Biology subjects

Bolger, A.

Publications and source records attributed to Bolger, A..

3 recordsLinked to original sources

bioRxiv2023

Helixer--de novo Prediction of Primary Eukaryotic Gene Models Combining Deep Learning and a Hidden Markov Model.

AO_SCPLOWBSTRACTC_SCPLOWGene structural annotation is a critical step in obtaining biological knowledge from genome sequences yet remains a major challenge in genomics projects. Current de novo Hidden Markov Models are limited in their capacity to model biological complexity; while current pipelines are resource-intensive and their results vary in quality with the available extrinsic data. Here, we build on our previous work in applying Deep Learning to gene calling to make a fully applicable, fast and user friendly tool for predicting primary gene models from DNA sequence alone. The quality is state-of-the-art, with predictions scoring closer by most measures to the references than to predictions from other de novo tools. Helixers predictions can be used as is or could be integrated in pipelines to boost quality further. Moreover, there is substantial potential for further improvements and advancements in gene calling with Deep Learning. Helixer is open source and available at https://github.com/weberlab-hhu/Helixer A web interface is available at https://www.plabipd.de/helixer_main.html

bioinformatics↗

bioRxiv2019

Plant-microbe co-evolution: allicin resistance in a Pseudomonas fluorescens strain (PfAR-1) isolated from garlic

The antibiotic defense substance allicin (diallylthiosulfinate) is produced by garlic (Allium sativum L.) after tissue damage, giving garlic its characteristic odor. Allicin is a redox-toxin that oxidizes thiols in glutathione and cellular proteins. A highly allicin-resistant Pseudomonas fluorescens strain (PfAR-1) was isolated from garlic, and genomic clones were shotgun electroporated into an allicin-susceptible P. syringae strain (Ps4612). Recipients showing allicin-resistance had all inherited a group of genes from one of three similar genomic islands (GI), that had been identified in an in silico analysis of the PfAR-1 genome. A core fragment of 8-10 congruent genes with redox-related functions, present in each GI, was shown to confer allicin-specific resistance to P. syringae, and even to an unrelated E. coli strain. Transposon mutagenesis and overexpression analyses revealed the contribution of individual candidate genes to allicin-resistance. Moreover, PfAR-1 was unusual in having 3 glutathione reductase (glr) genes, two copies in two of the GIs, but outside of the core group, and one copy in the PfAR-1 genome. Glr activity was approximately 2-fold higher in PfAR-1 than in related susceptible Pf0-1, with only a single glr gene. Moreover, an E. coli {Delta}glr mutant showed increased susceptibility to allicin, which was complemented by PfAR-1 glr1. Taken together, our data support a multi-component resistance mechanism against allicin, achieved through horizontal gene transfer during coevolution, and allowing exploitation of the garlic ecological niche. GI regions syntenic with PfAR-1 GIs are present in other plant-associated bacterial species, perhaps suggesting a wider role in adaptation to plants per se.

evolutionary biology↗

bioRxiv2018

The genome and metabolome of the tobacco tree, Nicotiana glauca: a potential renewable feedstock for the bioeconomy

BackgroundGiven its tolerance to stress and its richness in particular secondary metabolites, the tobacco tree, Nicotiana glauca, has been considered a promising biorefinery feedstock that would not be competitive with food and fodder crops.\n\nResultsHere we present a 3.5 Gbp draft sequence and annotation of the genome of N. glauca spanning 731,465 scaffold sequences, with an N50 size of approximately 92 kbases. Furthermore, we supply a comprehensive transcriptome and metabolome analysis of leaf development comprising multiple techniques and platforms.\n\nThe genome sequence is predicted to cover nearly 80% of the estimated total genome size of N. glauca. With 73,799 genes predicted and a BUSCO score of 94.9%, we have assembled the majority of gene-rich regions successfully. RNA-Seq data revealed stage-and/or tissue-specific expression of genes, and we determined a general trend of a decrease of tricarboxylic acid cycle metabolites and an increase of terpenoids as well as some of their corresponding transcripts during leaf development.\n\nConclusionThe N. glauca draft genome and its detailed transcriptome, together with paired metabolite data, constitute a resource for future studies of valuable compound analysis in tobacco species and present the first steps towards a further resolution of phylogenetic, whole genome studies in tobacco.

plant biology↗