Article (Scientific journals)
SNP-based quantitative deconvolution of biological mixtures: application to the detection of cows with subclinical mastitis by whole-genome sequencing of tank milk.
Coppieters, Wouter; Karim, Latifa; Georges, Michel
2020In Genome Research, 30 (8), p. 1201 - 1207
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Keywords :
Animals; Cattle; Cell Count/methods; Female; Gene Frequency/genetics; Genome/genetics; Genotyping Techniques; Mass Screening/methods; Mastitis/diagnosis; Mastitis/genetics; Milk; Polymorphism, Single Nucleotide/genetics; Whole Genome Sequencing/methods; Cell Count; Gene Frequency; Genome; Mass Screening; Mastitis; Polymorphism, Single Nucleotide; Whole Genome Sequencing; Genetics; Genetics (clinical)
Abstract :
[en] Biological products of importance in food (e.g., milk) and medical (e.g., donor blood-derived products) sciences often correspond to mixtures of samples contributed by multiple individuals. Identifying which individuals contributed to the mixture and in what proportions may be of interest in several circumstances. We herein present a method that allows to do this by shallow whole-genome sequencing of the DNA in mixed samples from hundreds of donors. We show the efficacy of the approach for the detection of cows with subclinical mastitis by analysis of farms' tank mixtures containing milk from as many as 500 cows.
Disciplines :
Genetics & genetic processes
Author, co-author :
Coppieters, Wouter ;  Université de Liège - ULiège > GIGA > GIGA Platform Genomics
Karim, Latifa ;  Université de Liège - ULiège > GIGA > GIGA Platform Genomics
Georges, Michel  ;  Université de Liège - ULiège > GIGA > GIGA Innovation
Language :
English
Title :
SNP-based quantitative deconvolution of biological mixtures: application to the detection of cows with subclinical mastitis by whole-genome sequencing of tank milk.
Publication date :
August 2020
Journal title :
Genome Research
ISSN :
1088-9051
eISSN :
1549-5469
Publisher :
Cold Spring Harbor Laboratory Press, United States
Volume :
30
Issue :
8
Pages :
1201 - 1207
Peer reviewed :
Peer Reviewed verified by ORBi
Funding text :
We thank Jean-Bernard Davière, Pierre Lenormand, Bonny Van Ranst, Kristien Neyens, and Miel Hostens for providing the samples and information needed to conduct the experiments. This work was funded by the Unit of Animal Genomics and by the ERC DAMONA grant to M.G.
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