{"type": "FeatureCollection", "features": [{"id": "10.1038/s41586-023-05791-5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:18:00Z", "type": "Journal Article", "created": "2023-03-08", "title": "The giant diploid faba genome unlocks variation in a global protein crop", "description": "Abstract<p>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.</p", "keywords": ["Crops", " Agricultural", "DNA Copy Number Variations", "Retroelements", "[SDV]Life Sciences [q-bio]", "DNA", " Satellite", "Genes", " Plant", "630", "Article", "Chromosomes", " Plant", "Plant Proteins", "Recombination", " Genetic", "2. Zero hunger", "Geography", "Gene Amplification", "Genetic Variation", "Genomics", "15. Life on land", "11831 Plant biology", "Diploidy", "Agronomy", "metabolism ; Genome-Wide Association Study ; Plant Proteins ; genetics ; Plant Breeding ; Vicia faba ; DNA Copy Number Variations ; Diploidy", "Vicia faba", "[SDV] Life Sciences [q-bio]", "Plant Breeding", "Genetics", " developmental biology", " physiology", "13. 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It has been suggested that adaptation concomitant with range shifts plays key roles in species responses during climate oscillations, but the role of selection for local adaptation to climatic changes remains largely unexplored. Here, we investigated population structure, demographic history and signatures of climate-driven selection based on genome-wide polymorphism data of 141 Japanese Arabidopsis halleri individuals, with European ones as outgroups. Coalescent-based analyses suggested a genetic differentiation between Japanese subpopulations since the Last Glacial Period (LGP), which would have contributed to shaping the current pattern of population structure. Population demographic analysis revealed the population size fluctuations in the LGP, which were particularly prominent since the subpopulations started to diverge (\uffe2\uff88\uffbc50, 000 years ago). The ecological niche modeling predicted the geographic or distribution range shifts from southern coastal regions to northern coastal and mountainous areas, possibly in association with the population size fluctuations. Through genome-wide association analyses of bioclimatic variables and selection scans, we investigated whether climate-associated loci are enriched in the extreme tails of selection scans, and demonstrated the prevailing signatures of selection, particularly toward a warmer climate in southern subpopulations and a drier environment in northern subpopulations, which may have taken place during or after the LGP. Our study highlights the importance of integrating climate associations, selection scans and population demographic analyses for identifying genomic signatures of population-specific adaptation, which would also help us predict the evolutionary responses to future climate changes.</p", "keywords": ["[SDV] Life Sciences [q-bio]", "Genetics", " Population", "Special Issue - Regular Paper", "Japan", "Climate", "Climate Change", "Acclimatization", "Arabidopsis", "Selection", " Genetic", "Adaptation", " Physiological", "Genome", " Plant", "Genome-Wide Association Study"]}, "links": [{"href": "https://academic.oup.com/pcp/advance-article-pdf/doi/10.1093/pcp/pcae113/60430271/pcae113.pdf"}, {"href": "https://doi.org/10.1093/pcp/pcae113"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20And%20Cell%20Physiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/pcp/pcae113", "name": "item", "description": "10.1093/pcp/pcae113", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/pcp/pcae113"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-09-30T00:00:00Z"}}, {"id": "10.1105/tpc.20.00318", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:18:49Z", "type": "Journal Article", "created": "2020-10-10", "title": "ARADEEPOPSIS, an Automated Workflow for Top-View Plant Phenomics using Semantic Segmentation of Leaf States", "description": "Linking plant phenotype to genotype is a common goal to both plant breeders and geneticists. However, collecting phenotypic data for large numbers of plants remain a bottleneck. Plant phenotyping is mostly image based and therefore requires rapid and robust extraction of phenotypic measurements from image data. However, because segmentation tools usually rely on color information, they are sensitive to background or plant color deviations. We have developed a versatile, fully open-source pipeline to extract phenotypic measurements from plant images in an unsupervised manner. ARADEEPOPSIS (https://github.com/Gregor-Mendel-Institute/aradeepopsis) uses semantic segmentation of top-view images to classify leaf tissue into three categories: healthy, anthocyanin rich, and senescent. This makes it particularly powerful at quantitative phenotyping of different developmental stages, mutants with aberrant leaf color and/or phenotype, and plants growing in stressful conditions. On a panel of 210 natural Arabidopsis (Arabidopsis thaliana) accessions, we were able to not only accurately segment images of phenotypically diverse genotypes but also to identify known loci related to anthocyanin production and early necrosis in genome-wide association analyses. Our pipeline accurately processed images of diverse origin, quality, and background composition, and of a distantly related Brassicaceae. ARADEEPOPSIS is deployable on most operating systems and high-performance computing environments and can be used independently of bioinformatics expertise and resources.", "keywords": ["0301 basic medicine", "0303 health sciences", "Genotype", "Large-Scale Biology Articles", "Arabidopsis", "Computational Biology", "Semantics", "Workflow", "Plant Leaves", "03 medical and health sciences", "Phenotype", "Image Processing", " Computer-Assisted", "Phenomics", "Software", "Genome-Wide Association Study"]}, "links": [{"href": "https://doi.org/10.1105/tpc.20.00318"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20Plant%20Cell", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1105/tpc.20.00318", "name": "item", "description": "10.1105/tpc.20.00318", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1105/tpc.20.00318"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-09T00:00:00Z"}}, {"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": "Abstract                   <p>                     Increasing 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.                   </p", "keywords": ["Crops", " Agricultural", "DNA Copy Number Variations", "Retroelements", "[SDV]Life Sciences [q-bio]", "DNA", " Satellite", "Genes", " Plant", "630", "Article", "Chromosomes", " Plant", "Plant Proteins", "Recombination", " Genetic", "2. Zero hunger", "Geography", "Gene Amplification", "Genetic Variation", "Genomics", "15. 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It has been suggested that adaptation concomitant with range shifts plays key roles in species responses during climate oscillations, but the role of selection for local adaptation to climatic changes remains largely unexplored. Here, we investigated population structure, demographic history and signatures of climate-driven selection based on genome-wide polymorphism data of 141 Japanese Arabidopsis halleri individuals, with European ones as outgroups. Coalescent-based analyses suggested a genetic differentiation between Japanese subpopulations since the Last Glacial Period (LGP), which would have contributed to shaping the current pattern of population structure. Population demographic analysis revealed the population size fluctuations in the LGP, which were particularly prominent since the subpopulations started to diverge (\uffe2\uff88\uffbc50, 000 years ago). The ecological niche modeling predicted the geographic or distribution range shifts from southern coastal regions to northern coastal and mountainous areas, possibly in association with the population size fluctuations. Through genome-wide association analyses of bioclimatic variables and selection scans, we investigated whether climate-associated loci are enriched in the extreme tails of selection scans, and demonstrated the prevailing signatures of selection, particularly toward a warmer climate in southern subpopulations and a drier environment in northern subpopulations, which may have taken place during or after the LGP. Our study highlights the importance of integrating climate associations, selection scans and population demographic analyses for identifying genomic signatures of population-specific adaptation, which would also help us predict the evolutionary responses to future climate changes.</p", "keywords": ["Demographic history", "Arabidopsis halleri", "Local adaptation", "Climate", "Climate Change", "Acclimatization", "Arabidopsis", "Adaptation", " Physiological", "[SDV.EE.BIO] Life Sciences [q-bio]/Ecology", " environment/Bioclimatology", "Genetics", " Population", "Special Issue - Regular Paper", "Japan", "[SDV.GEN.GPL] Life Sciences [q-bio]/Genetics/Plants genetics", "[SDV.BID.EVO] Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE]", "[SDV.GEN.GPO] Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE]", "Climate change", "Selection", " Genetic", "Population genomics", "Glacial cycles", "Genome", " Plant", "Genome-Wide Association Study"]}, "links": [{"href": "https://academic.oup.com/pcp/advance-article-pdf/doi/10.1093/pcp/pcae113/60430271/pcae113.pdf"}, {"href": "https://doi.org/PMC12085087"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20And%20Cell%20Physiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC12085087", "name": "item", "description": "PMC12085087", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC12085087"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-09-30T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Genome-Wide+Association+Study&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Genome-Wide+Association+Study&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Genome-Wide+Association+Study&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Genome-Wide+Association+Study&offset=5", "hreflang": "en-US"}], "numberMatched": 5, "numberReturned": 5, "distributedFeatures": [], "timeStamp": "2026-04-05T04:14:06.766931Z"}