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Background: Body size, nutrition and socioeconomic position (SEP) in early life have been associated with a wide range of long-term health effects. Epigenetics is one possible mechanism through which these early life exposures can impact later life health. We conducted a systematic review examining the observational evidence for the impact of body size, nutrition and SEP in early life on the epigenome in humans. Methods: This systematic review is registered with the PROSPERO database (registration number: CRD42016050193). Three datasets were simultaneously searched using Ovid and the resulting studies were evaluated by at least two independent reviewers. Studies measuring epigenetic markers either at the same time as, or after, the early life exposure and have a measure of body size, nutrition or SEP in early life (up to 12 years), written in English and from a community-dwelling participants were included. Results: We identified 90 eligible studies. Seventeen of these papers examined more than one early life exposure of interest. Fifty six papers examined body size, 37 nutrition and 17 SEP. All of the included papers examined DNA methylation (DNAm) as the epigenetic marker. Overall there was no strong evidence for a consistent association between these early life variables in DNAm which may be due to the heterogeneous study designs, data collection methods and statistical analyses. Conclusions: Despite these inconclusive results, the hypothesis that the early life environment can impact DNAm, potentially persisting into adult life, was supported by some studies and warrants further investigation. We provide recommendations for future studies. [ABSTRACT FROM AUTHOR]

This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has. [ABSTRACT FROM AUTHOR]

The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods—Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets. [ABSTRACT FROM AUTHOR]

Coordination is essential for improving supply chain performance, and one of the most critical factors in achieving the coordination of a supply chain is the integrated research of production and distribution. In this paper, a novel two-stage hybrid solution methodology is proposed. In the first stage, products are processed on the serial machines of multiple manufacturers located in two industrial parks. A fuzzy multi-objective scheduling optimization is performed using a modified non-dominated sorting genetic algorithm II (NSGA-II). The result obtained in the first stage is used in the second stage to optimize the distribution scheduling problem using a modified genetic annealing algorithm (GAA). Finally, simulation results verify both the feasibility and efficiency of the proposed solution methodology. [ABSTRACT FROM AUTHOR]

In clinical neuropsychology the cognitive abilities of neurological patients are commonly estimated using well-established paper-based tests. Typically, scores on some tests remain relatively well preserved, whilst others exhibit a significant and disproportionate decline. Scores on those tests that measure preserved cognitive functions (so-called ‘hold’ tests) may be used to estimate premorbid abilities, including scores in non-hold tests that would have been expected prior to the onset of cognitive impairment. Many hold tests entail word reading, with each word being graded as correctly or incorrectly pronounced. Inevitably, such tests are likely to contain words that provide little or no diagnostic power (i.e., can be eliminated without negatively affecting prediction accuracy). In this paper, a genetic algorithm is developed and demonstrated, using n = 92 neurologically healthy participants, to identify optimal word subsets from the National Adult Reading Test that minimize the mean error in predicting the most widely used clinical measure of IQ and cognitive ability, the Wechsler Adult Intelligence Scale Fourth Edition IQ. In addition to requiring only 17–20 of the original 50 words (suggesting that this test could be revised to be up to 66% shorter) and minimizing mean prediction error, the algorithm increases the proportion of the variance in the predicted variable explained in comparison to using all words (from r2 = 0.46 to r2 = 0.61). In a clinical setting this would improve estimates of premorbid cognitive function and, if an abbreviated revision to this test were to be adopted, reduce the arduousness of the test for patients. The proposed method is evaluated with jackknifing and leave one out cross validation. The general approach may be used to optimize the relationship between any two psychological tests by finding the question subset in one test that minimizes the prediction error in a second test by training the genetic algorithm using data collected from participants upon whom both tests have been administered. This approach may also be used to develop new predictive tests, since it provides a method to identify an optimal subset of a set of candidate questions (for which empirical data have been collected) that maximizes prediction accuracy and the proportion of variance in the predicted variable that can be explained. [ABSTRACT FROM AUTHOR]

The problem that passengers are hard to take taxis while empty driving rate is high widely exists under the traditional taxi operation mode. The implementation of taxi carpooling mode can alleviate the problem in a certain extent. The objective of this study is to optimize the taxi carpooling path. Firstly, the taxi carpooling path optimization model with single objective and its extended model with multiple objectives are built respectively. Then, the single objective path optimization model of taxi carpooling is solved based on the improved single objective genetic algorithm, and the multiple-objective path optimization model of taxi carpooling is solved based on the improved multiple-objective genetic algorithm. Finally, a case study is carried out based on a road network with 24 nodes. The case study results show the path optimization models and algorithms of taxi carpooling proposed in the paper can quickly get the taxi carpooling path, and can increase the income of taxi driver while reduce the cost for passengers. [ABSTRACT FROM AUTHOR]

High-fat diet is associated with hypercholesterolemia and seminal alterations in White New Zealand rabbits. We have previously reported disorders in the development of the manchette-acrosome complex during spermiogenesis and decreased testicular efficiency in hypercholesterolemic rabbits. On the other hand, olive oil incorporated into the diet improves cholesterolemia and semen parameters affected in hypercholesterolemic rabbits. In this paper, we report the recovery—with the addition of olive oil to diet—from the sub-cellular mechanisms involved in the shaping of the sperm cell and testicular efficiency altered in hypercholesterolemic rabbits. Using morphological (structural, ultra-structural and immuno-fluorescence techniques) and cell biology techniques, a reorganization of the manchette and related structures was observed when olive oil was added to the high-fat diet. Specifically, actin filaments, microtubules and lipid rafts—abnormally distributed in hypercholesterolemic rabbits—were recovered with dietary olive oil supplementation. The causes of the decline in sperm count were studied in the previous report and here in more detail. These were attributed to the decrease in the efficiency index and also to the increase in the apoptotic percentage in testis from animals under the high-fat diet. Surprisingly, the addition of olive oil to the diet avoided the sub-cellular, efficiency and apoptosis changes observed in hypercholesterolemic rabbits. This paper reports the positive effects of the olive oil addition to the diet in the recovery of testicular efficiency and normal sperm shaping, mechanisms altered by hypercholesterolemia. [ABSTRACT FROM AUTHOR]

Organismal complexity broadly relates to the number of different cell types within an organism and generally increases across a phylogeny. Whilst gene expression will underpin organismal complexity, it has long been clear that a simple count of gene number is not a sufficient explanation. In this paper, we use open-access information from the Ensembl databases to quantify the functional diversity of human genes that are broadly involved in transcription. Functional diversity is described in terms of the numbers of paralogues, protein isoforms and structural domains for each gene. The change in functional diversity is then calculated for up to nine orthologues from the nematode worm to human and correlated to the change in cell-type number. Those with the highest correlation are subject to gene ontology term enrichment and interaction analyses. We found that a range of genes that encode proteins associated with dynamic changes to chromatin are good candidates to contribute to organismal complexity. [ABSTRACT FROM AUTHOR]

This paper investigates an improved genetic algorithm on multiple automated guided vehicle (multi-AGV) path planning. The innovations embody in two aspects. First, three-exchange crossover heuristic operators are used to produce more optimal offsprings for getting more information than with the traditional two-exchange crossover heuristic operators in the improved genetic algorithm. Second, double-path constraints of both minimizing the total path distance of all AGVs and minimizing single path distances of each AGV are exerted, gaining the optimal shortest total path distance. The simulation results show that the total path distance of all AGVs and the longest single AGV path distance are shortened by using the improved genetic algorithm. [ABSTRACT FROM AUTHOR]

Double cycling is an efficient tool to increase the efficiency of quay crane (QC) in container terminals. In this paper, an optimization model for double cycling is developed to optimize the operation sequence of multiple QCs. The objective is to minimize the makespan of the ship handling operation considering the ship balance constraint. To solve the model, an algorithm based on Lagrangian relaxation is designed. Finally, we compare the efficiency of the Lagrangian relaxation based heuristic with the branch-and-bound method and a genetic algorithm using instances of different sizes. The results of numerical experiments indicate that the proposed model can effectively reduce the unloading and loading times of QCs. The effects of the ship balance constraint are more notable when the number of QCs is high. [ABSTRACT FROM AUTHOR]

Collaborative beamforming (CBF) with a finite number of collaborating nodes (CNs) produces sidelobes that are highly dependent on the collaborating nodes’ locations. The sidelobes cause interference and affect the communication rate of unintended receivers located within the transmission range. Nulling is not possible in an open-loop CBF since the collaborating nodes are unable to receive feedback from the receivers. Hence, the overall sidelobe reduction is required to avoid interference in the directions of the unintended receivers. However, the impact of sidelobe reduction on the capacity improvement at the unintended receiver has never been reported in previous works. In this paper, the effect of peak sidelobe (PSL) reduction in CBF on the capacity of an unintended receiver is analyzed. Three meta-heuristic optimization methods are applied to perform PSL minimization, namely genetic algorithm (GA), particle swarm algorithm (PSO) and a simplified version of the PSO called the weightless swarm algorithm (WSA). An average reduction of 20 dB in PSL alongside 162% capacity improvement is achieved in the worst case scenario with the WSA optimization. It is discovered that the PSL minimization in the CBF provides capacity improvement at an unintended receiver only if the CBF cluster is small and dense. [ABSTRACT FROM AUTHOR]

SCCmec elements are very important mobile genetic elements in Staphylococci that carry beta-lactam resistance genes mecA/mecC, recombinase genes and a variety of accessory genes. Twelve main types and a couple of variants have yet been described. In addition, there are also other SCC elements harbouring other markers. In order to subtype strains of methicillin-resistant S. aureus (MRSA) based on variations within their SCCmec elements, 86 markers were selected from published SCC sequences for an assay based on multiplexed primer extension reactions followed by hybridisation to the specific probes. These included mecA/mecC, fusC, regulatory genes, recombinase genes, genes from ACME and heavy metal resistance loci as well as several genes of unknown function. Hybridisation patterns for published genome or SCC sequences were theoretically predicted. For validation of the microarray based assay and for stringent hybridisation protocol optimization, real hybridization experiments with fully sequenced reference strains were performed modifying protocols until yielded the results were in concordance to the theoretical predictions. Subsequently, 226 clinical isolates from two hospitals in the city of Dresden, Germany, were characterised in detail. Beside previously described types and subtypes, a wide variety of additional SCC types or subtypes and pseudoSCC elements were observed as well as numerous composite elements. Within the study collection, 61 different such elements have been identified. Since hybridisation cannot recognise the localisation of target genes, gene duplications or inversions, this is a rather conservative estimate. Interestingly, some widespread epidemic strains engulf distinct variants with different SCCmec subtypes. Notable examples are ST239-MRSA-III, CC5-, CC22-, CC30-, and CC45-MRSA-IV or CC398-MRSA-V. Conversely, identical SCC elements were observed in different strains with SCCmec IVa being spread among the highest number of Clonal Complexes. The proposed microarray can help to distinguish isolates that appear similar or identical by other typing methods and it can be used as high-throughput screening tool for the detection of putative new SCC types or variants that warrant further investigation and sequencing. The high degree of diversity of SCC elements even within so-called strains could be helpful for epidemiological typing. It also raises the question on scale and speed of the evolution of SCC elements. [ABSTRACT FROM AUTHOR]

Measurement of telomere length is crucial for the study of telomere maintenance and its role in molecular pathophysiology of diseases and in aging. Several methods are used to measure telomere length, the choice of which usually depends on the type and size of sample to be assayed, as well as cost and throughput considerations. The goal of this study was to investigate the factors that may influence the reliability of qPCR-based relative telomere length measurements in whole blood. Day to day intra-individual variability, types of blood anticoagulant, sample storage conditions, processing and site of blood draw were investigated. Two qPCR-based methods to measure telomere length (monoplex vs. multiplex) were also investigated and showed a strong correlation between them. Freezing and thawing of the blood and storage of the blood at 4°C for up to 4 days did not affect telomere length values. Telomere lengths in dried blood spots were significantly higher than both whole blood and peripheral mononuclear blood cells, and were highly correlated with both. We found that telomere length measurements were significantly higher in dried blood spots collected directly from fingertip prick compared to dried blood spots prepared with anticoagulated whole blood collected from the finger, and non-blotted whole blood taken from both finger and arm venipuncture. This suggests that DNA from cells blotted on paper is not equivalent to that collected from venipuncture whole blood, and caution should be taken when comparing between blood sample types. [ABSTRACT FROM AUTHOR]

Background: Tumor proliferation speed, most commonly assessed by counting of mitotic figures in histological slide preparations, is an important biomarker for breast cancer. Although mitosis counting is routinely performed by pathologists, it is a tedious and subjective task with poor reproducibility, particularly among non-experts. Inter- and intraobserver reproducibility of mitosis counting can be improved when a strict protocol is defined and followed. Previous studies have examined only the agreement in terms of the mitotic count or the mitotic activity score. Studies of the observer agreement at the level of individual objects, which can provide more insight into the procedure, have not been performed thus far. Methods: The development of automatic mitosis detection methods has received large interest in recent years. Automatic image analysis is viewed as a solution for the problem of subjectivity of mitosis counting by pathologists. In this paper we describe the results from an interobserver agreement study between three human observers and an automatic method, and make two unique contributions. For the first time, we present an analysis of the object-level interobserver agreement on mitosis counting. Furthermore, we train an automatic mitosis detection method that is robust with respect to staining appearance variability and compare it with the performance of expert observers on an “external” dataset, i.e. on histopathology images that originate from pathology labs other than the pathology lab that provided the training data for the automatic method. Results: The object-level interobserver study revealed that pathologists often do not agree on individual objects, even if this is not reflected in the mitotic count. The disagreement is larger for objects from smaller size, which suggests that adding a size constraint in the mitosis counting protocol can improve reproducibility. The automatic mitosis detection method can perform mitosis counting in an unbiased way, with substantial agreement with human experts. [ABSTRACT FROM AUTHOR]

Our understanding of how chromosomes structurally organize and dynamically interact has been revolutionized through the lens of long-chain polymer physics. Major protein contributors to chromosome structure and dynamics are condensin and cohesin that stochastically generate loops within and between chains, and entrap proximal strands of sister chromatids. In this paper, we explore the ability of transient, protein-mediated, gene-gene crosslinks to induce clusters of genes, thereby dynamic architecture, within the highly repeated ribosomal DNA that comprises the nucleolus of budding yeast. We implement three approaches: live cell microscopy; computational modeling of the full genome during G1 in budding yeast, exploring four decades of timescales for transient crosslinks between 5kbp domains (genes) in the nucleolus on Chromosome XII; and, temporal network models with automated community (cluster) detection algorithms applied to the full range of 4D modeling datasets. The data analysis tools detect and track gene clusters, their size, number, persistence time, and their plasticity (deformation). Of biological significance, our analysis reveals an optimal mean crosslink lifetime that promotes pairwise and cluster gene interactions through “flexible” clustering. In this state, large gene clusters self-assemble yet frequently interact (merge and separate), marked by gene exchanges between clusters, which in turn maximizes global gene interactions in the nucleolus. This regime stands between two limiting cases each with far less global gene interactions: with shorter crosslink lifetimes, “rigid” clustering emerges with clusters that interact infrequently; with longer crosslink lifetimes, there is a dissolution of clusters. These observations are compared with imaging experiments on a normal yeast strain and two condensin-modified mutant cell strains. We apply the same image analysis pipeline to the experimental and simulated datasets, providing support for the modeling predictions. [ABSTRACT FROM AUTHOR]

Hydroxymethylcytosine (5hmC) methylation is a well-known epigenetic mark that is involved in gene regulation and may impact genome stability. To investigate a possible role of 5hmC in cancer development and progression, one must be able to detect and quantify its level first. In this paper, we address the issue of 5hmC detection at a single base resolution, starting with consideration of the well-established 5hmC measure Δβ and, in particular, with an analysis of its properties, both analytically and empirically. Then we propose several alternative hydroxymethylation measures and compare their properties with those of Δβ. In the absence of a gold standard, the (pairwise) resemblance of those 5hmC measures to Δβ is characterized by means of a similarity analysis and relative accuracy analysis. All results are illustrated on matched healthy and cancer tissue data sets as derived by means of bisulfite (BS) and oxidative bisulfite converting (oxBS) procedures. [ABSTRACT FROM AUTHOR]

The symbiosis between rhizobia and legumes is characterized by a complex molecular dialogue in which the bacterial NodD protein plays a major role due to its capacity to activate the expression of the nodulation genes in the presence of appropiate flavonoids. These genes are involved in the synthesis of molecules, the nodulation factors (NF), responsible for launching the nodulation process. Rhizobium tropici CIAT 899, a rhizobial strain that nodulates Phaseolus vulgaris, is characterized by its tolerance to multiple environmental stresses such as high temperatures, acidity or elevated osmolarity. This strain produces nodulation factors under saline stress and the same set of CIAT 899 nodulation genes activated by inducing flavonoids are also up-regulated in a process controlled by the NodD2 protein. In this paper, we have studied the effect of osmotic stress (high mannitol concentrations) on the R. tropici CIAT 899 transcriptomic response. In the same manner as with saline stress, the osmotic stress mediated NF production and export was controlled directly by NodD2. In contrast to previous reports, the nodA2FE operon and the nodA3 and nodD1 genes were up-regulated with mannitol, which correlated with an increase in the production of biologically active NF. Interestingly, in these conditions, this regulatory protein controlled not only the expression of nodulation genes but also the expression of other genes involved in protein folding and synthesis, motility, synthesis of polysaccharides and, surprinsingly, nitrogen fixation. Moreover, the non-metabolizable sugar dulcitol was also able to induce the NF production and the activation of nod genes in CIAT 899. [ABSTRACT FROM AUTHOR]

Complex eukaryotic promoters normally contain multiple cis-regulatory sequences for different transcription factors (TFs). The binding patterns of the TFs to these sites, as well as the way the TFs interact with each other and with the RNA polymerase (RNAp), lead to combinatorial problems rarely understood in detail, especially under varying epigenetic conditions. The aim of this paper is to build a model describing how the main regulatory cluster of the olfactory receptor Or59b drives transcription of this gene in Drosophila. The cluster-driven expression of this gene is represented as the equilibrium probability of RNAp being bound to the promoter region, using a statistical thermodynamic approach. The RNAp equilibrium probability is computed in terms of the occupancy probabilities of the single TFs of the cluster to the corresponding binding sites, and of the interaction rules among TFs and RNAp, using experimental data of Or59b expression to tune the model parameters. The model reproduces correctly the changes in RNAp binding probability induced by various mutation of specific sites and epigenetic modifications. Some of its predictions have also been validated in novel experiments. [ABSTRACT FROM AUTHOR]

Many different time-series methods have been widely used in forecast stock prices for earning a profit. However, there are still some problems in the previous time series models. To overcome the problems, this paper proposes a hybrid time-series model based on a feature selection method for forecasting the leading industry stock prices. In the proposed model, stepwise regression is first adopted, and multivariate adaptive regression splines and kernel ridge regression are then used to select the key features. Second, this study constructs the forecasting model by a genetic algorithm to optimize the parameters of support vector regression. To evaluate the forecasting performance of the proposed models, this study collects five leading enterprise datasets in different industries from 2003 to 2012. The collected stock prices are employed to verify the proposed model under accuracy. The results show that proposed model is better accuracy than the other listed models, and provide persuasive investment guidance to investors. [ABSTRACT FROM AUTHOR]

Telomeres protect against chromosomal damage. Accelerated telomere loss has been associated with premature aging syndromes such as Werner’s syndrome and Dyskeratosis Congenita, while, progressive telomere loss activates a DNA damage response leading to chromosomal instability, typically observed in cancer cells and senescent cells. Therefore, identifying mechanisms of telomere length maintenance is critical for understanding human pathologies. In this paper we demonstrate that mitochondrial dysfunction plays a causal role in telomere shortening. Furthermore, hnRNPA2, a mitochondrial stress responsive lysine acetyltransferase (KAT) acetylates telomere histone H4at lysine 8 of (H4K8) and this acetylation is associated with telomere attrition. Cells containing dysfunctional mitochondria have higher telomere H4K8 acetylation and shorter telomeres independent of cell proliferation rates. Ectopic expression of KAT mutant hnRNPA2 rescued telomere length possibly due to impaired H4K8 acetylation coupled with inability to activate telomerase expression. The phenotypic outcome of telomere shortening in immortalized cells included chromosomal instability (end-fusions) and telomerase activation, typical of an oncogenic transformation; while in non-telomerase expressing fibroblasts, mitochondrial dysfunction induced-telomere attrition resulted in senescence. Our findings provide a mechanistic association between dysfunctional mitochondria and telomere loss and therefore describe a novel epigenetic signal for telomere length maintenance. [ABSTRACT FROM AUTHOR]

Telomere length (TL) has been associated with a range of aging outcomes as well as mortality. Recent research has shown both high heritability (~70%) of TL as well as moderate spousal similarity (r~0.3) using European datasets. This paper explores the level of spousal concordance in telomere length in the Health and Retirement Study, a national sample of adults in the US. The results show that the spousal correlations are lower (r~0.11). Regression-based associations in TL in the US are low (beta~0.08) and also vary by the number of times respondents have been married, where spouses married a single time have higher associations in TL (beta~.12) than spouses married more once (beta~0.03). I also find variation in spousal TL association levels based on husband’s education level. These findings suggest the possibility of both assortative mating patterns related to telomere length as well as likelihood of shared environmental factors that cause TL similarity in people who are socially connected. [ABSTRACT FROM AUTHOR]

Several modern genomic technologies, such as DNA-Methylation arrays, measure spatially registered probes that number in the hundreds of thousands across multiple chromosomes. The measured probes are by themselves less interesting scientifically; instead scientists seek to discover biologically interpretable genomic regions comprised of contiguous groups of probes which may act as biomarkers of disease or serve as a dimension-reducing pre-processing step for downstream analyses. In this paper, we introduce an unsupervised feature learning technique which maps technological units (probes) to biological units (genomic regions) that are common across all subjects. We use ideas from fusion penalties and convex clustering to introduce a method for Spatial Convex Clustering, or SpaCC. Our method is specifically tailored to detecting multi-subject regions of methylation, but we also test our approach on the well-studied problem of detecting segments of copy number variation. We formulate our method as a convex optimization problem, develop a massively parallelizable algorithm to find its solution, and introduce automated approaches for handling missing values and determining tuning parameters. Through simulation studies based on real methylation and copy number variation data, we show that SpaCC exhibits significant performance gains relative to existing methods. Finally, we illustrate SpaCC’s advantages as a pre-processing technique that reduces large-scale genomics data into a smaller number of genomic regions through several cancer epigenetics case studies on subtype discovery, network estimation, and epigenetic-wide association. [ABSTRACT FROM AUTHOR]

Drosophila melanogaster polytene chromosomes display specific banding pattern; the underlying genetic organization of this pattern has remained elusive for many years. In the present paper, we analyze 32 cytology-mapped polytene chromosome interbands. We estimated molecular locations of these interbands, described their molecular and genetic organization and demonstrate that polytene chromosome interbands contain the 5′ ends of housekeeping genes. As a rule, interbands display preferential “head-to-head” orientation of genes. They are enriched for “broad” class promoters characteristic of housekeeping genes and associate with open chromatin proteins and Origin Recognition Complex (ORC) components. In two regions, 10A and 100B, coding sequences of genes whose 5′-ends reside in interbands map to constantly loosely compacted, early-replicating, so-called “grey” bands. Comparison of expression patterns of genes mapping to late-replicating dense bands vs genes whose promoter regions map to interbands shows that the former are generally tissue-specific, whereas the latter are represented by ubiquitously active genes. Analysis of RNA-seq data (modENCODE-FlyBase) indicates that transcripts from interband-mapping genes are present in most tissues and cell lines studied, across most developmental stages and upon various treatment conditions. We developed a special algorithm to computationally process protein localization data generated by the modENCODE project and show that Drosophila genome has about 5700 sites that demonstrate all the features shared by the interbands cytologically mapped to date. [ABSTRACT FROM AUTHOR]

DNA methylation is an essential epigenetic modification involved in regulating the expression of mammalian genomes. A variety of experimental approaches to generate genome-wide or whole-genome DNA methylation data have emerged in recent years. Methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq) is one of the major tools used in whole-genome epigenetic studies. However, analyzing this data in terms of accuracy, sensitivity, and speed still remains an important challenge. Existing methods, such as BATMAN and MEDIPS, analyze MeDIP-seq data by dividing the whole genome into equal length windows and assume that each CpG of the same window has the same methylation level. More precise work is necessary to estimate the methylation level of each CpG site in the whole genome. In this paper, we propose a Statistical Inferences with MeDIP-seq Data (SIMD) to infer the methylation level for each CpG site. In addition, we analyze a real dataset for DNA methylation. The results show that our method displays improved precision in detecting differentially methylated CpG sites compared to the existing method. To meet the demands of the application, we have developed an R package called “SIMD”, which is freely available in . [ABSTRACT FROM AUTHOR]

Countries, research institutions, and scholars are interested in identifying and promoting high-impact and transformative scientific research. This paper presents a novel set of text- and citation-based metrics that can be used to identify high-impact and transformative works. The 11 metrics can be grouped into seven types: Radical-Generative, Radical-Destructive, Risky, Multidisciplinary, Wide Impact, Growing Impact, and Impact (overall). The metrics are exemplified, validated, and compared using a set of 10,778,696 MEDLINE articles matched to the Science Citation Index ExpandedTM. Articles are grouped into six 5-year periods (spanning 1983–2012) using publication year and into 6,159 fields constructed using comparable MeSH terms, with which each article is tagged. The analysis is conducted at the level of a field-period pair, of which 15,051 have articles and are used in this study. A factor analysis shows that transformativeness and impact are positively related (ρ = .402), but represent distinct phenomena. Looking at the subcomponents of transformativeness, there is no evidence that transformative work is adopted slowly or that the generation of important new concepts coincides with the obsolescence of existing concepts. We also find that the generation of important new concepts and highly cited work is more risky. Finally, supporting the validity of our metrics, we show that work that draws on a wider range of research fields is used more widely. [ABSTRACT FROM AUTHOR]

Background: Health in early life is crucial for health later in life. Exposure to air pollution during embryonic and early-life development can result in placental epigenetic modification and foetus reprogramming, which can influence disease susceptibility in later life. Objectives: The aim of this paper was to investigate the placental adaptation in the level of global DNA methylation and differential gene expression in the methylation cycle in new-borns exposed to high fine particulate matter in the foetal stage. Study design: This is a nested case-control study. We enrolled pregnant healthy women attending prenatal care clinics in Tehran, Iran, who were residents of selected polluted and unpolluted regions, before the 14th week of pregnancy. We calculated the regional background levels of particle mass- particles with aerodynamics diameter smaller than 2.5 μm (PM2.5) and 10 μm (PM10)—of two regions of interest. At the time of delivery, placental tissue was taken for gene expression and DNA methylation analyses. We also recorded birth outcomes (the new-born’s sex, birth date, birth weight and length, head and chest circumference, gestational age, Apgar score, and level of neonatal care required). Results: As regards PM2.5 and PM10 concentrations in different time windows of pregnancy, there were significantly independent positive correlations between PM10 and PM2.5 in the first trimester of all subjects and placental global DNA methylation levels (p-value = 0.01, p-value = 0.03, respectively). The gene expression analysis showed there was significant correlation between S-adenosylmethionine expression and PM2.5 (p = 0.003) and PM10 levels in the first trimester (p = 0.03). Conclusion: Our data showed prenatal exposures to air pollutants in the first trimester could influence placental adaptation by DNA methylation. [ABSTRACT FROM AUTHOR]

FAcilitates Chromatin Transcription (FACT) is a complex of SSRP1 and SPT16 that is involved in chromatin remodeling during transcription, replication, and DNA repair. FACT has been mostly studied in cell-free or single cell model systems because general FACT knockout (KO) is embryonically lethal (E3.5). FACT levels are limited to the early stages of development and stem cell niches of adult tissues. FACT is upregulated in poorly differentiated aggressive tumors. Importantly, FACT inhibition (RNAi) is lethal for tumors but not normal cells, making FACT a lucrative target for anticancer therapy. To develop a better understanding of FACT function in the context of the mammalian organism under normal physiological conditions and in disease, we aimed to generate a conditional FACT KO mouse model. Because SPT16 stability is dependent on the SSRP1-SPT16 association and the presence of SSRP1 mRNA, we targeted the Ssrp1 gene using a CreERT2- LoxP approach to generate the FACT KO model. Here, we highlight the limitations of the CreERT2-LoxP (Rosa26) system that we encountered during the generation of this model. In vitro studies showed an inefficient excision rate of ectopically expressed CreERT2 (retroviral CreERT2) in fibroblasts with homozygous floxed Ssrp1. In vitro and in vivo studies showed that the excision efficiency could only be increased with germline expression of two alleles of Rosa26CreERT2. The expression of one germline Rosa26CreERT2 allele led to the incomplete excision of Ssrp1. The limited efficiency of the CreERT2-LoxP system may be sufficient for studies involving the deletion of genes that interfere with cell growth or viability due to the positive selection of the phenotype. However, it may not be sufficient for studies that involve the deletion of genes supporting growth, or those crucial for development. Although CreERT2-LoxP is broadly used, it has limitations that have not been widely discussed. This paper aims to encourage such discussions. [ABSTRACT FROM AUTHOR]

This paper presents a limited-stop service for a bus fleet to meet the unbalanced demand of passengers on a bus route and to improve the transit service of the bus route. This strategy includes two parts: a degree assessment of unbalanced passenger demand and an optimization of the limited-stop service. The degree assessment of unbalanced passenger demand, which is based on the different passenger demand between stations and the unbalance of passengers within the station, is used to judge whether implementing the limited-stop service is necessary for a bus route. The optimization of limited-stop service considers the influence of stop skipping action and bus capacity on the left-over passengers to determine the proper skipping stations for the bus fleet serving the entire route by minimizing both the waiting time and in-vehicle time of passengers and the running time of vehicles. A solution algorithm based on genetic algorithm is also presented to evaluate the degree of unbalanced passenger demand and optimize the limited-stop scheme. Then, the proper strategy is tested on a bus route in Changchun city of China. The threshold of degree assessment of unbalanced passenger demand can be calibrated and adapted to different passenger demands. [ABSTRACT FROM AUTHOR]

In this paper, we introduce sequence-based multiscale modeling for biomolecular data analysis. We employ spectral clustering method in our modeling and reveal the difference between sequence-based global scale clustering and local scale clustering. Essentially, two types of distances, i.e., Euclidean (or spatial) distance and genomic (or sequential) distance, can be used in data clustering. Clusters from sequence-based global scale models optimize spatial distances, meaning spatially adjacent loci are more likely to be assigned into the same cluster. Sequence-based local scale models, on the other hand, result in clusters that optimize genomic distances. That is to say, in these models, sequentially adjoining loci tend to be cluster together. We propose two sequence-based multiscale models (SeqMMs) for the study of chromosome hierarchical structures, including genomic compartments and topological associated domains (TADs). We find that genomic compartments are determined only by global scale information in the Hi-C data. The removal of all the local interactions within a band region as large as 10 Mb in genomic distance has almost no significant influence on the final compartment results. Further, in TAD analysis, we find that when the sequential scale is small, a tiny variation of diagonal band region in a contact map will result in a great change in the predicted TAD boundaries. When the scale value is larger than a threshold value, the TAD boundaries become very consistent. This threshold value is highly related to TAD sizes. By the comparison of our results with those previously obtained using a spectral clustering model, we find that our method is more robust and reliable. Finally, we demonstrate that almost all TAD boundaries from both clustering methods are local minimum of a TAD summation function. [ABSTRACT FROM AUTHOR]

Computational analysis of promoters is hindered by the complexity of their architecture. In less studied genomes with complex organization, false positive promoter predictions are common. Accurate identification of transcription start sites and core promoter regions remains an unsolved problem. In this paper, we present a comprehensive analysis of genomic features associated with promoters and show that probabilistic integrative algorithms-driven models allow accurate classification of DNA sequence into “promoters” and “non-promoters” even in absence of the full-length cDNA sequences. These models may be built upon the maps of the distributions of sequence polymorphisms, RNA sequencing reads on genomic DNA, methylated nucleotides, transcription factor binding sites, as well as relative frequencies of nucleotides and their combinations. Positional clustering of binding sites shows that the cells of Oryza sativa utilize three distinct classes of transcription factors: those that bind preferentially to the [-500,0] region (188 “promoter-specific” transcription factors), those that bind preferentially to the [0,500] region (282 “5′ UTR-specific” TFs), and 207 of the “promiscuous” transcription factors with little or no location preference with respect to TSS. For the most informative motifs, their positional preferences are conserved between dicots and monocots. [ABSTRACT FROM AUTHOR]

Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm. [ABSTRACT FROM AUTHOR]

Energy demand is an important economic index, and demand forecasting has played a significant role in drawing up energy development plans for cities or countries. As the use of large datasets and statistical assumptions is often impractical to forecast energy demand, the GM(1,1) model is commonly used because of its simplicity and ability to characterize an unknown system by using a limited number of data points to construct a time series model. This paper proposes a genetic-algorithm-based remnant GM(1,1) (GARGM(1,1)) with sign estimation to further improve the forecasting accuracy of the original GM(1,1) model. The distinctive feature of GARGM(1,1) is that it simultaneously optimizes the parameter specifications of the original and its residual models by using the GA. The results of experiments pertaining to a real case of energy demand in China showed that the proposed GARGM(1,1) outperforms other remnant GM(1,1) variants. [ABSTRACT FROM AUTHOR]

SOX14 is a member of the SOX family of transcription factors mainly involved in the regulation of neural development. Recently, it became evident that SOX14 is one of four hypermethylated genes in cervical carcinoma, considered as a tumor suppressor candidate in this type of malignancy. In this paper we elucidated the role of SOX14 in the regulation of malignant properties of cervical carcinoma cells in vitro. Functional analysis performed in HeLa cells revealed that SOX14 overexpression decreased viability and promoted apoptosis through altering the expression of apoptosis related genes. Our results demonstrated that overexpression of SOX14 initiated accumulation of p53, demonstrating potential cross-talk between SOX14 and the p53 signaling pathway. Further analysis unambiguously showed that SOX14 triggered posttranslational modification of p53 protein, as detected by the significantly increased level of phospho-p53 (Ser-15) in SOX14-overexpressing HeLa cells. Moreover, the obtained results revealed that SOX14 activated p53 protein, which was confirmed by elevated p21Waf1/Cip1, a well known target gene of p53. This study advances our understanding about the role of SOX14 and might explain the molecular mechanism by which this transcription factor could exert tumor suppressor properties in cervical carcinoma. [ABSTRACT FROM AUTHOR]

DNA methylation is an important epigenetic modification regulating gene expression, genomic imprinting, transposon silencing and chromatin structure in plants and plays an important role in leaf senescence. However, the DNA methylation pattern during Gossypium hirsutum L. cotyledon senescence is poorly understood. In this study, global DNA methylation patterns were compared between two cotyledon development stages, young (J1) and senescence (J2), using methylated DNA immunoprecipitation (MeDIP-Seq). Methylated cytosine occurred mostly in repeat elements, especially LTR/Gypsy in both J1 and J2. When comparing J1 against J2, there were 1222 down-methylated genes and 623 up-methylated genes. Methylated genes were significantly enriched in carbohydrate metabolism, biosynthesis of other secondary metabolites and amino acid metabolism pathways. The global DNA methylation level decreased from J1 to J2, especially in gene promoters, transcriptional termination regions and regions around CpG islands. We further investigated the expression patterns of 9 DNA methyltransferase-associated genes and 2 DNA demethyltransferase-associated genes from young to senescent cotyledons, which were down-regulated during cotyledon development. In this paper, we first reported that senescent cotton cotyledons exhibited lower DNA methylation levels, primarily due to decreased DNA methyltransferase activity and which also play important role in regulating secondary metabolite process. [ABSTRACT FROM AUTHOR]

We performed a systematic review to identify all original publications describing the asymmetric inheritance of cellular organelles in normal animal eukaryotic cells and to critique the validity and imprecision of the evidence. Searches were performed in Embase, MEDLINE and Pubmed up to November 2015. Screening of titles, abstracts and full papers was performed by two independent reviewers. Data extraction and validity were performed by one reviewer and checked by a second reviewer. Study quality was assessed using the SYRCLE risk of bias tool, for animal studies and by developing validity tools for the experimental model, organelle markers and imprecision. A narrative data synthesis was performed. We identified 31 studies (34 publications) of the asymmetric inheritance of organelles after mitotic or meiotic division. Studies for the asymmetric inheritance of centrosomes (n = 9); endosomes (n = 6), P granules (n = 4), the midbody (n = 3), mitochondria (n = 3), proteosomes (n = 2), spectrosomes (n = 2), cilia (n = 2) and endoplasmic reticulum (n = 2) were identified. Asymmetry was defined and quantified by variable methods. Assessment of the statistical reliability of the results indicated only two studies (7%) were judged to have low concern, the majority of studies (77%) were 'unclear' and five (16%) were judged to have 'high concerns'; the main reasons were low technical repeats (<10). Assessment of model validity indicated that the majority of studies (61%) were judged to be valid, ten studies (32%) were unclear and two studies (7%) were judged to have 'high concerns'; both described 'stem cells' without providing experimental evidence to confirm this (pluripotency and self-renewal). Assessment of marker validity indicated that no studies had low concern, most studies were unclear (96.5%), indicating there were insufficient details to judge if the markers were appropriate. One study had high concern for marker validity due to the contradictory results of two markers for the same organelle. For most studies the validity and imprecision of results could not be confirmed. In particular, data were limited due to a lack of reporting of interassay variability, sample size calculations, controls and functional validation of organelle markers. An evaluation of 16 systematic reviews containing cell assays found that only 50% reported adherence to PRISMA or ARRIVE reporting guidelines and 38% reported a formal risk of bias assessment. 44% of the reviews did not consider how relevant or valid the models were to the research question. 75% reviews did not consider how valid the markers were. 69% of reviews did not consider the impact of the statistical reliability of the results. Future systematic reviews in basic or preclinical research should ensure the rigorous reporting of the statistical reliability of the results in addition to the validity of the methods. Increased awareness of the importance of reporting guidelines and validation tools is needed for the scientific community. [ABSTRACT FROM AUTHOR]

The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades; however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards this goal of incorporating biochemical data into ASD diagnosis, this paper analyzes measurements of metabolite concentrations of the folate-dependent one-carbon metabolism and transulfuration pathways taken from blood samples of 83 participants with ASD and 76 age-matched neurotypical peers. Fisher Discriminant Analysis enables multivariate classification of the participants as on the spectrum or neurotypical which results in 96.1% of all neurotypical participants being correctly identified as such while still correctly identifying 97.6% of the ASD cohort. Furthermore, kernel partial least squares is used to predict adaptive behavior, as measured by the Vineland Adaptive Behavior Composite score, where measurement of five metabolites of the pathways was sufficient to predict the Vineland score with an R2 of 0.45 after cross-validation. This level of accuracy for classification as well as severity prediction far exceeds any other approach in this field and is a strong indicator that the metabolites under consideration are strongly correlated with an ASD diagnosis but also that the statistical analysis used here offers tremendous potential for extracting important information from complex biochemical data sets. [ABSTRACT FROM AUTHOR]

This paper reports detailed FISH-based karyotypes for three diploid wheatgrass species Agropyron cristatum (L.) Beauv., Thinopyrum bessarabicum (Savul.&Rayss) A. Löve, Pseudoroegneria spicata (Pursh) A. Löve, the supposed ancestors of hexaploid Thinopyrum intermedium (Host) Barkworth & D.R.Dewey, compiled using DNA repeats and comparative genome analysis based on COS markers. Fluorescence in situ hybridization (FISH) with repetitive DNA probes proved suitable for the identification of individual chromosomes in the diploid JJ, StSt and PP genomes. Of the seven microsatellite markers tested only the (GAA)n trinucleotide sequence was appropriate for use as a single chromosome marker for the P. spicata AS chromosome. Based on COS marker analysis, the phylogenetic relationship between diploid wheatgrasses and the hexaploid bread wheat genomes was established. These findings confirmed that the J and E genomes are in neighbouring clusters. [ABSTRACT FROM AUTHOR]

Various systems have been proposed to support biological image analysis, with the intent of decreasing false annotations and reducing the heavy burden on biologists. These systems generally comprise a feature extraction method and a classification method. Task-oriented methods for feature extraction leverage characteristic images for each problem, and they are very effective at improving the classification accuracy. However, it is difficult to utilize such feature extraction methods for versatile task in practice, because few biologists specialize in Computer Vision and/or Pattern Recognition to design the task-oriented methods. Thus, in order to improve the usability of these supporting systems, it will be useful to develop a method that can automatically transform the image features of general propose into the effective form toward the task of their interest. In this paper, we propose a semi-supervised feature transformation method, which is formulated as a natural coupling of principal component analysis (PCA) and linear discriminant analysis (LDA) in the framework of graph-embedding. Compared with other feature transformation methods, our method showed favorable classification performance in biological image analysis. [ABSTRACT FROM AUTHOR]

Glechoma L. (Lamiaceae) is distributed in eastern Asia and Europe. Understanding chromosome evolution in Glechoma has been strongly hampered by its small chromosomes, constant karyotype and polyploidy. Here phylogenetic patterns and chromosomal variation in Glechoma species are considered, using genome sizes, chromosome mapping of 5S and 35S rDNAs by fluorescence in situ hybridisation (FISH), and phylogenetic analyses of internal transcribed spacers (nrITS) of 35S rDNA and 5S rDNA NTS sequences. Species and populations of Glechoma are tetraploid (2n = 36) with base chromosome number of x = 9. Four chromosomes carry pericentric 5S rDNA sites in their short arms in all the species. Two to four of these chromosomes also carry 35S rDNA in subterminal regions of the same arms. Two to four other chromosomes have 35S rDNA sites, all located subterminally within short arms; one individual possessed additional weak pericentric 35S rDNA signals on three other chromosomes. Five types of rDNA locus distribution have been defined on the basis of 35S rDNA variation, but none is species-specific, and most species have more than one type. Glechoma hederacea has four types. Genome size in Glechoma ranges from 0.80 to 0.94 pg (1C), with low levels of intrapopulational variation in all species. Phylogenetic analyses of ITS and NTS sequences distinguish three main clades coinciding with geographical distribution: European (G. hederacea–G. hirsuta), Chinese and Korean (G. longituba), and Japanese (G. grandis). The paper presents the first comparative cytogenetic analyses of Glechoma species including karyotype structure, rDNA location and number, and genome size interpreted in a phylogenetic context. The observed variation suggests that the genus is still in genomic flux. Genome size, but not rDNA loci number and distribution, provides a character for species delimitation which allows better inferences of interspecific relationships to be made, in the absence of well-defined morphological differentiation. [ABSTRACT FROM AUTHOR]

G-quadruplex structures (G4) are found throughout the human genome and are known to play a regulatory role in a variety of molecular processes. Structurally, they have many configurations and can form from one or more DNA strands. At the gene level, they regulate gene expression and protein synthesis. In this paper, chromosomal-level patterns of distribution are analyzed on the human genome to identify high-level distribution patterns potentially related to global functional processes. Here we show unique high density banding patterns on individual chromosomes that are highly correlated, appearing in a mirror pattern, across forward and reverse DNA strands. The highest density of G4 sequences occurs within four megabases of one end of most chromosomes and contains G4 motifs that bind with zinc finger proteins. These findings suggest that G4 may play a role in global chromosomal processes such as those found in meiosis. [ABSTRACT FROM AUTHOR]

Due to its palindromic setup, AZFc (Azoospermia Factor c) region of chromosome Y is one of the most unstable regions of the human genome. It contains eight gene families expressed mainly in the testes. Several types of rearrangement resulting in changes in the cumulative copy number of the gene families were reported to be associated with diseases such as male infertility and testicular germ cell tumors. The best studied AZFc rearrangement is gr/gr deletion. Its carriers show widespread phenotypic variation from azoospermia to normospermia. This phenomenon was initially attributed to different gr/gr subtypes that would eliminate distinct members of the affected gene families. However, studies conducted to confirm this hypothesis have brought controversial results, perhaps, in part, due to the shortcomings of the utilized subtyping methodology. This proof-of-concept paper is meant to introduce here a novel method aimed at subtyping AZFc rearrangements. It is able to differentiate the partial deletion and partial duplication subtypes of the Deleted in Azoospermia (DAZ) gene family. The keystone of the method is the determination of the copy number of the gene family member-specific variant(s) in a series of sequence family variant (SFV) positions. Most importantly, we present a novel approach for the correct interpretation of the variant copy number data to determine the copy number of the individual DAZ family members in the context of frequent interloci gene conversion.Besides DAZ1/DAZ2 and DAZ3/DAZ4 deletions, not yet described rearrangements such as DAZ2/DAZ4 deletion and three duplication subtypes were also found by the utilization of the novel approach. A striking feature is the extremely high concordance among the individual data pointing to a certain type of rearrangement. In addition to being able to identify DAZ deletion subtypes more reliably than the methods used previously, this approach is the first that can discriminate DAZ duplication subtypes as well. [ABSTRACT FROM AUTHOR]

This paper presents ChroTeMo, a tool for chromosome territory modelling, accompanied by ChroTeVi–a chromosome territory visualisation software that uses the data obtained by ChroTeMo. These tools have been developed in order to complement the molecular cytogenetic research of interphase nucleus structure in a model grass Brachypodium distachyon. Although the modelling tool has been initially created for one particular species, it has universal application. The proposed version of ChroTeMo allows for generating a model of chromosome territory distribution in any given plant or animal species after setting the initial, species-specific parameters. ChroTeMo has been developed as a fully probabilistic modeller. Due to this feature, the comparison between the experimental data on the structure of a nucleus and the results obtained from ChroTeMo can indicate whether the distribution of chromosomes inside a nucleus is also fully probabilistic or is subjected to certain non-random patterns. The presented tools have been written in Python, so they are multiplatform, portable and easy to read. Moreover, if necessary they can be further developed by users writing their portions of code. The source code, documentation, and wiki, as well as the issue tracker and the list of related articles that use ChroTeMo and ChroTeVi, are accessible in a public repository at Github under GPL 3.0 license. [ABSTRACT FROM AUTHOR]

The promise of portable diagnostic devices relies on three basic requirements: comparable sensitivity to established platforms, inexpensive manufacturing and cost of operations, and the ability to survive rugged field conditions. Solid state nanopores can meet all these requirements, but to achieve high manufacturing yields at low costs, assays must be tolerant to fabrication imperfections and to nanopore enlargement during operation. This paper presents a model for molecular engineering techniques that meets these goals with the aim of detecting target sequences within DNA. In contrast to methods that require precise geometries, we demonstrate detection using a range of pore geometries. As a result, our assay model tolerates any pore-forming method and in-situ pore enlargement. Using peptide nucleic acid (PNA) probes modified for conjugation with synthetic bulk-adding molecules, pores ranging 15-50 nm in diameter are shown to detect individual PNA-bound DNA. Detection of the CFTRΔF508 gene mutation, a codon deletion responsible for ∼66% of all cystic fibrosis chromosomes, is demonstrated with a 26-36 nm pore size range by using a size-enhanced PNA probe. A mathematical framework for assessing the statistical significance of detection is also presented. [ABSTRACT FROM AUTHOR]

Correct pairing, synapsis and recombination between homologous chromosomes are essential for normal meiosis. All these events are strongly regulated, and our knowledge of the mechanisms involved in this regulation is increasing rapidly. Chromosomal rearrangements are known to disturb these processes. In the present paper, synapsis and recombination (number and distribution of MLH1 foci) were studied in three boars (Sus scrofa domestica) carrying different chromosomal rearrangements. One (T34he) was heterozygote for the t(3;4)(p1.3;q1.5) reciprocal translocation, one (T34ho) was homozygote for that translocation, while the third (T34Inv) was heterozygote for both the translocation and a pericentric inversion inv(4)(p1.4;q2.3). All three boars were normal for synapsis and sperm production. This particular situation allowed us to rigorously study the impact of rearrangements on recombination. Overall, the rearrangements induced only minor modifications of the number of MLH1 foci (per spermatocyte or per chromosome) and of the length of synaptonemal complexes for chromosomes 3 and 4. The distribution of MLH1 foci in T34he was comparable to that of the controls. Conversely, the distributions of MLH1 foci on chromosome 4 were strongly modified in boar T34Inv (lack of crossover in the heterosynaptic region of the quadrivalent, and crossover displaced to the chromosome extremities), and also in boar T34ho (two recombination peaks on the q-arms compared with one of higher magnitude in the controls). Analyses of boars T34he and T34Inv showed that the interference was propagated through the breakpoints. A different result was obtained for boar T34ho, in which the breakpoints (transition between SSC3 and SSC4 chromatin on the bivalents) seemed to alter the transmission of the interference signal. Our results suggest that the number of crossovers and crossover interference could be regulated by partially different mechanisms. [ABSTRACT FROM AUTHOR]

This paper reports a quantitative genetics and genomic analysis of undesirable coat color patterns in goats. Two undesirable coat colors have routinely been recorded for the past 15 years in French Saanen goats. One fifth of Saanen females have been phenotyped “pink” (8.0%) or “pink neck” (11.5%) and consequently have not been included in the breeding program as elite animals. Heritability of the binary “pink” and “pink neck” phenotype, estimated from 103,443 females was 0.26 for “pink” and 0.21 for “pink neck”. Genome wide association studies (using haplotypes or single SNPs) were implemented using a daughter design of 810 Saanen goats sired by 9 Artificial Insemination bucks genotyped with the goatSNP50 chip. A highly significant signal (-log10pvalue = 10.2) was associated with the “pink neck” phenotype on chromosome 11, suggesting the presence of a major gene. Highly significant signals for the “pink” phenotype were found on chromosomes 5 and 13 (-log10p values of 7.2 and, 7.7 respectively). The most significant SNP on chromosome 13 was in the ASIP gene region, well known for its association with coat color phenotypes. Nine significant signals were also found for both traits. The highest signal for each trait was detected by both single SNP and haplotype approaches, whereas the smaller signals were not consistently detected by the two methods. Altogether these results demonstrated a strong genetic control of the “pink” and “pink neck” phenotypes in French Saanen goats suggesting that SNP information could be used to identify and remove undesired colored animals from the breeding program. [ABSTRACT FROM AUTHOR]

Phytophthora root rot caused by Phytophthora capsici (P. capsici) is a serious limitation to pepper production in Southern China, with high temperature and humidity. Mapping PRR resistance genes can provide linked DNA markers for breeding PRR resistant varieties by molecular marker-assisted selection (MAS). Two BC1 populations and an F2 population derived from a cross between P. capsici-resistant accession, Criollo de Morelos 334 (CM334) and P. capsici-susceptible accession, New Mexico Capsicum Accession 10399 (NMCA10399) were used to investigate the genetic characteristics of PRR resistance. PRR resistance to isolate Byl4 (race 3) was controlled by a single dominant gene, PhR10, that was mapped to an interval of 16.39Mb at the end of the long arm of chromosome 10. Integration of bulked segregant analysis (BSA) and Specific Length Amplified Fragment sequencing (SLAF-seq) provided an efficient genetic mapping strategy. Ten polymorphic Simple Sequence Repeat (SSR) markers were found within this region and used to screen the genotypes of 636 BC1 plants, delimiting PhR10 to a 2.57 Mb interval between markers P52-11-21 (1.5 cM away) and P52-11-41 (1.1 cM). A total of 163 genes were annotated within this region and 31 were predicted to be associated with disease resistance. PhR10 is a novel race specific gene for PRR, and this paper describes linked SSR markers suitable for marker-assisted selection of PRR resistant varieties, also laying a foundation for cloning the resistance gene. [ABSTRACT FROM AUTHOR]

Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in ), particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur) and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among chromosomes in the Uyghur, with a large region of excess French ancestry harboring a gene with a known disease association. Similar variation was detected in the mouse hybrid zone, with notable constancy in regions of excess ancestry among admixed populations. By filling what has been an analytical gap, the proposed method should be a useful tool for many biologists. A computer program (), written in , has been developed based on the proposed method and is available on-line at . [ABSTRACT FROM AUTHOR]

Background: Pyrosequencing has emerged as an alternative method of nucleic acid sequencing, well suited for many applications which aim to characterize single nucleotide polymorphisms, mutations, microbial types and CpG methylation in the target DNA. The commercially available pyrosequencing systems can harbor two different types of software which allow analysis in AQ or CpG mode, respectively, both widely employed for DNA methylation analysis. Objective: Aim of the study was to assess the performance for DNA methylation analysis at CpG sites of the two pyrosequencing software which allow analysis in AQ or CpG mode, respectively. Despite CpG mode having been specifically generated for CpG methylation quantification, many investigations on this topic have been carried out with AQ mode. As proof of equivalent performance of the two software for this type of analysis is not available, the focus of this paper was to evaluate if the two modes currently used for CpG methylation assessment by pyrosequencing may give overlapping results. Methods: We compared the performance of the two software in quantifying DNA methylation in the promoter of selected genes (GSTP1, MGMT, LINE-1) by testing two case series which include DNA from paraffin embedded prostate cancer tissues (PC study, N = 36) and DNA from blood fractions of healthy people (DD study, N = 28), respectively. Results: We found discrepancy in the two pyrosequencing software-based quality assignment of DNA methylation assays. Compared to the software for analysis in the AQ mode, less permissive criteria are supported by the Pyro Q-CpG software, which enables analysis in CpG mode. CpG mode warns the operators about potential unsatisfactory performance of the assay and ensures a more accurate quantitative evaluation of DNA methylation at CpG sites. Conclusion: The implementation of CpG mode is strongly advisable in order to improve the reliability of the methylation analysis results achievable by pyrosequencing. [ABSTRACT FROM AUTHOR]

The identification of body fluids is an essential tool for clarifying the course of events at a criminal site. The analytical problem is the fact that the biological material has been very often exposed to detrimental exogenous influences. Thereby, the molecular substrates used for the identification of the traces may become degraded. So far, most protocols utilize cell specific proteins or RNAs. Instead of measuring these more sensitive compounds this paper describes the application of the differential DNA-methylation. As a result of two genome wide screenings with the Illumina HumanMethylation BeadChips 27 and 450k we identified 150 candidate loci revealing differential methylation with regard to the body fluids venous blood, menstrual blood, vaginal fluid, saliva and sperm. Among them we selected 9 loci as the most promising markers. For the final determination of the methylation degree we applied the SNuPE-method. Because the degree of methylation might be modified by various endogenous and exogenous factors, we tested each marker with approximately 100 samples of each target fluid in a validation study. The stability of the detection procedure is proved in various simulated forensic surroundings according to standardized conditions. We studied the potential influence of 12 relatively common tumors on the methylation of the 9 markers. For this purpose the target fluids of 34 patients have been analysed. Only the cervix carcinoma might have an remarkable effect because impairing the signal of both vaginal markers. Using the Illumina MiSeq device we tested the potential influence of cis acting sequence variants on the methylation degree of the 9 markers in the specific body fluid DNA of 50 individuals. For 4 marker loci we observed such an influence either by sole SNPs or haplotypes. The identification of each target fluid is possible in arbitrary mixtures with the remaining four body fluids. The sensitivity of the individual body fluid tests is in the same range as for the forensic STR-analysis. It is the first forensic body fluid protocol which considers the exogenic and endogenic parameters potentially interfering with the true results. [ABSTRACT FROM AUTHOR]

In the Drosophila oogenesis, germline stem cells (GSCs) continuously self-renew and differentiate into daughter cells for consecutive germline lineage commitment. This developmental process has become an in vivo working platform for studying adult stem cell fate regulation. An increasing number of studies have shown that while concerted actions of extrinsic signals from the niche and intrinsic regulatory machineries control GSC self-renewal and germline differentiation, epigenetic regulation is implicated in the process. Here, we report that Brahma (Brm), the ATPase subunit of the Drosophila SWI/SNF chromatin-remodeling complexes, is required for maintaining GSC fate. Removal or knockdown of Brm function in either germline or niche cells causes a GSC loss, but does not disrupt normal germline differentiation within the germarium evidenced at the molecular and morphological levels. There are two Drosophila SWI/SNF complexes: the Brm-associated protein (BAP) complex and the polybromo-containing BAP (PBAP) complex. More genetic studies reveal that mutations in polybromo/bap180, rather than gene encoding Osa, the BAP complex-specific subunit, elicit a defect in GSC maintenance reminiscent of the brm mutant phenotype. Further genetic interaction test suggests a functional association between brm and polybromo in controlling GSC self-renewal. Taken together, studies in this paper provide the first demonstration that Brm in the form of the PBAP complex functions in the GSC fate regulation. [ABSTRACT FROM AUTHOR]