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Pardeshi LA, van Duivenbode I, Pel MJC, Jonkheer EM, Kupczok A, de Ridder D, Smit S, van der Lee TAJ. Pangenomics to understand prophage dynamics in the Pectobacterium genus and the radiating lineages of Pectobacterium brasiliense. Microb Genom 2025; 11. [PMID: 40331911 DOI: 10.1099/mgen.0.001392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2025] Open
Abstract
Bacterial pathogens of the genus Pectobacterium are responsible for soft-rot and blackleg diseases in a wide range of crops and have a global impact on food production. The emergence of new lineages and their competitive succession is frequently observed in Pectobacterium species, in particular in Pectobacterium brasiliense. With a focus on one such recently emerged P. brasiliense lineage in the Netherlands that causes blackleg in potatoes, we studied genome evolution in this genus using a reference-free graph-based pangenome approach. We clustered 1,977,865 proteins from 454 Pectobacterium spp. genomes into 30,156 homology groups. The Pectobacterium genus pangenome is open, and its growth is mainly contributed by the accessory genome. Bacteriophage genes were enriched in the accessory genome and contributed 16% of the pangenome. Blackleg-causing P. brasiliense isolates had increased genome size with high levels of prophage integration. To study the diversity and dynamics of these prophages across the pangenome, we developed an approach to trace prophages across genomes using pangenome homology group signatures. We identified lineage-specific as well as generalist bacteriophages infecting Pectobacterium species. Our results capture the ongoing dynamics of mobile genetic elements, even in the clonal lineages. The observed lineage-specific prophage dynamics provide mechanistic insights into Pectobacterium pangenome growth and contribution to the radiating lineages of P. brasiliense.
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Affiliation(s)
- Lakhansing A Pardeshi
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, Netherlands
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708PB, Wageningen, Netherlands
| | - Inge van Duivenbode
- Dutch General Inspection Service for Agricultural Seeds and Seed Potatoes (NAK), Randweg 14, 8304 AS Emmeloord, Netherlands
| | - Michiel J C Pel
- Netherlands Institute for Vectors, Invasive Plants and Plant Health (NIVIP), National Plant Protection Organization (NPPO), Netherlands Food and Consumer Product Safety Authority (NVWA), Geertjesweg 15, 6706 EA Wageningen, Netherlands
| | - Eef M Jonkheer
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, Netherlands
| | - Anne Kupczok
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, Netherlands
| | - Dick de Ridder
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, Netherlands
| | - Sandra Smit
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, Netherlands
| | - Theo A J van der Lee
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708PB, Wageningen, Netherlands
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2
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Ruperao P, Rangan P, Shah T, Sharma V, Rathore A, Mayes S, Pandey MK. Developing pangenomes for large and complex plant genomes and their representation formats. J Adv Res 2025:S2090-1232(25)00071-2. [PMID: 39894347 DOI: 10.1016/j.jare.2025.01.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 01/27/2025] [Accepted: 01/27/2025] [Indexed: 02/04/2025] Open
Abstract
BACKGROUND The development of pangenomes has revolutionized genomic studies by capturing the complete genetic diversity within a species. Pangenome assembly integrates data from multiple individuals to construct a comprehensive genomic landscape, revealing both core and accessory genomic elements. This approach enables the identification of novel genes, structural variations, and gene presence-absence variations, providing insights into species evolution, adaptation, and trait variation. Representing pangenomes requires innovative visualization formats that effectively convey the complex genomic structures and variations. AIM This review delves into contemporary methodologies and recent advancements in constructing pangenomes, particularly in plant genomes. It examines the structure of pangenome representation, including format comparison, conversion, visualization techniques, and their implications for enhancing crop improvement strategies. KEY SCIENTIFIC CONCEPTS OF REVIEW Earlier comparative studies have illuminated novel gene sequences, copy number variations, and presence-absence variations across diverse crop species. The concept of a pan-genome, which captures multiple genetic variations from a broad spectrum of genotypes, offers a holistic perspective of a species' genetic makeup. However, constructing a pan-genome for plants with larger genomes poses challenges, including managing vast genome sequence data and comprehending the genetic variations within the germplasm. To address these challenges, researchers have explored cost-effective alternatives to encapsulate species diversity in a single assembly known as a pangenome. This involves reducing the volume of genome sequences while focusing on genetic variations. With the growing prominence of the pan-genome concept in plant genomics, several software tools have emerged to facilitate pangenome construction. This review sheds light on developing and utilizing software tools tailored for constructing pan-genomes in plants. It also discusses representation formats suitable for downstream analyses, offering valuable insights into the genetic landscape and evolutionary dynamics of plant species. In summary, this review underscores the significance of pan-genome construction and representation formats in resolving the genetic architecture of plants, particularly those with complex genomes. It provides a comprehensive overview of recent advancements, aiding in exploring and understanding plant genetic diversity.
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Affiliation(s)
- Pradeep Ruperao
- Center of Excellence in Genomics and Systems Biology (CEGSB) and Center for Pre-Breeding Research (CPBR), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
| | - Parimalan Rangan
- ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India; Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Australia
| | - Trushar Shah
- International Institute of Tropical Agriculture (IITA), Nairobi, Kenya
| | - Vinay Sharma
- Center of Excellence in Genomics and Systems Biology (CEGSB) and Center for Pre-Breeding Research (CPBR), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Abhishek Rathore
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Sean Mayes
- Center of Excellence in Genomics and Systems Biology (CEGSB) and Center for Pre-Breeding Research (CPBR), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Manish K Pandey
- Center of Excellence in Genomics and Systems Biology (CEGSB) and Center for Pre-Breeding Research (CPBR), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
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3
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van Workum DJM, Mehrem SL, Snoek BL, Alderkamp MC, Lapin D, Mulder FFM, Van den Ackerveken G, de Ridder D, Schranz ME, Smit S. Lactuca super-pangenome reduces bias towards reference genes in lettuce research. BMC PLANT BIOLOGY 2024; 24:1019. [PMID: 39468479 PMCID: PMC11514843 DOI: 10.1186/s12870-024-05712-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 10/15/2024] [Indexed: 10/30/2024]
Abstract
BACKGROUND Breeding of lettuce (Lactuca sativa L.), the most important leafy vegetable worldwide, for enhanced disease resistance and resilience relies on multiple wild relatives to provide the necessary genetic diversity. In this study, we constructed a super-pangenome based on four Lactuca species (representing the primary, secondary and tertiary gene pools) and comprising 474 accessions. We include 68 newly sequenced accessions to improve cultivar coverage and add important foundational breeding lines. RESULTS With the super-pangenome we find substantial presence/absence variation (PAV) and copy-number variation (CNV). Functional enrichment analyses of core and variable genes show that transcriptional regulators are conserved whereas disease resistance genes are variable. PAV-genome-wide association studies (GWAS) and CNV-GWAS are largely congruent with single-nucleotide polymorphism (SNP)-GWAS. Importantly, they also identify several major novel quantitative trait loci (QTL) for resistance against Bremia lactucae in variable regions not present in the reference lettuce genome. The usability of the super-pangenome is demonstrated by identifying the likely origin of non-reference resistance loci from the wild relatives Lactuca serriola, Lactuca saligna and Lactuca virosa. CONCLUSIONS The super-pangenome offers a broader view on the gene repertoire of lettuce, revealing relevant loci that are not in the reference genome(s). The provided methodology and data provide a strong basis for research into PAVs, CNVs and other variation underlying important biological traits of lettuce and other crops.
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Affiliation(s)
- Dirk-Jan M van Workum
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, 6708 PB, the Netherlands
| | - Sarah L Mehrem
- Theoretical Biology & Bioinformatics, Utrecht University, Padualaan 8, Utrecht, 3584 CH, the Netherlands
| | - Basten L Snoek
- Theoretical Biology & Bioinformatics, Utrecht University, Padualaan 8, Utrecht, 3584 CH, the Netherlands
| | - Marrit C Alderkamp
- Translational Plant Biology, Utrecht University, Padualaan 8, Utrecht, 3584 CH, the Netherlands
| | - Dmitry Lapin
- Translational Plant Biology, Utrecht University, Padualaan 8, Utrecht, 3584 CH, the Netherlands
| | - Flip F M Mulder
- Department of Genetics, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, the Netherlands
| | | | - Dick de Ridder
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, 6708 PB, the Netherlands
| | - M Eric Schranz
- Biosystematics Group, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, 6708 PB, the Netherlands
| | - Sandra Smit
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, 6708 PB, the Netherlands.
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4
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Langschied F, Bordin N, Cosentino S, Fuentes-Palacios D, Glover N, Hiller M, Hu Y, Huerta-Cepas J, Coelho LP, Iwasaki W, Majidian S, Manzano-Morales S, Persson E, Richards TA, Gabaldón T, Sonnhammer E, Thomas PD, Dessimoz C, Ebersberger I. Quest for Orthologs in the Era of Biodiversity Genomics. Genome Biol Evol 2024; 16:evae224. [PMID: 39404012 PMCID: PMC11523110 DOI: 10.1093/gbe/evae224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/11/2024] [Indexed: 11/01/2024] Open
Abstract
The era of biodiversity genomics is characterized by large-scale genome sequencing efforts that aim to represent each living taxon with an assembled genome. Generating knowledge from this wealth of data has not kept up with this pace. We here discuss major challenges to integrating these novel genomes into a comprehensive functional and evolutionary network spanning the tree of life. In summary, the expanding datasets create a need for scalable gene annotation methods. To trace gene function across species, new methods must seek to increase the resolution of ortholog analyses, e.g. by extending analyses to the protein domain level and by accounting for alternative splicing. Additionally, the scope of orthology prediction should be pushed beyond well-investigated proteomes. This demands the development of specialized methods for the identification of orthologs to short proteins and noncoding RNAs and for the functional characterization of novel gene families. Furthermore, protein structures predicted by machine learning are now readily available, but this new information is yet to be integrated with orthology-based analyses. Finally, an increasing focus should be placed on making orthology assignments adhere to the findable, accessible, interoperable, and reusable (FAIR) principles. This fosters green bioinformatics by avoiding redundant computations and helps integrating diverse scientific communities sharing the need for comparative genetics and genomics information. It should also help with communicating orthology-related concepts in a format that is accessible to the public, to counteract existing misinformation about evolution.
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Affiliation(s)
- Felix Langschied
- Department for Applied Bioinformatics, Institute of Cell Biology and Neuroscience, Goethe University, Frankfurt, Germany
| | - Nicola Bordin
- Institute of Structural and Molecular Biology, University College London, WC1E 6BT, London, UK
| | - Salvatore Cosentino
- Department of Integrated Biosciences, The University of Tokyo, 277-0882 Tokyo, Japan
| | - Diego Fuentes-Palacios
- Barcelona Supercomputing Center (BSC-CNS), 08034 Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
| | - Natasha Glover
- SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
| | - Michael Hiller
- Department of Comparative Genomics, Institute of Cell Biology and Neuroscience, Goethe University, Frankfurt, Germany
| | - Yanhui Hu
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, Boston, MA 02115, USA
| | - Jaime Huerta-Cepas
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Campus de Montegancedo-UPM, Madrid, Spain
| | - Luis Pedro Coelho
- Centre for Microbiome Research, School of Biomedical Sciences, Queensland University of Technology, Translational Research Institute, Woolloongabba, Queensland, Australia
| | - Wataru Iwasaki
- Department of Integrated Biosciences, University of Tokyo, 277-0882 Tokyo, Japan
| | - Sina Majidian
- SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
| | - Saioa Manzano-Morales
- Barcelona Supercomputing Center (BSC-CNS), 08034 Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
| | - Emma Persson
- Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Solna, Sweden
| | | | - Toni Gabaldón
- Barcelona Supercomputing Center (BSC-CNS), 08034 Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
- CIBER de Enfermedades Infecciosas, Instituto de Salud Carlos III, Madrid, Spain
| | - Erik Sonnhammer
- Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Solna, Sweden
| | - Paul D Thomas
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Christophe Dessimoz
- SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
| | - Ingo Ebersberger
- Department for Applied Bioinformatics, Institute of Cell Biology and Neuroscience, Goethe University, Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Biodiversity and Climate Research Centre (S-BIK-F), Frankfurt am Main, Germany
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5
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Garassino F, Bengoa Luoni S, Cumerlato T, Reyes Marquez F, Harbinson J, Aarts MGM, Nijveen H, Smit S. Cross-species transcriptomics reveals differential regulation of essential photosynthesis genes in Hirschfeldia incana. G3 (BETHESDA, MD.) 2024; 14:jkae175. [PMID: 39115294 PMCID: PMC11457080 DOI: 10.1093/g3journal/jkae175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 07/06/2024] [Indexed: 10/08/2024]
Abstract
Photosynthesis is the only yield-related trait not yet substantially improved by plant breeding. Previously, we have established H. incana as the model plant for high photosynthetic light-use efficiency (LUE). Now we aim to unravel the genetic basis of this trait in H. incana, potentially contributing to the improvement of photosynthetic LUE in other species. Here, we compare its transcriptomic response to high light with that of Arabidopsis thaliana, Brassica rapa, and Brassica nigra, 3 fellow Brassicaceae members with lower photosynthetic LUE. We built a high-light, high-uniformity growing environment, in which the plants developed normally without signs of stress. We compared gene expression in contrasting light conditions across species, utilizing a panproteome to identify orthologous proteins. In-depth analysis of 3 key photosynthetic pathways showed a general trend of lower gene expression under high-light conditions for all 4 species. However, several photosynthesis-related genes in H. incana break this trend. We observed cases of constitutive higher expression (like antenna protein LHCB8), treatment-dependent differential expression (as for PSBE), and cumulative higher expression through simultaneous expression of multiple gene copies (like LHCA6). Thus, H. incana shows differential regulation of essential photosynthesis genes, with the light-harvesting complex as the first point of deviation. The effect of these expression differences on protein abundance and turnover, and ultimately the high photosynthetic LUE phenotype is relevant for further investigation. Furthermore, this transcriptomic resource of plants fully grown under, rather than briefly exposed to, a very high irradiance, will support the development of highly efficient photosynthesis in crops.
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Affiliation(s)
- Francesco Garassino
- Laboratory of Genetics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Sofia Bengoa Luoni
- Laboratory of Genetics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Tommaso Cumerlato
- Laboratory of Genetics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Francisca Reyes Marquez
- Laboratory of Genetics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Jeremy Harbinson
- Laboratory of Biophysics, Wageningen University & Research, Stippeneng 4, Wageningen 6708 WE, The Netherlands
| | - Mark G M Aarts
- Laboratory of Genetics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Harm Nijveen
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Sandra Smit
- Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
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van der Lee TAJ, van Gent-Pelzer MPE, Jonkheer EM, Brankovics B, Houwers IM, van der Wolf JM, Bonants PJM, van Duivenbode I, Vreeburg RAM, Nas M, Smit S. An Efficient Triplex TaqMan Quantitative PCR to Detect a Blackleg-Causing Lineage of Pectobacterium brasiliense in Potato Based on a Pangenome Analysis. Microorganisms 2023; 11:2080. [PMID: 37630640 PMCID: PMC10459533 DOI: 10.3390/microorganisms11082080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 08/08/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023] Open
Abstract
P. brasiliense is an important bacterial pathogen causing blackleg (BL) in potatoes. Nevertheless, P. brasiliense is often detected in seed lots that do not develop any of the typical blackleg symptoms in the potato crop when planted. Field bioassays identified that P. brasiliense strains can be categorized into two distinct classes, some able to cause blackleg symptoms and some unable to do it. A comparative pangenomic approach was performed on 116 P. brasiliense strains, of which 15 were characterized as BL-causing strains and 25 as non-causative. In a genetically homogeneous clade comprising all BL-causing P. brasiliense strains, two genes only present in the BL-causing strains were identified, one encoding a predicted lysozyme inhibitor Lprl (LZI) and one encoding a putative Toll/interleukin-1 receptor (TIR) domain-containing protein. TaqMan assays for the specific detection of BL-causing P. brasiliense were developed and integrated with the previously developed generic P. brasiliense assay into a triplex TaqMan assay. This simultaneous detection makes the scoring more efficient as only a single tube is needed, and it is more robust as BL-causing strains of P. brasiliense should be positive for all three assays. Individual P. brasiliense strains were found to be either positive for all three assays or only for the P. brasiliense assay. In potato samples, the mixed presence of BL-causing and not BL-causing P. brasiliense strains was observed as shown by the difference in Ct value of the TaqMan assays. However, upon extension of the number of strains, it became clear that in recent years additional BL-causing lineages of P. brasiliense were detected for which additional assays must be developed.
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Affiliation(s)
- Theo A. J. van der Lee
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Marga P. E. van Gent-Pelzer
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Eef M. Jonkheer
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Balázs Brankovics
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Ilse M. Houwers
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Jan M. van der Wolf
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Peter J. M. Bonants
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Inge van Duivenbode
- Dutch General Inspection Service (NAK), Randweg 14, 8304 AS Emmeloord, The Netherlands
| | - Robert A. M. Vreeburg
- Dutch General Inspection Service (NAK), Randweg 14, 8304 AS Emmeloord, The Netherlands
| | - Mathijs Nas
- Dutch General Inspection Service (NAK), Randweg 14, 8304 AS Emmeloord, The Netherlands
| | - Sandra Smit
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
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7
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Garassino F, Wijfjes RY, Boesten R, Reyes Marquez F, Becker FFM, Clapero V, van den Hatert I, Holmer R, Schranz ME, Harbinson J, de Ridder D, Smit S, Aarts MGM. The genome sequence of Hirschfeldia incana, a new Brassicaceae model to improve photosynthetic light-use efficiency. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 112:1298-1315. [PMID: 36239071 PMCID: PMC10100226 DOI: 10.1111/tpj.16005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 10/09/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023]
Abstract
Photosynthesis is a key process in sustaining plant and human life. Improving the photosynthetic capacity of agricultural crops is an attractive means to increase their yields. While the core mechanisms of photosynthesis are highly conserved in C3 plants, these mechanisms are very flexible, allowing considerable diversity in photosynthetic properties. Among this diversity is the maintenance of high photosynthetic light-use efficiency at high irradiance as identified in a small number of exceptional C3 species. Hirschfeldia incana, a member of the Brassicaceae family, is such an exceptional species, and because it is easy to grow, it is an excellent model for studying the genetic and physiological basis of this trait. Here, we present a reference genome of H. incana and confirm its high photosynthetic light-use efficiency. While H. incana has the highest photosynthetic rates found so far in the Brassicaceae, the light-saturated assimilation rates of closely related Brassica rapa and Brassica nigra are also high. The H. incana genome has extensively diversified from that of B. rapa and B. nigra through large chromosomal rearrangements, species-specific transposon activity, and differential retention of duplicated genes. Duplicated genes in H. incana, B. rapa, and B. nigra that are involved in photosynthesis and/or photoprotection show a positive correlation between copy number and gene expression, providing leads into the mechanisms underlying the high photosynthetic efficiency of these species. Our work demonstrates that the H. incana genome serves as a valuable resource for studying the evolution of high photosynthetic light-use efficiency and enhancing photosynthetic rates in crop species.
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Affiliation(s)
| | - Raúl Y. Wijfjes
- Bioinformatics GroupWageningen University & ResearchWageningenNetherlands
- Present address:
Faculty of BiologyLudwig Maximilian University of MunichMunichGermany
| | - René Boesten
- Laboratory of GeneticsWageningen University & ResearchWageningenNetherlands
| | | | - Frank F. M. Becker
- Laboratory of GeneticsWageningen University & ResearchWageningenNetherlands
| | - Vittoria Clapero
- Laboratory of GeneticsWageningen University & ResearchWageningenNetherlands
- Present address:
Max Planck Institute for Molecular Plant PhysiologyGolmGermany
| | | | - Rens Holmer
- Bioinformatics GroupWageningen University & ResearchWageningenNetherlands
| | - M. Eric Schranz
- Biosystematics GroupWageningen University & ResearchWageningenNetherlands
| | - Jeremy Harbinson
- Laboratory of BiophysicsWageningen University & ResearchWageningenNetherlands
| | - Dick de Ridder
- Bioinformatics GroupWageningen University & ResearchWageningenNetherlands
| | - Sandra Smit
- Bioinformatics GroupWageningen University & ResearchWageningenNetherlands
| | - Mark G. M. Aarts
- Laboratory of GeneticsWageningen University & ResearchWageningenNetherlands
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8
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Jonkheer EM, van Workum DJM, Sheikhizadeh Anari S, Brankovics B, de Haan JR, Berke L, van der Lee TAJ, de Ridder D, Smit S. PanTools v3: functional annotation, classification and phylogenomics. Bioinformatics 2022; 38:4403-4405. [PMID: 35861394 PMCID: PMC9477522 DOI: 10.1093/bioinformatics/btac506] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 07/08/2022] [Indexed: 12/24/2022] Open
Abstract
SUMMARY The ever-increasing number of sequenced genomes necessitates the development of pangenomic approaches for comparative genomics. Introduced in 2016, PanTools is a platform that allows pangenome construction, homology grouping and pangenomic read mapping. The use of graph database technology makes PanTools versatile, applicable from small viral genomes like SARS-CoV-2 up to large plant or animal genomes like tomato or human. Here, we present our third major update to PanTools that enables the integration of functional annotations and provides both gene-level analyses and phylogenetics. AVAILABILITY AND IMPLEMENTATION PanTools is implemented in Java 8 and released under the GNU GPLv3 license. Software and documentation are available at https://git.wur.nl/bioinformatics/pantools. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | | | - Balázs Brankovics
- Biointeractions and Plant Health, Wageningen Plant Research, Wageningen 6708PB, The Netherlands
| | - Jorn R de Haan
- Genetwister Technologies B.V, Wageningen 6709PA, The Netherlands
| | - Lidija Berke
- Genetwister Technologies B.V, Wageningen 6709PA, The Netherlands
| | - Theo A J van der Lee
- Biointeractions and Plant Health, Wageningen Plant Research, Wageningen 6708PB, The Netherlands
| | - Dick de Ridder
- Bioinformatics Group, Wageningen University, Wageningen 6708PB, The Netherlands
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Jonkheer EM, Brankovics B, Houwers IM, van der Wolf JM, Bonants PJM, Vreeburg RAM, Bollema R, de Haan JR, Berke L, Smit S, de Ridder D, van der Lee TAJ. The Pectobacterium pangenome, with a focus on Pectobacterium brasiliense, shows a robust core and extensive exchange of genes from a shared gene pool. BMC Genomics 2021; 22:265. [PMID: 33849459 PMCID: PMC8045196 DOI: 10.1186/s12864-021-07583-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/26/2021] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Bacterial plant pathogens of the Pectobacterium genus are responsible for a wide spectrum of diseases in plants, including important crops such as potato, tomato, lettuce, and banana. Investigation of the genetic diversity underlying virulence and host specificity can be performed at genome level by using a comprehensive comparative approach called pangenomics. A pangenomic approach, using newly developed functionalities in PanTools, was applied to analyze the complex phylogeny of the Pectobacterium genus. We specifically used the pangenome to investigate genetic differences between virulent and avirulent strains of P. brasiliense, a potato blackleg causing species dominantly present in Western Europe. RESULTS Here we generated a multilevel pangenome for Pectobacterium, comprising 197 strains across 19 species, including type strains, with a focus on P. brasiliense. The extensive phylogenetic analysis of the Pectobacterium genus showed robust distinct clades, with most detail provided by 452,388 parsimony-informative single-nucleotide polymorphisms identified in single-copy orthologs. The average Pectobacterium genome consists of 47% core genes, 1% unique genes, and 52% accessory genes. Using the pangenome, we zoomed in on differences between virulent and avirulent P. brasiliense strains and identified 86 genes associated to virulent strains. We found that the organization of genes is highly structured and linked with gene conservation, function, and transcriptional orientation. CONCLUSION The pangenome analysis demonstrates that evolution in Pectobacteria is a highly dynamic process, including gene acquisitions partly in clusters, genome rearrangements, and loss of genes. Pectobacterium species are typically not characterized by a set of species-specific genes, but instead present themselves using new gene combinations from the shared gene pool. A multilevel pangenomic approach, fusing DNA, protein, biological function, taxonomic group, and phenotypes, facilitates studies in a flexible taxonomic context.
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Affiliation(s)
- Eef M Jonkheer
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
| | - Balázs Brankovics
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Ilse M Houwers
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Jan M van der Wolf
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Peter J M Bonants
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Robert A M Vreeburg
- Nederlandse Algemene Keuringsdienst voor zaaizaad en pootgoed van landbouwgewassen, Randweg 14, 8304 AS, Emmeloord, The Netherlands
| | - Robert Bollema
- Nederlandse Algemene Keuringsdienst voor zaaizaad en pootgoed van landbouwgewassen, Randweg 14, 8304 AS, Emmeloord, The Netherlands
| | - Jorn R de Haan
- Genetwister Technologies B.V, Nieuwe Kanaal 7b, 6709 PA, Wageningen, The Netherlands
| | - Lidija Berke
- Genetwister Technologies B.V, Nieuwe Kanaal 7b, 6709 PA, Wageningen, The Netherlands
| | - Sandra Smit
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Dick de Ridder
- Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Theo A J van der Lee
- Biointeractions and Plant Health, Wageningen Plant Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
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Eizenga JM, Novak AM, Sibbesen JA, Heumos S, Ghaffaari A, Hickey G, Chang X, Seaman JD, Rounthwaite R, Ebler J, Rautiainen M, Garg S, Paten B, Marschall T, Sirén J, Garrison E. Pangenome Graphs. Annu Rev Genomics Hum Genet 2020; 21:139-162. [PMID: 32453966 DOI: 10.1146/annurev-genom-120219-080406] [Citation(s) in RCA: 130] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Low-cost whole-genome assembly has enabled the collection of haplotype-resolved pangenomes for numerous organisms. In turn, this technological change is encouraging the development of methods that can precisely address the sequence and variation described in large collections of related genomes. These approaches often use graphical models of the pangenome to support algorithms for sequence alignment, visualization, functional genomics, and association studies. The additional information provided to these methods by the pangenome allows them to achieve superior performance on a variety of bioinformatic tasks, including read alignment, variant calling, and genotyping. Pangenome graphs stand to become a ubiquitous tool in genomics. Although it is unclear whether they will replace linearreference genomes, their ability to harmoniously relate multiple sequence and coordinate systems will make them useful irrespective of which pangenomic models become most common in the future.
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Affiliation(s)
- Jordan M Eizenga
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Adam M Novak
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Jonas A Sibbesen
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Simon Heumos
- Quantitative Biology Center, University of Tübingen, 72076 Tübingen, Germany
| | - Ali Ghaffaari
- Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.,Max Planck Institute for Informatics, 66123 Saarbrücken, Germany.,Saarbrücken Graduate School for Computer Science, Saarland University, 66123 Saarbrücken, Germany
| | - Glenn Hickey
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Xian Chang
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Josiah D Seaman
- Royal Botanic Gardens, Kew, Richmond TW9 3AB, United Kingdom.,School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom
| | - Robin Rounthwaite
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Jana Ebler
- Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.,Max Planck Institute for Informatics, 66123 Saarbrücken, Germany.,Saarbrücken Graduate School for Computer Science, Saarland University, 66123 Saarbrücken, Germany
| | - Mikko Rautiainen
- Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.,Max Planck Institute for Informatics, 66123 Saarbrücken, Germany.,Saarbrücken Graduate School for Computer Science, Saarland University, 66123 Saarbrücken, Germany
| | - Shilpa Garg
- Departments of Genetics and Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02215, USA.,Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA
| | - Benedict Paten
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Tobias Marschall
- Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.,Max Planck Institute for Informatics, 66123 Saarbrücken, Germany
| | - Jouni Sirén
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
| | - Erik Garrison
- Genomics Institute, University of California, Santa Cruz, California 95064, USA;
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