Structural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of study.

The advent of metagenomics in animal breeding poses the challenge of statistically modelling the relationship between the microbiome, the host genetics and relevant complex traits. A set of structural equation models (SEMs) of a recursive type within a Markov chain Monte Carlo (MCMC) framework was proposed here to jointly analyse the host-metagenome-phenotype relationship. A non-recursive bivariate model was set as benchmark to compare the recursive model. The relative abundance of rumen microbes (RA), methane concentration (CH4 ) and the host genetics was used as a case of study. Data were from 337 Holstein cows from 12 herds in the north and north-west of Spain. Microbial composition from each cow was obtained from whole metagenome sequencing of ruminal content samples using a MinION device from Oxford Nanopore Technologies. Methane concentration was measured with Guardian® NG infrared gas monitor from Edinburgh Sensors during cow's visits to the milking automated system. A quarterly average from the methane eructation peaks for each cow was computed and used as phenotype for CH4 . Heritability of CH4 was estimated at 0.12 ± 0.01 in both the recursive and bivariate models. Likewise, heritability estimates for the relative abundance of the taxa overlapped between models and ranged between 0.08 and 0.48. Genetic correlations between the microbial composition and CH4 ranged from -0.76 to 0.65 in the non-recursive bivariate model and from -0.68 to 0.69 in the recursive model. Regardless of the statistical model used, positive genetic correlations with methane were estimated consistently for the seven genera pertaining to the Ciliophora phylum, as well as for those genera belonging to the Euryarchaeota (Methanobrevibacter sp.), Chytridiomycota (Neocallimastix sp.) and Fibrobacteres (Fibrobacter sp.) phyla. These results suggest that rumen's whole metagenome recursively regulates methane emissions in dairy cows and that both CH4 and the microbiota compositions are partially controlled by the host genotype.

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.

Genetic relationship of discrete-time survival with fertility and production in dairy cattle using bivariate models.

Bivariate analyses of functional longevity in dairy cattle measured as survival to next lactation (SURV) with milk yield and fertility traits were carried out. A sequential threshold-linear censored model was implemented for the analyses of SURV. Records on 96,642 lactations from 41,170 cows were used to estimate genetic parameters, using animal models, for longevity, 305 d-standardized milk production (MY305), days open (DO) and number of inseminations to conception (INS) in the Spanish Holstein population; 31% and 30% of lactations were censored for DO and INS, respectively. Heritability estimates for SURV and MY305 were 0.11 and 0.27 respectively; while heritability estimates for fertility traits were lower (0.07 for DO and 0.03 for INS). Antagonist genetic correlations were estimated between SURV and fertility (-0.78 and -0.54 for DO and INS, respectively) or production (-0.53 for MY305), suggesting reduced functional longevity with impaired fertility and increased milk production. Longer days open seems to affect survival more than increased INS. Also, high productive cows were more problematic, less functional and more liable to being culled. The results suggest that the sequential threshold model is a method that might be considered at evaluating genetic relationship between discrete-time survival and other traits, due to its flexibility.