Differential regulation of a MYB transcription factor is correlated with transgenerational epigenetic inheritance of trichome density in Mimulus guttatus

This is the peer reviewed version of the following article: Scoville, A. G., Barnett, L. L., Bodbyl-Roels, S., Kelly, J. K. and Hileman, L. C. (2011), Differential regulation of a MYB transcription factor is correlated with transgenerational epigenetic inheritance of trichome density in Mimulus guttatus. New Phytologist, 191: 251–263. doi:10.1111/j.1469-8137.2011.03656.x, which has been published in final form at http://doi.org/10.1111/j.1469-8137.2011.03656.x. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Epigenetic inheritance, transgenerational transmission of traits not proximally determined by DNA sequence, has been linked to transmission of chromatin modifications and gene regulation, which are known to be sensitive to environmental factors. Mimulus guttatus increases trichome (plant hair) density in response to simulated herbivore damage. Increased density is expressed in progeny even if progeny do not experience damage. To better understand epigenetic inheritance of trichome production, we tested the hypothesis that candidate gene expression states are inherited in response to parental damage. Using M. guttatus recombinant inbred lines, offspring of leaf-damaged and control plants were raised without damage. Relative expression of candidate trichome development genes was measured in offspring. Line and parental damage effects on trichome density were measured. Associations between gene expression, trichome density, and response to parental damage were determined. We identified M. guttatus MYB MIXTA-like 8 as a possible negative regulator of trichome development. We found that parental leaf damage induces down-regulation of MYB MIXTA-like 8 in progeny, which is associated with epigenetically inherited increased trichome density. Our results link epigenetic transmission of an ecologically important trait with differential gene expression states – providing insight into a mechanism underlying environmentally induced ‘soft inheritance’

QiSampler: evaluation of scoring schemes for high-throughput datasets using a repetitive sampling strategy on gold standards

<p>Abstract</p> <p>Background</p> <p>High-throughput biological experiments can produce a large amount of data showing little overlap with current knowledge. This may be a problem when evaluating alternative scoring mechanisms for such data according to a gold standard dataset because standard statistical tests may not be appropriate.</p> <p>Findings</p> <p>To address this problem we have implemented the QiSampler tool that uses a repetitive sampling strategy to evaluate several scoring schemes or experimental parameters for any type of high-throughput data given a gold standard. We provide two example applications of the tool: selection of the best scoring scheme for a high-throughput protein-protein interaction dataset by comparison to a dataset derived from the literature, and evaluation of functional enrichment in a set of tumour-related differentially expressed genes from a thyroid microarray dataset.</p> <p>Conclusions</p> <p>QiSampler is implemented as an open source R script and a web server, which can be accessed at <url>http://cbdm.mdc-berlin.de/tools/sampler/</url>.</p

Oscillatory surface rheotaxis of swimming E. coli bacteria

Bacterial contamination of biological conducts, catheters or water resources is a major threat to public health and can be amplified by the ability of bacteria to swim upstream. The mechanisms of this rheotaxis, the reorientation with respect to flow gradients, often in complex and confined environments, are still poorly understood. Here, we follow individual E. coli bacteria swimming at surfaces under shear flow with two complementary experimental assays, based on 3D Lagrangian tracking and fluorescent flagellar labelling and we develop a theoretical model for their rheotactic motion. Three transitions are identified with increasing shear rate: Above a first critical shear rate, bacteria shift to swimming upstream. After a second threshold, we report the discovery of an oscillatory rheotaxis. Beyond a third transition, we further observe coexistence of rheotaxis along the positive and negative vorticity directions. A full theoretical analysis explains these regimes and predicts the corresponding critical shear rates. The predicted transitions as well as the oscillation dynamics are in good agreement with experimental observations. Our results shed new light on bacterial transport and reveal new strategies for contamination prevention.Comment: 12 pages, 5 figure

P-odd and CP-odd Four-Quark Contributions to Neutron EDM

In a class of beyond-standard-model theories, CP-odd observables, such as the neutron electric dipole moment, receive significant contributions from flavor-neutral P-odd and CP-odd four-quark operators. However, considerable uncertainties exist in the hadronic matrix elements of these operators strongly affecting the experimental constraints on CP-violating parameters in the theories. Here we study their hadronic matrix elements in combined chiral perturbation theory and nucleon models. We first classify the operators in chiral representations and present the leading-order QCD evolutions. We then match the four-quark operators to the corresponding ones in chiral hadronic theory, finding symmetry relations among the matrix elements. Although this makes lattice QCD calculations feasible, we choose to estimate the non-perturbative matching coefficients in simple quark models. We finally compare the results for the neutron electric dipole moment and P-odd and CP-odd pion-nucleon couplings with the previous studies using naive factorization and QCD sum rules. Our study shall provide valuable insights on the present hadronic physics uncertainties in these observables.Comment: 40 pages, 7 figures. This is the final version. A discussion of the uncertainty of the calculation is adde

Wolbachia in the flesh: symbiont intensities in germ-line and somatic tissues challenge the conventional view of Wolbachia transmission routes

Symbionts can substantially affect the evolution and ecology of their hosts. The investigation of the tissue-specific distribution of symbionts (tissue tropism) can provide important insight into host-symbiont interactions. Among other things, it can help to discern the importance of specific transmission routes and potential phenotypic effects. The intracellular bacterial symbiont Wolbachia has been described as the greatest ever panzootic, due to the wide array of arthropods that it infects. Being primarily vertically transmitted, it is expected that the transmission of Wolbachia would be enhanced by focusing infection in the reproductive tissues. In social insect hosts, this tropism would logically extend to reproductive rather than sterile castes, since the latter constitute a dead-end for vertically transmission. Here, we show that Wolbachia are not focused on reproductive tissues of eusocial insects, and that non-reproductive tissues of queens and workers of the ant Acromyrmex echinatior, harbour substantial infections. In particular, the comparatively high intensities of Wolbachia in the haemolymph, fat body, and faeces, suggest potential for horizontal transmission via parasitoids and the faecal-oral route, or a role for Wolbachia modulating the immune response of this host. It may be that somatic tissues and castes are not the evolutionary dead-end for Wolbachia that is commonly thought

Detectability of Plasmodium falciparum clones

BACKGROUND: In areas of high transmission people often harbour multiple clones of Plasmodium falciparum, but even PCR-based diagnostic methods can only detect a fraction (the detectability, q) of all clones present in a host. Accurate measurements of detectability are desirable since it affects estimates of multiplicity of infection, prevalence, and frequency of breakthrough infections in clinical drug trials. Detectability can be estimated by typing repeated samples from the same host but it has been unclear what should be the time interval between the samples and how the data should be analysed. METHODS: A longitudinal molecular study was conducted in the Kassena-Nankana district in northern Ghana. From each of the 80 participants, four finger prick samples were collected over a period of 8 days, and tested for presence of different Merozoite Surface Protein (msp) 2 genotypes. Implications for estimating q were derived from these data by comparing the fit of statistical models of serial dependence and over-dispersion. RESULTS: The distribution of the frequencies of detection for msp2 genotypes was close to binomial if the time span between consecutive blood samples was at least 7 days. For shorter intervals the probabilities of detection were positively correlated, i.e. the shorter the interval between two blood collections, the more likely the diagnostic results matched for a particular genotype. Estimates of q were rather insensitive to the statistical model fitted. CONCLUSIONS: A simple algorithm based on analysing blood samples collected 7 days apart is justified for generating robust estimates of detectability. The finding of positive correlation of detection probabilities for short time intervals argues against imperfect detection being directly linked to the 48-hour periodicity of P. falciparum. The results suggest that the detectability of a given parasite clone changes over time, at an unknown rate, but fast enough to regard blood samples taken one week apart as statistically independent

A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more variables than observations

<p>Abstract</p> <p>Background</p> <p>With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables than observations are now routinely being collected. Finding relationships between response variables of interest and variables in such data sets is an important problem akin to finding needles in a haystack. Whilst methods for a number of response types have been developed a general approach has been lacking.</p> <p>Results</p> <p>The major contribution of this paper is to present a unified methodology which allows many common (statistical) response models to be fitted to such data sets. The class of models includes virtually any model with a linear predictor in it, for example (but not limited to), multiclass logistic regression (classification), generalised linear models (regression) and survival models. A fast algorithm for finding sparse well fitting models is presented. The ideas are illustrated on real data sets with numbers of variables ranging from thousands to millions. R code implementing the ideas is available for download.</p> <p>Conclusion</p> <p>The method described in this paper enables existing work on response models when there are less variables than observations to be leveraged to the situation when there are many more variables than observations. It is a powerful approach to finding parsimonious models for such datasets. The method is capable of handling problems with millions of variables and a large variety of response types within the one framework. The method compares favourably to existing methods such as support vector machines and random forests, but has the advantage of not requiring separate variable selection steps. It is also works for data types which these methods were not designed to handle. The method usually produces very sparse models which make biological interpretation simpler and more focused.</p

Reproducibility of different screening classifications in ultrasonography of the newborn hip

<p>Abstract</p> <p>Background</p> <p>Ultrasonography of the hip has gained wide acceptance as a primary method for diagnosis, screening and treatment monitoring of developmental hip dysplasia in infants. The aim of the study was to examine the degree of concordance of two objective classifications of hip morphology and subjective parameters by three investigators with different levels of experience.</p> <p>Methods</p> <p>In 207 consecutive newborns (101 boys; 106 girls) the following parameters were assessed: bony roof angle (α-angle) and cartilage roof angle (β-angle) according to Graf's basic standard method, "femoral head coverage" (FHC) as described by Terjesen, shape of the bony roof and position of the cartilaginous roof. Both hips were measured twice by each investigator with a 7.5 MHz linear transducer (SONOLINE G60S^®ultrasound system, SIEMENS, Erlangen, Germany).</p> <p>Results</p> <p>Mean kappa-coefficients for the subjective parameters shape of the bony roof (0.97) and position of the cartilaginous roof (1.0) demonstrated high intra-observer reproducibility. Best results were achieved for α-angle, followed by β-angle and finally FHC. With respect to limits of agreement, inter-observer reproducibility was calculated less precisely.</p> <p>Conclusions</p> <p>Higher measurement differences were evaluated more in objective scorings. Those variations were observed by every investigator irrespective of level of experience.</p

The Random Nature of Genome Architecture: Predicting Open Reading Frame Distributions

Background: A better understanding of the size and abundance of open reading frames (ORFS) in whole genomes may shed light on the factors that control genome complexity. Here we examine the statistical distributions of open reading frames (i.e. distribution of start and stop codons) in the fully sequenced genomes of 297 prokaryotes, and 14 eukaryotes. Methodology/Principal Findings: By fitting mixture models to data from whole genome sequences we show that the size-frequency distributions for ORFS are strikingly similar across prokaryotic and eukaryotic genomes. Moreover, we show that i) a large fraction (60–80%) of ORF size-frequency distributions can be predicted a priori with a stochastic assembly model based on GC content, and that (ii) size-frequency distributions of the remaining “non-random” ORFs are well-fitted by log-normal or gamma distributions, and similar to the size distributions of annotated proteins. Conclusions/Significance: Our findings suggest stochastic processes have played a primary role in the evolution of genome complexity, and that common processes govern the conservation and loss of functional genomics units in both prokaryotes and eukaryotes.8 page(s

Effects of Blood Collection Conditions on Ovarian Cancer Serum Markers

Evaluating diagnostic and early detection biomarkers requires comparing serum protein concentrations among biosamples ascertained from subjects with and without cancer. Efforts are generally made to standardize blood processing and storage conditions for cases and controls, but blood sample collection conditions cannot be completely controlled. For example, blood samples from cases are often obtained from persons aware of their diagnoses, and collected after fasting or in surgery, whereas blood samples from some controls may be obtained in different conditions, such as a clinic visit. By measuring the effects of differences in collection conditions on three different markers, we investigated the potential of these effects to bias validation studies.We analyzed serum concentrations of three previously studied putative ovarian cancer serum biomarkers-CA 125, Prolactin and MIF-in healthy women, women with ovarian cancer undergoing gynecologic surgery, women undergoing surgery for benign ovary pathology, and women undergoing surgery with pathologically normal ovaries. For women undergoing surgery, a blood sample was collected either in the clinic 1 to 39 days prior to surgery, or on the day of surgery after anesthesia was administered but prior to the surgical procedure, or both. We found that one marker, prolactin, was dramatically affected by collection conditions, while CA 125 and MIF were unaffected. Prolactin levels were not different between case and control groups after accounting for the conditions of sample collection, suggesting that sample ascertainment could explain some or all of the previously reported results about its potential as a biomarker for ovarian cancer.Biomarker validation studies should use standardized collection conditions, use multiple control groups, and/or collect samples from cases prior to influence of diagnosis whenever feasible to detect and correct for potential biases associated with sample collection