Effects of Ankle Position While Performing One- and Two-Leg Floor Bridging Exercises on Core and Lower Extremity Muscle Recruitment.

Given there are no known studies which have examined multiple lower extremity muscles between different ankle positions during bridging activities, the objective was to assess how employing two different ankle positions (PF versus DF) while performing five common bridging exercises (three bipedal and two unipedal) used in rehabilitation and athletic performance affect core and select lower extremity muscle EMG recruitment. Twenty healthy subjects performed a 5 s isometric hold during five two- and one-leg bridge exercises: (1) on right leg with left knee to chest (1LB-LFlex); (2) on right leg with left knee extended (1LB-LExt); (3) standard two-leg bridge (2LB); (4) two-leg bridge with resistance band around knees (2LB-ABD); and (5) two-leg bridge with ball between knees (2LB-ADD). Surface electromyographic (EMG) data were collected using a Noraxon Telemyo Direct Transmission System from fourteen muscles: (1) three superficial quadriceps (VM, VL, and RF); (2) three hip abductors (TFL, GMED, and GMAX); (3) medial hamstrings (ST) and lateral hamstrings (BF); (4) hip adductors (ADD); (5) erector spinae (ES); (6) latissimus dorsi (LATS); (7) upper rectus abdominis (RA); and (8) external oblique (EO) and internal oblique (IO). EMG data were normalized by maximum voluntary isometric contractions (MVICs). A paired t-test (p < 0.01) was used to assess differences in normalized mean EMG activities between DF and PF for each exercise. EMG activities were significantly greater in DF than PF for the (a) VM, VL, and RF during 1LB-LFlex; (b) ADD during 1LB-LFlex, 1LB-LExt; (c) EO during 1LB-LFlex; and (d) IO during 1LB-LFex. In contrast, EMG activities were significantly greater in PF than DF for ST and BF during all five bridge exercises. Bridging with PF (feet flat) was most effective in recruiting the hamstrings, while bridging with DF (feet up) was most effective in recruiting the quadriceps, hip adductors, and internal and external obliques.

Publisher Correction: The calcium-permeable channel OSCA1.3 regulates plant stomatal immunity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The calcium-permeable channel OSCA1.3 regulates plant stomatal immunity.

Perception of biotic and abiotic stresses often leads to stomatal closure in plants1,2. Rapid influx of calcium ions (Ca2+) across the plasma membrane has an important role in this response, but the identity of the Ca2+ channels involved has remained elusive3,4. Here we report that the Arabidopsis thaliana Ca2+-permeable channel OSCA1.3 controls stomatal closure during immune signalling. OSCA1.3 is rapidly phosphorylated upon perception of pathogen-associated molecular patterns (PAMPs). Biochemical and quantitative phosphoproteomics analyses reveal that the immune receptor-associated cytosolic kinase BIK1 interacts with and phosphorylates the N-terminal cytosolic loop of OSCA1.3 within minutes of treatment with the peptidic PAMP flg22, which is derived from bacterial flagellin. Genetic and electrophysiological data reveal that OSCA1.3 is permeable to Ca2+, and that BIK1-mediated phosphorylation on its N terminus increases this channel activity. Notably, OSCA1.3 and its phosphorylation by BIK1 are critical for stomatal closure during immune signalling, and OSCA1.3 does not regulate stomatal closure upon perception of abscisic acid-a plant hormone associated with abiotic stresses. This study thus identifies a plant Ca2+ channel and its activation mechanisms underlying stomatal closure during immune signalling, and suggests specificity in Ca2+ influx mechanisms in response to different stresses.

Rapid fine mapping of causative mutations from sets of unordered, contig-sized fragments of genome sequence.

BACKGROUND: Traditional Map based Cloning approaches, used for the identification of desirable alleles, are extremely labour intensive and years can elapse between the mutagenesis and the detection of the polymorphism. High throughput sequencing based Mapping-by-sequencing approach requires an ordered genome assembly and cannot be used with fragmented, un-scaffolded draft genomes, limiting its application to model species and precluding many important organisms. RESULTS: We addressed this gap in resource and presented a computational method and software implementations called CHERIPIC (Computing Homozygosity Enriched Regions In genomes to Prioritise Identification of Candidate variants). We have successfully validated implementation of CHERIPIC using three different types of bulk segregant sequence data from Arabidopsis, maize and barley, respectively. CONCLUSIONS: CHERIPIC allows users to rapidly analyse bulk segregant sequence data and we have made it available as a pre-packaged binary with all dependencies for Linux and MacOS and as Galaxy tool.

Arabidopsis downy mildew effector HaRxL106 suppresses plant immunity by binding to RADICAL-INDUCED CELL DEATH1.

The oomycete pathogen Hyaloperonospora arabidopsidis (Hpa) causes downy mildew disease on Arabidopsis. To colonize its host, Hpa translocates effector proteins that suppress plant immunity into infected host cells. Here, we investigate the relevance of the interaction between one of these effectors, HaRxL106, and Arabidopsis RADICAL-INDUCED CELL DEATH1 (RCD1). We use pathogen infection assays as well as molecular and biochemical analyses to test the hypothesis that HaRxL106 manipulates RCD1 to attenuate transcriptional activation of defense genes. We report that HaRxL106 suppresses transcriptional activation of salicylic acid (SA)-induced defense genes and alters plant growth responses to light. HaRxL106-mediated suppression of immunity is abolished in RCD1 loss-of-function mutants. We report that RCD1-type proteins are phosphorylated, and we identified Mut9-like kinases (MLKs), which function as phosphoregulatory nodes at the level of photoreceptors, as RCD1-interacting proteins. An mlk1,3,4 triple mutant exhibits stronger SA-induced defense marker gene expression compared with wild-type plants, suggesting that MLKs also affect transcriptional regulation of SA signaling. Based on the combined evidence, we hypothesize that nuclear RCD1/MLK complexes act as signaling nodes that integrate information from environmental cues and pathogen sensors, and that the Arabidopsis downy mildew pathogen targets RCD1 to prevent activation of plant immunity.

Plant immune and growth receptors share common signalling components but localise to distinct plasma membrane nanodomains.

Cell surface receptors govern a multitude of signalling pathways in multicellular organisms. In plants, prominent examples are the receptor kinases FLS2 and BRI1, which activate immunity and steroid-mediated growth, respectively. Intriguingly, despite inducing distinct signalling outputs, both receptors employ common downstream signalling components, which exist in plasma membrane (PM)-localised protein complexes. An important question is thus how these receptor complexes maintain signalling specificity. Live-cell imaging revealed that FLS2 and BRI1 form PM nanoclusters. Using single-particle tracking we could discriminate both cluster populations and we observed spatiotemporal separation between immune and growth signalling platforms. This finding was confirmed by visualising FLS2 and BRI1 within distinct PM nanodomains marked by specific remorin proteins and differential co-localisation with the cytoskeleton. Our results thus suggest that signalling specificity between these pathways may be explained by the spatial separation of FLS2 and BRI1 with their associated signalling components within dedicated PM nanodomains.

The GOBLET training portal: a global repository of bioinformatics training materials, courses and trainers.

SUMMARY: Rapid technological advances have led to an explosion of biomedical data in recent years. The pace of change has inspired new collaborative approaches for sharing materials and resources to help train life scientists both in the use of cutting-edge bioinformatics tools and databases and in how to analyse and interpret large datasets. A prototype platform for sharing such training resources was recently created by the Bioinformatics Training Network (BTN). Building on this work, we have created a centralized portal for sharing training materials and courses, including a catalogue of trainers and course organizers, and an announcement service for training events. For course organizers, the portal provides opportunities to promote their training events; for trainers, the portal offers an environment for sharing materials, for gaining visibility for their work and promoting their skills; for trainees, it offers a convenient one-stop shop for finding suitable training resources and identifying relevant training events and activities locally and worldwide. AVAILABILITY AND IMPLEMENTATION: http://mygoblet.org/training-portal.

EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics.

BACKGROUND: Next Generation Sequencing technologies have facilitated differential gene expression analysis through RNA-seq and Tag-seq methods. RNA-seq has biases associated with transcript lengths, lacks uniform coverage of regions in mRNA and requires 10-20 times more reads than a typical Tag-seq. Most existing Tag-seq methods either have biases or not high throughput due to use of restriction enzymes or enzymatic manipulation of 5' ends of mRNA or use of RNA ligations. RESULTS: We have developed EXpression Profiling through Randomly Sheared cDNA tag Sequencing (EXPRSS) that employs acoustic waves to randomly shear cDNA and generate sequence tags at a relatively defined position (~150-200 bp) from the 3' end of each mRNA. Implementation of the method was verified through comparative analysis of expression data generated from EXPRSS, NlaIII-DGE and Affymetrix microarray and through qPCR quantification of selected genes. EXPRSS is a strand specific and restriction enzyme independent tag sequencing method that does not require cDNA length-based data transformations. EXPRSS is highly reproducible, is high-throughput and it also reveals alternative polyadenylation and polyadenylated antisense transcripts. It is cost-effective using barcoded multiplexing, avoids the biases of existing SAGE and derivative methods and can reveal polyadenylation position from paired-end sequencing. CONCLUSIONS: EXPRSS Tag-seq provides sensitive and reliable gene expression data and enables high-throughput expression profiling with relatively simple downstream analysis.

Coval: improving alignment quality and variant calling accuracy for next-generation sequencing data.

Accurate identification of DNA polymorphisms using next-generation sequencing technology is challenging because of a high rate of sequencing error and incorrect mapping of reads to reference genomes. Currently available short read aligners and DNA variant callers suffer from these problems. We developed the Coval software to improve the quality of short read alignments. Coval is designed to minimize the incidence of spurious alignment of short reads, by filtering mismatched reads that remained in alignments after local realignment and error correction of mismatched reads. The error correction is executed based on the base quality and allele frequency at the non-reference positions for an individual or pooled sample. We demonstrated the utility of Coval by applying it to simulated genomes and experimentally obtained short-read data of rice, nematode, and mouse. Moreover, we found an unexpectedly large number of incorrectly mapped reads in 'targeted' alignments, where the whole genome sequencing reads had been aligned to a local genomic segment, and showed that Coval effectively eliminated such spurious alignments. We conclude that Coval significantly improves the quality of short-read sequence alignments, thereby increasing the calling accuracy of currently available tools for SNP and indel identification. Coval is available at http://sourceforge.net/projects/coval105/.

SVGenes: a library for rendering genomic features in scalable vector graphic format.

MOTIVATION: Drawing genomic features in attractive and informative ways is a key task in visualization of genomics data. Scalable Vector Graphics (SVG) format is a modern and flexible open standard that provides advanced features including modular graphic design, advanced web interactivity and animation within a suitable client. SVGs do not suffer from loss of image quality on re-scaling and provide the ability to edit individual elements of a graphic on the whole object level independent of the whole image. These features make SVG a potentially useful format for the preparation of publication quality figures including genomic objects such as genes or sequencing coverage and for web applications that require rich user-interaction with the graphical elements. RESULTS: SVGenes is a Ruby-language library that uses SVG primitives to render typical genomic glyphs through a simple and flexible Ruby interface. The library implements a simple Page object that spaces and contains horizontal Track objects that in turn style, colour and positions features within them. Tracks are the level at which visual information is supplied providing the full styling capability of the SVG standard. Genomic entities like genes, transcripts and histograms are modelled in Glyph objects that are attached to a track and take advantage of SVG primitives to render the genomic features in a track as any of a selection of defined glyphs. The feature model within SVGenes is simple but flexible and not dependent on particular existing gene feature formats meaning graphics for any existing datasets can easily be created without need for conversion. AVAILABILITY: The library is provided as a Ruby Gem from https://rubygems.org/gems/bio-svgenes under the MIT license, and open source code is available at https://github.com/danmaclean/bioruby-svgenes also under the MIT License. CONTACT: dan.maclean@tsl.ac.uk.

Genome analyses of the wheat yellow (stripe) rust pathogen Puccinia striiformis f. sp. tritici reveal polymorphic and haustorial expressed secreted proteins as candidate effectors.

BACKGROUND: Wheat yellow (stripe) rust caused by Puccinia striiformis f. sp. tritici (PST) is one of the most devastating diseases of wheat worldwide. To design effective breeding strategies that maximize the potential for durable disease resistance it is important to understand the molecular basis of PST pathogenicity. In particular, the characterisation of the structure, function and evolutionary dynamics of secreted effector proteins that are detected by host immune receptors can help guide and prioritize breeding efforts. However, to date, our knowledge of the effector repertoire of cereal rust pathogens is limited. RESULTS: We re-sequenced genomes of four PST isolates from the US and UK to identify effector candidates and relate them to their distinct virulence profiles. First, we assessed SNP frequencies between all isolates, with heterokaryotic SNPs being over tenfold more frequent (5.29 ± 2.23 SNPs/kb) than homokaryotic SNPs (0.41 ± 0.28 SNPs/kb). Next, we implemented a bioinformatics pipeline to integrate genomics, transcriptomics, and effector-focused annotations to identify and classify effector candidates in PST. RNAseq analysis highlighted transcripts encoding secreted proteins that were significantly enriched in haustoria compared to infected tissue. The expression of 22 candidate effector genes was characterised using qRT-PCR, revealing distinct temporal expression patterns during infection in wheat. Lastly, we identified proteins that displayed non-synonymous substitutions specifically between the two UK isolates PST-87/7 and PST-08/21, which differ in virulence to two wheat varieties. By focusing on polymorphic variants enriched in haustoria, we identified five polymorphic effector candidates between PST-87/7 and PST-08/21 among 2,999 secreted proteins. These allelic variants are now a priority for functional validation as virulence/avirulence effectors in the corresponding wheat varieties. CONCLUSIONS: Integration of genomics, transcriptomics, and effector-directed annotation of PST isolates has enabled us to move beyond the single isolate-directed catalogues of effector proteins and develop a framework for mining effector proteins in closely related isolates and relate these back to their defined virulence profiles. This should ultimately lead to more comprehensive understanding of the PST pathogenesis system, an important first step towards developing more effective surveillance and management strategies for one of the most devastating pathogens of wheat.

Identifying and classifying trait linked polymorphisms in non-reference species by walking coloured de bruijn graphs.

Single Nucleotide Polymorphisms are invaluable markers for tracing the genetic basis of inheritable traits and the ability to create marker libraries quickly is vital for timely identification of target genes. Next-generation sequencing makes it possible to sample a genome rapidly, but polymorphism detection relies on having a reference genome to which reads can be aligned and variants detected. We present Bubbleparse, a method for detecting variants directly from next-generation reads without a reference sequence. Bubbleparse uses the de Bruijn graph implementation in the Cortex framework as a basis and allows the user to identify bubbles in these graphs that represent polymorphisms, quickly, easily and sensitively. We show that the Bubbleparse algorithm is sensitive and can detect many polymorphisms quickly and that it performs well when compared with polymorphism detection methods based on alignment to a reference in Arabidopsis thaliana. We show that the heuristic can be used to maximise the number of true polymorphisms returned, and with a proof-of-principle experiment show that Bubbleparse is very effective on data from unsequenced wild relatives of potato and enabled us to identify disease resistance linked genes quickly and easily.

Spatio-temporal cellular dynamics of the Arabidopsis flagellin receptor reveal activation status-dependent endosomal sorting.

The activity of surface receptors is location specific, dependent upon the dynamic membrane trafficking network and receptor-mediated endocytosis (RME). Therefore, the spatio-temporal dynamics of RME are critical to receptor function. The plasma membrane receptor flagellin sensing2 (FLS2) confers immunity against bacterial infection through perception of flagellin (flg22). Following elicitation, FLS2 is internalized into vesicles. To resolve FLS2 trafficking, we exploited quantitative confocal imaging for colocalization studies and chemical interference. FLS2 localizes to bona fide endosomes via two distinct endocytic trafficking routes depending on its activation status. FLS2 receptors constitutively recycle in a Brefeldin A (BFA)-sensitive manner, while flg22-activated receptors traffic via ARA7/Rab F2b- and ARA6/Rab F1-positive endosomes insensitive to BFA. FLS2 endocytosis required a functional Rab5 GTPase pathway as revealed by dominant-negative ARA7/Rab F2b. Flg22-induced FLS2 endosomal numbers were increased by Concanamycin A treatment but reduced by Wortmannin, indicating that activated FLS2 receptors are targeted to late endosomes. RME inhibitors Tyrphostin A23 and Endosidin 1 altered but did not block induced FLS2 endocytosis. Additional inhibitor studies imply the involvement of the actin-myosin system in FLS2 internalization and trafficking. Altogether, we report a dynamic pattern of subcellular trafficking for FLS2 and reveal a defined framework for ligand-dependent endocytosis of this receptor.

Genome analyses of an aggressive and invasive lineage of the Irish potato famine pathogen.

Pest and pathogen losses jeopardise global food security and ever since the 19(th) century Irish famine, potato late blight has exemplified this threat. The causal oomycete pathogen, Phytophthora infestans, undergoes major population shifts in agricultural systems via the successive emergence and migration of asexual lineages. The phenotypic and genotypic bases of these selective sweeps are largely unknown but management strategies need to adapt to reflect the changing pathogen population. Here, we used molecular markers to document the emergence of a lineage, termed 13_A2, in the European P. infestans population, and its rapid displacement of other lineages to exceed 75% of the pathogen population across Great Britain in less than three years. We show that isolates of the 13_A2 lineage are among the most aggressive on cultivated potatoes, outcompete other aggressive lineages in the field, and overcome previously effective forms of plant host resistance. Genome analyses of a 13_A2 isolate revealed extensive genetic and expression polymorphisms particularly in effector genes. Copy number variations, gene gains and losses, amino-acid replacements and changes in expression patterns of disease effector genes within the 13_A2 isolate likely contribute to enhanced virulence and aggressiveness to drive this population displacement. Importantly, 13_A2 isolates carry intact and in planta induced Avrblb1, Avrblb2 and Avrvnt1 effector genes that trigger resistance in potato lines carrying the corresponding R immune receptor genes Rpi-blb1, Rpi-blb2, and Rpi-vnt1.1. These findings point towards a strategy for deploying genetic resistance to mitigate the impact of the 13_A2 lineage and illustrate how pathogen population monitoring, combined with genome analysis, informs the management of devastating disease epidemics.

Bio-samtools: Ruby bindings for SAMtools, a library for accessing BAM files containing high-throughput sequence alignments.

BACKGROUND: The SAMtools utilities comprise a very useful and widely used suite of software for manipulating files and alignments in the SAM and BAM format, used in a wide range of genetic analyses. The SAMtools utilities are implemented in C and provide an API for programmatic access, to help make this functionality available to programmers wishing to develop in the high level Ruby language we have developed bio-samtools, a Ruby binding to the SAMtools library. RESULTS: The utility of SAMtools is encapsulated in 3 main classes, Bio::DB::Sam, representing the alignment files and providing access to the data in them, Bio::DB::Alignment, representing the individual read alignments inside the files and Bio::DB::Pileup, representing the summarised nucleotides of reads over a single point in the nucleotide sequence to which the reads are aligned. CONCLUSIONS: Bio-samtools is a flexible and easy to use interface that programmers of many levels of experience can use to access information in the popular and common SAM/BAM format.

Gee Fu: a sequence version and web-services database tool for genomic assembly, genome feature and NGS data.

SUMMARY: Scientists now use high-throughput sequencing technologies and short-read assembly methods to create draft genome assemblies in just days. Tools and pipelines like the assembler, and the workflow management environments make it easy for a non-specialist to implement complicated pipelines to produce genome assemblies and annotations very quickly. Such accessibility results in a proliferation of assemblies and associated files, often for many organisms. These assemblies get used as a working reference by lots of different workers, from a bioinformatician doing gene prediction or a bench scientist designing primers for PCR. Here we describe Gee Fu, a database tool for genomic assembly and feature data, including next-generation sequence alignments. Gee Fu is an instance of a Ruby-On-Rails web application on a feature database that provides web and console interfaces for input, visualization of feature data via AnnoJ, access to data through a web-service interface, an API for direct data access by Ruby scripts and access to feature data stored in BAM files. Gee Fu provides a platform for storing and sharing different versions of an assembly and associated features that can be accessed and updated by bench biologists and bioinformaticians in ways that are easy and useful for each. AVAILABILITY: http://tinyurl.com/geefu CONTACT: dan.maclean@tsl.ac.uk.

The hyphal tip structure of Basidiobolus sp.: a zygomycete fungus of uncertain phylogeny.

To date, among the zygomycete fungi that have been examined, a Spitzenkörper has not been reported. In this paper, the cytoplasmic order of hyphal tip cells of Basidiobolus sp., a zygomycete genus of uncertain phylogeny, has been examined using light microscopy and transmission electron microscopy methods. With phase-contrast light optics, a phase-dark body was observed at the tips of growing hyphae of Basidiobolus sp. The hyphal apex also showed high affinity for FM4-64 labelling resulting in an intense fluorescence signal. The phase-dark inclusion exhibited independent motility within the hyphal apex and its presence and position were correlated to the rate and direction of hyphal growth. The hyphal apex of Basidiobolus sp. did not contain γ-tubulin. Ultrastructural observations revealed a dense cluster of vesicles at the hyphal apex. These results suggest that the growing hypha of Basidiobolus sp. contains a Spitzenkörper, a character generally attributed to members of the ascomycete and basidiomycete fungi and not to zygomycete fungi.

Genome evolution following host jumps in the Irish potato famine pathogen lineage.

Many plant pathogens, including those in the lineage of the Irish potato famine organism Phytophthora infestans, evolve by host jumps followed by specialization. However, how host jumps affect genome evolution remains largely unknown. To determine the patterns of sequence variation in the P. infestans lineage, we resequenced six genomes of four sister species. This revealed uneven evolutionary rates across genomes with genes in repeat-rich regions showing higher rates of structural polymorphisms and positive selection. These loci are enriched in genes induced in planta, implicating host adaptation in genome evolution. Unexpectedly, genes involved in epigenetic processes formed another class of rapidly evolving residents of the gene-sparse regions. These results demonstrate that dynamic repeat-rich genome compartments underpin accelerated gene evolution following host jumps in this pathogen lineage.

Genome-wide sequencing data reveals virulence factors implicated in banana Xanthomonas wilt.

Banana Xanthomonas wilt is a newly emerging disease that is currently threatening the livelihoods of millions of farmers in East Africa. The causative agent is Xanthomonas campestris pathovar musacearum (Xcm), but previous work suggests that this pathogen is much more closely related to species Xanthomonas vasicola than to X. campestris. We have generated draft genome sequences for a banana-pathogenic strain of Xcm isolated in Uganda and for a very closely related strain of X. vasicola pathovar vasculorum, originally isolated from sugarcane, that is nonpathogenic on banana. The draft sequences revealed overlapping but distinct repertoires of candidate virulence effectors in the two strains. Both strains encode homologues of the Pseudomonas syringae effectors HopW, HopAF1 and RipT from Ralstonia solanacearum. The banana-pathogenic and non-banana-pathogenic strains also differed with respect to lipopolysaccharide synthesis and type-IV pili, and in at least several thousand single-nucleotide polymorphisms in the core conserved genome. We found evidence of horizontal transfer between X. vasicola and very distantly related bacteria, including members of other divisions of the Proteobacteria. The availability of these draft genomes will be an invaluable tool for further studies aimed at understanding and combating this important disease.