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Lu Y, Huang J, Liu D, Kong X, Song Y, Jing L. Pangenome Data Analysis Reveals Characteristics of Resistance Gene Analogs Associated with Sclerotinia sclerotiorum Resistance in Sunflower. Life (Basel) 2024; 14:1322. [PMID: 39459622 PMCID: PMC11509514 DOI: 10.3390/life14101322] [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: 08/31/2024] [Revised: 10/10/2024] [Accepted: 10/15/2024] [Indexed: 10/28/2024] Open
Abstract
The sunflower, an important oilseed crop and food source across the world, is susceptible to several pathogens, which cause severe losses in sunflower production. The utilization of genetic resistance is the most economical, effective measure to prevent infectious diseases. Based on the sunflower pangenome, in this study, we explored the variability of resistance gene analogs (RGAs) within the species. According to a comparative analysis of RGA candidates in the sunflower pangenome using the RGAugury pipeline, a total of 1344 RGAs were identified, comprising 1107 conserved, 199 varied, and 38 rare RGAs. We also identified RGAs associated with resistance against Sclerotinia sclerotiorum (S. sclerotiorum) in sunflower at the quantitative trait locus (QTL). A total of 61 RGAs were found to be located at four quantitative trait loci (QTLs). Through a detailed expression analysis of RGAs in one susceptible and two tolerant sunflower inbred lines (ILs) across various time points post inoculation, we discovered that 348 RGAs exhibited differential expression in response to Sclerotinia head rot (SHR), with 17 of these differentially expressed RGAs being situated within the QTL regions. In addition, 15 RGA candidates had gene introgression. Our data provide a better understanding of RGAs, which facilitate genomics-based improvements in disease resistance in sunflower.
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Affiliation(s)
| | | | | | | | | | - Lan Jing
- College of Horticulture and Plant Protection, Inner Mongolia Agricultural University, Huhhot 010011, China; (Y.L.); (J.H.); (D.L.); (X.K.); (Y.S.)
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Zhang H, Wafula EK, Eilers J, Harkess A, Ralph PE, Timilsena PR, dePamphilis CW, Waite JM, Honaas LA. Building a foundation for gene family analysis in Rosaceae genomes with a novel workflow: A case study in Pyrus architecture genes. FRONTIERS IN PLANT SCIENCE 2022; 13:975942. [PMID: 36452099 PMCID: PMC9702816 DOI: 10.3389/fpls.2022.975942] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 09/21/2022] [Indexed: 05/26/2023]
Abstract
The rapid development of sequencing technologies has led to a deeper understanding of plant genomes. However, direct experimental evidence connecting genes to important agronomic traits is still lacking in most non-model plants. For instance, the genetic mechanisms underlying plant architecture are poorly understood in pome fruit trees, creating a major hurdle in developing new cultivars with desirable architecture, such as dwarfing rootstocks in European pear (Pyrus communis). An efficient way to identify genetic factors for important traits in non-model organisms can be to transfer knowledge across genomes. However, major obstacles exist, including complex evolutionary histories and variable quality and content of publicly available plant genomes. As researchers aim to link genes to traits of interest, these challenges can impede the transfer of experimental evidence across plant species, namely in the curation of high-quality, high-confidence gene models in an evolutionary context. Here we present a workflow using a collection of bioinformatic tools for the curation of deeply conserved gene families of interest across plant genomes. To study gene families involved in tree architecture in European pear and other rosaceous species, we used our workflow, plus a draft genome assembly and high-quality annotation of a second P. communis cultivar, 'd'Anjou.' Our comparative gene family approach revealed significant issues with the most recent 'Bartlett' genome - primarily thousands of missing genes due to methodological bias. After correcting assembly errors on a global scale in the 'Bartlett' genome, we used our workflow for targeted improvement of our genes of interest in both P. communis genomes, thus laying the groundwork for future functional studies in pear tree architecture. Further, our global gene family classification of 15 genomes across 6 genera provides a valuable and previously unavailable resource for the Rosaceae research community. With it, orthologs and other gene family members can be easily identified across any of the classified genomes. Importantly, our workflow can be easily adopted for any other plant genomes and gene families of interest.
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Affiliation(s)
- Huiting Zhang
- Tree Fruit Research Laboratory, Agricultural Research Service (ARS), United States Department of Agriculture (USDA), Wenatchee, WA, United States
- Department of Horticulture, Washington State University, Pullman, WA, United States
| | - Eric K. Wafula
- Department of Biology, The Pennsylvania State University, University Park, PA, United States
| | - Jon Eilers
- Tree Fruit Research Laboratory, Agricultural Research Service (ARS), United States Department of Agriculture (USDA), Wenatchee, WA, United States
| | - Alex E. Harkess
- College of Agriculture, Auburn University, Auburn, AL, United States
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
| | - Paula E. Ralph
- Department of Biology, The Pennsylvania State University, University Park, PA, United States
| | - Prakash Raj Timilsena
- Department of Biology, The Pennsylvania State University, University Park, PA, United States
| | - Claude W. dePamphilis
- Department of Biology, The Pennsylvania State University, University Park, PA, United States
| | - Jessica M. Waite
- Tree Fruit Research Laboratory, Agricultural Research Service (ARS), United States Department of Agriculture (USDA), Wenatchee, WA, United States
| | - Loren A. Honaas
- Tree Fruit Research Laboratory, Agricultural Research Service (ARS), United States Department of Agriculture (USDA), Wenatchee, WA, United States
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Inturrisi F, Bayer PE, Cantila AY, Tirnaz S, Edwards D, Batley J. In silico integration of disease resistance QTL, genes and markers with the Brassica juncea physical map. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:37. [PMID: 37309382 PMCID: PMC10248627 DOI: 10.1007/s11032-022-01309-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 06/09/2022] [Indexed: 06/14/2023]
Abstract
Brassica juncea (AABB), Indian mustard, is a source of disease resistance genes for a wide range of pathogens. The availability of reference genome sequences for B. juncea has made it possible to characterise the genomic structure and distribution of these disease resistance genes. Potentially functional disease resistance genes can be identified by co-localization with genetically mapped disease resistance quantitative trait loci (QTL). Here we identify and characterise disease resistance gene analogs (RGAs), including nucleotide-binding site-leucine-rich repeat (NLR), receptor-like kinase (RLK) and receptor-like protein (RLP) classes, and investigate their association with disease resistance QTL intervals. The molecular genetic marker sequences for four white rust (Albugo candida) disease resistance QTL, six blackleg (Leptosphaeria maculans) disease resistance QTL and BjCHI1, a gene cloned from B. juncea for hypocotyl rot disease, were extracted from previously published studies and used to compare with candidate RGAs. Our results highlight the complications for the identification of functional resistance genes, including the duplicated appearance of genetic markers for several resistance loci, including Ac2(t), AcB1-A4.1, AcB1-A5.1, Rlm6 and PhR2 in both the A and B genomes, due to the presence of homoeologous regions. Furthermore, the white rust loci, Ac2(t) and AcB1-A4.1, mapped to the same position on chromosome A04 and may be different alleles of the same gene. Despite these challenges, a total of nine candidate genomic regions hosting 14 RLPs, 28 NLRs and 115 RLKs were identified. This study facilitates the mapping and cloning of functional resistance genes for applications in crop improvement programs. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01309-5.
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Affiliation(s)
- Fabian Inturrisi
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA Australia
| | - Philipp E. Bayer
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA Australia
| | - Aldrin Y. Cantila
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA Australia
| | - Soodeh Tirnaz
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA Australia
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA Australia
| | - Jacqueline Batley
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA Australia
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Soundararajan P, Park SG, Won SY, Moon MS, Park HW, Ku KM, Kim JS. Influence of Genotype on High Glucosinolate Synthesis Lines of Brassica rapa. Int J Mol Sci 2021; 22:ijms22147301. [PMID: 34298919 PMCID: PMC8305852 DOI: 10.3390/ijms22147301] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 12/03/2022] Open
Abstract
This study was conducted to investigate doubled haploid (DH) lines produced between high GSL (HGSL) Brassica rapa ssp. trilocularis (yellow sarson) and low GSL (LGSL) B. rapa ssp. chinensis (pak choi) parents. In total, 161 DH lines were generated. GSL content of HGSL DH lines ranged from 44.12 to 57.04 μmol·g−1·dry weight (dw), which is within the level of high GSL B. rapa ssp. trilocularis (47.46 to 59.56 μmol g−1 dw). We resequenced five of the HGSL DH lines and three of the LGSL DH lines. Recombination blocks were formed between the parental and DH lines with 108,328 single-nucleotide polymorphisms in all chromosomes. In the measured GSL, gluconapin occurred as the major substrate in HGSL DH lines. Among the HGSL DH lines, BrYSP_DH005 had glucoraphanin levels approximately 12-fold higher than those of the HGSL mother plant. The hydrolysis capacity of GSL was analyzed in HGSL DH lines with a Korean pak choi cultivar as a control. Bioactive compounds, such as 3-butenyl isothiocyanate, 4-pentenyl isothiocyanate, 2-phenethyl isothiocyanate, and sulforaphane, were present in the HGSL DH lines at 3-fold to 6.3-fold higher levels compared to the commercial cultivar. The selected HGSL DH lines, resequencing data, and SNP identification were utilized for genome-assisted selection to develop elite GSL-enriched cultivars and the industrial production of potential anti-cancerous metabolites such as gluconapin and glucoraphanin.
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Affiliation(s)
- Prabhakaran Soundararajan
- Genomics Division, Department of Agricultural Bio-Resources, National Institute of Agricultural Sciences, Rural Development Administration, Wansan-gu, Jeonju 54874, Korea; (P.S.); (S.Y.W.); (M.-S.M.); (H.W.P.)
| | - Sin-Gi Park
- Bioinformatics Team of Theragen Etex Institute, Suwon 16229, Korea;
| | - So Youn Won
- Genomics Division, Department of Agricultural Bio-Resources, National Institute of Agricultural Sciences, Rural Development Administration, Wansan-gu, Jeonju 54874, Korea; (P.S.); (S.Y.W.); (M.-S.M.); (H.W.P.)
| | - Mi-Sun Moon
- Genomics Division, Department of Agricultural Bio-Resources, National Institute of Agricultural Sciences, Rural Development Administration, Wansan-gu, Jeonju 54874, Korea; (P.S.); (S.Y.W.); (M.-S.M.); (H.W.P.)
| | - Hyun Woo Park
- Genomics Division, Department of Agricultural Bio-Resources, National Institute of Agricultural Sciences, Rural Development Administration, Wansan-gu, Jeonju 54874, Korea; (P.S.); (S.Y.W.); (M.-S.M.); (H.W.P.)
| | - Kang-Mo Ku
- BK21 Interdisciplinary Program in IT-Bio Convergence System, Chonnam National University, Gwangju 61186, Korea;
- Department of Horticulture, Chonnam National University, Gwangju 61186, Korea
| | - Jung Sun Kim
- Genomics Division, Department of Agricultural Bio-Resources, National Institute of Agricultural Sciences, Rural Development Administration, Wansan-gu, Jeonju 54874, Korea; (P.S.); (S.Y.W.); (M.-S.M.); (H.W.P.)
- Correspondence:
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Raman H, Raman R, Qiu Y, Zhang Y, Batley J, Liu S. The Rlm13 Gene, a New Player of Brassica napus- Leptosphaeria maculans Interaction Maps on Chromosome C03 in Canola. FRONTIERS IN PLANT SCIENCE 2021; 12:654604. [PMID: 34054900 PMCID: PMC8150007 DOI: 10.3389/fpls.2021.654604] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 03/25/2021] [Indexed: 05/24/2023]
Abstract
Canola exhibits an extensive genetic variation for resistance to blackleg disease, caused by the fungal pathogen Leptosphaeria maculans. Despite the identification of several Avr effectors and R (race-specific) genes, specific interactions between Avr-R genes are not yet fully understood in the Brassica napus-L. maculans pathosystem. In this study, we investigated the genetic basis of resistance in an F2 : 3 population derived from Australian canola varieties CB-Telfer (Rlm4)/ATR-Cobbler (Rlm4) using a single-spore isolate of L. maculans, PHW1223. A genetic linkage map of the CB-Telfer/ATR-Cobbler population was constructed using 7,932 genotyping-by-sequencing-based DArTseq markers and subsequently utilized for linkage and haplotype analyses. Genetic linkage between DArTseq markers and resistance to PHW1223 isolate was also validated using the B. napus 60K Illumina Infinium array. Our results revealed that a major locus for resistance, designated as Rlm13, maps on chromosome C03. To date, no R gene for resistance to blackleg has been reported on the C subgenome in B. napus. Twenty-four candidate R genes were predicted to reside within the quantitative trait locus (QTL) region. We further resequenced both the parental lines of the mapping population (CB-Telfer and ATR-Cobbler, > 80 × coverage) and identified several structural sequence variants in the form of single-nucleotide polymorphisms (SNPs), insertions/deletions (InDels), and presence/absence variations (PAVs) near Rlm13. Comparative mapping revealed that Rlm13 is located within the homoeologous A03/C03 region in ancestral karyotype block "R" of Brassicaceae. Our results provide a "target" for further understanding the Avr-Rlm13 gene interaction as well as a valuable tool for increasing resistance to blackleg in canola germplasm.
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Affiliation(s)
- Harsh Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Rosy Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Yu Qiu
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Yuanyuan Zhang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
| | - Shengyi Liu
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
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Singh KP, Kumari P, Rai PK. Current Status of the Disease-Resistant Gene(s)/QTLs, and Strategies for Improvement in Brassica juncea. FRONTIERS IN PLANT SCIENCE 2021; 12:617405. [PMID: 33747001 PMCID: PMC7965955 DOI: 10.3389/fpls.2021.617405] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 02/08/2021] [Indexed: 05/15/2023]
Abstract
Brassica juncea is a major oilseed crop in tropical and subtropical countries, especially in south-east Asia like India, China, Bangladesh, and Pakistan. The widespread cultivation of genetically similar varieties tends to attract fungal pathogens which cause heavy yield losses in the absence of resistant sources. The conventional disease management techniques are often expensive, have limited efficacy, and cause additional harm to the environment. A substantial approach is to identify and use of resistance sources within the Brassica hosts and other non-hosts to ensure sustainable oilseed crop production. In the present review, we discuss six major fungal pathogens of B. juncea: Sclerotinia stem rot (Sclerotinia sclerotiorum), Alternaria blight (Alternaria brassicae), White rust (Albugo candida), Downy mildew (Hyaloperonospora parasitica), Powdery mildew (Erysiphe cruciferarum), and Blackleg (Leptoshaeria maculans). From discussing studies on pathogen prevalence in B. juncea, the review then focuses on highlighting the resistance sources and quantitative trait loci/gene identified so far from Brassicaceae and non-filial sources against these fungal pathogens. The problems in the identification of resistance sources for B. juncea concerning genome complexity in host subpopulation and pathotypes were addressed. Emphasis has been laid on more elaborate and coordinated research to identify and deploy R genes, robust techniques, and research materials. Examples of fully characterized genes conferring resistance have been discussed that can be transformed into B. juncea using advanced genomics tools. Lastly, effective strategies for B. juncea improvement through introgression of novel R genes, development of pre-breeding resistant lines, characterization of pathotypes, and defense-related secondary metabolites have been provided suggesting the plan for the development of resistant B. juncea.
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Affiliation(s)
- Kaushal Pratap Singh
- ICAR-Directorate of Rapeseed-Mustard Research, Bharatpur, India
- *Correspondence: Kaushal Pratap Singh,
| | - Preetesh Kumari
- Genetics Division, ICAR-Indian Agricultural Research Institute, New Delhi, India
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Dolatabadian A, Bayer PE, Tirnaz S, Hurgobin B, Edwards D, Batley J. Characterization of disease resistance genes in the Brassica napus pangenome reveals significant structural variation. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:969-982. [PMID: 31553100 PMCID: PMC7061875 DOI: 10.1111/pbi.13262] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 08/30/2019] [Accepted: 09/13/2019] [Indexed: 05/18/2023]
Abstract
Methods based on single nucleotide polymorphism (SNP), copy number variation (CNV) and presence/absence variation (PAV) discovery provide a valuable resource to study gene structure and evolution. However, as a result of these structural variations, a single reference genome is unable to cover the entire gene content of a species. Therefore, pangenomics analysis is needed to ensure that the genomic diversity within a species is fully represented. Brassica napus is one of the most important oilseed crops in the world and exhibits variability in its resistance genes across different cultivars. Here, we characterized resistance gene distribution across 50 B. napus lines. We identified a total of 1749 resistance gene analogs (RGAs), of which 996 are core and 753 are variable, 368 of which are not present in the reference genome (cv. Darmor-bzh). In addition, a total of 15 318 SNPs were predicted within 1030 of the RGAs. The results showed that core R-genes harbour more SNPs than variable genes. More nucleotide binding site-leucine-rich repeat (NBS-LRR) genes were located in clusters than as singletons, with variable genes more likely to be found in clusters. We identified 106 RGA candidates linked to blackleg resistance quantitative trait locus (QTL). This study provides a better understanding of resistance genes to target for genomics-based improvement and improved disease resistance.
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Affiliation(s)
- Aria Dolatabadian
- UWA School of Biological Sciences and the UWA Institute of AgricultureFaculty of ScienceThe University of Western AustraliaCrawleyWAAustralia
| | - Philipp E. Bayer
- UWA School of Biological Sciences and the UWA Institute of AgricultureFaculty of ScienceThe University of Western AustraliaCrawleyWAAustralia
| | - Soodeh Tirnaz
- UWA School of Biological Sciences and the UWA Institute of AgricultureFaculty of ScienceThe University of Western AustraliaCrawleyWAAustralia
| | - Bhavna Hurgobin
- UWA School of Biological Sciences and the UWA Institute of AgricultureFaculty of ScienceThe University of Western AustraliaCrawleyWAAustralia
| | - David Edwards
- UWA School of Biological Sciences and the UWA Institute of AgricultureFaculty of ScienceThe University of Western AustraliaCrawleyWAAustralia
| | - Jacqueline Batley
- UWA School of Biological Sciences and the UWA Institute of AgricultureFaculty of ScienceThe University of Western AustraliaCrawleyWAAustralia
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Lv H, Fang Z, Yang L, Zhang Y, Wang Y. An update on the arsenal: mining resistance genes for disease management of Brassica crops in the genomic era. HORTICULTURE RESEARCH 2020; 7:34. [PMID: 32194970 PMCID: PMC7072071 DOI: 10.1038/s41438-020-0257-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 01/12/2020] [Accepted: 01/15/2020] [Indexed: 05/18/2023]
Abstract
Brassica species include many economically important crops that provide nutrition and health-promoting substances to humans worldwide. However, as with all crops, their production is constantly threatened by emerging viral, bacterial, and fungal diseases, whose incidence has increased in recent years. Traditional methods of control are often costly, present limited effectiveness, and cause environmental damage; instead, the ideal approach is to mine and utilize the resistance genes of the Brassica crop hosts themselves. Fortunately, the development of genomics, molecular genetics, and biological techniques enables us to rapidly discover and apply resistance (R) genes. Herein, the R genes identified in Brassica crops are summarized, including their mapping and cloning, possible molecular mechanisms, and application in resistance breeding. Future perspectives concerning how to accurately discover additional R gene resources and efficiently utilize these genes in the genomic era are also discussed.
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Affiliation(s)
- Honghao Lv
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture, 12# Zhongguancun South Street, Beijing, 100081 China
| | - Zhiyuan Fang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture, 12# Zhongguancun South Street, Beijing, 100081 China
| | - Limei Yang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture, 12# Zhongguancun South Street, Beijing, 100081 China
| | - Yangyong Zhang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture, 12# Zhongguancun South Street, Beijing, 100081 China
| | - Yong Wang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture, 12# Zhongguancun South Street, Beijing, 100081 China
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Raman H, Raman R, Qiu Y, Yadav AS, Sureshkumar S, Borg L, Rohan M, Wheeler D, Owen O, Menz I, Balasubramanian S. GWAS hints at pleiotropic roles for FLOWERING LOCUS T in flowering time and yield-related traits in canola. BMC Genomics 2019; 20:636. [PMID: 31387521 PMCID: PMC6685183 DOI: 10.1186/s12864-019-5964-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Accepted: 07/09/2019] [Indexed: 12/20/2022] Open
Abstract
Background Transition to flowering at the right time is critical for local adaptation and to maximize grain yield in crops. Canola is an important oilseed crop with extensive variation in flowering time among varieties. However, our understanding of underlying genes and their role in canola productivity is limited. Results We report our analyses of a diverse GWAS panel (300–368 accessions) of canola and identify SNPs that are significantly associated with variation in flowering time and response to photoperiod across multiple locations. We show that several of these associations map in the vicinity of FLOWERING LOCUS T (FT) paralogs and its known transcriptional regulators. Complementary QTL and eQTL mapping studies, conducted in an Australian doubled haploid population, also detected consistent genomic regions close to the FT paralogs associated with flowering time and yield-related traits. FT sequences vary between accessions. Expression levels of FT in plants grown in field (or under controlled environment cabinets) correlated with flowering time. We show that markers linked to the FT paralogs display association with variation in multiple traits including flowering time, plant emergence, shoot biomass and grain yield. Conclusions Our findings suggest that FT paralogs not only control flowering time but also modulate yield-related productivity traits in canola. Electronic supplementary material The online version of this article (10.1186/s12864-019-5964-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Harsh Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, 2650, Australia.
| | - Rosy Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, 2650, Australia
| | - Yu Qiu
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, 2650, Australia
| | - Avilash Singh Yadav
- School of Biological Sciences, Monash University, Clayton, VIC3800, Australia
| | - Sridevi Sureshkumar
- School of Biological Sciences, Monash University, Clayton, VIC3800, Australia
| | - Lauren Borg
- Centre for Bioinformatics and Biometrics, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Maheswaran Rohan
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, 2650, Australia
| | - David Wheeler
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW, 2800, Australia
| | - Oliver Owen
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, 2650, Australia
| | - Ian Menz
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, 2650, Australia
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Karthikeyan A, Li K, Li C, Yin J, Li N, Yang Y, Song Y, Ren R, Zhi H, Gai J. Fine-mapping and identifying candidate genes conferring resistance to Soybean mosaic virus strain SC20 in soybean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:461-476. [PMID: 29181547 DOI: 10.1007/s00122-017-3014-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2017] [Accepted: 11/04/2017] [Indexed: 05/27/2023]
Abstract
KEY MESSAGE The Mendelian gene conferring resistance to Soybean mosaic virus Strain SC20 in soybean was fine-mapped onto a 79-kb segment on Chr.13 where two closely linked candidate genes were identified and qRT-PCR verified. Soybean mosaic virus (SMV) threatens the world soybean production, particularly in China. A country-wide SMV strain system composed of 22 strains was established in China, among which SC20 is a dominant strain in five provinces in Southern China. Resistance to SC20 was evaluated in parents, F1, F2 and the F2:7 RIL (recombinant inbred line) population derived from a cross between Qihuang-1 (resistant) and NN1138-2 (susceptible). The segregation ratio of resistant to susceptible in the populations suggested a single dominant gene involved in the resistance to SC20 in Qihuang-1. A "partial genome mapping strategy" was used to map the resistance gene on Chromosome 13. Linkage analysis between 178 RILs and genetic markers showed that the SC20-resistance gene located at 3.9 and 3.8 cM to the flanking markers BARCSOYSSR_13_1099 and BARCSOYSSR_13_1185 on Chromosome 13. Subsequently, a residual heterozygote segregating population with 346 individuals was developed by selfing four plants heterozygous at markers adjacent to the tentative SC20-resistance gene; then, the candidate region was delimited to a genomic interval of approximately 79 kb flanked by the new markers gm-ssr_13-14 and gm-indel_13-3. Among the seven annotated candidate genes in this region, two genes, Glyma.13G194700 and Glyma.13G195100, encoding Toll Interleukin Receptor-nucleotide-binding-leucine-rich repeat resistance proteins were identified as candidate resistance genes by quantitative real-time polymerase chain reaction and sequence analysis. The two closely linked genes work together to cause the phenotypic segregation as a single Mendelian gene. These results will facilitate marker-assisted selection, gene cloning and breeding for the resistance to SC20.
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Affiliation(s)
- Adhimoolam Karthikeyan
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Kai Li
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Cui Li
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Jinlong Yin
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Na Li
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Yunhua Yang
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Yingpei Song
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Rui Ren
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Haijian Zhi
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Junyi Gai
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China.
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095, Jiangsu, China.
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
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11
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Bayer PE, Hurgobin B, Golicz AA, Chan CK, Yuan Y, Lee H, Renton M, Meng J, Li R, Long Y, Zou J, Bancroft I, Chalhoub B, King GJ, Batley J, Edwards D. Assembly and comparison of two closely related Brassica napus genomes. PLANT BIOTECHNOLOGY JOURNAL 2017; 15:1602-1610. [PMID: 28403535 PMCID: PMC5698052 DOI: 10.1111/pbi.12742] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Revised: 02/06/2017] [Accepted: 04/09/2017] [Indexed: 05/18/2023]
Abstract
As an increasing number of plant genome sequences become available, it is clear that gene content varies between individuals, and the challenge arises to predict the gene content of a species. However, genome comparison is often confounded by variation in assembly and annotation. Differentiating between true gene absence and variation in assembly or annotation is essential for the accurate identification of conserved and variable genes in a species. Here, we present the de novo assembly of the B. napus cultivar Tapidor and comparison with an improved assembly of the Brassica napus cultivar Darmor-bzh. Both cultivars were annotated using the same method to allow comparison of gene content. We identified genes unique to each cultivar and differentiate these from artefacts due to variation in the assembly and annotation. We demonstrate that using a common annotation pipeline can result in different gene predictions, even for closely related cultivars, and repeat regions which collapse during assembly impact whole genome comparison. After accounting for differences in assembly and annotation, we demonstrate that the genome of Darmor-bzh contains a greater number of genes than the genome of Tapidor. Our results are the first step towards comparison of the true differences between B. napus genomes and highlight the potential sources of error in future production of a B. napus pangenome.
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Affiliation(s)
- Philipp E. Bayer
- School of Biological SciencesThe University of Western AustraliaCrawleyWAAustralia
| | - Bhavna Hurgobin
- School of Biological SciencesThe University of Western AustraliaCrawleyWAAustralia
- School of Agriculture and Food SciencesUniversity of QueenslandSt. LuciaQldAustralia
| | - Agnieszka A. Golicz
- Plant Molecular Biology and Biotechnology LaboratoryFaculty of Veterinary and Agricultural SciencesUniversity of Melbourne, ParkvilleMelbourneVic.Australia
| | | | - Yuxuan Yuan
- School of Biological SciencesThe University of Western AustraliaCrawleyWAAustralia
| | - HueyTyng Lee
- School of Biological SciencesThe University of Western AustraliaCrawleyWAAustralia
- School of Agriculture and Food SciencesUniversity of QueenslandSt. LuciaQldAustralia
| | - Michael Renton
- School of Biological SciencesThe University of Western AustraliaCrawleyWAAustralia
- School of Agriculture and EnvironmentThe University of Western AustraliaCrawleyWAAustralia
| | - Jinling Meng
- National Key Laboratory of Crop Genetic ImprovementKey Laboratory of Rapeseed Genetic ImprovementMinistry of Agriculture P. R. ChinaHuazhong Agricultural UniversityWuhanChina
| | - Ruiyuan Li
- National Key Laboratory of Crop Genetic ImprovementKey Laboratory of Rapeseed Genetic ImprovementMinistry of Agriculture P. R. ChinaHuazhong Agricultural UniversityWuhanChina
| | - Yan Long
- National Key Laboratory of Crop Genetic ImprovementKey Laboratory of Rapeseed Genetic ImprovementMinistry of Agriculture P. R. ChinaHuazhong Agricultural UniversityWuhanChina
| | - Jun Zou
- National Key Laboratory of Crop Genetic ImprovementKey Laboratory of Rapeseed Genetic ImprovementMinistry of Agriculture P. R. ChinaHuazhong Agricultural UniversityWuhanChina
| | | | - Boulos Chalhoub
- Organization and Evolution of Complex Genomes (OECG)Institut National de la Recherche agronomique (INRA)Université d'Evry Val d'Essonne (UEVE)EvryFrance
- Institute of System and Synthetic Biology, GenopoleCentre National de la Recherche ScientifiqueUniversité d'Evry Val d'EssonneUniversité Paris‐SaclayEvryFrance
| | - Graham J. King
- National Key Laboratory of Crop Genetic ImprovementKey Laboratory of Rapeseed Genetic ImprovementMinistry of Agriculture P. R. ChinaHuazhong Agricultural UniversityWuhanChina
- Southern Cross Plant ScienceSouthern Cross UniversityLismoreNSWAustralia
| | - Jacqueline Batley
- School of Biological SciencesThe University of Western AustraliaCrawleyWAAustralia
| | - David Edwards
- School of Biological SciencesThe University of Western AustraliaCrawleyWAAustralia
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12
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Neik TX, Barbetti MJ, Batley J. Current Status and Challenges in Identifying Disease Resistance Genes in Brassica napus. FRONTIERS IN PLANT SCIENCE 2017; 8:1788. [PMID: 29163558 PMCID: PMC5681527 DOI: 10.3389/fpls.2017.01788] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 10/02/2017] [Indexed: 05/18/2023]
Abstract
Brassica napus is an economically important crop across different continents including temperate and subtropical regions in Europe, Canada, South Asia, China and Australia. Its widespread cultivation also brings setbacks as it plays host to fungal, oomycete and chytrid pathogens that can lead to serious yield loss. For sustainable crop production, identification of resistance (R) genes in B. napus has become of critical importance. In this review, we discuss four key pathogens affecting Brassica crops: Clubroot (Plasmodiophora brassicae), Blackleg (Leptosphaeria maculans and L. biglobosa), Sclerotinia Stem Rot (Sclerotinia sclerotiorum), and Downy Mildew (Hyaloperonospora parasitica). We first review current studies covering prevalence of these pathogens on Brassica crops and highlight the R genes and QTL that have been identified from Brassica species against these pathogens. Insights into the relationships between the pathogen and its Brassica host, the unique host resistance mechanisms and how these affect resistance outcomes is also presented. We discuss challenges in identification and deployment of R genes in B. napus in relation to highly specific genetic interactions between host subpopulations and pathogen pathotypes and emphasize the need for common or shared techniques and research materials or tighter collaboration between researchers to reconcile the inconsistencies in the research outcomes. Using current genomics tools, we provide examples of how characterization and cloning of R genes in B. napus can be carried out more effectively. Lastly, we put forward strategies to breed resistant cultivars through introgressions supported by genomic approaches and suggest prospects that can be implemented in the future for a better, pathogen-resistant B. napus.
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Affiliation(s)
- Ting Xiang Neik
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Martin J. Barbetti
- School of Agriculture and Environment and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
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13
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Cheng F, Wu J, Cai C, Fu L, Liang J, Borm T, Zhuang M, Zhang Y, Zhang F, Bonnema G, Wang X. Genome resequencing and comparative variome analysis in a Brassica rapa and Brassica oleracea collection. Sci Data 2016; 3:160119. [PMID: 27996963 PMCID: PMC5170593 DOI: 10.1038/sdata.2016.119] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 10/21/2016] [Indexed: 11/09/2022] Open
Abstract
The closely related species Brassica rapa and B. oleracea encompass a wide range of vegetable, fodder and oil crops. The release of their reference genomes has facilitated resequencing collections of B. rapa and B. oleracea aiming to build their variome datasets. These data can be used to investigate the evolutionary relationships between and within the different species and the domestication of the crops, hereafter named morphotypes. These data can also be used in genetic studies aiming at the identification of genes that influence agronomic traits. We selected and resequenced 199 B. rapa and 119 B. oleracea accessions representing 12 and nine morphotypes, respectively. Based on these resequencing data, we obtained 2,249,473 and 3,852,169 high quality SNPs (single-nucleotide polymorphisms), as well as 303,617 and 417,004 InDels for the B. rapa and B. oleracea populations, respectively. The variome datasets of B. rapa and B. oleracea represent valuable resources to researchers working on evolution, domestication or breeding of Brassica vegetable crops.
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Affiliation(s)
- Feng Cheng
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
| | - Jian Wu
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
| | - Chengcheng Cai
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
| | - Lixia Fu
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
| | - Jianli Liang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
| | - Theo Borm
- Wageningen UR Plant Breeding, Wageningen University and Research centre, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Mu Zhuang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
| | - Yangyong Zhang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
| | - Fenglan Zhang
- Beijing Academy of Agriculture and Foresty Science (BAAFS), Beijing Vegetable Research Center (BVRC), Beijing 10089, China
| | - Guusje Bonnema
- Wageningen UR Plant Breeding, Wageningen University and Research centre, Droevendaalsesteeg 1, Wageningen 6708 PB, The Netherlands
| | - Xiaowu Wang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Beijing 10081, China
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14
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Raman H, Raman R, Coombes N, Song J, Diffey S, Kilian A, Lindbeck K, Barbulescu DM, Batley J, Edwards D, Salisbury PA, Marcroft S. Genome-wide Association Study Identifies New Loci for Resistance to Leptosphaeria maculans in Canola. FRONTIERS IN PLANT SCIENCE 2016; 7:1513. [PMID: 27822217 PMCID: PMC5075532 DOI: 10.3389/fpls.2016.01513] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Accepted: 09/23/2016] [Indexed: 05/18/2023]
Abstract
Key message "We identified both quantitative and quantitative resistance loci to Leptosphaeria maculans, a fungal pathogen, causing blackleg disease in canola. Several genome-wide significant associations were detected at known and new loci for blackleg resistance. We further validated statistically significant associations in four genetic mapping populations, demonstrating that GWAS marker loci are indeed associated with resistance to L. maculans. One of the novel loci identified for the first time, Rlm12, conveys adult plant resistance in canola." Blackleg, caused by Leptosphaeria maculans, is a significant disease which affects the sustainable production of canola (Brassica napus). This study reports a genome-wide association study based on 18,804 polymorphic SNPs to identify loci associated with qualitative and quantitative resistance to L. maculans. Genomic regions delimited with 694 significant SNP markers, that are associated with resistance evaluated using 12 single spore isolates and pathotypes from four canola stubble were identified. Several significant associations were detected at known disease resistance loci including in the vicinity of recently cloned Rlm2/LepR3 genes, and at new loci on chromosomes A01/C01, A02/C02, A03/C03, A05/C05, A06, A08, and A09. In addition, we validated statistically significant associations on A01, A07, and A10 in four genetic mapping populations, demonstrating that GWAS marker loci are indeed associated with resistance to L. maculans. One of the novel loci identified for the first time, Rlm12, conveys adult plant resistance and mapped within 13.2 kb from Arabidopsis R gene of TIR-NBS class. We showed that resistance loci are located in the vicinity of R genes of Arabidopsis thaliana and Brassica napus on the sequenced genome of B. napus cv. Darmor-bzh. Significantly associated SNP markers provide a valuable tool to enrich germplasm for favorable alleles in order to improve the level of resistance to L. maculans in canola.
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Affiliation(s)
- Harsh Raman
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga WaggaNSW, Australia
| | - Rosy Raman
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga WaggaNSW, Australia
| | - Neil Coombes
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga WaggaNSW, Australia
| | - Jie Song
- Diversity Array Technology P/L, University of Canberra, CanberraACT, Australia
| | - Simon Diffey
- Centre for Bioinformatics and Biometrics, University of Wollongong, WollongongNSW, Australia
| | - Andrzej Kilian
- Diversity Array Technology P/L, University of Canberra, CanberraACT, Australia
| | - Kurt Lindbeck
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga WaggaNSW, Australia
| | - Denise M. Barbulescu
- Department of Economic Development, Jobs, Transport and Resources, HorshamVIC, Australia
| | - Jacqueline Batley
- School of Plant Biology, University of Western Australia, CrawleyWA, Australia
| | - David Edwards
- School of Plant Biology, University of Western Australia, CrawleyWA, Australia
- Institute of Agriculture, University of Western Australia, CrawleyWA, Australia
| | - Phil A. Salisbury
- Department of Economic Development, Jobs, Transport and Resources, HorshamVIC, Australia
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, ParkvilleVIC, Australia
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15
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Fletcher RS, Herrmann D, Mullen JL, Li Q, Schrider DR, Price N, Lin J, Grogan K, Kern A, McKay JK. Identification of Polymorphisms Associated with Drought Adaptation QTL in Brassica napus by Resequencing. G3 (BETHESDA, MD.) 2016; 6:793-803. [PMID: 26801646 PMCID: PMC4825650 DOI: 10.1534/g3.115.021279] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2015] [Accepted: 01/17/2016] [Indexed: 11/24/2022]
Abstract
Brassica napus is a globally important oilseed for which little is known about the genetics of drought adaptation. We previously mapped twelve quantitative trait loci (QTL) underlying drought-related traits in a biparental mapping population created from a cross between winter and spring B. napus cultivars. Here we resequence the genomes of the mapping population parents to identify genetic diversity across the genome and within QTL regions. We sequenced each parental cultivar on the Illumina HiSeq platform to a minimum depth of 23 × and performed a reference based assembly in order to describe the molecular variation differentiating them at the scale of the genome, QTL and gene. Genome-wide patterns of variation were characterized by an overall higher single nucleotide polymorphism (SNP) density in the A genome and a higher ratio of nonsynonymous to synonymous substitutions in the C genome. Nonsynonymous substitutions were used to categorize gene ontology terms differentiating the parent genomes along with a list of putative functional variants contained within each QTL. Marker assays were developed for several of the discovered polymorphisms within a pleiotropic QTL on chromosome A10. QTL analysis with the new, denser map showed the most associated marker to be that developed from an insertion/deletion polymorphism located in the candidate gene Bna.FLC.A10, and it was the only candidate within the QTL interval with observed polymorphism. Together, these results provide a glimpse of genome-wide variation differentiating annual and biennial B. napus ecotypes as well as a better understanding of the genetic basis of root and drought phenotypes.
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Affiliation(s)
| | - David Herrmann
- Cargill Specialty Seeds & Oils, Fort Collins, Colorado 80525
| | - Jack L Mullen
- Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, Colorado 80523
| | - Qinfei Li
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400716, China
| | - Daniel R Schrider
- Department of Genetics, Rutgers University, Piscataway, New Jersey 08854
| | - Nicholas Price
- Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, Colorado 80523
| | - Junjiang Lin
- Department of Computer Science, University of Toronto, Ontario M5S 2J7, Canada
| | - Kelsi Grogan
- Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, Colorado 80523
| | - Andrew Kern
- Department of Genetics, Rutgers University, Piscataway, New Jersey 08854
| | - John K McKay
- Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, Colorado 80523
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16
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Hayward AC, Tollenaere R, Dalton-Morgan J, Batley J. Molecular marker applications in plants. Methods Mol Biol 2015; 1245:13-27. [PMID: 25373746 DOI: 10.1007/978-1-4939-1966-6_2] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Individuals within a population of a sexually reproducing species will have some degree of heritable genomic variation caused by mutations, insertion/deletions (INDELS), inversions, duplications, and translocations. Such variation can be detected and screened using molecular, or genetic, markers. By definition, molecular markers are genetic loci that can be easily tracked and quantified in a population and may be associated with a particular gene or trait of interest. This chapter will review the current major applications of molecular markers in plants.
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Affiliation(s)
- Alice C Hayward
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD, Australia
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17
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Abstract
The detection and analysis of genetic variation plays an important role in plant breeding and this role is increasing with the continued development of genome sequencing technologies. Molecular genetic markers are important tools to characterize genetic variation and assist with genomic breeding. Processing and storing the growing abundance of molecular marker data being produced requires the development of specific bioinformatics tools and advanced databases. Molecular marker databases range from species specific through to organism wide and often host a variety of additional related genetic, genomic, or phenotypic information. In this chapter, we will present some of the features of plant molecular genetic marker databases, highlight the various types of marker resources, and predict the potential future direction of crop marker databases.
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18
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Liu JJ, Sniezko RA, Sturrock RN, Chen H. Western white pine SNP discovery and high-throughput genotyping for breeding and conservation applications. BMC PLANT BIOLOGY 2014; 14:380. [PMID: 25547170 PMCID: PMC4302426 DOI: 10.1186/s12870-014-0380-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2014] [Accepted: 12/11/2014] [Indexed: 05/10/2023]
Abstract
BACKGROUND Western white pine (WWP, Pinus monticola Douglas ex D. Don) is of high interest in forest breeding and conservation because of its high susceptibility to the invasive disease white pine blister rust (WPBR, caused by the fungus Cronartium ribicola J. C. Fisch). However, WWP lacks genomic resource development and is evolutionarily far away from plants with available draft genome sequences. Here we report a single nucleotide polymorphism (SNP) study by bulked segregation-based RNA-Seq analysis. RESULTS A collection of resistance germplasm was used for construction of cDNA libraries and SNP genotyping. Approximately 36-89 million 2 × 100-bp reads were obtained per library and de-novo assembly generated the first shoot-tip reference transcriptome containing a total of 54,661 unique transcripts. Bioinformatic SNP detection identified >100,000 high quality SNPs in three expressed candidate gene groups: Pinus highly conserved genes (HCGs), differential expressed genes (DEGs) in plant defense response, and resistance gene analogs (RGAs). To estimate efficiency of in-silico SNP discovery, genotyping assay was developed by using Sequenom iPlex and it unveiled SNP success rates from 40.1% to 61.1%. SNP clustering analyses consistently revealed distinct populations, each composed of multiple full-sib seed families by parentage assignment in the WWP germplasm collection. Linkage disequilibrium (LD) analysis identified six genes in significant association with major gene (Cr2) resistance, including three RGAs (two NBS-LRR genes and one receptor-like protein kinase -RLK gene), two HCGs, and one DEG. At least one SNP locus provided an excellent marker for Cr2 selection across P. monticola populations. CONCLUSIONS The WWP shoot tip transcriptome and those validated SNP markers provide novel genomic resources for genetic, evolutionary and ecological studies. SNP loci of those candidate genes associated with resistant phenotypes can be used as positional and functional variation sites for further characterization of WWP major gene resistance against C. ribicola. Our results demonstrate that integration of RNA-seq-based transcriptome analysis and high-throughput genotyping is an effective approach for discovery of a large number of nucleotide variations and for identification of functional gene variants associated with adaptive traits in a non-model species.
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Affiliation(s)
- Jun-Jun Liu
- />Pacific Forestry Centre, Canadian Forest Service, Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5 Canada
| | - Richard A Sniezko
- />USDA Forest Service, Dorena Genetic Resource Center, 34963 Shoreview Road, Cottage Grove, OR 97424 USA
| | - Rona N Sturrock
- />Pacific Forestry Centre, Canadian Forest Service, Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5 Canada
| | - Hao Chen
- />Pacific Forestry Centre, Canadian Forest Service, Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5 Canada
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19
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Raman H, Dalton-Morgan J, Diffey S, Raman R, Alamery S, Edwards D, Batley J. SNP markers-based map construction and genome-wide linkage analysis in Brassica napus. PLANT BIOTECHNOLOGY JOURNAL 2014; 12:851-60. [PMID: 24698362 DOI: 10.1111/pbi.12186] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2013] [Revised: 01/29/2014] [Accepted: 02/21/2014] [Indexed: 05/19/2023]
Abstract
An Illumina Infinium array comprising 5306 single nucleotide polymorphism (SNP) markers was used to genotype 175 individuals of a doubled haploid population derived from a cross between Skipton and Ag-Spectrum, two Australian cultivars of rapeseed (Brassica napus L.). A genetic linkage map based on 613 SNP and 228 non-SNP (DArT, SSR, SRAP and candidate gene markers) covering 2514.8 cM was constructed and further utilized to identify loci associated with flowering time and resistance to blackleg, a disease caused by the fungus Leptosphaeria maculans. Comparison between genetic map positions of SNP markers and the sequenced Brassica rapa (A) and Brassica oleracea (C) genome scaffolds showed several genomic rearrangements in the B. napus genome. A major locus controlling resistance to L. maculans was identified at both seedling and adult plant stages on chromosome A07. QTL analyses revealed that up to 40.2% of genetic variation for flowering time was accounted for by loci having quantitative effects. Comparative mapping showed Arabidopsis and Brassica flowering genes such as Phytochrome A/D, Flowering Locus C and agamous-Like MADS box gene AGL1 map within marker intervals associated with flowering time in a DH population from Skipton/Ag-Spectrum. Genomic regions associated with flowering time and resistance to L. maculans had several SNP markers mapped within 10 cM. Our results suggest that SNP markers will be suitable for various applications such as trait introgression, comparative mapping and high-resolution mapping of loci in B. napus.
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Affiliation(s)
- Harsh Raman
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
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Chalhoub B, Denoeud F, Liu S, Parkin IAP, Tang H, Wang X, Chiquet J, Belcram H, Tong C, Samans B, Corréa M, Da Silva C, Just J, Falentin C, Koh CS, Le Clainche I, Bernard M, Bento P, Noel B, Labadie K, Alberti A, Charles M, Arnaud D, Guo H, Daviaud C, Alamery S, Jabbari K, Zhao M, Edger PP, Chelaifa H, Tack D, Lassalle G, Mestiri I, Schnel N, Le Paslier MC, Fan G, Renault V, Bayer PE, Golicz AA, Manoli S, Lee TH, Thi VHD, Chalabi S, Hu Q, Fan C, Tollenaere R, Lu Y, Battail C, Shen J, Sidebottom CHD, Wang X, Canaguier A, Chauveau A, Bérard A, Deniot G, Guan M, Liu Z, Sun F, Lim YP, Lyons E, Town CD, Bancroft I, Wang X, Meng J, Ma J, Pires JC, King GJ, Brunel D, Delourme R, Renard M, Aury JM, Adams KL, Batley J, Snowdon RJ, Tost J, Edwards D, Zhou Y, Hua W, Sharpe AG, Paterson AH, Guan C, Wincker P. Plant genetics. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science 2014; 345:950-3. [PMID: 25146293 DOI: 10.1126/science.1253435] [Citation(s) in RCA: 1434] [Impact Index Per Article: 143.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Oilseed rape (Brassica napus L.) was formed ~7500 years ago by hybridization between B. rapa and B. oleracea, followed by chromosome doubling, a process known as allopolyploidy. Together with more ancient polyploidizations, this conferred an aggregate 72× genome multiplication since the origin of angiosperms and high gene content. We examined the B. napus genome and the consequences of its recent duplication. The constituent An and Cn subgenomes are engaged in subtle structural, functional, and epigenetic cross-talk, with abundant homeologous exchanges. Incipient gene loss and expression divergence have begun. Selection in B. napus oilseed types has accelerated the loss of glucosinolate genes, while preserving expansion of oil biosynthesis genes. These processes provide insights into allopolyploid evolution and its relationship with crop domestication and improvement.
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Affiliation(s)
- Boulos Chalhoub
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France.
| | - France Denoeud
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France. Université d'Evry Val d'Essone, UMR 8030, CP5706, Evry, France. Centre National de Recherche Scientifique (CNRS), UMR 8030, CP5706, Evry, France
| | - Shengyi Liu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture of People's Republic of China, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Isobel A P Parkin
- Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon, SK S7N 0X2, Canada.
| | - Haibao Tang
- J. Craig Venter Institute, Rockville, MD 20850, USA. Center for Genomics and Biotechnology, Fujian Agriculture and Forestry, University, Fuzhou 350002, Fujian Province, China
| | - Xiyin Wang
- Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA. Center of Genomics and Computational Biology, School of Life Sciences, Hebei United University, Tangshan, Hebei 063000, China
| | - Julien Chiquet
- Laboratoire de Mathématiques et Modélisation d'Evry-UMR 8071 CNRS/Université d'Evry val d'Essonne-USC INRA, Evry, France
| | - Harry Belcram
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Chaobo Tong
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture of People's Republic of China, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Birgit Samans
- Department of Plant Breeding, Research Center for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany
| | - Margot Corréa
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Corinne Da Silva
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Jérémy Just
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Cyril Falentin
- INRA, Institut de Génétique, Environnement et Protection des Plantes (IGEPP) UMR1349, BP35327, 35653 Le Rheu Cedex, France
| | - Chu Shin Koh
- National Research Council Canada, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada
| | - Isabelle Le Clainche
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Maria Bernard
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Pascal Bento
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Benjamin Noel
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Karine Labadie
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Adriana Alberti
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Mathieu Charles
- INRA, Etude du Polymorphisme des Génomes Végétaux, US1279, Centre National de Génotypage, CEA-IG, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Dominique Arnaud
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Hui Guo
- Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA
| | - Christian Daviaud
- Laboratory for Epigenetics and Environment, Centre National de Génotypage, CEA-IG, 2 rue Gaston Crémieux, 91000 Evry, France
| | - Salman Alamery
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD 4072, Australia
| | - Kamel Jabbari
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France. Cologne Center for Genomics, University of Cologne, Weyertal 115b, 50931 Köln, Germany
| | - Meixia Zhao
- Department of Agronomy, Purdue University, WSLR Building B018, West Lafayette, IN 47907, USA
| | - Patrick P Edger
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - Houda Chelaifa
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - David Tack
- Department of Botany, University of British Columbia, Vancouver, BC, Canada
| | - Gilles Lassalle
- INRA, Institut de Génétique, Environnement et Protection des Plantes (IGEPP) UMR1349, BP35327, 35653 Le Rheu Cedex, France
| | - Imen Mestiri
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Nicolas Schnel
- INRA, Institut de Génétique, Environnement et Protection des Plantes (IGEPP) UMR1349, BP35327, 35653 Le Rheu Cedex, France
| | - Marie-Christine Le Paslier
- INRA, Etude du Polymorphisme des Génomes Végétaux, US1279, Centre National de Génotypage, CEA-IG, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Guangyi Fan
- Beijing Genome Institute-Shenzhen, Shenzhen 518083, China
| | - Victor Renault
- Fondation Jean Dausset-Centre d'Étude du Polymorphisme Humain, 27 rue Juliette Dodu, 75010 Paris, France
| | - Philippe E Bayer
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD 4072, Australia
| | - Agnieszka A Golicz
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD 4072, Australia
| | - Sahana Manoli
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD 4072, Australia
| | - Tae-Ho Lee
- Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA
| | - Vinh Ha Dinh Thi
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Smahane Chalabi
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Qiong Hu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture of People's Republic of China, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Chuchuan Fan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Reece Tollenaere
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD 4072, Australia
| | - Yunhai Lu
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Christophe Battail
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Jinxiong Shen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | | | - Xinfa Wang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture of People's Republic of China, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Aurélie Canaguier
- Institut National de Recherche Agronomique (INRA)/Université d'Evry Val d'Essone, Unité de Recherche en Génomique Végétale, UMR1165, Organization and Evolution of Plant Genomes, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Aurélie Chauveau
- INRA, Etude du Polymorphisme des Génomes Végétaux, US1279, Centre National de Génotypage, CEA-IG, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Aurélie Bérard
- INRA, Etude du Polymorphisme des Génomes Végétaux, US1279, Centre National de Génotypage, CEA-IG, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Gwenaëlle Deniot
- INRA, Institut de Génétique, Environnement et Protection des Plantes (IGEPP) UMR1349, BP35327, 35653 Le Rheu Cedex, France
| | - Mei Guan
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
| | - Zhongsong Liu
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
| | - Fengming Sun
- Beijing Genome Institute-Shenzhen, Shenzhen 518083, China
| | - Yong Pyo Lim
- Molecular Genetics and Genomics Laboratory, Department of Horticulture, Chungnam National University, Daejeon-305764, South Korea
| | - Eric Lyons
- School of Plant Sciences, iPlant Collaborative, University of Arizona, Tucson, AZ, USA
| | | | - Ian Bancroft
- Department of Biology, University of York, Wentworth Way, Heslington, York YO10 5DD, UK
| | - Xiaowu Wang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinling Meng
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Jianxin Ma
- Department of Agronomy, Purdue University, WSLR Building B018, West Lafayette, IN 47907, USA
| | - J Chris Pires
- Division of Biological Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Graham J King
- Southern Cross Plant Science, Southern Cross University, Lismore, NSW 2480, Australia
| | - Dominique Brunel
- INRA, Etude du Polymorphisme des Génomes Végétaux, US1279, Centre National de Génotypage, CEA-IG, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Régine Delourme
- INRA, Institut de Génétique, Environnement et Protection des Plantes (IGEPP) UMR1349, BP35327, 35653 Le Rheu Cedex, France
| | - Michel Renard
- INRA, Institut de Génétique, Environnement et Protection des Plantes (IGEPP) UMR1349, BP35327, 35653 Le Rheu Cedex, France
| | - Jean-Marc Aury
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France
| | - Keith L Adams
- Department of Botany, University of British Columbia, Vancouver, BC, Canada
| | - Jacqueline Batley
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD 4072, Australia. School of Plant Biology, University of Western Australia, WA 6009, Australia
| | - Rod J Snowdon
- Department of Plant Breeding, Research Center for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany
| | - Jorg Tost
- Laboratory for Epigenetics and Environment, Centre National de Génotypage, CEA-IG, 2 rue Gaston Crémieux, 91000 Evry, France
| | - David Edwards
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD 4072, Australia. School of Plant Biology, University of Western Australia, WA 6009, Australia.
| | - Yongming Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
| | - Wei Hua
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture of People's Republic of China, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
| | - Andrew G Sharpe
- National Research Council Canada, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada.
| | - Andrew H Paterson
- Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA.
| | - Chunyun Guan
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China.
| | - Patrick Wincker
- Commissariat à l'Energie Atomique (CEA), Institut de Génomique (IG), Genoscope, BP5706, 91057 Evry, France. Université d'Evry Val d'Essone, UMR 8030, CP5706, Evry, France. Centre National de Recherche Scientifique (CNRS), UMR 8030, CP5706, Evry, France.
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Wei L, Xiao M, Hayward A, Fu D. Applications and challenges of next-generation sequencing in Brassica species. PLANTA 2013; 238:1005-24. [PMID: 24062086 DOI: 10.1007/s00425-013-1961-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2013] [Accepted: 09/12/2013] [Indexed: 05/09/2023]
Abstract
Next-generation sequencing (NGS) produces numerous (often millions) short DNA sequence reads, typically varying between 25 and 400 bp in length, at a relatively low cost and in a short time. This revolutionary technology is being increasingly applied in whole-genome, transcriptome, epigenome and small RNA sequencing, molecular marker and gene discovery, comparative and evolutionary genomics, and association studies. The Brassica genus comprises some of the most agro-economically important crops, providing abundant vegetables, condiments, fodder, oil and medicinal products. Many Brassica species have undergone the process of polyploidization, which makes their genomes exceptionally complex and can create difficulties in genomics research. NGS injects new vigor into Brassica research, yet also faces specific challenges in the analysis of complex crop genomes and traits. In this article, we review the advantages and limitations of different NGS technologies and their applications and challenges, using Brassica as an advanced model system for agronomically important, polyploid crops. Specifically, we focus on the use of NGS for genome resequencing, transcriptome sequencing, development of single-nucleotide polymorphism markers, and identification of novel microRNAs and their targets. We present trends and advances in NGS technology in relation to Brassica crop improvement, with wide application for sophisticated genomics research into agronomically important polyploid crops.
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Affiliation(s)
- Lijuan Wei
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Agronomy College, Jiangxi Agricultural University, Nanchang, 330045, China
- Chongqing Engineering Research Center for Rapeseed, College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Meili Xiao
- Chongqing Engineering Research Center for Rapeseed, College of Agronomy and Biotechnology, Southwest University, Chongqing, 400716, China
| | - Alice Hayward
- Centre for Integrative Legume Research, School of Agriculture and Food Sciences, The University of Queensland, St Lucia, 4072, Australia
| | - Donghui Fu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Agronomy College, Jiangxi Agricultural University, Nanchang, 330045, China.
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Zander M, Patel DA, Van de Wouw A, Lai K, Lorenc MT, Campbell E, Hayward A, Edwards D, Raman H, Batley J. Identifying genetic diversity of avirulence genes in Leptosphaeria maculans using whole genome sequencing. Funct Integr Genomics 2013; 13:295-308. [PMID: 23793572 DOI: 10.1007/s10142-013-0324-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2013] [Revised: 05/07/2013] [Accepted: 05/12/2013] [Indexed: 12/18/2022]
Abstract
Next generation sequencing technology allows rapid re-sequencing of individuals, as well as the discovery of single nucleotide polymorphisms (SNPs), for genomic diversity and evolutionary analyses. By sequencing two isolates of the fungal plant pathogen Leptosphaeria maculans, the causal agent of blackleg disease in Brassica crops, we have generated a resource of over 76 million sequence reads aligned to the reference genome. We identified over 21,000 SNPs with an overall SNP frequency of one SNP every 2,065 bp. Sequence validation of a selection of these SNPs in additional isolates collected throughout Australia indicates a high degree of polymorphism in the Australian population. In preliminary phylogenetic analysis, isolates from Western Australia clustered together and those collected from Brassica juncea stubble were identical. These SNPs provide a novel marker resource to study the genetic diversity of this pathogen. We demonstrate that re-sequencing provides a method of validating previously characterised SNPs and analysing differences in important genes, such as the disease related avirulence genes of L. maculans. Understanding the genetic characteristics of this devastating pathogen is vital in developing long-term solutions to managing blackleg disease in Brassica crops.
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Affiliation(s)
- Manuel Zander
- School of Agriculture and Food Sciences and Centre for Integrative Legume Research, University of Queensland, Brisbane, Queensland 4072, Australia
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Edwards D, Batley J, Snowdon RJ. Accessing complex crop genomes with next-generation sequencing. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2013; 126:1-11. [PMID: 22948437 DOI: 10.1007/s00122-012-1964-x] [Citation(s) in RCA: 133] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2012] [Accepted: 08/08/2012] [Indexed: 05/02/2023]
Abstract
Many important crop species have genomes originating from ancestral or recent polyploidisation events. Multiple homoeologous gene copies, chromosomal rearrangements and amplification of repetitive DNA within large and complex crop genomes can considerably complicate genome analysis and gene discovery by conventional, forward genetics approaches. On the other hand, ongoing technological advances in molecular genetics and genomics today offer unprecedented opportunities to analyse and access even more recalcitrant genomes. In this review, we describe next-generation sequencing and data analysis techniques that vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. We focus primarily on wheat and oilseed rape, two leading examples of major polyploid crop genomes whose size or complexity present different, significant challenges. In both cases, the latest DNA sequencing technologies, applied using quite different approaches, have enabled considerable progress towards unravelling the respective genomes. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and its relationship to yield and quality-related traits, is swiftly gathering momentum as DNA sequencing and the bioinformatic tools to deal with growing quantities of genomic data continue to develop. In the coming decade, genomic and transcriptomic sequencing, discovery and high-throughput screening of single nucleotide polymorphisms, presence-absence variations and other structural chromosomal variants in diverse germplasm collections will give detailed insight into the origins, domestication and available trait-relevant variation of polyploid crops, in the process facilitating novel approaches and possibilities for genomics-assisted breeding.
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Affiliation(s)
- David Edwards
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD 4072, Australia
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Edwards D, Henry RJ, Edwards KJ. Preface: advances in DNA sequencing accelerating plant biotechnology. PLANT BIOTECHNOLOGY JOURNAL 2012; 10:621-2. [PMID: 22765873 DOI: 10.1111/j.1467-7652.2012.00724.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
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