Cited by 80Genomics and Phylogenetic StudiesGenomics and Rare DiseasesChromosomal and Genetic Variations

Discovery of high-confidence human protein-coding genes and exons by whole-genome PhyloCSF helps elucidate 118 GWAS loci

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Mudge, Jonathan M., Jungreis, Irwin, Hunt, Toby, Gonzalez, Jose Manuel, Wright, James C., Kay, Mike, Davidson, Claire, Fitzgerald, Stephen +9 more·2019·Genome Research

Abstract

The most widely appreciated role of DNA is to encode protein, yet the exact portion of the human genome that is translated remains to be ascertained. We previously developed PhyloCSF, a widely used tool to identify evolutionary signatures of protein-coding regions using multispecies genome alignments. Here, we present the first whole-genome PhyloCSF prediction tracks for human, mouse, chicken, fly, worm, and mosquito. We develop a workflow that uses machine learning to predict novel conserved protein-coding regions and efficiently guide their manual curation. We analyze more than 1000 high-scoring human PhyloCSF regions and confidently add 144 conserved protein-coding genes to the GENCODE gene set, as well as additional coding regions within 236 previously annotated protein-coding genes, and 169 pseudogenes, most of them disabled after primates diverged. The majority of these represent new discoveries, including 70 previously undetected protein-coding genes. The novel coding genes are additionally supported by single-nucleotide variant evidence indicative of continued purifying selection in the human lineage, coding-exon splicing evidence from new GENCODE transcripts using next-generation transcriptomic data sets, and mass spectrometry evidence of translation for several new genes. Our discoveries required simultaneous comparative annotation of other vertebrate genomes, which we show is essential to remove spurious ORFs and to distinguish coding from pseudogene regions. Our new coding regions help elucidate disease-associated regions by revealing that 118 GWAS variants previously thought to be noncoding are in fact protein altering. Altogether, our PhyloCSF data sets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization.

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  • lncMtDloop has no protein-coding potential.

    “confirming that the lncMtDloop has no protein-coding potentials”

    From The mitochondrial long non-coding RNA lncMtloop regulates mitochondrial transcription and suppresses Alzheimer’s disease (2024) · cites this paper as Mudge et al, 2019

    The Results passages discuss coding potential in other genes and lncRNAs, but do not address lncMtDloop. Searches for “lncMtDloop” and “mitochondrial D-loop lncRNA no protein coding potential” found no passage assessing its coding potential. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 2

  1. The modENCODE Consortium, Roy S, Ernst J, Kharchenko PV, Kheradpour P, Negre N, Eaton ML, Landolin JM, Bristow CA, Ma L, 2010 Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science 330: 1787– 1797. 10.1126/science.1198374 21177974 PMC3192495 · DOI
  2. Verhoeven VJM, Hysi PG, Wojciechowski R, Fan Q, Guggenheim JA, Höhn R, MacGregor S, Hewitt AW, Nag A, Cheng C-Y, 2013 Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia. Nat Genet 45: 314– 318. 10.1038/ng.2554 23396134 PMC3740568 · DOI · Paper page

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Authors
Mudge, J. M., Jungreis, I., Hunt, T., Gonzalez, J. M., Wright, J. C., Kay, M., Davidson, C., Fitzgerald, S., Seal, R., Tweedie, S., He, L., Waterhouse, R. M., Li, Y., Bruford, E., Choudhary, J. S., Frankish, A., & Kellis, M.
Affiliations
  • European Bioinformatics Institute (GB)
  • Broad Institute (US)
  • Institute of Cancer Research (GB)
  • Wellcome Sanger Institute (GB)
  • SIB Swiss Institute of Bioinformatics (CH)
Venue
Genome Research
Published
2019-09-19
Volume
29
Issue
12
Pages
2073-2087
ISSN
  • 1088-9051 (ISSN-L)
  • 1549-5469
OpenAlex
W2974579541
Cited by
80
References
96
Citations by year
2026: 1 · 2025: 8 · 2024: 12 · 2023: 12 · 2022: 9 · 2021: 30 · 2020: 8
Type
posted content
Language
en
Open access
Locations
  • Genome Research (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • SERVAL (Université de Lausanne) (acceptedVersion, cc-by)
  • IRIS (submittedVersion, cc-by)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by)
  • HighWire Press Open Archive (submittedVersion)
Funders
  • National Human Genome Research Institute of the National Institutes of Health under Award (U41HG007234)
  • Wellcome Trust (WT108749/Z/15/Z, 208349/Z/17/Z)
  • National Institutes of Health (R01 HG004037)
  • Swiss National Science Foundation (PP00P3_170664)
  • National Human Genome Research Institute (U24HG003345)
  • European Molecular Biology Laboratory
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Chromosomal and Genetic Variations
Keywords
protein-coding genes, exon prediction, pseudogenes, purifying selection, single nucleotide variants, splicing, GENCODE, machine learning prediction
MeSH terms
Animals, Exons, Humans, Pseudogenes, Genome, Human, Open Reading Frames, Sequence Analysis, DNA, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing

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