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Biology subjects

Yang, A.

Publications and source records attributed to Yang, A..

8 recordsLinked to original sources
bioRxiv2018

Ecological niche modeling the potential geographic distribution of four Culicoides species of veterinary significance in Florida

Epizootic hemorrhagic disease (EHD) is a viral arthropod-borne disease affecting wild and domestic ruminants. EHD virus (EHDV) is transmitted to vertebrate animal hosts by biting midges in the genus Culicoides. Culicoides sonorensis Latreille is the only confirmed vector of EHDV in the United States but is considered rare in Florida and not sufficiently abundant to support EHDV transmission. This study used ecological niche modeling to map the potential geographical distributions and associated ecological variable space of four Culicoides species suspected of transmitting EHDV in Florida, including Culicoides insignis, Culicoides stellifer, Culicoides debilipalpis and Culicoides venustus. Models were developed with the Genetic Algorithm for Rule Set Production in DesktopGARP v1.1.3 using species occurrence data from field sampling along with environmental variables from WorldClim and Trypanosomiasis and Land use in Africa. For three Culicoides species (C. insignis, C. stellifer and C. debilipalpis) 96 - 98% of the presence points were predicted across the Florida landscape (63.77% - 72.53%). For C. venustus, models predicted 98.00% of presence points across 27.42% of Florida. Geographic variations were detected between species. Culicoides insignis was predicted to be restricted to peninsular Florida, and in contrast, C. venustus was predicted to be primarily in north Florida and the panhandle region. Culicoides stellifer and C. debilipalpis were predicted nearly statewide. Environmental conditions also differed by species, with some species ranges predicted by more narrow ranges of variables than others. The Normalized Difference Vegetation Index (NDVI) was a major predictor of C. venustus and C. insignis presence. For C. stellifer, Land Surface Temperature, Middle Infrared were the most limiting predictors of presence. The limiting variables for C. debilipalpis were NDVI Bi-Annual Amplitude and NDVI Annual Amplitude at 22.45% and 28.09%, respectively. The model outputs, including maps and environmental variable range predictions generated from these experiments provide an important first pass at predicting species of veterinary importance in Florida. Because EHDV cannot exist in the environment without the vector, model outputs can be used to estimate the potential risk of disease for animal hosts across Florida. Results also provide distribution and habitat information useful for integrated pest management practices.

ecology↗
bioRxiv2018

HPCI: A Perl module for writing cluster-portable bioinformatics pipelines

BackgroundMost biocomputing pipelines are run on clusters of computers. Each type of cluster has its own API (application programming interface). That API defines how a program that is to run on the cluster must request the submission, content and monitoring of jobs to be run on the cluster. Sometimes, it is desirable to run the same pipeline on different types of cluster. This can happen in situations including when:\n\nO_LIdifferent labs are collaborating, but they do not use the same type of cluster\nC_LIO_LIa pipeline is released to other labs as open source or commercial software\nC_LIO_LIa lab has access to multiple types of cluster, and wants to choose between them for scaling, cost or other purposes\nC_LIO_LIa lab is migrating their infrastructure from one cluster type to another\nC_LIO_LIduring testing or travelling, it is often desired to run on a single computer\nC_LI\n\nHowever, since each type of cluster has its own API, code that runs jobs on one type of cluster needs to be re-written if it is desired to run that application on a different type of cluster. To resolve this problem, we created a software module to generalize the submission of pipelines across computing environments, including local compute, clouds and clusters.\n\nResultsHPCI (High Performance Computing Interface) is a Perl module that provides the interface to a standardized generic cluster.\n\nWhen the HPCI module is used, it accepts a parameter to specify the cluster type. The HPCI module uses this to load a driver HPCD:: . This is used to translate the abstract HPCI interface to the specific software interface.\n\nSimply by changing the cluster parameter, the same pipeline can be run on a different type of cluster with no other changes.\n\nConclusionThe HPCI module assists in writing Perl programs that can be run in different lab environments, with different site configuration requirements and different types of hardware clusters. Rather than having to re-write portions of the program, it is only necessary to change a configuration file.\n\nUsing HPCI, an application can manage collections of jobs to be runs, specify ordering dependencies, detect success or failure of jobs run and allow automatic retry of failed jobs (allowing for the possibility of a changed configuration such as when the original attempt specified an inadequate memory allotment).

bioinformatics↗
bioRxiv2018

Herd Immunity Alters the Conditions for Performing Dose Schedule Comparisons: An Individual-based Model of Pneumococcal Carriage

BACKGROUND BACKGROUND METHODS RESULTS DISCUSSION CONCLUSIONS LIST OF ABBREVIATIONS Ethics approval and consent... Consent for publication Availability of data and... Competing interests Funding Authors' contributions DECLARATIONS REFERENCES Mass vaccination of infants and toddlers with pneumococcal conjugate vaccines (PCVs) has led to large declines in pneumococcal disease in countries around the world [1]. These vaccines currently contain 10 or 13 different capsular polysaccharides from Streptococcus pneumoniae, each conjugated to a protein carrier. In S. pneumoniae, the chemical structure of the capsular polys ...

epidemiology↗
bioRxiv2018

Structural differences between pri-miRNA paralogs promotes alternative Drosha cleavage and expands target repertoires

MicroRNA (miRNA) processing begins with Drosha cleavage, the fidelity of which is critical for downstream processing and mature miRNA target specificity. To understand how pri-miRNA sequence and structure influence Drosha cleavage, we studied the maturation of three pri-miR-9 paralogs, which encode the same mature miRNA but differ in the surrounding scaffold. We show that pri-miR-9-1 has a unique Drosha cleavage profile due to its distorted and flexible stem structure. Cleavage of pri-miR-9-1, but not pri-miR-9-2 or pri-miR-9-3, generates an alternative-miR-9 with a shifted seed sequence that expands the scope of its target RNAs. Analyses of low grade glioma patient samples indicate that the alternative-miR-9 plays a distinct role in preventing tumor progression. To generalize our model, we provide evidence that distortion of pri-miRNA stems correlates with Drosha cleavage at non-canonical sites. Our studies reveal that pri-miRNA paralogs can have distinct functions via differential Drosha processing.

molecular biology↗
bioRxiv2018

Scavenger: A pipeline for recovery of unaligned reads utilising similarity with aligned reads

MotivationRead alignment is an important step in RNA-seq analysis as the result of alignment forms the basis for further downstream analyses. However, recent studies have shown that published alignment tools have variable mapping sensitivity and do not necessarily align reads which should have been aligned, a problem we termed as the false-negative non-alignment problem.\n\nResultsWe have developed Scavenger, a pipeline for recovering unaligned reads using a novel mechanism which utilises information from aligned reads. Scavenger performs recovery of unaligned reads by re-aligning unaligned reads against a putative location derived from aligned reads with sequence similarity against unaligned reads. We show that Scavenger can successfully recover unaligned reads in both simulated and real RNA-seq datasets, including single-cell RNA-seq data. The reads recovered contain more genetic variants compared to previously aligned reads, indicating that divergence between personal and reference genomes plays a role in the false-negative non-alignment problem. We also explored the impact of read recovery on downstream analyses, in particular gene expression analysis, and showed that Scavenger is able to both recover genes which were previously non-expressed and also increase gene expression, with lowly expressed genes having the most impact from the addition of recovered reads. We also found that the majority of genes with >1 fold change in expression after recovery are categorised as pseudogenes, indicating that pseudogene expression can be affected by the false-negative non-alignment problem. Scavenger helps to solve the false-negative non-alignment problem through recovery of unaligned reads using information from previously aligned reads.\n\nAvailabilityScavenger is available via an open source license in https://github.com/VCCRI/Scavenger/\n\nContactj.ho@victorchang.edu.au

bioinformatics↗
bioRxiv2017

Comparing neurotransmitter metabolism in the brain of patients with symptomatic and aysmptomatic Alzheimer’s disease and healthy individuals

INTRODUCTIONThree of the four treatments for Alzheimers disease are cholinesterase inhibitors targeting the pathological reduction of acetylcholine levels. Here we aimed to determine the role of other neurotransmitter pathways in AD pathology.\n\nMETHODSTissue samples were obtained from three groups, controls, AD and asymptomatic AD i.e. cognitively normal individuals that had significant AD neuropathology. Three brain areas were studied, the middle frontal gyrus (MFG) the inferior temporal gyrus (ITG) and the cerebellum.\n\nRESULTS11 of 15 measured metabolites were shown to be associated with disease. Decreases in dopamine were seen in the ASYMAD group in the MFG when compared to control and AD patients (FC=0.78, p=4.1x10-3). In AD patients changes were mainly seen in the ITGs inhibitory GABAergic system.\n\nDISCUSSIONThese results indicate that dopamine could be depleted in brains with Alzheimers pathology but intact cognition, while and imbalance of several neurotransmitters is evident in the brain of AD patients.

neuroscience↗
bioRxiv2017

Adaptive Evolution Of Transcription Factor Binding Affinities

Understanding the molecular basis of gene expression evolution is a central problem in evolutionary biology. However, connecting changes in gene expression to increased fitness, and identifying the functional basis of those changes, remains challenging. To study adaptive evolution of gene expression in real time, we performed long term experimental evolution (LTEE) of Saccharomyces cerevisiae (budding yeast) in ammonium-limited chemostats. Following several hundred generations of continuous selection we found significant divergence of nitrogen-responsive gene expression in lineages with increased fitness. In multiple independent lineages we found repeated selection for non-synonymous mutations in the zinc finger DNA binding domain of the activating transcription factor (TF), GAT1, that operates within incoherent feedforward loops to control expression of the nitrogen catabolite repression (NCR) regulon. Missense mutations in the DNA binding domain of GAT1 reduce its binding affinity for the GATAA consensus sequence in a promoter-specific manner, resulting in increased expression of ammonium permease genes via both direct and indirect effects, thereby conferring increased fitness. We find that altered transcriptional output of the NCR regulon results in antagonistic pleiotropy in alternate environments and that the DNA binding domain of GAT1 is subject to purifying selection in natural populations. Our study shows that adaptive evolution of gene expression can entail tuning expression output by quantitative changes in TF binding affinities while maintaining the overall topology of a gene regulatory network.

evolutionary biology↗