Literature DB >> 27136003

Genetic and phenotypic variance and covariance components for methane emission and postweaning traits in Angus cattle.

K A Donoghue, T Bird-Gardiner, P F Arthur, R M Herd, R F Hegarty.   

Abstract

Ruminants contribute 80% of the global livestock greenhouse gas (GHG) emissions mainly through the production of methane, a byproduct of enteric microbial fermentation primarily in the rumen. Hence, reducing enteric methane production is essential in any GHG emissions reduction strategy in livestock. Data on 1,046 young bulls and heifers from 2 performance-recording research herds of Angus cattle were analyzed to provide genetic and phenotypic variance and covariance estimates for methane emissions and production traits and to examine the interrelationships among these traits. The cattle were fed a roughage diet at 1.2 times their estimated maintenance energy requirements and measured for methane production rate (MPR) in open circuit respiration chambers for 48 h. Traits studied included DMI during the methane measurement period, MPR, and methane yield (MY; MPR/DMI), with means of 6.1 kg/d (SD 1.3), 132 g/d (SD 25), and 22.0 g/kg (SD 2.3) DMI, respectively. Four forms of residual methane production (RMP), which is a measure of actual minus predicted MPR, were evaluated. For the first 3 forms, predicted MPR was calculated using published equations. For the fourth (RMP), predicted MPR was obtained by regression of MPR on DMI. Growth and body composition traits evaluated were birth weight (BWT), weaning weight (WWT), yearling weight (YWT), final weight (FWT), and ultrasound measures of eye muscle area, rump fat depth, rib fat depth, and intramuscular fat. Heritability estimates were moderate for MPR (0.27 [SE 0.07]), MY (0.22 [SE 0.06]), and the RMP traits (0.19 [SE 0.06] for each), indicating that genetic improvement to reduce methane emissions is possible. The RMP traits and MY were strongly genetically correlated with each other (0.99 ± 0.01). The genetic correlation of MPR with MY as well as with the RMP traits was moderate (0.32 to 0.63). The genetic correlation between MPR and the growth traits (except BWT) was strong (0.79 to 0.86). These results indicate that selection for lower MPR may have undesired effect on animal productivity. On the other hand, MY and the RMPR were either not genetically correlated or weakly correlated with BWT, YWT, and FWT (-0.06 to 0.23) and body composition traits (-0.18 to 0.18). Therefore, selection for lower MY or RMPR would lead to lower MPR without impacting animal productivity. Where the use of a ratio trait (e.g., MY) is not desirable, selection on any of the forms of RMP would be an alternative.

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Year:  2016        PMID: 27136003     DOI: 10.2527/jas.2015-0065

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  10 in total

1.  Feed efficiency and carcass metrics in growing cattle1.

Authors:  David N Kelly; Craig Murphy; Roy D Sleator; Michelle M Judge; Stephen B Conroy; Donagh P Berry
Journal:  J Anim Sci       Date:  2019-11-04       Impact factor: 3.159

2.  Feed and production efficiency of young crossbred beef cattle stratified on a terminal total merit index.

Authors:  David N Kelly; Stephen B Conroy; Craig P Murphy; Roy D Sleator; Donagh P Berry
Journal:  Transl Anim Sci       Date:  2020-07-01

3.  Bayesian modeling reveals host genetics associated with rumen microbiota jointly influence methane emission in dairy cows.

Authors:  Qianqian Zhang; Gareth Difford; Goutam Sahana; Peter Løvendahl; Jan Lassen; Mogens Sandø Lund; Bernt Guldbrandtsen; Luc Janss
Journal:  ISME J       Date:  2020-05-04       Impact factor: 10.302

4.  Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows.

Authors:  Gareth Frank Difford; Damian Rafal Plichta; Peter Løvendahl; Jan Lassen; Samantha Joan Noel; Ole Højberg; André-Denis G Wright; Zhigang Zhu; Lise Kristensen; Henrik Bjørn Nielsen; Bernt Guldbrandtsen; Goutam Sahana
Journal:  PLoS Genet       Date:  2018-10-12       Impact factor: 5.917

5.  Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle.

Authors:  Philip C Garnsworthy; Gareth F Difford; Matthew J Bell; Ali R Bayat; Pekka Huhtanen; Björn Kuhla; Jan Lassen; Nico Peiren; Marcin Pszczola; Diana Sorg; Marleen H P W Visker; Tianhai Yan
Journal:  Animals (Basel)       Date:  2019-10-21       Impact factor: 2.752

6.  Methane and Carbon Dioxide Emission of Beef Heifers in Relation with Growth and Feed Efficiency.

Authors:  Gilles Renand; Aurélie Vinet; Virginie Decruyenaere; David Maupetit; Dominique Dozias
Journal:  Animals (Basel)       Date:  2019-12-12       Impact factor: 2.752

7.  Phenotypic association among performance, feed efficiency and methane emission traits in Nellore cattle.

Authors:  Leandro Sannomiya Sakamoto; Luana Lelis Souza; Sarah Bernardes Gianvecchio; Matheus Henrique Vargas de Oliveira; Josineudson Augusto Ii de Vasconcelos Silva; Roberta Carrilho Canesin; Renata Helena Branco; Melissa Baccan; Alexandre Berndt; Lucia Galvão de Albuquerque; Maria Eugênia Zerlotti Mercadante
Journal:  PLoS One       Date:  2021-10-14       Impact factor: 3.240

8.  Bovine host genome acts on rumen microbiome function linked to methane emissions.

Authors:  Marina Martínez-Álvaro; Marc D Auffret; Carol-Anne Duthie; Richard J Dewhurst; Matthew A Cleveland; Mick Watson; Rainer Roehe
Journal:  Commun Biol       Date:  2022-04-12

Review 9.  Global Warming and Dairy Cattle: How to Control and Reduce Methane Emission.

Authors:  Dovilė Bačėninaitė; Karina Džermeikaitė; Ramūnas Antanaitis
Journal:  Animals (Basel)       Date:  2022-10-06       Impact factor: 3.231

10.  Genetic and genomic analyses for predicted methane-related traits in Japanese Black steers.

Authors:  Yoshinobu Uemoto; Masayuki Takeda; Atushi Ogino; Kazuhito Kurogi; Shinichro Ogawa; Masahiro Satoh; Fuminori Terada
Journal:  Anim Sci J       Date:  2020 Jan-Dec       Impact factor: 1.749

  10 in total

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