Gateway vectors for efficient artificial gene assembly in vitro and expression in yeast Saccharomyces cerevisiae

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Lab Retriever: a software tool for calculating likelihood ratios incorporating a probability of drop-out for forensic DNA profiles

BACKGROUND: Technological advances have enabled the analysis of very small amounts of DNA in forensic cases. However, the DNA profiles from such evidence are frequently incomplete and can contain contributions from multiple individuals. The complexity of such samples confounds the assessment of the statistical weight of such evidence. One approach to account for this uncertainty is to use a likelihood ratio framework to compare the probability of the evidence profile under different scenarios. While researchers favor the likelihood ratio framework, few open-source software solutions with a graphical user interface implementing these calculations are available for practicing forensic scientists. RESULTS: To address this need, we developed Lab Retriever, an open-source, freely available program that forensic scientists can use to calculate likelihood ratios for complex DNA profiles. Lab Retriever adds a graphical user interface, written primarily in JavaScript, on top of a C++ implementation of the previously published R code of Balding. We redesigned parts of the original Balding algorithm to improve computational speed. In addition to incorporating a probability of allelic drop-out and other critical parameters, Lab Retriever computes likelihood ratios for hypotheses that can include up to four unknown contributors to a mixed sample. These computations are completed nearly instantaneously on a modern PC or Mac computer. CONCLUSIONS: Lab Retriever provides a practical software solution to forensic scientists who wish to assess the statistical weight of evidence for complex DNA profiles. Executable versions of the program are freely available for Mac OSX and Windows operating systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0740-8) contains supplementary material, which is available to authorized users

Gene expression drives the evolution of dominance.

Dominance is a fundamental concept in molecular genetics and has implications for understanding patterns of genetic variation, evolution, and complex traits. However, despite its importance, the degree of dominance in natural populations is poorly quantified. Here, we leverage multiple mating systems in natural populations of Arabidopsis to co-estimate the distribution of fitness effects and dominance coefficients of new amino acid changing mutations. We find that more deleterious mutations are more likely to be recessive than less deleterious mutations. Further, this pattern holds across gene categories, but varies with the connectivity and expression patterns of genes. Our work argues that dominance arises as a consequence of the functional importance of genes and their optimal expression levels

DNA sense-and-respond protein modules for mammalian cells

We generated synthetic protein components that can detect specific DNA sequences and subsequently trigger a desired intracellular response. These modular sensors exploit the programmability of zinc-finger DNA recognition to drive the intein-mediated splicing of an artificial trans-activator that signals to a genetic circuit containing a given reporter or response gene. We used the sensors to mediate sequence recognition−induced apoptosis as well as to detect and report a viral infection. This work establishes a synthetic biology framework for endowing mammalian cells with sentinel capabilities, which provides a programmable means to cull infected cells. It may also be used to identify positively transduced or transfected cells, isolate recipients of intentional genomic edits and increase the repertoire of inducible parts in synthetic biology.United States. Defense Advanced Research Projects Agency (DARPA-BAA-11-23)Defense Threat Reduction Agency (DTRA) (HDTRA1-14-1-0006)United States. Air Force Office of Scientific Research (FA9550-14-1-0060

Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring

Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl-D-aspartate receptor (NMDAR)–mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia

FTO Gene Associated Fatness in Relation to Body Fat Distribution and Metabolic Traits throughout a Broad Range of Fatness

A common single nucleotide polymorphism (SNP) of FTO (rs9939609, T/A) is associated with total body fatness. We investigated the association of this SNP with abdominal and peripheral fatness and obesity-related metabolic traits in middle-aged men through a broad range of fatness present already in adolescence.Obese young Danish men (n = 753, BMI > or = 31.0 kg/m(2)) and a randomly selected group (n = 879) from the same population were examined in three surveys (mean age 35, 46 and 49 years, respectively). The traits included anthropometrics, body composition, oral glucose tolerance test, blood lipids, blood pressure, fibrinogen and aspartate aminotransferase. Logistic regression analysis was used to assess the age-adjusted association between the phenotypes and the odds ratios for the FTO rs9939609 (TT and TA genotype versus the AA genotype), for anthropometrics and body composition estimated per unit z-score. BMI was strongly associated with the AA genotype in all three surveys: OR = 1.17, p = 1.1*10(-6), OR = 1.20, p = 1.7*10(-7), OR = 1.17, p = 3.4*10(-3), respectively. Fat body mass index was also associated with the AA genotype (OR = 1.21, p = 4.6*10(-7) and OR = 1.21, p = 1.0*10(-3)). Increased abdominal fatness was associated with the AA genotype when measured as waist circumference (OR = 1.21, p = 2.2*10(-6) and OR = 1.19, p = 5.9*10(-3)), sagittal abdominal diameter (OR = 1.17, p = 1.3*10(-4) and OR = 1.18, p = 0.011) and intra-abdominal adipose tissue (OR = 1.21, p = 0.005). Increased peripheral fatness measured as hip circumference (OR = 1.19, p = 1.3*10(-5) and OR = 1.18, p = 0.004) and lower body fat mass (OR = 1.26, p = 0.002) was associated with the AA genotype. The AA genotype was significantly associated with decreased Stumvoll insulin sensitivity index (OR = 0.93, p = 0.02) and with decreased non-fasting plasma HDL-cholesterol (OR = 0.57, p = 0.037), but not with any other of the metabolic traits. However, all significant results for both body fat distribution and metabolic traits were explained by a mediating effect of total fat mass.The association of the examined FTO SNP to general fatness throughout the range of fatness was confirmed, and this association explains the relation between the SNP and body fat distribution and decreased insulin sensitivity and HDL-cholesterol. The SNP was not significantly associated with other metabolic traits suggesting that they are not derived from the general accumulation of body fat

Evolutionary Dynamics of Co-Segregating Gene Clusters Associated with Complex Diseases

BACKGROUND: The distribution of human disease-associated mutations is not random across the human genome. Despite the fact that natural selection continually removes disease-associated mutations, an enrichment of these variants can be observed in regions of low recombination. There are a number of mechanisms by which such a clustering could occur, including genetic perturbations or demographic effects within different populations. Recent genome-wide association studies (GWAS) suggest that single nucleotide polymorphisms (SNPs) associated with complex disease traits are not randomly distributed throughout the genome, but tend to cluster in regions of low recombination. PRINCIPAL FINDINGS: Here we investigated whether deleterious mutations have accumulated in regions of low recombination due to the impact of recent positive selection and genetic hitchhiking. Using publicly available data on common complex diseases and population demography, we observed an enrichment of hitchhiked disease associations in conserved gene clusters subject to selection pressure. Evolutionary analysis revealed that these conserved gene clusters arose by multiple concerted rearrangements events across the vertebrate lineage. We observed distinct clustering of disease-associated SNPs in evolutionary rearranged regions of low recombination and high gene density, which harbor genes involved in immunity, that is, the interleukin cluster on 5q31 or RhoA on 3p21. CONCLUSIONS: Our results suggest that multiple lineage specific rearrangements led to a physical clustering of functionally related and linked genes exhibiting an enrichment of susceptibility loci for complex traits. This implies that besides recent evolutionary adaptations other evolutionary dynamics have played a role in the formation of linked gene clusters associated with complex disease traits

Geographic differences in allele frequencies of susceptibility SNPs for cardiovascular disease

<p>Abstract</p> <p>Background</p> <p>We hypothesized that the frequencies of risk alleles of SNPs mediating susceptibility to cardiovascular diseases differ among populations of varying geographic origin and that population-specific selection has operated on some of these variants.</p> <p>Methods</p> <p>From the database of genome-wide association studies (GWAS), we selected 36 cardiovascular phenotypes including coronary heart disease, hypertension, and stroke, as well as related quantitative traits (eg, body mass index and plasma lipid levels). We identified 292 SNPs in 270 genes associated with a disease or trait at <it>P </it>< 5 × 10^-8. As part of the Human Genome-Diversity Project (HGDP), 158 (54.1%) of these SNPs have been genotyped in 938 individuals belonging to 52 populations from seven geographic areas. A measure of population differentiation, <it>F</it>_ST, was calculated to quantify differences in risk allele frequencies (RAFs) among populations and geographic areas.</p> <p>Results</p> <p>Large differences in RAFs were noted in populations of Africa, East Asia, America and Oceania, when compared with other geographic regions. The mean global <it>F</it>_ST(0.1042) for 158 SNPs among the populations was not significantly higher than the mean global <it>F</it>_STof 158 autosomal SNPs randomly sampled from the HGDP database. Significantly higher global <it>F</it>_ST(<it>P </it>< 0.05) was noted in eight SNPs, based on an empirical distribution of global <it>F</it>_STof 2036 putatively neutral SNPs. For four of these SNPs, additional evidence of selection was noted based on the integrated Haplotype Score.</p> <p>Conclusion</p> <p>Large differences in RAFs for a set of common SNPs that influence risk of cardiovascular disease were noted between the major world populations. Pairwise comparisons revealed RAF differences for at least eight SNPs that might be due to population-specific selection or demographic factors. These findings are relevant to a better understanding of geographic variation in the prevalence of cardiovascular disease.</p

Haplotype differences for copy number variants in the 22q11.23 region among human populations: a pigmentation-based model for selective pressure.

Two gene clusters are tightly linked in a narrow region of chromosome 22q11.23: the macrophage migration inhibitory factor (MIF) gene family and the glutathione S-transferase theta class. Within 120 kb in this region, two 30-kb deletions reach high frequencies in human populations. This gives rise to four haplotypic arrangements, which modulate the number of genes in both families. The variable patterns of linkage disequilibrium (LD) between these copy number variants (CNVs) in diverse human populations remain poorly understood. We analyzed 2469 individuals belonging to 27 human populations with different ethnic origins. Then we correlated the genetic variability of 22q11.23 CNVs with environmental variables. We confirmed an increasing strength of LD from Africa to Asia and to Europe. Further, we highlighted strongly significant correlations between the frequency of one of the haplotypes and pigmentation-related variables: skin color (R2=0.675, P<0.001), distance from the equator (R2=0.454, P<0.001), UVA radiation (R2=0.439, P<0.001), and UVB radiation (R2=0.313, P=0.002). The fact that all MIF-related genes are retained on this haplotype and the evidences gleaned from experimental systems seem to agree with the role of MIF-related genes in melanogenesis. As such, we propose a model that explains the geographic and ethnic distribution of 22q11.23 CNVs among human populations, assuming that MIF-related gene dosage could be associated with adaptation to low UV radiatio