1
|
Nakombo-Gbassault P, Arenas S, Affortit P, Faye A, Flis P, Sine B, Moukouanga D, Gantet P, Komba EK, Kane N, Bennett M, Wells D, Cubry P, Bailey E, Grondin A, Vigouroux Y, Laplaze L. Genetic control of the leaf ionome in pearl millet and correlation with root and agromorphological traits. PLoS One 2025; 20:e0319140. [PMID: 40388386 PMCID: PMC12088009 DOI: 10.1371/journal.pone.0319140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2025] [Accepted: 04/22/2025] [Indexed: 05/21/2025] Open
Abstract
Pearl millet (Pennisetum glaucum) thrives in arid and nutrient-poor environments, establishing its role as a crucial cereal crop for food security in sub-Saharan Africa. Despite its remarkable adaptability, its yields remain below genetic potential, primarily due to limited water and nutrient availability. In this study, we conducted ionomic profiling and genome-wide association studies (GWAS) in field conditions across two growing seasons to unravel the genetic basis of nutrient acquisition in pearl millet. Soil ion content analyses revealed significant differences in nutrient distribution between field sites, while certain ions, such as phosphorus (P) and zinc (Zn), consistently displayed stratified accumulation patterns across years, suggesting stable depth-dependent trends. Evaluation of a genetically diverse panel of inbred lines revealed substantial variation in leaf ion concentrations, with high heritability estimates. Correlations between leaf ion content and root anatomical or agromorphological traits highlighted the intricate interplay between genetic and environmental factors shaping leaf ion accumulation. These analyses also uncovered potential trade-offs in nutrient acquisition strategies. GWAS identified genomic regions associated with leaf ion concentrations, and the integration of genetic and gene expression data facilitated the identification of candidate genes implicated in ion transport and homeostasis. Our findings provide valuable insights into the genetic regulation of nutrient acquisition in pearl millet, offering potential targets for breeding nutrient-efficient and climate-resilient varieties. This study underscores the importance of integrating genetic, physiological, and root architectural traits to enhance agricultural productivity and sustainability in resource-constrained environments.
Collapse
Affiliation(s)
- Princia Nakombo-Gbassault
- DIADE, Université de Montpellier, IRD, CIRAD, Montpellier France
- JEAI AgrobiodiveRCA, Université de Bangui, Bangui, Central African Republic
| | - Sebastian Arenas
- DIADE, Université de Montpellier, IRD, CIRAD, Montpellier France
| | - Pablo Affortit
- DIADE, Université de Montpellier, IRD, CIRAD, Montpellier France
| | - Awa Faye
- CERAAS, Institut Sénégalais des Recherches Agricoles (ISRA), Thiès, Senegal
| | - Paulina Flis
- School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom
| | - Bassirou Sine
- CERAAS, Institut Sénégalais des Recherches Agricoles (ISRA), Thiès, Senegal
| | | | - Pascal Gantet
- DIADE, Université de Montpellier, IRD, CIRAD, Montpellier France
| | - Ephrem Kosh Komba
- JEAI AgrobiodiveRCA, Université de Bangui, Bangui, Central African Republic
| | - Ndjido Kane
- CERAAS, Institut Sénégalais des Recherches Agricoles (ISRA), Thiès, Senegal
| | - Malcolm Bennett
- School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom
| | - Darren Wells
- School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom
| | - Philippe Cubry
- DIADE, Université de Montpellier, IRD, CIRAD, Montpellier France
| | - Elizabeth Bailey
- School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom
| | | | - Yves Vigouroux
- DIADE, Université de Montpellier, IRD, CIRAD, Montpellier France
| | - Laurent Laplaze
- DIADE, Université de Montpellier, IRD, CIRAD, Montpellier France
| |
Collapse
|
2
|
Leclerc L, Nguyen TH, Duval P, Mariotti V, Petitot AS, Orjuela J, Ogier JC, Gaudriault S, Champion A, Nègre N. Early transcriptomic responses of rice leaves to herbivory by Spodoptera frugiperda. Sci Rep 2024; 14:2836. [PMID: 38310172 PMCID: PMC10838271 DOI: 10.1038/s41598-024-53348-x] [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] [Received: 07/19/2023] [Accepted: 01/31/2024] [Indexed: 02/05/2024] Open
Abstract
During herbivory, chewing insects deposit complex oral secretions (OS) onto the plant wound. Understanding how plants respond to the different cues of herbivory remains an active area of research. In this study, we used an herbivory-mimick experiment to investigate the early transcriptional response of rice plants leaves to wounding, OS, and OS microbiota from Spodoptera frugiperda larvae. Wounding induced a massive early response associated to hormones such as jasmonates. This response switched drastically upon OS treatment indicating the activation of OS specific pathways. When comparing native and dysbiotic OS treatments, we observed few gene regulation. This suggests that in addition to wounding the early response in rice is mainly driven by the insect compounds of the OS rather than microbial. However, microbiota affected genes encoding key phytohormone synthesis enzymes, suggesting an additional modulation of plant response by OS microbiota.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Nicolas Nègre
- DGIMI, Univ Montpellier, INRAE, Montpellier, France.
| |
Collapse
|
3
|
Bonnamy M, Pinel-Galzi A, Gorgues L, Chalvon V, Hébrard E, Chéron S, Nguyen TH, Poulicard N, Sabot F, Pidon H, Champion A, Césari S, Kroj T, Albar L. Rapid evolution of an RNA virus to escape recognition by a rice nucleotide-binding and leucine-rich repeat domain immune receptor. THE NEW PHYTOLOGIST 2023; 237:900-913. [PMID: 36229931 DOI: 10.1111/nph.18532] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/16/2022] [Indexed: 06/16/2023]
Abstract
Viral diseases are a major limitation for crop production, and their control is crucial for sustainable food supply. We investigated by a combination of functional genetics and experimental evolution the resistance of rice to the rice yellow mottle virus (RYMV), which is among the most devastating rice pathogens in Africa, and the mechanisms underlying the extremely fast adaptation of the virus to its host. We found that the RYMV3 gene that protects rice against the virus codes for a nucleotide-binding and leucine-rich repeat domain immune receptor (NLRs) from the Mla-like clade of NLRs. RYMV3 detects the virus by forming a recognition complex with the viral coat protein (CP). The virus escapes efficiently from detection by mutations in its CP, some of which interfere with the formation of the recognition complex. This study establishes that NLRs also confer in monocotyledonous plants immunity to viruses, and reveals an unexpected functional diversity for NLRs of the Mla clade that were previously only known as fungal disease resistance proteins. In addition, it provides precise insight into the mechanisms by which viruses adapt to plant immunity and gives important knowledge for the development of sustainable resistance against viral diseases of cereals.
Collapse
Affiliation(s)
- Mélia Bonnamy
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - Agnès Pinel-Galzi
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - Lucille Gorgues
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - Véronique Chalvon
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - Eugénie Hébrard
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - Sophie Chéron
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | | | - Nils Poulicard
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - François Sabot
- DIADE, Univ Montpellier, IRD, 34394, Montpellier, France
| | - Hélène Pidon
- DIADE, Univ Montpellier, IRD, 34394, Montpellier, France
- Institute for Resistance Research and Stress Tolerance, Julius Kühn Institute, 06484, Quedlinburg, Germany
| | | | - Stella Césari
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - Thomas Kroj
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| | - Laurence Albar
- PHIM Plant Health Institute, Univ Montpellier, IRD, CIRAD, INRAE, Institut Agro, 34980, Montpellier, France
| |
Collapse
|
4
|
Grimplet J. Genomic and Bioinformatic Resources for Perennial Fruit Species. Curr Genomics 2022; 23:217-233. [PMID: 36777875 PMCID: PMC9875543 DOI: 10.2174/1389202923666220428102632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 03/12/2022] [Accepted: 03/12/2022] [Indexed: 11/22/2022] Open
Abstract
In the post-genomic era, data management and development of bioinformatic tools are critical for the adequate exploitation of genomics data. In this review, we address the actual situation for the subset of crops represented by the perennial fruit species. The agronomical singularity of these species compared to plant and crop model species provides significant challenges on the implementation of good practices generally not addressed in other species. Studies are usually performed over several years in non-controlled environments, usage of rootstock is common, and breeders heavily rely on vegetative propagation. A reference genome is now available for all the major species as well as many members of the economically important genera for breeding purposes. Development of pangenome for these species is beginning to gain momentum which will require a substantial effort in term of bioinformatic tool development. The available tools for genome annotation and functional analysis will also be presented.
Collapse
Affiliation(s)
- Jérôme Grimplet
- Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Unidad de Hortofruticultura, Gobierno de Aragón, Avda. Montañana, Zaragoza, Spain
- Instituto Agroalimentario de Aragón–IA2 (CITA-Universidad de Zaragoza), Calle Miguel Servet, Zaragoza, Spain
| |
Collapse
|
5
|
Population Genome Sequencing of the Scab Fungal Species Venturia inaequalis, Venturia pirina, Venturia aucupariae and Venturia asperata. G3-GENES GENOMES GENETICS 2019; 9:2405-2414. [PMID: 31253647 PMCID: PMC6686934 DOI: 10.1534/g3.119.400047] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The Venturia genus comprises fungal species that are pathogens on Rosaceae host plants, including V. inaequalis and V. asperata on apple, V. aucupariae on sorbus and V. pirina on pear. Although the genetic structure of V. inaequalis populations has been investigated in detail, genomic features underlying these subdivisions remain poorly understood. Here, we report whole genome sequencing of 87 Venturia strains that represent each species and each population within V. inaequalis. We present a PacBio genome assembly for the V. inaequalis EU-B04 reference isolate. The size of selected genomes was determined by flow cytometry, and varied from 45 to 93 Mb. Genome assemblies of V. inaequalis and V. aucupariae contain a high content of transposable elements (TEs), most of which belong to the Gypsy or Copia LTR superfamilies and have been inactivated by Repeat-Induced Point mutations. The reference assembly of V. inaequalis presents a mosaic structure of GC-equilibrated regions that mainly contain predicted genes and AT-rich regions, mainly composed of TEs. Six pairs of strains were identified as clones. Single-Nucleotide Polymorphism (SNP) analysis between these clones revealed a high number of SNPs that are mostly located in AT-rich regions due to misalignments and allowed determining a false discovery rate. The availability of these genome sequences is expected to stimulate genetics and population genomics research of Venturia pathogens. Especially, it will help understanding the evolutionary history of Venturia species that are pathogenic on different hosts, a history that has probably been substantially influenced by TEs.
Collapse
|
6
|
Ahmed AE, Heldenbrand J, Asmann Y, Fadlelmola FM, Katz DS, Kendig K, Kendzior MC, Li T, Ren Y, Rodriguez E, Weber MR, Wozniak JM, Zermeno J, Mainzer LS. Managing genomic variant calling workflows with Swift/T. PLoS One 2019; 14:e0211608. [PMID: 31287816 PMCID: PMC6615596 DOI: 10.1371/journal.pone.0211608] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 06/08/2019] [Indexed: 12/30/2022] Open
Abstract
Bioinformatics research is frequently performed using complex workflows with multiple steps, fans, merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Scientific workflow management systems could help with that. Many are now being proposed, but is there yet the “best” workflow management system for bioinformatics? Such a system would need to satisfy numerous, sometimes conflicting requirements: from ease of use, to seamless deployment at peta- and exa-scale, and portability to the cloud. We evaluated Swift/T as a candidate for such role by implementing a primary genomic variant calling workflow in the Swift/T language, focusing on workflow management, performance and scalability issues that arise from production-grade big data genomic analyses. In the process we introduced novel features into the language, which are now part of its open repository. Additionally, we formalized a set of design criteria for quality, robust, maintainable workflows that must function at-scale in a production setting, such as a large genomic sequencing facility or a major hospital system. The use of Swift/T conveys two key advantages. (1) It operates transparently in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.), thus a single workflow is trivially portable across numerous clusters. (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, which makes it easy to maintain and to request resources optimal for each stage of the pipeline. While Swift/T’s data-level parallelism eliminates the need to code parallel analysis of multiple samples, it does make debugging more difficult, as is common for implicitly parallel code. Nonetheless, the language gives users a powerful and portable way to scale up analyses in many computing architectures. The code for our implementation of a variant calling workflow using Swift/T can be found on GitHub at https://github.com/ncsa/Swift-T-Variant-Calling, with full documentation provided at http://swift-t-variant-calling.readthedocs.io/en/latest/.
Collapse
Affiliation(s)
- Azza E. Ahmed
- Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
- Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Khartoum, Khartoum, Sudan
| | - Jacob Heldenbrand
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Yan Asmann
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Faisal M. Fadlelmola
- Centre for Bioinformatics & Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Daniel S. Katz
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Katherine Kendig
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Matthew C. Kendzior
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Tiffany Li
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Yingxue Ren
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Elliott Rodriguez
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Matthew R. Weber
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Justin M. Wozniak
- Argonne National Laboratory, Argonne, Illinois, United States of America
| | - Jennie Zermeno
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
| | - Liudmila S. Mainzer
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America
- * E-mail:
| |
Collapse
|
7
|
Merot‐L'anthoene V, Tournebize R, Darracq O, Rattina V, Lepelley M, Bellanger L, Tranchant‐Dubreuil C, Coulée M, Pégard M, Metairon S, Fournier C, Stoffelen P, Janssens SB, Kiwuka C, Musoli P, Sumirat U, Legnaté H, Kambale J, Ferreira da Costa Neto J, Revel C, de Kochko A, Descombes P, Crouzillat D, Poncet V. Development and evaluation of a genome-wide Coffee 8.5K SNP array and its application for high-density genetic mapping and for investigating the origin of Coffea arabica L. PLANT BIOTECHNOLOGY JOURNAL 2019; 17:1418-1430. [PMID: 30582651 PMCID: PMC6576098 DOI: 10.1111/pbi.13066] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 12/10/2018] [Indexed: 06/09/2023]
Abstract
Coffee species such as Coffea canephora P. (Robusta) and C. arabica L. (Arabica) are important cash crops in tropical regions around the world. C. arabica is an allotetraploid (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 22). Interestingly, these progenitor species harbour a greater level of genetic variability and are an important source of genes to broaden the narrow Arabica genetic base. Here, we describe the development, evaluation and use of a single-nucleotide polymorphism (SNP) array for coffee trees. A total of 8580 unique and informative SNPs were selected from C. canephora and C. arabica sequencing data, with 40% of the SNP located in annotated genes. In particular, this array contains 227 markers associated to 149 genes and traits of agronomic importance. Among these, 7065 SNPs (~82.3%) were scorable and evenly distributed over the genome with a mean distance of 54.4 Kb between markers. With this array, we improved the Robusta high-density genetic map by adding 1307 SNP markers, whereas 945 SNPs were found segregating in the Arabica mapping progeny. A panel of C. canephora accessions was successfully discriminated and over 70% of the SNP markers were transferable across the three species. Furthermore, the canephora-derived subgenome of C. arabica was shown to be more closely related to C. canephora accessions from northern Uganda than to other current populations. These validated SNP markers and high-density genetic maps will be useful to molecular genetics and for innovative approaches in coffee breeding.
Collapse
|
8
|
Civáň P, Ali S, Batista-Navarro R, Drosou K, Ihejieto C, Chakraborty D, Ray A, Gladieux P, Brown TA. Origin of the Aromatic Group of Cultivated Rice (Oryza sativa L.) Traced to the Indian Subcontinent. Genome Biol Evol 2019; 11:832-843. [PMID: 30793171 PMCID: PMC6427689 DOI: 10.1093/gbe/evz039] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/19/2019] [Indexed: 02/06/2023] Open
Abstract
The aromatic group of Asian cultivated rice is a distinct population with considerable genetic diversity on the Indian subcontinent and includes the popular Basmati types characterized by pleasant fragrance. Genetic and phenotypic associations with other cultivated groups are ambiguous, obscuring the origin of the aromatic population. From analysis of genome-wide diversity among over 1,000 wild and cultivated rice accessions, we show that aromatic rice originated in the Indian subcontinent from hybridization between a local wild population and examples of domesticated japonica that had spread to the region from their own center of origin in East Asia. Most present-day aromatic accessions have inherited their cytoplasm along with 29-47% of their nuclear genome from the local Indian rice. We infer that the admixture occurred 4,000-2,400 years ago, soon after japonica rice reached the region. We identify aus as the original crop of the Indian subcontinent, indica and japonica as later arrivals, and aromatic a specific product of local agriculture. These results prompt a reappraisal of our understanding of the emergence and development of rice agriculture in the Indian subcontinent.
Collapse
Affiliation(s)
- Peter Civáň
- Manchester Institute of Biotechnology, School of Earth and Environmental Sciences, University of Manchester, United Kingdom
- INRA-Université Clermont-Auvergne, UMR 1095 GDEC, Clermont-Ferrand, France
| | - Sajid Ali
- Institute of Biotechnology & Genetic Engineering, The University of Agriculture, Peshawar, Pakistan
| | | | - Konstantina Drosou
- Manchester Institute of Biotechnology, School of Earth and Environmental Sciences, University of Manchester, United Kingdom
| | - Chioma Ihejieto
- Manchester Institute of Biotechnology, School of Earth and Environmental Sciences, University of Manchester, United Kingdom
| | | | - Avik Ray
- Center for Studies in Ethnobiology, Biodiversity, and Sustainability (CEiBa), Malda, West Bengal, India
| | - Pierre Gladieux
- BGPI, Université de Montpellier, INRA, CIRAD, Montpellier SupAgro, Montpellier, France
| | - Terence A Brown
- Manchester Institute of Biotechnology, School of Earth and Environmental Sciences, University of Manchester, United Kingdom
| |
Collapse
|
9
|
Cubry P, Tranchant-Dubreuil C, Thuillet AC, Monat C, Ndjiondjop MN, Labadie K, Cruaud C, Engelen S, Scarcelli N, Rhoné B, Burgarella C, Dupuy C, Larmande P, Wincker P, François O, Sabot F, Vigouroux Y. The Rise and Fall of African Rice Cultivation Revealed by Analysis of 246 New Genomes. Curr Biol 2018; 28:2274-2282.e6. [PMID: 29983312 DOI: 10.1016/j.cub.2018.05.066] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/10/2018] [Accepted: 05/24/2018] [Indexed: 12/23/2022]
Abstract
African rice (Oryza glaberrima) was domesticated independently from Asian rice. The geographical origin of its domestication remains elusive. Using 246 new whole-genome sequences, we inferred the cradle of its domestication to be in the Inner Niger Delta. Domestication was preceded by a sharp decline of most wild populations that started more than 10,000 years ago. The wild population collapse occurred during the drying of the Sahara. This finding supports the hypothesis that depletion of wild resources in the Sahara triggered African rice domestication. African rice cultivation strongly expanded 2,000 years ago. During the last 5 centuries, a sharp decline of its cultivation coincided with the introduction of Asian rice in Africa. A gene, PROG1, associated with an erect plant architecture phenotype, showed convergent selection in two rice cultivated species, Oryza glaberrima from Africa and Oryza sativa from Asia. In contrast, a shattering gene, SH5, showed selection signature during African rice domestication, but not during Asian rice domestication. Overall, our genomic data revealed a complex history of African rice domestication influenced by important climatic changes in the Saharan area, by the expansion of African agricultural society, and by recent replacement by another domesticated species.
Collapse
Affiliation(s)
- Philippe Cubry
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France
| | - Christine Tranchant-Dubreuil
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France; SouthGreen Development Platform, Agropolis Campus, Montpellier, France
| | - Anne-Céline Thuillet
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France
| | - Cécile Monat
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France; SouthGreen Development Platform, Agropolis Campus, Montpellier, France
| | | | - Karine Labadie
- CEA, Institut de Biologie François Jacob, Genoscope, 2 Rue Gaston Crémieux, 91057 Evry, France; CNRS, UMR 8030, CP5706, Evry, France; Université d'Evry, UMR 8030, CP5706, Evry, France
| | - Corinne Cruaud
- CEA, Institut de Biologie François Jacob, Genoscope, 2 Rue Gaston Crémieux, 91057 Evry, France; CNRS, UMR 8030, CP5706, Evry, France; Université d'Evry, UMR 8030, CP5706, Evry, France
| | - Stefan Engelen
- CEA, Institut de Biologie François Jacob, Genoscope, 2 Rue Gaston Crémieux, 91057 Evry, France; CNRS, UMR 8030, CP5706, Evry, France; Université d'Evry, UMR 8030, CP5706, Evry, France
| | - Nora Scarcelli
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France
| | - Bénédicte Rhoné
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France; Université Lyon 1, CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Lyon, France
| | - Concetta Burgarella
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France
| | | | - Pierre Larmande
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France; SouthGreen Development Platform, Agropolis Campus, Montpellier, France; Institut de Biologie Computationnelle (IBC), Université Montpellier 2, 860 Rue St Priest, 34095 Montpellier Cedex 5, France
| | - Patrick Wincker
- CEA, Institut de Biologie François Jacob, Genoscope, 2 Rue Gaston Crémieux, 91057 Evry, France; CNRS, UMR 8030, CP5706, Evry, France; Université d'Evry, UMR 8030, CP5706, Evry, France
| | - Olivier François
- Université Grenoble-Alpes, CNRS, UMR 5525 TIMC-IMAG, 38042 Grenoble, France
| | - François Sabot
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France; SouthGreen Development Platform, Agropolis Campus, Montpellier, France; Université de Montpellier, Place Eugène Bataillon, 34000 Montpellier, France.
| | - Yves Vigouroux
- Institut de Recherche pour le Développement, UMR DIADE, 911 Avenue Agropolis, 34394 Montpellier, France; Université de Montpellier, Place Eugène Bataillon, 34000 Montpellier, France.
| |
Collapse
|
10
|
The Number of Target Molecules of the Amplification Step Limits Accuracy and Sensitivity in Ultradeep-Sequencing Viral Population Studies. J Virol 2017; 91:JVI.00561-17. [PMID: 28566384 DOI: 10.1128/jvi.00561-17] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 05/25/2017] [Indexed: 11/20/2022] Open
Abstract
The invention of next-generation sequencing (NGS) techniques marked the coming of a new era in the detection of the genetic diversity of intrahost viral populations. A good understanding of the genetic structure of these populations requires, first, the ability to identify the different isolates or variants and, second, the ability to accurately quantify them. However, the initial amplification step of NGS studies can impose potential quantitative biases, modifying the variant relative frequencies. In particular, the number of target molecules (NTM) used during the amplification step is vastly overlooked although of primary importance, as it sets the limit of the accuracy and sensitivity of the sequencing procedure. In the present article, we investigated quantitative biases in an NGS study of populations of a multipartite single-stranded DNA (ssDNA) virus at different steps of the procedure. We studied 20 independent populations of the ssDNA virus faba bean necrotic stunt virus (FBNSV) in two host plants, Vicia faba and Medicago truncatula FBNSV is a multipartite virus composed of eight genomic segments, whose specific and host-dependent relative frequencies are defined as the "genome formula." Our results show a significant distortion of the FBNSV genome formula after the amplification and sequencing steps. We also quantified the genetic bottleneck occurring at the amplification step by documenting the NTM of two genomic segments of FBNSV. We argue that the NTM must be documented and carefully considered when determining the sensitivity and accuracy of data from NGS studies.IMPORTANCE The advent of next-generation sequencing (NGS) techniques now enables study of the genetic diversity of viral populations. A good understanding of the genetic structure of these populations first requires the ability to identify the different isolates or variants and second requires the ability to accurately quantify them. Prior to sequencing, viral genomes need to be amplified, a step that potentially imposes quantitative biases and modifies the viral population structure. In particular, the number of target molecules (NTM) used during the amplification step is of primary importance, as it sets the limit of the accuracy and sensitivity of the sequencing procedure. In this work, we used 20 replicated populations of the multipartite faba bean necrotic stunt virus (FBNSV) to estimate the various limitations of ultradeep-sequencing studies performed on intrahost viral populations. We report quantitative biases during rolling-circle amplification and the NTM of two genomic segments of FBNSV.
Collapse
|
11
|
Mashl RJ, Scott AD, Huang KL, Wyczalkowski MA, Yoon CJ, Niu B, DeNardo E, Yellapantula VD, Handsaker RE, Chen K, Koboldt DC, Ye K, Fenyö D, Raphael BJ, Wendl MC, Ding L. GenomeVIP: a cloud platform for genomic variant discovery and interpretation. Genome Res 2017; 27:1450-1459. [PMID: 28522612 PMCID: PMC5538560 DOI: 10.1101/gr.211656.116] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Accepted: 05/03/2017] [Indexed: 12/12/2022]
Abstract
Identifying genomic variants is a fundamental first step toward the understanding of the role of inherited and acquired variation in disease. The accelerating growth in the corpus of sequencing data that underpins such analysis is making the data-download bottleneck more evident, placing substantial burdens on the research community to keep pace. As a result, the search for alternative approaches to the traditional “download and analyze” paradigm on local computing resources has led to a rapidly growing demand for cloud-computing solutions for genomics analysis. Here, we introduce the Genome Variant Investigation Platform (GenomeVIP), an open-source framework for performing genomics variant discovery and annotation using cloud- or local high-performance computing infrastructure. GenomeVIP orchestrates the analysis of whole-genome and exome sequence data using a set of robust and popular task-specific tools, including VarScan, GATK, Pindel, BreakDancer, Strelka, and Genome STRiP, through a web interface. GenomeVIP has been used for genomic analysis in large-data projects such as the TCGA PanCanAtlas and in other projects, such as the ICGC Pilots, CPTAC, ICGC-TCGA DREAM Challenges, and the 1000 Genomes SV Project. Here, we demonstrate GenomeVIP's ability to provide high-confidence annotated somatic, germline, and de novo variants of potential biological significance using publicly available data sets.
Collapse
Affiliation(s)
- R Jay Mashl
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Division of Oncology, Department of Medicine, Washington University, St. Louis, Missouri 63108, USA
| | - Adam D Scott
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Division of Oncology, Department of Medicine, Washington University, St. Louis, Missouri 63108, USA
| | - Kuan-Lin Huang
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Division of Oncology, Department of Medicine, Washington University, St. Louis, Missouri 63108, USA
| | | | - Christopher J Yoon
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Division of Oncology, Department of Medicine, Washington University, St. Louis, Missouri 63108, USA
| | - Beifang Niu
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA
| | - Erin DeNardo
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA
| | - Venkata D Yellapantula
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Division of Oncology, Department of Medicine, Washington University, St. Louis, Missouri 63108, USA
| | - Robert E Handsaker
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, Massachusetts 02142, USA.,Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
| | - Daniel C Koboldt
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA
| | - Kai Ye
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Division of Oncology, Department of Medicine, Washington University, St. Louis, Missouri 63108, USA
| | - David Fenyö
- Langone Medical Center, New York University, New York, New York 10016, USA
| | - Benjamin J Raphael
- Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, Rhode Island 02912, USA
| | - Michael C Wendl
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Department of Genetics, Washington University, St. Louis, Missouri 63108, USA.,Department of Mathematics, Washington University, St. Louis, Missouri 63108, USA
| | - Li Ding
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA.,Division of Oncology, Department of Medicine, Washington University, St. Louis, Missouri 63108, USA.,Department of Genetics, Washington University, St. Louis, Missouri 63108, USA.,Siteman Cancer Center, Washington University, St. Louis, Missouri 63108, USA
| |
Collapse
|
12
|
Pinel-Galzi A, Dubreuil-Tranchant C, Hébrard E, Mariac C, Ghesquière A, Albar L. Mutations in Rice yellow mottle virus Polyprotein P2a Involved in RYMV2 Gene Resistance Breakdown. FRONTIERS IN PLANT SCIENCE 2016; 7:1779. [PMID: 27965688 PMCID: PMC5125353 DOI: 10.3389/fpls.2016.01779] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Accepted: 11/11/2016] [Indexed: 05/09/2023]
Abstract
Rice yellow mottle virus (RYMV) is one of the major diseases of rice in Africa. The high resistance of the Oryza glaberrima Tog7291 accession involves a null allele of the RYMV2 gene, whose ortholog in Arabidopsis, CPR5, is a transmembrane nucleoporin involved in effector-triggered immunity. To optimize field deployment of the RYMV2 gene and improve its durability, which is often a weak point in varietal resistance, we analyzed its efficiency toward RYMV isolates representing the genetic diversity of the virus and the molecular basis of resistance breakdown. Tog7291 resistance efficiency was highly variable depending on the isolate used, with infection rates ranging from 0 to 98% of plants. Back-inoculation experiments indicated that infection cases were not due to an incomplete resistance phenotype but to the emergence of resistance-breaking (RB) variants. Interestingly, the capacity of the virus to overcome Tog7291 resistance is associated with a polymorphism at amino-acid 49 of the VPg protein which also affects capacity to overcome the previously studied RYMV1 resistance gene. This polymorphism appeared to be a main determinant of the emergence of RB variants. It acts independently of the resistance gene and rather reflects inter-species adaptation with potential consequences for the durability of resistance. RB mutations were identified by full-length or partial sequencing of the RYMV genome in infected Tog7291 plants and were validated by directed mutagenesis of an infectious viral clone. We found that Tog7291 resistance breakdown involved mutations in the putative membrane anchor domain of the polyprotein P2a. Although the precise effect of these mutations on rice/RYMV interaction is still unknown, our results offer a new perspective for the understanding of RYMV2 mediated resistance mechanisms. Interestingly, in the susceptible IR64 variety, RB variants showed low infectivity and frequent reversion to the wild-type genotype, suggesting that Tog7291 resistance breakdown is associated with a major loss of viral fitness in normally susceptible O. sativa varieties. Despite the high frequency of resistance breakdown in controlled conditions, this loss of fitness is an encouraging element with regards to RYMV2 resistance durability.
Collapse
Affiliation(s)
- Agnès Pinel-Galzi
- Interactions Plantes Microorganismes Environnement, Institut de Recherche pour le Développement – Centre de Coopération Internationale en Recherche Agronomique pour le Développement – Université de MontpellierMontpellier, France
| | - Christine Dubreuil-Tranchant
- Plant Diversity Adaptation and Development Research Unit, Institut de Recherche pour le Développement – Université de MontpellierMontpellier, France
| | - Eugénie Hébrard
- Interactions Plantes Microorganismes Environnement, Institut de Recherche pour le Développement – Centre de Coopération Internationale en Recherche Agronomique pour le Développement – Université de MontpellierMontpellier, France
| | - Cédric Mariac
- Plant Diversity Adaptation and Development Research Unit, Institut de Recherche pour le Développement – Université de MontpellierMontpellier, France
| | - Alain Ghesquière
- Plant Diversity Adaptation and Development Research Unit, Institut de Recherche pour le Développement – Université de MontpellierMontpellier, France
| | - Laurence Albar
- Plant Diversity Adaptation and Development Research Unit, Institut de Recherche pour le Développement – Université de MontpellierMontpellier, France
| |
Collapse
|