Integrated analysis of inflammatory mRNAs, miRNAs, and lncRNAs elucidates the molecular interactome behind bovine mastitis.

Mastitis is known as intramammary inflammation, which has a multifactorial complex phenotype. However, the underlying molecular pathogenesis of mastitis remains poorly understood. In this study, we utilized a combination of RNA-seq and miRNA-seq techniques, along with computational systems biology approaches, to gain a deeper understanding of the molecular interactome involved in mastitis. We retrieved and processed one hundred transcriptomic libraries, consisting of 50 RNA-seq and 50 matched miRNA-seq data, obtained from milk-isolated monocytes of Holstein-Friesian cows, both infected with Streptococcus uberis and non-infected controls. Using the weighted gene co-expression network analysis (WGCNA) approach, we constructed co-expressed RNA-seq-based and miRNA-seq-based modules separately. Module-trait relationship analysis was then performed on the RNA-seq-based modules to identify highly-correlated modules associated with clinical traits of mastitis. Functional enrichment analysis was conducted to understand the functional behavior of these modules. Additionally, we assigned the RNA-seq-based modules to the miRNA-seq-based modules and constructed an integrated regulatory network based on the modules of interest. To enhance the reliability of our findings, we conducted further analyses, including hub RNA detection, protein-protein interaction (PPI) network construction, screening of hub-hub RNAs, and target prediction analysis on the detected modules. We identified a total of 17 RNA-seq-based modules and 3 miRNA-seq-based modules. Among the significant highly-correlated RNA-seq-based modules, six modules showed strong associations with clinical characteristics of mastitis. Functional enrichment analysis revealed that the turquoise module was directly related to inflammation persistence and mastitis development. Furthermore, module assignment analysis demonstrated that the blue miRNA-seq-based module post-transcriptionally regulates the turquoise RNA-seq-based module. We also identified a set of different RNAs, including hub-hub genes, hub-hub TFs (transcription factors), hub-hub lncRNAs (long non-coding RNAs), and hub miRNAs within the modules of interest, indicating their central role in the molecular interactome underlying the pathogenic mechanisms of S. uberis infection. This study provides a comprehensive insight into the molecular crosstalk between immunoregulatory mRNAs, miRNAs, and lncRNAs during S. uberis infection. These findings offer valuable directions for the development of molecular diagnosis and biological therapies for mastitis.

Study of whole genome linkage disequilibrium patterns of Iranian water buffalo breeds using the Axiom Buffalo Genotyping 90K Array.

Accuracy of genome-wide association studies, and the successful implementation of genomic selection depends on the level of linkage disequilibrium (LD) across the genome and also the persistence of LD phase between populations. In the present study LD between adjacent SNPs and LD decay between SNPs was calculated in three Iranian water buffalo populations. Persistence of LD phase was evaluated across these populations and effective population size (Ne) was estimated from corrected r2 information. A set of 404 individuals from three Iranian buffalo populations were genotyped with the Axiom Buffalo Genotyping 90K Array. Average r2 and |D'| between adjacent SNP pairs across all chromosomes was 0.27 and 0.66 for AZI, 0.29 and 0.68 for KHU, and 0.32 and 0.72 for MAZ. The LD between the SNPs decreased with increasing physical distance from 100Kb to 1Mb between markers, from 0.234 to 0.018 for AZI, 0.254 to 0.034 for KHU, and 0.297 to 0.119 for MAZ, respectively. These results indicate that a density of 90K SNP is sufficient for genomic analyses relying on long range LD (e.g. GWAS and genomic selection). The persistence of LD phase decreased with increasing marker distances across all the populations, but remained above 0.8 for AZI and KHU for marker distances up to 100Kb. For multi-breed genomic evaluation, the 90K SNP panel is suitable for AZI and KHU buffalo breeds. Estimated effective population sizes for AZI, KHU and MAZ were 477, 212 and 32, respectively, for recent generations. The estimated effective population sizes indicate that the MAZ is at risk and requires careful management.

Regulation of lipid metabolism in adipose depots of fat-tailed and thin-tailed lambs during negative and positive energy balances.

This study aimed to evaluate the effects of negative and positive energy balances on gene expression of regulators and enzymes controlling lipogenesis and lipolysis in muscle and adipose depots of fat-tailed and thin-tailed lambs. Lambs were slaughtered during neutral, negative and positive energy balances for sample collection. Real time q-PCR was conducted to measure the gene expression. Expression of PPARγ was increased in response to positive energy balance regardless of genotype and type of tissue (P<0.04). Expression of SREBF1 was reduced in response to negative and positive energy balances in fat-tailed lambs, whereas in thin-tailed lambs, downregulated SREBF1 was restored during positive energy balance (P<0.01). Enhancement in FABP4 expression in response to negative and positive energy balances was respectively higher in thin-tailed and fat-tailed lambs affected by interaction of genotype and energy balance (P<0.11). In thin-tailed lambs, the enhanced FABP4 expression in response to negative energy balance was considerably higher in mesenteric adipose depot, whereas in fat-tailed lambs, positive energy balance induced enhancement in FABP4 expression was considerably higher in fat-tail adipose depot. The results demonstrate that transcription regulation of lipogenesis and lipolysis during negative and positive energy balances occurs differently in fat-tailed and thin-tailed lambs. Thin-tailed and fat-tailed lambs are respectively more responsive to negative and positive energy balances and mesenteric and fat-tail adipose depots respectively in thin-tailed and fat-tailed lambs are the main adipose depots responsible for higher responsiveness of thin-tailed and fat-tailed lambs to negative and positive energy balances.