Recovery of metagenome-assembled genomes from the rumen and fecal microbiomes of Bos indicus beef cattle

Autor(es)

Conteville, Liliane Costa ; da Silva, Juliana Virginio ; Andrade, Bruno Gabriel Nascimento ; Coutinho, Luiz Lehmann ; Palhares, Julio Cesar Pascale ; Regitano, Luciana Correia de Almeida

• Tipo de documento: Artigo Científico
• Fonte: SCIENTIFIC DATA; v. 11, n. 1, p. 7-pg., 2024-12-18.

Resumo

Nelore is a Bos indicus beef breed that is well-adapted to tropical environments and constitutes most of the world's largest commercial cattle herd: the Brazilian bovine herd. Despite its significance, microbial genome recovery from ruminant microbiomes has largely excluded representatives from Brazilian Nelore cattle. To address this gap, this study presents a comprehensive dataset of microbial genomes recovered from the rumen and feces of 52 Brazilian Nelore bulls. A total of 1,526 non-redundant metagenome-assembled genomes (MAGs) were recovered from their gastrointestinal tract, with 497 ruminal and 486 fecal classified as high-quality. Phylogenetic analysis revealed that the bacterial MAGs fall into 12 phyla, with Firmicutes and Bacteroidota being the most predominant, while all archaeal MAGs belong to the genus Methanobrevibacter. The exploration of these microbial genomes will provide valuable insights into the metabolic potential and functional roles of individual microorganisms within host-microbiome interactions, contributing to a better understanding of the microbiome's roles in bovine performance. (AU)

• Processo FAPESP: 20/15565-7 - Aplicação de metagenômica shotgun para detalhar a diversidade taxonômica e funcional do microbioma de Nelore associado a fatores dietéticos e fenotípicos
• Beneficiário: Liliane Costa Conteville
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 19/04089-2 - O Hologenoma de Nelore: implicações na qualidade de carne e em eficiência alimentar
• Beneficiário: Luciana Correia de Almeida Regitano
• Modalidade de apoio: Auxílio à Pesquisa - Programa eScience e Data Science - Temático