Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle.

BACKGROUND: Mitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions. RESULTS: The ß-diversity analyses suggested a subtle association between methane production and overall microbiota composition (0.01 < R2 < 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (Padj < 0.05). Those genera associated with high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated with low methane emissions. The genus-level association network showed 2 clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs were found to be differentially abundant between low- and high-emission animals and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated with high methane emissions. The KEGG network showed 3 clusters grouping KEGGs associated with high emissions, low emissions, and not differentially abundant in either. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low-emission animals. CONCLUSIONS: Methane emissions are largely associated with the relative abundance of ciliates and fungi. The role of nitrate electron acceptors can be particularly important because this respiration mechanism directly competes with methanogenesis. Whole metagenome sequencing is necessary to jointly consider the relative abundance of Bacteria, Archaea, and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH4 emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding.

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.

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.