Distribution of male yellow dungflies around ovipasition sites: the effect of body size

Abstract.

• 1 Spatial and temporal variation in body size of yellow dungflies, Scatophaga stercoraria, gathering on and around cow droppings was studied in an Icelandic population in order to elucidate the effect of male and female size on male mating tactics.
• 2 Males copulating on droppings were on average larger than males copulating in the grass, but of similar size to males guarding ovipositing females. Males searching on droppings were smaller than males copulating or guarding females on droppings but larger than males copulating in the grass. No such differences were found in female size.
• 3 Resource-holding power of males (RHP, i.e. male: female size ratio) differed between the three mating groups and was highest for males on the droppings. Size and RHP clearly affect the tactics of copulating males. Males with low RHP tend to copulate in the grass in spite of the cost of longer copulation duration. We argue that this is caused by risk of takeovers from large searching males.
• 4 There was no change in male size with the age of individual droppings. Contrary to what might be expected, large searching males are not predominantly found at fresh droppings when the probability of catching unpaired females is highest. We suggest instead that good prospects in taking females over from other males must make the strategy to search for females on older droppings profitable.
• 5 RHP did not change with age of dropping in the three mating groups. The size of ovipositing females increased with age of dropping, probably reflecting longer copulation and egg-laying times of large females.
• 6 We found an overall positive relationship between sizes of male and female partners. This correlation was highly significant for copulating pairs in the grass. This is probably a consequence of males with low RHP copulating in the grass and fights in which larger males take over females from smaller males. A weaker, but significant, correlation was found amongst ovipositing pairs. This must be due to take-over effects. No size correlation was found for pairs copulating on droppings.

     

An airflow olfactometer for measuring olfactory responses of hymenopterous parasitoids and other small insects

ABSTRACT. A new type of airflow olfactometer is described, and results given of experiments using it to measure behavioural olfactory responses of hymenopterous parasitoids. Compared with Y-tube olfactometers it shows several advantages. In its exposure chamber four separate abutting odour fields are presented so that the test insect can readily enter and re-enter them. More than one odour (or different concentrations of one odour) can be tested at the same time, thereby providing complex preference test situations. The various behavioural measures that can be assessed in the apparatus are examined and discussed.     

Prototypic sequences for human repetitive DNA

Summary We report a collection of 53 prototypic sequences representing known families of repetitive elements from the human genome. The prototypic sequences are either consensus sequences or selected examples of repetitive sequences. The collection includes: prototypes for high and medium reiteration frequency interspersed repeats, long terminal repeats of endogenous retroviruses, alphoid repeats, telomere-associated repeats, and some miscellaneous repeats. The collection is annotated and available electronically.[/ap ]Offprint requests to: J. Jurka     

New data and collaborations at the Saccharomyces Genome Database: updated reference genome,alleles, and the Alliance of Genome Resources

Saccharomyces cerevisiae is used to provide fundamental understanding of eukaryotic genetics, gene product function, and cellular biological processes. Saccharomyces Genome Database (SGD) has been supporting the yeast research community since 1993, serving as its de facto hub. Over the years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation, and developed various tools and methods for analysis and curation of a variety of emerging data types. More recently, SGD and six other model organism focused knowledgebases have come together to create the Alliance of Genome Resources to develop sustainable genome information resources that promote and support the use of various model organisms to understand the genetic and genomic bases of human biology and disease. Here we describe recent activities at SGD, including the latest reference genome annotation update, the development of a curation system for mutant alleles, and new pages addressing homology across model organisms as well as the use of yeast to study human disease.     

TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis

Tumor-specific neoantigens have attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database (TSNAdb v1.0), based on pan-cancer immunogenomic analyses of somatic mutation data and human leukocyte antigen (HLA) allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas (TCGA) and The Cancer Immunome Atlas (TCIA). We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients, which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy. TSNAdb is freely available at http://biopharm.zju.edu.cn/tsnadb.     

In silico epitope-based vaccine design against influenza a neuraminidase protein: Computational analysis established on B- and T-cell epitope predictions

ObjectiveInfluenza A virus belongs to the most studied virus and its mutant initiates epidemic and pandemics outbreaks. Inoculation is the significant foundation to diminish the risk of infection. To prevent an incidence of influenza from the transmission, various practical approaches require more advancement and progress. More efforts and research must take in front to enhance vaccine efficacy.MethodsThe present research emphasizes the development and expansion of a universal vaccine for the influenza virus. Research focuses on vaccine design with high efficacy. In this study, numerous computational approaches were used, covering a wide range of elements and ideas in bioinformatics methodology. Various B and T-cell epitopic peptides derived from the Neuraminidase protein N1 are recognized by these approaches. With the implementation of numerous obtained databases and bioinformatics tools, the different immune framework methods of the conserved sequences of N1 neuraminidase were analyzed. NCBI databases were employed to retrieve amino acid sequences. The antigenic nature of the neuraminidase sequence was achieved by the VaxiJen server and Kolaskar and Tongaonkar method. After screening of various B and T cell epitopes, one efficient peptide each from B cell epitope and T cell epitopes was assessed for their antigenic determinant vaccine efficacy. Identical two B cell epitopes were recognized from the N1 protein when analyzed using B-cell epitope prediction servers. The detailed examination of amino acid sequences for interpretation of B and T cell epitopes was achieved with the help of the ABCPred and Immune Epitope Database.ResultsComputational immunology via immunoinformatic study exhibited RPNDKTG as having its high conservancy efficiency and demonstrated as a good antigenic, accessible surface hydrophilic B-cell epitope. Among T cell epitope analysis, YVNISNTNF was selected for being a conserved epitope. T cell epitope was also analyzed for its allergenicity and cytotoxicity evaluation. YVNISNTNF epitope was found to be a non-allergen and not toxic for cells as well. This T-cell epitope with maximum world populace coverages was scrutinized for its association with the HLA-DRB1*0401 molecule. Results from docking simulation analyses showed YVNISNTNF having lower binding energy, the radius of gyration (Rg), RMSD values, and RMSE values which make the protein structure more stable and increase its ability to become an epitopic peptide for influenza virus vaccination.ConclusionsWe propose that this epitope analysis may be successfully used as a measurement tool for the robustness of an antigen–antibody reaction between mutant strains in the annual design of the influenza vaccine.     

Voice Pathologies Classification and Detection Using EMD-DWT Analysis Based on Higher Order Statistic Features

BackgroundThe voice is a prominent tool allowing people to communicate and to change information in their daily activities. However, any slight alteration in the voice production system may affect the voice quality. Over the last years, researchers in biomedical engineering field worked to develop a robust automatic system that may help clinicians to perform a preventive diagnosis in order to detect the voice pathologies in an early stage.MethodIn this context, pathological voice detection and classification method based on EMD-DWT analysis and Higher Order Statistics (HOS) features, is proposed. Also DWT coefficients features are extracted and tested. To carry out our experiments a wide subset of voice signal from normal subjects and subjects which suffer from the five most frequent pathologies in the Saarbrücken Voice Database (SVD), is selected. In The first step, we applied the Empirical Mode Decomposition (EMD) to the voice signal. Afterwards, among the obtained candidates of Intrinsic Mode Functions (IMFs), we choose the robust one based on temporal energy criterion. In the second step, the selected IMF was decomposed via the Discrete Wavelet Transform (DWT). As a result, two features vector includes six HOSs parameters, and a features vector includes six DWT features were formed from both approximation and detail coefficients. In order to classify the obtained data a support vector machine (SVM) is employed. After having trained the proposed system using the SVD database, the system was evaluated using voice signals of volunteer's subjects from the Neurological department of RABTA Hospital of Tunis.ResultsThe proposed method gives promising results in pathological voices detection. The accuracies reached 99.26% using HOS features and 93.1% using DWT features for SVD database. In the classification, an accuracy of 100% was reached for “Funktionelle Dysphonia vs. Rekrrensparese” based on HOS features. Nevertheless, using DWT features the accuracy achieved was 90.32% for “Hyperfunktionelle Dysphonia vs. Rekurrensparse”. Furthermore, in the validation the accuracies reached were 94.82%, 91.37% for HOS and DWT features, respectively. In the classification the highest accuracies reached were for classifying “Parkinson versus Paralysis” 94.44% and 88.87% based on HOS and DWT features, respectively.ConclusionHOS features show promising results in the automatic voice pathology detection and classification compared to DWT features. Thus, it can reliably be used as noninvasive tool to assist clinical evaluation for pathological voices identification.     

Open access to tree genomes: the path to a better forest

An open-access culture and a well-developed comparative-genomics infrastructure must be developed in forest trees to derive the full potential of genome sequencing in this diverse group of plants that are the dominant species in much of the earth''s terrestrial ecosystems.