SalMotifDB
SalMotifDB annotates transcription factors (TFs) and cis-regulatory binding sites in salmonid genomes to enable prediction of regulatory interactions and interpretation of how non-coding variation affects gene expression and phenotypes.
Key Features:
- Extensive motif compilation: Incorporates 3,072 unique DNA motifs compiled from a wide array of metazoan motif databases for analysis across salmonid species.
- Multi-species regulatory network construction: Constructs putative regulatory networks by leveraging multi-species motif databases to study evolutionary aspects such as gene expression divergence in gene duplicates resulting from whole genome duplications.
- Regulatory annotations: Provides regulatory annotations that link non-coding genomic regions to predicted TF binding and potential effects on gene expression and phenotype.
- Application to lipid metabolism and duplicate divergence: Applied to predict key lipid metabolism regulators influencing gene expression related to lipid and fatty acid content in salmonid feed and to explain a significant portion of expression divergence among duplicated genes after whole genome duplication.
Scientific Applications:
- Life-history and trait variation: Analyze regulatory mechanisms underlying life-history trait variation in salmonids.
- Aquaculture trait investigation: Investigate regulatory bases of economically important traits in aquaculture, including lipid and fatty acid content related to feed.
- Evolutionary genomics: Study the evolutionary consequences of whole genome duplications and resulting expression divergence among gene duplicates in salmonids.
Methodology:
Motif matching and TF prediction are used to construct putative regulatory networks.
Topics
Details
- Programming Languages:
- R
- Added:
- 11/14/2019
- Last Updated:
- 12/16/2020
Operations
Publications
Mulugeta TD, Nome T, To T, Gundappa MK, Macqueen DJ, Våge DI, Sandve SR, Hvidsten TR. SalMotifDB: a tool for analyzing putative transcription factor binding sites in salmonid genomes. BMC Genomics. 2019;20(1). doi:10.1186/s12864-019-6051-0. PMID:31477007. PMCID:PMC6720087.
PMID: 31477007
PMCID: PMC6720087
Funding: - Research Council of Norway: 208481, 244164, 248792
- Norwegian National Infrastructure for Research Data: NS9055K