Biology subjects

Jones, A.

Publications and source records attributed to Jones, A..

10 recordsLinked to original sources

bioRxiv2018

Mapping the human kinome in response to DNA damage

We provide a catalog for the effects of the human kinome on cell survival in response to DNA damaging agents, selected to cover all major DNA repair pathways. By treating 313 kinase-deficient cell lines with ten diverse DNA damaging agents, including seven commonly used chemotherapeutics, we were able to identify kinase specific vulnerabilities and resistances. In order to identify novel synthetic lethal interactions, we investigate the cellular response to carmustine for 25 cell lines, by establishing a phenotypic FACS assay designed to mechanistically investigate and validate gene-drug interactions. We show apoptosis, cell cycle, DNA damage and proliferation after alkylation or crosslink-induced damage for selected cell lines and rescue the cellular sensitivity of DYRK4, EPHB6, MARK3, PNCK as a proof of principle for our study. Our data suggest that some cancers with inactivated DYRK4, EPHB6, MARK3 or PNCK gene could be particularly vulnerable to treatment by alkylating chemotherapeutic agents carmustine or temozolomide.

systems biology↗

bioRxiv2018

EREFinder: Genome-wide detection of estrogen response elements

MotivationEstrogen response elements (EREs) are specific DNA sequences to which ligand-bound estrogen receptors (ERs) physically bind, allowing them to act as transcription factors for target genes. Locating EREs and ER responsive regions is therefore a potentially important component of the study of estrogen-regulated pathways.\n\nResultsWe tested and demonstrated the ability of EREFinder, a novel algorithm we developed, to locate regions of ER-binding across the human genome and show that these regions designated by the program occur more frequently near estrogen responsive genes. EREFinder can handle large input files, has settings to allow for broad and narrow searches, and provides the full output to allow for greater data manipulation. These features facilitate a wide range of hypothesis testing for researchers and make EREFinder an excellent tool to aid in estrogen-related research.\n\nAvailability and ImplementationSource code and binaries freely available for download at https://github.com/JonesLabIdaho/EREfinder, implemented in C++ and supported on Linux and MS Windows.\n\nContactaanderson@bio.tamu.edu\n\nSupplemental MaterialsR scripts can be found at https://github.com/JonesLabIdaho/EREfinder

bioinformatics↗

bioRxiv2018

DNAscan: a fast, computationally and memory efficient bioinformatics pipeline for the analysis of DNA next-generation-sequencing data

The generation of DNA Next Generation Sequencing (NGS) data is a commonly applied approach for studying the genetic basis of biological processes, including diseases, and underpins the aspirations of precision medicine. However, there are significant challenges when dealing with NGS data. A huge number of bioinformatics tools exist and it is therefore challenging to design an analysis pipeline; NGS analysis is computationally intensive, requiring expensive infrastructure which can be problematic given that many medical and research centres do not have adequate high performance computing facilities and the use of cloud computing facilities is not always possible due to privacy and ownership issues. We have therefore developed a fast and efficient bioinformatics pipeline that allows for the analysis of DNA sequencing data, while requiring little computational effort and memory usage. We achieved this by exploiting state-of-the-art bioinformatics tools. DNAscan can analyse raw, 40x whole genome NGS data in 8 hours, using as little as 8 threads and 16 Gbs of RAM, while guaranteeing a high performance. DNAscan can look for SNVs, small indels, SVs, repeat expansions and viral genetic material (or any other organism). Its results are annotated using a customisable variety of databases including ClinVar, Exac and dbSNP, and a local deployment of the gene.iobio platform is available for an on-the-fly result visualisation.

bioinformatics↗

bioRxiv2018

Active Function Learning

How do people actively explore to learn about functional relationships, that is, how continuous inputs map onto continuous outputs? We introduce a novel paradigm to investigate information search in continuous, multi-feature function learning scenarios. Participants either actively selected or passively observed information to learn about an underlying linear function. We develop and compare different variants of rule-based (linear regression) and non-parametric (Gaussian process regression) active learning approaches to model participants active learning behavior. Our results show that participants performance is best described by a rule-based model that attempts to efficiently learn linear functions with a focus on high and uncertain outcomes. These results advance our understanding of how people actively search for information to learn about functional relations in the environment.

animal behavior and cognition↗

bioRxiv2017

Comparative Qualitative Phosphoproteomics Analysis Identifies Shared Phosphorylation Motifs and Associated Biological Processes in Flowering Plants

Phosphorylation is regarded as one of the most prevalent post-translational modifications and plays a key role in regulating cellular processes. In this work we carried out a comparative bioinformatics analysis of phosphoproteomics data, to profile two model species representing the largest subclasses in flowering plants the dicot Arabidopsis thaliana and the monocot Oryza sativa, to understand the extent to which phosphorylation signaling and function is conserved across evolutionary divergent plants. Using pre-existing mass spectrometry phosphoproteomics datasets and bioinformatic tools and resources, we identified 6,537 phosphopeptides from 3,189 phosphoproteins in Arabidopsis and 2,307 phosphopeptides from 1,613 phosphoproteins in rice. The relative abundance ratio of serine, threonine, and tyrosine phosphorylation sites in rice and Arabidopsis were highly similar: 88.3: 11.4: 0.4 and 86.7: 12.8: 0.5, respectively. Tyrosine phosphorylation shows features different from serine and threonine phosphorylation and was found to be more frequent in doubly-phosphorylated peptides in Arabidopsis. We identified phosphorylation sequence motifs in the two species to explore the similarities, finding nineteen pS motifs and two pT motifs that are shared in rice and Arabidopsis; among them are five novel motifs that have not previously been described in both species. The majority of shared motif-containing proteins were mapped to the same biological processes with similar patterns of fold enrichment, indicating high functional conservation. We also identified shared patterns of crosstalk between phosphoserines with motifs pSXpS, pSXXpS and pSXXXpS, where X is any amino acid, in both species indicating this is an evolutionary conserved signaling mechanism in flowering plants. However, our results are suggestive that there is greater co-occurrence of crosstalk between phosphorylation sites in Arabidopsis, and we were able to identify several pairs of motifs that are statistically significantly enriched to co-occur in Arabidopsis proteins, but not in rice.

bioinformatics↗

bioRxiv2017

Temporal dissociation of salience and prediction error responses to appetitive and aversive taste

The feedback-related negativity, a frontocentral event-related potential (ERP) occurring 200350 milliseconds (ms) after emotionally-valued outcomes, has been posited as the neural correlate of reward prediction error, a key component of associative learning. Recent evidence challenged this interpretation and has led to the suggestion that this ERP expresses salience, instead. Here we distinguish between utility prediction error and salience by delivering or withholding hedonistically matched appetitive and aversive tastes, and measure ERPs to cues signalling each taste. We observed a typical FRN (computed as the loss-minus-gain difference wave) to appetitive taste, but a reverse-FRN to aversive taste. When tested axiomatically, frontocentral ERPs showed a salience response across tastes, with a particularly early response to outcome delivery, supporting recent propositions of a fast, unsigned and unspecific response to salient stimuli. ERPs also expressed aversive prediction error peaking at 285ms, which conformed to the logic of an axiomatic model of prediction error. With stimuli that most resemble those used in animal models we did not detect any frontocentral ERP signal for utility prediction error, in contrast with dominant views of the functional role of the feedback-related negativity ERP. We link the animal and human literature and present a challenge for current perspectives on associative learning research using ERPs.

neuroscience↗

bioRxiv2017

Surgically disconnected temporal pole exhibits resting functional connectivity with remote brain regions

Functional connectivity, as measured by resting-state fMRI, has proven a powerful method for studying brain systems in the context of behavior, development, and disease states. However, the relationship of functional connectivity to structural connectivity remains unclear. If functional connectivity relies on structural connectivity, then anatomical isolation of a brain region should eliminate functional connectivity with other brain regions. We tested this by measuring functional connectivity of the surgically disconnected temporal pole in resection patients (N=5; mean age 37; 2F, 3M). Functional connectivity was evaluated based on coactivation of whole-brain fMRI data with the average low-frequency BOLD signal from disconnected tissue in each patient. In sharp contrast to our prediction, we observed significant functional connectivity between the disconnected temporal pole and remote brain regions in each disconnection case. These findings raise important questions about the neural bases of functional connectivity measures derived from the fMRI BOLD signal.

neuroscience↗

bioRxiv2017

Population Genomics And The Evolution Of Virulence In The Fungal Pathogen Cryptococcus neoformans

Cryptococcus neoformans is an opportunistic fungal pathogen that causes approximately 625,000 deaths per year from nervous system infections. Here, we leveraged a unique, genetically diverse population of C. neoformans from sub-Saharan Africa, commonly isolated from mopane trees, to determine how selective pressures in the environment coincidentally adapted C. neoformans for human virulence. Genome sequencing and phylogenetic analysis of 387 isolates, representing the global VNI and African VNB lineages, highlighted a deep, non-recombining split in VNB (herein VNBI and VNBII). VNBII was enriched for clinical samples relative to VNBI, while phenotypic profiling of 183 isolates demonstrated that VNBI isolates were significantly more resistant to oxidative stress and more heavily melanized than VNBII isolates. Lack of melanization in both lineages was associated with loss-of-function mutations in the BZP4 transcription factor. A genome-wide association study across all VNB isolates revealed sequence differences between clinical and environmental isolates in virulence factors and stress response genes. Inositol transporters and catabolism genes, which process sugars present in plants and the human nervous system, were identified as targets of selection in all three lineages. Further phylogenetic and population genomic analyses revealed extensive loss of genetic diversity in VNBI, suggestive of a history of population bottlenecks, along with unique evolutionary trajectories for mating type loci. These data highlight the complex evolutionary interplay between adaptation to natural environments and opportunistic infections, and that selection on specific pathways may predispose isolates to human virulence.

genomics↗

bioRxiv2016

Detection of long repeat expansions from PCR-free whole-genome sequence data

Identifying large repeat expansions such as those that cause amyotrophic lateral sclerosis (ALS) and Fragile X syndrome is challenging for short-read (100-150 bp) whole genome sequencing (WGS) data. A solution to this problem is an important step towards integrating WGS into precision medicine. We have developed a software tool called ExpansionHunter that, using PCR-free WGS short-read data, can genotype repeats at the locus of interest, even if the expanded repeat is larger than the read length. We applied our algorithm to WGS data from 3,001 ALS patients who have been tested for the presence of the C9orf72 repeat expansion with repeat-primed PCR (RP-PCR). Taking the RP-PCR calls as the ground truth, our WGS-based method identified pathogenic repeat expansions with 98.1% sensitivity and 99.7% specificity. Further inspection identified that all 11 conflicts were resolved as errors in the original RP-PCR results. Compared against this updated result, ExpansionHunter correctly classified all (212/212) of the expanded samples as either expansions (208) or potential expansions (4). Additionally, 99.9% (2,786/2,789) of the wild type samples were correctly classified as wild type by this method with the remaining two identified as possible expansions. We further applied our algorithm to a set of 144 samples where every sample had one of eight different pathogenic repeat expansions including examples associated with fragile X syndrome, Friedreichs ataxia and Huntingtons disease and correctly flagged all of the known repeat expansions. Finally, we tested the accuracy of our method for short repeats by comparing our genotypes with results from 860 samples sized using fragment length analysis and determined that our calls were >95% accurate. ExpansionHunter can be used to accurately detect known pathogenic repeat expansions and provides researchers with a tool that can be used to identify new pathogenic repeat expansions.

bioinformatics↗

bioRxiv2016

Differential protein expression marks the transition from infection with Opisthorchis viverrini to cholangiocarcinoma

Parts of Southeast Asia have the highest incidence of intrahepatic cholangiocarcinoma (CCA) in the world due to infection by the liver fluke Opisthorchis viverrini (Ov). Ov-associated CCA is the culmination of chronic Ov-infection, with the persistent production of the growth factors and cytokines associated with persistent inflammation, which can endure for years in Ov-infected individuals prior to transitioning to CCA. Isobaric labelling and tandem mass spectrometry of liver tissue from a hamster model of CCA was used to compare protein expression profiles from inflammed tissue (Ov-infected but not cancerous) versus cancerous tissue (Ov-induced CCA). Immunohistochemistry and immunoblotting were used to verify dysregulated proteins in the animal model and in human tissue. We identified 154 dysregulated proteins that marked the transition from Ov-infection to Ov-induced CCA, i.e. proteins dysregulated during carcinogenesis but not Ov-infection. The verification of dysregulated proteins in resected liver tissue from humans with Ov-associated CCA showed the numerous parallels in protein dysregulation between human and animal models of Ov-induced CCA. To identify potential circulating markers for CCA, dysregulated proteins were compared to proteins isolated from exosomes secreted by a human CCA cell line (KKU055) and 27 proteins were identified as dysregulated in CCA and present in exosomes. These data form the basis of potential diagnostic biomarkers for human Ov-associated CCA. The profile of protein dysregulation observed during chronic Ov-infection and then in Ov-induced CCA provides insight into the etiology of an infection-induced inflammation-related cancer.\n\nAbbreviations

cancer biology↗