Plastid genome characterisation in Brassica and Brassicaceae using a new set of nine SSRs.

We report a new set of nine primer pairs specifically developed for amplification of Brassica plastid SSR markers. The wide utility of these markers is demonstrated for haplotype identification and detection of polymorphism in B. napus, B. nigra, B. oleracea, B. rapa and in related genera Arabidopsis, Camelina, Raphanus and Sinapis. Eleven gene regions (ndhB-rps7 spacer, rbcL-accD spacer, rpl16 intron, rps16 intron, atpB-rbcL spacer, trnE-trnT spacer, trnL intron, trnL-trnF spacer, trnM-atpE spacer, trnR-rpoC2 spacer, ycf3-psaA spacer) were sequenced from a range of Brassica and related genera for SSR detection and primer design. Other sequences were obtained from GenBank/EMBL. Eight out of nine selected SSR loci showed polymorphism when amplified using the new primers and a combined analysis detected variation within and between Brassica species, with the number of alleles detected per locus ranging from 5 (loci MF-6, MF-1) to 11 (locus MF-7). The combined SSR data were used in a neighbour-joining analysis (SMM, D (DM) distances) to group the samples based on the presence and absence of alleles. The analysis was generally able to separate plastid types into taxon-specific groups. Multi-allelic haplotypes were plotted onto the neighbour joining tree. A total number of 28 haplotypes were detected and these differentiated 22 of the 41 accessions screened from all other accessions. None of these haplotypes was shared by more than one species and some were not characteristic of their predicted type. We interpret our results with respect to taxon differentiation, hybridisation and introgression patterns relating to the 'Triangle of U'.

Inferring epidemic contact structure from phylogenetic trees.

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.

Using transcription modules to identify expression clusters perturbed in Williams-Beuren syndrome.

The genetic dissection of the phenotypes associated with Williams-Beuren Syndrome (WBS) is advancing thanks to the study of individuals carrying typical or atypical structural rearrangements, as well as in vitro and animal studies. However, little is known about the global dysregulations caused by the WBS deletion. We profiled the transcriptomes of skin fibroblasts from WBS patients and compared them to matched controls. We identified 868 differentially expressed genes that were significantly enriched in extracellular matrix genes, major histocompatibility complex (MHC) genes, as well as genes in which the products localize to the postsynaptic membrane. We then used public expression datasets from human fibroblasts to establish transcription modules, sets of genes coexpressed in this cell type. We identified those sets in which the average gene expression was altered in WBS samples. Dysregulated modules are often interconnected and share multiple common genes, suggesting that intricate regulatory networks connected by a few central genes are disturbed in WBS. This modular approach increases the power to identify pathways dysregulated in WBS patients, thus providing a testable set of additional candidates for genes and their interactions that modulate the WBS phenotypes.

trome, trEST and trGEN: databases of predicted protein sequences.

We previously introduced two new protein databases (trEST and trGEN) of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Here, we present the updates made on these two databases plus a new database (trome), which uses alignments of EST data to HTG or full genomes to generate virtual transcripts and coding sequences. This new database is of higher quality and since it contains the information in a much denser format it is of much smaller size. These new databases are in a Swiss-Prot-like format and are updated on a weekly basis (trEST and trGEN) or every 3 months (trome). They can be downloaded by anonymous ftp from ftp://ftp.isrec.isb-sib.ch/pub/databases.

The Gene Ontology in 2010: extensions and refinements.

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.

EuroPhenome: a repository for high-throughput mouse phenotyping data.

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.

The Individualized Genetic Barrier Predicts Treatment Response in a Large Cohort of HIV-1 Infected Patients.

The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests.

Numerous potentially functional but non-genic conserved sequences on human chromosome 21.

The use of comparative genomics to infer genome function relies on the understanding of how different components of the genome change over evolutionary time. The aim of such comparative analysis is to identify conserved, functionally transcribed sequences such as protein-coding genes and non-coding RNA genes, and other functional sequences such as regulatory regions, as well as other genomic features. Here, we have compared the entire human chromosome 21 with syntenic regions of the mouse genome, and have identified a large number of conserved blocks of unknown function. Although previous studies have made similar observations, it is unknown whether these conserved sequences are genes or not. Here we present an extensive experimental and computational analysis of human chromosome 21 in an effort to assign function to sequences conserved between human chromosome 21 (ref. 8) and the syntenic mouse regions. Our data support the presence of a large number of potentially functional non-genic sequences, probably regulatory and structural. The integration of the properties of the conserved components of human chromosome 21 to the rapidly accumulating functional data for this chromosome will improve considerably our understanding of the role of sequence conservation in mammalian genomes.

Integrative analysis of the Regulatory Region of the FGFR3 Oncogene

The study of transcriptional regulation often needs the integration of diverse yet independent data. In the present work, sequence conservation, predic-tion of transcription factor binding sites (TFBS) and gene expression analysis have been applied to the detection of putative transcription factor (TF) modules in the regulatory region of the FGFR3 oncogene. Several TFs with conserved binding sites in the FGFR3 regulatory region have shown high positive or negative corre-lation with FGFR3 expression both in urothelial carcinoma and in benign nevi. By means of conserved TF cluster analysis, two different TF modules have been iden-tified in the promoter and first intron of FGFR3 gene. These modules contain acti-vating AP2, E2F, E47 and SP1 binding sites plus motifs for EGR with possible repressor function.

Improving a leaves automatic recognition process using PCA

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

A genomic island present along the bacterial chromosome of the Parachlamydiaceae UWE25, an obligate amoebal endosymbiont, encodes a potentially functional F-like conjugative DNA transfer system.

BACKGROUND: The genome of Protochlamydia amoebophila UWE25, a Parachlamydia-related endosymbiont of free-living amoebae, was recently published, providing the opportunity to search for genomic islands (GIs). RESULTS: On the residual cumulative G+C content curve, a G+C-rich 19-kb region was observed. This sequence is part of a 100-kb chromosome region, containing 100 highly co-oriented ORFs, flanked by two 17-bp direct repeats. Two identical gly-tRNA genes in tandem are present at the proximal end of this genetic element. Several mobility genes encoding transposases and bacteriophage-related proteins are located within this chromosome region. Thus, this region largely fulfills the criteria of GIs. The G+C content analysis shows that several modules compose this GI. Surprisingly, one of them encodes all genes essential for F-like conjugative DNA transfer (traF, traG, traH, traN, traU, traW, and trbC), involved in sex pilus retraction and mating pair stabilization, strongly suggesting that, similarly to the other F-like operons, the parachlamydial tra unit is devoted to DNA transfer. A close relatedness of this tra unit to F-like tra operons involved in conjugative transfer is confirmed by phylogenetic analyses performed on concatenated genes and gene order conservation. These analyses and that of gly-tRNA distribution in 140 GIs suggest a proteobacterial origin of the parachlamydial tra unit. CONCLUSIONS: A GI of the UWE25 chromosome encodes a potentially functional F-like DNA conjugative system. This is the first hint of a putative conjugative system in chlamydiae. Conjugation most probably occurs within free-living amoebae, that may contain hundreds of Parachlamydia bacteria tightly packed in vacuoles. Such a conjugative system might be involved in DNA transfer between internalized bacteria. Since this system is absent from the sequenced genomes of Chlamydiaceae, we hypothesize that it was acquired after the divergence between Parachlamydiaceae and Chlamydiaceae, when the Parachlamydia-related symbiont was an intracellular bacteria. It suggests that this heterologous DNA was acquired from a phylogenetically-distant bacteria sharing an amoebal vacuole. Since Parachlamydiaceae are emerging agents of pneumonia, this GI might be involved in pathogenicity. In future, conjugative systems might be developed as genetic tools for Chlamydiales.

Long synthetic peptides for the production of vaccines and drugs: a technological platform coming of age.

Long synthetic peptides (LSPs) have a variety of important clinical uses as synthetic vaccines and drugs. Techniques for peptide synthesis were revolutionized in the 1960s and 1980s, after which efficient techniques for purification and characterization of the product were developed. These improved techniques allowed the stepwise synthesis of increasingly longer products at a faster rate, greater purity, and lower cost for clinical use. A synthetic peptide approach, coupled with bioinformatics analysis of genomes, can tremendously expand the search for clinically relevant products. In this Review, we discuss efforts to develop a malaria vaccine from LSPs, among other clinically directed work.

Identification of HMX1 target genes: a predictive promoter model approach.

PURPOSE: A homozygous mutation in the H6 family homeobox 1 (HMX1) gene is responsible for a new oculoauricular defect leading to eye and auricular developmental abnormalities as well as early retinal degeneration (MIM 612109). However, the HMX1 pathway remains poorly understood, and in the first approach to better understand the pathway's function, we sought to identify the target genes. METHODS: We developed a predictive promoter model (PPM) approach using a comparative transcriptomic analysis in the retina at P15 of a mouse model lacking functional Hmx1 (dmbo mouse) and its respective wild-type. This PPM was based on the hypothesis that HMX1 binding site (HMX1-BS) clusters should be more represented in promoters of HMX1 target genes. The most differentially expressed genes in the microarray experiment that contained HMX1-BS clusters were used to generate the PPM, which was then statistically validated. Finally, we developed two genome-wide target prediction methods: one that focused on conserving PPM features in human and mouse and one that was based on the co-occurrence of HMX1-BS pairs fitting the PPM, in human or in mouse, independently. RESULTS: The PPM construction revealed that sarcoglycan, gamma (35kDa dystrophin-associated glycoprotein) (Sgcg), teashirt zinc finger homeobox 2 (Tshz2), and solute carrier family 6 (neurotransmitter transporter, glycine) (Slc6a9) genes represented Hmx1 targets in the mouse retina at P15. Moreover, the genome-wide target prediction revealed that mouse genes belonging to the retinal axon guidance pathway were targeted by Hmx1. Expression of these three genes was experimentally validated using a quantitative reverse transcription PCR approach. The inhibitory activity of Hmx1 on Sgcg, as well as protein tyrosine phosphatase, receptor type, O (Ptpro) and Sema3f, two targets identified by the PPM, were validated with luciferase assay. CONCLUSIONS: Gene expression analysis between wild-type and dmbo mice allowed us to develop a PPM that identified the first target genes of Hmx1.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.