DEG 10, an update of the database of essential genes that includes both protein-coding genes and noncoding genomic elements

By Hao Luo, Yan Lin, F. Gao, Chun-Ting Zhang, Ren Zhang. Nucleic Acids Res., 2013

527 citations recorded by the source corpus.

The combination of high-density transposon-mediated mutagenesis and high-throughput sequencing has led to significant advancements in research on essential genes, resulting in a dramatic increase in the number of identified prokaryotic essential genes under diverse conditions and a revised essential-gene concept that includes all essential genomic elements, rather than focusing on protein-coding genes only. DEG 10, a new release of the Database of Essential Genes (available at http://www.essentialgene.org), has been developed to accommodate these quantitative and qualitative advancements. In addition to increasing the number of bacterial and archaeal essential genes determined by genome-wide gene essentiality screens, DEG 10 also harbors essential noncoding RNAs, promoters, regulatory sequences and replication origins. These essential genomic elements are determined not only in vitro, but also in vivo, under diverse conditions including those for survival, pathogenesis and antibiotic resistance. We have developed customizable BLAST tools that allow users to perform species- and experiment-specific BLAST searches for a single gene, a list of genes, annotated or unannotated genomes. Therefore, DEG 10 includes essential genomic elements under different conditions in three domains of life, with customizable BLAST tools.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f931271dc718f971bfb7b77cdc9d7481929c0392

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In Genetics

1. Marco Abreu
2. J. Caufield
3. Peter Uetz
4. Christopher Wimble

In Molecular Biology

1. Marco Abreu
2. J. Caufield
3. Peter Uetz
4. Christopher Wimble

Citations in the corpus

• Protein Complexes in Bacteria (2015, methodology): “Essentiality data was collected from the Database of Essential Genes [ 11 ] .”
• VacSol: a high throughput in silico pipeline to predict potential therapeutic targets in prokaryotic pathogens using subtractive reverse vaccinology (2017, methodology): “[28] VFDB Virulence factors database.”