Dataset Information

Identifying interaction partners of noncanonical peptides.

ABSTRACT: Studies have revealed dozens of functional peptides in putative ‘noncoding’ regions and raised the question of how many proteins are encoded by noncanonical open reading frames (ORFs). We comprehensively annotated genome-wide translated ORFs across five eukaryotic by analyzing ribosome profiling reads. We revealed pervasive translation in annotated untranslated regions of mRNAs or off-frame regions (i.e., uORFs, dORFs, and iORFs). We developed a logistic regression model based on ORF features to calculate the peptide functional probability in humans. Systematic ectopic expression experiments showed that peptides encoded by ncORFs follow the basic principles governing conventional protein subcellular localization and carry out diverse biological functions.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Zhe Ji

LAB HEAD: Zhe Ji

PROVIDER: PXD037658 | Pride | 2024-05-23

REPOSITORIES: pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	raw.zip	Other
	txt.zip	Other

Items per page:

1 - 2 of 2

Publications

Widespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features.

Yang Haiwang H Li Qianru Q Stroup Emily K EK Wang Sheng S Ji Zhe Z

Nature communications 20240302 1

Studies have revealed dozens of functional peptides in putative 'noncoding' regions and raised the question of how many proteins are encoded by noncanonical open reading frames (ORFs). Here, we comprehensively annotate genome-wide translated ORFs across five eukaryotes (human, mouse, zebrafish, worm, and yeast) by analyzing ribosome profiling data. We develop a logistic regression model named PepScore based on ORF features (expected length, encoded domain, and conservation) to calculate the prob ...[more]

PMID: 38431639

Similar Datasets

Project description:While the majority of protein-coding genes in the human genome have been identified, the location of the regulatory sequences that control their expression in time and space remains poorly defined. The importance of identifying these elements is underscored by a growing number of studies (such as GWAS) supporting a relationship between variation in non-coding sequences and human disease. M-BM- emonstrated that ChIP-Seq with p300 directly on human or mouse tissues represents a powerful method to identify the location and tissue-specific activity pattern of enhancers in the genome.M-BM- a highly specific chromatin mark for the prediction of in vivo enhancers, it is not without limitations. M-BM- comparison of p300-bound regions with previously generated enhancer sets shows that the majority of enhancers are activated independently of p300. To attempt to identify a larger proportion of enhancers in vivo, we have focused on several additional transcriptional coactivators that are hypothesized to be associated with active tissue-specific enhancers. M-BM- limited availability of ChIP-seq grade antibodies for these coactivators, FLAG-tag knock-in mice were generated and ChIP-seq using a FLAG antibody was performed on various tissues from e11.5 mouse embryos. Indeed, as these mouse lines have become available we have validated their valuable role as marks for transcriptional enhancers in vivo.M-BM- studies are expected to further expand the catalogue of in vivo functional enhancers, which will aid in the decoding of the regulatory genome and provide new insights into the role of gene regulation in human biology and disease. In addition to FLAG data, this accession includes histone acetylation / methylation ChIP-seq data from e11.5 mouse embryonic tissues. Histone ChIP-seq data was used in combination with FLAG data for various computational analyses. Examination of FLAG-labeled transcriptional coactivator binding in mouse embryonic stage 11.5 and embryonic stem cells