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Accurate annotation of human protein-coding small open reading frames


Functional protein-coding small open reading frames (smORFs) are emerging as an important class of genes. However, the number of translated smORFs in the human genome is unclear because proteogenomic methods are not sensitive enough, and, as we show, Ribo-seq strategies require additional measures to ensure comprehensive and accurate smORF annotation. Here, we integrate de novo transcriptome assembly and Ribo-seq into an improved workflow that overcomes obstacles with previous methods, to more confidently annotate thousands of smORFs. Evolutionary conservation analyses suggest that hundreds of smORF-encoded microproteins are likely functional. Additionally, many smORFs are regulated during fundamental biological processes, such as cell stress. Peptides derived from smORFs are also detectable on human leukocyte antigen complexes, revealing smORFs as a source of antigens. Thus, by including additional validation into our smORF annotation workflow, we accurately identify thousands of unannotated translated smORFs that will provide a rich pool of unexplored, functional human genes.

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Fig. 1: Outline of top-down smORF annotation workflow.
Fig. 2: Comparison of translation prediction for smORFs versus annotated ORFs.
Fig. 3: smORF regulation during ER stress.
Fig. 4: Characteristics of protein-coding smORFs.
Fig. 5: Protein-coding smORFs identified on unannotated transcripts.
Fig. 6: Microproteins detected in HLA-I complexes.

Data availability

All sequencing datasets generated in this study are available through GEO (GSE125218).

Code availability

A custom java script used for three-frame in silico translation of assembled transcripts is included as Supplementary Data 4.


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We thank the Saghatelian laboratory for helpful comments and suggestions throughout the study, and N. Ingolia for advice on RNase I digestion conditions. We also thank M. Ku, N. Hah and the Salk Institute Next Generation Sequencing Core for preparation of RNA-seq libraries and high-throughput sequencing of Ribo-seq and RNA-seq libraries. This research was supported by NIH/NIGMS (R01 GM102491, A.S.), Leona M. and Harry B. Helmsley Charitable Trust grant (A.S.), Dr Frederick Paulsen Chair/Ferring Pharmaceuticals (A.S.), NIH/NIGMS postdoctoral fellowship (F32 GM123685, T.F.M.), George E. Hewitt Foundation for medical research (Q.C.) and a Pioneer Fellowship (D.T.). This work was also supported by the Razavi Newman Integrative Genomics and Bioinformatics Core and the Next Generation Sequencing Core Facilities of the Salk Institute with funding from the NIH-NCICCSG (P30 014195) and the Chapman Foundation.

Author information




T.F.M. and A.S. conceived the project, designed the experiments and wrote the manuscript. T.F.M. performed cell culture and prepared RPFs and total RNA. T.F.M. and C.D. prepared Ribo-seq libraries. T.F.M. analyzed Ribo-seq and RNA-seq data, developed the smORF annotation workflow and wrote custom scripts to generate Ribo-seq plots. M.N.S. performed de novo transcriptome assembly and generated ORF databases. Q.C. performed HLA-I experiments. T.F.M. and D.T. analyzed HLA-I proteomics data. All authors discussed the results and edited the manuscript. A.S. supervised the study.

Corresponding authors

Correspondence to Thomas F. Martinez or Alan Saghatelian.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–14.


Reporting Summary

Supplementary Data 1

List of protein-coding smORFs identified in this study and their properties.

Supplementary Data 2

List of significantly regulated ER stress smORFs and annotated genes.

Supplementary Data 3

List of smORFs containing conserved protein domains and predicted transmembrane helices, as well as smORFs encoding peptides identified in HLA-I proteomics datasets.

Supplementary Data 4

Custom java script used to generate a three-frame ORF database from transcriptome assembly in gtf format.

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Martinez, T.F., Chu, Q., Donaldson, C. et al. Accurate annotation of human protein-coding small open reading frames. Nat Chem Biol 16, 458–468 (2020).

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