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Direct cloning of PCR fragments by TA cloning or blunt end ligation are two simple methods which would greatly benefit high-throughput (HTP) cloning constructions if the efficiency can be improved. In this study, we have developed a ribosomal binding site (RBS) switching strategy for direct cloning of PCR fragments. RBS is an A/G rich region upstream of the translational start codon and is essential for gene expression. Change from A/G to T/C in the RBS blocks its activity and thereby abolishes gene expression. Based on this property, we introduced an inactive RBS upstream of a selectable marker gene, and designed a fragment insertion site within this inactive RBS. Forward and reverse insertions of specifically tailed fragments will respectively form an active and inactive RBS, thus all background from vector self-ligation and fragment reverse insertions will be eliminated due to the non-expression of the marker gene. The effectiveness of our strategy for TA cloning and blunt end ligation are confirmed. Application of this strategy to gene over-expression, a bacterial two-hybrid system, a bacterial one-hybrid system, and promoter bank construction are also verified. The advantages of this simple procedure, together with its low cost and high efficiency, makes our strategy extremely useful in HTP cloning constructions.

Two-dimensional angular correlation distributions have been measured for the first time for positron and positronium annihilation in low-density helium, neon, argon, krypton and xenon, and in a range of helium-xenon mixtures. The full widths of the (cylindrically averaged) free positron components are in reasonable agreement with theoretical values. The intensity of the mixed-state positronium (Ps) component (mean vacuum lifetime 9.7 ns in a magnetic field of 0.8 T) in helium is consistent with the Ps fraction previously determined in lifetime measurements; the widths of the Ps component in helium, neon and argon are consistent with a Ps-atom scattering cross section below 6.8 eV in all three gases of approximately (9-0.5 E) pi a02, where E is the Ps energy in eV.

Background: Much effort has been expended in exploring the connections between transcriptome, disease and drug, based on the premise that drug induced perturbations in the transcriptome will affect the phenotype and finally help to cure a disease. MicroRNAs (miRNAs) play a key role in the regulation of the transcriptome and have been identified as a key mediator in human disease and drug response. However, even if miRNA expression can be precisely detected, the information regarding miRNAs action on a particular part of the transcriptome is still lacking. Here, we introduced a novel concept, the Context-specific MiRNA activity (CoMi activity), to reflect a miRNA's regulation effect on a context specific gene set, by calculating the statistical difference between the distributions of its target gene expression and non-target gene expression. In this study we investigate whether CoMi activity could provide a novel perspective on miRNA mechanisms of action in disease and drug response, and facilitate in silico drug screening.

MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context).

Crimean-Congo hemorrhagic fever (CCHF) is a severe illness with high fatality. Cases are reported in several countries in Africa, Europe, the Middle East, and Asia. Phylogenetic analyses based on the virus S (nucleocapsid), M (glycoprotein), and L (polymerase) genome segments sequences indicate distinct geographic lineages exist but their specific genetic characteristics require elucidation. In this work we collected all full length S segment sequences and generated a phylogenetic tree based on the alignment of these 62 samples. We then analyzed the alignment using entries from AAIndex, the Amino Acid Index database, to identify amino acid mutations that performed significant changes in charge, pka, hydropathy and side chain volume. Finally, we mapped these changes back to the tree and alignment to identify correlated mutations or sites that characterized a specific lineage. Based on this analysis we are able to propose a number of sites that appear to be important for virus function and which would be good candidates for experimental mutational analysis studies.

Japanese encephalitis virus (JEV), a mosquito-borne zoonotic pathogen, is one of the major causes of viral encephalitis worldwide. Previous phylogenetic studies based on the envelope protein indicated that there are four genotypes, and surveillance data suggest that genotype I is gradually replacing genotype III as the dominant strain. Here we report an evolutionary analysis based on 98 full-length genome sequences of JEV, including 67 new samples isolated from humans, pigs, mosquitoes, midges. and bats in affected areas. To investigate the relationships between the genotypes and the significance of genotype I in recent epidemics, we estimated evolutionary rates, ages of common ancestors, and population demographics. Our results indicate that the genotypes diverged in the order IV, III, II, and I and that the genetic diversity of genotype III has decreased rapidly while that of genotype I has increased gradually, consistent with its emergence as the dominant genotype.

It is well established that different sites within a protein evolve at different rates according to their role within the protein; identification of these correlated mutations can aid in tasks such as ab initio protein structure, structure function analysis or sequence alignment. Mutual Information is a standard measure for coevolution between two sites but its application is limited by signal to noise ratio. In this work we report a preliminary study to investigate whether larger sequence sets could circumvent this problem by calculating mutual information arrays for two sets of drug naive sequences from the HIV gp120 protein for the B and C subtypes. Our results suggest that while the larger sequences sets can improve the signal to noise ratio, the gain is offset by the high mutation rate of the HIV virus which makes it more difficult to achieve consistent alignments. Nevertheless, we were able to predict a number of coevolving sites that were supported by previous experimental studies as well as a region close to the C terminal of the protein that was highly variable in the C subtype but highly conserved in the B subtype.

miRPara, is a new software tool that predicts mature miRNA in a species specific manner based on three SVM trained models from a comprehensive set of different parameters related to the physical properties of the pre-miRNA and its miRNAs. It achieves an accuracy of up to 80% for animal and virus sequences against experimentally verified mature miRNAs predicted from long genome sequences, making it one of the most accurate methods available. Because of the greater diversity of the plant miRNAs, only 70% accuracy was achieved, but this was nevertheless more accurate than results obtained with other prediction software.

The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call ‘synergistic outcome determination’ (SOD), a concept similar to ‘Synthetic Lethality’. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies.

In recent years, the in silico epitopes prediction tools have facilitated the progress of vaccines development significantly and many have been applied to predict epitopes in viruses successfully. Herein, a general overview of different tools currently available, including T cell and B cell epitopes prediction tools, is presented. And the principles of different prediction algorithms are reviewed briefly. Finally, several examples are present to illustrate the application of the prediction tools.

Cupriavidus necator JMP134 utilizes meta-nitrophenol (MNP) as a sole source of carbon, nitrogen, and energy. The metabolic reconstruction of MNP degradation performed in silico suggested that the mnp cluster might have played important roles in MNP degradation. In order to experimentally confirm the prediction, we have now characterized mnpA-encoded meta-nitrophenol nitroreductase involved in the initial reaction of MNP degradation. Real-time PCR analysis indicated that mnpA played an essential role in MNP degradation. MnpA was purified to homogeneity as His-tagged proteins and was considered to be a dimer as determined by gel filtration. MnpA was an MNP nitroreductase with a tightly bound flavin mononucleotide (FMN), catalyzing the partial reduction of MNP to meta-hydroxylaminophenol via meta-nitrosophenol in the presence of NADPH and oxygen. The accumulation of meta-nitrosophenol was confirmed with the results of liquid chromatography-diode array detection and time-of-flight mass spectrometry for the first time. The low K (m) and high k (cat) of MnpA as well as MNP-inducible transcription of mnpA suggested that MNP was the physiological substrate for this nitroreductase. In addition, the phylogenetic analysis revealed that nitroreductases of known physiological function including MnpA constituted a new clade in the nitro-FMN-reductase superfamily.

The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call ‘synergistic outcome determination’ (SOD), a concept similar to ‘Synthetic Lethality’. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies.

Background Plant infection models provide certain advantages over animal models in the study of pathogenesis. However, current plant models face some limitations, e.g., plant and pathogen cannot co-culture in a contained environment. Development of such a plant model is needed to better illustrate host-pathogen interactions. Methodology/principal findings We describe a novel model plant system for the study of human pathogenic bacterial infection on a large scale. This system was initiated by co-cultivation of axenic duckweed (Lemna minor) plants with pathogenic bacteria in 24-well polystyrene cell culture plate. Pathogenesis of bacteria to duckweed was demonstrated with Pseudomonas aeruginosa and Staphylococcus aureus as two model pathogens. P. aeruginosa PAO1 caused severe detriment to duckweed as judged from inhibition to frond multiplication and chlorophyll formation. Using a GFP-marked PAO1 strain, we demonstrated that bacteria colonized on both fronds and roots and formed biofilms. Virulence of PAO1 to duckweed was attenuated in its quorum sensing (QS) mutants and in recombinant strains overexpressing the QS quenching enzymes. RN4220, a virulent strain of S. aureus, caused severe toxicity to duckweed while an avirulent strain showed little effect. Using this system for antimicrobial chemical selection, green tea polyphenols exhibited inhibitory activity against S. aureus virulence. This system was further confirmed to be effective as a pathogenesis model using a number of pathogenic bacterial species. Conclusions/significance Our results demonstrate that duckweed can be used as a fast, inexpensive and reproducible model plant system for the study of host-pathogen interactions, could serve as an alternative choice for the study of some virulence factors, and could also potentially be used in large-scale screening for the discovery of antimicrobial chemicals.

We have performed measurements on entwined single crystals of YBCO using both photoemission and positron angular correlation of annihilation radiation and on single crystals of LSCO using only angular correlation. Fermi surface features in good agreement with band theory were found and identified in all of the measurements. In photoemission the Fermi momentum was fixed for several points and the band dispersion below the Fermi energy was mapped. In positron angular correlation measurements the shape of the Fermi surface was mapped for the CuO chains (YBCO) and the CuO planes (LSCO). Demonstration of the existence of Fermi surfaces in the HTSC materials points a direction for future theoretical considerations.

To sequence and analyze the whole genome of Japanese encephalitis virus (JEV) strain named 47 which was isolated from patient's cerebrospinal fluid sample in Heilongjiang province in 1950.RNA was extracted from the recovery strain 47 and amplified with self-designed JEV genome sequencing primers. The differentiation analysis for nucleotides and coding amino acids and phylogenetic analysis were performed by the software of DNAStar, Modeltest, and Phylip.The whole genome of strain 47 has 10,977 nucleotides. An open reading frame from 95 to 10,391 including 10,296 nucleotides is capable of coding a 3432 amino acid polyprotein. The nucleotide difference between strain 47 and 5 vaccine strains is 2.4%-4.4%, the amino acid difference between strain 47 and 5 vaccine strains is 0.3%-1.1%. The best evolution model for the whole genome is GTR + I + G. Based on the phylogenetic analysis, strain 47 belongs to the genotype III JEV.Strain 47 is highly conserved on whole genome nucleotide and amino acid sequence. And it is belongs to the genotype III JEV.

Xinjiang, China is an endemic area for Kaposi’s sarcoma (KS) but the seroprevalence of Kaposi’s sarcoma-associated herpesvirus (KSHV) and risk factors remain undefined. In this study, antibodies to one KSHV latent protein (ORF73) and two KSHV lytic proteins (ORF65 and ORF-K8.1) were examined in 2,228 subjects from the general population and 37 subjects infected with HIV-1 in Xinjiang, and 560 subjects from the general population in Hubei, a low KS incidence region. The serostatus of a serum sample was defined based on positive results in any one of the three serologic assays. The seroprevalence of KSHV in the general population was higher in Xinjiang than in Hubei (19.2% vs 9.5%; odds ratios [OR], 2.28; 95% confidence interval [CI], 1.68–3.08; P < 0.001). Among the ethnic groups in Xinjiang, 68 (15.8%) Han, 182 (20.7%) Uygur, 140 (19.9%) Hazakh, 9 (33.3%) Xibo, and 29 (16.8%) Hui were KSHV-seropositive, respectively. Compared to the Han, the latter groups had an increase in the risk of KSHV of 62.2%, 63.8%, 180.1% and 30.2% (P = 0.003, 0.004, 0.018, and 0.286, respectively). Subjects aged < 20, 20–50, and > 50 had a seroprevalence of KSHV of 11.8%, 17.9% and 24.6%, respectively. Compared to subjects aged < 20, the latter groups had an increase in the risk of KSHV of 63.3% and 144.5% (P = 0.009 and < 0.001, respectively). Subjects infected with HIV-1 in Xinjiang had a seroprevalence of KSHV of 43.2%, and a 220% increase in the risk of KSHV compared to the general population (P < 0.001). Similar results were obtained when the seroprevalence of KSHV was analyzed with any single or two of the three serologic assays alone. Genotyping identified 3 unique sequences clustered in the A clade. This study indicates that Xinjiang has a high seroprevalence of KSHV. Geographic location, ethnicity, age and HIV-1 infection are risk factors. Serologic and genotyping results suggest the introduction of KSHV into Xinjiang by specific ethnic groups.

We have performed an ultra-high precision measurement (5 × 10 8 coincidence counts) of the basal-plane electron-positron momentum density (MD) in well oxygenated, twin-free, single crystals of YBa 2 Cu 3 O 7δ . The anisotropies of the raw and processed MD spectra and LCW-transformed spectra (k-space densities) not only show the D 2 symmetry appropriate to the untwinned crystals but, more importantly, unambiguously show a dear image of a major Fermi surface sheet. The form of the FS image is in substantial agreement with theoretical predictions of a Γ-X electron ridge section associated with states in the Cu-O chains.

Rapid advances in the fields of DNA vaccines and gene therapy have produced increased demands for large quantities of recombinant plasmid DNA. The protocol presented here extracts plasmid DNA in a scalable continuous process based on an alkaline lysis protocol. In the process, harvested bacteria are passed through two mixing chambers at controlled speeds to effect lysis and control alkalinity. The resulting solution is passed through a series of filters to remove contaminants and then ethanol precipitated. This process replaces all the centrifugation steps before obtaining crude plasmid and can be easily scaled up to meet demands for larger quantities. Using this procedure, plasmid can be extracted and purified from 4 l of Escherichia coli culture at an OD 600 nm of 50 in

The authors have measured the two-dimensional electron-positron momentum density (resolved momentum components along (100) and (010)) for single crystals of YBa2Cu3O7- delta at a significantly higher level of statistical precision for this orientation than that embraced in earlier published works. They have found in their data structures suggesting that the positron annihilates predominantly on oxygen sites in the copper-oxygen chains. These structures are also present in the results of a companion ligand field calculation and arise from spatial variations in the electron and positron wavefunction overlaps. Even at the present level of statistical precision, the authors are unable to argue for or against the existence of a Fermi surface.

The DHPC (DNA Hilbert–Peano curve) is a new tool for visualizing large-scale genome sequences by mapping sequences into a two-dimensional square. It utilizes the space-filling function of Hilbert–Peano mapping. By applying a Gauss smoothing technique and a user-defined color function, a large-scale genome sequence can be mapped into a two-dimensional color image. In the calculated DHPCs, many genome characteristics are revealed. In this article we introduce the method and show how DHPCs may be used to identify regions of different base composition. The power of the method is demonstrated by presenting multiple examples such as repeating sequences, degree of base bias, regions of homogeneity and their boundaries, and mark of annotated segments. We also present several genome curves generated by DHPC to demonstrate how DHPC can be used to find previously unidentified sequence features in these genomes.

With advances in the development of DNA vaccines and gene therapy, there is a growing need for plasmid DNA with high quality for fundamental research and clinical trials. In this report, a scalable automated process for large-scale preparation of plasmid is described. This process is based on alkaline lysis and can be easily scaled up to meet demands for larger quantities. In the process, harvested bacteria are passed through two mixing chambers at controlled speeds to affect lysis and control alkalinity. The resulting solution is passed through a series of filters to remove contaminants, and ethanol precipitated. System parameters are examined to maximize the quantity and quality of the prepared plasmid. Using this procedure, plasmid can be extracted and purified from 1 l of Escherichia coli cultures at an OD600 nm of 50 in less than 45 min. The plasmid yields are approximately 90 mg/l culture.

A machine that employs a novel reagent delivery technique for biomolecular synthesis has been developed. This machine separates the addressing of individual synthesis sites from the actual process of reagent delivery by using masks placed over the sites. Because of this separation, this machine is both cost-effective and scalable, and thus the time required to synthesize 384 or 1536 unique biomolecules is very nearly the same. Importantly, the mask design allows scaling of the number of synthesis sites without the addition of new valving. Physical and biological comparisons between DNA made on a commercially available synthesizer and this unit show that it produces DNA of similar quality.

We have developed a simple and efficient system (ORF-FINDER) for selecting open reading frames (ORFs) from randomly fragmented genomic DNA fragments. The ORF-FINDER vectors are plasmids that contain a translational start site out of frame with respect to the gene for green fluorescent protein (GFP). Insertion of DNA fragments that bring the initiating ATG in frame with GFP and that contain no stop codons (that is, ORFs) results in the expression of ORF-GFP fusion proteins. In addition, we have developed software (GeneWorks and GenomeAnalyzer) to predict the optimal insert size for maximizing the number of gene-coding ORFs and minimizing unintentionally selected non-coding ORFs. To demonstrate the feasibility of using the ORF-FINDER system to screen genomes for ORFs, we cloned yeast genomic DNA and succeeded in enriching for ORFs by 25-fold. Furthermore, we have shown that the vector can effectively isolate ORFs from the more complex genomes of eukaryotic parasites. We envision that ORF-FINDER will have several applications including genome sequencing projects, gene building from oligonucleotides and construction of expression libraries enriched for ORFs.

Background Rabies reemerged in China during the 1990s with a gradual increase in the number and geographical dispersion of cases. As a consequence, a national surveillance program was introduced in 2005 to investigate the outbreak in terms of vaccination coverage, PEP treatment, and geographical and social composition. Methods The surveillance program was coordinated at the national level by the Chinese Center for Disease Control (CCDC) with data collected by regional health centres and provincial CCDCs, and from other official sources. Various statistical and multivariate analysis techniques were then used to evaluate the role and significance of implemented policies and strategies related to rabies prevention and control over this period. Results From 2005–2012, 19,221 cases were reported across 30 provinces, but these primarily occurred in rural areas of southern and eastern China, and were predominantly associated with farmers, students and preschool children. In particular, detailed analysis of fatalities reported from 2010 to 2011 shows they were associated with very low rates of post exposure treatment compared to the cases with standard PEP. Nevertheless, regulation of post-exposure prophylaxis quality, together with improved management and vaccination of domesticated animals, has improved prevention and control of rabies. Conclusions The various control policies implemented by the government has played a key role in reducing rabies incidences in China. However, level of PEP treatment varies according to sex, age, degree and site of exposure, as well as the source of infection. Regulation of PEP quality together with improved management and vaccination of domesticated animals have also helped to improve prevention and control of rabies.

Background The family Tymoviridae comprises three plant virus genera, including Tymovirus, Marafivirus, and Maculavirus, which are found in most parts of the world and cause severe agricultural losses. We describe a putatively novel member of the family Tymoviridae, which is isolated from mosquitoes (Culex spp.), referred to as CuTLV. Methods and Results The CuTLV was isolated by cell culture, which replicates and causes cytopathic effects in Aedes albopictus C6/36 cells, but not in mammalian BHK-21 or Vero cells. The complete 6471 nucleotide sequence of CuTLV was determined. The genome of CuTLV is predicted to contain three open reading frames (ORFs). The largest ORF1 is 5307 nucleotides (nt) in length and encodes a putative polypeptide of 1769 amino acids (aa), which contains the conserved motifs for the methyltransferase (MTR), Tymovirus endopeptidase (PRO), helicase (HEL), and RNA-dependent RNA polymerase (RdRp) of the replication-associated proteins (RPs) of positive-stranded RNA viruses. In contrast, the ORF1 sequence does not contain the so-called “tymobox” or “marafibox”, the conserved subgenomic RNA promoter present in all tymoviruses or marafiviruses, respectively. ORF2 and ORF3 putatively encode a 248-aa coat protein (CP) and a proline-rich 149-aa polypeptide. The whole genomic nucleotide identity of CuTLV with other members of family Tymoviridae ranged from 46.2% (ChiYMV) to 52.4% (GFkV). Phylogenetic analysis based on the putative RP and CP genes of CuTLV demonstrated that the virus is most closely related to viruses in the genus Maculavirus. Conclusions The CuTLV is a novel virus related to members of the family Tymoviridae, with molecular characters that are distinct from those of tymoviruses, marafiviruses, and other maculaviruses or macula-like viruses. This is the first report of the isolation of a Tymoviridae-like virus from mosquitoes. Further investigations are required to clarify the origin, replication strategy, and the public health or agricultural importance of the CuTLV.

We report new measurements of the electron-positron momentum spectra of YBa2Cu3O7-x performed with ultra-high statistical precision. These data differ from previous results in two significant respects: They show the D2 symmetry appropriate for untwinned crystals and, more importantly, they show unmistakable, statistically significant, discontinuities that are evidence of a major Fermi surface section.

We report new, ultra high precision measurements of the electron-positron momentum spectra of YBa 2 Cu 3 O 7− x and La 1.874 Sr .126 CuO 4 . The YBCO experiments were performed on twin free, single crystals and show discontinuities with the symmetry of the Fermi surface of the CuO chain bands. Conduction band and underlying features in LSCO share the same symmetry and can only be separated with the aid of LDA calculations.

A series of angular correlation spectra for positrons annihilating in the noble gases and in gas mixtures has been obtained using the University of East Anglia two-dimensional angular correlation spectrometer.l Beta positrons from a sodium-22 source are guided by a O.8T magnetic field to the interaction region, which is first evacuated and then filled with gas at 1 bar pressure at room temperature. Gamma cameras placed at 3m on either side of the sample chamber record the two-photon annihilations of free positrons and positronium (Ps) atoms in a 9mm-diameter volume of gas at the centre of the cell. Events recorded include annihilation from the triplet (m = O) — singlet state, which at O.8T is 91% mixed and has a mean lifetime of 9.7ns. In contrast, a negligible number of two-photon decays are rec — orded from (triplet) o-Ps atoms quenched on the (distant) walls of the gas cell or through collisions with gas atoms within the viewed volume.

We discuss our measurements of the 2D-angular correlation of positron annihilation radiation (ACAR) in La 2 CuO 4 , YBa 2 Cu 3 O 7 (YBCO), and NiO. The measurements for NiO are the first such 2D-ACAR measurements; the YBCO results are of a higher statistical quality than previously reported in the literature. The data are compared with complementary theoretical calculations and with each other. We discuss the implication of our analysis for ACAR studies of similar and related systems.

Background MicroRNAs are a family of ~22 nt small RNAs that can regulate gene expression at the post-transcriptional level. Identification of these molecules and their targets can aid understanding of regulatory processes. Recently, HTS has become a common identification method but there are two major limitations associated with the technique. Firstly, the method has low efficiency, with typically less than 1 in 10,000 sequences representing miRNA reads and secondly the method preferentially targets highly expressed miRNAs. If sequences are available, computational methods can provide a screening step to investigate the value of an HTS study and aid interpretation of results. However, current methods can only predict miRNAs for short fragments and have usually been trained against small datasets which don't always reflect the diversity of these molecules. Results We have developed a software tool, miRPara, that predicts most probable mature miRNA coding regions from genome scale sequences in a species specific manner. We classified sequences from miRBase into animal, plant and overall categories and used a support vector machine to train three models based on an initial set of 77 parameters related to the physical properties of the pre-miRNA and its miRNAs. By applying parameter filtering we found a subset of ~25 parameters produced higher prediction ability compared to the full set. Our software achieves an accuracy of up to 80% against experimentally verified mature miRNAs, making it one of the most accurate methods available. Conclusions miRPara is an effective tool for locating miRNAs coding regions in genome sequences and can be used as a screening step prior to HTS experiments. It is available at http://www.whiov.ac.cn/bioinformatics/mirpara