Biology subjects

Bolger, M. E.

Publications and source records attributed to Bolger, M. E..

3 recordsLinked to original sources

bioRxiv2025

PubPlant: a continuously updated online resource for sequenced and published plant genomes

Advances in next-generation sequencing technologies over the last decade have substantially reduced the cost and effort required to sequence plant genomes. Whereas early efforts focused primarily on economically important crops and model species, attention has now turned to a broader range of plants, including those with larger and more complex genomes. In 2024, the genomes of 500 plant species were published, including 370 sequenced for the first time. Tracking and providing access to published plant genomes (now covering more than 1800 species) is an invaluable service for plant researchers. PubPlant is an online resource that serves this purpose by cataloging published plant genome sequences and offering multiple visualizations (https://www.plabipd.de/pubplant_main.html). It includes a chronology of genome publications, and cladograms to display the phylogenetic relationships among the sequenced plants. An overview diagram for seed plants highlights taxonomic orders and families with sequenced species, and reveals those that have been overlooked thus far. As a use case for PubPlant, we evaluated the status of sequenced food crops. We found that the five plant families featuring the most food crops were those containing the most sequenced plant species.

plant biology↗

bioRxiv2017

LOGAN: A framework for LOssless Graph-based ANalysis of high throughput sequence data

Recent massive growth in the production of sequencing data necessitates matching improve-ments in bioinformatics tools to effectively utilize it. Existing tools suffer from limitations in both scalability and applicability which are inherent to their underlying algorithms and data structures. We identify the key requirements for the ideal data structure for sequence analy-ses: it should be informationally lossless, locally updatable, and memory efficient; requirements which are not met by data structures underlying the major assembly strategies Overlap Layout Consensus and De Bruijn Graphs. We therefore propose a new data structure, the LOGAN graph, which is based on a memory efficient Sparse De Bruijn Graph with routing information. Innovations in storing routing information and careful implementation allow sequence datasets for Escherichia coli (4.6Mbp, 117x coverage), Arabidopsis thaliana (135Mbp, 17.5x coverage) and Solanum pennellii (1.2Gbp, 47x coverage) to be loaded into memory on a desktop computer in seconds, minutes, and hours respectively. Memory consumption is competitive with state of the art alternatives, while losslessly representing the reads in an indexed and updatable form. Both Second and Third Generation Sequencing reads are supported. Thus, the LOGAN graph is positioned to be the backbone for major breakthroughs in sequence analysis such as integrated hybrid assembly, assembly of exceptionally large and repetitive genomes, as well as assembly and representation of pan-genomes.

bioinformatics↗

bioRxiv2017

Reconstructing The Gigabase Plant Genome Of Solanum pennellii Using Nanopore Sequencing

Recent updates in sequencing technology have made it possible to obtain Gigabases of sequence data from one single flowcell. Prior to this update, the nanopore sequencing technology was mainly used to analyze and assemble microbial samples1-3. Here, we describe the generation of a comprehensive nanopore sequencing dataset with a median fragment size of 11,979 bp for the wild tomato species Solanum pennellii featuring an estimated genome size of ca 1.0 to 1.1 Gbases. We describe its genome assembly to a contig N50 of 2.5 MB using a pipeline comprising a Canu4 pre-processing and a subsequent assembly using SMARTdenovo. We show that the obtained nanopore based de novo genome reconstruction is structurally highly similar to that of the reference S. pennellii LA7165 genome but has a high error rate caused mostly by deletions in homopolymers. After polishing the assembly with Illumina short read data we obtained an error rate of <0.02 % when assessed versus the same Illumina data. More importantly however we obtained a gene completeness of 96.53% which even slightly surpasses that of the reference S. pennellii genome5. Taken together our data indicate such long read sequencing data can be used to affordably sequence and assemble Gbase sized diploid plant genomes.\n\nRaw data is available at http://www.plabipd.de/portal/solanum-pennellii and has been deposited as PRJEB19787.

genomics↗