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Wei S, Chougule K, Olson A, Lu Z, Tello-Ruiz MK, Kumar V, Kumari S, Zhang L, Olson A, Kim C, Gladman N, Ware D. GrameneOryza: a comprehensive resource for Oryza genomes, genetic variation, and functional data. Database (Oxford) 2025; 2025:baaf021. [PMID: 40214100 PMCID: PMC11986821 DOI: 10.1093/database/baaf021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Revised: 01/29/2025] [Accepted: 03/27/2025] [Indexed: 04/14/2025]
Abstract
Rice is a vital staple crop, sustaining over half of the global population, and is a key model for genetic research. To support the growing need for comprehensive and accessible rice genomic data, GrameneOryza (https://oryza.gramene.org) was developed as an online resource adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data management. It distinguishes itself through its comprehensive multispecies focus, encompassing a wide variety of Oryza genomes and related species, and its integration with FAIR principles to ensure data accessibility and usability. It offers a community curated selection of high-quality Oryza genomes, genetic variation, gene function, and trait data. The latest release, version 8, includes 28 Oryza genomes, covering wild rice and domesticated cultivars. These genomes, along with Leersia perrieri and seven additional outgroup species, form the basis for 38 K protein-coding gene family trees, essential for identifying orthologs, paralogs, and developing pan-gene sets. GrameneOryza's genetic variation data features 66 million single-nucleotide variants (SNVs) anchored to the Os-Nipponbare-Reference-IRGSP-1.0 genome, derived from various studies, including the Rice Genome 3 K (RG3K) project. The RG3K sequence reads were also mapped to seven additional platinum-quality Asian rice genomes, resulting in 19 million SNVs for each genome, significantly expanding the coverage of genetic variation beyond the Nipponbare reference. Of the 66 million SNVs on IRGSP-1.0, 27 million acquired standardized reference SNP cluster identifiers (rsIDs) from the European Variation Archive release v5. Additionally, 1200 distinct phenotypes provide a comprehensive overview of quantitative trait loci (QTL) features. The newly introduced Oryza CLIMtools portal offers insights into environmental impacts on genome adaptation. The platform's integrated search interface, along with a BLAST server and curation tools, facilitates user access to genomic, phylogenetic, gene function, and QTL data, supporting broad research applications. Database URL: https://oryza.gramene.org.
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Affiliation(s)
- Sharon Wei
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Kapeel Chougule
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Andrew Olson
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Zhenyuan Lu
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Marcela K Tello-Ruiz
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Vivek Kumar
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Sunita Kumari
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Lifang Zhang
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Audra Olson
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Catherine Kim
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
| | - Nick Gladman
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
- USDA ARS NEA, Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, 538 Tower Road, Ithaca, NY 14853-2901, United States
| | - Doreen Ware
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, United States
- USDA ARS NEA, Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, 538 Tower Road, Ithaca, NY 14853-2901, United States
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Liu R, Hu C, Gao D, Li M, Yuan X, Chen L, Shu Q, Wang Z, Yang X, Dai Z, Yu H, Yang F, Zheng A, Lv M, Garg V, Jiao C, Zhang H, Hou W, Teng C, Zhou X, Du C, Xiang C, Xu D, Tang Y, Chitikineni A, Duan Y, Maalouf F, Agrawal SK, Wei L, Zhao N, Barmukh R, Li X, Wang D, Ding H, Liu Y, Chen X, Varshney RK, He Y, Zong X, Yang T. A special short-wing petal faba genome and genetic dissection of floral and yield-related traits accelerate breeding and improvement of faba bean. Genome Biol 2025; 26:62. [PMID: 40098156 PMCID: PMC11916958 DOI: 10.1186/s13059-025-03532-7] [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: 07/02/2024] [Accepted: 03/06/2025] [Indexed: 03/19/2025] Open
Abstract
BACKGROUND A comprehensive study of the genome and genetics of superior germplasms is fundamental for crop improvement. As a widely adapted protein crop with high yield potential, the improvement in breeding and development of the seeds industry of faba bean have been greatly hindered by its giant genome size and high outcrossing rate. RESULTS To fully explore the genomic diversity and genetic basis of important agronomic traits, we first generate a de novo genome assembly and perform annotation of a special short-wing petal faba bean germplasm (VF8137) exhibiting a low outcrossing rate. Comparative genome and pan-genome analyses reveal the genome evolution characteristics and unique pan-genes among the three different faba bean genomes. In addition, the genome diversity of 558 accessions of faba bean germplasm reveals three distinct genetic groups and remarkable genetic differences between the southern and northern germplasms. Genome-wide association analysis identifies several candidate genes associated with adaptation- and yield-related traits. We also identify one candidate gene related to short-wing petals by combining quantitative trait locus mapping and bulked segregant analysis. We further elucidate its function through multiple lines of evidence from functional annotation, sequence variation, expression differences, and protein structure variation. CONCLUSIONS Our study provides new insights into the genome evolution of Leguminosae and the genomic diversity of faba bean. It offers valuable genomic and genetic resources for breeding and improvement of faba bean.
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Affiliation(s)
- Rong Liu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian District, Beijing, 100081, China
| | - Chaoqin Hu
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China
| | - Dan Gao
- Smartgenomics Technology Institute, Tianjin, 301700, China
| | - Mengwei Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian District, Beijing, 100081, China
| | - Xingxing Yuan
- Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, 210014, China
| | - Liyang Chen
- Smartgenomics Technology Institute, Tianjin, 301700, China
| | - Qin Shu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian District, Beijing, 100081, China
| | - Zonghe Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian District, Beijing, 100081, China
| | - Xin Yang
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China
| | - Zhengming Dai
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China
| | - Haitian Yu
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China
| | - Feng Yang
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China
| | - Aiqing Zheng
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China
| | - Meiyuan Lv
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China
| | - Vanika Garg
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia
| | - Chengzhi Jiao
- Smartgenomics Technology Institute, Tianjin, 301700, China
| | - Hongyan Zhang
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, Qinghai, 810016, China
- Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, Qinghai, 810016, China
| | - Wanwei Hou
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, Qinghai, 810016, China
- Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, Qinghai, 810016, China
| | - Changcai Teng
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, Qinghai, 810016, China
- Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, Qinghai, 810016, China
| | - Xianli Zhou
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, Qinghai, 810016, China
- Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, Qinghai, 810016, China
| | - Chengzhang Du
- Chongqing Academy of Agricultural Sciences, Chongqing, 401329, China
| | - Chao Xiang
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, Sichuan, 610066, China
| | - Dongxu Xu
- Zhangjiakou Academy of Agricultural Sciences, Zhangjiakou, Hebei, 075032, China
| | - Yongsheng Tang
- Qujing Academy of Agricultural Sciences, Qujingaq, Yunnan, 655000, China
| | - Annapurna Chitikineni
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia
| | - Yinmei Duan
- Dali Academy of Agricultural Sciences, Dali, Yunnan, 671005, China
| | - Fouad Maalouf
- International Center for Agricultural Researchin the, Dry Areas (ICARDA), Beirut, 1108-2010, Lebanon
| | - Shiv Kumar Agrawal
- International Center for Agricultural Researchin the, Dry Areas (ICARDA), Beirut, 1108-2010, Lebanon
| | - Libin Wei
- Jiangsu Yanjiang Institute of Agricultural Sciences, Nantong, Jiangsu, 226541, China
| | - Na Zhao
- Jiangsu Yanjiang Institute of Agricultural Sciences, Nantong, Jiangsu, 226541, China
| | - Rutwik Barmukh
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia
| | - Xiang Li
- Yuxi Academy of Agricultural Sciences, Yuxi, Yunnan, 653100, China
| | - Dong Wang
- Institute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences/Shandong Provincial Key Laboratory of Crop Genetic Improvement, Ecology and Physiology, Jinan, Shandong, 250100, China
| | - Hanfeng Ding
- Institute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences/Shandong Provincial Key Laboratory of Crop Genetic Improvement, Ecology and Physiology, Jinan, Shandong, 250100, China
| | - Yujiao Liu
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, Qinghai, 810016, China.
| | - Xin Chen
- Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, 210014, China.
| | - Rajeev K Varshney
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia.
| | - Yuhua He
- Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan, 650205, China.
| | - Xuxiao Zong
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian District, Beijing, 100081, China.
| | - Tao Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Haidian District, Beijing, 100081, 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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Khanbo S, Phadphon P, Naktang C, Sangsrakru D, Waiyamitra P, Narong N, Yundaeng C, Tangphatsornruang S, Laosatit K, Somta P, Pootakham W. A chromosome-scale genome assembly of mungbean ( Vigna radiata). PeerJ 2024; 12:e18771. [PMID: 39726742 PMCID: PMC11670757 DOI: 10.7717/peerj.18771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Accepted: 12/05/2024] [Indexed: 12/28/2024] Open
Abstract
Background Mungbean (Vigna radiata) is one of the most socio-economically important leguminous food crops of Asia and a rich source of dietary protein and micronutrients. Understanding its genetic makeup is crucial for genetic improvement and cultivar development. Methods In this study, we combined single-tube long-fragment reads (stLFR) sequencing technology with high-throughput chromosome conformation capture (Hi-C) technique to obtain a chromosome-level assembly of V. radiata cultivar 'KUML4'. Results The final assembly of the V. radiata genome was 468.08 Mb in size, with a scaffold N50 of 40.75 Mb. This assembly comprised 11 pseudomolecules, covering 96.94% of the estimated genome size. The genome contained 253.85 Mb (54.76%) of repetitive sequences and 27,667 protein-coding genes. Our gene prediction recovered 98.3% of the highly conserved orthologs based on Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis. Comparative analyses using sequence data from single-copy orthologous genes indicated that V. radiata diverged from V. mungo approximately 4.17 million years ago. Moreover, gene family analysis revealed that major gene families associated with defense responses were significantly expanded in V. radiata. Conclusion Our chromosome-scale genome assembly of V. radiata cultivar KUML4 will provide a valuable genomic resource, supporting genetic improvement and molecular breeding. This data will also be valuable for future comparative genomics studies among legume species.
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Affiliation(s)
- Supaporn Khanbo
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Poompat Phadphon
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Chaiwat Naktang
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Duangjai Sangsrakru
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Pitchaporn Waiyamitra
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Nattapol Narong
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Chutintorn Yundaeng
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Sithichoke Tangphatsornruang
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
| | - Kularb Laosatit
- Department of Agronomy, Faculty of Agriculture at Kamphaeng Saen, Kasetsart University, Kamphaeng Saen Campus, Nakhon Pathom, Thailand
| | - Prakit Somta
- Department of Agronomy, Faculty of Agriculture at Kamphaeng Saen, Kasetsart University, Kamphaeng Saen Campus, Nakhon Pathom, Thailand
| | - Wirulda Pootakham
- National Omics Center, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand
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Ning W, Wang W, Liu Z, Xie W, Chen H, Hong D, Yang QY, Cheng S, Guo L. The pan-NLRome analysis based on 23 genomes reveals the diversity of NLRs in Brassica napus. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:2. [PMID: 39713061 PMCID: PMC11655762 DOI: 10.1007/s11032-024-01522-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Accepted: 12/02/2024] [Indexed: 12/24/2024]
Abstract
Brassica napus, a globally significant oilseed crop, exhibits a wide distribution across diverse climatic zones. B. napus is being increasingly susceptible to distinct diseases, such as blackleg, clubroot and sclerotinia stem rot, leading to substantial reductions in yield. Nucleotide-binding site leucine-rich repeat genes (NLRs), the most pivotal family of resistance genes, can be effectively harnessed by identifying and uncovering their diversity to acquire premium disease-resistant gene resources. Here, we collected the genomes of 23 accessions and established the first comprehensive pan-NLRome in B. napus by leveraging multiple genomic resources. We observe significant variation in the number of NLR genes across different B. napus accessions, ranging from 189 to 474. Notably, TNL (TIR-NBS-LRR) genes constitute approximately half of the total count, indicating their predominant presence in B. napus. The number of NLRs in the C subgenome is significantly higher than that in the A subgenome, and chromosome C09 exhibits the highest density of NLR genes with featuring multiple NLR clusters. Domain analysis reveals that the integrated domains significantly enhance the diversity of NLRs, with B3 DNA binding, VQ, and zinc fingers being the most prevalent integrated domains. Pan-genomic analysis reveals that the core type of NLR genes, which is present in most accessions, constitutes approximately 58% of the total NLRs. Furthermore, we conduct a comparative analysis of the diversity of NLR genes across distinct ecotypes, leading to the identification of ecotype-specific NLRs and their integrated domains. In conclusion, our study effectively addresses the limitations of a single reference genome and provides valuable insights into the diversity of NLR genes in B. napus, thereby contributing to disease resistance breeding.
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Affiliation(s)
- Weidong Ning
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070 China
- Yazhouwan National Laboratory, Sanya, 572025 Hainan China
- 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
| | - Wenzheng Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Zijian Liu
- 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
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Hanchen Chen
- Yazhouwan National Laboratory, Sanya, 572025 Hainan China
| | - Dengfeng Hong
- Yazhouwan National Laboratory, Sanya, 572025 Hainan China
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Qing-Yong Yang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070 China
- Yazhouwan National Laboratory, Sanya, 572025 Hainan China
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - 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
| | - Liang Guo
- Yazhouwan National Laboratory, Sanya, 572025 Hainan China
- 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
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
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Sabety J, Svara A, Tegtmeier R, Feulner H, Cho P, Sakina A, Hickok D, Khan A. Unlocking diversity from wild relatives of perennial fruit crops in the pan-genomics era. CURRENT OPINION IN PLANT BIOLOGY 2024; 82:102652. [PMID: 39476558 DOI: 10.1016/j.pbi.2024.102652] [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: 06/30/2024] [Revised: 09/12/2024] [Accepted: 09/26/2024] [Indexed: 12/07/2024]
Abstract
Crop wild relatives of perennial fruit crops have a wealth of untapped genetic diversity that can be utilized for cultivar development. However, barriers such as linkage drag, long juvenility, and high heterozygosity have hindered their utilization. Advancements in genome sequencing technologies and assembly methods, combined with the integration of chromosome conformation capture have made it possible to construct high-quality reference genomes. These genome assemblies can be combined into pan-genomes, capturing inter- and intraspecific variations across coding and non-coding regions. Pan-genomes of perennial fruit crops are being developed to identify the genetic basis of traits. This will help overcome breeding challenges, enabling faster and more targeted development of new cultivars with novel traits through breeding and biotechnology.
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Affiliation(s)
- Jean Sabety
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA
| | - Anze Svara
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA
| | - Richard Tegtmeier
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA
| | - Hana Feulner
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA
| | - Patrick Cho
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA
| | - Aafreen Sakina
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA
| | - David Hickok
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA
| | - Awais Khan
- Plant Pathology and Plant-Microbe Biology Section, Cornell University, 630 N Street, Geneva, NY, 14456, USA.
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7
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Kaur H, Shannon LM, Samac DA. A stepwise guide for pangenome development in crop plants: an alfalfa (Medicago sativa) case study. BMC Genomics 2024; 25:1022. [PMID: 39482604 PMCID: PMC11526573 DOI: 10.1186/s12864-024-10931-w] [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: 06/13/2024] [Accepted: 10/21/2024] [Indexed: 11/03/2024] Open
Abstract
BACKGROUND The concept of pangenomics and the importance of structural variants is gaining recognition within the plant genomics community. Due to advancements in sequencing and computational technology, it has become feasible to sequence the entire genome of numerous individuals of a single species at a reasonable cost. Pangenomes have been constructed for many major diploid crops, including rice, maize, soybean, sorghum, pearl millet, peas, sunflower, grapes, and mustards. However, pangenomes for polyploid species are relatively scarce and are available in only few crops including wheat, cotton, rapeseed, and potatoes. MAIN BODY In this review, we explore the various methods used in crop pangenome development, discussing the challenges and implications of these techniques based on insights from published pangenome studies. We offer a systematic guide and discuss the tools available for constructing a pangenome and conducting downstream analyses. Alfalfa, a highly heterozygous, cross pollinated and autotetraploid forage crop species, is used as an example to discuss the concerns and challenges offered by polyploid crop species. We conducted a comparative analysis using linear and graph-based methods by constructing an alfalfa graph pangenome using three publicly available genome assemblies. To illustrate the intricacies captured by pangenome graphs for a complex crop genome, we used five different gene sequences and aligned them against the three graph-based pangenomes. The comparison of the three graph pangenome methods reveals notable variations in the genomic variation captured by each pipeline. CONCLUSION Pangenome resources are proving invaluable by offering insights into core and dispensable genes, novel gene discovery, and genome-wide patterns of variation. Developing user-friendly online portals for linear pangenome visualization has made these resources accessible to the broader scientific and breeding community. However, challenges remain with graph-based pangenomes including compatibility with other tools, extraction of sequence for regions of interest, and visualization of genetic variation captured in pangenome graphs. These issues necessitate further refinement of tools and pipelines to effectively address the complexities of polyploid, highly heterozygous, and cross-pollinated species.
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Affiliation(s)
- Harpreet Kaur
- Department of Horticultural Science, University of Minnesota, St. Paul, MN, 55108, USA.
| | - Laura M Shannon
- Department of Horticultural Science, University of Minnesota, St. Paul, MN, 55108, USA
| | - Deborah A Samac
- USDA-ARS, Plant Science Research Unit, St. Paul, MN, 55108, USA
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8
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Guo M, Lian Q, Mei Y, Yang W, Zhao S, Zhang S, Xing X, Zhang H, Gao K, He W, Wang Z, Wang H, Zhou J, Cheng L, Bao Z, Huang S, Yan J, Zhao X. Analyzes of pan-genome and resequencing atlas unveil the genetic basis of jujube domestication. Nat Commun 2024; 15:9320. [PMID: 39472552 PMCID: PMC11522667 DOI: 10.1038/s41467-024-53718-z] [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: 02/19/2024] [Accepted: 10/21/2024] [Indexed: 11/02/2024] Open
Abstract
Jujube (Ziziphus jujuba Mill.), belonging to the Rhamnaceae family, is gaining increasing prominence as a perennial fruit crop with significant economic and medicinal values. Here, we conduct de novo assembly of four reference-grade genomes, encompassing one wild and three cultivated jujube accessions. We present insights into the population structure, genetic diversity, and genomic variations within a diverse collection of 1059 jujube accessions. Analyzes of the jujube pan-genome, based on our four assemblies and four previously released genomes, reveal extensive genomic variations within domestication-associated regions, potentially leading to the discovery of a candidate gene that regulates flowering and fruit ripening. By leveraging the pan-genome and a large-scale resequencing population, we identify two candidate genes involved in domestication traits, including the seed-setting rate, the bearing-shoot length and the leaf size in jujube. These genomic resources will accelerate evolutionary and functional genomics studies of jujube.
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Affiliation(s)
- Mingxin Guo
- College of Life Sciences, Luoyang Normal University, Luoyang, China.
| | - Qun Lian
- 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, Shenzhen, China
- School of Biology & Environmental Science, University College Dublin, Belfield, Dublin, Ireland
| | - Ye Mei
- 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, Shenzhen, China
| | - Wangwang Yang
- College of Life Sciences, Luoyang Normal University, Luoyang, China
| | - Suna Zhao
- College of Life Sciences, Luoyang Normal University, Luoyang, China
| | - Siyuan Zhang
- College of Life Sciences, Luoyang Normal University, Luoyang, China
| | - Xinfeng Xing
- College of Life Sciences, Luoyang Normal University, Luoyang, China
| | - Haixiang Zhang
- College of Life Sciences, Luoyang Normal University, Luoyang, China
| | - Keying Gao
- College of Life Sciences, Luoyang Normal University, Luoyang, China
| | - Wentong He
- National Foundation for Improved Cultivar of Chinese Jujube, Bureau of Natural Resources and Planning of Cangxian County, Cangzhou, China
| | - Zhitong Wang
- National Foundation for Improved Cultivar of Chinese Jujube, Bureau of Natural Resources and Planning of Cangxian County, Cangzhou, China
| | - Huan Wang
- 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, Shenzhen, China
| | - Jun Zhou
- School of Biological Science and Engineering, North Minzu University, Yinchuan, China
| | - Lin Cheng
- 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, Shenzhen, China
- Plant Genetics and Rhizosphere Processes Laboratory, TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech, Gembloux, Belgium
| | - Zhigui Bao
- 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, Shenzhen, China
| | - Sanwen Huang
- 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, Shenzhen, China
| | - Jianbin Yan
- 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, Shenzhen, China.
| | - Xusheng Zhao
- College of Life Sciences, Luoyang Normal University, Luoyang, China.
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9
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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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10
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Cortinovis G, Vincenzi L, Anderson R, Marturano G, Marsh JI, Bayer PE, Rocchetti L, Frascarelli G, Lanzavecchia G, Pieri A, Benazzo A, Bellucci E, Di Vittori V, Nanni L, Ferreira Fernández JJ, Rossato M, Aguilar OM, Morrell PL, Rodriguez M, Gioia T, Neumann K, Alvarez Diaz JC, Gratias A, Klopp C, Bitocchi E, Geffroy V, Delledonne M, Edwards D, Papa R. Adaptive gene loss in the common bean pan-genome during range expansion and domestication. Nat Commun 2024; 15:6698. [PMID: 39107305 PMCID: PMC11303546 DOI: 10.1038/s41467-024-51032-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 07/28/2024] [Indexed: 08/10/2024] Open
Abstract
The common bean (Phaseolus vulgaris L.) is a crucial legume crop and an ideal evolutionary model to study adaptive diversity in wild and domesticated populations. Here, we present a common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. It reveals ~234 Mb of additional sequences containing 6,905 protein-coding genes missing from the reference, constituting 49% of all presence/absence variants (PAVs). More non-synonymous mutations are found in PAVs than core genes, probably reflecting the lower effective population size of PAVs and fitness advantages due to the purging effect of gene loss. Our results suggest pan-genome shrinkage occurred during wild range expansion. Selection signatures provide evidence that partial or complete gene loss was a key adaptive genetic change in common bean populations with major implications for plant adaptation. The pan-genome is a valuable resource for food legume research and breeding for climate change mitigation and sustainable agriculture.
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Affiliation(s)
- Gaia Cortinovis
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Leonardo Vincenzi
- Department of Biotechnology, University of Verona, 37134, Verona, Italy
| | - Robyn Anderson
- Centre for Applied Bioinformatics and School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia
| | | | - Jacob Ian Marsh
- Centre for Applied Bioinformatics and School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia
| | - Philipp Emanuel Bayer
- Centre for Applied Bioinformatics and School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia
| | - Lorenzo Rocchetti
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Giulia Frascarelli
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Giovanna Lanzavecchia
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Alice Pieri
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Andrea Benazzo
- Department of Life Sciences and Biotechnology, University of Ferrara, 44100, Ferrara, Italy
| | - Elisa Bellucci
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Valerio Di Vittori
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Laura Nanni
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | | | - Marzia Rossato
- Department of Biotechnology, University of Verona, 37134, Verona, Italy
- Genartis s.r.l, 37126, Verona, Italy
| | - Orlando Mario Aguilar
- Institute of Biotechnology and Molecular Biology, UNLP-CONICET, CCT La Plata, La Plata, Argentina
| | - Peter Laurent Morrell
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108-6026, USA
| | - Monica Rodriguez
- Department of Agriculture, University of Sassari, 07100, Sassari, Italy
- CBV-Centro per la Conservazione e Valorizzazione della Biodiversità Vegetale, University of Sassari, 07041, Alghero, Italy
| | - Tania Gioia
- School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, 85100, Potenza, Italy
| | - Kerstin Neumann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Seeland, Germany
| | - Juan Camilo Alvarez Diaz
- CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), University of Evry, University Paris-Saclay, 91405, Orsay, France
| | - Ariane Gratias
- CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), University of Evry, University Paris-Saclay, 91405, Orsay, France
| | - Christophe Klopp
- INRAE, Genotoul Bioinformatics Platform, Applied Mathematics and Informatics of Toulouse, Sigenae, MIAT, UR875, Castanet Tolosan, France
| | - Elena Bitocchi
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy
| | - Valérie Geffroy
- CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), University of Evry, University Paris-Saclay, 91405, Orsay, France.
| | - Massimo Delledonne
- Department of Biotechnology, University of Verona, 37134, Verona, Italy.
- Genartis s.r.l, 37126, Verona, Italy.
| | - David Edwards
- Centre for Applied Bioinformatics and School of Biological Sciences, University of Western Australia, Perth, WA, 6009, Australia.
| | - Roberto Papa
- Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, 60131, Ancona, Italy.
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11
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Sarawad A, Hosagoudar S, Parvatikar P. Pan-genomics: Insight into the Functional Genome, Applications, Advancements, and Challenges. Curr Genomics 2024; 26:2-14. [PMID: 39911277 PMCID: PMC11793047 DOI: 10.2174/0113892029311541240627111506] [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: 02/20/2024] [Revised: 04/30/2024] [Accepted: 05/29/2024] [Indexed: 02/07/2025] Open
Abstract
A pan-genome is a compilation of the common and unique genomes found in a given species. It incorporates the genetic information from all of the genomes sampled, producing a big and diverse set of genetic material. Pan-genomic analysis has various advantages over typical genomics research. It creates a vast and varied spectrum of genetic material by combining the genetic data from all the sampled genomes. Comparing pan-genomics analysis to conventional genomic research, there are a number of benefits. Although the most recent era of pan-genomic studies has used cutting-edge sequencing technology to shed fresh light on biological variety and improvement, the potential uses of pan-genomics in improvement have not yet been fully realized. Pan-genome research in various organisms has demonstrated that missing genetic components and the detection of significant Structural Variants (SVs) can be investigated using pan-genomic methods. Many individual-specific sequences have been linked to biological adaptability, phenotypic, and key economic attributes. This study aims to focus on how pangenome analysis uncovers genetic differences in various organisms, including human, and their effects on phenotypes, as well as how this might help us comprehend the diversity of species. The review also concentrated on potential problems and the prospects for future pangenome research.
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Affiliation(s)
- Akansha Sarawad
- Department of Biotechnology, Applied School of Science and Technology, BLDE (DU), Vijayapura, Karnataka, India
| | - Spoorti Hosagoudar
- Department of Biotechnology, Applied School of Science and Technology, BLDE (DU), Vijayapura, Karnataka, India
| | - Prachi Parvatikar
- Department of Biotechnology, Applied School of Science and Technology, BLDE (DU), Vijayapura, Karnataka, India
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12
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Wang P, Abbas M, He J, Zhou L, Cheng H, Guo H. Advances in genome sequencing and artificially induced mutation provides new avenues for cotton breeding. FRONTIERS IN PLANT SCIENCE 2024; 15:1400201. [PMID: 39015293 PMCID: PMC11250495 DOI: 10.3389/fpls.2024.1400201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 06/10/2024] [Indexed: 07/18/2024]
Abstract
Cotton production faces challenges in fluctuating environmental conditions due to limited genetic variation in cultivated cotton species. To enhance the genetic diversity crucial for this primary fiber crop, it is essential to augment current germplasm resources. High-throughput sequencing has significantly impacted cotton functional genomics, enabling the creation of diverse mutant libraries and the identification of mutant functional genes and new germplasm resources. Artificial mutation, established through physical or chemical methods, stands as a highly efficient strategy to enrich cotton germplasm resources, yielding stable and high-quality raw materials. In this paper, we discuss the good foundation laid by high-throughput sequencing of cotton genome for mutant identification and functional genome, and focus on the construction methods of mutant libraries and diverse sequencing strategies based on mutants. In addition, the important functional genes identified by the cotton mutant library have greatly enriched the germplasm resources and promoted the development of functional genomes. Finally, an innovative strategy for constructing a cotton CRISPR mutant library was proposed, and the possibility of high-throughput screening of cotton mutants based on a UAV phenotyping platform was discussed. The aim of this review was to expand cotton germplasm resources, mine functional genes, and develop adaptable materials in a variety of complex environments.
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Affiliation(s)
- Peilin Wang
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, Hainan, China
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mubashir Abbas
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jianhan He
- Institute of Cereal and Oil Crops, Hebei Academy of Agriculture and Forestry Sciences, Hebei Key Laboratory of Crop Genetics and Breeding, Shijiazhuang, Hebei, China
| | - Lili Zhou
- Yazhouwan National Laboratory, Sanya, Hainan, China
| | - Hongmei Cheng
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huiming Guo
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, Hainan, China
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
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13
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Wang Y, Li P, Zhu Y, Zhang F, Zhang S, He Y, Wu Y, Lin Y, Wang H, Ren W, Wang L, Yang Y, Wang R, Zheng P, Liu Y, Wang S, Yue J. Graph-Based Pangenome of Actinidia chinensis Reveals Structural Variations Mediating Fruit Degreening. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2400322. [PMID: 38757662 PMCID: PMC11267314 DOI: 10.1002/advs.202400322] [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: 01/09/2024] [Revised: 04/19/2024] [Indexed: 05/18/2024]
Abstract
Fruit ripening is associated with the degreening process (loss of chlorophyll) that occurs in most fruit species. Kiwifruit is one of the special species whose fruits may maintain green flesh by accumulating a large amount of chlorophyll even after ripening. However, little is known about the genetic variations related to the fruit degreening process. Here, a graph-based kiwifruit pangenome by analyzing 14 chromosome-scale haplotype-resolved genome assemblies from seven representative cultivars or lines in Actinidia chinensis is built. A total of 49,770 non-redundant gene families are identified, with core genes constituting 46.6%, and dispensable genes constituting 53.4%. A total of 84,591 non-redundant structural variations (SVs) are identified. The pangenome graph integrating both reference genome sequences and variant information facilitates the identification of SVs related to fruit color. The SV in the promoter of the AcBCM gene determines its high expression in the late developmental stage of fruits, which causes chlorophyll accumulation in the green-flesh fruits by post-translationally regulating AcSGR2, a key enzyme of chlorophyll catabolism. Taken together, a high-quality pangenome is constructed, unraveled numerous genetic variations, and identified a novel SV mediating fruit coloration and fruit quality, providing valuable information for further investigating genome evolution and domestication, QTL genes function, and genomics-assisted breeding.
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Affiliation(s)
- Yingzhen Wang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
- School of Forestry Science and TechnologyLishui Vocational and Technical CollegeLishui323000China
| | - Pengwei Li
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Yanyan Zhu
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Feng Zhang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Sijia Zhang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Yan He
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Ying Wu
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Yunzhi Lin
- Ministry of Education Key Laboratory for Bio‐resource and Eco‐environmentCollege of Life ScienceState Key Laboratory of Hydraulics and Mountain River EngineeringSichuan UniversityChengdu610064China
| | - Hongtao Wang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Wangmei Ren
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Lihuan Wang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Ying Yang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Runze Wang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Pengpeng Zheng
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Yongsheng Liu
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
- Ministry of Education Key Laboratory for Bio‐resource and Eco‐environmentCollege of Life ScienceState Key Laboratory of Hydraulics and Mountain River EngineeringSichuan UniversityChengdu610064China
| | - Songhu Wang
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
| | - Junyang Yue
- Anhui Province Key Laboratory of Horticultural Crop Quality BiologySchool of HorticultureAnhui Agricultural UniversityHefei230036China
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14
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Xie X, Deng X, Chen L, Yuan J, Chen H, Wei C, Liu X, Wuertz S, Qiu G. Integrated genomics provides insights into the evolution of the polyphosphate accumulation trait of Ca. Accumulibacter. ENVIRONMENTAL SCIENCE AND ECOTECHNOLOGY 2024; 20:100353. [PMID: 39221073 PMCID: PMC11361876 DOI: 10.1016/j.ese.2023.100353] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 11/18/2023] [Accepted: 11/23/2023] [Indexed: 09/04/2024]
Abstract
Candidatus Accumulibacter, a prominent polyphosphate-accumulating organism (PAO) in wastewater treatment, plays a crucial role in enhanced biological phosphorus removal (EBPR). The genetic underpinnings of its polyphosphate accumulation capabilities, however, remain largely unknown. Here, we conducted a comprehensive genomic analysis of Ca. Accumulibacter-PAOs and their relatives within the Rhodocyclaceae family, identifying 124 core genes acquired via horizontal gene transfer (HGT) at its least common ancestor. Metatranscriptomic analysis of an enrichment culture of Ca. Accumulibacter revealed active transcription of 44 of these genes during an EBPR cycle, notably including the polyphosphate kinase 2 (PPK2) gene instead of the commonly recognized polyphosphate kinase 1 (PPK1) gene. Intriguingly, the phosphate regulon (Pho) genes showed minimal transcriptions, pointing to a distinctive fact of Pho dysregulation, where PhoU, the phosphate signaling complex protein, was not regulating the high-affinity phosphate transport (Pst) system, resulting in continuous phosphate uptake. To prevent phosphate toxicity, Ca. Accumulibacter utilized the laterally acquired PPK2 to condense phosphate into polyphosphate, resulting in the polyphosphate-accumulating feature. This study provides novel insights into the evolutionary emergence of the polyphosphate-accumulating trait in Ca. Accumulibacter, offering potential advancements in understanding the PAO phenotype in the EBPR process.
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Affiliation(s)
- Xiaojing Xie
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Xuhan Deng
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Liping Chen
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Jing Yuan
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Hang Chen
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Chaohai Wei
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Xianghui Liu
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, 637551, Singapore
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, 637551, Singapore
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, 639798, Singapore
| | - Guanglei Qiu
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, 637551, Singapore
- Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, Guangzhou, 510006, China
- The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, Guangzhou, 510006, China
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15
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Jiang C, Zhao G, Wang H, Zheng W, Zhang R, Wang L, Zheng Z. Comparative genomics analysis and transposon mutagenesis provides new insights into high menaquinone-7 biosynthetic potential of Bacillus subtilis natto. Gene 2024; 907:148264. [PMID: 38346457 DOI: 10.1016/j.gene.2024.148264] [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: 10/06/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 02/15/2024]
Abstract
This research combined Whole-Genome sequencing, intraspecific comparative genomics and transposon mutagenesis to investigate the menaquinone-7 (MK-7) synthesis potential in Bacillus subtilis natto. First, Whole-Genome sequencing showed that Bacillus subtilis natto BN-P15-11-1 contains one single circular chromosome in size of 3,982,436 bp with a GC content of 43.85 %, harboring 4,053 predicted coding genes. Next, the comparative genomics analysis among strain BN-P15-11-1 with model Bacillus subtilis 168 and four typical Bacillus subtilis natto strains proves that the closer evolutionary relationship Bacillus subtilis natto BN-P15-11-1 and Bacillus subtilis 168 both exhibit strong biosynthetic potential. To further dig for MK-7 biosynthesis latent capacity of BN-P15-11-1, we constructed a mutant library using transposons and a high throughput screening method using microplates. We obtained a YqgQ deficient high MK-7 yield strain F4 with a yield 3.02 times that of the parent strain. Experiments also showed that the high yield mutants had defects in different transcription and translation regulatory factor genes, indicating that regulatory factor defects may affect the biosynthesis and accumulation of MK-7 by altering the overall metabolic level. The findings of this study will provide more novel insights on the precise identification and rational utilization of the Bacillus subtilis subspecies for biosynthesis latent capacity.
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Affiliation(s)
- Chunxu Jiang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China; University of Science and Technology of China, Hefei, Anhui, PR China
| | - Genhai Zhao
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China
| | - Han Wang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China
| | - Wenqian Zheng
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China; University of Science and Technology of China, Hefei, Anhui, PR China
| | - Rui Zhang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China
| | - Li Wang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China.
| | - Zhiming Zheng
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China.
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16
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Jadhav Y, Thakur NR, Ingle KP, Ceasar SA. The role of phenomics and genomics in delineating the genetic basis of complex traits in millets. PHYSIOLOGIA PLANTARUM 2024; 176:e14349. [PMID: 38783512 DOI: 10.1111/ppl.14349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 04/22/2024] [Accepted: 04/26/2024] [Indexed: 05/25/2024]
Abstract
Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.
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Affiliation(s)
- Yashoda Jadhav
- International Crops Research Institutes for the Semi-Arid Tropics, Patancheru, TS, India
| | - Niranjan Ravindra Thakur
- International Crops Research Institutes for the Semi-Arid Tropics, Patancheru, TS, India
- Vasantrao Naik Marathwada Agricultural University, Parbhani, MS, India
| | | | - Stanislaus Antony Ceasar
- Division of Plant Molecular Biology and Biotechnology, Department of Biosciences, Rajagiri College of Social Sciences, Kochi, KL, India
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17
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Lu Y, Liu D, Kong X, Song Y, Jing L. Pangenome characterization and analysis of the NAC gene family reveals genes for Sclerotinia sclerotiorum resistance in sunflower (Helianthus annuus). BMC Genom Data 2024; 25:39. [PMID: 38693490 PMCID: PMC11064331 DOI: 10.1186/s12863-024-01227-9] [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: 01/07/2024] [Accepted: 04/22/2024] [Indexed: 05/03/2024] Open
Abstract
BACKGROUND Sunflower (Helianthus annuus) is one of the most important economic crops in oilseed production worldwide. The different cultivars exhibit variability in their resistance genes. The NAC transcription factor (TF) family plays diverse roles in plant development and stress responses. With the completion of the H. annuus genome sequence, the entire complement of genes coding for NACs has been identified. However, the reference genome of a single individual cannot cover all the genetic information of the species. RESULTS Considering only a single reference genome to study gene families will miss many meaningful genes. A pangenome-wide survey and characterization of the NAC genes in sunflower species were conducted. In total, 139 HaNAC genes are identified, of which 114 are core and 25 are variable. Phylogenetic analysis of sunflower NAC proteins categorizes these proteins into 16 subgroups. 138 HaNACs are randomly distributed on 17 chromosomes. SNP-based haplotype analysis shows haplotype diversity of the HaNAC genes in wild accessions is richer than in landraces and modern cultivars. Ten HaNAC genes in the basal stalk rot (BSR) resistance quantitative trait loci (QTL) are found. A total of 26 HaNAC genes are differentially expressed in response to Sclerotinia head rot (SHR). A total of 137 HaNAC genes are annotated in Gene Ontology (GO) and are classified into 24 functional groups. GO functional enrichment analysis reveals that HaNAC genes are involved in various functions of the biological process. CONCLUSIONS We identified NAC genes in H. annuus (HaNAC) on a pangenome-wide scale and analyzed S. sclerotiorum resistance-related NACs. This study provided a theoretical basis for further genomic improvement targeting resistance-related NAC genes in sunflowers.
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Affiliation(s)
- Yan Lu
- College of Horticulture and Plant Protection, Inner Mongolia Agricultural University, Hohhot, China
| | - Dongqi Liu
- College of Horticulture and Plant Protection, Inner Mongolia Agricultural University, Hohhot, China
| | - Xiangjiu Kong
- College of Horticulture and Plant Protection, Inner Mongolia Agricultural University, Hohhot, China
| | - Yang Song
- College of Horticulture and Plant Protection, Inner Mongolia Agricultural University, Hohhot, China
| | - Lan Jing
- College of Horticulture and Plant Protection, Inner Mongolia Agricultural University, Hohhot, China.
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18
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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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19
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Rosani U, Sollitto M, Fogal N, Salata C. Comparative analysis of Presence-Absence gene Variations in five hard tick species: impact and functional considerations. Int J Parasitol 2024; 54:147-156. [PMID: 37806426 DOI: 10.1016/j.ijpara.2023.08.004] [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: 01/25/2023] [Revised: 08/06/2023] [Accepted: 08/31/2023] [Indexed: 10/10/2023]
Abstract
Tick species are vectors of harmful human and animal diseases, and their expansion is raising concerns under the global environmental changes' scenario. Ticks host and transmit bacteria, protozoa and viruses, making the understanding of host-pathogen molecular pathways critical to development of effective disease control strategies. Despite the considerable sizes and repeat contents of tick genomes, individual tick genomics is perhaps the most effective approach to reveal genotypic traits of interest. Presence-Absence gene Variations (PAVs) can contribute to individual differences within species, with dispensable genes carried by subsets of individuals possibly underpinning functional significance at individual or population-levels. We exploited 350 resequencing datasets of Dermacentor silvarum, Haemaphysalis longicornis, Ixodes persulcatus, Rhipicephalus microplus and Rhipicephalus sanguineus hard tick specimens to reveal the extension of PAV and the conservation of dispensable genes among individuals and, comparatively, between species. Overall, we traced 550-3,346 dispensable genes per species and were able to reconstruct 5.3-7 Mb of genomic regions not included in the respective reference genomes, as part of the tick pangenomes. Both dispensable genes and de novo predicted genes indicated that PAVs preferentially impacted mobile genetic elements in these tick species.
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Affiliation(s)
- Umberto Rosani
- Department of Biology, University of Padova, 35121 Padova, Italy.
| | - Marco Sollitto
- Department of Life Science, University of Trieste, 34100 Trieste, Italy; Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, 6000 Koper, Slovenia
| | - Nicolò Fogal
- Department of Biology, University of Padova, 35121 Padova, Italy
| | - Cristiano Salata
- Department of Molecular Medicine, University of Padova, 35121 Padova, Italy
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20
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Liu X, Zheng J, Ding J, Wu J, Zuo F, Zhang G. When Livestock Genomes Meet Third-Generation Sequencing Technology: From Opportunities to Applications. Genes (Basel) 2024; 15:245. [PMID: 38397234 PMCID: PMC10888458 DOI: 10.3390/genes15020245] [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: 12/23/2023] [Revised: 01/30/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024] Open
Abstract
Third-generation sequencing technology has found widespread application in the genomic, transcriptomic, and epigenetic research of both human and livestock genetics. This technology offers significant advantages in the sequencing of complex genomic regions, the identification of intricate structural variations, and the production of high-quality genomes. Its attributes, including long sequencing reads, obviation of PCR amplification, and direct determination of DNA/RNA, contribute to its efficacy. This review presents a comprehensive overview of third-generation sequencing technologies, exemplified by single-molecule real-time sequencing (SMRT) and Oxford Nanopore Technology (ONT). Emphasizing the research advancements in livestock genomics, the review delves into genome assembly, structural variation detection, transcriptome sequencing, and epigenetic investigations enabled by third-generation sequencing. A comprehensive analysis is conducted on the application and potential challenges of third-generation sequencing technology for genome detection in livestock. Beyond providing valuable insights into genome structure analysis and the identification of rare genes in livestock, the review ventures into an exploration of the genetic mechanisms underpinning exemplary traits. This review not only contributes to our understanding of the genomic landscape in livestock but also provides fresh perspectives for the advancement of research in this domain.
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Affiliation(s)
- Xinyue Liu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Junyuan Zheng
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jialan Ding
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Jiaxin Wu
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
| | - Fuyuan Zuo
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
| | - Gongwei Zhang
- College of Animal Science and Technology, Southwest University, Rongchang, Chongqing 402460, China; (X.L.); (J.Z.); (J.D.); (J.W.); (F.Z.)
- Beef Cattle Engineering and Technology Research Center of Chongqing, Southwest University, Rongchang, Chongqing 402460, China
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21
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Qi H, Yu F, Lü S, Damaris RN, Dong G, Yang P. Exploring domestication pattern in lotus: insights from dispensable genome assembly. FRONTIERS IN PLANT SCIENCE 2023; 14:1294033. [PMID: 38034573 PMCID: PMC10687544 DOI: 10.3389/fpls.2023.1294033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 11/01/2023] [Indexed: 12/02/2023]
Abstract
Lotus (Nelumbo nucifera Gaertn.), an important aquatic plant in horticulture and ecosystems, has been cultivated for more than 7000 years and domesticated into three different subgroups: flower lotus, rhizome lotus, and seed lotus. To explore the domesticated regions of each subgroup, re-sequencing data of 371 lotus accessions collected from the public database were aligned to the genome of 'China-Antique (CA)'. Unmapped reads were used to build the dispensable genome of each subgroup using a metagenome-like assembly strategy. More than 27 Mb of the dispensable genome in these three subgroups and the wild group was assembled, of which 11,761 genes were annotated. Some of the contigs in the dispensable genome were similar to the genomic segments of other lotus accessions other than 'CA'. The annotated genes in each subgroup played essential roles in specific developmental processes. Dissection of selective signals in three cultivated subgroups also demonstrated that subgroup-specific metabolic pathways, such as the brassinosteroids metabolism enrichment in FL, associated with these selected genes in each subgroup and the contigs in dispensable genome nearly located in the domesticated regions of each subgroup, respectively. Our data presented a valuable resource for facilitating lotus genomic studies, complemented the helpful information to the reference genome, and shed light on the selective signals of domesticated subgroups.
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Affiliation(s)
- Huanhuan Qi
- School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China
- State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China
| | - Feng Yu
- State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China
| | - Shiyou Lü
- State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China
| | | | - Guoqing Dong
- School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China
| | - Pingfang Yang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China
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22
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Wang T, Duan S, Xu C, Wang Y, Zhang X, Xu X, Chen L, Han Z, Wu T. Pan-genome analysis of 13 Malus accessions reveals structural and sequence variations associated with fruit traits. Nat Commun 2023; 14:7377. [PMID: 37968318 PMCID: PMC10651928 DOI: 10.1038/s41467-023-43270-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 11/06/2023] [Indexed: 11/17/2023] Open
Abstract
Structural variations (SVs) and copy number variations (CNVs) contribute to trait variations in fleshy-fruited species. Here, we assemble 10 genomes of genetically diverse Malus accessions, including the ever-green cultivar 'Granny Smith' and the widely cultivated cultivar 'Red Fuji'. Combining with three previously reported genomes, we assemble the pan-genome of Malus species and identify 20,220 CNVs and 317,393 SVs. We also observe CNVs that are positively correlated with expression levels of the genes they are associated with. Furthermore, we show that the noncoding RNA generated from a 209 bp insertion in the intron of mitogen-activated protein kinase homology encoding gene, MMK2, regulates the gene expression and affects fruit coloration. Moreover, we identify overlapping SVs associated with fruit quality and biotic resistance. This pan-genome uncovers possible contributions of CNVs to gene expression and highlights the role of SVs in apple domestication and economically important traits.
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Affiliation(s)
- Ting Wang
- College of Horticulture, China Agricultural University, Beijing, China
| | - Shiyao Duan
- Plant Science and Technology College, Beijing University of Agriculture, Beijing, China
| | - Chen Xu
- College of Horticulture, China Agricultural University, Beijing, China
| | - Yi Wang
- College of Horticulture, China Agricultural University, Beijing, China
| | - Xinzhong Zhang
- College of Horticulture, China Agricultural University, Beijing, China
| | - Xuefeng Xu
- College of Horticulture, China Agricultural University, Beijing, China
| | - Liyang Chen
- Smartgenomics Technology Institute, Tianjin, China
| | - Zhenhai Han
- College of Horticulture, China Agricultural University, Beijing, China.
| | - Ting Wu
- College of Horticulture, China Agricultural University, Beijing, China.
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23
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Saco A, Rey-Campos M, Gallardo-Escárate C, Gerdol M, Novoa B, Figueras A. Gene presence/absence variation in Mytilus galloprovincialis and its implications in gene expression and adaptation. iScience 2023; 26:107827. [PMID: 37744033 PMCID: PMC10514466 DOI: 10.1016/j.isci.2023.107827] [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: 05/16/2023] [Revised: 07/12/2023] [Accepted: 09/01/2023] [Indexed: 09/26/2023] Open
Abstract
Presence/absence variation (PAV) is a well-known phenomenon in prokaryotes that was described for the first time in bivalves in 2020 in Mytilus galloprovincialis. The objective of the present study was to further our understanding of the PAV phenomenon in mussel biology. The distribution of PAV was studied in a mussel chromosome-level genome assembly, revealing a widespread distribution but with hotspots of dispensability. Special attention was given to the effect of PAV in gene expression, since dispensable genes were found to be inherently subject to distortions due to their sparse distribution among individuals. Furthermore, the high expression and strong tissue specificity of some dispensable genes, such as myticins, strongly supported their biological relevance. The significant differences in the repertoire of dispensable genes associated with two geographically distinct populations suggest that PAV is involved in local adaptation. Overall, the PAV phenomenon would provide a key selective advantage at the population level.
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Affiliation(s)
- Amaro Saco
- Institute of Marine Research, Spanish National Research Council, Vigo, Spain
| | - Magalí Rey-Campos
- Institute of Marine Research, Spanish National Research Council, Vigo, Spain
| | | | - Marco Gerdol
- Department of Life Sciences, University of Trieste, Trieste, Italy
| | - Beatriz Novoa
- Institute of Marine Research, Spanish National Research Council, Vigo, Spain
| | - Antonio Figueras
- Institute of Marine Research, Spanish National Research Council, Vigo, Spain
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24
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Kang M, Wu H, Liu H, Liu W, Zhu M, Han Y, Liu W, Chen C, Song Y, Tan L, Yin K, Zhao Y, Yan Z, Lou S, Zan Y, Liu J. The pan-genome and local adaptation of Arabidopsis thaliana. Nat Commun 2023; 14:6259. [PMID: 37802986 PMCID: PMC10558531 DOI: 10.1038/s41467-023-42029-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 09/27/2023] [Indexed: 10/08/2023] Open
Abstract
Arabidopsis thaliana serves as a model species for investigating various aspects of plant biology. However, the contribution of genomic structural variations (SVs) and their associate genes to the local adaptation of this widely distribute species remains unclear. Here, we de novo assemble chromosome-level genomes of 32 A. thaliana ecotypes and determine that variable genes expand the gene pool in different ecotypes and thus assist local adaptation. We develop a graph-based pan-genome and identify 61,332 SVs that overlap with 18,883 genes, some of which are highly involved in ecological adaptation of this species. For instance, we observe a specific 332 bp insertion in the promoter region of the HPCA1 gene in the Tibet-0 ecotype that enhances gene expression, thereby promotes adaptation to alpine environments. These findings augment our understanding of the molecular mechanisms underlying the local adaptation of A. thaliana across diverse habitats.
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Affiliation(s)
- Minghui Kang
- State Key Laboratory of Grassland Agro-ecosystem, College of Ecology, Lanzhou University, Lanzhou, 730000, China
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Haolin Wu
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Huanhuan Liu
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Wenyu Liu
- State Key Laboratory of Grassland Agro-ecosystem, College of Ecology, Lanzhou University, Lanzhou, 730000, China
| | - Mingjia Zhu
- State Key Laboratory of Grassland Agro-ecosystem, College of Ecology, Lanzhou University, Lanzhou, 730000, China
| | - Yu Han
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Wei Liu
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Chunlin Chen
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Yan Song
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Luna Tan
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Kangqun Yin
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Yusen Zhao
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Zhen Yan
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Shangling Lou
- State Key Laboratory of Grassland Agro-ecosystem, College of Ecology, Lanzhou University, Lanzhou, 730000, China.
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China.
| | - Yanjun Zan
- Key Laboratory of Tobacco Improvement and Biotechnology, Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao, 266000, China.
| | - Jianquan Liu
- State Key Laboratory of Grassland Agro-ecosystem, College of Ecology, Lanzhou University, Lanzhou, 730000, China.
- Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China.
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25
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Contreras-Moreira B, Saraf S, Naamati G, Casas AM, Amberkar SS, Flicek P, Jones AR, Dyer S. GET_PANGENES: calling pangenes from plant genome alignments confirms presence-absence variation. Genome Biol 2023; 24:223. [PMID: 37798615 PMCID: PMC10552430 DOI: 10.1186/s13059-023-03071-z] [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: 06/07/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023] Open
Abstract
Crop pangenomes made from individual cultivar assemblies promise easy access to conserved genes, but genome content variability and inconsistent identifiers hamper their exploration. To address this, we define pangenes, which summarize a species coding potential and link back to original annotations. The protocol get_pangenes performs whole genome alignments (WGA) to call syntenic gene models based on coordinate overlaps. A benchmark with small and large plant genomes shows that pangenes recapitulate phylogeny-based orthologies and produce complete soft-core gene sets. Moreover, WGAs support lift-over and help confirm gene presence-absence variation. Source code and documentation: https://github.com/Ensembl/plant-scripts .
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Affiliation(s)
- Bruno Contreras-Moreira
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
- Estación Experimental Aula Dei-CSIC, 50059, Zaragoza, Spain.
| | - Shradha Saraf
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Guy Naamati
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Ana M Casas
- Estación Experimental Aula Dei-CSIC, 50059, Zaragoza, Spain
| | - Sandeep S Amberkar
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Andrew R Jones
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Sarah Dyer
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
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26
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Lyu X, Xia Y, Wang C, Zhang K, Deng G, Shen Q, Gao W, Zhang M, Liao N, Ling J, Bo Y, Hu Z, Yang J, Zhang M. Pan-genome analysis sheds light on structural variation-based dissection of agronomic traits in melon crops. PLANT PHYSIOLOGY 2023; 193:1330-1348. [PMID: 37477947 DOI: 10.1093/plphys/kiad405] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 06/21/2023] [Indexed: 07/22/2023]
Abstract
Sweetness and appearance of fresh fruits are key palatable and preference attributes for consumers and are often controlled by multiple genes. However, fine-mapping the key loci or genes of interest by single genome-based genetic analysis is challenging. Herein, we present the chromosome-level genome assembly of 1 landrace melon accession (Cucumis melo ssp. agrestis) with wild morphologic features and thus construct a melon pan-genome atlas via integrating sequenced melon genome datasets. Our comparative genomic analysis reveals a total of 3.4 million genetic variations, of which the presence/absence variations (PAVs) are mainly involved in regulating the function of genes for sucrose metabolism during melon domestication and improvement. We further resolved several loci that are accountable for sucrose contents, flesh color, rind stripe, and suture using a structural variation (SV)-based genome-wide association study. Furthermore, via bulked segregation analysis (BSA)-seq and map-based cloning, we uncovered that a single gene, (CmPIRL6), determines the edible or inedible characteristics of melon fruit exocarp. These findings provide important melon pan-genome information and provide a powerful toolkit for future pan-genome-informed cultivar breeding of melon.
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Affiliation(s)
- Xiaolong Lyu
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Yuelin Xia
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Chenhao Wang
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Kejia Zhang
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Guancong Deng
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Qinghui Shen
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Wei Gao
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
- Hainan Institute, Zhejiang University, Yazhou District, Sanya 572025, China
| | - Mengyi Zhang
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
- Hainan Institute, Zhejiang University, Yazhou District, Sanya 572025, China
| | - Nanqiao Liao
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Jian Ling
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China
| | - Yongming Bo
- Key Laboratory of Vegetable Breeding, Ningbo Weimeng Seed Co., Ltd, Ningbo 315100, China
| | - Zhongyuan Hu
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
- Hainan Institute, Zhejiang University, Yazhou District, Sanya 572025, China
- Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Ministry of Agriculture, Hangzhou 310058, China
| | - Jinghua Yang
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
- Hainan Institute, Zhejiang University, Yazhou District, Sanya 572025, China
- Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Ministry of Agriculture, Hangzhou 310058, China
| | - Mingfang Zhang
- Laboratory of Germplasm Innovation and Molecular Breeding, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
- Hainan Institute, Zhejiang University, Yazhou District, Sanya 572025, China
- Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Ministry of Agriculture, Hangzhou 310058, China
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Naithani S, Deng CH, Sahu SK, Jaiswal P. Exploring Pan-Genomes: An Overview of Resources and Tools for Unraveling Structure, Function, and Evolution of Crop Genes and Genomes. Biomolecules 2023; 13:1403. [PMID: 37759803 PMCID: PMC10527062 DOI: 10.3390/biom13091403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/29/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pan-genomes of several crops. The pan-genomes of crops constructed from various cultivars, accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novel genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding to mitigate the impact of global climate change. Here, we summarize the tools used for pan-genome assembly and annotations, web-portals hosting plant pan-genomes, etc. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and future potential of this emerging field of study.
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Affiliation(s)
- Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA;
| | - Cecilia H. Deng
- Molecular & Digital Breeing Group, New Cultivar Innovation, The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand;
| | - Sunil Kumar Sahu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China;
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA;
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28
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Dadras A, Fürst-Jansen JMR, Darienko T, Krone D, Scholz P, Sun S, Herrfurth C, Rieseberg TP, Irisarri I, Steinkamp R, Hansen M, Buschmann H, Valerius O, Braus GH, Hoecker U, Feussner I, Mutwil M, Ischebeck T, de Vries S, Lorenz M, de Vries J. Environmental gradients reveal stress hubs pre-dating plant terrestrialization. NATURE PLANTS 2023; 9:1419-1438. [PMID: 37640935 PMCID: PMC10505561 DOI: 10.1038/s41477-023-01491-0] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 07/11/2023] [Indexed: 08/31/2023]
Abstract
Plant terrestrialization brought forth the land plants (embryophytes). Embryophytes account for most of the biomass on land and evolved from streptophyte algae in a singular event. Recent advances have unravelled the first full genomes of the closest algal relatives of land plants; among the first such species was Mesotaenium endlicherianum. Here we used fine-combed RNA sequencing in tandem with a photophysiological assessment on Mesotaenium exposed to a continuous range of temperature and light cues. Our data establish a grid of 42 different conditions, resulting in 128 transcriptomes and ~1.5 Tbp (~9.9 billion reads) of data to study the combinatory effects of stress response using clustering along gradients. Mesotaenium shares with land plants major hubs in genetic networks underpinning stress response and acclimation. Our data suggest that lipid droplet formation and plastid and cell wall-derived signals have denominated molecular programmes since more than 600 million years of streptophyte evolution-before plants made their first steps on land.
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Affiliation(s)
- Armin Dadras
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
| | - Janine M R Fürst-Jansen
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
- Campus Institute Data Science, University of Goettingen, Goettingen, Germany
| | - Tatyana Darienko
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
| | - Denis Krone
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
| | - Patricia Scholz
- Albrecht-von-Haller-Institute for Plant Sciences, Department of Plant Biochemistry, University of Goettingen, Goettingen, Germany
| | - Siqi Sun
- Institute of Plant Biology and Biotechnology, Green Biotechnology, University of Münster, Münster, Germany
| | - Cornelia Herrfurth
- Albrecht-von-Haller-Institute for Plant Sciences, Department of Plant Biochemistry, University of Goettingen, Goettingen, Germany
- Goettingen Center for Molecular Biosciences, Service Unit for Metabolomics and Lipidomics, University of Goettingen, Goettingen, Germany
| | - Tim P Rieseberg
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
| | - Iker Irisarri
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
- Campus Institute Data Science, University of Goettingen, Goettingen, Germany
- Section Phylogenomics, Centre for Molecular Biodiversity Research, Leibniz Institute for the Analysis of Biodiversity Change, Museum of Nature, Hamburg, Germany
| | - Rasmus Steinkamp
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
| | - Maike Hansen
- Institute for Plant Sciences and Cluster of Excellence on Plant Sciences, Biocenter, University of Cologne, Cologne, Germany
| | - Henrik Buschmann
- Faculty of Applied Computer Sciences and Biosciences, Section Biotechnology and Chemistry, Molecular Biotechnology, University of Applied Sciences Mittweida, Mittweida, Germany
| | - Oliver Valerius
- Institute of Microbiology and Genetics and Göttingen Center for Molecular Biosciences and Service Unit LCMS Protein Analytics, Department of Molecular Microbiology and Genetics, University of Goettingen, Goettingen, Germany
| | - Gerhard H Braus
- Institute of Microbiology and Genetics and Göttingen Center for Molecular Biosciences and Service Unit LCMS Protein Analytics, Department of Molecular Microbiology and Genetics, University of Goettingen, Goettingen, Germany
| | - Ute Hoecker
- Institute for Plant Sciences and Cluster of Excellence on Plant Sciences, Biocenter, University of Cologne, Cologne, Germany
| | - Ivo Feussner
- Albrecht-von-Haller-Institute for Plant Sciences, Department of Plant Biochemistry, University of Goettingen, Goettingen, Germany
- Goettingen Center for Molecular Biosciences, Service Unit for Metabolomics and Lipidomics, University of Goettingen, Goettingen, Germany
- Goettingen Center for Molecular Biosciences, Department of Plant Biochemistry, University of Goettingen, Goettingen, Germany
| | - Marek Mutwil
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Till Ischebeck
- Institute of Plant Biology and Biotechnology, Green Biotechnology, University of Münster, Münster, Germany
| | - Sophie de Vries
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany
| | - Maike Lorenz
- Albrecht-von-Haller-Institute for Plant Sciences, Department of Experimental Phycology and SAG Culture Collection of Algae, University of Goettingen, Goettingen, Germany
| | - Jan de Vries
- Institute of Microbiology and Genetics, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany.
- Campus Institute Data Science, University of Goettingen, Goettingen, Germany.
- Goettingen Center for Molecular Biosciences, Department of Applied Bioinformatics, University of Goettingen, Goettingen, Germany.
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Glick L, Mayrose I. The Effect of Methodological Considerations on the Construction of Gene-Based Plant Pan-genomes. Genome Biol Evol 2023; 15:evad121. [PMID: 37401440 PMCID: PMC10340445 DOI: 10.1093/gbe/evad121] [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: 01/29/2023] [Revised: 06/21/2023] [Accepted: 06/28/2023] [Indexed: 07/05/2023] Open
Abstract
Pan-genomics is an emerging approach for studying the genetic diversity within plant populations. In contrast to common resequencing studies that compare whole genome sequencing data with a single reference genome, the construction of a pan-genome (PG) involves the direct comparison of multiple genomes to one another, thereby enabling the detection of genomic sequences and genes not present in the reference, as well as the analysis of gene content diversity. Although multiple studies describing PGs of various plant species have been published in recent years, a better understanding regarding the effect of the computational procedures used for PG construction could guide researchers in making more informed methodological decisions. Here, we examine the effect of several key methodological factors on the obtained gene pool and on gene presence-absence detections by constructing and comparing multiple PGs of Arabidopsis thaliana and cultivated soybean, as well as conducting a meta-analysis on published PGs. These factors include the construction method, the sequencing depth, and the extent of input data used for gene annotation. We observe substantial differences between PGs constructed using three common procedures (de novo assembly and annotation, map-to-pan, and iterative assembly) and that results are dependent on the extent of the input data. Specifically, we report low agreement between the gene content inferred using different procedures and input data. Our results should increase the awareness of the community to the consequences of methodological decisions made during the process of PG construction and emphasize the need for further investigation of commonly applied methodologies.
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Affiliation(s)
- Lior Glick
- Department of Life Sciences, School of Plant Sciences and Food Security, Tel-Aviv University, Tel Aviv, Israel
| | - Itay Mayrose
- Department of Life Sciences, School of Plant Sciences and Food Security, Tel-Aviv University, Tel Aviv, Israel
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30
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Resistance strategies for defense against Albugo candida causing white rust disease. Microbiol Res 2023; 270:127317. [PMID: 36805163 DOI: 10.1016/j.micres.2023.127317] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/12/2022] [Accepted: 02/01/2023] [Indexed: 02/11/2023]
Abstract
Albugo candida, the causal organism of white rust, is an oomycete obligate pathogen infecting crops of Brassicaceae family occurred on aerial part, including vegetable and oilseed crops at all growth stages. The disease expression is characterized by local infection appearing on the abaxial region developing white or creamy yellow blister (sori) on leaves and systemic infections cause hypertrophy and hyperplasia leading to stag-head of reproductive organ. To overcome this problem, several disease management strategies like fungicide treatments were used in the field and disease-resistant varieties have also been developed using conventional and molecular breeding. Due to high variability among A. candida isolates, there is no single approach available to understand the diverse spectrum of disease symptoms. In absence of resistance sources against pathogen, repetitive cultivation of genetically-similar varieties locally tends to attract oomycete pathogen causing heavy yield losses. In the present review, a deep insight into the underlying role of the non-host resistance (NHR) defence mechanism available in plants, and the strategies to exploit available gene pools from plant species that are non-host to A. candida could serve as novel sources of resistance. This work summaries the current knowledge pertaining to the resistance sources available in non-host germ plasm, the understanding of defence mechanisms and the advance strategies covers molecular, biochemical and nature-based solutions in protecting Brassica crops from white rust disease.
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Carballo J, Bellido AM, Selva JP, Zappacosta D, Gallo CA, Albertini E, Caccamo M, Echenique V. From tetraploid to diploid, a pangenomic approach to identify genes lost during synthetic diploidization of Eragrostis curvula. FRONTIERS IN PLANT SCIENCE 2023; 14:1133986. [PMID: 36993842 PMCID: PMC10040859 DOI: 10.3389/fpls.2023.1133986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 02/24/2023] [Indexed: 06/19/2023]
Abstract
INTRODUCTION In Eragrostis curvula, commonly known as weeping lovegrass, a synthetic diploidization event of the facultative apomictic tetraploid Tanganyika INTA cv. originated from the sexual diploid Victoria cv. Apomixis is an asexual reproduction by seeds in which the progeny is genetically identical to the maternal plant. METHODS To assess the genomic changes related to ploidy and to the reproductive mode occurring during diploidization, a mapping approach was followed to obtain the first E. curvula pangenome assembly. In this way, gDNA of Tanganyika INTA was extracted and sequenced in 2x250 Illumina pair-end reads and mapped against the Victoria genome assembly. The unmapped reads were used for variant calling, while the mapped reads were assembled using Masurca software. RESULTS The length of the assembly was 28,982,419 bp distributed in 18,032 contigs, and the variable genes annotated in these contigs rendered 3,952 gene models. Functional annotation of the genes showed that the reproductive pathway was differentially enriched. PCR amplification in gDNA and cDNA of Tanganyika INTA and Victoria was conducted to validate the presence/absence variation in five genes related to reproduction and ploidy. The polyploid nature of the Tanganyika INTA genome was also evaluated through the variant calling analysis showing the single nucleotide polymorphism (SNP) coverage and allele frequency distribution with a segmental allotetraploid pairing behavior. DISCUSSION The results presented here suggest that the genes were lost in Tanganyika INTA during the diploidization process that was conducted to suppress the apomictic pathway, affecting severely the fertility of Victoria cv.
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Affiliation(s)
- Jose Carballo
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Universidad Nacional del Sur-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
| | - Andrés Martin Bellido
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Universidad Nacional del Sur-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
| | - Juan Pablo Selva
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Universidad Nacional del Sur-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
- Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
| | - Diego Zappacosta
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Universidad Nacional del Sur-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
- Departamento de Agronomía, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
| | - Cristian Andres Gallo
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Universidad Nacional del Sur-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
| | - Emidio Albertini
- Dipartimento di Scienze Agrarie, Alimentari e Ambientali, Università degli Studi di Perugia, Perugia, Italy
| | | | - Viviana Echenique
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Universidad Nacional del Sur-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Bahía Blanca, Argentina
- Departamento de Agronomía, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
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32
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Abstract
Over the past decade, advances in plant genotyping have been critical in enabling the identification of genetic diversity, in understanding evolution, and in dissecting important traits in both crops and native plants. The widespread popularity of single-nucleotide polymorphisms (SNPs) has prompted significant improvements to SNP-based genotyping, including SNP arrays, genotyping by sequencing, and whole-genome resequencing. More recent approaches, including genotyping structural variants, utilizing pangenomes to capture species-wide genetic diversity and exploiting machine learning to analyze genotypic data sets, are pushing the boundaries of what plant genotyping can offer. In this chapter, we highlight these innovations and discuss how they will accelerate and advance future genotyping efforts.
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33
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Gladman N, Goodwin S, Chougule K, Richard McCombie W, Ware D. Era of gapless plant genomes: innovations in sequencing and mapping technologies revolutionize genomics and breeding. Curr Opin Biotechnol 2023; 79:102886. [PMID: 36640454 PMCID: PMC9899316 DOI: 10.1016/j.copbio.2022.102886] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/03/2022] [Accepted: 12/13/2022] [Indexed: 01/15/2023]
Abstract
Whole-genome sequencing and assembly have revolutionized plant genetics and molecular biology over the last two decades. However, significant shortcomings in first- and second-generation technology resulted in imperfect reference genomes: numerous and large gaps of low quality or undeterminable sequence in areas of highly repetitive DNA along with limited chromosomal phasing restricted the ability of researchers to characterize regulatory noncoding elements and genic regions that underwent recent duplication events. Recently, advances in long-read sequencing have resulted in the first gapless, telomere-to-telomere (T2T) assemblies of plant genomes. This leap forward has the potential to increase the speed and confidence of genomics and molecular experimentation while reducing costs for the research community.
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Affiliation(s)
- Nicholas Gladman
- U.S. Department of Agriculture-Agricultural Research Service, NEA Robert W. Holley Center for Agriculture and Health, 538 Tower Rd, Ithaca, NY 14853, USA; Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724 , USA
| | - Sara Goodwin
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724 , USA
| | - Kapeel Chougule
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724 , USA
| | | | - Doreen Ware
- U.S. Department of Agriculture-Agricultural Research Service, NEA Robert W. Holley Center for Agriculture and Health, 538 Tower Rd, Ithaca, NY 14853, USA; Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724 , USA.
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34
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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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35
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Voelker WG, Krishnan K, Chougule K, Alexander LC, Lu Z, Olson A, Ware D, Songsomboon K, Ponce C, Brenton ZW, Boatwright JL, Cooper EA. Ten new high-quality genome assemblies for diverse bioenergy sorghum genotypes. FRONTIERS IN PLANT SCIENCE 2023; 13:1040909. [PMID: 36684744 PMCID: PMC9846640 DOI: 10.3389/fpls.2022.1040909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 12/09/2022] [Indexed: 06/17/2023]
Abstract
Introduction Sorghum (Sorghum bicolor (L.) Moench) is an agriculturally and economically important staple crop that has immense potential as a bioenergy feedstock due to its relatively high productivity on marginal lands. To capitalize on and further improve sorghum as a potential source of sustainable biofuel, it is essential to understand the genomic mechanisms underlying complex traits related to yield, composition, and environmental adaptations. Methods Expanding on a recently developed mapping population, we generated de novo genome assemblies for 10 parental genotypes from this population and identified a comprehensive set of over 24 thousand large structural variants (SVs) and over 10.5 million single nucleotide polymorphisms (SNPs). Results We show that SVs and nonsynonymous SNPs are enriched in different gene categories, emphasizing the need for long read sequencing in crop species to identify novel variation. Furthermore, we highlight SVs and SNPs occurring in genes and pathways with known associations to critical bioenergy-related phenotypes and characterize the landscape of genetic differences between sweet and cellulosic genotypes. Discussion These resources can be integrated into both ongoing and future mapping and trait discovery for sorghum and its myriad uses including food, feed, bioenergy, and increasingly as a carbon dioxide removal mechanism.
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Affiliation(s)
- William G. Voelker
- Dept. of Bioinformatics & Genomics, University of North Carolina at Charlotte, Charlotte, NC, United States
- North Carolina Research Campus, Kannapolis, NC, United States
| | - Krittika Krishnan
- Dept. of Bioinformatics & Genomics, University of North Carolina at Charlotte, Charlotte, NC, United States
- North Carolina Research Campus, Kannapolis, NC, United States
| | - Kapeel Chougule
- Cold Spring Harbor Research Laboratory, Cold Spring Harbor, NY, United States
| | - Louie C. Alexander
- Dept. of Bioinformatics & Genomics, University of North Carolina at Charlotte, Charlotte, NC, United States
- North Carolina Research Campus, Kannapolis, NC, United States
| | - Zhenyuan Lu
- Cold Spring Harbor Research Laboratory, Cold Spring Harbor, NY, United States
| | - Andrew Olson
- Cold Spring Harbor Research Laboratory, Cold Spring Harbor, NY, United States
| | - Doreen Ware
- Cold Spring Harbor Research Laboratory, Cold Spring Harbor, NY, United States
- United States Department of Agriculture - Agricultural Research Service in the North Atlantic Area (USDA-ARS NAA), Robert W. Holley Center for Agriculture and Health, Ithaca, NY, United States
| | - Kittikun Songsomboon
- Dept. of Bioinformatics & Genomics, University of North Carolina at Charlotte, Charlotte, NC, United States
- North Carolina Research Campus, Kannapolis, NC, United States
| | - Cristian Ponce
- Dept. of Bioinformatics & Genomics, University of North Carolina at Charlotte, Charlotte, NC, United States
- North Carolina Research Campus, Kannapolis, NC, United States
| | - Zachary W. Brenton
- Carolina Seed Systems, Darlington, SC, United States
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
| | - J. Lucas Boatwright
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Dept. of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - Elizabeth A. Cooper
- Dept. of Bioinformatics & Genomics, University of North Carolina at Charlotte, Charlotte, NC, United States
- North Carolina Research Campus, Kannapolis, NC, United States
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Liu C, Wang Y, Peng J, Fan B, Xu D, Wu J, Cao Z, Gao Y, Wang X, Li S, Su Q, Zhang Z, Wang S, Wu X, Shang Q, Shi H, Shen Y, Wang B, Tian J. High-quality genome assembly and pan-genome studies facilitate genetic discovery in mung bean and its improvement. PLANT COMMUNICATIONS 2022; 3:100352. [PMID: 35752938 PMCID: PMC9700124 DOI: 10.1016/j.xplc.2022.100352] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 05/31/2022] [Accepted: 06/22/2022] [Indexed: 05/29/2023]
Abstract
Mung bean is an economically important legume crop species that is used as a food, consumed as a vegetable, and used as an ingredient and even as a medicine. To explore the genomic diversity of mung bean, we assembled a high-quality reference genome (Vrad_JL7) that was ∼479.35 Mb in size, with a contig N50 length of 10.34 Mb. A total of 40,125 protein-coding genes were annotated, representing ∼96.9% of the genetic region. We also sequenced 217 accessions, mainly landraces and cultivars from China, and identified 2,229,343 high-quality single-nucleotide polymorphisms (SNPs). Population structure revealed that the Chinese accessions diverged into two groups and were distinct from non-Chinese lines. Genetic diversity analysis based on genomic data from 750 accessions in 23 countries supported the hypothesis that mung bean was first domesticated in south Asia and introduced to east Asia probably through the Silk Road. We constructed the first pan-genome of mung bean germplasm and assembled 287.73 Mb of non-reference sequences. Among the genes, 83.1% were core genes and 16.9% were variable. Presence/absence variation (PAV) events of nine genes involved in the regulation of the photoperiodic flowering pathway were identified as being under selection during the adaptation process to promote early flowering in the spring. Genome-wide association studies (GWASs) revealed 2,912 SNPs and 259 gene PAV events associated with 33 agronomic traits, including a SNP in the coding region of the SWEET10 homolog (jg24043) involved in crude starch content and a PAV event in a large fragment containing 11 genes for color-related traits. This high-quality reference genome and pan-genome will provide insights into mung bean breeding.
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Affiliation(s)
- Changyou Liu
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Yan Wang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | | | - Baojie Fan
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Dongxu Xu
- Zhangjiakou Academy of Agricultural Sciences, Zhangjiakou 075300, China
| | - Jing Wu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Zhimin Cao
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Yunqing Gao
- Zhangjiakou Academy of Agricultural Sciences, Zhangjiakou 075300, China
| | - Xueqing Wang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Shutong Li
- Zhangjiakou Academy of Agricultural Sciences, Zhangjiakou 075300, China
| | - Qiuzhu Su
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Zhixiao Zhang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Shen Wang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Xingbo Wu
- Tropical Research and Education Center, Department of Environmental Horticulture, University of Florida, 18905 SW 280th St, Homestead, FL 33031, USA
| | - Qibing Shang
- Zhangjiakou Academy of Agricultural Sciences, Zhangjiakou 075300, China
| | - Huiying Shi
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | - Yingchao Shen
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China
| | | | - Jing Tian
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050035, China.
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Hameed A, Poznanski P, Nadolska-Orczyk A, Orczyk W. Graph Pangenomes Track Genetic Variants for Crop Improvement. Int J Mol Sci 2022; 23:13420. [PMID: 36362207 PMCID: PMC9659059 DOI: 10.3390/ijms232113420] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/28/2022] [Accepted: 10/29/2022] [Indexed: 09/08/2024] Open
Abstract
Global climate change and the urgency to transform crops require an exhaustive genetic evaluation. The large polyploid genomes of food crops, such as cereals, make it difficult to identify candidate genes with confirmed hereditary. Although genome-wide association studies (GWAS) have been proficient in identifying genetic variants that are associated with complex traits, the resolution of acquired heritability faces several significant bottlenecks such as incomplete detection of structural variants (SV), genetic heterogeneity, and/or locus heterogeneity. Consequently, a biased estimate is generated with respect to agronomically complex traits. The graph pangenomes have resolved this missing heritability and provide significant details in terms of specific loci segregating among individuals and evolving to variations. The graph pangenome approach facilitates crop improvements through genome-linked fast breeding.
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Affiliation(s)
| | | | | | - Waclaw Orczyk
- Plant Breeding and Acclimatization Institute-National Research Institute, Radzikow, 05-870 Blonie, Poland
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Zandberg JD, Fernandez CT, Danilevicz MF, Thomas WJW, Edwards D, Batley J. The Global Assessment of Oilseed Brassica Crop Species Yield, Yield Stability and the Underlying Genetics. PLANTS (BASEL, SWITZERLAND) 2022; 11:2740. [PMID: 36297764 PMCID: PMC9610009 DOI: 10.3390/plants11202740] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/08/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
The global demand for oilseeds is increasing along with the human population. The family of Brassicaceae crops are no exception, typically harvested as a valuable source of oil, rich in beneficial molecules important for human health. The global capacity for improving Brassica yield has steadily risen over the last 50 years, with the major crop Brassica napus (rapeseed, canola) production increasing to ~72 Gt in 2020. In contrast, the production of Brassica mustard crops has fluctuated, rarely improving in farming efficiency. The drastic increase in global yield of B. napus is largely due to the demand for a stable source of cooking oil. Furthermore, with the adoption of highly efficient farming techniques, yield enhancement programs, breeding programs, the integration of high-throughput phenotyping technology and establishing the underlying genetics, B. napus yields have increased by >450 fold since 1978. Yield stability has been improved with new management strategies targeting diseases and pests, as well as by understanding the complex interaction of environment, phenotype and genotype. This review assesses the global yield and yield stability of agriculturally important oilseed Brassica species and discusses how contemporary farming and genetic techniques have driven improvements.
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Affiliation(s)
- Jaco D. Zandberg
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | | | - Monica F. Danilevicz
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - William J. W. Thomas
- School of Biological Sciences, University of Western Australia, Perth, WA 6009, Australia
| | - David Edwards
- Center for Applied Bioinformatics, 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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Zia K, Rao MJ, Sadaqat M, Azeem F, Fatima K, Tahir ul Qamar M, Alshammari A, Alharbi M. Pangenome-wide analysis of cyclic nucleotide-gated channel (CNGC) gene family in citrus Spp. Revealed their intraspecies diversity and potential roles in abiotic stress tolerance. Front Genet 2022; 13:1034921. [PMID: 36303546 PMCID: PMC9593079 DOI: 10.3389/fgene.2022.1034921] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 09/27/2022] [Indexed: 11/27/2022] Open
Abstract
Cyclic nucleotide-gated channels (CNGC) gene family has been found to be involved in physiological processes including signaling pathways, environmental stresses, plant growth, and development. This gene family of non-selective cation channels is known to regulate the uptake of calcium and is reported in several plant species. The pangenome-wide studies enable researchers to understand the genetic diversity comprehensively; as a comparative analysis of multiple plant species or member of a species at once helps to better understand the evolutionary relationships and diversity present among them. In the current study, pangenome-wide analysis of the CNGC gene family has been performed on five Citrus species. As a result, a total of 32 genes in Citrus sinensis, 27 genes in Citrus recticulata, 30 genes in Citrus grandis, 31 genes in Atalantia buxfolia, and 30 genes in Poncirus trifoliata were identified. In addition, two unique genes CNGC13 and CNGC14 were identified, which may have potential roles. All the identified CNGC genes were unevenly distributed on 9 chromosomes except P. trifoliata had genes distributed on 7 chromosomes and were classified into four major groups and two sub-groups namely I, II, III, IV-A, and IV-B. Cyclic nucleotide binding (CNB) motif, calmodulin-binding motif (CaMB), and motif for IQ-domain were conserved in Citrus Spp. Intron exon structures of citrus species were not exactly as same as the gene structures of Arabidopsis. The majority of cis-regulatory elements (CREs) were light responsive and others include growth, development, and stress-related indicating potential roles of the CNGC gene family in these functions. Both segmental and tandem duplication were involved in the expansion of the CNGC gene family in Citrus Spp. The miRNAs are involved in the response of CsCNGC genes towards drought stress along with having regulatory association in the expression of these genes. Protein- Protein interaction (PPI) analysis also showed the interaction of CNGC proteins with other CNGCs which suggested their potential role in pathways regulating different biological processes. GO enrichment revealed that CNGC genes were involved in the transport of ions across membranes. Furthermore, tissue-specific expression patterns of leaves sample of C. sinensis were studied under drought stress. Out of 32 genes of C. sinensis 3 genes i.e., CsCNGC1.4, CsCNGC2.1, and CsCNGC4.2 were highly up-regulated, and only CsCNGC4.6 was highly down-regulated. The qRT-PCR analysis also showed that CNGC genes were highly expressed after treatment with drought stress, while gene expression was lower under controlled conditions. This work includes findings based on multiple genomes instead of one, therefore, this will provide more genomic information rather than single genome-based studies. These findings will serve as a basis for further functional insights into the CNGC gene family.
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Affiliation(s)
- Komal Zia
- Integrative Omics and Molecular Modeling Laboratory, Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Faisalabad, Pakistan
| | - Muhammad Junaid Rao
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi Key Laboratory of Sugarcane Biology, College of Agriculture, Guangxi University, Nanning, China
| | - Muhammad Sadaqat
- Integrative Omics and Molecular Modeling Laboratory, Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Faisalabad, Pakistan
| | - Farrukh Azeem
- Integrative Omics and Molecular Modeling Laboratory, Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Faisalabad, Pakistan
| | - Kinza Fatima
- Integrative Omics and Molecular Modeling Laboratory, Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Faisalabad, Pakistan
| | - Muhammad Tahir ul Qamar
- Integrative Omics and Molecular Modeling Laboratory, Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Faisalabad, Pakistan
- Department of Botany and Plant Sciences, University of California Riverside (UCR), Riverside, CA, United States
- *Correspondence: Muhammad Tahir ul Qamar,
| | - Abdulrahman Alshammari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Metab Alharbi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
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40
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Naranjo-Ortiz MA, Molina M, Fuentes D, Mixão V, Gabaldón T. Karyon: a computational framework for the diagnosis of hybrids, aneuploids, and other nonstandard architectures in genome assemblies. Gigascience 2022; 11:giac088. [PMID: 36205401 PMCID: PMC9540331 DOI: 10.1093/gigascience/giac088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 11/23/2021] [Accepted: 08/24/2022] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Recent technological developments have made genome sequencing and assembly highly accessible and widely used. However, the presence in sequenced organisms of certain genomic features such as high heterozygosity, polyploidy, aneuploidy, heterokaryosis, or extreme compositional biases can challenge current standard assembly procedures and result in highly fragmented assemblies. Hence, we hypothesized that genome databases must contain a nonnegligible fraction of low-quality assemblies that result from such type of intrinsic genomic factors. FINDINGS Here we present Karyon, a Python-based toolkit that uses raw sequencing data and de novo genome assembly to assess several parameters and generate informative plots to assist in the identification of nonchanonical genomic traits. Karyon includes automated de novo genome assembly and variant calling pipelines. We tested Karyon by diagnosing 35 highly fragmented publicly available assemblies from 19 different Mucorales (Fungi) species. CONCLUSIONS Our results show that 10 (28.57%) of the assemblies presented signs of unusual genomic configurations, suggesting that these are common, at least for some lineages within the Fungi.
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Affiliation(s)
- Miguel A Naranjo-Ortiz
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain
- Health and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
- Biology Department, Clark University, Worcester, MA 01610, USA
- Naturhistoriskmuseum, University of Oslo, Oslo 0562, Norway
| | - Manu Molina
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain
- Health and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
- Life Sciences Department, Barcelona Supercomputing Centre (BSC-CNS), Barcelona 08034, Spain
| | - Diego Fuentes
- Life Sciences Department, Barcelona Supercomputing Centre (BSC-CNS), Barcelona 08034, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona 08028, Spain
| | - Verónica Mixão
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain
- Health and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
- Life Sciences Department, Barcelona Supercomputing Centre (BSC-CNS), Barcelona 08034, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona 08028, Spain
| | - Toni Gabaldón
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain
- Health and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain
- Life Sciences Department, Barcelona Supercomputing Centre (BSC-CNS), Barcelona 08034, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona 08028, Spain
- ICREA, Pg. Lluís Companys 23, Barcelona 08010, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas, Barcelona 28029, Spain
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Yang T, Liu R, Luo Y, Hu S, Wang D, Wang C, Pandey MK, Ge S, Xu Q, Li N, Li G, Huang Y, Saxena RK, Ji Y, Li M, Yan X, He Y, Liu Y, Wang X, Xiang C, Varshney RK, Ding H, Gao S, Zong X. Improved pea reference genome and pan-genome highlight genomic features and evolutionary characteristics. Nat Genet 2022; 54:1553-1563. [PMID: 36138232 PMCID: PMC9534762 DOI: 10.1038/s41588-022-01172-2] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Accepted: 07/26/2022] [Indexed: 12/21/2022]
Abstract
Complete and accurate reference genomes and annotations provide fundamental resources for functional genomics and crop breeding. Here we report a de novo assembly and annotation of a pea cultivar ZW6 with contig N50 of 8.98 Mb, which features a 243-fold increase in contig length and evident improvements in the continuity and quality of sequence in complex repeat regions compared with the existing one. Genome diversity of 118 cultivated and wild pea demonstrated that Pisum abyssinicum is a separate species different from P. fulvum and P. sativum within Pisum. Quantitative trait locus analyses uncovered two known Mendel's genes related to stem length (Le/le) and seed shape (R/r) as well as some candidate genes for pod form studied by Mendel. A pan-genome of 116 pea accessions was constructed, and pan-genes preferred in P. abyssinicum and P. fulvum showed distinct functional enrichment, indicating the potential value of them as pea breeding resources in the future.
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Affiliation(s)
- Tao Yang
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Rong Liu
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yingfeng Luo
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Songnian Hu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Dong Wang
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Institute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences / Shandong Provincial Key Laboratory of Crop Genetic Improvement, Ecology and Physiology, Jinan, China
| | - Chenyu Wang
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Manish K Pandey
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Song Ge
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Quanle Xu
- College of Life Sciences, Northwest A&F University, Yangling, China
| | - Nana Li
- Institute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences / Shandong Provincial Key Laboratory of Crop Genetic Improvement, Ecology and Physiology, Jinan, China
- College of Life Science, Shandong Normal University, Jinan, China
| | - Guan Li
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuning Huang
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Rachit K Saxena
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Yishan Ji
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mengwei Li
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xin Yan
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuhua He
- Institute of Grain Crops, Yunnan Academy of Agricultural Sciences, Kunming, China
| | - Yujiao Liu
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China
- Qinghai Academy of Agricultural and Forestry Sciences, Xining, China
| | - Xuejun Wang
- Jiangsu Yanjiang Institute of Agricultural Sciences, Nantong, China
| | - Chao Xiang
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, China
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
- Murdoch's Centre for Crop and Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
| | - Hanfeng Ding
- Institute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences / Shandong Provincial Key Laboratory of Crop Genetic Improvement, Ecology and Physiology, Jinan, China.
- College of Life Science, Shandong Normal University, Jinan, China.
| | - Shenghan Gao
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
| | - Xuxiao Zong
- National Key Facility for Crop Gene Resources and Genetic Improvement / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
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Evolutionary divergence of duplicated genomes in newly described allotetraploid cottons. Proc Natl Acad Sci U S A 2022; 119:e2208496119. [PMID: 36122204 PMCID: PMC9522333 DOI: 10.1073/pnas.2208496119] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Wild relatives of domesticated plants provide a rich resource for crop improvement and a valuable comparative perspective for understanding genomic, physiological, and agricultural traits. Here, we provide high-quality reference genomes of one early domesticated form of the economically most important cotton species, Gossypium hirsutum, and two other wild species, to clarify evolutionary relationships and understand the genomic changes that characterize these species and their close relatives. We document abundant gene resources involved in adaptation to environmental challenges, highlighting the potential for introgression of favorable genes into domesticated cotton and for increasing resilience to climate variability. Our study complements other recent genomic analyses in the cotton genus and provides a valuable foundation for breeding improved cotton varieties. Allotetraploid cotton (Gossypium) species represents a model system for the study of plant polyploidy, molecular evolution, and domestication. Here, chromosome-scale genome sequences were obtained and assembled for two recently described wild species of tetraploid cotton, Gossypium ekmanianum [(AD)6, Ge] and Gossypium stephensii [(AD)7, Gs], and one early form of domesticated Gossypium hirsutum, race punctatum [(AD)1, Ghp]. Based on phylogenomic analysis, we provide a dated whole-genome level perspective for the evolution of the tetraploid Gossypium clade and resolved the evolutionary relationships of Gs, Ge, and domesticated G. hirsutum. We describe genomic structural variation that arose during Gossypium evolution and describe its correlates—including phenotypic differentiation, genetic isolation, and genetic convergence—that contributed to cotton biodiversity and cotton domestication. Presence/absence variation is prominent in causing cotton genomic structural variations. A presence/absence variation-derived gene encoding a phosphopeptide-binding protein is implicated in increasing fiber length during cotton domestication. The relatively unimproved Ghp offers the potential for gene discovery related to adaptation to environmental challenges. Expanded gene families enoyl-CoA δ isomerase 3 and RAP2-7 may have contributed to abiotic stress tolerance, possibly by targeting plant hormone-associated biochemical pathways. Our results generate a genomic context for a better understanding of cotton evolution and for agriculture.
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Anilkumar C, Sunitha NC, Devate NB, Ramesh S. Advances in integrated genomic selection for rapid genetic gain in crop improvement: a review. PLANTA 2022; 256:87. [PMID: 36149531 DOI: 10.1007/s00425-022-03996-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 09/11/2022] [Indexed: 06/16/2023]
Abstract
Genomic selection and its importance in crop breeding. Integration of GS with new breeding tools and developing SOP for GS to achieve maximum genetic gain with low cost and time. The success of conventional breeding approaches is not sufficient to meet the demand of a growing population for nutritious food and other plant-based products. Whereas, marker assisted selection (MAS) is not efficient in capturing all the favorable alleles responsible for economic traits in the process of crop improvement. Genomic selection (GS) developed in livestock breeding and then adapted to plant breeding promised to overcome the drawbacks of MAS and significantly improve complicated traits controlled by gene/QTL with small effects. Large-scale deployment of GS in important crops, as well as simulation studies in a variety of contexts, addressed G × E interaction effects and non-additive effects, as well as lowering breeding costs and time. The current study provides a complete overview of genomic selection, its process, and importance in modern plant breeding, along with insights into its application. GS has been implemented in the improvement of complex traits including tolerance to biotic and abiotic stresses. Furthermore, this review hypothesises that using GS in conjunction with other crop improvement platforms accelerates the breeding process to increase genetic gain. The objective of this review is to highlight the development of an appropriate GS model, the global open source network for GS, and trans-disciplinary approaches for effective accelerated crop improvement. The current study focused on the application of data science, including machine learning and deep learning tools, to enhance the accuracy of prediction models. Present study emphasizes on developing plant breeding strategies centered on GS combined with routine conventional breeding principles by developing GS-SOP to achieve enhanced genetic gain.
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Affiliation(s)
- C Anilkumar
- ICAR-National Rice Research Institute, Cuttack, India
| | - N C Sunitha
- University of Agricultural Sciences, Bangalore, India
| | | | - S Ramesh
- University of Agricultural Sciences, Bangalore, India.
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Lee JH, Venkatesh J, Jo J, Jang S, Kim GW, Kim JM, Han K, Ro N, Lee HY, Kwon JK, Kim YM, Lee TH, Choi D, Van Deynze A, Hill T, Kfir N, Freiman A, Davila Olivas NH, Elkind Y, Paran I, Kang BC. High-quality chromosome-scale genomes facilitate effective identification of large structural variations in hot and sweet peppers. HORTICULTURE RESEARCH 2022; 9:uhac210. [PMID: 36467270 PMCID: PMC9715575 DOI: 10.1093/hr/uhac210] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
Pepper (Capsicum annuum) is an important vegetable crop that has been subjected to intensive breeding, resulting in limited genetic diversity, especially for sweet peppers. Previous studies have reported pepper draft genome assemblies using short read sequencing, but their capture of the extent of large structural variants (SVs), such as presence-absence variants (PAVs), inversions, and copy-number variants (CNVs) in the complex pepper genome falls short. In this study, we sequenced the genomes of representative sweet and hot pepper accessions by long-read and/or linked-read methods and advanced scaffolding technologies. First, we developed a high-quality reference genome for the sweet pepper cultivar 'Dempsey' and then used the reference genome to identify SVs in 11 other pepper accessions and constructed a graph-based pan-genome for pepper. We annotated an average of 42 972 gene families in each pepper accession, defining a set of 19 662 core and 23 115 non-core gene families. The new pepper pan-genome includes informative variants, 222 159 PAVs, 12 322 CNVs, and 16 032 inversions. Pan-genome analysis revealed PAVs associated with important agricultural traits, including potyvirus resistance, fruit color, pungency, and pepper fruit orientation. Comparatively, a large number of genes are affected by PAVs, which is positively correlated with the high frequency of transposable elements (TEs), indicating TEs play a key role in shaping the genomic landscape of peppers. The datasets presented herein provide a powerful new genomic resource for genetic analysis and genome-assisted breeding for pepper improvement.
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Affiliation(s)
| | | | - Jinkwan Jo
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Siyoung Jang
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Geon Woo Kim
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Jung-Min Kim
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Koeun Han
- Vegetable Research Division, National Institute of Horticultural and Herbal Science, Rural Development Administration, Jeonju 55365, Republic of Korea
| | - Nayoung Ro
- National Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea
| | - Hea-Young Lee
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Jin-Kyung Kwon
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Yong-Min Kim
- Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Tae-Ho Lee
- Genomics Division, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea
| | - Doil Choi
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Allen Van Deynze
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Theresa Hill
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Nir Kfir
- NRGene, 5 Golda Meir St., Ness Ziona 7403649, Israel
| | - Aviad Freiman
- Top Seeds International Ltd. Moshav Sharona, 1523200, Israel
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45
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Naqvi RZ, Siddiqui HA, Mahmood MA, Najeebullah S, Ehsan A, Azhar M, Farooq M, Amin I, Asad S, Mukhtar Z, Mansoor S, Asif M. Smart breeding approaches in post-genomics era for developing climate-resilient food crops. FRONTIERS IN PLANT SCIENCE 2022; 13:972164. [PMID: 36186056 PMCID: PMC9523482 DOI: 10.3389/fpls.2022.972164] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 08/15/2022] [Indexed: 06/16/2023]
Abstract
Improving the crop traits is highly required for the development of superior crop varieties to deal with climate change and the associated abiotic and biotic stress challenges. Climate change-driven global warming can trigger higher insect pest pressures and plant diseases thus affecting crop production sternly. The traits controlling genes for stress or disease tolerance are economically imperative in crop plants. In this scenario, the extensive exploration of available wild, resistant or susceptible germplasms and unraveling the genetic diversity remains vital for breeding programs. The dawn of next-generation sequencing technologies and omics approaches has accelerated plant breeding by providing the genome sequences and transcriptomes of several plants. The availability of decoded plant genomes offers an opportunity at a glance to identify candidate genes, quantitative trait loci (QTLs), molecular markers, and genome-wide association studies that can potentially aid in high throughput marker-assisted breeding. In recent years genomics is coupled with marker-assisted breeding to unravel the mechanisms to harness better better crop yield and quality. In this review, we discuss the aspects of marker-assisted breeding and recent perspectives of breeding approaches in the era of genomics, bioinformatics, high-tech phonemics, genome editing, and new plant breeding technologies for crop improvement. In nutshell, the smart breeding toolkit in the post-genomics era can steadily help in developing climate-smart future food crops.
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46
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Yan M, Nie H, Wang Y, Wang X, Jarret R, Zhao J, Wang H, Yang J. Exploring and exploiting genetics and genomics for sweetpotato improvement: Status and perspectives. PLANT COMMUNICATIONS 2022; 3:100332. [PMID: 35643086 PMCID: PMC9482988 DOI: 10.1016/j.xplc.2022.100332] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 04/17/2022] [Accepted: 05/02/2022] [Indexed: 05/14/2023]
Abstract
Sweetpotato (Ipomoea batatas (L.) Lam.) is one of the most important root crops cultivated worldwide. Because of its adaptability, high yield potential, and nutritional value, sweetpotato has become an important food crop, particularly in developing countries. To ensure adequate crop yields to meet increasing demand, it is essential to enhance the tolerance of sweetpotato to environmental stresses and other yield-limiting factors. The highly heterozygous hexaploid genome of I. batatas complicates genetic studies and limits improvement of sweetpotato through traditional breeding. However, application of next-generation sequencing and high-throughput genotyping and phenotyping technologies to sweetpotato genetics and genomics research has provided new tools and resources for crop improvement. In this review, we discuss the genomics resources that are available for sweetpotato, including the current reference genome, databases, and available bioinformatics tools. We systematically review the current state of knowledge on the polyploid genetics of sweetpotato, including studies of its origin and germplasm diversity and the associated mapping of important agricultural traits. We then outline the conventional and molecular breeding approaches that have been applied to sweetpotato. Finally, we discuss future goals for genetic studies of sweetpotato and crop improvement via breeding in combination with state-of-the-art multi-omics approaches such as genomic selection and gene editing. These approaches will advance and accelerate genetic improvement of this important root crop and facilitate its sustainable global production.
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Affiliation(s)
- Mengxiao Yan
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China
| | - Haozhen Nie
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China
| | - Yunze Wang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xinyi Wang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | | | - Jiamin Zhao
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Hongxia Wang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China.
| | - Jun Yang
- Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China.
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47
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Lu W, Sui M, Zhao X, Jia H, Han D, Yan X, Han Y. Genome-Wide Identification of Candidate Genes Underlying Soluble Sugar Content in Vegetable Soybean ( Glycine max L.) via Association and Expression Analysis. FRONTIERS IN PLANT SCIENCE 2022; 13:930639. [PMID: 35991392 PMCID: PMC9387354 DOI: 10.3389/fpls.2022.930639] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 05/18/2022] [Indexed: 05/11/2023]
Abstract
Soluble sugar is a major indicator of the intrinsic quality of vegetable soybean [Glycine max (L.) Merr. ]. The improvement of soluble sugar content in soybean is very important due to its healthcare functions for humans. The genetic mechanism of soluble sugar in soybean is unclear. In this study, 278 diverse soybean accessions were utilized to identify the quantitative trait nucleotides (QTNs) for total soluble sugar content in soybean seeds based on a genome-wide association study (GWAS). A total of 25,921 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected for GWAS. Totally, thirteen QTNs associated with total soluble sugar content were identified, which were distributed on ten chromosomes. One hundred and fifteen genes near the 200-kb flanking region of these identified QTNs were considered candidate genes associated with total soluble sugar content in soybean seed. Gene-based association analysis and haplotype analysis were utilized to further identify the effect of candidate genes on total soluble sugar content. Totally, 84 SNPs from seventeen genes across four chromosomes were significantly associated with the total soluble sugar content. Among them, three SNPs from Glyma.02G292900 were identified at two locations, and other eighty-one SNPs from sixteen genes were detected at three locations. Furthermore, expression level analysis of candidate genes revealed that Glyma.02G293200 and Glyma.02G294900 were significantly positively associated with soluble sugar content and Glyma.02G294000 was significantly negatively associated with soluble sugar content. Six genes (i.e., Glyma.02G292600, Glyma.02G292700, Glyma.02G294000, Glyma.02G294300, Glyma.02G294400, and Glyma.15G264200) identified by GWAS were also detected by the analysis of differential expression genes based on soybean germplasms with higher and lower soluble sugar content. Among them, Glyma.02G294000 is the only gene that was identified by gene-based association analysis with total soluble sugar content and was considered an important candidate gene for soluble sugar content. These candidate genes and beneficial alleles would be useful for improving the soluble sugar content of soybean.
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Affiliation(s)
- Wencheng Lu
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Meinan Sui
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Xunchao Zhao
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Hongchang Jia
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Dezhi Han
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Xiaofei Yan
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Yingpeng Han
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
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48
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Hu G, Cheng L, Cheng Y, Mao W, Qiao Y, Lan Y. Pan-genome analysis of three main Chinese chestnut varieties. FRONTIERS IN PLANT SCIENCE 2022; 13:916550. [PMID: 35958219 PMCID: PMC9358723 DOI: 10.3389/fpls.2022.916550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 07/05/2022] [Indexed: 05/02/2023]
Abstract
Chinese chestnut (Castanea mollissima Blume) is one of the earliest domesticated plants of high nutritional and ecological value, yet mechanisms of C. mollissima underlying its growth and development are poorly understood. Although individual chestnut species differ greatly, the molecular basis of the formation of their characteristic traits remains unknown. Though the draft genomes of chestnut have been previously released, the pan-genome of different variety needs to be studied. We report the genome sequence of three cultivated varieties of chestnut herein, namely Hei-Shan-Zhai-7 (H7, drought-resistant variety), Yan-Hong (YH, easy-pruning variety), and Yan-Shan-Zao-Sheng (ZS, early-maturing variety), to expedite convenience and efficiency in its genetics-based breeding. We obtained three chromosome-level chestnut genome assemblies through a combination of Oxford Nanopore technology, Illumina HiSeq X, and Hi-C mapping. The final genome assemblies are 671.99 Mb (YH), 790.99 Mb (ZS), and 678.90 Mb (H7), across 12 chromosomes, with scaffold N50 sizes of 50.50 Mb (YH), 65.05 Mb (ZS), and 52.16 Mb (H7). Through the identification of homologous genes and the cluster analysis of gene families, we found that H7, YH and ZS had 159, 131, and 91 unique gene families, respectively, and there were 13,248 single-copy direct homologous genes in the three chestnut varieties. For the convenience of research, the chestnut genome database was constructed. Based on the results of gene family identification, the presence/absence variations (PAVs) information of the three sample genes was calculated, and a total of 2,364, 2,232, and 1,475 unique genes were identified in H7, YH and ZS, respectively. Our results suggest that the GBSS II-b gene family underwent expansion in chestnut (relative to nearest source species). Overall, we developed high-quality and well-annotated genome sequences of three C. mollissima varieties, which will facilitate clarifying the molecular mechanisms underlying important traits, and shortening the breeding process.
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Affiliation(s)
| | | | | | | | | | - Yanping Lan
- Engineering & Technology Research Center for Chestnut of National Forestry and Grassland Administration, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China) of Ministry of Agriculture, Beijing Engineering Research Center for Deciduous Fruit Trees, Institute of Forestry and Pomology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
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49
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Li W, Liu J, Zhang H, Liu Z, Wang Y, Xing L, He Q, Du H. Plant pan-genomics: recent advances, new challenges, and roads ahead. J Genet Genomics 2022; 49:833-846. [PMID: 35750315 DOI: 10.1016/j.jgg.2022.06.004] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 10/18/2022]
Abstract
Pan-genomics can encompass most of the genetic diversity of a species or population and has proved to be a powerful tool for studying genomic evolution and the origin and domestication of species, and for providing information for plant improvement. Plant genomics has greatly progressed because of improvements in sequencing technologies and the rapid reduction of sequencing costs. Nevertheless, pan-genomics still presents many challenges, including computationally intensive assembly methods, high costs with large numbers of samples, ineffective integration of big data, and difficulty in applying it to downstream multi-omics analysis and breeding research. In this review, we summarize the definition and recent achievements of plant pan-genomics, computational technologies used for pan-genome construction, and the applications of pan-genomes in plant genomics and molecular breeding. We also discuss challenges and perspectives for future pan-genomics studies and provide a detailed pipeline for sample selection, genome assembly and annotation, structural variation identification, and construction and application of graph-based pan-genomes. The aim is to provide important guidance for plant pan-genome research and a better understanding of the genetic basis of genome evolution, crop domestication, and phenotypic diversity for future studies.
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Affiliation(s)
- Wei Li
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Jianan Liu
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Hongyu Zhang
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Ze Liu
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Yu Wang
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Longsheng Xing
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Qiang He
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China
| | - Huilong Du
- School of Life Sciences, Institute of Life Sciences and Green Development, Hebei University, Baoding, Hebei 071000, China.
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50
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Yadav R, Kalia S, Rangan P, Pradheep K, Rao GP, Kaur V, Pandey R, Rai V, Vasimalla CC, Langyan S, Sharma S, Thangavel B, Rana VS, Vishwakarma H, Shah A, Saxena A, Kumar A, Singh K, Siddique KHM. Current Research Trends and Prospects for Yield and Quality Improvement in Sesame, an Important Oilseed Crop. FRONTIERS IN PLANT SCIENCE 2022; 13:863521. [PMID: 35599863 PMCID: PMC9120847 DOI: 10.3389/fpls.2022.863521] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 03/16/2022] [Indexed: 06/04/2023]
Abstract
Climate change is shifting agricultural production, which could impact the economic and cultural contexts of the oilseed industry, including sesame. Environmental threats (biotic and abiotic stresses) affect sesame production and thus yield (especially oil content). However, few studies have investigated the genetic enhancement, quality improvement, or the underlying mechanisms of stress tolerance in sesame. This study reveals the challenges faced by farmers/researchers growing sesame crops and the potential genetic and genomic resources for addressing the threats, including: (1) developing sesame varieties that tolerate phyllody, root rot disease, and waterlogging; (2) investigating beneficial agro-morphological traits, such as determinate growth, prostrate habit, and delayed response to seed shattering; (3) using wild relatives of sesame for wide hybridization; and (4) advancing existing strategies to maintain sesame production under changing climatic conditions. Future research programs need to add technologies and develop the best research strategies for economic and sustainable development.
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Affiliation(s)
- Rashmi Yadav
- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Sanjay Kalia
- Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi, India
| | - Parimalan Rangan
- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - K. Pradheep
- National Bureau of Plant Genetic Resources, Thrissur, India
| | - Govind Pratap Rao
- Indian Agricultural Research Institute, Pusa Campus, New Delhi, India
| | - Vikender Kaur
- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Renu Pandey
- Indian Agricultural Research Institute, Pusa Campus, New Delhi, India
| | - Vandna Rai
- National Institute for Plant Biotechnology, Pusa Campus, New Delhi, India
| | | | - Sapna Langyan
- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Sanjula Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Punjab, India
| | - Boopathi Thangavel
- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | | | | | - Anshuman Shah
- National Institute for Plant Biotechnology, Pusa Campus, New Delhi, India
| | - Abhishek Saxena
- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Ashok Kumar
- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Kuldeep Singh
- International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
| | - Kadambot H. M. Siddique
- The UWA School of Agriculture and Environment, The UWA Institute of Agriculture, The University of Western Australia (UWA), Perth, WA, Australia
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