Gene expression variation and expression quantitative trait mapping of human chromosome 21 genes.

Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.

Multi-ethnic fine-mapping of 14 central adiposity loci.

The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowing the signals remains necessary. Twelve of 14 loci identified in GIANT EA samples retained strong associations with WHR in our joint EA/individuals of African Ancestry (AA) analysis (log-Bayes factor >6.1). Trans-ethnic analyses at five loci (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86 and ITPR2-SSPN) substantially narrowed the signals to smaller sets of variants, some of which are in regions that have evidence of regulatory activity. By leveraging varying linkage disequilibrium structures across different populations, single-nucleotide polymorphisms (SNPs) with strong signals and narrower credible sets from trans-ethnic meta-analysis of central obesity provide more precise localizations of potential functional variants and suggest a possible regulatory role. Meta-analysis results for WHR were obtained from 77 167 EA participants from GIANT and 23 564 AA participants from the African Ancestry Anthropometry Genetics Consortium. For fine mapping we interrogated SNPs within ± 250 kb flanking regions of 14 previously reported index SNPs from loci discovered in EA populations by performing trans-ethnic meta-analysis of results from the EA and AA meta-analyses. We applied a Bayesian approach that leverages allelic heterogeneity across populations to combine meta-analysis results and aids in fine-mapping shared variants at these locations. We annotated variants using information from the ENCODE Consortium and Roadmap Epigenomics Project to prioritize variants for possible functionality.

Anatomical correlates for category-specific naming of objects and actions: A brain stimulation mapping study.

The production of object and action words can be dissociated in aphasics, yet their anatomical correlates have been difficult to distinguish in functional imaging studies. To investigate the extent to which the cortical neural networks underlying object- and action-naming processing overlap, we performed electrostimulation mapping (ESM), which is a neurosurgical mapping technique routinely used to examine language function during brain-tumor resections. Forty-one right-handed patients who had surgery for a brain tumor were asked to perform overt naming of object and action pictures under stimulation. Overall, 73 out of the 633 stimulated cortical sites (11.5%) were associated with stimulation-induced language interferences. These interference sites were very much localized (<1 cm(2) ), and showed substantial variability across individuals in their exact localization. Stimulation interfered with both object and action naming over 44 sites, whereas it specifically interfered with object naming over 19 sites and with action naming over 10 sites. Specific object-naming sites were mainly identified in Broca's area (Brodmann area 44/45) and the temporal cortex, whereas action-naming specific sites were mainly identified in the posterior midfrontal gyrus (Brodmann area 6/9) and Broca's area (P = 0.003 by the Fisher's exact test). The anatomical loci we emphasized are in line with a cortical distinction between objects and actions based on conceptual/semantic features, so the prefrontal/premotor cortex would preferentially support sensorimotor contingencies associated with actions, whereas the temporal cortex would preferentially underpin (functional) properties of objects. Hum Brain Mapp 35:429-443, 2014. © 2012 Wiley Periodicals, Inc.

Genomic organization, fine-mapping, and expression of the human islet-brain 1 (IB1)/c-Jun-amino-terminal kinase interacting protein-1 (JIP-1) gene.

Islet-brain 1 (IB1), a regulator of the pancreatic beta-cell function in the rat, is homologous to JIP-1, a murine inhibitor of c-Jun amino-terminal kinase (JNK). Whether IB1 and JIP-1 are present in humans was not known. We report the sequence of the 2133-bp human IB1 cDNA, the expression, structure, and fine-mapping of the human IB1 gene, and the characterization of an IB1 pseudogene. Human IB1 is 94% identical to rat IB1. The tissue-specific expression of IB1 in human is similar to that observed in rodent. The IB1 gene contains 12 exons and maps to chromosome 11 (11p11.2-p12), a region that is deleted in DEFECT-11 syndrome. Apart from an IB1 pseudogene on chromosome 17 (17q21), no additional IB1-related gene was found in the human genome. Our data indicate that the sequence and expression pattern of IB1 are highly conserved between rodent and human and provide the necessary tools to investigate whether IB1 is involved in human diseases.

Mapping the proteome of Leishmania Viannia parasites using two-dimensional polyacrylamide gel electrophoresis and associated technologies.

In this study we have demonstrated the potential of two-dimensional electrophoresis (2DE)-based technologies as tools for characterization of the Leishmania proteome (the expressed protein complement of the genome). Standardized neutral range (pH 5-7) proteome maps of Leishmania (Viannia) guyanensis and Leishmania (Viannia) panamensis promastigotes were reproducibly generated by 2DE of soluble parasite extracts, which were prepared using lysis buffer containing urea and nonidet P-40 detergent. The Coomassie blue and silver nitrate staining systems both yielded good resolution and representation of protein spots, enabling the detection of approximately 800 and 1,500 distinct proteins, respectively. Several reference protein spots common to the proteomes of all parasite species/strains studied were isolated and identified by peptide mass spectrometry (LC-ES-MS/MS), and bioinformatics approaches as members of the heat shock protein family, ribosomal protein S12, kinetoplast membrane protein 11 and a hypothetical Leishmania-specific 13 kDa protein of unknown function. Immunoblotting of Leishmania protein maps using a monoclonal antibody resulted in the specific detection of the 81.4 kDa and 77.5 kDa subunits of paraflagellar rod proteins 1 and 2, respectively. Moreover, differences in protein expression profiles between distinct parasite clones were reproducibly detected through comparative proteome analyses of paired maps using image analysis software. These data illustrate the resolving power of 2DE-based proteome analysis. The production and basic characterization of good quality Leishmania proteome maps provides an essential first step towards comparative protein expression studies aimed at identifying the molecular determinants of parasite drug resistance and virulence, as well as discovering new drug and vaccine targets.

Mapping of a gene coding for a major late structural polypeptide on the vaccinia virus genome.

Cell-free translation of total RNA isolated from vaccinia virus-infected cells late in infection results in a complex mixture of polypeptides. A monospecific antibody directed against one of the major structural proteins of the virus particle immunoprecipitated a single polypeptide with a molecular weight of 11,000 (11K) from this mixture. Immunoprecipitation was therefore used to identify the structural polypeptide among the in vitro translation products of RNA purified by hybridization selection to restriction fragments of the vaccinia virus genome. This allowed us to map the mRNA coding for the 11K polypeptide to the extreme left-hand end of the HindIII E fragment. Detailed transcriptional mapping of this region of the genome by nuclease S1 analysis revealed the presence of a late RNA transcribed from the rightward-reading strand. Its 5' end mapped at ca. 130 base pairs to the left of the HindIII site at the junction between the HindIII F and E fragments. The map position of this RNA coincided precisely with the map position of the late message coding for the 11K polypeptide.

Connectivity differences in brain networks.

The scenario considered here is one where brain connectivity is represented as a network and an experimenter wishes to assess the evidence for an experimental effect at each of the typically thousands of connections comprising the network. To do this, a univariate model is independently fitted to each connection. It would be unwise to declare significance based on an uncorrected threshold of α=0.05, since the expected number of false positives for a network comprising N=90 nodes and N(N-1)/2=4005 connections would be 200. Control of Type I errors over all connections is therefore necessary. The network-based statistic (NBS) and spatial pairwise clustering (SPC) are two distinct methods that have been used to control family-wise errors when assessing the evidence for an experimental effect with mass univariate testing. The basic principle of the NBS and SPC is the same as supra-threshold voxel clustering. Unlike voxel clustering, where the definition of a voxel cluster is unambiguous, 'clusters' formed among supra-threshold connections can be defined in different ways. The NBS defines clusters using the graph theoretical concept of connected components. SPC on the other hand uses a more stringent pairwise clustering concept. The purpose of this article is to compare the pros and cons of the NBS and SPC, provide some guidelines on their practical use and demonstrate their utility using a case study involving neuroimaging data.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

The challenge of modeling nuclear receptor regulatory networks in mammalian cells.

Nuclear receptors are a major component of signal transduction in animals. They mediate the regulatory activities of many hormones, nutrients and metabolites on the homeostasis and physiology of cells and tissues. It is of high interest to model the corresponding regulatory networks. While molecular and cell biology studies of individual promoters have provided important mechanistic insight, a more complex picture is emerging from genome-wide studies. The regulatory circuitry of nuclear receptor regulated gene expression networks, and their response to cellular signaling, appear highly dynamic, and involve long as well as short range chromatin interactions. We review how progress in understanding the kinetics and regulation of cofactor recruitment, and the development of new genomic methods, provide opportunities but also a major challenge for modeling nuclear receptor mediated regulatory networks.

Mapping the structural core of human cerebral cortex.

Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.

Reconciliation of metabolites and biochemical reactions for metabolic networks.

Genome-scale metabolic network reconstructions are now routinely used in the study of metabolic pathways, their evolution and design. The development of such reconstructions involves the integration of information on reactions and metabolites from the scientific literature as well as public databases and existing genome-scale metabolic models. The reconciliation of discrepancies between data from these sources generally requires significant manual curation, which constitutes a major obstacle in efforts to develop and apply genome-scale metabolic network reconstructions. In this work, we discuss some of the major difficulties encountered in the mapping and reconciliation of metabolic resources and review three recent initiatives that aim to accelerate this process, namely BKM-react, MetRxn and MNXref (presented in this article). Each of these resources provides a pre-compiled reconciliation of many of the most commonly used metabolic resources. By reducing the time required for manual curation of metabolite and reaction discrepancies, these resources aim to accelerate the development and application of high-quality genome-scale metabolic network reconstructions and models.

Mapping of the genes coding for the two major vaccinia virus core polypeptides.

We have mapped the genes coding for two major structural polypeptides of the vaccinia virus core by hybrid selection and transcriptional mapping. First, RNA was selected by hybridization to restriction fragments of the vaccinia virus genome, translated in vitro and the products were immunoprecipitated with antibodies against the two polypeptides. This approach allowed us to map the genes to the left hand end of the largest Hind III restriction fragment of 50 kilobase pairs. Second, transcriptional mapping of this region of the genome revealed the presence of the two expected RNAs. Both RNAs are transcribed from the leftward reading strand and the 5'-ends of the genes are separated by about 7.5 kilobase pairs of DNA. Thus, two genes encoding structural polypeptides with a similar location in the vaccinia virus particle are clustered at approximately 105 kilobase pairs from the left hand end of the 180 kilobase pair vaccinia virus genome.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

New insights into the molecular basis of desmoplakin- and desmin-related cardiomyopathies.

Desmosomes are intercellular adhesive complexes that anchor the intermediate filament cytoskeleton to the cell membrane in epithelia and cardiac muscle cells. The desmosomal component desmoplakin plays a key role in tethering various intermediate filament networks through its C-terminal plakin repeat domain. To gain better insight into the cytoskeletal organization of cardiomyocytes, we investigated the association of desmoplakin with desmin by cell transfection, yeast two-hybrid, and/or in vitro binding assays. The results indicate that the association of desmoplakin with desmin depends on sequences within the linker region and C-terminal extremity of desmoplakin, where the B and C subdomains contribute to efficient binding; a potentially phosphorylatable serine residue in the C-terminal extremity of desmoplakin affects its association with desmin; the interaction of desmoplakin with non-filamentous desmin requires sequences contained within the desmin C-terminal rod portion and tail domain in yeast, whereas in in vitro binding studies the desmin tail is dispensable for association; and mutations in either the C-terminus of desmoplakin or the desmin tail linked to inherited cardiomyopathy seem to impair desmoplakindesmin interaction. These studies increase our understanding of desmoplakin-intermediate filament interactions, which are important for maintenance of cytoarchitecture in cardiomyocytes, and give new insights into the molecular basis of desmoplakin- and desmin-related human diseases.