Identification of protein coding regions in RNA transcripts
By Shiyuyun Tang, Alexandre Lomsadze, Mark Borodovsky. ACM International Conference on Bioinformatics, Computational Biology and Biomedicine, 2014
429 citations recorded by the source corpus.
Massive parallel sequencing of RNA transcripts by the next generation technology (RNA-Seq) is a powerful method of generating critically important data for discovery of structure and function of eukaryotic genes. The transcripts may or may not carry protein-coding regions. If protein coding region is present, it should be a continuous (spliced) open reading frame. Gene finding in transcripts can be done by statistical (alignment-free) as well as by alignment based methods. We describe a new tool, GeneMarkS-T, for ab initio identification of protein-coding regions, complete or incomplete, in RNA transcripts assembled from RNA-Seq reads. Important feature of GeneMarkS-T is unsupervised estimation of parameters of the algorithm that makes unnecessary several conventional steps used in the gene prediction protocols, most importantly the manually curated preparation of training sets. We demonstrate that i/the GeneMarkS-T self-training is robust with respect to the presence of errors in assembled transcripts and ii/accuracy of GeneMarkS-T in identification of protein-coding regions and, particularly, in prediction of gene starts compares favorably to other existing methods.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/05a97685448c6ff27f398db8cab7091081097712
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In Molecular Biology
- Mark Borodovsky
- Alexandre Lomsadze
- Tomás Bruna
- Katharina Jasmin Hoff
- Mario Stanke
- L. Gabriel
- Matthis Ebel
- Ana Conesa
Citations in the corpus
- BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS and TSEBRA (2023, positive): “Protein-coding genes are predicted in assembled transcripts by GeneMarkS-T [Tang et al., 2015].”
- SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification (2017, background): “…mechanisms have been reported to play critical roles in differentiation 4–7 , speciation 3,8 and multiple human diseases such as cancer 9–11 , diabetes 12,13 or neurological disorders 14–18 , and therefore play a fundamental role in the establishment of organismal complexity 3,19,20 .”