Projects / Programmes
Development of bioinformatics tools for identification of genetic biomarkers for fat deposition in mammals
| Code |
Science |
Field |
Subfield |
| 4.02.00 |
Biotechnical sciences |
Animal production |
|
| Code |
Science |
Field |
| B220 |
Biomedical sciences |
Genetics, cytogenetics |
| Code |
Science |
Field |
| 4.02 |
Agricultural and Veterinary Sciences |
Animal and Dairy science |
bioinformatics, biomarkers, fat deposition, genomics, microRNA, obesity, polymorphisms
Researchers (1)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
32581 |
PhD Minja Zorc |
Computer science and informatics |
Head |
2014 - 2016 |
182 |
Organisations (1)
Abstract
Obesity is polygenic disease which presents a major health issue. It affects people of all ages as well as domestic animals. The unravelling of genetic bases of fat deposition might help to develop therapeutics and understand the process of fat deposition. The amount of available genomic data and the need for genomic data analysis methods grow. Systemic approaches are becoming important in complex phenotypes research.
Within the central website for fat deposition research (http://www.integratomics-time.com/fat_deposition), the most comprehensive database of manually curated database of fat deposition candidate loci in mammals Obesity Gene Atlas was published. The aim of the research project is to update and extend the existing database and develop bioinformatics tools for the development of biomarkers for fat deposition. The number of new publications on the genetic basis of fat deposition is growing rapidly. Therefore, the update of the existing database is necessary. For this purpose the tool for automated search of candidate genes from the literature for regular updates of the database will be developed. In prior analyses based on the data from the Obesity Gene Atlas there was need for additional information relating to a genomic research layer (proteomics, transcriptomics, epigenomics), within which the candidate locus was associated with the phenotype are needed. The extension of the database would allow analyses based on systems biology approaches.
For the prioritization of candidate loci and the development of biomarkers, the bioinformatics tools miRNA SNiPer and miRNA Viewer SNiPer were developed. Both tools will be upgraded, updated and integrated with the fat deposition candidate loci database. The tool miRNA SNiPer will enable us to identify the polymorphisms within various regions of the candidate miRNA genes. Using the miRNA Viewer tool the graphical presentation of fat deposition candidate loci overlaps will be provided.
Both, miRNA SNiPer and miRNA Viewer SNiPer are useful bioinformatics tools for miRNA research. Therefore, further development of the tools is needed. The database Obesity Gene Atlas is an important source of information for further research of the genetic basis of fat deposition, and an update of the database is necessary. An automated process for candidate loci database will be developed and the structure of database of fat deposition candidate loci with layers of genomics research (-omics) will be defined. It will enable analysis of a complex phenotype using systems biology approaches.
The results of the research project will enable us to use the systems biology approaches for solving an important health issue. The approach developed within the project might be used for research of other complex phenotypes. The fat deposition candidate loci database can be extended and might become a central repository of candidate genes for complex phenotypes.
Significance for science
The results of the research project will enable the use of systems biology approaches to study important health issues and pave the way for new applications in animals. The developed approach may also be used to study other complex phenotypes. The database of fat deposition candidate might be expanded into a central repository of candidate genes of complex phenotypes using the tools, developed in the frame of the research project.
Significance for the country
Bioinformatics and systems biology represent new interdisciplinary research areas. Integration of publicly available data and development of bioinformatics methods may lead to biology research improvement and research costs reduction. The implementation of interdisciplinary projects such as present, leads to knowledge obtaining in the rapidly changing and developing research area.
Most important scientific results
Annual report
2014,
2015,
final report
Most important socioeconomically and culturally relevant results
Final report
