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Variance component estimation and genome-wide association of predicted methane production in crossbred beef steers.

Authors :
Lakamp AD
Ahlberg CM
Allwardt K
Broocks A
Bruno K
Mcphillips L
Taylor A
Krehbiel CR
Calvo-Lorenzo MS
Richards C
Place SE
Desilva U
Kuehn LA
Weaber RL
Bormann JM
Rolf MM
Source :
Journal of animal science [J Anim Sci] 2023 Jan 03; Vol. 101.
Publication Year :
2023

Abstract

Enteric methane is a potent greenhouse gas and represents an escape of energy from the ruminant digestive system. Additive genetic variation in methane production suggests that genetic selection offers an opportunity to diminish enteric methane emissions. Logistic and monetary difficulties in directly measuring methane emissions can make genetic evaluation on an indicator trait such as predicted methane production a more appealing option, and inclusion of genotyping data can result in greater genetic progress. Three predicted methane production traits were calculated for 830 crossbred steers fed in seven groups. The methane prediction equations used included mathematical models from Ellis et al. (2007), Mills et al. (2003), and IPCC (2019). Pearson correlations between the traits were all greater than 0.99, indicating that each prediction equation behaved similarly. Further, the Spearman correlations between the estimated breeding values for each trait were also 0.99, which suggests any of the predicted methane models could be used without substantially changing the ranking of the selection candidates. The heritabilities of Ellis, Mills, and IPCC predicted methane production were 0.60, 0.62, and 0.59, respectively. A genome-wide association study identified one single nucleotide polymorphism (SNP) that reached the threshold for significance for all of the traits on chromosome 7 related to oxidoreductase activity. Additionally, the SNP slightly below the significance threshold indicate genes related to collagen, intracellular microtubules, and DNA transcription may play a role in predicted methane production or its component traits.<br /> (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Details

Language :
English
ISSN :
1525-3163
Volume :
101
Database :
MEDLINE
Journal :
Journal of animal science
Publication Type :
Academic Journal
Accession number :
37328159
Full Text :
https://doi.org/10.1093/jas/skad179