Comparison of 16S rRNA Sequencing and Shotgun Metagenome Sequencing for Genotypic and Phenotypic Parameter Estimation of Methane in Cattle

Background<br/>Methane emissions from ruminants significantly contribute to greenhouse gas production, making it crucial for sustainable livestock breeding to understand how genetic and microbial factors influence methane production.<br/>Results<br/>We compared the heritability and microbiability for methane using microbial features derived from 16S rRNA amplicon data ((16s Microbial taxa (16s-MT), 16s Predicted microbial genes (16s-PMG), 16s Predicted metabolic pathways (16s-PMP)) with those from shotgun metagenomics (metagenomic species (M-S) and metagenomic genus (M-G) from MGnify, GTDB, and NCBI databases). For the same datasets, we also estimated the heritability of each microbial feature. The heritability of methane ranged from 0.08 to 0.14 across datasets, with the highest estimate obtained from M-S GTDB data. The 16s-MT yielded also the highest value for microbiability (0.38). Most microbial features had low heritability, while a subset had high values (up to 0.8). Species level features such as XBB1006 sp017442585 (0.99) and Anaerofustis sp019420015 and Enterousia sp900320405 (0.98) from GTDB and RUG592 sp902767285 (0.94) from MGnify had high heritabilities. We found that the microbiota in the rumen is primarily determined by environmental factors, whereas host genetics has a significant impact on the abundance of certain functionally important microbes, which play a crucial role in metabolic pathways such propanoate metabolism. <br/>Conclusion<br/>This study presents the first comparison of microbial heritability and methane heritability at multiple levels, including 16s-MT, 16s-PMG, 16s-PMP, and species and genus abundance from metagenomic datasets in dairy cattle, highlighting heritable microbial species as potential targets for microbiome-informed breeding strategies to reduce methane emissions.<br/>