957 resultados para human genome variation
Resumo:
New Global Positioning System (GPS) receivers allow now to measure a location on earth at high frequency (5Hz) with a centimetric precision using phase differential positioning method. We studied whether such technique was accurate enough to retrieve basic parameters of human locomotion. Eight subjects walked on an athletics track at four different imposed step frequencies (70-130steps/min) plus a run at free pace. Differential carrier phase localization between a fixed base station and the mobile antenna mounted on the walking person was calculated. In parallel, a triaxial accelerometer, attached to the low back, recorded body accelerations. The different parameters were averaged for 150 consecutive steps of each run for each subject (total of 6000 steps analyzed). We observed a perfect correlation between average step duration measured by accelerometer and by GPS (r=0.9998, N=40). Two important parameters for the calculation of the external work of walking were also analyzed, namely the vertical lift of the trunk and the velocity variation per step. For an average walking speed of 4.0km/h, average vertical lift and velocity variation were, respectively, 4.8cm and 0.60km/h. The average intra-individual step-to-step variability at a constant speed, which includes GPS errors and the biological gait style variation, were found to be 24. 5% (coefficient of variation) for vertical lift and 44.5% for velocity variation. It is concluded that GPS technique can provide useful biomechanical parameters for the analysis of an unlimited number of strides in an unconstrained free-living environment.
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The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.
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Sera from transgenic mice (TM) carrying human genes of alpha 1-acid glycoprotein (orosomucoid or ORM) have been analyzed by isoelectrofocusing and subsequent immunoblotting with antihuman ORM antibodies. With this technique it is possible to reveal selectively the human protein secreted in the TM sera. Orosomucoid bands present in TM sera have been compared with those of the most common human ORM phenotypes to correlate the products of specific genes to previously identified genetic variants. In this paper, we report the identification of the genes encoding for variants ORM1 F1 and ORM2 A, which are genes AGP-A and AGP-B/B' respectively. The nucleotide sequences of these genes are known; therefore a direct correlation between variants and specific amino acid sequences can be established.
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Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.
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Determination of the precise composition and variation of microbiota in cystic fibrosis lungs is crucial since chronic inflammation due to microorganisms leads to lung damage and ultimately, death. However, this constitutes a major technical challenge. Culturing of microorganisms does not provide a complete representation of a microbiota, even when using culturomics (high-throughput culture). So far, only PCR-based metagenomics have been investigated. However, these methods are biased towards certain microbial groups, and suffer from uncertain quantification of the different microbial domains. We have explored whole genome sequencing (WGS) using the Illumina high-throughput technology applied directly to DNA extracted from sputa obtained from two cystic fibrosis patients. To detect all microorganism groups, we used four procedures for DNA extraction, each with a different lysis protocol. We avoided biases due to whole DNA amplification thanks to the high efficiency of current Illumina technology. Phylogenomic classification of the reads by three different methods produced similar results. Our results suggest that WGS provides, in a single analysis, a better qualitative and quantitative assessment of microbiota compositions than cultures and PCRs. WGS identified a high quantity of Haemophilus spp. (patient 1) or Staphylococcus spp. plus Streptococcus spp. (patient 2) together with low amounts of anaerobic (Veillonella, Prevotella, Fusobacterium) and aerobic bacteria (Gemella, Moraxella, Granulicatella). WGS suggested that fungal members represented very low proportions of the microbiota, which were detected by cultures and PCRs because of their selectivity. The future increase of reads' sizes and decrease in cost should ensure the usefulness of WGS for the characterisation of microbiota.
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Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.
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The genomic loci occupied by RNA polymerase (RNAP) III have been characterized in human culture cells by genome-wide chromatin immunoprecipitations, followed by deep sequencing (ChIP-seq). These studies have shown that only ∼40% of the annotated 622 human tRNA genes and pseudogenes are occupied by RNAP-III, and that these genes are often in open chromatin regions rich in active RNAP-II transcription units. We have used ChIP-seq to characterize RNAP-III-occupied loci in a differentiated tissue, the mouse liver. Our studies define the mouse liver RNAP-III-occupied loci including a conserved mammalian interspersed repeat (MIR) as a potential regulator of an RNAP-III subunit-encoding gene. They reveal that synteny relationships can be established between a number of human and mouse RNAP-III genes, and that the expression levels of these genes are significantly linked. They establish that variations within the A and B promoter boxes, as well as the strength of the terminator sequence, can strongly affect RNAP-III occupancy of tRNA genes. They reveal correlations with various genomic features that explain the observed variation of 81% of tRNA scores. In mouse liver, loci represented in the NCBI37/mm9 genome assembly that are clearly occupied by RNAP-III comprise 50 Rn5s (5S RNA) genes, 14 known non-tRNA RNAP-III genes, nine Rn4.5s (4.5S RNA) genes, and 29 SINEs. Moreover, out of the 433 annotated tRNA genes, half are occupied by RNAP-III. Transfer RNA gene expression levels reflect both an underlying genomic organization conserved in dividing human culture cells and resting mouse liver cells, and the particular promoter and terminator strengths of individual genes.
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Huntington's disease (HD) pathology is well understood at a histological level but a comprehensive molecular analysis of the effect of the disease in the human brain has not previously been available. To elucidate the molecular phenotype of HD on a genome-wide scale, we compared mRNA profiles from 44 human HD brains with those from 36 unaffected controls using microarray analysis. Four brain regions were analyzed: caudate nucleus, cerebellum, prefrontal association cortex [Brodmann's area 9 (BA9)] and motor cortex [Brodmann's area 4 (BA4)]. The greatest number and magnitude of differentially expressed mRNAs were detected in the caudate nucleus, followed by motor cortex, then cerebellum. Thus, the molecular phenotype of HD generally parallels established neuropathology. Surprisingly, no mRNA changes were detected in prefrontal association cortex, thereby revealing subtleties of pathology not previously disclosed by histological methods. To establish that the observed changes were not simply the result of cell loss, we examined mRNA levels in laser-capture microdissected neurons from Grade 1 HD caudate compared to control. These analyses confirmed changes in expression seen in tissue homogenates; we thus conclude that mRNA changes are not attributable to cell loss alone. These data from bona fide HD brains comprise an important reference for hypotheses related to HD and other neurodegenerative diseases.
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Neuroticism is a moderately heritable personality trait considered to be a risk factor for developing major depression, anxiety disorders and dementia. We performed a genome-wide association study in 2,235 participants drawn from a population-based study of neuroticism, making this the largest association study for neuroticism to date. Neuroticism was measured by the Eysenck Personality Questionnaire. After Quality Control, we analysed 430,000 autosomal SNPs together with an additional 1.2 million SNPs imputed with high quality from the Hap Map CEU samples. We found a very small effect of population stratification, corrected using one principal component, and some cryptic kinship that required no correction. NKAIN2 showed suggestive evidence of association with neuroticism as a main effect (p < 10(-6)) and GPC6 showed suggestive evidence for interaction with age (p approximately = 10(-7)). We found support for one previously-reported association (PDE4D), but failed to replicate other recent reports. These results suggest common SNP variation does not strongly influence neuroticism. Our study was powered to detect almost all SNPs explaining at least 2% of heritability, and so our results effectively exclude the existence of loci having a major effect on neuroticism.
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AIMS: The time course of atherosclerosis burden in distinct vascular territories remains poorly understood. We longitudinally evaluated the natural history of atherosclerotic progression in two different arterial territories using high spatial resolution magnetic resonance imaging (HR-MRI), a powerful, safe, and non-invasive tool. METHODS AND RESULTS: We prospectively studied a cohort of 30 patients (mean age 68.3, n = 9 females) with high Framingham general cardiovascular disease 10-year risk score (29.5%) and standard medical therapy with mild-to-moderate atherosclerosis intra-individually at the level of both carotid and femoral arteries. A total of 178 HR-MRI studies of carotid and femoral arteries performed at baseline and at 1- and 2-year follow-up were evaluated in consensus reading by two experienced readers for lumen area (LA), total vessel area (TVA), vessel wall area (VWA = TVA - LA), and normalized wall area index (NWI = VWA/TVA). At the carotid level, LA decreased (-3.19%/year, P = 0.018), VWA increased (+3.83%/year, P = 0.019), and TVA remained unchanged. At the femoral level, LA remained unchanged, VWA and TVA increased (+5.23%/year and +3.11%/year, both P < 0.01), and NWI increased for both carotid and femoral arteries (+2.28%/year, P = 0.01, and +1.8%/year, P = 0.033). CONCLUSION: The atherosclerotic burden increased significantly in both carotid and femoral arteries. However, carotid plaque progression was associated with negative remodelling, whereas the increase in femoral plaque burden was compensated by positive remodelling. This finding could be related to anatomic and flow differences and/or to the distinct degree of obstruction in the two arterial territories.
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BACKGROUND: Small RNAs (sRNAs) are widespread among bacteria and have diverse regulatory roles. Most of these sRNAs have been discovered by a combination of computational and experimental methods. In Pseudomonas aeruginosa, a ubiquitous Gram-negative bacterium and opportunistic human pathogen, the GacS/GacA two-component system positively controls the transcription of two sRNAs (RsmY, RsmZ), which are crucial for the expression of genes involved in virulence. In the biocontrol bacterium Pseudomonas fluorescens CHA0, three GacA-controlled sRNAs (RsmX, RsmY, RsmZ) regulate the response to oxidative stress and the expression of extracellular products including biocontrol factors. RsmX, RsmY and RsmZ contain multiple unpaired GGA motifs and control the expression of target mRNAs at the translational level, by sequestration of translational repressor proteins of the RsmA family. RESULTS: A combined computational and experimental approach enabled us to identify 14 intergenic regions encoding sRNAs in P. aeruginosa. Eight of these regions encode newly identified sRNAs. The intergenic region 1698 was found to specify a novel GacA-controlled sRNA termed RgsA. GacA regulation appeared to be indirect. In P. fluorescens CHA0, an RgsA homolog was also expressed under positive GacA control. This 120-nt sRNA contained a single GGA motif and, unlike RsmX, RsmY and RsmZ, was unable to derepress translation of the hcnA gene (involved in the biosynthesis of the biocontrol factor hydrogen cyanide), but contributed to the bacterium's resistance to hydrogen peroxide. In both P. aeruginosa and P. fluorescens the stress sigma factor RpoS was essential for RgsA expression. CONCLUSION: The discovery of an additional sRNA expressed under GacA control in two Pseudomonas species highlights the complexity of this global regulatory system and suggests that the mode of action of GacA control may be more elaborate than previously suspected. Our results also confirm that several GGA motifs are required in an sRNA for sequestration of the RsmA protein.
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The genotyping of human papillomaviruses (HPV) is essential for the surveillance of HPV vaccines. We describe and validate a low-cost PGMY-based PCR assay (PGMY-CHUV) for the genotyping of 31 HPV by reverse blotting hybridization (RBH). Genotype-specific detection limits were 50 to 500 genome equivalents per reaction. RBH was 100% specific and 98.61% sensitive using DNA sequencing as the gold standard (n = 1,024 samples). PGMY-CHUV was compared to the validated and commercially available linear array (Roche) on 200 samples. Both assays identified the same positive (n = 182) and negative samples (n = 18). Seventy-six percent of the positives were fully concordant after restricting the comparison to the 28 genotypes shared by both assays. At the genotypic level, agreement was 83% (285/344 genotype-sample combinations; κ of 0.987 for single infections and 0.853 for multiple infections). Fifty-seven of the 59 discordant cases were associated with multiple infections and with the weakest genotypes within each sample (P < 0.0001). PGMY-CHUV was significantly more sensitive for HPV56 (P = 0.0026) and could unambiguously identify HPV52 in mixed infections. PGMY-CHUV was reproducible on repeat testing (n = 275 samples; 392 genotype-sample combinations; κ of 0.933) involving different reagents lots and different technicians. Discordant results (n = 47) were significantly associated with the weakest genotypes in samples with multiple infections (P < 0.0001). Successful participation in proficiency testing also supported the robustness of this assay. The PGMY-CHUV reagent costs were estimated at $2.40 per sample using the least expensive yet proficient genotyping algorithm that also included quality control. This assay may be used in low-resource laboratories that have sufficient manpower and PCR expertise.
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Adenovirus serotype 5 (Ad5) vectors and specific neutralizing antibodies (NAbs) generate immune complexes (ICs) which are potent inducers of dendritic cell (DC) maturation. Here we show that ICs generated with rare Ad vector serotypes, such as Ad26 and Ad35, which are lead candidates in HIV vaccine development, are poor inducers of DC maturation and that their potency in inducing DC maturation strongly correlated with the number of Toll-like receptor 9 (TLR9)-agonist motifs present in the Ad vector's genome. In addition, we showed that antihexon but not antifiber antibodies are responsible for the induction of Ad IC-mediated DC maturation.
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This study investigates the role of human agency in the gene flow and geographical distribution of the Australian baobab, Adansonia gregorii. The genus Adansonia is a charismatic tree endemic to Africa, Madagascar, and northwest Australia that has long been valued by humans for its multiple uses. The distribution of genetic variation in baobabs in Africa has been partially attributed to human-mediated dispersal over millennia, but this relationship has never been investigated for the Australian species. We combined genetic and linguistic data to analyse geographic patterns of gene flow and movement of word-forms for A. gregorii in the Aboriginal languages of northwest Australia. Comprehensive assessment of genetic diversity showed weak geographic structure and high gene flow. Of potential dispersal vectors, humans were identified as most likely to have enabled gene flow across biogeographic barriers in northwest Australia. Genetic-linguistic analysis demonstrated congruence of gene flow patterns and directional movement of Aboriginal loanwords for A. gregorii. These findings, along with previous archaeobotanical evidence from the Late Pleistocene and Holocene, suggest that ancient humans significantly influenced the geographic distribution of Adansonia in northwest Australia.
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Isolated gonadotropin-releasing hormone (GnRH) deficiency is a treatable albeit rare form of reproductive failure that has revealed physiological mechanisms controlling human reproduction, but despite substantial progress in discovering pathogenic single-gene defects, most of the genetic basis of GnRH deficiency remains uncharted. Although unbiased genetic investigations of affected families have identified mutations in previously unsuspected genes as causes of this disease in some cases, their application has been severely limited because of the negative effect of GnRH deficiency on fertility; moreover, relatively few of the many candidate genes nominated because of biological plausibility from in vitro or animal model experiments were subsequently validated in patients. With the advent of exciting technological platforms for sequencing, homozygosity mapping, and detection of structural variation at the whole-genome level, human investigations are again assuming the leading role for gene discovery. Using human GnRH deficiency as a paradigm and presenting original data from the screening of numerous candidate genes, we discuss the emerging model of patient-focused clinical genetic research and its complementarities with basic approaches in the near future.