Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

EuGI

General information

URL: http://eugi.bi.up.ac.za
Full name: EuGI
Description: SWGIS v2.0 predicts GIs in large eukaryotic chromosomes based on the atypical nucleotide composition of these regions. Along with SWGIS, the EuGI database, which houses GIs identified in 66 different eukaryotic species, and the EuGI web
Year founded: 2018
Last update: 2018.09.21
Version: v2.0
Accessibility:
Accessible
Country/Region: South Africa

Classification & Tag

Data type:
DNA
Data object:
NA
Database category:
Major species:
NA
Keywords:

Contact information

University/Institution: University of Pretoria
Address: Centre for Bioinformatics and Computational Biology; Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria 0002, Private Bag X20, Hatfield, 0028 South Africa
City: Hatfield
Province/State:
Country/Region: South Africa
Contact name (PI/Team): Frederick Johannes Clasen
Contact email (PI/Helpdesk): edohan.clasen@fabi.up.ac.za

Publications

29724163
EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes. [PMID: 29724163]
Frederick Johannes Clasen, Rian Ewald Pierneef, Bernard Slippers, Oleg Reva

BACKGROUND: Genomic islands (GIs) are inserts of foreign DNA that have potentially arisen through horizontal gene transfer (HGT). There are evidences that GIs can contribute significantly to the evolution of prokaryotes. The acquisition of GIs through HGT in eukaryotes has, however, been largely unexplored. In this study, the previously developed GI prediction tool, SeqWord Gene Island Sniffer (SWGIS), is modified to predict GIs in eukaryotic chromosomes. Artificial simulations are used to estimate ratios of predicting false positive and false negative GIs by inserting GIs into different test chromosomes and performing the SWGIS v2.0 algorithm. Using SWGIS v2.0, GIs are then identified in 36 fungal, 22 protozoan and 8 invertebrate genomes.
RESULTS: SWGIS v2.0 predicts GIs in large eukaryotic chromosomes based on the atypical nucleotide composition of these regions. Averages for predicting false negative and false positive GIs were 20.1% and 11.01% respectively. A total of 10,550 GIs were identified in 66 eukaryotic species with 5299 of these GIs coding for at least one functional protein. The EuGI web-resource, freely accessible at http://eugi.bi.up.ac.za , was developed that allows browsing the database created from identified GIs and genes within GIs through an interactive and visual interface.
CONCLUSIONS: SWGIS v2.0 along with the EuGI database, which houses GIs identified in 66 different eukaryotic species, and the EuGI web-resource, provide the first comprehensive resource for studying HGT in eukaryotes.

BMC Genomics. 2018:19(1) | 2 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
6505/6895 (5.671%)
Gene genome and annotation:
1928/2021 (4.651%)
Genotype phenotype and variation:
943/1005 (6.269%)
6505
Total Rank
2
Citations
0.286
z-index

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Record metadata

Created on: 2019-10-22
Curated by:
Amjad Ali [2019-11-13]
Ghulam Abbas [2019-10-22]