1,640 research outputs found

    Defining and Detecting Crossover-Interference Mutants in Yeast

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    The analysis of crossover interference in many creatures is complicated by the presence of two kinds of crossovers, interfering and noninterfering. In such creatures, the values of the traditional indicators of interference are subject not only to the strength of interference but also to the relative frequencies of crossing over contributed by the two kinds. We formalize the relationship among these variables and illustrate the possibilities and limitations of classical interference analysis with meiotic tetrad data from wild-type Saccharomyces cerevisiae and from mlh1 and ndj1 mutants

    Balancing Selection at the Tomato RCR3 Guardee Gene Family Maintains Variation in Strength of Pathogen Defense

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    Coevolution between hosts and pathogens is thought to occur between interacting molecules of both species. This results in the maintenance of genetic diversity at pathogen antigens (or so-called effectors) and host resistance genes such as the major histocompatibility complex (MHC) in mammals or resistance (R) genes in plants. In plant-pathogen interactions, the current paradigm posits that a specific defense response is activated upon recognition of pathogen effectors via interaction with their corresponding R proteins. According to the''Guard-Hypothesis,'' R proteins (the ``guards'') can sense modification of target molecules in the host (the ``guardees'') by pathogen effectors and subsequently trigger the defense response. Multiple studies have reported high genetic diversity at R genes maintained by balancing selection. In contrast, little is known about the evolutionary mechanisms shaping the guardee, which may be subject to contrasting evolutionary forces. Here we show that the evolution of the guardee RCR3 is characterized by gene duplication, frequent gene conversion, and balancing selection in the wild tomato species Solanum peruvianum. Investigating the functional characteristics of 54 natural variants through in vitro and in planta assays, we detected differences in recognition of the pathogen effector through interaction with the guardee, as well as substantial variation in the strength of the defense response. This variation is maintained by balancing selection at each copy of the RCR3 gene. Our analyses pinpoint three amino acid polymorphisms with key functional consequences for the coevolution between the guardee (RCR3) and its guard (Cf-2). We conclude that, in addition to coevolution at the ``guardee-effector'' interface for pathogen recognition, natural selection acts on the ``guard-guardee'' interface. Guardee evolution may be governed by a counterbalance between improved activation in the presence and prevention of auto-immune responses in the absence of the corresponding pathogen

    Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

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    Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al

    Belief formation in a signaling game without common prior: an experiment

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    Using belief elicitation, the paper investigates the process of belief formation and evolution in a signaling game in which a common prior is not induced. Both prior and posterior beliefs of Receivers about Senders' types are elicited, as well as beliefs of Senders about Receivers' strategies. In the experiment, subjects often start with diffuse uniform beliefs and update them in view of observations. However, the speed of updating is influenced by the strength of initial beliefs. An interesting result is that beliefs about the prior distribution of types are updated slower than posterior beliefs, which incorporate Senders' strategies. In the medium run, for some specifications of game parameters, this leads to outcomes being significantly different from the outcomes of the game in which a common prior is induced. It is also shown that elicitation of beliefs does not considerably change the pattern of play in this game

    Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

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    We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare

    Simultaneous genotyping of multiple polymorphisms in human serotonin transporter gene and detection of novel allelic variants

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    The serotonin transporter, called SLC6A4, SERT or 5-HTT, modulates neurotransmission by removal of serotonin from the synapse of serotonergic neurons, facilitating serotonin reuptake into the presynaptic terminus. Selective serotonin reuptake inhibitors block the action of the serotonin transporter and are used to treat depression and other neuropsychiatric disorders. Three polymorphisms in the 5-HTT gene have been implicated in treatment response and neuropsychiatric disorders. A 44-bp promoter ins/del polymorphism (5-HTTLPR) produces primarily long and/or short alleles due to either 14 (short) or 16 (long) repeats of variably conserved 20–23 bp units. Also implicated, a 17–18 bp variable number tandem repeat found in intron2 (StIn2) is expressed as triallelic content with 9, 10, or 12 repeats (StIn2.9, StIn2.10 or StIn2.12). Finally, a single nucleotide polymorphism rs25531 located within the promoter polymorphic-linked region alters the function of the long promoter allele. We developed a PCR-based fragment analysis assay, which is analyzed on an ABI sequencer, whereby we are able to detect all three genotypes simultaneously. Using this technique, we identified novel sequences, which demonstrate promoter repeat regions containing (1) a 17 repeat with rs25531 A/G polymorphism, (2) two with 18-repeat units, (3) one with 20-repeat units and (4) a 24-repeat sequence. The novel repeats were confirmed by direct sequencing of gel-purified amplicons

    A case of isolation by distance and short-term temporal stability of population structure in brown trout (Salmo trutta) within the River Dart, southwest England

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    This is an open access article that is freely available in ORE or from the publisher's web site. Please cite the published version.© 2009 The Authors. Journal compilation © 2009 Blackwell Publishing LtdSalmonid fishes exhibit high levels of population differentiation. In particular, the brown trout (Salmo trutta L.) demonstrates complex within river drainage genetic structure. Increasingly, these patterns can be related to the underlying evolutionary models, of which three scenarios (member-vagrant hypothesis, metapopulation model and panmixia) facilitate testable predictions for investigations into population structure. We analysed 1225 trout collected from the River Dart, a 75 km long river located in southwest England. Specimens were collected from 22 sample sites across three consecutive summers (2001–2003) and genetic variation was examined at nine microsatellite loci. A hierarchical analysis of molecular variance revealed that negligible genetic variation was attributed among temporal samples. The highest levels of differentiation occurred among samples isolated above barriers to fish movement, and once these samples were removed, a significant effect of isolation-by-distance was observed. These results suggest that, at least in the short-term, ecological events are more important in shaping the population structure of Dart trout than stochastic extinction events, and certainly do not contradict the expectations of a member-vagrant hypothesis. Furthermore, individual-level spatial autocorrelation analyses support previous recommendations for the preservation of a number of spawning sites spaced throughout the tributary system to conserve the high levels of genetic variation identified in salmonid species

    Quantifying Missing Heritability at Known GWAS Loci

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    Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain 1.29 X more heritability than GWAS-associated SNPs on average (P = 3.3 X 10[superscript -5]). For some diseases, this increase was individually significant:2.07 X for Multiple Sclerosis (MS) (P = 6.5 X 10 [superscript -9]) and for Crohn's Disease (CD) (P = 1.3 X 10[superscript -3]); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained 7.15 X more MS heritability than known MS SNPs (P 20,000 Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with 2.37 X more heritability from all SNPs at GWAS loci (P = 2.3 X 10[superscript -6]) and more heritability from all autoimmune disease loci (P < 1 X 10[superscript -16]) compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.National Institutes of Health (U.S.) (Grant R03HG006731)National Institutes of Health (U.S.) (Fellowship F32GM106584
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