抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

http://bartellab.wi.mit.edu/publication_reprints/Bartel_Cell09.pdf

MicroRNAs: Target Recognition and Regulatory Functions

Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.

MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets

Exosomes are vesicles of endocytic origin released by many cells. These vesicles can mediate communication between cells, facilitating processes such as antigen presentation. Here, we show that exosomes from a mouse and a human mast cell line (MC/9 and HMC-1, respectively), as well as primary bone marrow-derived mouse mast cells, contain RNA. Microarray assessments revealed the presence of mRNA from approximately 1300 genes, many of which are not present in the cytoplasm of the donor cell. In vitro translation proved that the exosome mRNAs were functional. Quality control RNA analysis of total RNA derived from exosomes also revealed presence of small RNAs, including microRNAs. The RNA from mast cell exosomes is transferable to other mouse and human mast cells. After transfer of mouse exosomal RNA to human mast cells, new mouse proteins were found in the recipient cells, indicating that transferred exosomal mRNA can be translated after entering another cell. In summary, we show that exosomes contain both mRNA and microRNA, which can be delivered to another cell, and can be functional in this new location. We propose that this RNA is called "exosomal shuttle RNA" (esRNA).

/pdf/exosome-mediated-transfer-of-mrnas-and-micrornas-is-a-novel-9o52kfcb0e.pdf

Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells

Changes in the patterns of gene expression are widely believed to underlie many of the phenotypic differences within and between species. Although much emphasis has been placed on changes in transcriptional regulation, gene expression is regulated at many levels, all of which must ultimately be studied together to obtain a complete picture of the evolution of gene expression. Here we compare the evolution of transcriptional regulation and post-transcriptional regulation that is mediated by microRNAs, a large class of small, non-coding RNAs in plants and animals, focusing on the evolution of the individual regulators and their binding sites. As an initial step towards integrating these mechanisms into a unified framework, we propose a simple model that describes the transcriptional regulation of new microRNA genes.

http://materiais.dbio.uevora.pt/BD/Crescimento/TFs-miRNAs.pdf

The evolution of gene regulation by transcription factors and microRNAs

Recently, several laboratories have reported thousands of circular RNAs (circRNAs) in animals. Numerous circRNAs are highly stable and have specific spatiotemporal expression patterns. Even though a function for circRNAs is unknown, these features make circRNAs an interesting class of RNAs as possible biomarkers and for further research. We developed a database and website, "circBase," where merged and unified data sets of circRNAs and the evidence supporting their expression can be accessed, downloaded, and browsed within the genomic context. circBase also provides scripts to identify known and novel circRNAs in sequencing data. The database is freely accessible through the web server at http://www.circbase.org/.

/pdf/circbase-a-database-for-circular-rnas-lpir0sh2cu.pdf

circBase: a database for circular RNAs

Translation of CircRNAs

The capacity of highly parallel sequencing technologies to detect small RNAs at unprecedented depth suggests their value in systematically identifying microRNAs (miRNAs). However, the identification of miRNAs from the large pool of sequenced transcripts from a single deep sequencing run remains a major challenge. Here, we present an algorithm, miRDeep, which uses a probabilistic model of miRNA biogenesis to score compatibility of the position and frequency of sequenced RNA with the secondary structure of the miRNA precursor. We demonstrate its accuracy and robustness using published Caenorhabditis elegans data and data we generated by deep sequencing human and dog RNAs. miRDeep reports altogether approximately 230 previously unannotated miRNAs, of which four novel C. elegans miRNAs are validated by northern blot analysis.

/pdf/discovering-micrornas-from-deep-sequencing-data-using-2mmotsjzva.pdf

Discovering microRNAs from deep sequencing data using miRDeep

In recent years, microRNAs (miRNAs) have emerged as a major class of regulatory genes, present in most metazoans and important for a diverse range of biological functions. Because experimental identification of miRNA targets is difficult, there has been an explosion of computational target predictions. Although the initial round of predictions resulted in very diverse results, subsequent computational and experimental analyses suggested that at least a certain class of conserved miRNA targets can be confidently predicted and that this class of targets is large, covering, for example, at least 30% of all human genes when considering about 60 conserved vertebrate miRNA gene families. Most recent approaches have also shown that there are correlations between domains of miRNA expression and mRNA levels of their targets. Our understanding of miRNA function is still extremely limited, but it may be that by integrating mRNA and miRNA sequence and expression data with other comparative genomic data, we will be able to gain global and yet specific insights into the function and evolution of a broad layer of post-transcriptional control.

Nikolaus Rajewsky

Papers

The evolution of gene regulation by transcription factors and microRNAs

circBase: a database for circular RNAs

Translation of CircRNAs

Discovering microRNAs from deep sequencing data using miRDeep

microRNA target predictions in animals.