ǂa ǂdata integration approach
Zala Brajnik (Author), Jernej Ogorevc (Author)

Abstract

Background Inflammation of the mammary tissue (mastitis) is one of the most detrimental health conditions in dairy ruminants and is considered the most economically important infectious disease of the dairy sector. Improving mastitis resistance is becoming an important goal in dairy ruminant breeding programmes. However, mastitis resistance is a complex trait and identification of mastitis-associated alleles in livestock is difficult. Currently, the only applicable approach to identify candidate loci for complex traits in large farm animals is to combine different information that supports the functionality of the identified genomic regions with respect to a complex trait. Methods To identify the most promising candidate loci for mastitis resistance we integrated heterogeneous data from multiple sources and compiled the information into a comprehensive database of mastitis-associated candidate loci. Mastitis-associated candidate genes reported in association, expression, and mouse model studies were collected by searching the relevant literature and databases. The collected data were integrated into a single database, screened for overlaps, and used for gene set enrichment analysis. Results The database contains candidate genes from association and expression studies and relevant transgenic mouse models. The 2448 collected candidate loci are evenly distributed across bovine chromosomes. Data integration and analysis revealed overlaps between different studies and/or with mastitis-associated QTL, revealing promising candidate genes for mastitis resistance. Conclusion Mastitis resistance is a complex trait influenced by numerous alleles. Based on the number of independent studies, we were able to prioritise candidate genes and propose a list of the 22 most promising. To our knowledge this is the most comprehensive database of mastitis associated candidate genes and could be helpful in selecting genes for functional validation studies.

Keywords

govedoreja;govedo;krave;molznice;mastitis;genetika;kandidatni geni;QTL;baza podatkov;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL BF - Biotechnical Faculty
UDC: 636.2:575
COBISS: 141296387 Link will open in a new window
ISSN: 2049-1891
Views: 269
Downloads: 60
Average score: 0 (0 votes)
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Other data

Secondary language: Slovenian
Secondary keywords: govedoreja;govedo;krave;molznice;mastitis;genetika;kandidatni geni;QTL;baza podatkov;
Type (COBISS): Article
Pages: str. 1-14
Volume: ǂVol. ǂ14
Issue: [article no.] 10
Chronology: 2023
DOI: 10.1186/s40104-022-00821-0
ID: 18487277