Your browser does not allow JavaScript!
JavaScript is necessary for the proper functioning of this website. Please enable JavaScript or use a modern browser.
Open Science Slovenia
Open Science
DiKUL
slv
|
eng
Search
Browse
New in RUL
About RUL
In numbers
Help
Sign in
Candidate genes for mastitis resistance in dairy cattle : a data integration approach
ID
Brajnik Kovačič, Zala
(
Author
),
ID
Ogorevc, Jernej
(
Author
)
PDF - Presentation file,
Download
(1,36 MB)
MD5: D226B0397F5F876D5CA86D49A85D3558
URL - Source URL, Visit
https://jasbsci.biomedcentral.com/articles/10.1186/s40104-022-00821-0
Image galllery
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.
Language:
English
Keywords:
association study
,
candidate genes
,
epigenetics
,
mammary gland
,
mastitis
,
quantitative trait loci
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
BF - Biotechnical Faculty
Publication status:
Published
Publication version:
Version of Record
Year:
2023
Number of pages:
14 str.
Numbering:
Vol. 14, art. 10
PID:
20.500.12556/RUL-145084
UDC:
636.2:575
ISSN on article:
2049-1891
DOI:
10.1186/s40104-022-00821-0
COBISS.SI-ID:
141296387
Publication date in RUL:
04.04.2023
Views:
533
Downloads:
89
Metadata:
Cite this work
Plain text
BibTeX
EndNote XML
EndNote/Refer
RIS
ABNT
ACM Ref
AMA
APA
Chicago 17th Author-Date
Harvard
IEEE
ISO 690
MLA
Vancouver
:
Copy citation
Share:
Record is a part of a journal
Title:
Journal of animal science and biotechnology
Shortened title:
J. anim. sci. biotechnol.
Publisher:
Springer Nature, BioMed Central
ISSN:
2049-1891
COBISS.SI-ID:
523180569
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
govedoreja
,
govedo
,
krave
,
molznice
,
mastitis
,
genetika
,
kandidatni geni
,
QTL
,
baza podatkov
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P4-0220
Name:
Primerjalna genomika in genomska biodiverziteta
Funder:
ARRS - Slovenian Research Agency
Funding programme:
Young researchers
Similar documents
Similar works from RUL:
Similar works from other Slovenian collections:
Back