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Quantitative profiling of pseudouridylation landscape in the human transcriptome

Nature Chemical Biology volume 19, pages 1185–1195 (2023) Cite this article

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Abstract

Pseudouridine (Ψ) is an abundant post-transcriptional RNA modification in ncRNA and mRNA. However, stoichiometric measurement of individual Ψ sites in human transcriptome remains unaddressed. Here we develop ‘PRAISE’, via selective chemical labeling of Ψ by bisulfite to induce nucleotide deletion signature during reverse transcription, to realize quantitative assessment of the Ψ landscape in the human transcriptome. Unlike traditional bisulfite treatment, our approach is based on quaternary base mapping and revealed an ~10% median modification level for 2,209 confident Ψ sites in HEK293T cells. By perturbing pseudouridine synthases, we obtained differential mRNA targets of PUS1, PUS7, TRUB1 and DKC1, with TRUB1 targets showing the highest modification stoichiometry. In addition, we quantified known and new Ψ sites in mitochondrial mRNA catalyzed by PUS1. Collectively, we provide a sensitive and convenient method to measure transcriptome-wide Ψ; we envision this quantitative approach would facilitate emerging efforts to elucidate the function and mechanism of mRNA pseudouridylation.

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Fig. 1: Bisulfite-Ψ adduct induces nucleotide deletion during reverse transcription.
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Fig. 2: PRAISE accurately measures Ψ stoichiometry in rRNA and synthetic spike-in oligos.
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Fig. 3: The quantitative landscape of Ψ in the human transcriptome.
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Fig. 4: The quantitative PUS-dependent Ψ maps.
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Fig. 5: Mitochondrial Ψ landscape and Ψ enzymes.
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Data availability

Raw and processed sequencing data have been deposited into the NCBI Gene Expression Omnibus (GEO) under the accession number GSE212210. The public datasets of Ψ-seq, Pseudo-seq, CeU-seq and BID-seq were downloaded from the GEO database with the accession numbers: GSE60047, GSE58200, GSE63655 and GSE179798. The reference transcriptome GRCh38 was downloaded from the following link: https://www.ncbi.nlm.nih.gov/data-hub/genome/GCF_000001405.40/. The reference of mitochondrial genome was downloaded from the following link: https://www.ncbi.nlm.nih.gov/nuccore/251831106. Source data are provided with this paper.

Code Availability

PRAISE tools, including a modified biopython package and several python scripts, were deposited on GitHub (https://github.com/Zhe-jiang/PRAISE). Besides, a detailed bioinformatics guide is available to help conduct the whole pipeline of PRAISE.

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Acknowledgements

The authors would like to thank G. Luo (State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China) for providing IVT RNA, H. Meng and B. He for advice on tailored alignment, R. Xu for help with TA cloning experiments, X. Xiong and H. Wu for advice on mitochondrial analysis, J. Song and H. Sun for discussions. We thank National Center for Protein Sciences at Peking University for assistance with fragments analysis and NGS experiments and High-Performance Computing Platform of the Center for Life Science for assistance with the bioinformatic analysis. This work was supported by the National Key Research and Development Program of China (2019YFA0110900 to C.Y., 2019YFA0802200 to C.Y., 2021YFC2302401 to M.Z. and 2020YFA0710401 to J.P.), National Natural Science Foundation of China (21825701 and 92153303 to C.Y.) and China Postdoctoral Science Foundation (2020M680219 to M.Z.).

Author information

Author notes

  1. These authors contributed equally: Meiling Zhang, Zhe Jiang.

Authors and Affiliations

  1. State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China

    Meiling Zhang, Zhe Jiang, Yuan Zhuang, Bo Lu, Jinying Peng & Chengqi Yi

  2. Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China

    Yichen Ma, Kai Li & Chengqi Yi

  3. Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China

    Yichen Ma & Kai Li

  4. School of Life Sciences, Tsinghua University, Beijing, China

    Wenqing Liu

  5. Tsinghua-Peking Joint Center for Life Sciences, Tsinghua University, Beijing, China

    Wenqing Liu

  6. Department of Chemical Biology and Synthetic and Functional Biomolecules Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, China

    Chengqi Yi

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Contributions

M.Z., Z.J. and C.Y. conceived the project and wrote the manuscript with the help of J.P.; M.Z. and Z.J. developed the chemical assay under the guidance of C.Y.; M.Z. designed and performed the experiments with the help of Y.M.; Z.J. designed the tailored alignment method and performed the bioinformatic analysis of NGS data with the help of W.L. and K.L.; Y.Z. performed validation experiments for the mitochondrial site and immunofluorescences; B.L. constructed TRUB1 knockout cells and helped screen RT conditions; C.Y. supervised the project.

Corresponding author

Correspondence to Chengqi Yi.

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Extended data

Extended Data Fig. 1 Performance of different chemical reaction and RTase on capturing Ψ-induced deletion signature under different conditions.

(a) The deletion rate of Ψ1367 site in 18S rRNA under different sulfite/bisulfite conditions. The standard bisulfite reagent (pH=5.1) is equivalent to a molar mixture of 95% bisulfite and 5% sulfite (bisulfite:sulfite=19:1). The proportion of sulfite and bisulfite was increased from 95% sulfite/5% bisulfite to 50% sulfite/50% bisulfite, and the pH values are showed in the horizontal axis. 50% sulfite/50% bisulfite reagent is corresponding to pH 6.5. (b) Chemical mechanism of conversion from cytidine to uridine, which is both acid-dependent and sulfite-dependent. (c) Chemical mechanism of reaction between pseudouridine and sulfite reagent. After Michael addition, Ψ-SO3 generates two isoforms. Then, after two steps of reverse Michael addition and Michael addition, the final products are two ring-open isoforms. (d) Chemical mechanism of transformation from uridine to uridine-bisulfite adduct. After alkaline treatment during the desulfonation step, the bisulfite group can be removed reversibly. (e) The deletion rate of Ψ1367 site in 18S rRNA under different time and temperature conditions. The horizontal axis represents time and temperature, and the vertical axis represents the deletion rate. (f) Fragments analysis of oligo RNA after Tris-HCl treatment for different time. ‘1 h’, ‘30 min’ and ‘15 min’ represent different treatment time. (g) Fragment analysis of fragmented total RNA. ‘untreated’ represents fragmented total RNA without treatment and ‘sulfite/bisulfite (85%/15%)’ represents fragmented total RNA with sulfite/bisulfite treated. (h) Heatmap of deletion rate of Ψs in rRNA under different reverse transcriptase conditions.

Extended Data Fig. 2 Identification of known and novel rRNA sites under DKC1 knockdown and evaluation of the deletion rate for other RNA modifications.

(a) An IGV view of read mapping showing deletion signals in position 1840–1860 of 28S rRNA. Two deletion sites were marked between four consecutive Ts in 1847–1850. (b) Boxplot representing the relative mRNA expression level of shControl and shDKC1 samples detected by qPCR. n = 2 biological replicates. (c) The protein expression level of DKC1 knock-down cells was determined by Western blot. GAPDH was used as a loading control. (d) Heatmap of deletion rates of all Ψ sites in 5.8S rRNA, 18S rRNA and 28 rRNA between shControl and shDKC1 sample. (e) Deletion rate of three additional Ψ sites in rRNA in shControl and shDKC1 sample. Each sites have two replicates of shControl and shDKC1 sample. (f) Deletion rate of treated and untreated samples on known Ψm and m1acp3Ψ sites in rRNA. (g) Deletion rate of treated and untreated samples on known Am (n = 34), Cm (n = 24), Gm (n = 32), and Um (n = 19) sites in rRNA. Error bars represent mean ± SD. (h) Deletion rate of treated and untreated samples on known m62A, m6A, m1A, ac4C, and m5C sites in rRNA.

Source data

Extended Data Fig. 3 Quality and statistics of sequencing libraries.

(a) Distribution of fragments size in two treated WT libraries after library construction. (b) Distribution of fragments size in two untreated WT libraries after library construction. (c) Distribution of sequencing reads length in two pairs of treated and untreated WT libraries. Data from Illumina is analyzed by FastQC. (d) Mapping rates of WT and KO libraries from WT, PUS1, PUS7, and TRUB1 knock-out cell lines.

Extended Data Fig. 4 Performance comparison of PRAISE data from different biological replicates and KAPA RNA-seq kit.

(a, b) The performance of a new batch of HEK293T cells using Takara v3 library construction. a, Venn plot depicting ~78% overlapping between two technical replicates. b, Correlation of deletion rates of overlapping 2,749 Ψ sites detected in both technical replicates (R2 = 0.965). (c) Venn plot depicting the 84.6% overlapping between two biological replicates using Takara v3 library construction. ‘Overlapped sites of 1st batch’ represents 2,209 Ψ sites originally reported in HEK293T cells, and ‘Overlapped sites of 2nd batch’ represents 2,749 Ψ sites detected in two technical replicates of 2nd batch cells. (d) Correlation of deletion rates of overlapped Ψ sites in (c) of two biological replicates (R2 = 0.966). (e, f) The performance of a new batch of HEK293T cells using KAPA library construction kit (KAPA Stranded RNA-Seq Kit, #kk8400). e, Venn plot depicting the ~86% overlapping between two technical replicates. f, Correlation of deletion rates of 2,055 Ψ sites detected in two technical replicates (R2 = 0.980). (g) Venn plot depicting the 67.5% overlapping between two biological replicates using Takara v3 library construction and KAPA kit. ‘Overlapped sites of 1st batch’ represents originally 2,209 Ψ sites reported in HEK293T cells, and ‘Overlapped sites of 3rd batch’ represents 2,055 Ψ sites detected in two technical replicates of 3rd batch cells. (h) Correlation of deletion rates of overlapped Ψ sites in (g) between two biological replicates (R2 = 0.959).

Extended Data Fig. 5 Quality control of IVT samples and codon usage of cellular Ψ sites.

(a) Venn diagram depicting gene overlap between wild type cellular RNA sample (red) and IVT sample (blue). IVT, in vitro transcription. (b) Read coverage from the 5’ end to the 3’ end of transcripts in wild type cellular RNA (orange) and IVT RNA (blue) libraries. Each library has two replicates and are combined and scaled to a normalized gene model. (c) Venn diagram depicting overlap of Ψ sites between IVT replicate 1 (red) and IVT replicate 2 (blue). (d) Genes containing Ψ sites are analyzed using gene ontology of cellular components. P values were adjusted using the Benjamini–Hochberg procedure. (e) Bar plot of relative enrichment distribution of 2,209 Ψ sites across transcript segments. CDS, coding sequence. (f) Pi chart representing proportions of Ψ sites within ‘T’, ‘TT’ and ‘≥TTT’ contexts in human mRNA. (g) The counts of Ψ sites in codon types as well as positions are shown. Ψ sites observed at the first (purple), second (pink) and third (blue) codon position are indicated. Note that only Ψ sites present in the single and double U contexts (accounting for approximately 39% and 40% of all Ψ sites) were used for the codon preference analysis.

Extended Data Fig. 6 Distribution and secondary structure of PUS-dependent Ψ sites.

(a) Quantification of Ψ modification of small RNA (<200 nt) in wild type and PUS knocked out cell lines. Values and error bars represent mean ± s.d. of n = 3 biological replicates. (b) Distribution of PUS1 dependent Ψ sites in human mRNA (32) and ncRNA (5). CDS, coding sequence. (c) Distribution of PUS7 dependent Ψ sites in human mRNA (145) and ncRNA (19). (d) Distribution of TRUB1 dependent Ψ sites in human mRNA (305) and ncRNA (38). (e) Bar plot of relative enrichment distribution of 165 PUS7-dependent Ψ sites in HEK293T mRNA. CDS, coding sequence. (f) Bar plot of relative enrichment distribution of 346 TRUB1-dependent Ψ sites in HEK293T mRNA. CDS, coding sequence. (g) Deletion rates of Ψ sites in mRNA in WT and DKC1 KD cells. The horizontal axis represents deletion rates of mRNA Ψ sites in WT HEK293T cells, and the vertical axis represents deletion rates of mRNA Ψ sites in DKC1 KD cells. (h) Bar plot of deletion rate of Ψ sites (n = 473) in mRNA between wild type and DKC1 KD sample. Box plot middle lines mark the median and the boundaries of the box indicate the 25th and 75th percentiles; whiskers encompass all data that are not considered outliers. (i) Motif analysis of DKC1-dependent Ψ sites within the single U context. (j) Distribution and relative enrichment across transcript segments of 473 DKC1-dependent Ψ sites in HEK293T mRNA. (k) Heatmap depicting secondary structure of 37 PUS1 dependent Ψ sites. A 24 nucleotides interval around Ψ site (at position 0) is selected. Paired bases are marked in red and unpaired bases are marked in blue. (l) Heatmap depicting secondary structure of 165 RNA strands containing PUS7 dependent Ψ sites. A 24 nucleotides interval around Ψ site (at position 0) is selected. Paired bases are marked in red and unpaired bases are marked in blue.

Extended Data Fig. 7 Comparison of PRAISE and the CMC-based Ψ methods, including Ψ-seq, Pseudo-seq, CeU-seq.

(a) Venn diagram depicting the overlap of Ψ sites detected in mRNA between PRAISE and Ψ-seq. (b) Deletion rates of Ψ-seq-only sites in PRAISE (n = 231) and random ‘U’ sites in PRAISE (n = 2,000). They had about 2% deletion rates and are higher than the background signal, but were not called because they are below our 5% cutoff. (c) Read coverage of Ψ-seq-only sites in PRAISE (n = 231) and PRAISE-only sites in Ψ-seq data (n = 2,101). (d) Venn diagram depicting the overlap of Ψ sites detected in mRNA between PRAISE and Pseudo-seq. (e) Venn diagram depicting the overlap between PRAISE and CeU-seq Ψ sites. (f) Pi chart of CeU-seq-only sites in PRAISE data. ‘Low coverage’ represents the coverage is lower than 20 reads. ‘High p value’ represents the p-value is higher than 0.0001 in PRAISE data. (g) Deletion rates of CeU-seq-only sites with sufficient reads in PRAISE (n = 776) and random U sites in PRAISE data (n = 2,000). (h) Pi chart of 1,642 PRAISE-only sites in CeU-seq data. (i) Stop rates of 48.2% of PRAISE-only sites with read coverage in CeU-seq data (n = 791). Data from three replicates are shown. (j, k) Venn diagram depicting the overlap between PRAISE sites and highest (j) or high (k) confidence sites from Safra et al in Genome research 2017. (l) Deletion rate of non-overlapped ‘high-confidence’ sites in PRAISE (n = 542) and random U sites in PRAISE data (n = 2,000). (m) Read coverage of non-overlapped ‘high-confidence’ sites in PRAISE data (n = 542) and PRAISE-only sites in Ψ-seq data (n = 1,758). Box plot middle lines mark the median and the boundaries of the box indicate the 25th and 75th percentiles; whiskers encompass all data that are not considered outliers.

Extended Data Fig. 8 Comparison of PRAISE and BID-seq data.

(a, b) Deletion rates of Ψ sites in 18 s rRNA(a) and 28 s rRNA(b) detected by PRAISE and BID-seq. (c) Deletion rates of all detected Ψ sites in 18 rRNA and 28S rRNA between PRAISE and BID-seq. The horizontal axis represents deletion rates of rRNA Ψ sites in PRAISE, and the vertical axis represents deletion rates of rRNA Ψ sites in BID-seq. (d) Venn diagram depicting two Ψ sites (Ψ in MDK and NDUFS2) detected in stop codon by both PRAISE and BID-seq. (e) Venn diagram depicting four Ψ sites detected in mitochondrial mRNA by PRAISE (Ψ in MT-CO1, MT-CO3, MT-ND4, and MT-CYB), two of which are also detected by BID-seq (Ψ in MT-CO1 and MT-CO3).

Extended Data Fig. 9 Validation of four mRNA Ψ sites in HEK239T cells identified by PRAISE.

(a) Four representative mRNA Ψ sites identified by PRAISE only or also by CMC-based approaches and BID-seq. Noted that they were all assigned to a particular Ψ writer by PRAISE; Ψ sites in NBAS and UNC13B were only detected by PRAISE. (b) Deletion rates of the four mRNA sites in HEK293T wild-type and PUS1, PUS7, TRUB1 knock-out cell lines in PRAISE data. (c) Melting curves of qPCR products containing four mRNA sites detected by CMC-assisted, qPCR-based method. The curves were obtained by high-resolution melting analysis.

Extended Data Fig. 10 Ψ sites in mt-tRNA and mitochondrial targets assigned to PUS1.

(a) Schematic diagram of PRAISE to identify Ψ sites in mitochondrial tRNAs. Total small RNAs are first treated by Alkb demethylase to demethylase m1A and m3C, and then treated with 85% sulfite/15% bisulfite solution. RNA was then followed by 3’ adapter ligation, reverse transcription, 5’ linker ligation, PCR, and sequencing. The ‘Untreated’ sample is set as a negative control. (b) Venn diagram depicting the overlap of Ψ sites detected in mitochondrial tRNA between PRAISE and previously reported method (Suzuki T et al.41). (c) Deletion rates of 51 known Ψ sites and 1 novel of Ψ sites in mitochondrial tRNA. For each site, deletion rates of treated and untreated are marked with different symbols. (d) Sequence alignment and comparation of PUS1 isoform 1 and isoform 2 in human cell line. Mitochondrial target sequence of PUS1 isoform 1 is marked in red color. (e) Double immunofluorescence staining of HeLa cells transfected with expression vectors encoding Flag-tagged PUS1 isoform 1 and 2 (green) and DAPI (blue). The left panels show the expression vectors, and the right panels show the green and blue images merged in Adobe Photoshop. Representative images were obtained under the same exposure condition from n = 3 biological repeats. (f) Deletion rates of Ψ sites in mitochondrial RNA (mt-RNA) in PUS1 KO and HEK293T cells. The horizontal axis represents deletion rate of mt-RNA Ψ sites in HEK293T cells, and the vertical axis represents deletion rate of mt-RNA Ψ sites in PUS1 KO cells. (g) Sequencing depth of regions surrounding Ψ3286 in mt-Leu tRNA and the corresponding deletion rate in HEK293T (WT) and TRUB1 KO treated samples are plotted. (h) Deletion rate of Ψ sites in mt-RNA in PUS7 KO and HEK293T cells. The horizontal axis represents deletion rate of mt-RNA Ψ sites in HEK293T cells, and the vertical axis represents deletion rate of mt-RNA Ψ sites in PUS7 KO cells.

Supplementary information

Supplementary Information (download PDF )

Supplementary Fig. 1 and Supplementary Tables 1–3.

Reporting Summary (download PDF )

Supplementary Datasets 1–6 (download XLSX )

Ψ identified by PRAISE in HEK293T rRNA; a list of Ψ identified by PRAISE in HEK293T mRNAs and ncRNAs; four PUS-dependent Ψ lists in HEK293T mRNAs and ncRNAs; expression level of mRNA containing PUS-dependent Ψ; a list of mitochondrial Ψ in HEK293T using polyA+ RNA fractions; a list of Ψ in HEK293T mitochondrial tRNAs.

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Zhang, M., Jiang, Z., Ma, Y. et al. Quantitative profiling of pseudouridylation landscape in the human transcriptome. Nat Chem Biol 19, 1185–1195 (2023). https://doi.org/10.1038/s41589-023-01304-7

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