Biology subjects

O'Sullivan, D. M.

Publications and source records attributed to O'Sullivan, D. M..

3 recordsLinked to original sources

bioRxiv2020

VC1 catalyzes a key step in the biosynthesis of vicine from GTP in faba bean

Faba bean is a widely adapted and high-yielding legume cultivated for its protein-rich seeds1. However, the seeds accumulate the anti-nutritional pyrimidine glucosides vicine and convicine, which can cause haemolytic anaemia--favism--in the 400 million individuals genetically predisposed by a deficiency in glucose-6-phosphate dehydrogenase2. Here, we identify the first enzyme associated with vicine and convicine biosynthesis, which we name VC1. We show that VC1 co-locates with the major QTL for vicine and convicine content and that the expression of VC1 correlates highly with vicine content across tissues. We also show that low-vicine varieties express a version of VC1 carrying a small, frame-shift insertion, and that overexpression of wild-type VC1 leads to an increase in vicine levels. VC1 encodes a functional GTP cyclohydrolase II, an enzyme normally involved in riboflavin biosynthesis from the purine GTP. Through feeding studies, we demonstrate that GTP is a precursor of vicine both in faba bean and in the distantly related plant bitter gourd. Our results reveal an unexpected biosynthetic origin for vicine and convicine and pave the way for the development of faba bean cultivars that are free from these anti-nutrients, providing a safe and sustainable source of dietary protein.

biochemistry↗

bioRxiv2019

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

BackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a one-stop test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.\n\nMethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ( participants) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.\n\nResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.\n\nConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

microbiology↗

bioRxiv2019

A framework for gene mapping in wheat demonstrated using the Yr7 yellow rust resistance gene

We used three approaches to map the yellow rust resistance gene Yr7 and identify associated SNPs in wheat. First, we used a traditional QTL mapping approach using a double haploid (DH) population and mapped Yr7 to a low-recombination region of chromosome 2B. To fine map the QTL, we then used an association mapping panel. Both populations were SNP array genotyped allowing alignment of QTL and genome-wide association scans based on common segregating SNPs. Analysis of the association panel spanning the QTL interval, narrowed the interval down to a single haplotype block. Finally, we used mapping-by-sequencing of resistant and susceptible DH bulks to identify a candidate gene in the interval showing high homology to a previously suggested Yr7 candidate and to populate the Yr7 interval with a higher density of polymorphisms. We highlight the power of combining mapping-by-sequencing, delivering a complete list of gene-based segregating polymorphisms in the interval with the high recombination, low LD precision of the association mapping panel. Our mapping-by-sequencing methodology is applicable to any trait and our results validate the approach in wheat, where with a near complete reference genome sequence, we are able to define a small interval containing the causative gene.\n\nHighlightWe show progression from genetic mapping to mapping-by-sequencing and the overlap of defined intervals by each approach culminating with interval refinement and identification of a candidate gene for disease resistance.

genetics↗