SmORFer: a modular algorithm to detect small ORFs in prokaryotes
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ABSTRACT:
ORGANISM(S): Staphylococcus aureus
PROVIDER: GSE150601 | GEO | 2021/05/12
REPOSITORIES: GEO
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Project description:smORFer: a modular algorithm to detect small ORFs in prokaryotes
| PRJNA632889 | ENA
Project description:Emerging evidence places small proteins (≤50 amino acids) more centrally in physiological processes. Yet, their functional identification and the systematic genome annotation of their cognate small open-reading frames (smORFs) remains challenging both experimentally and computationally. Ribosome profiling or Ribo-Seq (that is a deep sequencing of ribosome-protected fragments) enables detecting of actively translated open-reading frames (ORFs) and empirical annotation of coding sequences (CDSs) using the in-register translation pattern that is characteristic for genuinely translating ribosomes. Multiple identifiers of ORFs that use the 3-nt periodicity in Ribo-Seq data sets have been successful in eukaryotic smORF annotation. They have difficulties evaluating prokaryotic genomes due to the unique architecture (e.g. polycistronic messages, overlapping ORFs, leaderless translation, non-canonical initiation etc.). Here, we present a new algorithm, smORFer, which performs with high accuracy in prokaryotic organisms in detecting putative smORFs. The unique feature of smORFer is that it uses an integrated approach and considers structural features of the genetic sequence along with in-frame translation and uses Fourier transform to convert these parameters into a measurable score to faithfully select smORFs. The algorithm is executed in a modular way, and dependent on the data available for a particular organism, different modules can be selected for smORF search.
| S-EPMC8421149 | biostudies-literature
Project description:Aminoglycosides resistance mechanisms inference algorithm
| PRJEB29576 | ENA
Project description:Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1,000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385,000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH, and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM’s performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of less than 10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2-5 kb, and 1 kb, respectively. Keywords: CNV detection algorithm development and assessment
2008-03-12 | GSE10511 | GEO
Project description:Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1,000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385,000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH, and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM’s performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of less than 10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2-5 kb, and 1 kb, respectively. Keywords: CNV detection algorithm development and assessment All four samples in this series are hybridizations of genomic DNA from inbred mouse strains 129X1/SvJ versus C57BL6/J. The experiments were performed at increasing resolutions (one 385K, two 2.1M, and one 3.1M).
2008-03-11 | E-GEOD-10511 | biostudies-arrayexpress
Project description:Identifying all essential genomic components is critical for the assembly of minimal artificial life. In the genome-reduced bacterium Mycoplasma pneumoniae, we found, that small ORFs (smORFs; <100 residues), accounting for 10% of all ORFs, are the most frequently essential genomic components (53%). Essentiality of smORFs may be explained by their function as members of protein and/or DNA/RNA complexes. In larger proteins, essentiality applied to individual domains and not entire proteins, a notion we could confirm by expression of truncated domains. The fraction of essential non-coding RNAs non-overlapping with essential genes is 5% higher than of non-transcribed regions (0.9%), pointing to the important functions of the former. The data highlights the minimal genome (33%, 269410 bp of M. pneumoniae genome), with an unexpected hidden layer of smORFs with essential functions.
2015-03-03 | PXD001611 | Pride
Project description:The absence of thousands of recently annotated small open reading frame (smORF)-encoded peptides and small proteins (microproteins) from databases has precluded their analysis in metabolism and metabolic disease. Given the outsized importance of small proteins and peptides in metabolism—insulin, leptin, amylin, glucagon, and glucagon-like peptide-1 (GLP-1)—microproteins are a potentially rich source of uncharacterized metabolic regulators. Here, we annotate smORFs in primary differentiated brown, white, and beige mouse adipose cells. Ribosome profiling (Ribo-Seq) detected a total of 3,877 unannotated smORFs. Analysis of RNA-Seq datasets revealed diet-regulated smORF expression in adipose tissues, and validated the adipose translation of the feeding-neuron marker gene Gm8773. Gm8773 encodes the mouse homolog of FAM237B, a neurosecretory protein that stimulates food intake and promotes weight gain in chickens. Testing of recombinant mFAM237B produced similar orexigenic activity in mice further supporting a role for FAM237B a metabolic regulator and part of the brain-adipose axis. Furthermore, we showed that data independent acquisition mass spectrometry (DIA-MS) proteomics can provide a sensitive, flexible, and quantitative platform for identifying microproteins by mass spectrometry. Using this system led to the detection of 58 microproteins from cell culture and an additional 25 from mouse serum. The proteomics data established the anti-inflammatory microprotein AW112010 as a circulating factor, and found that serum levels of a microprotein translated from a FRS2 uORF is elevated in older obese mice. Together, the data highlight the value of this database in examining understudied smORFs and microproteins in metabolic research and identifying additional regulators of metabolism.
2022-12-13 | GSE197909 | GEO
Project description:The absence of thousands of recently annotated small open reading frame (smORF)-encoded peptides and small proteins (microproteins) from databases has precluded their analysis in metabolism and metabolic disease. Given the outsized importance of small proteins and peptides in metabolism—insulin, leptin, amylin, glucagon, and glucagon-like peptide-1 (GLP-1)—microproteins are a potentially rich source of uncharacterized metabolic regulators. Here, we annotate smORFs in primary differentiated brown, white, and beige mouse adipose cells. Ribosome profiling (Ribo-Seq) detected a total of 3,877 unannotated smORFs. Analysis of RNA-Seq datasets revealed diet-regulated smORF expression in adipose tissues, and validated the adipose translation of the feeding-neuron marker gene Gm8773. Gm8773 encodes the mouse homolog of FAM237B, a neurosecretory protein that stimulates food intake and promotes weight gain in chickens. Testing of recombinant mFAM237B produced similar orexigenic activity in mice further supporting a role for FAM237B a metabolic regulator and part of the brain-adipose axis. Furthermore, we showed that data independent acquisition mass spectrometry (DIA-MS) proteomics can provide a sensitive, flexible, and quantitative platform for identifying microproteins by mass spectrometry. Using this system led to the detection of 58 microproteins from cell culture and an additional 25 from mouse serum. The proteomics data established the anti-inflammatory microprotein AW112010 as a circulating factor, and found that serum levels of a microprotein translated from a FRS2 uORF is elevated in older obese mice. Together, the data highlight the value of this database in examining understudied smORFs and microproteins in metabolic research and identifying additional regulators of metabolism.
2022-12-13 | GSE198107 | GEO
Project description:The Oxford Nanopore technology has a great potential for the analysis of genome methylation, including full-genome methylome profiling. However, there are certain issues while identifying methylation motif sequences caused by low sensitivity of the currently available motif enrichment algorithms. Here, we present Snapper, a new highly-sensitive approach to extract methylation motif sequences based on a greedy motif selection algorithm. Snapper has shown higher enrichment sensitivity compared with the MEME tool coupled with Tombo or Nanodisco instruments, which was demonstrated on H. pylori strain J99 studied earlier using the PacBio technology. In addition, we used Snapper to characterize the total methylome of a new H.pylori strain A45. The analysis revealed the presence of at least 4 methylation sites that have not been described for H. pylori earlier. We experimentally confirmed a new CCAG-specific methyltransferase and indirectly inferred a new CCAAK-specific methyltransferase.
2024-01-26 | PXD038899 | Pride
Project description:A post-processing algorithm for miRNA microarray data
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