Microbiome studies in animal science using 16S rRNA gene sequencing have become increasingly common in recent years as sequencing costs continue to fall and bioinformatic tools become more powerful and user-friendly. The combination of molecular biology, microbiology, microbial ecology, computer science, and bioinformatics—in addition to the traditional considerations when conducting an animal science study—makes microbiome studies sometimes intimidating due to the intersection of different fields. The objective of this review is to serve as a jumping-off point for those animal scientists less familiar with 16S rRNA gene sequencing and analyses and to bring up common issues and concerns that arise when planning an animal microbiome study from design through analysis. This review includes an overview of 16S rRNA gene sequencing, its advantages, and its limitations; experimental design considerations such as study design, sample size, sample pooling, and sample locations; wet lab considerations such as field handing, microbial cell lysis, low biomass samples, library preparation, and sequencing controls; and computational considerations such as identification of contamination, accounting for uneven sequencing depth, constructing diversity metrics, assigning taxonomy, differential abundance testing, and, finally, data availability. In addition to general considerations, we highlight some special considerations by species and sample type.

Lameness is a major animal welfare and economic issue for the dairy industry and is a challenge to overcome due to multifaceted causes. Digital cushion thickness (DCT) is a strong predictor of lameness and is phenotypically associated with incidence of claw horn disruption lesions (CHDL; sole ulcers and white line disease). We hypothesized that DCT varies between digits and across lactation within the cow. This variation could be characterized to predict the occurrence of CHDL or compromised locomotion. BCS, visual locomotion score (VLS), DCT, and presence or absence of lesions were collected at 4 time points: <40 d prepartum (DPP), 1 to 30 d in milk (DIM), 90 to 120 DIM, and ≥255 DIM for 183 commercial Holstein cows enrolled in the study. Cows underwent digital sonographic examination for the measurement of DCT evaluated at the typical sole ulcer site beneath the flexor tuberosity for the right front medial and lateral digits and right hind medial and lateral digits. Factors such as parity number and stage in lactation were obtained from farm management software (DairyComp 305; Valley Agricultural Software, Tulare, CA). Cows were grouped by parity: primiparous (parity = 1) or multiparous (parity ≥ 2). The prevalence of CHDL among time points ranged from 0% to 4.2% for primiparous cows vs. 2.5% to 25% for multiparous cows, whereas the prevalence of lameness based on VLS of 3 to 5 ranged from 1.7% to 8.3% for primiparous cows vs. 12.7% to 33% for multiparous cows. DCT varied within primiparous and multiparous cows based on stage of lactation and digit (P < 0.05) and was thicker for both parity groups prior to dry off (≥255 DIM) and thinnest prior to calving (<40 DPP) and after peak lactation (90 to 120 DIM). The DCT of the front medial digit was thickest for primiparous heifers, whereas the hind lateral digit was thickest for multiparous cows. The DCT of the hind medial digit was thinnest for both parity groups. Parity group and DCT of the hind lateral digit <40 DPP were important predictors of CHDL (P < 0.05), whereas parity group and DCT of the hind lateral digit and front lateral digit at 1 to 30 DIM were key predictors of VLS lameness (P < 0.05). These results may help identify animals with higher odds of developing these diseases by highlighting key time points and specific digits of importance for monitoring. In addition, it improves our biological understanding of the relationship between DCT and lameness.

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