| The global production and value of cultured grass carp(Ctenopharyngodon idella) in recent years has been ranked in the forefront among all the fish species in China and around the world. Under the artificial cultivation condition, cultured grass carp is more susceptible to various diseases. Improving the disease-resistance of grass carp is one of the important ways to increase the yield. The differences of disease resistance is related to genetics. It is important to explore the differences between the disease susceptible and resistant stocks of grass carp from the level of transcription for revealing the molecular mechanism of this difference. In this study, the two stocks were constructed with disease susceptible grass carp(SGC) and resistant grass carp(RGC) infected with Aeromonas hydrophila. Differential expression profiles of mi RNA and m RNA were defined in the SGC and RGC through the high throughput sequencing technology. Key mi RNA and m RNA with important regulatory roles were functionally characterized to clarify their association with disease resistance.1. m RNA sequencing analysis of SGC and RGCTwo c DNA libraries constructed from spleen and kidney tissue of SGC and RGC were sequenced by Illumina Hiseq 2000 technology with 7.09 G and 6.13 G data obtained respectively. 199,554 transcription sequences were obtained after filtration, splicing and assembling of the sequencing data. 28,311 transcription were annotated by the BLASTx analysis. From the two c DNA libraries, 721 unigenes were identified to be expressed at significantly different levels; 475 were significantly up-regulated and 246 were significantly down-regulated in the SGC in comparison to the RGC library. Biological function and signal pathway enrichment analysis showed that the differentially expressed genes were mainly enriched in immune related signaling pathways.2. Screening and identification of key mi RNA in the spleen of SGC and RGCTwo small RNA libraries constructed from spleen of SGC and RGC were sequenced by Illumina Hiseq 2000 technology. 61 mi RNAs were identified in mi RBase 19.0 and the other 124 mi RNAs showed no homology to any known metazoan mi RNAs. Among them, mi R-451 and mi R-101 a was the most abundant mi RNA in SGC and RGC, respectively; while, cid-mi Rn-85 has the largest fold-change of 4.12 times between SGC and RGC. 21 mi RNAs were found to be differentially expressed between SGC and RGC. 5 mi RNAs were high expression in SGC, 16 in RGC. 287 target genes predicted by mi Randa were correlated with 21 mi RNAs. The 287 target genes were also uploaded into the KEGG database for pathway enrichment analysis. And the results showed that 35 pathways referred to immune-related function.Further study on the 5 mi RNAs of significantly higher expression in SGC was performed to clarify their association with disease resistance. lei-7i and cid-mi Rn-118 was the most abundant in spleen and kidney, cid-mi Rn-3 and mi R-451 was the most abundant in blood. A clear time-dependent expression pattern of let-7i, cid-mi Rn-118, cid-mi Rn-3 and mi R-451 was found after the bacterial challenge. Target genes likely regulated by lei-7i and cid-mi Rn-118 was identified using mi Randa. In addition, Cinfil3-6 and Citlr4 genes were direct targets of let-7i and cid-mi Rn-118 by dual luciferase reporter system and over expression test. The Citlr4 was significantly higher in spleen and kidney. Bacteria and viruses could affect the expression level of Citlr4. Overexpression of Citlr4 could activate the downstream immune genes, like il-1β, il-8 and TNF-α.3. Screening and identification of key mi RNA in the kidney of SGC and RGCTwo small RNA libraries from kidney of SGC and RGC were sequenced by Illumina Hiseq 2000 technology. 97 mi RNAs were present in mi RBase 19.0 and the remaining 95 mi RNAs showed no homology to any known metazoan mi RNAs. mi R-101 a was the most abundant mi RNA in SGC and RGC, cid-mi Rn-154 had the largest fold-change of about 5.19 times between SGC and RGC. 9 mi RNAs were significant differences expression in kidney between SGC and RGC, with 3 mi RNAs exhibiting elevated expression expression in SGC, 6 in RGC. And 188 of the target genes predicted by mi Randa were correlated with the 9 mi RNAs. The 188 target genes were also uploaded into the KEGGdatabase for pathway enrichment analysis, and results showed that 26 pathways referred to immune-related function.Further study on 9 mi RNAs of significantly different expression in SGC and RGC was performed. 9 mi RNAs were constitutively expressed in 6 immune tissues of untreated grass carp. The binding sites of the mi RNAs(mi R142a-3p, mi R-21, mi R-223, cid-mi Rn-115 and cid-mi Rn-131) were identified in the Citlr5 3’UTR region using mi Randa software. The inverse expression correlation between cid-mi Rn-115, mi R-142a-3p and Citlr5 were detected in grass carp tissue expression profile and CIK stimulation test. The cid-mi Rn-115 and mi R-142a-3p leaded to a significant decrease in endogenous Citlr5 expression. The Citlr5 was significantly higher in spleen and liver. Bacteria and viruses could affect the expression of Citlr5. Overexpression of Citlr5 could activate the downstream immune genes, like il-1β, il-8 and TNF-α.4. Determination of reference mi RNAs for relative quantification in grass carpIn this part, the stability of seven mi RNAs(mi R-126-3p, mi R-101 a, mi R-451, mi R-22 a, mi R-146, mi R-142a-5p and mi R-192) and two gene(18s r RNA and β-actin) was investigated by q RT-PCR in different tissues and during different development stages of grass carp. Stability values were calculated with ge Norm, Norm Finder, Best Keeper and Delta CT algorithms. mi R-126-3p was the most stable reference mi RNA gene during developmental stages 1–5, while mi R-22 a was the most stable during developmental stages 6–18. When each tissue type was considered, the most stable mi RNAs were mi R-126-3p in blood and liver, mi R-101 a in the gills, mi R-192 in the kidney, mi R-451 in the intestine and mi R-22 a in the brain, head kidney, spleen, heart, muscle, skin and fin. |
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