Evidence for a novel overlapping coding sequence in POLG initiated at a CUG start codon

Khan, Yousuf A.; Jungreis, Irwin; Wright, James C.; Mudge, Jonathan M.; Choudhary, Jyoti S.; Firth, Andrew E.; Kellis, M

doi:10.1186/s12863-020-0828-7

Cited by 34 publications

(34 citation statements)

References 61 publications

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“…These peptides are compiled into a reference spectral library, which is used to validate their existence in our experimental proteomics data and large public MS datasets. For example transcriptomic, conservation, and ribosome profiling data combined with experimental peptide evidence supported the discovery and validation of an alternate protein isoform originating from a non-ATG start site in the gene POLG ( 24 ), and highlighted a novel class of unannotated protein-coding features that are now under active investigation.…”

Section: Protein-coding Genesmentioning

confidence: 99%

Gencode 2021

Frankish

Diekhans

Jungreis

et al. 2020

Nucleic Acids Research

Self Cite

966

682

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The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics. GENCODE annotation processes make use of primary data and bioinformatic tools and analysis generated both within the consortium and externally to support the creation of transcript structures and the determination of their function. Here, we present improvements to our annotation infrastructure, bioinformatics tools, and analysis, and the advances they support in the annotation of the human and mouse genomes including: the completion of first pass manual annotation for the mouse reference genome; targeted improvements to the annotation of genes associated with SARS-CoV-2 infection; collaborative projects to achieve convergence across reference annotation databases for the annotation of human and mouse protein-coding genes; and the first GENCODE manually supervised automated annotation of lncRNAs. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

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Section: Protein-coding Genesmentioning

confidence: 99%

Gencode 2021

Frankish

Diekhans

Jungreis

et al. 2020

Nucleic Acids Research

Self Cite

966

682

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“…Beyond protein-coding constraint for amino-acid translation, we also evaluated nucleotide-level overlapping constraint within protein-coding regions indicative of dual-coding regions, RNA structures, RNA-binding protein sites, etc, using reduced synonymous-substitution rate estimated using FRESCo, which we previously developed and applied to viruses 29 and human 30 . We annotated 1394 synonymously-constrained codons (14% of 9744, FDR=0.125) and defined 92 synonymous-constraint elements (SCEs) (covering 1555 codons), using 9-codon-resolution significantly-decreased synonymous rate relative to gene average 29,31 .…”

Section: Strain Selection Alignment Constraintmentioning

confidence: 99%

“…Evolutionary evidence for/against overlapping ORFs is harder to resolve, as protein-coding signatures in the primary reading frame heavily influence scores in alternate frames: they skew the signal as protein-preserving mutations in one frame are typically protein-disruptive in the other, and they compress the signal as there are fewer substitutions. However, their dual-coding nature leads to a depletion of synonymous substitutions in the primary ORF localized over the overlapping segment, resulting in a strong signal of overlapping-constraint [29][30][31] , used next to investigate ORFs 9c and 9b overlapping N.…”

Section: N-overlapping Orf 9b Is Coding 9c Is Notmentioning

confidence: 99%

SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes

Jungreis

Sealfon

Kellis

2020

Preprint

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Despite its overwhelming clinical importance for understanding and mitigating the COVID-19 pandemic, the protein-coding gene content of the SARS-CoV-2 genome remains unresolved, with the function and even protein-coding status of many hypothetical proteins unknown and often conflicting among different annotations, thus hindering efforts for systematic dissection of its biology and the impact of recent mutations. Comparative genomics is a powerful approach for distinguishing protein-coding versus non-coding functional elements, based on their characteristic patterns of change, which we previously used to annotate protein-coding genes in human, fly, and other species. Here, we use comparative genomics to provide a high-confidence set of SARS-CoV-2 protein-coding genes, to characterize their protein-level and nucleotide-level evolutionary constraint, and to interpret the functional implications for SARS-CoV-2 mutations acquired during the current pandemic. We select 44 complete Sarbecovirus genomes at evolutionary distances well-suited for protein-coding and non-coding element identification, create whole-genome alignments spanning all named and putative genes, and quantify their protein-coding evolutionary signatures using PhyloCSF and their overlapping constraint using FRESCo. We find strong protein-coding signatures for all named genes and for hypothetical ORFs 3a, 6, 7a, 7b, and 8, indicating protein-coding roles, and provide strong evidence of protein-coding status for a recently-proposed alternate-frame novel ORF within 3a. By contrast, ORF10 shows no protein-coding signatures but shows unusually-high nucleotide-level constraint, indicating it has important but non-coding functions, and ORF14 and SARS-CoV-1 ORF3b, which overlap other genes, lack evolutionary signatures expected for dual-coding regions, indicating they do not produce functional proteins. ORF9b has ambiguous protein-coding signatures, preventing us from resolving its protein-coding status. ORF8 shows extremely fast nucleotide-level evolution, lacks a known function, and was deactivated in SARS-CoV-1, but shows clear signatures indicating protein-coding function worthy of further investigation given its rapid evolution and potential role in replication. SARS-CoV-2 mutations are preferentially excluded from evolutionarily-constrained amino acid residues and synonymously-constrained nucleotides, indicating purifying constraint acting at both coding and non-coding levels. In contrast, we find a conserved region in the nucleocapsid that is enriched for recent mutations, which could indicate a selective signal, and find that several spike-protein mutations previously identified as candidates for increased transmission and several mutations in isolates found to generate higher viral load in-vitro disrupt otherwise-perfectly-conserved amino-acids, consistent with adaptations for human-to-human transmission.

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“…Additionally, several other novel transcripts and their functionality within the genome has been established 5 . Moreover, contrary to the one gene-one protein hypothesis, multiple ORFs within known genes that can encode protein-products have been identified 6,7 . Therefore, multiple translations from protein-coding and noncoding regions highlights that the human proteome is much more diverse than what is currently known and we call this separate and undefined class of open reading frames as novel open reading frames (nORFs).…”

Section: Introductionmentioning

confidence: 86%

Use of short-read RNA-Seq data to identify transcripts that can translate novel ORFs

Erady

Puntambekar

Prabakaran

2020

Preprint

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Identification of as of yet unannotated or undefined novel open reading frames (nORFs) and exploration of their functions in multiple organisms has revealed that vast regions of the genome have remained unexplored or 'hidden'. Present within both protein-coding and noncoding regions, these nORFs signify the presence of a much more diverse proteome than previously expected. Given the need to study nORFs further, proper identification strategies must be in place, especially because they cannot be identified using conventional gene signatures. Although Ribo-Seq and proteogenomics are frequently used to identify and investigate nORFs, in this study, we propose a workflow for identifying nORF containing transcripts using our precompiled database of nORFs with translational evidence, using sample transcript information. Further, we discuss the potential uses of this identification, the caveats involved in such a transcript identification and finally present a few representative results from our analysis of naive mouse B and T cells, human post-mortem brain and cichlid fish transcriptome. Our proposed workflow can identify noncoding transcripts that can potentially translate intronic, intergenic and several other classes of nORFs. One-line summary:A systematic workflow to identify nORF containing transcripts using sample transcript information.

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Evidence for a novel overlapping coding sequence in POLG initiated at a CUG start codon

Cited by 34 publications

References 61 publications

Gencode 2021

Gencode 2021

SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes

Use of short-read RNA-Seq data to identify transcripts that can translate novel ORFs

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