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Discovering microproteins: making the most of ribosome profiling data.
Chothani, Sonia; Ho, Lena; Schafer, Sebastian; Rackham, Owen.
Afiliação
  • Chothani S; Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore.
  • Ho L; Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore.
  • Schafer S; Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore.
  • Rackham O; Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore, Singapore.
RNA Biol ; 20(1): 943-954, 2023 01.
Article em En | MEDLINE | ID: mdl-38013207
ABSTRACT
Building a reference set of protein-coding open reading frames (ORFs) has revolutionized biological process discovery and understanding. Traditionally, gene models have been confirmed using cDNA sequencing and encoded translated regions inferred using sequence-based detection of start and stop combinations longer than 100 amino-acids to prevent false positives. This has led to small ORFs (smORFs) and their encoded proteins left un-annotated. Ribo-seq allows deciphering translated regions from untranslated irrespective of the length. In this review, we describe the power of Ribo-seq data in detection of smORFs while discussing the major challenge posed by data-quality, -depth and -sparseness in identifying the start and end of smORF translation. In particular, we outline smORF cataloguing efforts in humans and the large differences that have arisen due to variation in data, methods and assumptions. Although current versions of smORF reference sets can already be used as a powerful tool for hypothesis generation, we recommend that future editions should consider these data limitations and adopt unified processing for the community to establish a canonical catalogue of translated smORFs.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Perfil de Ribossomos Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Perfil de Ribossomos Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article