Heritability estimates and genome-wide association study of methane emission traits in Nellore cattle

Author:

Souza Luana Lelis1,Dominguez-Castaño Pablo12ORCID,Gianvecchio Sarah Bernardes13,Sakamoto Leandro Sannomiya3,Rodrigues Gustavo Roberto Dias13,Soares Tainara Luana da Silva13,Bonilha Sarah Figueiredo Martins34,Marcatto Juliana de Oliveira Santos5,Galvão Albuquerque Lucia14,Vasconcelos Silva Josineudson Augusto II64,Zerlotti Mercadante Maria Eugênia134

Affiliation:

1. Faculty of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP) , 14884-900, Jaboticabal , Brazil

2. Facultad de Ciencias Agrarias, Fundación Universitaria Agraria de Colombia-UNIAGRARIA , Bogotá 111166 , Colombia

3. Institute of Animal Science (IZ), Beef Cattle Research Center , 14160-970, Sertãozinho , Brazil

4. National Council for Science and Technological Development , 71605-001, Brasilia , Brazil

5. Embrapa Environment , 13820-000, Jaguariuna , Brazil

6. Faculty of Veterinary Medicine and Animal Science, São Paulo State University (UNESP) , 18618-000, Botucatu , Brazil

Abstract

Abstract The objectives of the present study were to estimate the heritability for daily methane emission (CH4) and residual daily methane emission (CH4res) in Nellore cattle, as well as to perform genome-wide association studies (GWAS) to identify genomic regions and candidate genes influencing the genetic variation of CH4 and CH4res. Methane emission phenotypes of 743 Nellore animals belonging to 3 breeding programs were evaluated. CH4 was measured using the sulfur hexafluoride (SF6) tracer technique (which involves an SF6 permeation tube introduced into the rumen, and an appropriate apparatus on each animal), and CH4res was obtained as the difference between observed CH4 and CH4 adjusted for dry matter intake. A total of 6,252 genotyped individuals were used for genomic analyses. Data were analyzed with a univariate animal model by the single-step GBLUP method using the average information restricted maximum likelihood (AIREML) algorithm. The effects of single nucleotide polymorphisms (SNPs) were obtained using a single-step GWAS approach. Candidate genes were identified based on genomic windows associated with quantitative trait loci (QTLs) related to the 2 traits. Annotation of QTLs and identification of candidate genes were based on the initial and final coordinates of each genomic window considering the bovine genome ARS-UCD1.2 assembly. Heritability estimates were of moderate to high magnitude, being 0.42 ± 0.09 for CH4 and 0.21 ± 0.09 for CH4res, indicating that these traits will respond rapidly to genetic selection. GWAS revealed 11 and 15 SNPs that were significantly associated (P < 10−6) with genetic variation of CH4 and CH4res, respectively. QTLs associated with feed efficiency, residual feed intake, body weight, and height overlapped with significant markers for the traits evaluated. Ten candidate genes were present in the regions of significant SNPs; 3 were associated with CH4 and 7 with CH4res. The identified genes are related to different functions such as modulation of the rumen microbiota, fatty acid production, and lipid metabolism. CH4 and CH4res presented sufficient genetic variation and may respond rapidly to selection. Therefore, these traits can be included in animal breeding programs aimed at reducing enteric methane emissions across generations.

Publisher

Oxford University Press (OUP)

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