| Bovine mastitis, defined as ‘an inflammation of the mammary gland', generally is considered the most frequent and costly disease of dairy cattle. mi RNAs are post-transcriptional regulators that bind to complementary sequences on target m RNAs. Several reviews have summarized the diverse mi RNA biological roles, including growth and development, hormone secretion, modulating innate and adaptive immune responses as well as diseases. The post-transcriptional regulation of mi RNAs is closely related to the expression of mastitis-related genes. Here, we present the mi RNA expression profiles in peripheral blood from healthy and mastitis Holstein cattle by deep sequencing, map and catalog expressed mi RNAs, including bovine known, novel and candidate mi RNAs. Differentially expressed mi RNAs were screened and the candidate mi RNAs were chosen randomly to confirm the expression profiles by quantitative PCR. The genetic variation of PRMT2 gene was carried out by gene clone, PCR-RFLP and quantitative PCR. Moreover, we verified target genes of mi R-146 a by vector construction and cell culture. The main results of the study are showed as following:1. Solexa sequencing of miRNA in peripheral blood from Holstein cattleTwo small libraries in peripheral blood from healthy(H) and mastitis(M) Holstein cattle were constructed for Solexa sequencing technique. Solexa sequencing provided a total of 16,733,120 and 9,373,740 raw reads respectively. After removal of low quality data, 10,654,985(63.68%) and 8,708,111(93.90%) clean reads were ultimately obtained. Of the total small sequences in the two libraries, the majority clean reads were 21~23 nt in length, 83.62% of clean reads from the H library and 85.36% of clean reads from the M library, which is typical of the small RNA of Dicer-processed products. Among the small sequences, the number of 23 nt small RNAs(29.82% of total clean reads) is the most dominant fragments in H library and so is the number of 21 nt small RNAs(32.53% of total clean reads).2. Features of miRNA in peripheral blood from Holstein cattleA total of 608 pre-mi RNAs encoding 753 mi RNAs, the mi RNAs were categorized into three groups based on their hits: 448 known mi RNAs, 25 conserved mi RNAs, 270 novel candidates. The genome location and context annotation of 608 pre-mi RNAs were detected inour study, of which 95 pre-mi RNAs can not mapped to the bovine genome. Our most interesting finding is that there were many pairs of known mi RNAs and novel candidates with the same pre-mi RNA structures but very different reads, 145 pairs of mi RNAs were dectected in the study. We grouped pre-mi RNAs into clusters(at least two pre-mi RNAs in a cluster) if their interdistance were less than a difined maximum interdistance(MID) value. 56 clusters were identified with MID = 3 kb, 59 clusters were identified with MID = 10 kb, 58 clusters were identified with MID = 50 kb.3. Validation of bovine mi RNAs in peripheral blood from Holstein cattleA total of 18 known mi RNAs and 6 novel mi RNAs were randomly selected for experimental validation by stem-loop PCR and gene clone. The results showed that these 24 mi RNAs were successfully cloned in bovine, which indicates the reliability of Solexa sequencing.4. Identification of mastitis-related miRNAs in peripheral blood and their target predictIdentification of mi RNAs differentially expressed between the two libraries was performed after their reads were normalized. The results showed that a total of 173 mi RNAs were differentially expressed between the H and M libraries, of which 123 were up-regulated and 50 were down-regulated in the peripheral blood from mastitis Holstein cattle compared to healthy Holstein cattle. We selected randomly 14 differentially expressed mi RNAs, including 9 down-regulated mi RNAs and 5 up-regulated mi RNAs to validate the results of Solexa sequencing using stem-loop PCR. The top 10 unique mi RNAs with the highest expression level accounted for 83.77% and 80.85% of the clean reads in healthy and mastitis Holstein cattle libraries respectively. The unified set of the top 10 unique mi RNAs in the two libraries correspond to 12 unique mi RNAs. Among these 12 types of mi RNAs, 8(bta-mi R-486, bta-mi R-451, bta-mi R-191, bta-mi R-339 b, mml-mi R-486-5p, bta-mi R-25, bta-mi R-342, bta-mi R-30e-5p) are present in the top 10 mi RNAs in two libraries, which suggests essential roles in various conditions. To identify the potential target genes of the differentially expressed mi RNAs, target prediction was performed using MIREAP software. The predicted target genes for the differnential expression with highly abundant mi RNAs were claaified according to GO enrichment analysis and KEGG function annotations. 173 mi RNAs were predicted putative targets, 73,703 genes were selected as potential targets. Most of the target genes were involved in protein transport, positive regulation of transcription from RNA polymerase II promoter, positive regulation of I-kappa B kinase/NF-kappa B cascade, Chemokine signaling pathway, Arginine and proline metabolism, m RNA surveillance pathway, which indicated that some mi RNAs may have important roles in immune system.5. Genetic vatiation analysis of mastitis-related mi RNA?s target gene in dairy cattleTo explore the variability of the PRMT2 gene and resistance to mastitis in cows, splice variant(SV), and single nucleotide polymorphisms(SNPs) were identified in this study. A SV lacking exon 7(98-bp) was found in healthy and mastitis-infected mammary tissues. Two of four SNPs(A10276G, C24375T) were significantly associated with bovine milk yield and protein content. Further, we estimated the relative expression of PRMT2-SV in the mammary tissue of dairy cattle by using quantitative real-time PCR. The result showed that expression of the PRMT2-SV m RNA was significantly upregulated 4.02-fold(p < 0.05) in infected mammary tissues compared to healthy tissues. Our findings reveal that PRMT2-SV may play an important role in mastitis resistance in dairy cattle. The two SNPs may be used as a possible candidate SNPs for marker-assisted selection and management in Holstein cattle.6. Predict and verify targrt genes of mi R-146aTRAF and TLR4 gene are predicted as target genes of mi R-146 a using bioinformatics mthords. Wild and mutant fragments of bovine TRAF and TLR4 gene 3'UTR were cloned into the luciferase report psi CHECK-2 vector. The level of reporter gene expression was determined using the Dual-luciferase Reporter Assay System. The results showed that TRAF and TLR4 gene are both target genes of mi R-146 a. |
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