Host Genome–Metagenome Analyses Using Combinatorial Network Methods Reveal Key Metagenomic and Host Genetic Features for Methane Emission and Feed Efficiency in Cattle

• DOI: 10.3389/fgene.2022.795717
• Publication Date: 2022-02-23T14:48:42Z
• Authors: Stefano Cardinale; Haja N. Kadarmideen
• Keywords: 2. Zero hunger; 0303 health sciences; Synomics insight; rumen microbiome; Rumen microbiome; synomics insight; methane emission; heritability; QH426-470; Heritability; 03 medical and health sciences; cattle; 13. Climate action; Methane emission; combinatorial analyses; Genetics; Cattle; Combinatorial analyses

Cattle production is one of the key contributors to global warming due methane emission, which a by-product converting feed stuff into milk and meat for human consumption. Rumen hosts numerous microbial communities that are involved in digestive process, leading notable amounts emission. The factors underlying differences emission between individual animals to, among other factors, both specific enrichments certain host genetic influence abundances. detection such involves various biostatistical bioinformatics methods. In this study, our main objective was reanalyze publicly available data set using proprietary Synomics Insights platform based on novel combinatorial network machine learning methods detect metagenomic features residual intake (RFI) dairy cattle. compare results with standard tools, as those found microbiome QIIME2 classic GWAS analysis. used comprised 1,016 cows 16S short read sequencing from two cow breeds: Holstein Nordic Reds. Host genomic consisted 50 k 150 SNP arrays. Although several traits were analyzed by original authors, here, we considered only phenotype associating factors. can identify taxa differentially abundant showing high or low RFI. Focusing exclusively enriched taxa, study identified 26 order-level networks reported significantly either emitters. Additionally, Z-test proportions 21/26 (81%) these emitters ( p value <.05). particular, phylum Proteobacteria order Desulfovibrionales while Veillonellales be more previously cattle (Wallace et al., 2015). comparison, tool ANCOM Methanosarcinales could groups. We also investigated link genome rumen applying comparing it an industry method. This resulted identification determinants associated changes heritable components microbiome. Only four SNPs GWAS, whereas 1,290 significant not GWAS. Gene Ontology (GO) analysis transcription factor dominant biological function. estimated heritability core 73 taxonomies showed some species medium highly (0.25–0.62), paving way selective breeding desirable characteristics. 113 >90% taxonomies. Finally, have characterized small (<10) strongly bacterial orders known role methanogenesis, Desulfobacterales Methanobacteriales.