ArticleNucleic acids research2018
High throughput discovery of protein variants using proteomics informed by transcriptomics.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
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- Proteogenomic Gene Structure Validation in the Pineapple Genome.Journal of proteome research · 2024Article
- Single-cell analysis of isoform switching and transposable element expression during preimplantation embryonic development.PLoS biology · 2024Article
- Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach.Frontiers in genetics · 2022Article
- Histologic progression of acne inversa/hidradenitis suppurativa: Implications for future investigations and therapeutic intervention.Experimental dermatology · 2021Article
- Article
- Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer.NPJ breast cancer · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Proteomics informed by transcriptomics (PIT), in which proteomic MS/MS spectra are searched against open reading frames derived from de novo assembled transcripts, can reveal previously unknown translated genomic elements (TGEs). However, determining which TGEs are truly novel, which are variants of known proteins, and which are simply artefacts of poor sequence assembly, is challenging. We have designed and implemented an automated solution that classifies putative TGEs by comparing to reference proteome sequences. This allows large-scale identification of sequence polymorphisms, splice isoforms and novel TGEs supported by presence or absence of variant-specific peptide evidence. Unlike previously reported methods, ours does not require a catalogue of known variants, making it more applicable to non-model organisms. The method was validated on human PIT data, then applied to Mus musculus, Pteropus alecto and Aedes aegypti. Novel discoveries included 60 human protein isoforms, 32 392 polymorphisms in P. alecto, and TGEs with non-methionine start sites including tyrosine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.