MouseIndelDB: a database integrating genomic indel polymorphisms that distinguish mouse strains

MouseIndelDB is an integrated database resource containing thousands of previously unreported mouse genomic indel (insertion and deletion) polymorphisms ranging from ∼100 nt to 10 Kb in size. The database currently includes polymorphisms identified from our alignment of 26 million whole-genome shotgun sequence traces from four laboratory mouse strains mapped against the reference C57BL/6J genome using GMAP. They can be queried on a local level by chromosomal coordinates, nearby gene names or other genomic feature identifiers, or in bulk format using categories including mouse strain(s), class of polymorphism(s) and chromosome number. The results of such queries are presented either as a custom track on the UCSC mouse genome browser or in tabular format. We anticipate that the MouseIndelDB database will be widely useful for research in mammalian genetics, genomics, and evolutionary biology. Access to the MouseIndelDB database is freely available at: http://variation.osu.edu/

Generating confidence intervals on biological networks

<p>Abstract</p> <p>Background</p> <p>In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interacting nodes. The structure of the network may introduce dependencies among the nodes and it will in general be necessary to account for these dependencies in the statistical analysis. To this end we require some form of Null model of the network: generally rewired replicates of the network are generated which preserve only the degree (number of interactions) of each node. We show that this can fail to capture important features of network structure, and may result in unrealistic significance levels, when potentially confounding additional information is available.</p> <p>Methods</p> <p>We present a new network resampling Null model which takes into account the degree sequence as well as available biological annotations. Using gene ontology information as an illustration we show how this information can be accounted for in the resampling approach, and the impact such information has on the assessment of statistical significance of correlations and motif-abundances in the <it>Saccharomyces cerevisiae </it>protein interaction network. An algorithm, GOcardShuffle, is introduced to allow for the efficient construction of an improved Null model for network data.</p> <p>Results</p> <p>We use the protein interaction network of <it>S. cerevisiae</it>; correlations between the evolutionary rates and expression levels of interacting proteins and their statistical significance were assessed for Null models which condition on different aspects of the available data. The novel GOcardShuffle approach results in a Null model for annotated network data which appears better to describe the properties of real biological networks.</p> <p>Conclusion</p> <p>An improved statistical approach for the statistical analysis of biological network data, which conditions on the available biological information, leads to qualitatively different results compared to approaches which ignore such annotations. In particular we demonstrate the effects of the biological organization of the network can be sufficient to explain the observed similarity of interacting proteins.</p

Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins

<p>Abstract</p> <p>Background</p> <p>Phylogenies capture the evolutionary ancestry linking extant species. Correlations and similarities among a set of species are mediated by and need to be understood in terms of the phylogenic tree. In a similar way it has been argued that biological networks also induce correlations among sets of interacting genes or their protein products.</p> <p>Results</p> <p>We develop suitable statistical resampling schemes that can incorporate these two potential sources of correlation into a single inferential framework. To illustrate our approach we apply it to protein interaction data in yeast and investigate whether the phylogenetic trees of interacting proteins in a panel of yeast species are more similar than would be expected by chance.</p> <p>Conclusions</p> <p>While we find only negligible evidence for such increased levels of similarities, our statistical approach allows us to resolve the previously reported contradictory results on the levels of co-evolution induced by protein-protein interactions. We conclude with a discussion as to how we may employ the statistical framework developed here in further functional and evolutionary analyses of biological networks and systems.</p

Advances in research on the use of biochar in soil for remediation: a review

Purpose: Soil contamination mainly from human activities remains a major environmental problem in the contemporary world. Significant work has been undertaken to position biochar as a readily-available material useful for the management of contaminants in various environmental media notably soil. Here, we review the increasing research on the use of biochar in soil for the remediation of some organic and inorganic contaminants.  Materials and methods: Bibliometric analysis was carried out within the past 10 years to determine the increasing trend in research related to biochar in soil for contaminant remediation. Five exemplar contaminants were reviewed in both laboratory and field-based studies. These included two inorganic (i.e., As and Pb) and three organic classes (i.e., sulfamethoxazole, atrazine, and PAHs). The contaminants were selected based on bibliometric data and as representatives of their various contaminant classes. For example, As and Pb are potentially toxic elements (anionic and cationic, respectively), while sulfamethoxazole, atrazine, and PAHs represent antibiotics, herbicides, and hydrocarbons, respectively.  Results and discussion: The interaction between biochar and contaminants in soil is largely driven by biochar precursor material and pyrolysis temperature as well as some characteristics of the contaminants such as octanol-water partition coefficient (KOW) and polarity. The structural and chemical characteristics of biochar in turn determine the major sorption mechanisms and define biochar’s suitability for contaminant sorption. Based on the reviewed literature, a soil treatment plan is suggested to guide the application of biochar in various soil types (paddy soils, brownfield, and mine soils) at different pH levels (4–5.5) and contaminant concentrations ( 50 mg kg−1).  Conclusions: Research on biochar has grown over the years with significant focus on its properties, and how these affect biochar’s ability to immobilize organic and inorganic contaminants in soil. Few of these studies have been field-based. More studies with greater focus on field-based soil remediation are therefore required to fully understand the behavior of biochar under natural circumstances. Other recommendations are made aimed at stimulating future research in areas where significant knowledge gaps exist

Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics

Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis

Evolution of pathogenicity and sexual reproduction in eight Candida genomes

Candida species are the most common cause of opportunistic fungal infection worldwide. Here we report the genome sequences of six Candida species and compare these and related pathogens and non-pathogens. There are significant expansions of cell wall, secreted and transporter gene families in pathogenic species, suggesting adaptations associated with virulence. Large genomic tracts are homozygous in three diploid species, possibly resulting from recent recombination events. Surprisingly, key components of the mating and meiosis pathways are missing from several species. These include major differences at the mating-type loci (MTL); Lodderomyces elongisporus lacks MTL, and components of the a1/2 cell identity determinant were lost in other species, raising questions about how mating and cell types are controlled. Analysis of the CUG leucine-to-serine genetic-code change reveals that 99% of ancestral CUG codons were erased and new ones arose elsewhere. Lastly, we revise the Candida albicans gene catalogue, identifying many new genes.publishe

Delayed mortality, resistance and the sweet spot, as the good, the bad and the ugly in phosphine use

Phosphine is the most commonly used gas for fumigation for durable commodities globally, but there is still inadequate information regarding its efficacy in conjunction with proper concentration monitoring. In a series of bioassays, insect mortality after specific exposure intervals to phosphine in selected species was examined, as well as the appearance of the so called "sweet spot". The species that were tested were: Oryzaephilus surinamensis (L.), Tribolium castaneum (Herbst), Sitophilus oryzae (L.) and Rhyzopertha dominica (F.) with populations that had different levels of phosphine resistance. Evaluation was conducted by using the Phosphine Tolerance Test (PTT), with exposure of the adult stage for 15, 30, 60, 90, 150 and 300 min at 3000 ppm. At the end of these intervals (separate bioassays for each time interval), the insects were transferred to Petri dishes, in which recovery was recorded at different time intervals (2 h, 1, 2 and 7 days). The majority of susceptible populations of all species were instantly immobilized even in the shortest exposure period (15 min), in contrast with resistant populations that were active even after 300 min. After exposure to phosphine, populations and exposure time affected mortality of susceptible populations, whereas resistant populations recovered regardless of species and exposure time. Additional bioassays at the concentrations of 500, 1000, 2000 and 3000 ppm for 1, 3, 5, 20, 30 and 40 h showed the presence of the "sweet spot", i.e., decrease of mortality with the increase of concentration. In fact, for most of the tested species, the "sweet spot" appeared in 1000 and 2000 ppm at a 5-h exposure time, regardless of the level of resistance to phosphine. This observation is particularly important both in terms of the assessment of resistance and in the context of non-linear recovery at elevated concentrations, indicating the occurrence of strong hormetic reversals in phosphine efficacy. © 2021, The Author(s)