The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions.

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

Review: Diving into the cow hologenome to reduce methane emissions and increase sustainability.

Interest on methane emissions from livestock has increased in later years as it is an anthropogenic greenhouse gas with an important warming potential. The rumen microbiota has a large influence on the production of enteric methane. Animals harbour a second genome consisting of microbes, collectively referred to as the "microbiome". The rumen microbial community plays an important role in feed digestion, feed efficiency, methane emission and health status. This review recaps the current knowledge on the genetic control that the cow exerts on the rumen microbiota composition. Heritability estimates for the rumen microbiota composition range between 0.05 and 0.40 in the literature, depending on the taxonomical group or microbial gene function. Variables depicting microbial diversity or aggregating microbial information are also heritable within the same range. This study includes a genome-wide association analysis on the microbiota composition, considering the relative abundance of some microbial taxa previously associated to enteric methane in dairy cattle (Archaea, Dialister, Entodinium, Eukaryota, Lentisphaerae, Methanobrevibacter, Neocallimastix, Prevotella and Stentor). Host genomic regions associated with the relative abundance of these microbial taxa were identified after Benjamini-Hoschberg correction (Padj < 0.05). An in-silico functional analysis using FUMA and DAVID online tools revealed that these gene sets were enriched in tissues like brain cortex, brain amigdala, pituitary, salivary glands and other parts of the digestive system, and are related to appetite, satiety and digestion. These results allow us to have greater knowledge about the composition and function of the rumen microbiome in cattle. The state-of-the art strategies to include methane traits in the selection indices in dairy cattle populations is reviewed. Several strategies to include methane traits in the selection indices have been studied worldwide, using bioeconomical models or economic functions under theoretical frameworks. However, their incorporation in the breeding programmes is still scarce. Some potential strategies to include methane traits in the selection indices of dairy cattle population are presented. Future selection indices will need to increase the weight of traits related to methane emissions and sustainability. This review will serve as a compendium of the current state of the art in genetic strategies to reduce methane emissions in dairy cattle.

Influence of age at first calving in a continuous calving season on productive, functional, and economic performance in a Blonde d'Aquitaine beef population.

The lifetime production of 7,655 cows with known age at first calving and a total of 27,118 parity records from 301 purebred Blonde d'Aquitaine herds were used to demonstrate the economic benefits of 2 yr of age at first calving. Ages at first calving ranged from 20 to 48 mo, and cows were divided into 5 calving groups, starting with early calving from age 20 to 27 mo up to late calving from age 40 to 48 mo. The information was gathered into 2 data sets, one for only primiparous cows and the second for all cows. The traits analyzed in this study were grouped as functional, linear type, and production traits. Functional traits were calving interval, calving ease, and number of calvings. Skeletal, muscle, and functional appraisal were included as linear type traits. The production traits studied were BW and weaning weight, carcass growth, and conformation of the offspring. The only significant traits found in primiparous cows were late age at first calving, which resulted in heavier BW calves, and early age at first calving, which resulted in calves with greater carcass conformation scores. Age at first calving was found to be significant only in its effect on BW and the number of calvings over a cow's lifetime, with lighter calves for early age at first calving. Heritability for age at first calving was 0.17. Genetic correlation of age at first calving with direct calving ease was positive (0.27) and that with maternal calving ease was negative (-0.39). Age at first calving showed a negative genetic correlation with lifetime number of calvings (-0.29) and a positive correlation with calving interval (0.14). Correlations with production and type traits were low, except for skeletal development (-0.29). Based on phenotypic and genetic analysis, there is a tendency for early-calving cows to produce a greater lifetime number of calves with less muscle but good carcass growth. Age at first calving affected the number of heifers in the herd, replacement rate, and number of animals slaughtered each year. Shortening the age at first calving from 3 to 2 yr led to a reduction of heifer feeding cost of US$21.24 (17.7€), a reduction of production cost of $26.52 (22.1€), and a profit increase of $25.80 (21.50€) per slaughtered animal per year over lifetime cow production.

Expected consequences of including methane footprint into the breeding goals in beef cattle. A Spanish Blonde d'Aquitaine population as a case of study.

This study evaluates two potential scenarios for including methane (CH4 ) emissions in the breeding objectives of beef cattle, using the Spanish population of Blonde d'Aquitaine as a case of study. First, CH4 emissions were included as a cost using a shadow carbon price of 1.22€/CH4 kg (0.044€/CO2 kg) (carbon tax scenario). In the other scenario, a CH4 quota was applied, optimizing emissions per unit of product. The current production system was used as benchmark scenario (Scenario 1). The economic value of CH4 was calculated under all scenarios using a bioeconomic model that translated the production system into a mathematical function. Then, CH4 emissions were included with proper relative weight in the selection index under each scenario. The economic value of CH4 production from cows was -0.54€/year and -0.16€/year in a carbon tax and in a CH4 quota scenario, respectively. Economic values for CH4 production from fattening calves were -1.22€/year and -0.34€/year in a carbon tax and a quota scenario, respectively. The relative weights of total CH4 traits in the indices were 4.9% and 1.8% in a carbon tax and quota scenario. The carbon tax scenario led to smaller cows (-7.59 kg of mature weight) and a decrease in carcass weight gain of calves (-4.78 g/day) involving a reduction in emissions in comparison with Scenario 1 (-0.76 CH4 kg/slaughtered calf/year). However, it also led to a lower expected gain in profit per unit of product (-7.86 €/slaughtered calf/year). A carbon quota scenario would select slightly smaller cows (-0.48 kg) with similar responses in maternal abilities (age at first calving, calving interval, maternal weaning weight, and calving ease) and growth, and lower emissions (-0.22 CH4 kg/slaughtered calf/year) regarding the benchmark scenario. Profit per cow would increase by +1.52€/slaughtered calf/year although this scenario implies a reduction in the number of cows per herd. In a carbon tax scenario, higher reduction in emissions implied a reduction of profitability per animal.