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Miao H, Zhang J, Zheng Y, Jia C, Hu Y, Wang J, Zhang J, Sun P, Jin Z, Zhou Y, Zheng S, Wang W, Rouard M, Xie J, Liu J. Shaping the future of bananas: advancing genetic trait regulation and breeding in the postgenomics era. HORTICULTURE RESEARCH 2025; 12:uhaf044. [PMID: 40236735 PMCID: PMC11997438 DOI: 10.1093/hr/uhaf044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2024] [Accepted: 02/03/2025] [Indexed: 04/17/2025]
Abstract
Bananas (Musa spp.) are among the top-produced food crops, serving as a primary source of food for millions of people. Cultivated bananas originated primarily from the wild diploid species Musa acuminata (A genome) and Musa balbisiana (B genome) through intra- and interspecific hybridization and selections via somatic variation. Following the publication of complete A- and B-genome sequences, prospects for complementary studies on S- and T-genome traits, key gene identification for yield, ripening, quality, and stress resistance, and advances in molecular breeding have significantly expanded. In this review, latest research progress on banana A, B, S, and T genomes is briefly summarized, highlighting key advances in banana cytoplasmic inheritance, flower and fruit development, sterility, and parthenocarpy, postharvest ripening and quality regulation, and biotic and abiotic stress resistance associated with desirable economic traits. We provide updates on transgenic, gene editing, and molecular breeding. We also explore future directions for banana breeding and genetic improvement.
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Affiliation(s)
- Hongxia Miao
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Jianbin Zhang
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Yunke Zheng
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Caihong Jia
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Yulin Hu
- Key Laboratory of Tropical Fruit Biology of Ministry of Agriculture and Rural Affairs, Key Laboratory of Hainan Province for Postharvest Physiology and Technology of Tropical Horticultural Products, South Subtropical Crop Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xiuhu Road 1, Mazhang District, Zhanjiang 524000, China
| | - Jingyi Wang
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Jing Zhang
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Peiguang Sun
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Zhiqiang Jin
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
| | - Yongfeng Zhou
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Pengfei Road 7, Dapengxin District, Shenzhen 518000, China
| | - Sijun Zheng
- Yunnan Key Laboratory of Green Prevention and Control of Agricultural Transboundary Pests, Agricultural Environment and Resources Institute, Yunnan Academy of Agricultural Sciences, Beijing Road 2238, Kunming 650205, China
- Bioversity International, Yunnan Academy of Agricultural Sciences, Beijing Road 2238, Kunming 650205, China
| | - Wei Wang
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
| | - Mathieu Rouard
- Bioversity International, Parc Scientifique Agropolis II, Montpellier 34397, Cedex 5, France
| | - Jianghui Xie
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
| | - Juhua Liu
- National key Laboratory of Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology & Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Sanya/Haikou 571101, China
- Hainan Key Laboratory for Protection and Utilization of Tropical Bioresources, Hainan Institute for Tropical Agricultural Resources, Chinese Academy of Tropical Agricultural Sciences, Xueyuan Road 4, Longhua District, Haikou 571101, China
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MacNish TR, Al‐Mamun HA, Bayer PE, McPhan C, Fernandez CGT, Upadhyaya SR, Liu S, Batley J, Parkin IAP, Sharpe AG, Edwards D. Brassica Panache: A multi-species graph pangenome representing presence absence variation across forty-one Brassica genomes. THE PLANT GENOME 2025; 18:e20535. [PMID: 39648684 PMCID: PMC11730171 DOI: 10.1002/tpg2.20535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 10/20/2024] [Accepted: 11/01/2024] [Indexed: 12/10/2024]
Abstract
Brassicas are an economically important crop species that provide a source of healthy oil and vegetables. With the rising population and the impact of climate change on agriculture, there is an increasing need to improve agronomically important traits of crops such as Brassica. The genomes of plant species have significant sequence presence absence variation (PAV), which is a source of genetic variation that can be used for crop improvement, and this species variation can be captured through the construction of pangenomes. Graph pangenomes are a recent reference format that represent the genomic variation with a species or population as alternate paths in a sequence graph. Graph pangenomes contain information on alignment, PAV, and annotation. Here we present the first multi-species graph pangenome for Brassica visualized with pangenome analyzer with chromosomal exploration (Panache).
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Affiliation(s)
- Tessa R. MacNish
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
- Center for Applied BioinformaticsThe University of Western AustraliaPerthWestern AustraliaAustralia
| | - Hawlader A. Al‐Mamun
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
- Center for Applied BioinformaticsThe University of Western AustraliaPerthWestern AustraliaAustralia
| | - Philipp E. Bayer
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
- Center for Applied BioinformaticsThe University of Western AustraliaPerthWestern AustraliaAustralia
- Minderoo FoundationPerthWestern AustraliaAustralia
| | - Connor McPhan
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
- Center for Applied BioinformaticsThe University of Western AustraliaPerthWestern AustraliaAustralia
| | - Cassandria G. Tay Fernandez
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
- Center for Applied BioinformaticsThe University of Western AustraliaPerthWestern AustraliaAustralia
| | - Shriprabha R. Upadhyaya
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
- Center for Applied BioinformaticsThe University of Western AustraliaPerthWestern AustraliaAustralia
| | - Shengyi Liu
- Oil Crops Research Institute, CAASWuhanChina
| | - Jacqueline Batley
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
| | | | | | - David Edwards
- School of Biological SciencesThe University of Western AustraliaPerthWestern AustraliaAustralia
- Center for Applied BioinformaticsThe University of Western AustraliaPerthWestern AustraliaAustralia
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He W, Li X, Qian Q, Shang L. The developments and prospects of plant super-pangenomes: Demands, approaches, and applications. PLANT COMMUNICATIONS 2025; 6:101230. [PMID: 39722458 PMCID: PMC11897476 DOI: 10.1016/j.xplc.2024.101230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2024] [Revised: 12/04/2024] [Accepted: 12/20/2024] [Indexed: 12/28/2024]
Abstract
By integrating genomes from different accessions, pangenomes provide a more comprehensive and reference-bias-free representation of genetic information within a population compared to a single reference genome. With the rapid accumulation of genomic sequencing data and the expanding scope of plant research, plant pangenomics has gradually evolved from single-species to multi-species studies. This shift has given rise to the concept of a super-pangenome that covers all genomic sequences within a genus-level taxonomic group. By incorporating both cultivated and wild species, the super-pangenome has greatly enhanced the resolution of research in various areas such as plant genetic diversity, evolution, domestication, and molecular breeding. In this review, we present a comprehensive overview of the plant super-pangenome, emphasizing its development requirements, construction strategies, potential applications, and notable achievements. We also highlight the distinctive advantages and promising prospects of super-pangenomes while addressing current challenges and future directions.
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Affiliation(s)
- Wenchuang He
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - XiaoXia Li
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Qian Qian
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; Yazhouwan National Laboratory, Sanya 572024, China; State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, China; Academician Workstation, National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya 572024, China.
| | - Lianguang Shang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; Yazhouwan National Laboratory, Sanya 572024, China; Academician Workstation, National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya 572024, China.
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Sampaio JR, Oliveira WDDS, Nascimento FDS, Junior LCDS, Rebouças TA, Moreira RFC, Ramos APDS, dos Santos-Serejo JA, Amorim EP, Ferreira CF. Calcium-Binding Protein and Polymorphism in Musa spp. Somaclones Resistant to Fusarium oxysporum. Curr Issues Mol Biol 2024; 46:12119-12132. [PMID: 39590313 PMCID: PMC11593143 DOI: 10.3390/cimb46110719] [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: 10/02/2024] [Revised: 10/22/2024] [Accepted: 10/24/2024] [Indexed: 11/28/2024] Open
Abstract
The fresh fruits of 'Grande Naine' (Cavendish AAA-Musa spp.) dominate the world market, especially in countries with a population in a situation of social vulnerability. However, Fusarium wilt, caused by the fungus Fusarium oxysporum f.sp. cubense race 4 Subtropical (Foc ST4), emerges as a serious threat to banana production, requiring the development of resistant cultivars based on biotechnological strategies, such as the induction of mutation in tissue culture. This study aimed to identify and characterize genetic variation in somaclones resistant to Fusarium oxysporum f.sp. cubense subtropical race 4 (Foc ST4), derived from 'Grand Naine' bananas, by molecular markers based on retrotransposons IRAP (Inter-retrotransposon Amplified Polymorphism) and REMAP (Retrotransposon-Microsatellite Amplified Polymorphism). Nine combinations of IRAP and six combinations of REMAP primers were used. The low number of polymorphic bands did not allow for genetic diversity studies; however, ten polymorphic bands between the somaclones and control were sequenced. Of these, three presented good base calling and were aligned, namely, 1AF, 2AF, and 3AF bands. Only the 1AF band presented function related to stress response with homology to a calcium-binding protein. These proteins act early in plant infection as secondary messengers activated by pathogen-associated molecular patterns (PAMPs), initiating the cascade of plant defense signals. The fact that this band is present in all somaclones reinforces previous assessments of their resistance to Foc ST4. The use of markers IRAP and REMAP produced polymorphic bands that can, through future primer design and field validations, accelerate the identification of resistant banana genotypes for use in banana genetic breeding programs.
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Affiliation(s)
- Juliana Rodrigues Sampaio
- Department of Agricultural, Environmental and Biological Sciencies, Federal University of Recôncavo da Bahia, Rua Rui Barbosa, 710-Centro, Cruz das Almas 44380-000, BA, Brazil; (J.R.S.); (L.C.d.S.J.); (R.F.C.M.)
| | | | - Fernanda dos Santos Nascimento
- Embrapa Mandioca e Fruticultura, Rua Embrapa, s/no, Chapadinha, Cruz das Almas 44380-000, BA, Brazil; (F.d.S.N.); (T.A.R.); (A.P.d.S.R.); (J.A.d.S.-S.); (E.P.A.)
| | - Luiz Carlos de Souza Junior
- Department of Agricultural, Environmental and Biological Sciencies, Federal University of Recôncavo da Bahia, Rua Rui Barbosa, 710-Centro, Cruz das Almas 44380-000, BA, Brazil; (J.R.S.); (L.C.d.S.J.); (R.F.C.M.)
| | - Tamyres Amorim Rebouças
- Embrapa Mandioca e Fruticultura, Rua Embrapa, s/no, Chapadinha, Cruz das Almas 44380-000, BA, Brazil; (F.d.S.N.); (T.A.R.); (A.P.d.S.R.); (J.A.d.S.-S.); (E.P.A.)
| | - Ricardo Franco Cunha Moreira
- Department of Agricultural, Environmental and Biological Sciencies, Federal University of Recôncavo da Bahia, Rua Rui Barbosa, 710-Centro, Cruz das Almas 44380-000, BA, Brazil; (J.R.S.); (L.C.d.S.J.); (R.F.C.M.)
| | - Andresa Priscila de Souza Ramos
- Embrapa Mandioca e Fruticultura, Rua Embrapa, s/no, Chapadinha, Cruz das Almas 44380-000, BA, Brazil; (F.d.S.N.); (T.A.R.); (A.P.d.S.R.); (J.A.d.S.-S.); (E.P.A.)
| | - Janay Almeida dos Santos-Serejo
- Embrapa Mandioca e Fruticultura, Rua Embrapa, s/no, Chapadinha, Cruz das Almas 44380-000, BA, Brazil; (F.d.S.N.); (T.A.R.); (A.P.d.S.R.); (J.A.d.S.-S.); (E.P.A.)
| | - Edson Perito Amorim
- Embrapa Mandioca e Fruticultura, Rua Embrapa, s/no, Chapadinha, Cruz das Almas 44380-000, BA, Brazil; (F.d.S.N.); (T.A.R.); (A.P.d.S.R.); (J.A.d.S.-S.); (E.P.A.)
| | - Claudia Fortes Ferreira
- Embrapa Mandioca e Fruticultura, Rua Embrapa, s/no, Chapadinha, Cruz das Almas 44380-000, BA, Brazil; (F.d.S.N.); (T.A.R.); (A.P.d.S.R.); (J.A.d.S.-S.); (E.P.A.)
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Cui D, Xiong G, Ye L, Gornall R, Wang Z, Heslop-Harrison P, Liu Q. Genome-wide analysis of flavonoid biosynthetic genes in Musaceae ( Ensete, Musella, and Musa species) reveals amplification of flavonoid 3',5'-hydroxylase. AOB PLANTS 2024; 16:plae049. [PMID: 39450414 PMCID: PMC11500454 DOI: 10.1093/aobpla/plae049] [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: 01/23/2024] [Accepted: 09/09/2024] [Indexed: 10/26/2024]
Abstract
Flavonoids in Musaceae are involved in pigmentation and stress responses, including cold resistance, and are a component of the healthy human diet. Identification and analysis of the sequence and copy number of flavonoid biosynthetic genes are valuable for understanding the nature and diversity of flavonoid evolution in Musaceae species. In this study, we identified 71-80 flavonoid biosynthetic genes in chromosome-scale genome sequence assemblies of Musaceae, including those of Ensete glaucum, Musella lasiocarpa, Musa beccarii, M. acuminata, M. balbisiana and M. schizocarpa, checking annotations with BLAST and determining the presence of conserved domains. The number of genes increased through segmental duplication and tandem duplication. Orthologues of both structural and regulatory genes in the flavonoid biosynthetic pathway are highly conserved across Musaceae. The flavonoid 3',5'-hydroxylase gene F3'5'H was amplified in Musaceae and ginger compared with grasses (rice, Brachypodium, Avena longiglumis, and sorghum). One group of genes from this gene family amplified near the centromere of chromosome 2 in the x = 11 Musaceae species. Flavonoid biosynthetic genes displayed few consistent responses in the yellow and red bracts of Musella lasiocarpa when subjected to low temperatures. The expression levels of MlDFR2/3 (dihydroflavonol reductase) increased while MlLAR (leucoanthocyanidin reductase) was reduced by half. Overall, the results establish the range of diversity in both sequence and copy number of flavonoid biosynthetic genes during evolution of Musaceae. The combination of allelic variants of genes, changes in their copy numbers, and variation in transcription factors with the modulation of expression under cold treatments and between genotypes with contrasting bract-colours suggests the variation may be exploited in plant breeding programmes, particularly for improvement of stress-resistance in the banana crop.
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Affiliation(s)
- Dongli Cui
- Key Laboratory of National Forestry and Grassland Administration Plant Conservation and Utilization in Southern China/Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- South China National Botanical Garden, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- University of Chinese Academy of Sciences, Yuquan Road 19, Shijingshan District, Beijing 100049, China
| | - Gui Xiong
- Key Laboratory of National Forestry and Grassland Administration Plant Conservation and Utilization in Southern China/Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- South China National Botanical Garden, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- University of Chinese Academy of Sciences, Yuquan Road 19, Shijingshan District, Beijing 100049, China
| | - Lyuhan Ye
- Key Laboratory of National Forestry and Grassland Administration Plant Conservation and Utilization in Southern China/Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- South China National Botanical Garden, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- University of Chinese Academy of Sciences, Yuquan Road 19, Shijingshan District, Beijing 100049, China
| | - Richard Gornall
- University of Leicester, Department of Genetics and Genome Biology, Institute for Environmental Futures, University Road, Leicester LE1 7RH, UK
| | - Ziwei Wang
- Henry Fok School of Biology and Agriculture, Shaoguan University, University Road 288, Zhenjiang District, Shaoguan 512005, China
| | - Pat Heslop-Harrison
- Key Laboratory of National Forestry and Grassland Administration Plant Conservation and Utilization in Southern China/Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- University of Leicester, Department of Genetics and Genome Biology, Institute for Environmental Futures, University Road, Leicester LE1 7RH, UK
| | - Qing Liu
- Key Laboratory of National Forestry and Grassland Administration Plant Conservation and Utilization in Southern China/Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- South China National Botanical Garden, Xingke Road 723, Tianhe District, Guangzhou 510650, China
- State Key Laboratory of Plant Diversity and Specialty Crops, South China Botanical Garden, Chinese Academy of Sciences, Xingke Road 723, Tianhe District, Guangzhou 510650, China
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Matthews CA, Watson-Haigh NS, Burton RA, Sheppard AE. A gentle introduction to pangenomics. Brief Bioinform 2024; 25:bbae588. [PMID: 39552065 PMCID: PMC11570541 DOI: 10.1093/bib/bbae588] [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: 06/25/2024] [Revised: 09/12/2024] [Accepted: 11/01/2024] [Indexed: 11/19/2024] Open
Abstract
Pangenomes have emerged in response to limitations associated with traditional linear reference genomes. In contrast to a traditional reference that is (usually) assembled from a single individual, pangenomes aim to represent all of the genomic variation found in a group of organisms. The term 'pangenome' is currently used to describe multiple different types of genomic information, and limited language is available to differentiate between them. This is frustrating for researchers working in the field and confusing for researchers new to the field. Here, we provide an introduction to pangenomics relevant to both prokaryotic and eukaryotic organisms and propose a formalization of the language used to describe pangenomes (see the Glossary) to improve the specificity of discussion in the field.
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Affiliation(s)
- Chelsea A Matthews
- School of Agriculture, Food and Wine, Waite Campus, University of Adelaide, Urrbrae, South Australia 5064, Australia
| | - Nathan S Watson-Haigh
- Australian Genome Research Facility, Victorian Comprehensive Cancer Centre, Melbourne, Victoria 3000, Australia
- South Australian Genomics Centre, SAHMRI, North Terrace, Adelaide, South Australia 5000, Australia
- Alkahest Inc., San Carlos, CA 94070, United States
| | - Rachel A Burton
- School of Agriculture, Food and Wine, Waite Campus, University of Adelaide, Urrbrae, South Australia 5064, Australia
| | - Anna E Sheppard
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia
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Hu H, Li R, Zhao J, Batley J, Edwards D. Technological Development and Advances for Constructing and Analyzing Plant Pangenomes. Genome Biol Evol 2024; 16:evae081. [PMID: 38669452 PMCID: PMC11058698 DOI: 10.1093/gbe/evae081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 04/09/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
A pangenome captures the genomic diversity for a species, derived from a collection of genetic sequences of diverse populations. Advances in sequencing technologies have given rise to three primary methods for pangenome construction and analysis: de novo assembly and comparison, reference genome-based iterative assembly, and graph-based pangenome construction. Each method presents advantages and challenges in processing varying amounts and structures of DNA sequencing data. With the emergence of high-quality genome assemblies and advanced bioinformatic tools, the graph-based pangenome is emerging as an advanced reference for exploring the biological and functional implications of genetic variations.
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Affiliation(s)
- Haifei Hu
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangzhou 510640, China
| | - Risheng Li
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangzhou 510640, China
- College of Agriculture, South China Agricultural University, Guangzhou, Guangdong 510642, China
| | - Junliang Zhao
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangzhou 510640, China
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - David Edwards
- School of Biological Sciences, University of Western Australia, Perth, WA, Australia
- Centre for Applied Bioinformatics, University of Western Australia, Perth, WA 6009, Australia
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Hu H, Scheben A, Wang J, Li F, Li C, Edwards D, Zhao J. Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:544-554. [PMID: 37961986 PMCID: PMC10893937 DOI: 10.1111/pbi.14224] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/11/2023] [Accepted: 10/22/2023] [Indexed: 11/15/2023]
Abstract
Inversions, a type of chromosomal structural variation, significantly influence plant adaptation and gene functions by impacting gene expression and recombination rates. However, compared with other structural variations, their roles in functional biology and crop improvement remain largely unexplored. In this review, we highlight technological and methodological advancements that have allowed a comprehensive understanding of inversion variants through the pangenome framework and machine learning algorithms. Genome editing is an efficient method for inducing or reversing inversion mutations in plants, providing an effective mechanism to modify local recombination rates. Given the potential of inversions in crop breeding, we anticipate increasing attention on inversions from the scientific community in future research and breeding applications.
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Affiliation(s)
- Haifei Hu
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co‐construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering LaboratoryGuangzhouChina
| | - Armin Scheben
- Simons Center for Quantitative Biology, Cold Spring Harbor LaboratoryCold Spring HarborNew YorkUSA
| | - Jian Wang
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co‐construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering LaboratoryGuangzhouChina
| | - Fangping Li
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
| | - Chengdao Li
- Western Crop Genetics Alliance, Centre for Crop & Food Innovation, Food Futures Institute, College of Science, Health, Engineering and EducationMurdoch UniversityMurdochWestern AustraliaAustralia
| | - David Edwards
- School of Biological SciencesUniversity of Western AustraliaPerthWestern AustraliaAustralia
- Australia & Centre for Applied BioinformaticsUniversity of Western AustraliaPerthWestern AustraliaAustralia
| | - Junliang Zhao
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co‐construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering LaboratoryGuangzhouChina
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9
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Della Coletta R, Fernandes SB, Monnahan PJ, Mikel MA, Bohn MO, Lipka AE, Hirsch CN. Importance of genetic architecture in marker selection decisions for genomic prediction. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:220. [PMID: 37819415 DOI: 10.1007/s00122-023-04469-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 09/25/2023] [Indexed: 10/13/2023]
Abstract
KEY MESSAGE We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait. Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.
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Affiliation(s)
- Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Samuel B Fernandes
- Department of Crop, Soil and Environmental Sciences at University of Arkansas, Fayetteville, AR, 72701, USA
| | - Patrick J Monnahan
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Mark A Mikel
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Martin O Bohn
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
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10
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Song B, Ning W, Wei D, Jiang M, Zhu K, Wang X, Edwards D, Odeny DA, Cheng S. Plant genome resequencing and population genomics: Current status and future prospects. MOLECULAR PLANT 2023; 16:1252-1268. [PMID: 37501370 DOI: 10.1016/j.molp.2023.07.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023]
Abstract
Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.
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Affiliation(s)
- Bo Song
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Weidong Ning
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; Huazhong Agricultural University, College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Wuhan, Hubei, China
| | - Di Wei
- Biotechnology Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 53007, China
| | - Mengyun Jiang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Kun Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Xingwei Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Damaris A Odeny
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) - Eastern and Southern Africa, Nairobi, Kenya
| | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
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11
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Ruperao P, Rangan P, Shah T, Thakur V, Kalia S, Mayes S, Rathore A. The Progression in Developing Genomic Resources for Crop Improvement. Life (Basel) 2023; 13:1668. [PMID: 37629524 PMCID: PMC10455509 DOI: 10.3390/life13081668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/21/2023] [Accepted: 07/25/2023] [Indexed: 08/27/2023] Open
Abstract
Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques.
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Affiliation(s)
- Pradeep Ruperao
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Parimalan Rangan
- ICAR-National Bureau of Plant Genetic Resources, PUSA Campus, New Delhi 110012, India;
| | - Trushar Shah
- International Institute of Tropical Agriculture (IITA), Nairobi 30709-00100, Kenya;
| | - Vivek Thakur
- Department of Systems & Computational Biology, School of Life Sciences, University of Hyderabad, Hyderabad 500046, India;
| | - Sanjay Kalia
- Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi 110003, India;
| | - Sean Mayes
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502324, India
| | - Abhishek Rathore
- Excellence in Breeding, International Maize and Wheat Improvement Center (CIMMYT), Hyderabad 502324, India
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12
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Sinha D, Maurya AK, Abdi G, Majeed M, Agarwal R, Mukherjee R, Ganguly S, Aziz R, Bhatia M, Majgaonkar A, Seal S, Das M, Banerjee S, Chowdhury S, Adeyemi SB, Chen JT. Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals. Genes (Basel) 2023; 14:1484. [PMID: 37510388 PMCID: PMC10380062 DOI: 10.3390/genes14071484] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.
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Affiliation(s)
- Dwaipayan Sinha
- Department of Botany, Government General Degree College, Mohanpur 721436, India
| | - Arun Kumar Maurya
- Department of Botany, Multanimal Modi College, Modinagar, Ghaziabad 201204, India
| | - Gholamreza Abdi
- Department of Biotechnology, Persian Gulf Research Institute, Persian Gulf University, Bushehr 75169, Iran
| | - Muhammad Majeed
- Department of Botany, University of Gujrat, Punjab 50700, Pakistan
| | - Rachna Agarwal
- Applied Genomics Section, Bhabha Atomic Research Centre, Mumbai 400085, India
| | - Rashmi Mukherjee
- Research Center for Natural and Applied Sciences, Department of Botany (UG & PG), Raja Narendralal Khan Women's College, Gope Palace, Midnapur 721102, India
| | - Sharmistha Ganguly
- Department of Dravyaguna, Institute of Post Graduate Ayurvedic Education and Research, Kolkata 700009, India
| | - Robina Aziz
- Department of Botany, Government, College Women University, Sialkot 51310, Pakistan
| | - Manika Bhatia
- TERI School of Advanced Studies, New Delhi 110070, India
| | - Aqsa Majgaonkar
- Department of Botany, St. Xavier's College (Autonomous), Mumbai 400001, India
| | - Sanchita Seal
- Department of Botany, Polba Mahavidyalaya, Polba 712148, India
| | - Moumita Das
- V. Sivaram Research Foundation, Bangalore 560040, India
| | - Swastika Banerjee
- Department of Botany, Kairali College of +3 Science, Champua, Keonjhar 758041, India
| | - Shahana Chowdhury
- Department of Biotechnology, Faculty of Engineering Sciences, German University Bangladesh, TNT Road, Telipara, Chandona Chowrasta, Gazipur 1702, Bangladesh
| | - Sherif Babatunde Adeyemi
- Ethnobotany/Phytomedicine Laboratory, Department of Plant Biology, Faculty of Life Sciences, University of Ilorin, Ilorin P.M.B 1515, Nigeria
| | - Jen-Tsung Chen
- Department of Life Sciences, National University of Kaohsiung, Kaohsiung 811, Taiwan
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13
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Chen A, Sun J, Viljoen A, Mostert D, Xie Y, Mangila L, Bothma S, Lyons R, Hřibová E, Christelová P, Uwimana B, Amah D, Pearce S, Chen N, Batley J, Edwards D, Doležel J, Crisp P, Brown AF, Martin G, Yahiaoui N, D'Hont A, Coin L, Swennen R, Aitken EAB. Genetic Mapping, Candidate Gene Identification and Marker Validation for Host Plant Resistance to the Race 4 of Fusarium oxysporum f. sp. cubense Using Musa acuminata ssp. malaccensis. Pathogens 2023; 12:820. [PMID: 37375510 PMCID: PMC10303076 DOI: 10.3390/pathogens12060820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 06/04/2023] [Accepted: 06/07/2023] [Indexed: 06/29/2023] Open
Abstract
Fusarium wilt of banana is a devastating disease that has decimated banana production worldwide. Host resistance to Fusarium oxysporum f. sp. Cubense (Foc), the causal agent of this disease, is genetically dissected in this study using two Musa acuminata ssp. Malaccensis segregating populations, segregating for Foc Tropical (TR4) and Subtropical (STR4) race 4 resistance. Marker loci and trait association using 11 SNP-based PCR markers allowed the candidate region to be delimited to a 12.9 cM genetic interval corresponding to a 959 kb region on chromosome 3 of 'DH-Pahang' reference assembly v4. Within this region, there was a cluster of pattern recognition receptors, namely leucine-rich repeat ectodomain containing receptor-like protein kinases, cysteine-rich cell-wall-associated protein kinases, and leaf rust 10 disease-resistance locus receptor-like proteins, positioned in an interspersed arrangement. Their transcript levels were rapidly upregulated in the resistant progenies but not in the susceptible F2 progenies at the onset of infection. This suggests that one or several of these genes may control resistance at this locus. To confirm the segregation of single-gene resistance, we generated an inter-cross between the resistant parent 'Ma850' and a susceptible line 'Ma848', to show that the STR4 resistance co-segregated with marker '28820' at this locus. Finally, an informative SNP marker 29730 allowed the locus-specific resistance to be assessed in a collection of diploid and polyploid banana plants. Of the 60 lines screened, 22 lines were predicted to carry resistance at this locus, including lines known to be TR4-resistant, such as 'Pahang', 'SH-3362', 'SH-3217', 'Ma-ITC0250', and 'DH-Pahang/CIRAD 930'. Additional screening in the International Institute for Tropical Agriculture's collection suggests that the dominant allele is common among the elite 'Matooke' NARITA hybrids, as well as in other triploid or tetraploid hybrids derived from East African highland bananas. Fine mapping and candidate gene identification will allow characterization of molecular mechanisms underlying the TR4 resistance. The markers developed in this study can now aid the marker-assisted selection of TR4 resistance in breeding programs around the world.
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Affiliation(s)
- Andrew Chen
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Jiaman Sun
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
- School of Life Science, Jiaying University, Meizhou 514015, China
| | - Altus Viljoen
- Department of Plant Pathology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Diane Mostert
- Department of Plant Pathology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Yucong Xie
- Department of Biology, Duke University, Durham, NC 27708-0338, USA
| | - Leroy Mangila
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Sheryl Bothma
- Department of Plant Pathology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Rebecca Lyons
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Eva Hřibová
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of the Region Haná for Bio-Technological and Agricultural Research, CZ-77900 Olomouc, Czech Republic
| | - Pavla Christelová
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of the Region Haná for Bio-Technological and Agricultural Research, CZ-77900 Olomouc, Czech Republic
| | - Brigitte Uwimana
- International Institute of Tropical Agriculture, Kampala P.O. Box 7878, Uganda
| | - Delphine Amah
- International Institute of Tropical Agriculture, Ibadan PMB 5320, Nigeria
| | - Stephen Pearce
- Sustainable Soils and Crops, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK
| | - Ning Chen
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Jacqueline Batley
- School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia
| | - David Edwards
- School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia
- The Centre for Applied Bioinformatics, University of Western Australia, Crawley, Perth, WA 6009, Australia
| | - Jaroslav Doležel
- Institute of Experimental Botany of the Czech Academy of Sciences, Centre of the Region Haná for Bio-Technological and Agricultural Research, CZ-77900 Olomouc, Czech Republic
| | - Peter Crisp
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Allan F Brown
- International Institute of Tropical Agriculture, Arusha P.O. Box 447, Tanzania
| | - Guillaume Martin
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Université de Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Nabila Yahiaoui
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Université de Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Angelique D'Hont
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Université de Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Lachlan Coin
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3004, Australia
| | - Rony Swennen
- International Institute of Tropical Agriculture, Kampala P.O. Box 7878, Uganda
- Division of Crop Biotechnics, Laboratory of Tropical Crop Improvement, Katholieke Universiteit Leuven, 3001 Leuven, Belgium
| | - Elizabeth A B Aitken
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
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14
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Neik TX, Siddique KHM, Mayes S, Edwards D, Batley J, Mabhaudhi T, Song BK, Massawe F. Diversifying agrifood systems to ensure global food security following the Russia–Ukraine crisis. FRONTIERS IN SUSTAINABLE FOOD SYSTEMS 2023. [DOI: 10.3389/fsufs.2023.1124640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023] Open
Abstract
The recent Russia–Ukraine conflict has raised significant concerns about global food security, leaving many countries with restricted access to imported staple food crops, particularly wheat and sunflower oil, sending food prices soaring with other adverse consequences in the food supply chain. This detrimental effect is particularly prominent for low-income countries relying on grain imports, with record-high food prices and inflation affecting their livelihoods. This review discusses the role of Russia and Ukraine in the global food system and the impact of the Russia–Ukraine conflict on food security. It also highlights how diversifying four areas of agrifood systems—markets, production, crops, and technology can contribute to achieving food supply chain resilience for future food security and sustainability.
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15
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Nawae W, Naktang C, Charoensri S, U-thoomporn S, Narong N, Chusri O, Tangphatsornruang S, Pootakham W. Resequencing of durian genomes reveals large genetic variations among different cultivars. FRONTIERS IN PLANT SCIENCE 2023; 14:1137077. [PMID: 36875624 PMCID: PMC9978785 DOI: 10.3389/fpls.2023.1137077] [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: 01/04/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Durian (Durio zibethinus), which yields the fruit known as the "King of Fruits," is an important economic crop in Southeast Asia. Several durian cultivars have been developed in this region. In this study, we resequenced the genomes of three popular durian cultivars in Thailand, including Kradumthong (KD), Monthong (MT), and Puangmanee (PM) to investigate genetic diversities of cultivated durians. KD, MT, and PM genome assemblies were 832.7, 762.6, and 821.6 Mb, and their annotations covered 95.7, 92.4, and 92.7% of the embryophyta core proteins, respectively. We constructed the draft durian pangenome and analyzed comparative genomes with related species in Malvales. Long terminal repeat (LTR) sequences and protein families in durian genomes had slower evolution rates than that in cotton genomes. However, protein families with transcriptional regulation function and protein phosphorylation function involved in abiotic and biotic stress responses appeared to evolve faster in durians. The analyses of phylogenetic relationships, copy number variations (CNVs), and presence/absence variations (PAVs) suggested that the genome evolution of Thai durians was different from that of the Malaysian durian, Musang King (MK). Among the three newly sequenced genomes, the PAV and CNV profiles of disease resistance genes and the expressions of methylesterase inhibitor domain containing genes involved in flowering and fruit maturation in MT were different from those in KD and PM. These genome assemblies and their analyses provide valuable resources to gain a better understanding of the genetic diversity of cultivated durians, which may be useful for the future development of new durian cultivars.
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Affiliation(s)
- Wanapinun Nawae
- National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani, Thailand
| | - Chaiwat Naktang
- National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani, Thailand
| | - Salisa Charoensri
- National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani, Thailand
| | - Sonicha U-thoomporn
- National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani, Thailand
| | - Nattapol Narong
- National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani, Thailand
| | - Orwintinee Chusri
- Chantaburi Horticulture Research Center, Horticulture Research Institute, Department of Agriculture, Chantaburi, Thailand
| | - Sithichoke Tangphatsornruang
- National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani, Thailand
| | - Wirulda Pootakham
- National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani, Thailand
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16
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Chen A, Sun J, Martin G, Gray LA, Hřibová E, Christelová P, Yahiaoui N, Rounsley S, Lyons R, Batley J, Chen N, Hamill S, Rai SK, Coin L, Uwimana B, D’Hont A, Doležel J, Edwards D, Swennen R, Aitken EAB. Identification of a Major QTL-Controlling Resistance to the Subtropical Race 4 of Fusarium oxysporum f. sp. cubense in Musa acuminata ssp. malaccensis. Pathogens 2023; 12:pathogens12020289. [PMID: 36839561 PMCID: PMC9964652 DOI: 10.3390/pathogens12020289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 02/12/2023] Open
Abstract
Vascular wilt caused by the ascomycete fungal pathogen Fusarium oxysporum f. sp. cubense (Foc) is a major constraint of banana production around the world. The virulent race, namely Tropical Race 4, can infect all Cavendish-type banana plants and is now widespread across the globe, causing devastating losses to global banana production. In this study, we characterized Foc Subtropical Race 4 (STR4) resistance in a wild banana relative which, through estimated genome size and ancestry analysis, was confirmed to be Musa acuminata ssp. malaccensis. Using a self-derived F2 population segregating for STR4 resistance, quantitative trait loci sequencing (QTL-seq) was performed on bulks consisting of resistant and susceptible individuals. Changes in SNP index between the bulks revealed a major QTL located on the distal end of the long arm of chromosome 3. Multiple resistance genes are present in this region. Identification of chromosome regions conferring resistance to Foc can facilitate marker assisted selection in breeding programs and paves the way towards identifying genes underpinning resistance.
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Affiliation(s)
- Andrew Chen
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
- Correspondence:
| | - Jiaman Sun
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
- School of Life Science, Jiaying University, Meizhou 514015, China
| | - Guillaume Martin
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Lesley-Ann Gray
- Australian Genome Research Facility, Victorian Comprehensive Cancer Centre, Melbourne, VIC 3000, Australia
| | - Eva Hřibová
- Centre of the Region Haná for Biotechnological and Agricultural Research, Institute of Experimental Botany of the Czech Academy of Sciences, 77200 Olomouc, Czech Republic
| | - Pavla Christelová
- Centre of the Region Haná for Biotechnological and Agricultural Research, Institute of Experimental Botany of the Czech Academy of Sciences, 77200 Olomouc, Czech Republic
| | - Nabila Yahiaoui
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | | | - Rebecca Lyons
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Jacqueline Batley
- School of Biological Sciences, The University of Western Australia, Perth, WA 6907, Australia
| | - Ning Chen
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Sharon Hamill
- Department of Agriculture and Fisheries, Maroochy Research Facility, Nambour, QLD 4560, Australia
| | - Subash K. Rai
- Genome Innovation Hub, University of Queensland, Brisbane, QLD 4072, Australia
| | - Lachlan Coin
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3004, Australia
| | - Brigitte Uwimana
- International Institute of Tropical Agriculture, Kampala P.O. Box 7878, Uganda
| | - Angelique D’Hont
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Jaroslav Doležel
- Centre of the Region Haná for Biotechnological and Agricultural Research, Institute of Experimental Botany of the Czech Academy of Sciences, 77200 Olomouc, Czech Republic
| | - David Edwards
- School of Biological Sciences, The University of Western Australia, Perth, WA 6907, Australia
| | - Rony Swennen
- International Institute of Tropical Agriculture, Kampala P.O. Box 7878, Uganda
- Laboratory of Tropical Crop Improvement, Division of Crop Biotechnics, Katholieke Universiteit Leuven, 3001 Leuven, Belgium
| | - Elizabeth A. B. Aitken
- School of Agriculture and Food Science, The University of Queensland, Brisbane, QLD 4067, Australia
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17
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Gui S, Martinez-Rivas FJ, Wen W, Meng M, Yan J, Usadel B, Fernie AR. Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 113:446-459. [PMID: 36534120 DOI: 10.1111/tpj.16070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.
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Affiliation(s)
- Songtao Gui
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | | | - Weiwei Wen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Minghui Meng
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Björn Usadel
- IBG-4 Bioinformatics, Forschungszentrum Jülich, Wilhelm Johnen Str, BioSc, 52428, Jülich, Germany
- Institute for Biological Data Science, CEPLAS, Heinrich Heine University, 40225, Düsseldorf, Germany
| | - Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, Potsdam-Golm, 14476, Germany
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18
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Wang J, Yang W, Zhang S, Hu H, Yuan Y, Dong J, Chen L, Ma Y, Yang T, Zhou L, Chen J, Liu B, Li C, Edwards D, Zhao J. A pangenome analysis pipeline provides insights into functional gene identification in rice. Genome Biol 2023; 24:19. [PMID: 36703158 PMCID: PMC9878884 DOI: 10.1186/s13059-023-02861-9] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 01/18/2023] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND A pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, bioinformatics analysis tools for graph format genomes are lacking. RESULTS To overcome this problem, we develop a novel strategy for pangenome construction and a downstream pangenome analysis pipeline (PSVCP) that captures genetic variants' position information while maintaining a linearized layout. Using PSVCP, we construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome as the reference. We show that PSVCP successfully identifies causal structural variations for rice grain weight and plant height. Our results provide insights into rice population structure and genomic diversity. We characterize a new locus (qPH8-1) associated with plant height on chromosome 8 undetected by the SNP-based genome-wide association study (GWAS). CONCLUSIONS Our results demonstrate that the pangenome constructed by our pipeline combined with a presence and absence variation-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and the associated genome sequence and genetic variants data provide valuable genomic resources for rice genomics research and improvement in future.
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Affiliation(s)
- Jian Wang
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Wu Yang
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Shaohong Zhang
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Haifei Hu
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China.
- Western Crop Genetics Alliance, Murdoch University, Murdoch, Western Australia, 6150, Australia.
| | - Yuxuan Yuan
- School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Jingfang Dong
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Luo Chen
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Yamei Ma
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Tifeng Yang
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Lian Zhou
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Jiansong Chen
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Bin Liu
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China
| | - Chengdao Li
- Western Crop Genetics Alliance, Murdoch University, Murdoch, Western Australia, 6150, Australia.
| | - David Edwards
- School of Biological Sciences and Centre for Applied Bioinformatics, University of Western Australia, Perth, WA, Australia.
| | - Junliang Zhao
- Rice Research Institute & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong Academy of Agricultural Sciences, Guangzhou, 510640, China.
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19
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Bayer PE, Edwards D. Investigating Pangenome Graphs Using Wheat Panache. Methods Mol Biol 2023; 2703:23-29. [PMID: 37646934 DOI: 10.1007/978-1-0716-3389-2_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Pangenome graphs quickly become the central data structure representing the diversity of variation we see across related genomes. Pangenome graphs have been published for some species, including plants of agronomic interest. However, visualizing these graphs is not easy as the graphs are large, and variants within these graphs are complex. Tools are needed to visualize graph data structures. Here, we present a workflow to search and visualize a wheat pangenome graph using Wheat Panache. The approach presented assists researchers interested in wheat genomics.
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Affiliation(s)
- Philipp E Bayer
- Centre for Applied Bioinformatics and School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - David Edwards
- Centre for Applied Bioinformatics and School of Biological Sciences, The University of Western Australia, Perth, WA, Australia.
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20
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Dolatabadian A, Yuan Y, Bayer PE, Petereit J, Severn-Ellis A, Tirnaz S, Patel D, Edwards D, Batley J. Copy Number Variation among Resistance Genes Analogues in Brassica napus. Genes (Basel) 2022; 13:2037. [PMID: 36360273 PMCID: PMC9690292 DOI: 10.3390/genes13112037] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 10/26/2022] [Accepted: 10/31/2022] [Indexed: 10/31/2024] Open
Abstract
Copy number variations (CNVs) are defined as deletions, duplications and insertions among individuals of a species. There is growing evidence that CNV is a major factor underlining various autoimmune disorders and diseases in humans; however, in plants, especially oilseed crops, the role of CNVs in disease resistance is not well studied. Here, we investigate the genome-wide diversity and genetic properties of CNVs in resistance gene analogues (RGAs) across eight Brassica napus lines. A total of 1137 CNV events (704 deletions and 433 duplications) were detected across 563 RGAs. The results show CNVs are more likely to occur across clustered RGAs compared to singletons. In addition, 112 RGAs were linked to a blackleg resistance QTL, of which 25 were affected by CNV. Overall, we show that the presence and abundance of CNVs differ between lines, suggesting that in B. napus, the distribution of CNVs depends on genetic background. Our findings advance the understanding of CNV as an important type of genomic structural variation in B. napus and provide a resource to support breeding of advanced canola lines.
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Affiliation(s)
- Aria Dolatabadian
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - Yuxuan Yuan
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Philipp Emanuel Bayer
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - Jakob Petereit
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - Anita Severn-Ellis
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - Soodeh Tirnaz
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - Dhwani Patel
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - David Edwards
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - Jacqueline Batley
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
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21
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Droc G, Martin G, Guignon V, Summo M, Sempéré G, Durant E, Soriano A, Baurens FC, Cenci A, Breton C, Shah T, Aury JM, Ge XJ, Harrison PH, Yahiaoui N, D’Hont A, Rouard M. The banana genome hub: a community database for genomics in the Musaceae. HORTICULTURE RESEARCH 2022; 9:uhac221. [PMID: 36479579 PMCID: PMC9720444 DOI: 10.1093/hr/uhac221] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 09/22/2022] [Indexed: 06/17/2023]
Abstract
The Banana Genome Hub provides centralized access for genome assemblies, annotations, and the extensive related omics resources available for bananas and banana relatives. A series of tools and unique interfaces are implemented to harness the potential of genomics in bananas, leveraging the power of comparative analysis, while recognizing the differences between datasets. Besides effective genomic tools like BLAST and the JBrowse genome browser, additional interfaces enable advanced gene search and gene family analyses including multiple alignments and phylogenies. A synteny viewer enables the comparison of genome structures between chromosome-scale assemblies. Interfaces for differential expression analyses, metabolic pathways and GO enrichment were also added. A catalogue of variants spanning the banana diversity is made available for exploration, filtering, and export to a wide variety of software. Furthermore, we implemented new ways to graphically explore gene presence-absence in pangenomes as well as genome ancestry mosaics for cultivated bananas. Besides, to guide the community in future sequencing efforts, we provide recommendations for nomenclature of locus tags and a curated list of public genomic resources (assemblies, resequencing, high density genotyping) and upcoming resources-planned, ongoing or not yet public. The Banana Genome Hub aims at supporting the banana scientific community for basic, translational, and applied research and can be accessed at https://banana-genome-hub.southgreen.fr.
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Affiliation(s)
| | - Guillaume Martin
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
| | - Valentin Guignon
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier, France
| | - Marilyne Summo
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
| | - Guilhem Sempéré
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- CIRAD, UMR INTERTRYP, F-34398 Montpellier, France
- INTERTRYP, Université de Montpellier, CIRAD, IRD, 34398 Montpellier, France
| | - Eloi Durant
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Syngenta Seeds SAS, Saint-Sauveur, 31790, France
- DIADE, Univ Montpellier, CIRAD, IRD, Montpellier, 34830, France
| | - Alexandre Soriano
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
| | - Franc-Christophe Baurens
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Alberto Cenci
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier, France
| | - Catherine Breton
- French Institute of Bioinformatics (IFB) - South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France
- Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier, France
| | | | - Jean-Marc Aury
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 2 rue Gaston Crémieux, 91057 Evry, France
| | - Xue-Jun Ge
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510520, China
- Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Guangzhou 510520, China
| | - Pat Heslop Harrison
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510520, China
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK
| | - Nabila Yahiaoui
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Angélique D’Hont
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
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22
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Bayer PE, Petereit J, Durant É, Monat C, Rouard M, Hu H, Chapman B, Li C, Cheng S, Batley J, Edwards D. Wheat Panache: A pangenome graph database representing presence-absence variation across sixteen bread wheat genomes. THE PLANT GENOME 2022; 15:e20221. [PMID: 35644986 DOI: 10.1002/tpg2.20221] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 04/11/2022] [Indexed: 06/15/2023]
Abstract
Bread wheat (Triticum aestivum L.) is one of humanity's most important staple crops, characterized by a large and complex genome with a high level of gene presence-absence variation (PAV) between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high-quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate because of the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess PAV between bread wheat genomes.
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Affiliation(s)
- Philipp E Bayer
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
| | - Jakob Petereit
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
| | - Éloi Durant
- DIADE, Univ. of Montpellier, CIRAD, IRD, Montpellier, 34830, France
- Syngenta Seeds S.A.S., 12 chemin de l'Hobit, Saint-Sauveur, 31790, France
- Bioversity International, Parc Scientifique Agropolis II, Montpellier, 34397, France
- French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, 34398, France
| | - Cécile Monat
- Syngenta Seeds S.A.S., 12 chemin de l'Hobit, Saint-Sauveur, 31790, France
| | - Mathieu Rouard
- Bioversity International, Parc Scientifique Agropolis II, Montpellier, 34397, France
- French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, 34398, France
| | - Haifei Hu
- Western Crop Genetics Alliance, Murdoch Univ., 90 South Street, Murdoch, 6150, Australia
| | - Brett Chapman
- Western Crop Genetics Alliance, Murdoch Univ., 90 South Street, Murdoch, 6150, Australia
| | - Chengdao Li
- Western Crop Genetics Alliance, Murdoch Univ., 90 South Street, Murdoch, 6150, Australia
| | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Jacqueline Batley
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
| | - David Edwards
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
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23
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Li Z, Wang J, Fu Y, Jing Y, Huang B, Chen Y, Wang Q, Wang XB, Meng C, Yang Q, Xu L. The Musa troglodytarum L. genome provides insights into the mechanism of non-climacteric behaviour and enrichment of carotenoids. BMC Biol 2022; 20:186. [PMID: 36002843 PMCID: PMC9400310 DOI: 10.1186/s12915-022-01391-3] [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: 12/08/2021] [Accepted: 08/15/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Karat (Musa troglodytarum L.) is an autotriploid Fe'i banana of the Australimusa section. Karat was domesticated independently in the Pacific region, and karat fruit are characterized by a pink sap, a deep yellow-orange flesh colour, and an abundance of β-carotene. Karat fruit showed non-climacteric behaviour, with an approximately 215-day bunch filling time. These features make karat a valuable genetic resource for studying the mechanisms underlying fruit development and ripening and carotenoid biosynthesis. RESULTS Here, we report the genome of M. troglodytarum, which has a total length of 603 Mb and contains 37,577 predicted protein-coding genes. After divergence from the most recent common ancestors, M. troglodytarum (T genome) has experienced fusion of ancestral chromosomes 8 and 9 and multiple translocations and inversions, unlike the high synteny with few rearrangements found among M. schizocarpa (S genome), M. acuminata (A genome) and M. balbisiana (B genome). Genome microsynteny analysis showed that the triplication of MtSSUIIs due to chromosome rearrangement may lead to the accumulation of carotenoids and ABA in the fruit. The expression of duplicated MtCCD4s is repressed during ripening, leading to the accumulation of α-carotene, β-carotene and phytoene. Due to a long terminal repeat (LTR)-like fragment insertion upstream of MtERF11, karat cannot produce large amounts of ethylene but can produce ABA during ripening. These lead to non-climacteric behaviour and prolonged shelf-life, which contributes to an enrichment of carotenoids and riboflavin. CONCLUSIONS The high-quality genome of M. troglodytarum revealed the genomic basis of non-climacteric behaviour and enrichment of carotenoids, riboflavin, flavonoids and free galactose and provides valuable resources for further research on banana domestication and breeding and the improvement of nutritional and bioactive qualities.
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Affiliation(s)
- Zhiying Li
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Jiabin Wang
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Yunliu Fu
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Yonglin Jing
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Bilan Huang
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Ying Chen
- grid.428986.90000 0001 0373 6302College of Horticulture and Landscape Architecture, Hainan University, Haikou, 570228 China
| | - Qinglong Wang
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China
| | - Xiao Bing Wang
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Chunyang Meng
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Qingquan Yang
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
| | - Li Xu
- grid.453499.60000 0000 9835 1415Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou, 571737 Hainan China ,Ministry of Agriculture Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Danzhou, 571737 Hainan China ,Hainan Province Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation, Danzhou, 571737 Hainan China ,National Gene Bank of Tropical Crops, Danzhou, 571700 Hainan China
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24
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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.
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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
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25
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Taheri S, Teo CH, Heslop-Harrison JS, Schwarzacher T, Tan YS, Wee WY, Khalid N, Biswas MK, Mutha NVR, Mohd-Yusuf Y, Gan HM, Harikrishna JA. Genome Assembly and Analysis of the Flavonoid and Phenylpropanoid Biosynthetic Pathways in Fingerroot Ginger ( Boesenbergia rotunda). Int J Mol Sci 2022; 23:7269. [PMID: 35806276 PMCID: PMC9266397 DOI: 10.3390/ijms23137269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 06/20/2022] [Accepted: 06/27/2022] [Indexed: 01/27/2023] Open
Abstract
Boesenbergia rotunda (Zingiberaceae), is a high-value culinary and ethno-medicinal plant of Southeast Asia. The rhizomes of this herb have a high flavanone and chalcone content. Here we report the genome analysis of B. rotunda together with a complete genome sequence as a hybrid assembly. B. rotunda has an estimated genome size of 2.4 Gb which is assembled as 27,491 contigs with an N50 size of 12.386 Mb. The highly heterozygous genome encodes 71,072 protein-coding genes and has a 72% repeat content, with class I TEs occupying ~67% of the assembled genome. Fluorescence in situ hybridization of the 18 chromosome pairs at the metaphase showed six sites of 45S rDNA and two sites of 5S rDNA. An SSR analysis identified 238,441 gSSRs and 4604 EST-SSRs with 49 SSR markers common among related species. Genome-wide methylation percentages ranged from 73% CpG, 36% CHG and 34% CHH in the leaf to 53% CpG, 18% CHG and 25% CHH in the embryogenic callus. Panduratin A biosynthetic unigenes were most highly expressed in the watery callus. B rotunda has a relatively large genome with a high heterozygosity and TE content. This assembly and data (PRJNA71294) comprise a source for further research on the functional genomics of B. rotunda, the evolution of the ginger plant family and the potential genetic selection or improvement of gingers.
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Affiliation(s)
- Sima Taheri
- Centre for Research in Biotechnology for Agriculture, University of Malaya, Kuala Lumpur 50603, Malaysia; (S.T.); (C.H.T.); (Y.M.-Y.)
| | - Chee How Teo
- Centre for Research in Biotechnology for Agriculture, University of Malaya, Kuala Lumpur 50603, Malaysia; (S.T.); (C.H.T.); (Y.M.-Y.)
| | - John S. Heslop-Harrison
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK; (T.S.); (M.K.B.)
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization/Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
| | - Trude Schwarzacher
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK; (T.S.); (M.K.B.)
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization/Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
| | - Yew Seong Tan
- Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia;
| | - Wei Yee Wee
- School of Science, Monash University Malaysia, Subang Jaya 47500, Malaysia;
| | - Norzulaani Khalid
- Department of Biology, International University of Malaya-Wales, Kuala Lumpur 50603, Malaysia;
| | - Manosh Kumar Biswas
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, UK; (T.S.); (M.K.B.)
| | - Naresh V. R. Mutha
- Division of Infectious Diseases, Vanderbilt University Medical Center, Nashville, TN 37203, USA;
| | - Yusmin Mohd-Yusuf
- Centre for Research in Biotechnology for Agriculture, University of Malaya, Kuala Lumpur 50603, Malaysia; (S.T.); (C.H.T.); (Y.M.-Y.)
- Biology Division, Centre for Foundation Studies in Science, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Han Ming Gan
- Department of Biological Sciences, Sunway University, Bandar Sunway, Petaling Jaya 47500, Malaysia;
| | - Jennifer Ann Harikrishna
- Centre for Research in Biotechnology for Agriculture, University of Malaya, Kuala Lumpur 50603, Malaysia; (S.T.); (C.H.T.); (Y.M.-Y.)
- Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia;
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26
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Petereit J, Marsh JI, Bayer PE, Danilevicz MF, Thomas WJW, Batley J, Edwards D. Genetic and Genomic Resources for Soybean Breeding Research. PLANTS (BASEL, SWITZERLAND) 2022; 11:1181. [PMID: 35567182 PMCID: PMC9101001 DOI: 10.3390/plants11091181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 11/17/2022]
Abstract
Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop improvement.
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Affiliation(s)
| | - Jacob I. Marsh
- School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia; (J.P.); (J.I.M.); (P.E.B.); (M.F.D.); (W.J.W.T.); (J.B.)
| | | | | | | | | | - David Edwards
- School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia; (J.P.); (J.I.M.); (P.E.B.); (M.F.D.); (W.J.W.T.); (J.B.)
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27
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Fu N, Ji M, Rouard M, Yan HF, Ge XJ. Comparative plastome analysis of Musaceae and new insights into phylogenetic relationships. BMC Genomics 2022; 23:223. [PMID: 35313810 PMCID: PMC8939231 DOI: 10.1186/s12864-022-08454-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 03/08/2022] [Indexed: 01/16/2023] Open
Abstract
Background Musaceae is an economically important family consisting of 70-80 species. Elucidation of the interspecific relationships of this family is essential for a more efficient conservation and utilization of genetic resources for banana improvement. However, the scarcity of herbarium specimens and quality molecular markers have limited our understanding of the phylogenetic relationships in wild species of Musaceae. Aiming at improving the phylogenetic resolution of Musaceae, we analyzed a comprehensive set of 49 plastomes for 48 species/subspecies representing all three genera of this family. Results Musaceae plastomes have a relatively well-conserved genomic size and gene content, with a full length ranging from 166,782 bp to 172,514 bp. Variations in the IR borders were found to show phylogenetic signals to a certain extent in Musa. Codon usage bias analysis showed different preferences for the same codon between species and three genera and a common preference for A/T-ending codons. Among the two genes detected under positive selection (dN/dS > 1), ycf2 was indicated under an intensive positive selection. The divergent hotspot analysis allowed the identification of four regions (ndhF-trnL, ndhF, matK-rps16, and accD) as specific DNA barcodes for Musaceae species. Bayesian and maximum likelihood phylogenetic analyses using full plastome resulted in nearly identical tree topologies with highly supported relationships between species. The monospecies genus Musella is sister to Ensete, and the genus Musa was divided into two large clades, which corresponded well to the basic number of n = x = 11 and n = x =10/9/7, respectively. Four subclades were divided within the genus Musa. A dating analysis covering the whole Zingiberales indicated that the divergence of Musaceae family originated in the Palaeocene (59.19 Ma), and the genus Musa diverged into two clades in the Eocene (50.70 Ma) and then started to diversify from the late Oligocene (29.92 Ma) to the late Miocene. Two lineages (Rhodochlamys and Australimusa) radiated recently in the Pliocene /Pleistocene periods. Conclusions The plastome sequences performed well in resolving the phylogenetic relationships of Musaceae and generated new insights into its evolution. Plastome sequences provided valuable resources for population genetics and phylogenetics at lower taxon. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08454-3.
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Affiliation(s)
- Ning Fu
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Meiyuan Ji
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Mathieu Rouard
- Bioversity International, Parc Scientifique Agropolis II, 34397, Montpellier Cedex 5, France
| | - Hai-Fei Yan
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Xue-Jun Ge
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China. .,Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Guangzhou, China.
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28
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Tay Fernandez CG, Nestor BJ, Danilevicz MF, Gill M, Petereit J, Bayer PE, Finnegan PM, Batley J, Edwards D. Pangenomes as a Resource to Accelerate Breeding of Under-Utilised Crop Species. Int J Mol Sci 2022; 23:2671. [PMID: 35269811 PMCID: PMC8910360 DOI: 10.3390/ijms23052671] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 02/21/2022] [Accepted: 02/21/2022] [Indexed: 02/01/2023] Open
Abstract
Pangenomes are a rich resource to examine the genomic variation observed within a species or genera, supporting population genetics studies, with applications for the improvement of crop traits. Major crop species such as maize (Zea mays), rice (Oryza sativa), Brassica (Brassica spp.), and soybean (Glycine max) have had pangenomes constructed and released, and this has led to the discovery of valuable genes associated with disease resistance and yield components. However, pangenome data are not available for many less prominent crop species that are currently under-utilised. Despite many under-utilised species being important food sources in regional populations, the scarcity of genomic data for these species hinders their improvement. Here, we assess several under-utilised crops and review the pangenome approaches that could be used to build resources for their improvement. Many of these under-utilised crops are cultivated in arid or semi-arid environments, suggesting that novel genes related to drought tolerance may be identified and used for introgression into related major crop species. In addition, we discuss how previously collected data could be used to enrich pangenome functional analysis in genome-wide association studies (GWAS) based on studies in major crops. Considering the technological advances in genome sequencing, pangenome references for under-utilised species are becoming more obtainable, offering the opportunity to identify novel genes related to agro-morphological traits in these species.
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Affiliation(s)
| | | | | | | | | | | | | | | | - David Edwards
- School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia; (C.G.T.F.); (B.J.N.); (M.F.D.); (M.G.); (J.P.); (P.E.B.); (P.M.F.); (J.B.)
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29
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Tay Fernandez CG, Nestor BJ, Danilevicz MF, Marsh JI, Petereit J, Bayer PE, Batley J, Edwards D. Expanding Gene-Editing Potential in Crop Improvement with Pangenomes. Int J Mol Sci 2022; 23:ijms23042276. [PMID: 35216392 PMCID: PMC8879065 DOI: 10.3390/ijms23042276] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 02/14/2022] [Accepted: 02/15/2022] [Indexed: 02/01/2023] Open
Abstract
Pangenomes aim to represent the complete repertoire of the genome diversity present within a species or cohort of species, capturing the genomic structural variance between individuals. This genomic information coupled with phenotypic data can be applied to identify genes and alleles involved with abiotic stress tolerance, disease resistance, and other desirable traits. The characterisation of novel structural variants from pangenomes can support genome editing approaches such as Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR associated protein Cas (CRISPR-Cas), providing functional information on gene sequences and new target sites in variant-specific genes with increased efficiency. This review discusses the application of pangenomes in genome editing and crop improvement, focusing on the potential of pangenomes to accurately identify target genes for CRISPR-Cas editing of plant genomes while avoiding adverse off-target effects. We consider the limitations of applying CRISPR-Cas editing with pangenome references and potential solutions to overcome these limitations.
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30
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Hu H, Scheben A, Verpaalen B, Tirnaz S, Bayer PE, Hodel RGJ, Batley J, Soltis DE, Soltis PS, Edwards D. Amborella gene presence/absence variation is associated with abiotic stress responses that may contribute to environmental adaptation. THE NEW PHYTOLOGIST 2022; 233:1548-1555. [PMID: 34328223 PMCID: PMC9292397 DOI: 10.1111/nph.17658] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 07/26/2021] [Indexed: 05/03/2023]
Affiliation(s)
- Haifei Hu
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Armin Scheben
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
- Simons Center for Quantitative BiologyCold Spring Harbor LaboratoryCold Spring Harbor,NY11724USA
| | - Brent Verpaalen
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Soodeh Tirnaz
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Philipp E. Bayer
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Richard G. J. Hodel
- Department of BotanyNational Museum of Natural HistorySmithsonian InstitutionWashingtonDC20013‐7012USA
| | - Jacqueline Batley
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
| | - Douglas E. Soltis
- Department of BiologyUniversity of FloridaGainesvilleFL32611USA
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFL32611USA
- The Genetics InstituteUniversity of FloridaGainesvilleFL32610USA
- The Biodiversity InstituteUniversity of FloridaGainesvilleFL32611USA
| | - Pamela S. Soltis
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFL32611USA
- The Genetics InstituteUniversity of FloridaGainesvilleFL32610USA
- The Biodiversity InstituteUniversity of FloridaGainesvilleFL32611USA
| | - David Edwards
- School of Biological Sciences and Institute of AgricultureUniversity of Western AustraliaPerthWA6009Australia
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31
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Tay Fernandez CG, Marsh JI, Nestor BJ, Gill M, Golicz AA, Bayer PE, Edwards D. An SGSGeneloss-Based Method for Constructing a Gene Presence-Absence Table Using Mosdepth. Methods Mol Biol 2022; 2512:73-80. [PMID: 35818000 DOI: 10.1007/978-1-0716-2429-6_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Presence-absence variants (PAV) are genomic regions present in some individuals of a species, but not others. PAVs have been shown to contribute to genomic diversity, especially in bacteria and plants. These structural variations have been linked to traits and can be used to track a species' evolutionary history. PAVs are usually called by aligning short read sequence data from one or more individuals to a reference genome or pangenome assembly, and then comparing coverage. Regions where reads do not align define absence in that individual, and the regions are classified as PAVs. The method below details how to align sequence reads to a reference and how to use the sequencing-coverage calculator Mosdepth to identify PAVs and construct a PAV table for use in downstream comparative genome analysis.
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Affiliation(s)
- Cassandria G Tay Fernandez
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - Jacob I Marsh
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - Benjamin J Nestor
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - Mitchell Gill
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - Agnieszka A Golicz
- Department of Plant Breeding, Justus Liebig University Gießen, Gießen, Germany
| | - Philipp E Bayer
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - David Edwards
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia.
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32
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Mathiazhagan M, Chidambara B, Hunashikatti LR, Ravishankar KV. Genomic Approaches for Improvement of Tropical Fruits: Fruit Quality, Shelf Life and Nutrient Content. Genes (Basel) 2021; 12:1881. [PMID: 34946829 PMCID: PMC8701245 DOI: 10.3390/genes12121881] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/23/2021] [Accepted: 11/16/2021] [Indexed: 12/17/2022] Open
Abstract
The breeding of tropical fruit trees for improving fruit traits is complicated, due to the long juvenile phase, generation cycle, parthenocarpy, polyploidy, polyembryony, heterozygosity and biotic and abiotic factors, as well as a lack of good genomic resources. Many molecular techniques have recently evolved to assist and hasten conventional breeding efforts. Molecular markers linked to fruit development and fruit quality traits such as fruit shape, size, texture, aroma, peel and pulp colour were identified in tropical fruit crops, facilitating Marker-assisted breeding (MAB). An increase in the availability of genome sequences of tropical fruits further aided in the discovery of SNP variants/Indels, QTLs and genes that can ascertain the genetic determinants of fruit characters. Through multi-omics approaches such as genomics, transcriptomics, metabolomics and proteomics, the identification and quantification of transcripts, including non-coding RNAs, involved in sugar metabolism, fruit development and ripening, shelf life, and the biotic and abiotic stress that impacts fruit quality were made possible. Utilizing genomic assisted breeding methods such as genome wide association (GWAS), genomic selection (GS) and genetic modifications using CRISPR/Cas9 and transgenics has paved the way to studying gene function and developing cultivars with desirable fruit traits by overcoming long breeding cycles. Such comprehensive multi-omics approaches related to fruit characters in tropical fruits and their applications in breeding strategies and crop improvement are reviewed, discussed and presented here.
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Affiliation(s)
| | | | | | - Kundapura V. Ravishankar
- Division of Basic Sciences, ICAR Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bengaluru 560089, India; (M.M.); (B.C.); (L.R.H.)
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33
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Durant É, Sabot F, Conte M, Rouard M. Panache: a Web Browser-Based Viewer for Linearized Pangenomes. Bioinformatics 2021; 37:4556-4558. [PMID: 34601567 PMCID: PMC8652104 DOI: 10.1093/bioinformatics/btab688] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 07/28/2021] [Accepted: 09/24/2021] [Indexed: 11/15/2022] Open
Abstract
Motivation Pangenomics evolved since its first applications on bacteria, extending from the study of genes for a given population to the study of all of its sequences available. While multiple methods are being developed to construct pangenomes in eukaryotic species there is still a gap for efficient and user-friendly visualization tools. Emerging graph representations come with their own challenges, and linearity remains a suitable option for user-friendliness. Results We introduce Panache, a tool for the visualization and exploration of linear representations of gene-based and sequence-based pangenomes. It uses a layout similar to genome browsers to display presence absence variations and additional tracks along a linear axis with a pangenomics perspective. Availability and implementation Panache is available at github.com/SouthGreenPlatform/panache under the MIT License.
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Affiliation(s)
- Éloi Durant
- DIADE, Univ Montpellier, CIRAD, IRD, Montpellier, 34830, France.,Syngenta Seeds SAS, Saint-Sauveur, 31790, France.,Bioversity International, Parc Scientifique Agropolis II, Montpellier, 34397, France.,French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, 34398, France
| | - François Sabot
- DIADE, Univ Montpellier, CIRAD, IRD, Montpellier, 34830, France.,French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, 34398, France
| | | | - Mathieu Rouard
- Bioversity International, Parc Scientifique Agropolis II, Montpellier, 34397, France
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