Gene finding in novel genomes

By Ian Korf. BMC Bioinformatics, 2004

2,933 citations recorded by the source corpus.

BackgroundComputational gene prediction continues to be an important problem, especially for genomes with little experimental data.ResultsI introduce the SNAP gene finder which has been designed to be easily adaptable to a variety of genomes. In novel genomes without an appropriate gene finder, I demonstrate that employing a foreign gene finder can produce highly inaccurate results, and that the most compatible parameters may not come from the nearest phylogenetic neighbor. I find that foreign gene finders are more usefully employed to bootstrap parameter estimation and that the resulting parameters can be highly accurate.ConclusionSince gene prediction is sensitive to species-specific parameters, every genome needs a dedicated gene finder.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/02696b7d7aa816f5b25911f37ae618abb12fa347

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

1. Mark Yandell
2. Carson Holt
3. Mark Borodovsky
4. Alexandre Lomsadze
5. Mario Stanke
6. Daniel Ence
7. Vardges Ter-Hovhannisyan
8. Y. Chernoff

In Genetics

1. Mark Borodovsky
2. Mark Yandell
3. Mario Stanke
4. Alexandre Lomsadze
5. Katharina Jasmin Hoff
6. Daniel Ence
7. Carson Holt
8. Vardges Ter-Hovhannisyan

In Molecular Biology

1. Mark Borodovsky
2. Alexandre Lomsadze
3. Mario Stanke
4. Tomás Bruna
5. Katharina Jasmin Hoff
6. Mark Yandell
7. Carson Holt
8. Daniel Ence

Citations in the corpus

• CpGAVAS, an integrated web server for the annotation, visualization, analysis, and GenBank submission of completely sequenced chloroplast genome sequences (2012, methodology): “Several programs such as SNAP [12], Augustus [13], and Maker [14] have been widely used.”
• BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS and TSEBRA (2023, positive): “MAKER2 was executed according to recommendations provided by the developers of MAKER2, integrating GeneMark, AUGUSTUS and SNAP predictions.”
• Genome Annotation and Curation Using MAKER and MAKER-P (2014, methodology): “The process used to create a species parameter/HMM file is described in SNAP’s internal documentation (Korf, 2004).”
• BUSCO Applications from Quality Assessments to Gene Prediction and Phylogenomics (2017, methodology): “Additionally, the BUSCO-generated general feature format and GenBankformatted gene models can be used as inputs for training other gene predictors like SNAP (Korf 2004).”
• AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints (2005, background): “A large number of gene finding programs have been proposed since the 1980s (1–5).”
• Macronuclear Genome Sequence of the Ciliate Tetrahymena thermophila, a Model Eukaryote (2006, neutral): “thermophila using a two-phase bootstrapping process [182], due to the dearth of curated training data available at the time.”
• Daphnia as an emerging model for toxicological genomics (2008, positive): “Gene predictions with SNAP (Korf, 2004) have been generated to locate new as well as known genes.”