Heritable and Nonheritable Rumen Bacteria Are Associated with Different Characters of Lactation Performance of Dairy Cows

Recent studies have reported that some rumen microbes are heritable. However, it is necessary to clarify the functions and specific contributions of the heritable rumen microbes to cattle phenotypes (microbiability) in comparison with those that are nonheritable. This study aimed to identify the distribution and predicted functions of heritable and nonheritable bacterial taxa at species level in the rumen of dairy cows and their respective contributions to energy-corrected milk yield, protein content and yield, and fat content and yield in milk. Thirty-two heritable and 674 nonheritable bacterial taxa were identified at species level, and the functional analysis revealed that predicted microbial functions for both groups were mainly enriched for energy, amino acid, and ribonucleotide metabolism. The mean microbiability (to reflect a single taxon's contribution) of heritable bacteria was found to range from 0.16% to 0.33% for the different milk traits, whereas the range for nonheritable bacteria was 0.03% to 0.06%. These findings suggest a strong contribution by host genetics in shaping the rumen microbiota, which contribute significantly to milk production traits. Therefore, there is an opportunity to further improve milk production traits through attention to host genetics and the interaction with the rumen microbiota. IMPORTANCE Rumen bacteria produce volatile fatty acids which exert a far-reaching influence on hepatic metabolism, mammary gland metabolism, and animal production. In the current study, 32 heritable and 674 nonheritable bacterial taxa at species level were identified, and shown to have different microbiability (overall community contribution) and mean microbiability (the average of a single taxon's contribution) for lactation performance. The predicted functions of heritable and nonheritable bacterial taxa also differed, suggesting that targeted nutritional and genetic breeding approaches could be used to manipulate them to improve dairy cow performance.