Literature DB >> 25403186

Genetic parameters for predicted methane production and laser methane detector measurements.

N K Pickering1, M G G Chagunda2, G Banos2, R Mrode2, J C McEwan1, E Wall3.   

Abstract

Enteric ruminant methane is the most important greenhouse gas emitted from the pastoral agricultural systems. Genetic improvement of livestock provides a cumulative and permanent impact on performance, and using high-density SNP panels can increase the speed of improvement for most traits. In this study, a data set of 1,726 dairy cows, collected since 1990, was used to calculate a predicted methane emission (PME) trait from feed and energy intake and requirements based on milk yield, live weight, feed intake, and condition score data. Repeated measurements from laser methane detector (LMD) data were also available from 57 cows. The estimated heritabilities for PME, milk yield, DMI, live weight, condition score, and LMD data were 0.13, 0.25, 0.11, 0.92, 0.38, and 0.05, respectively. There was a high genetic correlation between DMI and PME. No SNP reached the Bonferroni significance threshold for the PME traits. One SNP was within the 3 best SNP for PME at wk 10, 20, 30, and 40. Genomic prediction accuracies between dependent variable and molecular breeding value ranged between 0.26 and 0.30. These results are encouraging; however, more work is required before a PME trait can be implemented in a breeding program.

Entities:  

Keywords:  dairy cattle; genomewide association; genomic selection; heritability; methane

Mesh:

Substances:

Year:  2014        PMID: 25403186     DOI: 10.2527/jas.2014-8302

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


  9 in total

Review 1.  Host genetics associated with gut microbiota and methane emission in cattle.

Authors:  Sudarshan Mahala; Anju Kala; Amit Kumar
Journal:  Mol Biol Rep       Date:  2022-07-01       Impact factor: 2.742

2.  Estimates of the genetic contribution to methane emission in dairy cows: a meta-analysis.

Authors:  Navid Ghavi Hossein-Zadeh
Journal:  Sci Rep       Date:  2022-07-19       Impact factor: 4.996

3.  Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance.

Authors:  Rainer Roehe; Richard J Dewhurst; Carol-Anne Duthie; John A Rooke; Nest McKain; Dave W Ross; Jimmy J Hyslop; Anthony Waterhouse; Tom C Freeman; Mick Watson; R John Wallace
Journal:  PLoS Genet       Date:  2016-02-18       Impact factor: 5.917

4.  Gene and transcript abundances of bacterial type III secretion systems from the rumen microbiome are correlated with methane yield in sheep.

Authors:  Janine Kamke; Priya Soni; Yang Li; Siva Ganesh; William J Kelly; Sinead C Leahy; Weibing Shi; Jeff Froula; Edward M Rubin; Graeme T Attwood
Journal:  BMC Res Notes       Date:  2017-08-08

Review 5.  Application of meta-omics techniques to understand greenhouse gas emissions originating from ruminal metabolism.

Authors:  Robert J Wallace; Timothy J Snelling; Christine A McCartney; Ilma Tapio; Francesco Strozzi
Journal:  Genet Sel Evol       Date:  2017-01-16       Impact factor: 4.297

6.  Assessment of methane emission traits in ewes using a laser methane detector: genetic parameters and impact on lamb weaning performance.

Authors:  Jessica Reintke; Kerstin Brügemann; Tong Yin; Petra Engel; Henrik Wagner; Axel Wehrend; Sven König
Journal:  Arch Anim Breed       Date:  2020-04-16

7.  Genome-wide association studies for methane emission and ruminal volatile fatty acids using Holstein cattle sequence data.

Authors:  Ali Jalil Sarghale; Mohammad Moradi Shahrebabak; Hossein Moradi Shahrebabak; Ardeshir Nejati Javaremi; Mahdi Saatchi; Majid Khansefid; Younes Miar
Journal:  BMC Genet       Date:  2020-11-23       Impact factor: 2.797

8.  Ovine rumen papillae biopsy via oral endoscopy; a rapid and repeatable method for serial sampling.

Authors:  K M McRae; M Schultz; C G Mackintosh; G H Shackell; M F Martinez; K J Knowler; M Williams; C Ho; S N Elmes; J C McEwan
Journal:  N Z Vet J       Date:  2016-01-14       Impact factor: 1.628

9.  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

  9 in total

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