Is rumination time an indicator of methane production in dairy cows?

As long as large-scale recording of expensive-to-measure and labor-consuming traits, such as dry matter intake (DMI) and CH4 production (CH4P), continues to be challenging in practical conditions, alternative traits that are already routinely recorded in dairy herds should be investigated. An ideal indicator trait must, in addition to expressing genetic variation, have a strong correlation with the trait of interest. Our aim was to estimate individual level and phenotypic correlations between rumination time (RT), CH4P, and DMI to determine if RT could be used as an indicator trait for CH4P and DMI. Data from 343 Danish Holstein cows were collected at the Danish Cattle Research Centre for a period of approximately 3 yr. The data set consisted of 14,890 records for DMI, 15,835 for RT, and 6,693 for CH4P. Data were divided in primiparous cows only (PC) and all cows (MC), and then divided in lactation stage (early, mid, late, and whole lactation) to analyze the changes over lactation. Linear mixed models, including an animal effect but no pedigree, were used to estimate the correlations among traits. Phenotypic and individual level correlations between RT and both CH4P and DMI were close to zero, regardless of lactation stage and data set (PC or MC). However, CH4P and DMI were highly correlated, both across lactation stages and data sets. In conclusion, RT is unsuitable to be used as an indicator trait for either CH4P or DMI. Our study failed to validate RT as a useful indicator trait for both CH4P and DMI, but more studies with novel phenotypes can offer different approaches to select and incorporate important yet difficult to record traits into breeding goals and selection indexes.

Genetic correlations between methane production and fertility, health, and body type traits in Danish Holstein cows.

Our aim was to investigate the genetic correlations between CH4 production and body conformation, fertility, and health traits in dairy cows. Data were collected from 10 commercial Holstein herds in Denmark, including 5,758 cows with records for body conformation traits, 7,390 for fertility traits, 7,439 for health traits, and 1,397 with individual CH4 measurements. Methane production was measured during milking in automatic milking systems, using a sniffer approach. Correlations between CH4 and several different traits were estimated. These traits were interval between calving and first insemination, interval between first and last insemination, number of inseminations, udder diseases, other diseases, height, body depth, chest width, dairy character, top line, and body condition score. Bivariate linear models were used to estimate the genetic parameters within and between CH4 and the other traits. In general, the genetic correlations between CH4 and the traits investigated were low. The heritability of CH4 was 0.25, and ranged from 0.02 to 0.07 for fertility and health traits, and from 0.17 to 0.74 for body conformation traits. Further research with a larger data set should be performed to more accurately establish how CH4 relates to fertility, health, and body conformation traits in dairy cattle. This will be useful in the design of future breeding goals that consider the production of CH4.

Direct multitrait selection realizes the highest genetic response for ratio traits.

For a number of traits the phenotype considered to be the goal trait is a combination of 2 or more traits, like methane (CH) emission (CH/kg of milk). Direct selection on CH4 emission defined as a ratio is problematic, because it is uncertain whether the improvement comes from an improvement in milk yield, a decrease in CH emission or both. The goal was to test different strategies on selecting for 2 antagonistic traits- improving milk yield while decreasing methane emissions. The hypothesis was that to maximize genetic gain for a ratio trait, the best approach is to select directly for the component traits rather than using a ratio trait or a trait where 1 trait is corrected for the other as the selection criteria. Stochastic simulation was used to mimic a dairy cattle population. Three scenarios were tested, which differed in selection criteria but all selecting for increased milk yield: 1) selection based on a multitrait approach using the correlation structure between the 2 traits, 2) the ratio of methane to milk and 3) gross methane phenotypically corrected for milk. Four correlation sets were tested in all scenarios, to access robustness of the results. An average genetic gain of 66 kg of milk per yr was obtained in all scenarios, but scenario 1 had the best response for decreased methane emissions, with a genetic gain of 24.8 l/yr, while scenarios 2 and 3 had genetic gains of 27.1 and 27.3 kg/yr. The results found were persistent across correlation sets. These results confirm the hypothesis that to obtain the highest genetic gain a multitrait selection is a better approach than selecting for the ratio directly. The results are exemplified for a methane and milk scenario but can be generalized to other situations where combined traits need to be improved.

Polymorphisms in the ghrelin gene and their associations with milk yield and quality in water buffaloes.

Ghrelin is a gastrointestinal hormone that acts in releasing growth hormone and influences the body general metabolism. It has been proposed as a candidate gene for traits such as growth, carcass quality, and milk production of livestock because it influences feed intake. In this context, the aim of this study was to verify the existence of polymorphisms in the ghrelin gene and their associations with milk, fat and protein yield, and percentage in water buffaloes (Bubalus bubalis). A group of 240 animals was studied. Five primer pairs were used and 11 single nucleotide polymorphisms (SNP) were found in the ghrelin gene by sequencing. The animals were genotyped for 8 SNP by PCR-RFLP. The SNP g.960G>A and g.778C>T were associated with fat yield and the SNP g.905T>C was associated with fat yield and percentage and protein percentage. These SNP are located in intronic regions of DNA and may be in noncoding RNA sites or affect transcriptional efciency. The ghrelin gene in buffaloes influences milk fat and protein synthesis. The polymorphisms observed can be used as molecular markers to assist selection.