Molecular Characterization of a Novel Budgerigar Fledgling Disease Virus Strain From Budgerigars in China

Budgerigar fledgling disease virus (BFDV) is the causative polyomavirus of budgerigar fledgling disease, an important avian immunosuppressive disease in budgerigars (Melopsittacus undulatus). In the current study, we explored the etiological role and molecular characteristics of BFDV. We identified a novel BFDV strain, designated as SC-YB19, belonging to a unique cluster with three other domestic strains (WF-GM01, SD18, and APV-P) and closely related to Polish isolates based on complete sequences. Sequence analysis showed that SC-YB19 had an 18-nucleotide (nt) deletion in the enhancer region, corresponding to the sequence position 164–181 nt, which differed significantly from all other BFDV strains. Based on sequence alignment, three unique nucleotide substitutions were found in VP4 (position 821), VP1 (position 2,383), and T-antigen (position 3,517) of SC-YB19, compared with SD18, WF-GM01, QDJM01, HBYM02, APV7, and BFDV1. Phylogenetic analyses based on complete sequences suggested that SC-YB19, along with the domestic WF-GM01, SD18, and APV-P strains, formed a single branch and were closely related to Polish, Japanese, and American isolates. These results demonstrate that BFDV genotype variations are co-circulating in China, thus providing important insight into BFDV evolution.

Retrospective and prospective prioritization in visual working memory

A growing body of research indicates that items assigned with a higher ‘value’ prior to presentationare better recalled in working memory tasks. This has been interpreted as reflecting the strategic prioritization of these items via selective attention during encoding, maintenance, and retrieval. The current study sought to establish whether value-based prioritization effects can be obtained in a sequential visual working memory task when value information is provided retrospectively during maintenance and items are no longer present in the environment. Enhanced recall of high value items along with costs to low value items (relative to equal value trials) was observed, although the high value benefit was only reliably found on the final sequence position. In comparison, a follow- up experiment in which values were provided prior to presentation found large prioritization benefits across sequence positions. This study illustrates that attention can be retrospective shifted between working memory representations based on value, but the effectiveness of this strategic process depends on item availability and accessibility, either in the environment or in working memory.

Molecular Characterization of Budgerigar Fledgling Disease Virus SC-YB19, with an 18-Nucleotides Deletion, in China

Background: Budgerigar fledgling disease virus (BFDV) poses a serious threat to the Chinese psittacine industry, causing enormous economic losses. This study aims to reveal the etiological role of BFDV and evaluate the molecular characterization.Results: We report on BFDV, designated SC-YB19, which had an 18-nucleotide (nt) deletion in the enhancer region, corresponding to the sequence position 164–181 nt, when compared with other BFDV strains. Sequence analyses suggested that 19 nucleotide substitutions were identified with the domestic strains, APV7 and AF118150. Phylogenetic analysis indicated that SC-YB19, along with three domestic strains, formed a unique cluster, and were closely related to Polish isolates. Conclusion: Taken together, these results demonstrate that a BFDV genotype variation was co-circulating in China, and provide important insights on evolution of BFDV.

Evolutionary Action Score of TP53 Mutations: Integrated Clinico-pathologic And Protein Structural Analysis in Myelodysplastic Syndromes

ABSTRACTTo determine the impact of TP53 mutations on the phenotype and outcome of myelodysplastic syndromes, we quantified the deleterious effects of missense TP53 mutations using the computationally-derived evolutionary action score (higher score indicates worse impact), based on the phylogenetic divergence of the sequence position and amino acid change perturbation, and correlated with clinico-pathologic-genomic features in 270 newly-diagnosed TP53-mutant patients primarily treated with hypomethylating agents. Using recursive partitioning and regression trees, we identified a subset of patients with low-EAp53 mutations (≤52) with improved overall survival (OS) (n=17, 6%) compared to high-EAp53 (n=253, 94%) [median OS, 48 vs. 10 months; p=0.01]. Compared to high-EAp53, low-EAp53 patients had lower cytogenetic complexity, lower TP53 protein expression, lacked multi-allelic TP53 alterations, but had more somatic mutations in other genes. There was no difference in median TP53 variant allele frequency or distribution of R-IPSS. 3D-protein modeling showed clustering of poor-outcome mutations, indicating structural location influences outcome.

THE EFFECT OF TIME PRESSURE ON THE PERFORMANCE OF DEXTEROUS OPERATIONS

This study explores the effects of time pressure in dexterous operations on two types of interface: the fixed interface and the moving interface. Results show that the accuracy of finger movement is decreased, the information processing on the sense of sequence, position and direction is worsened by the psychological disturbance. The findings indicate that a fixed interface is more robust to performance and participants can learn and perform tasks quicker than a moving interface. Finally, the researchers give some practices on both fixed and moving interface design.

Mining Integrated Sequential Patterns From Multiple Databases

Existing work on multiple databases (MDBs) sequential pattern mining cannot mine frequent sequences to answer exact and historical queries from MDBs having different table structures. This article proposes the transaction id frequent sequence pattern (TidFSeq) algorithm to handle the difficult problem of mining frequent sequences from diverse MDBs. The TidFSeq algorithm transforms candidate 1-sequences to get transaction subsequences where candidate 1-sequences occurred as (1-sequence, itssubsequenceidlist) tuple or (1-sequence, position id list). Subsequent frequent i-sequences are computed using the counts of the sequence ids in each candidate i-sequence position id list tuples. An extended version of the general sequential pattern (GSP)-like candidate generates and a frequency count approach is used for computing supports of itemset (I-step) and separate (S-step) sequences without repeated database scans but with transaction ids. Generated patterns answer complex queries from MDBs. The TidFSeq algorithm has a faster processing time than existing algorithms.

SPDI: data model for variants and applications at NCBI

Motivation Normalizing sequence variants on a reference, projecting them across congruent sequences and aggregating their diverse representations are critical to the elucidation of the genetic basis of disease and biological function. Inconsistent representation of variants among variant callers, local databases and tools result in discrepancies that complicate analysis. NCBI’s genetic variation resources, dbSNP and ClinVar, require a robust, scalable set of principles to manage asserted sequence variants. Results The SPDI data model defines variants as a sequence of four attributes: sequence, position, deletion and insertion, and can be applied to nucleotide and protein variants. NCBI web services convert representations among HGVS, VCF and SPDI and provide two functions to aggregate variants. One, based on the NCBI Variant Overprecision Correction Algorithm, returns a unique, normalized representation termed the ‘Contextual Allele’. The SPDI data model, with its four operations, defines exactly the reference subsequence affected by the variant, even in repeat regions, such as homopolymer and other sequence repeats. The second function projects variants across congruent sequences and depends on an alignment dataset of non-assembly NCBI RefSeq sequences (prefixed NM, NR and NG), as well as inter- and intra-assembly-associated genomic sequences (NCs, NTs and NWs), supporting robust projection of variants across congruent sequences and assembly versions. The variant is projected to all congruent Contextual Alleles. One of these Contextual Alleles, typically the allele based on the latest assembly version, represents the entire set, is designated the unique ‘Canonical Allele’ and is used directly to aggregate variants across congruent sequences. Availability and implementation The SPDI services are available for open access at: https://api.ncbi.nlm.nih.gov/variation/v0. Supplementary information Supplementary data are available at Bioinformatics online.

6mer seed toxicity in viral microRNAs

SUMMARYMicro(mi)RNAs are short double stranded noncoding RNAs (19-23nts) that regulate gene expression by suppressing mRNAs through RNA interference. Targeting is determined by the seed sequence (position 2-7/8) of the mature miRNA. A minimal G-rich seed of just 6 nucleotides is highly toxic to cells by targeting genes essential for cell survival. A screen of 215 miRNAs encoded by 17 human pathogenic viruses (v-miRNAs) now suggests that a number of v-miRNAs can kill cells through a G-rich 6mer sequence embedded in their seed. Specifically, we demonstrate that miR-K12-6-5p, an oncoviral mimic of the tumor suppressive miR-15/16 family encoded by human Kaposi’s sarcoma-associated herpes virus, harbors a noncanonical toxic 6mer seed (position 3-8) and that v-miRNAs are more likely than cellular miRNAs to utilize a noncanonical 6mer seed. Our data suggest that during evolution viruses evolved to use 6mer seed toxicity to kill cells.

The Effect of Sample Bias and Experimental Artefacts on the Statistical Phylogenetic Analysis of Picornaviruses

Statistical phylogenetic methods are a powerful tool for inferring the evolutionary history of viruses through time and space. The selection of mathematical models and analysis parameters has a major impact on the outcome, and has been relatively well-described in the literature. The preparation of a sequence dataset is less formalized, but its impact can be even more profound. This article used simulated datasets of enterovirus sequences to evaluate the effect of sample bias on picornavirus phylogenetic studies. Possible approaches to the reduction of large datasets and their potential for introducing additional artefacts were demonstrated. The most consistent results were obtained using “smart sampling”, which reduced sequence subsets from large studies more than those from smaller ones in order to preserve the rare sequences in a dataset. The effect of sequences with technical or annotation errors in the Bayesian framework was also analyzed. Sequences with about 0.5% sequencing errors or incorrect isolation dates altered by just 5 years could be detected by various approaches, but the efficiency of identification depended upon sequence position in a phylogenetic tree. Even a single erroneous sequence could profoundly destabilize the whole analysis by increasing the variance of the inferred evolutionary parameters.

VOLPES: an interactive web-based tool for visualizing and comparing physicochemical properties of biological sequences

The structure, dynamics and, ultimately, biological function of proteins and nucleic acids are determined by the physicochemical properties of their primary sequences. Such properties are frequently captured via one-dimensional profile plots depicting a given physicochemical variable as a function of sequence position. Hydrophobicity, charge or structural disorder in proteins or nucleobase-density in nucleic acids are routinely visualized in this manner to analyze sequences at a glance. Such visualizations, however, are typically created case-by-case in a purely static manner, employ fixed visualization parameters only and do not enable a quantitative comparison between different sequences. Here, we present VOLPES (volpes.univie.ac.at), a user-friendly web server and the corresponding JavaScript library that enable a fully interactive, multifunctional visualization, analysis and comparison of the physicochemical properties of protein and nucleic-acid sequences, allowing unprecedented insight into biological sequence data and creating a starting point for further in-depth exploration.