Dataset Information

Microbial Populations in Ruminal Liquid Samples from Young Beefmaster Bulls at Both Extremes of RFI Values.

ABSTRACT: The gut microbiota is involved in the productivity of beef cattle, but the impact of different analysis strategies on microbial composition is unclear. Ruminal samples were obtained from Beefmaster calves (n = 10) at both extremes of residual feed intake (RFI) values (5 with the lowest and 5 with the highest RFI) from two consecutive days. Samples were processed using two different DNA extraction methods. The V3 and V4 regions of the 16S rRNA gene were amplified using PCR and sequenced with a MiSeq instrument (Illumina). We analyzed 1.6 million 16S sequences from all 40 samples (10 calves, 2 time points, and 2 extraction methods). The abundance of most microbes was significantly different between DNA extraction methods but not between high-efficiency (LRFI) and low-efficiency (HRFI) animals. Exceptions include the genus Succiniclasticum (lower in LRFI, p = 0.0011), and others. Diversity measures and functional predictions were also mostly affected by DNA extraction methods, but some pathways showed significant differences between RFI levels (e.g., methylglyoxal degradation, higher in LRFI, p = 0.006). The results suggest that the abundance of some ruminal microbes is associated with feed efficiency and serves as a cautionary tale for the interpretation of results obtained with a single DNA extraction method.

SUBMITTER: Manzanares-Miranda N

PROVIDER: S-EPMC10055678 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Microbial Populations in Ruminal Liquid Samples from Young Beefmaster Bulls at Both Extremes of RFI Values.

Manzanares-Miranda Nelson N Garcia-Mazcorro Jose F JF Pérez-Medina Eduardo B EB Vaquera-Vázquez Anakaren A Martínez-Ruiz Alejandro A Ramos-Zayas Yareellys Y Kawas Jorge R JR

Microorganisms 20230306 3

The gut microbiota is involved in the productivity of beef cattle, but the impact of different analysis strategies on microbial composition is unclear. Ruminal samples were obtained from Beefmaster calves (<i>n</i> = 10) at both extremes of residual feed intake (RFI) values (5 with the lowest and 5 with the highest RFI) from two consecutive days. Samples were processed using two different DNA extraction methods. The V3 and V4 regions of the 16S rRNA gene were amplified using PCR and sequenced wi ...[more]

PMID: 36985235

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Project description:The objective of this study was to evaluate the effect of the use of post-ruminal urea on performance, nitrogen metabolism and the ruminal environment of Nellore cattle reared on pasture during the dry season. In experiment 1 (Exp. 1), nine ruminal-cannulated Nellore steers, 30 ± 2 months old (651 ± 45 kg body weight (BW)), were allotted to a 3 × 3 Latin triple square. In experiment 2 (Exp. 2), 84 Nellore bulls, 18 ± 3 months old (315 ± 84 kg BW), were distributed in complete randomized blocks, by initial BW. Protein supplements were supplied daily, in the amount of 2 g/kg BW, and consisted of either CONT: protein + conventional urea (50% CP), PRU: protein + post ruminal urea (50% CP) and U + PRU: protein + urea conventional + post-ruminal urea (70% CP). The paddocks were composed of Urochloa brizantha cv. Marandu grass. In Exp. 1, there was no treatment effect for DM, OM, NDF, forage intake, and CP, but there was a higher intake for PRU (p < 0.005) and a higher digestibility for U+ PRU (p = 0.001). There was no effect on ruminal pH or NH3-N concentration (p ≥ 0.232), but there was an interaction between treatment and time for them (p < 0.039). Furthermore, there was a treatment effect on the total SCFA concentration, with CONT being higher than the others. A difference in the acetate:propionate ratio was found (p < 0.027), with a greater relationship for PRU and U + PRU. A treatment effect (p = 0.049) was found for the propionate proportion, with a higher proportion in the CONT. Nitrogen intake was consequently lower for the CONT and higher urinary excretion for the U + PRU (p = 0.002). Animals supplemented with CONT showed a tendency to have more Bacteria and fewer Archaea (p = 0.086). In Exp. 2, there was a treatment effect for the disappearance rate of the supplement (p < 0.001). Intake was faster for PRU and CONT, but performance was not affected by PRU (p = 0.311). The use of post-ruminal urea alters the microbial population, but does not affect performance. Therefore, supplementation with post-ruminal urea presented similar results compared to conventional urea. Ruminal and blood parameters and animal performance were not influenced by treatments.

Project description:BackgroundAt the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI).MethodsDense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length.ResultsRR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls.ConclusionsAccurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ~ 3,000 to 5,000 evenly spaced SNP.

Dataset Information

Microbial Populations in Ruminal Liquid Samples from Young Beefmaster Bulls at Both Extremes of RFI Values.

Publications

Microbial Populations in Ruminal Liquid Samples from Young Beefmaster Bulls at Both Extremes of RFI Values.

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