Disentangling the causal relationship between rabbit growth and cecal microbiota through structural equation models

Area of Science:

• Animal Science
• Microbiome Research
• Genetics

Background:

• Previous studies explored the cecal microbiome's impact on rabbit growth but didn't fully disentangle causal relationships.
• Genetic associations can confound the perceived effect of the microbiome on production traits.

Purpose of the Study:

• To apply structural equation models (SEM) to infer causal relationships between the cecal microbiota and rabbit growth.
• To differentiate direct host genetic effects from indirect genetic effects mediated by the microbiota.

Main Methods:

• Utilized structural equation models (SEM) to analyze the interplay between host genetics, cecal microbiota, and growth traits.
• Estimated indirect effects via structural coefficients, controlling for host genetics.

Main Results:

• Identified 138 operational taxonomic units (OTUs) with statistically significant effects on growth.
• A subset of OTUs (15 for ad libitum, 38 for restricted feeding) showed substantial effects (>0.2 SD).
• Specific OTUs from Desulfovibrio and Ruminococcaceae families had the largest impact on restricted growth, while an S24-7 family OTU affected ad libitum growth.

Conclusions:

• Disentangling direct and indirect effects is crucial for understanding mediation processes in production traits.
• This approach aids in predicting trait changes and designing microbial interventions.