary

Peer Review File

Supplementary Tables

Supplementary Table 1: Demography and number of individuals with STRmut and STRwt. Supplementary Table 2: Mature miRNA products produced from the STR-controlled pri-MIR in thyroid glands. Supplementary Table 3: Sequences of oligonucleotides.

Supplementary Data 1

Statistical supporting data for Supplementary Figs. 1–11.

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Unprocessed histology image for Fig. 3f.

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Grasberger, H., Dumitrescu, A.M., Liao, XH. et al. STR mutations on chromosome 15q cause thyrotropin resistance by activating a primate-specific enhancer of MIR7-2/MIR1179. Nat Genet 56, 877–888 (2024). https://doi.org/10.1038/s41588-024-01717-7

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