ABSTRACT
Background: Although draft genomes are available for most agronomically important plant species, the majority are incomplete, highly fragmented, and often riddled with assembly and scaffolding errors. These assembly issues hinder advances in tool development for functional genomics and systems biology. Findings: Here we utilized a robust, cost-effective approach to produce high-quality reference genomes. We report a near-complete genome of diploid woodland strawberry (Fragaria vesca) using single-molecule real-time sequencing from Pacific Biosciences (PacBio). This assembly has a contig N50 length of â¼7.9 million base pairs (Mb), representing a â¼300-fold improvement of the previous version. The vast majority (>99.8%) of the assembly was anchored to 7 pseudomolecules using 2 sets of optical maps from Bionano Genomics. We obtained â¼24.96 Mb of sequence not present in the previous version of the F. vesca genome and produced an improved annotation that includes 1496 new genes. Comparative syntenic analyses uncovered numerous, large-scale scaffolding errors present in each chromosome in the previously published version of the F. vesca genome. Conclusions: Our results highlight the need to improve existing short-read based reference genomes. Furthermore, we demonstrate how genome quality impacts commonly used analyses for addressing both fundamental and applied biological questions.
Subject(s)
Fragaria/genetics , Genome, Plant , High-Throughput Nucleotide Sequencing/methods , Optical Imaging/methods , Physical Chromosome Mapping/methods , DNA Methylation , Gene Ontology , Genome Size , Molecular Sequence Annotation , Optical Imaging/instrumentation , Physical Chromosome Mapping/instrumentation , SyntenyABSTRACT
Genetic linkage map is helpful for analysis on heredity of some gene families and map-based gene cloning because of its simple and elegant manifestation. One software is in need to draw a gene physical map, which shows a manner similar to the genetic linkage map, based on the relative physical distance between genes. Although some tools like GBrowse and MapViewer etc. are available to draw gene physical map, there are obvious limitations for them: (1) the data need to be decorated in advance; (2) users can't modify results. Therefore, we developed a bio-assisted mapping software--MapGene2Chrom with PC and web versions, which is based on Perl and SVG languages. The software can be used to draw the corresponding physical map quickly in SVG format based on the input data. It will become a useful tool for drawing gene physical map with the advantages of simple input data format, easily modified output and very good portability.
