Circulating microRNAs as biomarkers for detection of autologous blood transfusion.

MicroRNAs (miRNAs) are small non-coding RNAs that regulate various biological processes. Cell-free miRNAs measured in blood plasma have emerged as specific and sensitive markers of physiological processes and disease. In this study, we investigated whether circulating miRNAs can serve as biomarkers for the detection of autologous blood transfusion, a major doping technique that is still undetectable. Plasma miRNA levels were analyzed using high-throughput quantitative real-time PCR. Plasma samples were obtained before and at several time points after autologous blood transfusion (blood bag storage time 42 days) in 10 healthy subjects and 10 controls without transfusion. Other serum markers of erythropoiesis were determined in the same samples. Our results revealed a distinct change in the pattern of circulating miRNAs. Ten miRNAs were upregulated in transfusion samples compared with control samples. Among these, miR-30b, miR-30c, and miR-26b increased significantly and showed a 3.9-, 4.0-, and 3.0-fold change, respectively. The origin of these miRNAs was related to pulmonary and liver tissues. Erythropoietin (EPO) concentration decreased after blood reinfusion. A combination of miRNAs and EPO measurement in a mathematical model enhanced the efficiency of autologous transfusion detection through miRNA analysis. Therefore, our results lay the foundation for the development of miRNAs as novel blood-based biomarkers to detect autologous transfusion.

Loss-of-Function Mutations in PTPN11 Cause Metachondromatosis, but Not Ollier Disease or Maffucci Syndrome.

Metachondromatosis (MC) is a rare, autosomal dominant, incompletely penetrant combined exostosis and enchondromatosis tumor syndrome. MC is clinically distinct from other multiple exostosis or multiple enchondromatosis syndromes and is unlinked to EXT1 and EXT2, the genes responsible for autosomal dominant multiple osteochondromas (MO). To identify a gene for MC, we performed linkage analysis with high-density SNP arrays in a single family, used a targeted array to capture exons and promoter sequences from the linked interval in 16 participants from 11 MC families, and sequenced the captured DNA using high-throughput parallel sequencing technologies. DNA capture and parallel sequencing identified heterozygous putative loss-of-function mutations in PTPN11 in 4 of the 11 families. Sanger sequence analysis of PTPN11 coding regions in a total of 17 MC families identified mutations in 10 of them (5 frameshift, 2 nonsense, and 3 splice-site mutations). Copy number analysis of sequencing reads from a second targeted capture that included the entire PTPN11 gene identified an additional family with a 15 kb deletion spanning exon 7 of PTPN11. Microdissected MC lesions from two patients with PTPN11 mutations demonstrated loss-of-heterozygosity for the wild-type allele. We next sequenced PTPN11 in DNA samples from 54 patients with the multiple enchondromatosis disorders Ollier disease or Maffucci syndrome, but found no coding sequence PTPN11 mutations. We conclude that heterozygous loss-of-function mutations in PTPN11 are a frequent cause of MC, that lesions in patients with MC appear to arise following a "second hit," that MC may be locus heterogeneous since 1 familial and 5 sporadically occurring cases lacked obvious disease-causing PTPN11 mutations, and that PTPN11 mutations are not a common cause of Ollier disease or Maffucci syndrome.

Genetics of essential tremor.

Essential tremor (ET) is a prevalent condition manifesting with progressive action tremor. Although ET was traditionally viewed as a sporadic disease, a significant proportion of cases report a positive family history of tremor. Autosomal dominant inheritance can be demonstrated in many families. Previously, genome-wide linkage studies in families mapped three loci for ET, hereditary essential tremor-1 (ETM1), ETM2 and ETM3. However, no causal mutation has been replicated in candidate genes within these loci, including dopamine D3 receptor (DRD3) and HS1-binding protein 3 (HS1BP3). Recently, the first genome-wide association study in ET followed by replication studies conducted in diverse populations identified a significant association between the leucine-rich repeat and Ig domain containing 1 gene (LINGO1) SNP rs9652490 and risk for ET Although further novel variants were indentified in LINGO1 and its paralog LINGO2 that may be associated with risk for ET, the pathogenic mechanisms involved remain elusive. Given the possibility that ET as a complex trait may be influenced by the combined effects of rare variants, novel high-throughput technologies sequencing all exons across the genome (exome sequencing) or the whole genome (genome sequencing) may become crucial in understanding/deciphering the genetic background of ET.

Probing the T-cell receptor repertoire with deep sequencing.

PURPOSE OF REVIEW: To review major findings on the T-cell receptor (TCR) repertoire diversity in response to several viral infections based on conventional methods of PCR, cloning and sequencing and to discuss their limitations in light of the recent methodological advances in deep sequencing.¦RECENT FINDINGS: Direct sequencing of TCR expressed by Ag-specific T cells isolated ex vivo has revealed that the TCR repertoire is not as restricted as previously estimated. Furthermore, analyses performed independently of the T-cell clonal hierarchy have brought to light an unexpected diversity. The choice of methods is critical to characterize the complexity of the repertoire. Recent advances in deep sequencing have uncovered the diversity of the TCR repertoire and shown that the size of the repertoire in naive and Ag-experienced memory T cells is three-fold to 15-fold larger than formerly estimated. Interestingly, the TCR complementary determining region 3 sequences are not randomly selected and a certain degree of shared TCR repertoire has been observed between different individuals.¦SUMMARY: Deep sequencing is a major methodological advance allowing more accurate molecular characterization of the TCR repertoire. In the near future, such technologies will further contribute to delineate the complexity of pathogen-specific T-cell response and help defining correlates of a protective immunity.

Use of flow cytometric methods for single-cell analysis in environmental microbiology

Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

Genes mirror geography within Europe.

Understanding the genetic structure of human populations is of fundamental interest to medical, forensic and anthropological sciences. Advances in high-throughput genotyping technology have markedly improved our understanding of global patterns of human genetic variation and suggest the potential to use large samples to uncover variation among closely spaced populations. Here we characterize genetic variation in a sample of 3,000 European individuals genotyped at over half a million variable DNA sites in the human genome. Despite low average levels of genetic differentiation among Europeans, we find a close correspondence between genetic and geographic distances; indeed, a geographical map of Europe arises naturally as an efficient two-dimensional summary of genetic variation in Europeans. The results emphasize that when mapping the genetic basis of a disease phenotype, spurious associations can arise if genetic structure is not properly accounted for. In addition, the results are relevant to the prospects of genetic ancestry testing; an individual's DNA can be used to infer their geographic origin with surprising accuracy-often to within a few hundred kilometres.

Database construction and Peptide identification strategies for proteogenomic studies on sequenced genomes.

Since the advent of high-throughput DNA sequencing technologies, the ever-increasing rate at which genomes have been published has generated new challenges notably at the level of genome annotation. Even if gene predictors and annotation softwares are more and more efficient, the ultimate validation is still in the observation of predicted gene product( s). Mass-spectrometry based proteomics provides the necessary high throughput technology to show evidences of protein presence and, from the identified sequences, confirmation or invalidation of predicted annotations. We review here different strategies used to perform a MS-based proteogenomics experiment with a bottom-up approach. We start from the strengths and weaknesses of the different database construction strategies, based on different genomic information (whole genome, ORF, cDNA, EST or RNA-Seq data), which are then used for matching mass spectra to peptides and proteins. We also review the important points to be considered for a correct statistical assessment of the peptide identifications. Finally, we provide references for tools used to map and visualize the peptide identifications back to the original genomic information.

Mycorrhizal ecology and evolution: the past, the present, and the future.

1406 I. 1407 II. 1408 III. 1410 IV. 1411 V. 1413 VI. 1416 VII. 1418 1418 References 1419 SUMMARY: Almost all land plants form symbiotic associations with mycorrhizal fungi. These below-ground fungi play a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Up to 80% of plant N and P is provided by mycorrhizal fungi and many plant species depend on these symbionts for growth and survival. Estimates suggest that there are c. 50 000 fungal species that form mycorrhizal associations with c. 250 000 plant species. The development of high-throughput molecular tools has helped us to better understand the biology, evolution, and biodiversity of mycorrhizal associations. Nuclear genome assemblies and gene annotations of 33 mycorrhizal fungal species are now available providing fascinating opportunities to deepen our understanding of the mycorrhizal lifestyle, the metabolic capabilities of these plant symbionts, the molecular dialogue between symbionts, and evolutionary adaptations across a range of mycorrhizal associations. Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities. At the ecological level, network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks. Our analysis suggests that nestedness, modularity and specificity of mycorrhizal networks vary and depend on mycorrhizal type. Mechanistic models explaining partner choice, resource exchange, and coevolution in mycorrhizal associations have been developed and are being tested. This review ends with major frontiers for further research.

The case for resequencing studies of Arabidopsis thaliana accessions: mining the dark matter of natural genetic variation.

Ultra-high-throughput sequencing (UHTS) techniques are evolving rapidly and may soon become an affordable and routine tool for sequencing plant DNA, even in smaller plant biology labs. Here we review recent insights into intraspecific genome variation gained from UHTS, which offers a glimpse of the rather unexpected levels of structural variability among Arabidopsis thaliana accessions. The challenges that will need to be addressed to efficiently assemble and exploit this information are also discussed.

Role of NINJA in root jasmonate signaling.

Wound responses in plants have to be coordinated between organs so that locally reduced growth in a wounded tissue is balanced by appropriate growth elsewhere in the body. We used a JASMONATE ZIM DOMAIN 10 (JAZ10) reporter to screen for mutants affected in the organ-specific activation of jasmonate (JA) signaling in Arabidopsis thaliana seedlings. Wounding one cotyledon activated the reporter in both aerial and root tissues, and this was either disrupted or restricted to certain organs in mutant alleles of core components of the JA pathway including COI1, OPR3, and JAR1. In contrast, three other mutants showed constitutive activation of the reporter in the roots and hypocotyls of unwounded seedlings. All three lines harbored mutations in Novel Interactor of JAZ (NINJA), which encodes part of a repressor complex that negatively regulates JA signaling. These ninja mutants displayed shorter roots mimicking JA-mediated growth inhibition, and this was due to reduced cell elongation. Remarkably, this phenotype and the constitutive JAZ10 expression were still observed in backgrounds lacking the ability to synthesize JA or the key transcriptional activator MYC2. Therefore, JA-like responses can be recapitulated in specific tissues without changing a plant's ability to make or perceive JA, and MYC2 either has no role or is not the only derepressed transcription factor in ninja mutants. Our results show that the role of NINJA in the root is to repress JA signaling and allow normal cell elongation. Furthermore, the regulation of the JA pathway differs between roots and aerial tissues at all levels, from JA biosynthesis to transcriptional activation.

Evolutionary dynamics of coding and non-coding transcriptomes.

Gene expression changes may underlie much of phenotypic evolution. The development of high-throughput RNA sequencing protocols has opened the door to unprecedented large-scale and cross-species transcriptome comparisons by allowing accurate and sensitive assessments of transcript sequences and expression levels. Here, we review the initial wave of the new generation of comparative transcriptomic studies in mammals and vertebrate outgroup species in the context of earlier work. Together with various large-scale genomic and epigenomic data, these studies have unveiled commonalities and differences in the dynamics of gene expression evolution for various types of coding and non-coding genes across mammalian lineages, organs, developmental stages, chromosomes and sexes. They have also provided intriguing new clues to the regulatory basis and phenotypic implications of evolutionary gene expression changes.

Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data.

MOTIVATION: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts. Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent-daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays.

A comparison of methods for differential expression analysis of RNA-seq data.

BACKGROUND: Finding genes that are differentially expressed between conditions is an integral part of understanding the molecular basis of phenotypic variation. In the past decades, DNA microarrays have been used extensively to quantify the abundance of mRNA corresponding to different genes, and more recently high-throughput sequencing of cDNA (RNA-seq) has emerged as a powerful competitor. As the cost of sequencing decreases, it is conceivable that the use of RNA-seq for differential expression analysis will increase rapidly. To exploit the possibilities and address the challenges posed by this relatively new type of data, a number of software packages have been developed especially for differential expression analysis of RNA-seq data. RESULTS: We conducted an extensive comparison of eleven methods for differential expression analysis of RNA-seq data. All methods are freely available within the R framework and take as input a matrix of counts, i.e. the number of reads mapping to each genomic feature of interest in each of a number of samples. We evaluate the methods based on both simulated data and real RNA-seq data. CONCLUSIONS: Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. For larger sample sizes, the methods combining a variance-stabilizing transformation with the 'limma' method for differential expression analysis perform well under many different conditions, as does the nonparametric SAMseq method.

Native homing endonucleases can target conserved genes in humans and in animal models.

In recent years, both homing endonucleases (HEases) and zinc-finger nucleases (ZFNs) have been engineered and selected for the targeting of desired human loci for gene therapy. However, enzyme engineering is lengthy and expensive and the off-target effect of the manufactured endonucleases is difficult to predict. Moreover, enzymes selected to cleave a human DNA locus may not cleave the homologous locus in the genome of animal models because of sequence divergence, thus hampering attempts to assess the in vivo efficacy and safety of any engineered enzyme prior to its application in human trials. Here, we show that naturally occurring HEases can be found, that cleave desirable human targets. Some of these enzymes are also shown to cleave the homologous sequence in the genome of animal models. In addition, the distribution of off-target effects may be more predictable for native HEases. Based on our experimental observations, we present the HomeBase algorithm, database and web server that allow a high-throughput computational search and assignment of HEases for the targeting of specific loci in the human and other genomes. We validate experimentally the predicted target specificity of candidate fungal, bacterial and archaeal HEases using cell free, yeast and archaeal assays.

State of genomics and epigenomics research in the perspective of HIV cure.

PURPOSE OF REVIEW: One of the seven key scientific priorities identified in the road map on HIV cure research is to 'determine the host mechanisms that control HIV replication in the absence of therapy'. This review summarizes the recent work in genomics and in epigenetic control of viral replication that is relevant for this mission. RECENT FINDINGS: New technologies allow the joint analysis of host and viral transcripts. They identify the patterns of antisense transcription of the viral genome and its role in gene regulation. High-throughput studies facilitate the assessment of integration at the genome scale. Integration site, orientation and host genomic context modulate the transcription and should also be assessed at the level of single cells. The various models of latency in primary cells can be followed using dynamic study designs to acquire transcriptome and proteome data of the process of entry, maintenance and reactivation of latency. Dynamic studies can be applied to the study of transcription factors and chromatin modifications in latency and upon reactivation. SUMMARY: The convergence of primary cell models of latency, new high-throughput quantitative technologies applied to the study of time series and the identification of compounds that reactivate viral transcription bring unprecedented precision to the study of viral latency.