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Validating genomic prediction for nitrogen efficiency index and its composition traits of Holstein cows in early lactation.

Authors :
Chen, Y.
Atashi, H.
Mota, R. R.
Grelet, C.
Vanderick, S.
Hu, H.
Crowe, Mark
Fahey, Alan
Carter, Fiona
Matthews, Elizabeth
Santoro, Andreia
Byrne, Colin
Rudd, Pauline
O'Flaherty, Roisin
Hallinan, Sinead
Wathes, Claire
Salavati, Mazdak
Cheng, Zhangrui
Fouladi, Ali
Pollott, Geoff
Source :
Journal of Animal Breeding & Genetics. Nov2023, Vol. 140 Issue 6, p695-706. 12p.
Publication Year :
2023

Abstract

Nitrogen (N) use efficiency (NUE) is an economically important trait for dairy cows. Recently, we proposed a new N efficiency index (NEI), that simultaneously considers both NUE and N pollution. This study aimed to validate the genomic prediction for NEI and its composition traits and investigate the relationship between SNP effects estimated directly from NEI and indirectly from its composition traits. The NEI composition included genomic estimated breeding value of N intake (NINT), milk true protein N (MTPN) and milk urea N yield. The edited data were 132,899 records on 52,064 cows distributed in 773 herds. The pedigree contained 122,368 animals. Genotypic data of 566,294 SNP was available for 4514 individuals. A total of 4413 cows (including 181 genotyped) and 56 bulls (including 32 genotyped) were selected as the validation populations. The linear regression method was used to validate the genomic prediction of NEI and its composition traits using best linear unbiased prediction (BLUP) and singleā€step genomic BLUP (ssGBLUP). The mean theoretical accuracies of validation populations obtained from ssGBLUP were higher than those obtained from BLUP for both NEI and its composition traits, ranging from 0.57 (MTPN) to 0.72 (NINT). The highest mean prediction accuracies for NEI and its composition traits were observed for the genotyped cows estimated under ssGBLUP, ranging from 0.48 (MTPN) to 0.66 (NINT). Furthermore, the SNP effects estimated from NEI composition traits, multiplied by the relative weight were the same as those estimated directly from NEI. This study preliminary showed that genomic prediction can be used for NEI, however, we acknowledge the need for further validation of this result in a larger dataset. Moreover, the SNP effects of NEI can be indirectly calculated using the SNP effects estimated from its composition traits. This study provided a basis for adding genomic information to establish NEI as part of future routine genomic evaluation programs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09312668
Volume :
140
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Animal Breeding & Genetics
Publication Type :
Academic Journal
Accession number :
172894184
Full Text :
https://doi.org/10.1111/jbg.12819