Identification of novel and differentially expressed micro RNAs in ovine ovary and testis tissues using Solexa sequencing and bioinformatics

Micro RNAs（mi RNAs） are small, single stranded, non-coding RNA molecules, about 19–25 nucleotides in length, which regulate the development and functions of reproductive system of mammal.To discover novel mi RNAs and identify the differential expression of them in ovine ovary and testis tissues, the study constructed two libraries by using next-generation sequencing technologies（Solexa high-throughput sequencing technique）.As a result, 9 321 775 and 9 511 538 clean reads were obtained from the ovary and testis separately, which included 130 562（90 genes of ovary） and 56 272（85 genes of testis） of known mi RNAs and 486 potential novel mi RNAs reads.In this study, a total of 65 conserved mi RNAs were significantly differentially expressed（P〈0.01） between the two samples.Among them, 28 mi RNAs were up-regulated and 3 mi RNAs were down-regulated on ovary compared with testis.In addition, the known mi RNAs with the highest expression level（5 mi RNAs） and 30 novel mi RNAs with the functions related to reproduction were validated using the real-time quantitative RT-PCR.Moreover, the gene ontology（GO） annotation and Kyoto encyclopedia of genes and genomes（KEGG） pathway analysis showed that differentially expressed mi RNAs were involved in ovary and testis physiology, including signal transduction, gonad development, sex differentiation, gematogenesis, fertilization and embryo development.The results will be helpful to facilitate studies on the regulation of mi RNAs during ruminant reproduction.

Discovery of MicroRNAs Associated with the S Type Cytoplasmic Male Sterility in Maize

MicroRNAs （miRNAs） are endogenous small RNAs that play important regulatory roles in the growth and development processes of plants and animals. In this study, we examined the expression profiles of pollen miRNAs from a maize S type cytoplasmic male sterile line and its fertility restored line. In total, 100 known miRNAs belonging to 20 families and 81 novel miRNAs belonging to 44 families were identified. Two and seven known miRNAs had significant expression difference between the two lines at the level of P-value〈0.01 and 0.01〈P-value〈0.05, respectively. Four miRNAs showing 〉1.5 fold expression difference were verified by stem-loop RT-qPCR. Gene Ontology analysis of miRNA target genes revealed that these genes mainly participated in the transcriptional regulation processes.

Identification of Novel and Differentially Expressed MicroRNAs in the Ovaries of Laying and Non-Laying Ducks

MicroRNAs （miRNAs）, which post-transcriptionally regulate gene expression by binding to the 3′untranslated region of mRNAs to either inhibit or enhance translation, are involved in diverse biological processes. The use of high-throughput Solexa sequencing plays important roles in the discovery of miRNAs. In this study, we used high-throughput Solexa sequencing to identify novel duck miRNAs and compare the miRNA expression profiles in laying and non-laying duck ovaries. Using a bioinformatic analysis, we discovered 86 potential duck miRNAs similar to known chicken miRNAs and 43 unique sequences that matched known miRNAs of other species. We also found that miRNA variations and isoforms were widespread in our two RNA libraries, with most of the variations occurring in the 3′region of the miRNAs. Furthermore, we detected 55 miRNAs that exhibited significant expression differences between laying and non-laying ducks. Gene ontology （GO） and kyoto encyclopedia of genes and genomes （KEGG） enrichment analyses of the potential targets of the differentially expressed miRNAs indicated these miRNAs may play key roles in the egg laying process. Finally, we confirmed the differential expression of 5 miRNAs in the laying and non-laying samples by qRT-PCR. Cumulatively, our work provides the first look at the miRNA expression profile of the duck ovary and provides novel insight into the roles of miRNAs in egg laying and reproduction.

Prediction of candidate small non-coding RNAs inAgrobacterium by computational analysis

Small non-coding RNAs with important regulatory roles are not confined to eukaryotes. Recent work has uncovered a growing number of bacterial small RNAs （sRNAs）, some of which have been shown to regulate critical cellular processes. Computational approaches, in combination with molecular experiments, have played an important role in the identification of these sRNAs. At present, there is no information on the presence of small non-coding RNAs and their genes in the Agrobacterium tumefaciens genome. To identify potential sRNAs in this important bacterium, deep sequencing of the short RNA populations isolated from Agrobacterium tumefaciens C58 was carried out. From a data set of more than 10,000 short sequences, 16 candidate sRNAs have been tentatively identified based on computational analysis. All of these candidates can form stem-loop structures by RNA folding predictions and the majority of the secondary structures are rich in GC base-pairs：：Some are followed by a short stretch of U residues, indicative of a rho-independent transcription terminator, whereas some of the short RNAs are found in the stem region of the hairpin, indicative of eukaryotic-like sRNAs. Experimental strategies will need to be used to verify these candidates. The study of an expanded list of candidate sRNAs in Agrobacterium will allow a more complete understanding of the range of roles played by regulatory RNAs in prokaryotes.

Methotrexate combined with methylprednisolone for the recovery of motor function and differential gene expression in rats with spinal cord injury

Methylprednisolone is a commonly used drug for the treatment of spinal cord injury, but high doses of methylprednisolone can increase the incidence of infectious diseases. Methotrexate has anti-inflammatory activity and immunosuppressive effects, and can reduce in- flammation after spinal cord injury. To analyze gene expression changes and the molecular mechanism of methotrexate combined with methylprednisolone in the treatment of spinal cord injury, a rat model of spinal cord contusion was prepared using the PinPointTM preci- sion cortical impactor technique. Rats were injected with methylprednisolone 30 mg/kg 30 minutes after injury, and then subcutaneously injected with 0.3 mg/kg methotrexate 1 day after injury, once a day, for 2 weeks. TreadScan gait analysis found that at 4 and 8 weeks after injury, methotrexate combined with methylprednisolone significantly improved hind limb swing time, stride time, minimum longitudinal deviation, instant speed, footprint area and regularity index. Solexa high-throughput sequencing was used to analyze differential gene ex- pression. Compared with methylprednisolone alone, differential expression of 316 genes was detected in injured spinal cord treated with methotrexate and methylprednisolone. The 275 up-regulated genes were mainly related to nerve recovery, anti-oxidative, anti-inflammatory and anti-apoptotic functions, while 41 down-regulated genes were mainly related to proinflammatory and pro-apoptotic functions. These results indicate that methotrexate combined with methylprednisolone exhibited better effects on inhibiting the activity of inflammatory cytokines and enhancing antioxidant and anti-apoptotic effects and thereby produced stronger neuroprotective effects than methotrexate alone. The 316 differentially expressed genes play an important role in the above processes.

Global Analysis of Non-coding Small RNAs in Arabidopsis in Response to Jasmonate Treatment by Deep Sequencing Technology

In plants, non-coding small RNAs play a vital role in plant development and stress responses. To explore the possible role of non-coding small RNAs in the regulation of the jasmonate （JA） pathway, we compared the non-coding small RNAs between the JA-deficient aos mutant and the JA-treated wild type Arabidopsis via high-throughput sequencing. Thirty new miRNAs and 27 new miRNA candidates were identified through bioinformatics approach. Forty-nine known miRNAs （belonging to 24 families）, 15 new miRNAs and new miRNA candidates （belonging to 11 families） and 3 tasiRNA families were induced by JA, whereas 1 new miRNA, 1 tasiRNA family and 22 known miRNAs （belonging to 9 families） were repressed by JA.

Genome-wide analysis of Nilaparvata lugens nymphal responses to high-density and low-quality rice hosts

The brown planthopper （BPH） Nilaparvata lugens is an economically impor- tant pest on rice plants. In this study, the higher population density and yellow-ripe stage of rice plants were used to construct adverse survival conditions （ASC） against BPH nymphs. Simultaneously, the low population density and tillering stage of rice plants were used to establish a suitable survival condition （SSC） as a control. Solexa/Illumina sequencing was used to identify genes of BPH nymphs responding to ASC. Significantly longer duration development of BPH nymphs and significantly lower brachypterous ratio of BPH adults were observed by ASC compared with SSC. A total of 2 544 differentially expressed genes （DEGs） were obtained and analyzed by BLASTx, Gene Ontology and KEGG Orthology. Gene ontology analysis revealed that the DEGs were mainly involved in categories of cell, cell part, cellular process, binding, catalytic, organelle and metabolic processes. 1138 DEGs having enzyme commission numbers were assigned to different metabolic pathways. The largest clusters were neurodegenerative diseases （137, 12.0%）, followed by carbohy- drate metabolism （113, 9.9%）, amino acid metabolism （94, 8.3%）, nucleotide metabolism （76, 6.7%）, energy metabolism （64, 5.6%）, translation （60, 5.3%）, lipid metabolism （58, 5.1%）, and folding, sorting and degradation （52, 4.6%）. Expressing profile of 11 DEGs during eight nymphal developmental stages of BPH were analyzed by quantitative real- time polymerase chain reaction. The 11 genes exhibited differential expression between ASC and SSC during at least one developmental stage. The DEGs identified in this study provide molecular proof of how BPH reconfigures its gene expression profile to adapt to overcrowding and low-quality hosts.