Structure-guided isoform identification for the human transcriptome
- Johns Hopkins University, United States
- Seoul National University, Republic of Korea
Abstract
Recently-developed methods to predict three-dimensional protein structure with high accuracy have opened new avenues for genome and proteome research. We explore a new hypothesis in genome annotation, namely whether computationally predicted structures can help to identify which of multiple possible gene isoforms represents a functional protein product. Guided by protein structure predictions, we evaluated over 230,000 isoforms of human protein-coding genes assembled from over 10,000 RNA sequencing experiments across many human tissues. From this set of assembled transcripts, we identified hundreds of isoforms with more confidently predicted structure and potentially superior function in comparison to canonical isoforms in the latest human gene database. We illustrate our new method with examples where structure provides a guide to function in combination with expression and evolutionary evidence. Additionally, we provide the complete set of structures as a resource to better understand the function of human genes and their isoforms. These results demonstrate the promise of protein structure prediction as a genome annotation tool, allowing us to refine even the most highly-curated catalog of human proteins. More generally we demonstrate a practical, structure-guided approach that can be used to enhance the annotation of any genome.
Data availability
Gene identifiers for all predicted protein isoforms as well as pLDDT scores and evolutionary conservation data from mouse can be found in table S1. Predicted scores and GTEx expression data for all isoforms overlapping a MANE locus can be found in table S2. Data for the 401 alternate isoforms with evidence of relatively superior structure, and possibly superior function, can be found in table S3. Additionally, all data can be downloaded from the project website, isoform.io.
Article and author information
Author details
Funding
National Institutes of Health (R01-HG006677)
- Steven L Salzberg
National Institutes of Health (R35-GM130151)
- Steven L Salzberg
National Research Foundation of Korea (2019R1-A6A1-A10073437)
- Martin Steinegger
National Research Foundation of Korea (2020M3-A9G7-103933)
- Martin Steinegger
National Research Foundation of Korea (2021-R1C1-C102065)
- Martin Steinegger
National Research Foundation of Korea (2021-M3A9-I4021220)
- Martin Steinegger
Seoul National University (Creative-Pioneering Researchers Program)
- Martin Steinegger
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Volker Dötsch, Goethe University, Germany
Version history
- Preprint posted: June 9, 2022 (view preprint)
- Received: August 9, 2022
- Accepted: December 13, 2022
- Accepted Manuscript published: December 15, 2022 (version 1)
- Version of Record published: January 4, 2023 (version 2)
- Version of Record updated: January 17, 2023 (version 3)
Copyright
© 2022, Sommer et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 4,321
- views
-
- 457
- downloads
-
- 14
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Structure-guided isoform identification for the human transcriptome
eLife 11:e82556.
https://doi.org/10.7554/eLife.82556
Further reading
-
- Genetics and Genomics
Telomeres, which are chromosomal end structures, play a crucial role in maintaining genome stability and integrity in eukaryotes. In the baker’s yeast Saccharomyces cerevisiae, the X- and Y’-elements are subtelomeric repetitive sequences found in all 32 and 17 telomeres, respectively. While the Y’-elements serve as a backup for telomere functions in cells lacking telomerase, the function of the X-elements remains unclear. This study utilized the S. cerevisiae strain SY12, which has three chromosomes and six telomeres, to investigate the role of X-elements (as well as Y’-elements) in telomere maintenance. Deletion of Y’-elements (SY12YΔ), X-elements (SY12XYΔ+Y), or both X- and Y’-elements (SY12XYΔ) did not impact the length of the terminal TG1-3 tracks or telomere silencing. However, inactivation of telomerase in SY12YΔ, SY12XYΔ+Y, and SY12XYΔ cells resulted in cellular senescence and the generation of survivors. These survivors either maintained their telomeres through homologous recombination-dependent TG1-3 track elongation or underwent microhomology-mediated intra-chromosomal end-to-end joining. Our findings indicate the non-essential role of subtelomeric X- and Y’-elements in telomere regulation in both telomerase-proficient and telomerase-null cells and suggest that these elements may represent remnants of S. cerevisiae genome evolution. Furthermore, strains with fewer or no subtelomeric elements exhibit more concise telomere structures and offer potential models for future studies in telomere biology.
-
- Genetics and Genomics
- Neuroscience
Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.
