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SmORFer: a modular algorithm to detect small ORFs in prokaryotes.

ABSTRACT: 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.

SUBMITTER: Bartholomaus A

PROVIDER: S-EPMC8421149 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEpidermal growth factor receptor (EGFR) mutation status is the most valuable indicator in the screening of non-small-cell lung cancer (NSCLC) patients for tyrosine kinase inhibitor (TKI) therapy. Accurate, rapid and economical methods of detecting EGFR mutations have become important. The use of two mutation-specific antibodies targeting the delE746-A750 mutation in exon 19 and L858R mutation in exon 21 makes this task possible, but the lack of consensually acceptable criteria for positive results limits the application of this antibody based mutation detection.MethodsWe collected 399 specimens from NSCLC patients (145 resection specimens, 220 biopsy specimens, and 34 cytology specimens) whose EGFR mutation status had been detected by TaqMan PCR assay. Immunohistochemical (IHC) analyses using EGFR mutation-specific antibodies were employed for all samples. After staining and scoring, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated in accordance with different levels of positive grades in comparison with the results of PCR-based assay.ResultsIn IHC-based analyses, 144 cases were scored 0, 104 cases were scored 1+, 103 cases were scored 2+, and 48 cases were scored 3+. With the molecular-based results were set as the "gold standard", the prevalence of mutation was 6.94% (10/144), 23.08% (24/104), 67.96% (70/103) and 100% (48/48), respectively, for samples with scores 0, 1+, 2+ and 3+. When score 3+ was considered positive, the specificity and PPV were 100%; if only score 0 was considered negative, 93.06% NPV was obtained.ConclusionPatients with score 3+ have a perfect PPV (100%), and may accept TKI treatment directly without any molecular-based assays. Patients with score 0 had high NPV (93.06%), which could reach 97.22% when the detection of total EGFR was applied. However, samples with score 1+ or 2+ are unreliable and need further verification of EGFR mutation status by molecular-based assays.

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SmORFer: a modular algorithm to detect small ORFs in prokaryotes.

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