Recent transcriptome studies have revealed that a large number of transcripts in mammals and other organisms do not encode proteins but function as noncoding RNAs (ncRNAs) instead. As millions of transcripts are generated by large-scale cDNA and EST sequencing projects every year, there is a need for automatic methods to distinguish protein-coding RNAs from noncoding RNAs accurately and quickly. We developed a support vector machine-based classifier, named Coding Potential Calculator (CPC), to assess the protein-coding potential of a transcript based on six biologically meaningful sequence features. Tenfold cross-validation on the training dataset and further testing on several large datasets showed that CPC can discriminate coding from noncoding transcripts with high accuracy. Furthermore, CPC also runs an order-of-magnitude faster than a previous state-of-the-art tool and has higher accuracy. We developed a user-friendly web-based interface of CPC at http://cpc.cbi.pku.edu.cn. In addition to predicting the coding potential of the input transcripts, the CPC web server also graphically displays detailed sequence features and additional annotations of the transcript that may facilitate users’ further investigation.

Interleukin 17 (IL-17)-producing T helper cells (T(H)-17 cells) are increasingly recognized as key participants in various autoimmune diseases, including multiple sclerosis. Although sets of transcription factors and cytokines are known to regulate T(H)-17 differentiation, the role of noncoding RNA is poorly understood. Here we identify a T(H)-17 cell-associated microRNA, miR-326, whose expression was highly correlated with disease severity in patients with multiple sclerosis and mice with experimental autoimmune encephalomyelitis (EAE). In vivo silencing of miR-326 resulted in fewer T(H)-17 cells and mild EAE, and its overexpression led to more T(H)-17 cells and severe EAE. We also found that miR-326 promoted T(H)-17 differentiation by targeting Ets-1, a negative regulator of T(H)-17 differentiation. Our data show a critical role for microRNA in T(H)-17 differentiation and the pathogenesis of multiple sclerosis.

Novel silica-coated terbium(III) chelate fluorescent nanoparticles have been prepared and characterized as a new type of fluorescence probe for highly sensitive time-resolved fluorescence bioassay. The preparation was carried out in a water-in-oil microemulsion containing a strongly fluorescent Tb(3+) chelate, N,N,N(1),N(1)-[2,6-bis(3'-aminomethyl-1'-pyrazolyl)-phenylpyridine]tetrakis(acetate)-Tb(3+), Triton X-100, hexanol, and cyclohexane by controlling hydrolysis of tetraethyl orthosilicate. The nanoparticles are spherical and uniform in size, 42 +/- 3 nm in diameter, strongly fluorescent, and highly photostable and have enough of a long fluorescence lifetime (1.52 ms) for time-resolved fluorescence measurement. A stable and nontoxic method was developed for the surface modification and protein immobilization of the nanoparticles. As a model of application, the nanoparticle-labeled streptavidin was prepared and used in a sandwich-type time-resolved fluoroimmunoassay of human prostate-specific antigen (PSA) by using a 96-well microtiter plate as the solid-phase carrier. The method gives a detection limit of 7.0 pg/mL for the PSA assay.

Understanding of the RNA editing process has been broadened considerably by the next generation sequencing technology; however, several issues regarding this regulatory step remain unresolved – the strategies to accurately delineate the editome, the mechanism by which its profile is maintained, and its evolutionary and functional relevance. Here we report an accurate and quantitative profile of the RNA editome for rhesus macaque, a close relative of human. By combining genome and transcriptome sequencing of multiple tissues from the same animal, we identified 31,250 editing sites, of which 99.8% are A-to-G transitions. We verified 96.6% of editing sites in coding regions and 97.5% of randomly selected sites in non-coding regions, as well as the corresponding levels of editing by multiple independent means, demonstrating the feasibility of our experimental paradigm. Several lines of evidence supported the notion that the adenosine deamination is associated with the macaque editome – A-to-G editing sites were flanked by sequences with the attributes of ADAR substrates, and both the sequence context and the expression profile of ADARs are relevant factors in determining the quantitative variance of RNA editing across different sites and tissue types. In support of the functional relevance of some of these editing sites, substitution valley of decreased divergence was detected around the editing site, suggesting the evolutionary constraint in maintaining some of these editing substrates with their double-stranded structure. These findings thus complement the “continuous probing” model that postulates tinkering-based origination of a small proportion of functional editing sites. In conclusion, the macaque editome reported here highlights RNA editing as a widespread functional regulation in primate evolution, and provides an informative framework for further understanding RNA editing in human.

A unique ruthenium(II) complex, bis(2,2'-bipyridine)(4-(3,4-diaminophenoxy)-2,2'-bipyridine)ruthenium(II) hexafluorophosphate ([(Ru(bpy)(2)(dabpy)][PF(6)](2)), has been designed and synthesized as a highly sensitive and selective luminescence probe for the imaging of nitric oxide (NO) production in living cells. The complex can specifically react with NO in aqueous buffers under aerobic conditions to yield its triazole derivative with a high reaction rate constant at the 10(10) M(-1) s(-1) level; this reaction is accompanied by a remarkable increase of the luminescence quantum yield from 0.13 to 2.2 %. Compared with organic probes, the new Ru(II) complex probe shows the advantages of a large Stokes shift (>150 nm), water solubility, and a wide pH-availability range (pH independent at pH>5). In addition, it was found that the new probe could be easily transferred into both living animal cells and plant cells by the coincubation method, whereas the triazole derivative was cell-membrane impermeable. The probe was successfully used for luminescence-imaging detection of the exogenous NO in mouse macrophage cells and endogenous NO in gardenia cells. The results demonstrated the efficacy and advantages of the new probe for NO detection in living cells.

BackgroundDifferential coexpression analysis (DCEA) is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance.ResultsWe developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links). Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D) expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis.ConclusionsThis work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.

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