It is widely acknowledged that transcriptional diversity largely contributes to biological regulation in eukaryotes. Since the advent of second-generation sequencing technologies, a large number of RNA sequencing studies have considerably improved our understanding of transcriptome complexity. However, it still remains a huge challenge for obtaining full-length transcripts because of difficulties in the short read-based assembly. In the present study we employ PacBio single-molecule long-read sequencing technology for whole-transcriptome profiling in rabbit (Oryctolagus cuniculus). We totally obtain 36,186 high-confidence transcripts from 14,474 genic loci, among which more than 23% of genic loci and 66% of isoforms have not been annotated yet within the current reference genome. Furthermore, about 17% of transcripts are computationally revealed to be non-coding RNAs. Up to 24,797 alternative splicing (AS) and 11,184 alternative polyadenylation (APA) events are detected within this de novo constructed transcriptome, respectively. The results provide a comprehensive set of reference transcripts and hence contribute to the improved annotation of rabbit genome.

Bovine milk is rich in exosomes, which contain abundant miRNAs and play important roles in the regulation of neonatal growth and development of adaptive immunity. Here, we analyzed miRNA expression profiles of bovine milk exosomes from three healthy and three mastitic cows, and then six miRNA libraries were constructed. Interestingly, we detected no scRNAs and few snRNAs in milk exosomes; this result indicated a potential preference for RNA packaging in milk exosomes. A total of 492 known and 980 novel exosomal miRNAs were detected, and the 10 most expressed miRNAs in the six samples accounted for 80–90% of total miRNA-associated reads. Expression analyses identified 18 miRNAs with significantly different expression between healthy and infected animals; the predicted target genes of differentially expressed miRNAs were significantly enriched in immune system process, response to stimulus, growth, etc. Moreover, target genes were significantly enriched in several Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways including inflammatory, immune, and cancer pathways. Our survey provided comprehensive information about milk exosomes and exosomal miRNAs involved in mastitis. Moreover, the differentially expressed miRNAs, especially miR-223 and miR-142-5p, could be considered as potential candidates for mastitis.

Shi-Yi Chen*, Feilong Deng, Ming Zhang, Xianbo Jia, and Song-Jia Lai*. J. Microbiol. Biotechnol. 2020;30:804-10. https://doi.org/10.4014/jmb.2002.02010

Ketosis is a common metabolic disease in dairy cows during early lactation. However, information about the metabolomic and proteomic profiles associated with the incidence and progression of ketosis is still limited. In this study, an integrated metabolomics and proteomics approach was performed on blood serum sampled from cows diagnosed with clinical ketosis (case, ≥ 2.60 mmol/L plasma β-hydroxybutyrate; BHBA) and healthy controls (control, < 1.0 mmol/L BHBA). Samples were taken 2 weeks before parturition and 2 weeks after parturition from 19 animals (nine cases, 10 controls). All serum samples (n = 38) were subjected to Liquid Chromatography-Mass Spectrometry (LC-MS) based metabolomic analysis, and 20 samples underwent Data-Independent Acquisition (DIA) LC-MS based proteomic analysis. A total of 97 metabolites and 540 proteins were successfully identified, and multivariate analysis revealed significant differences in both metabolomic and proteomic profiles between cases and controls. We investigated clinical ketosis-associated metabolomic and proteomic changes using statistical analyses. Correlation analysis of statistically significant metabolites and proteins showed 78 strong correlations (correlation coefficient, R ≥ 0.7) between 38 metabolites and 25 proteins, which were then mapped to pathways using IMPaLA. Results showed that ketosis altered a wide range of metabolic pathways, such as metabolism, metabolism of proteins, gene expression and post-translational protein modification, vitamin metabolism, signaling, and disease related pathways. Findings presented here are relevant for identifying molecular targets for ketosis and biomarkers for ketosis detection during the transition period.