Increasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity1. However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value2. Faba bean (Vicia fabaL.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13\uffe2\uff80\uff89Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the\uffc2\uffa0improvement of sustainable protein production across the\uffc2\uffa0Mediterranean, subtropical and northern temperate agroecological zones.Analysis of focal copy number variations (CNVs) is highly relevant for cancer research, as they pinpoint driver genes. More specifically, due to selective pressure oncogenes and tumor suppressor genes are more often affected by these events than neighboring passengers. In cases where multiple candidates co-reside in a genomic locus, careful comparison is required to either identify multigenic minimally deleted regions of synergistic co-mutations, or the true single driver gene. The study of focal CNVs in large cancer genome cohorts requires specialized visualization and statistical analysis.
ResultsWe developed the GenomeTornadoPlot R-package which generates gene-centric visualizations of CNV types, locations and lengths from cohortwise NGS data. Furthermore, the software enables the pairwise comparison of proximate genes to identify co-mutation patterns or driver-passenger hierarchies. The visual examination provided by GenomeTornadoPlot is further supported by adaptable local and global focality scoring. Integrated into the GenomeTornadoPlot R-Package is the comprehensive PCAWG database of CNVs, comprising 2976 cancer genome entities from 46 cohorts of the Pan-cancer Analysis of Whole Genomes project. The GenomeTornadoPlot R-package can be used to perform exploratory or hypothesis-driven analyses on the basis of the PCAWG data or in combination with data provided by the user.
Availability and implementationGenomeTornadoPlot is written in R script and released via github: <https://github.com/chenhong-dkfz/GenomeTornadoPlot/>. The package is under the license of GPL-3.0.
", "keywords": ["570", "DNA Copy Number Variations", "ddc-570", "Genomics", "Oncogenes", "004 Data processing Computer science", "Software", "ddc-004", "570 Life sciences", "004", "3. Good health"]}, "links": [{"href": "https://archiv.ub.uni-heidelberg.de/volltextserver/34483/1/btac037.pdf"}, {"href": "https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/34483/1/btac037.pdf"}, {"href": "https://academic.oup.com/bioinformatics/article-pdf/38/7/2036/49009547/btac037.pdf"}, {"href": "https://doi.org/10.1093/bioinformatics/btac037"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Bioinformatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/bioinformatics/btac037", "name": "item", "description": "10.1093/bioinformatics/btac037", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/bioinformatics/btac037"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-31T00:00:00Z"}}, {"id": "10138/356895", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:03Z", "type": "Journal Article", "created": "2023-03-08", "title": "The giant diploid faba genome unlocks variation in a global protein crop", "description": "AbstractIncreasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity 1 . However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value 2 . Faba bean ( Vicia faba L.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13\uffe2\uff80\uff89Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the\uffc2\uffa0improvement of sustainable protein production across the\uffc2\uffa0Mediterranean, subtropical and northern temperate agroecological zones. Analysis of focal copy number variations (CNVs) is highly relevant for cancer research, as they pinpoint driver genes. More specifically, due to selective pressure oncogenes and tumor suppressor genes are more often affected by these events than neighboring passengers. In cases where multiple candidates co-reside in a genomic locus, careful comparison is required to either identify multigenic minimally deleted regions of synergistic co-mutations, or the true single driver gene. The study of focal CNVs in large cancer genome cohorts requires specialized visualization and statistical analysis.
ResultsWe developed the GenomeTornadoPlot R-package which generates gene-centric visualizations of CNV types, locations and lengths from cohortwise NGS data. Furthermore, the software enables the pairwise comparison of proximate genes to identify co-mutation patterns or driver-passenger hierarchies. The visual examination provided by GenomeTornadoPlot is further supported by adaptable local and global focality scoring. Integrated into the GenomeTornadoPlot R-Package is the comprehensive PCAWG database of CNVs, comprising 2976 cancer genome entities from 46 cohorts of the Pan-cancer Analysis of Whole Genomes project. The GenomeTornadoPlot R-package can be used to perform exploratory or hypothesis-driven analyses on the basis of the PCAWG data or in combination with data provided by the user.
Availability and implementationGenomeTornadoPlot is written in R script and released via github: <https://github.com/chenhong-dkfz/GenomeTornadoPlot/>. The package is under the license of GPL-3.0.
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