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Fu S, Chen X, Wang K, Chen J, Zhou J, Yi W, Lyu M, Ye Z, Bu W. Shared phylogeographic patterns and environmental responses of co-distributed soybean pests: Insights from comparative phylogeographic studies of Riptortus pedestris and Riptortus linearis in the subtropics of East Asia. Mol Phylogenet Evol 2024; 195:108055. [PMID: 38485106 DOI: 10.1016/j.ympev.2024.108055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/31/2024] [Accepted: 03/07/2024] [Indexed: 03/19/2024]
Abstract
Comparative phylogeographic studies of closely related species sharing co-distribution areas can elucidate the role of shared historical factors and environmental changes in shaping their phylogeographic pattern. The bean bugs, Riptortus pedestris and Riptortus linearis, which both inhabit subtropical regions in East Asia, are recognized as highly destructive soybean pests. Many previous studies have investigated the biological characteristics, pheromones, chemicals and control mechanisms of these two pests, but few studies have explored their phylogeographic patterns and underlying factors. In this study, we generated a double-digest restriction site-associated DNA sequencing (ddRAD-seq) dataset to investigate phylogeographic patterns and construct ecological niche models (ENM) for both Riptortus species. Our findings revealed similar niche occupancies and population genetic structures between the two species, with each comprising two phylogeographic lineages (i.e., the mainland China and the Indochina Peninsula clades) that diverged approximately 0.1 and 0.3 million years ago, respectively. This divergence likely resulted from the combined effects of temperatures variation and geographical barriers in the mountainous regions of Southwest China. Further demographic history and ENM analyses suggested that both pests underwent rapid expansion prior to the Last Glacial Maximum (LGM). Furthermore, ENM predicts a northward shift of both pests into new soybean-producing regions due to global warming. Our study indicated that co-distribution soybean pests with overlapping ecological niches and similar life histories in subtropical regions of East Asia exhibit congruent phylogeographic and demographic patterns in response to shared historical biogeographic drivers.
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Affiliation(s)
- Siying Fu
- College of Life Sciences, Nankai University, Tianjin 300071, China
| | - Xin Chen
- College of Life Sciences, Cangzhou Normal University, Cangzhou, China(2)
| | - Kaibin Wang
- College of Life Sciences, Nankai University, Tianjin 300071, China
| | - Juhong Chen
- College of Life Sciences, Nankai University, Tianjin 300071, China
| | - Jiayue Zhou
- College of Life Sciences, Nankai University, Tianjin 300071, China
| | - Wenbo Yi
- Department of Biology, Xinzhou Normal University, Xinzhou, Shanxi, China(2)
| | - Minhua Lyu
- Nanchang University, Affiliated Hospital 1, Jiangxi, China(2)
| | - Zhen Ye
- College of Life Sciences, Nankai University, Tianjin 300071, China.
| | - Wenjun Bu
- College of Life Sciences, Nankai University, Tianjin 300071, China.
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2
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Niu Y, Yung WS, Sze CC, Wong FL, Li MW, Chung G, Lam HM. Developing an SNP dataset for efficiently evaluating soybean germplasm resources using the genome sequencing data of 3,661 soybean accessions. BMC Genomics 2024; 25:475. [PMID: 38745120 PMCID: PMC11092025 DOI: 10.1186/s12864-024-10382-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/06/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Single nucleotide polymorphism (SNP) markers play significant roles in accelerating breeding and basic crop research. Several soybean SNP panels have been developed. However, there is still a lack of SNP panels for differentiating between wild and cultivated populations, as well as for detecting polymorphisms within both wild and cultivated populations. RESULTS This study utilized publicly available resequencing data from over 3,000 soybean accessions to identify differentiating and highly conserved SNP and insertion/deletion (InDel) markers between wild and cultivated soybean populations. Additionally, a naturally occurring mutant gene library was constructed by analyzing large-effect SNPs and InDels in the population. CONCLUSION The markers obtained in this study are associated with numerous genes governing agronomic traits, thus facilitating the evaluation of soybean germplasms and the efficient differentiation between wild and cultivated soybeans. The natural mutant gene library permits the quick identification of individuals with natural mutations in functional genes, providing convenience for accelerating soybean breeding using reverse genetics.
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Affiliation(s)
- Yongchao Niu
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong SAR, China
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Wai-Shing Yung
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong SAR, China
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Ching-Ching Sze
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong SAR, China
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Fuk-Ling Wong
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong SAR, China
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Man-Wah Li
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong SAR, China
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Gyuhwa Chung
- Department of Biotechnology, Chonnam National University, Yeosu-Si, Republic of Korea
| | - Hon-Ming Lam
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong SAR, China.
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518000, China.
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong SAR, China.
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Fiscus CJ, Herniter IA, Tchamba M, Paliwal R, Muñoz-Amatriaín M, Roberts PA, Abberton M, Alaba O, Close TJ, Oyatomi O, Koenig D. The pattern of genetic variability in a core collection of 2,021 cowpea accessions. G3 (Bethesda) 2024:jkae071. [PMID: 38708794 DOI: 10.1093/g3journal/jkae071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 03/18/2024] [Indexed: 05/07/2024]
Abstract
Cowpea is a highly drought-adapted leguminous crop with great promise for improving agricultural sustainability and food security. Here, we report analyses derived from array-based genotyping of 2,021 accessions constituting a core subset of the world's largest cowpea collection, held at the International Institute of Tropical Agriculture (IITA) in Ibadan, Nigeria. We used this dataset to examine genetic variation and population structure in worldwide cowpea. We confirm that the primary pattern of population structure is two geographically defined subpopulations originating in West and East Africa, respectively, and that population structure is associated with shifts in phenotypic distribution. Furthermore, we establish the cowpea core collection as a resource for genome-wide association studies by mapping the genetic basis of several phenotypes, with a focus on seed coat pigmentation patterning and color. We anticipate that the genotyped IITA Cowpea Core Collection will serve as a powerful tool for mapping complex traits, facilitating the acceleration of breeding programs to enhance the resilience of this crop in the face of rapid global climate change.
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Affiliation(s)
- Christopher J Fiscus
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Ira A Herniter
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Marimagne Tchamba
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | - Rajneesh Paliwal
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | | | - Philip A Roberts
- Department of Nematology, University of California, Riverside, Riverside, CA 92521, USA
| | - Michael Abberton
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | - Oluwafemi Alaba
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Timothy J Close
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
- Institute for Integrative Genome Biology, University of California, Riverside, Riverside, CA 92521, USA
| | - Olaniyi Oyatomi
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | - Daniel Koenig
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
- Institute for Integrative Genome Biology, University of California, Riverside, Riverside, CA 92521, USA
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4
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Wang W, Duan J, Wang X, Feng X, Chen L, Clark CB, Swarm SA, Wang J, Lin S, Nelson RL, Meyers BC, Feng X, Ma J. Long noncoding RNAs underlie multiple domestication traits and leafhopper resistance in soybean. Nat Genet 2024:10.1038/s41588-024-01738-2. [PMID: 38684899 DOI: 10.1038/s41588-024-01738-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 03/28/2024] [Indexed: 05/02/2024]
Abstract
The origin and functionality of long noncoding RNA (lncRNA) remain poorly understood. Here, we show that multiple quantitative trait loci modulating distinct domestication traits in soybeans are pleiotropic effects of a locus composed of two tandem lncRNA genes. These lncRNA genes, each containing two inverted repeats, originating from coding sequences of the MYB genes, function in wild soybeans by generating clusters of small RNA (sRNA) species that inhibit the expression of their MYB gene relatives through post-transcriptional regulation. By contrast, the expression of lncRNA genes in cultivated soybeans is severely repressed, and, consequently, the corresponding MYB genes are highly expressed, shaping multiple distinct domestication traits as well as leafhopper resistance. The inverted repeats were formed before the divergence of the Glycine genus from the Phaseolus-Vigna lineage and exhibit strong structure-function constraints. This study exemplifies a type of target for selection during plant domestication and identifies mechanisms of lncRNA formation and action.
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Affiliation(s)
- Weidong Wang
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Jingbo Duan
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA
| | - Xutong Wang
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Xingxing Feng
- Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Liyang Chen
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA
| | - Chancelor B Clark
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA
| | - Stephen A Swarm
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Beck's Hybrids, Atlanta, IN, USA
| | - Jinbin Wang
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA
| | - Sen Lin
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA
| | - Randall L Nelson
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Blake C Meyers
- Genome Center and Department of Plant Sciences, University of California, Davis, Davis, CA, USA
| | - Xianzhong Feng
- Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China.
| | - Jianxin Ma
- Department of Agronomy, Purdue University, West Lafayette, IN, USA.
- Center for Plant Biology, Purdue University, West Lafayette, IN, USA.
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5
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Mishra S, Srivastava AK, Khan AW, Tran LSP, Nguyen HT. The era of panomics-driven gene discovery in plants. Trends Plant Sci 2024:S1360-1385(24)00063-3. [PMID: 38658292 DOI: 10.1016/j.tplants.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 03/01/2024] [Accepted: 03/08/2024] [Indexed: 04/26/2024]
Abstract
Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.
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Affiliation(s)
- Shefali Mishra
- Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai, Maharashtra 400085, India
| | - Ashish Kumar Srivastava
- Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai, Maharashtra 400085, India; Homi Bhabha National Institute, Mumbai 400094, India.
| | - Aamir W Khan
- Division of Plant Science and Technology and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211, USA
| | - Lam-Son Phan Tran
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, USA
| | - Henry T Nguyen
- Division of Plant Science and Technology and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211, USA.
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6
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Guo D, Jiang H, Xie L. An R2R3-MYB Transcriptional Factor LuMYB314 Associated with the Loss of Petal Pigmentation in Flax ( Linum usitatissimum L.). Genes (Basel) 2024; 15:511. [PMID: 38674445 PMCID: PMC11050253 DOI: 10.3390/genes15040511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/14/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
The loss of anthocyanin pigments is one of the most common evolutionary transitions in petal color, yet the genetic basis for these changes in flax remains largely unknown. In this study, we used crossing studies, a bulk segregant analysis, genome-wide association studies, a phylogenetic analysis, and transgenic testing to identify genes responsible for the transition from blue to white petals in flax. This study found no correspondence between the petal color and seed color, refuting the conclusion that a locus controlling the seed coat color is associated with the petal color, as reported in previous studies. The locus controlling the petal color was mapped using a BSA-seq analysis based on the F2 population. However, no significantly associated genomic regions were detected. Our genome-wide association study identified a highly significant QTL (BP4.1) on chromosome 4 associated with flax petal color in the natural population. The combination of a local Manhattan plot and an LD heat map identified LuMYB314, an R2R3-MYB transcription factor, as a potential gene responsible for the natural variations in petal color in flax. The overexpression of LuMYB314 in both Arabidopsis thaliana and Nicotiana tabacum resulted in anthocyanin deposition, indicating that LuMYB314 is a credible candidate gene for controlling the petal color in flax. Additionally, our study highlights the limitations of the BSA-seq method in low-linkage genomic regions, while also demonstrating the powerful detection capabilities of GWAS based on high-density genomic variation mapping. This study enhances our genetic insight into petal color variations and has potential breeding value for engineering LuMYB314 to develop colored petals, bast fibers, and seeds for multifunctional use in flax.
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Affiliation(s)
- Dongliang Guo
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China;
| | - Haixia Jiang
- Key Laboratory of Plant Stress Biology in Arid Land, College of Life Science, Xinjiang Normal University, Urumqi 830017, China;
| | - Liqiong Xie
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi 830017, China;
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7
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Li F, Sayama T, Yokota Y, Hiraga S, Hashiguchi M, Tanaka H, Akashi R, Ishimoto M. Assessing genetic diversity and geographical differentiation in a global collection of wild soybean (Glycine soja Sieb. et Zucc.) and assigning a mini-core collection. DNA Res 2024; 31:dsae009. [PMID: 38490815 PMCID: PMC11090131 DOI: 10.1093/dnares/dsae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 02/19/2024] [Accepted: 03/15/2024] [Indexed: 03/17/2024] Open
Abstract
Wild soybean (Glycine soja), the ancestor of the cultivated soybean (G. max), is a crucial resource for capturing the genetic diversity of soybean species. In this study, we used a set of 78 genome-wide microsatellite markers to analyse the genetic diversity and geographic differentiation patterns in a global collection of 2,050 G. soja accessions and a mini-core collection of G. max stored in two public seed banks. We observed a notable reduction in the genetic diversity of G. max compared with G. soja and identified a close phylogenetic relationship between G. max and a G. soja subpopulation located in central China. Furthermore, we revealed substantial genetic divergence between northern and southern subpopulations, accompanied by diminished genetic diversity in the northern subpopulations. Two clusters were discovered among the accessions from north-eastern China-one genetically close to those from South Korea and Southern Japan, and another close to those from Amur Oblast, Russia. Finally, 192 accessions were assigned to a mini-core collection of G. soja, retaining 73.8% of the alleles detected in the entire collection. This mini-core collection is accessible to those who need it, facilitating efficient evaluation and utilization of G. soja genetic resources in soybean breeding initiatives.
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Affiliation(s)
- Feng Li
- Division of Crop Design Research, Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Ibaraki 305-8602, Japan
| | - Takashi Sayama
- Division of Crop Design Research, Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Ibaraki 305-8602, Japan
- Western Region Agricultural Research Center, National Agricultural and Food Research Organization (NARO), Zentsuji, Kagawa 765-8508, Japan
| | - Yuko Yokota
- Division of Crop Design Research, Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Ibaraki 305-8602, Japan
| | - Susumu Hiraga
- Division of Crop Design Research, Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Ibaraki 305-8602, Japan
| | - Masatsugu Hashiguchi
- Faculty of Agriculture, University of Miyazaki, Gakuen-kibanadai-nishi-1-1, Miyazaki, 889-2192, Japan
| | - Hidenori Tanaka
- Faculty of Agriculture, University of Miyazaki, Gakuen-kibanadai-nishi-1-1, Miyazaki, 889-2192, Japan
| | - Ryo Akashi
- Faculty of Agriculture, University of Miyazaki, Gakuen-kibanadai-nishi-1-1, Miyazaki, 889-2192, Japan
| | - Masao Ishimoto
- Division of Crop Design Research, Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Ibaraki 305-8602, Japan
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Fang C, Du H, Wang L, Liu B, Kong F. Mechanisms underlying key agronomic traits and implications for molecular breeding in soybean. J Genet Genomics 2024; 51:379-393. [PMID: 37717820 DOI: 10.1016/j.jgg.2023.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 09/05/2023] [Accepted: 09/05/2023] [Indexed: 09/19/2023]
Abstract
Soybean (Glycine max [L.] Merr.) is an important crop that provides protein and vegetable oil for human consumption. As soybean is a photoperiod-sensitive crop, its cultivation and yield are limited by the photoperiodic conditions in the field. In contrast to other major crops, soybean has a special plant architecture and a special symbiotic nitrogen fixation system, representing two unique breeding directions. Thus, flowering time, plant architecture, and symbiotic nitrogen fixation are three critical or unique yield-determining factors. This review summarizes the progress made in our understanding of these three critical yield-determining factors in soybean. Meanwhile, we propose potential research directions to increase soybean production, discuss the application of genomics and genomic-assisted breeding, and explore research directions to address future challenges, particularly those posed by global climate changes.
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Affiliation(s)
- Chao Fang
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, Guangdong 510006, China
| | - Haiping Du
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, Guangdong 510006, China
| | - Lingshuang Wang
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, Guangdong 510006, China
| | - Baohui Liu
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, Guangdong 510006, China
| | - Fanjiang Kong
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, Guangdong 510006, China.
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9
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Xu L, Hao J, Lv M, Liu P, Ge Q, Zhang S, Yang J, Niu H, Wang Y, Xue Y, Lu X, Tang J, Zheng J, Gou M. A genome-wide association study identifies genes associated with cuticular wax metabolism in maize. Plant Physiol 2024; 194:2616-2630. [PMID: 38206190 DOI: 10.1093/plphys/kiae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/20/2023] [Accepted: 12/11/2023] [Indexed: 01/12/2024]
Abstract
The plant cuticle is essential in plant defense against biotic and abiotic stresses. To systematically elucidate the genetic architecture of maize (Zea mays L.) cuticular wax metabolism, 2 cuticular wax-related traits, the chlorophyll extraction rate (CER) and water loss rate (WLR) of 389 maize inbred lines, were investigated and a genome-wide association study (GWAS) was performed using 1.25 million single nucleotide polymorphisms (SNPs). In total, 57 nonredundant quantitative trait loci (QTL) explaining 5.57% to 15.07% of the phenotypic variation for each QTL were identified. These QTLs contained 183 genes, among which 21 strong candidates were identified based on functional annotations and previous publications. Remarkably, 3 candidate genes that express differentially during cuticle development encode β-ketoacyl-CoA synthase (KCS). While ZmKCS19 was known to be involved in cuticle wax metabolism, ZmKCS12 and ZmKCS3 functions were not reported. The association between ZmKCS12 and WLR was confirmed by resequencing 106 inbred lines, and the variation of WLR was significant between different haplotypes of ZmKCS12. In this study, the loss-of-function mutant of ZmKCS12 exhibited wrinkled leaf morphology, altered wax crystal morphology, and decreased C32 wax monomer levels, causing an increased WLR and sensitivity to drought. These results confirm that ZmKCS12 plays a vital role in maize C32 wax monomer synthesis and is critical for drought tolerance. In sum, through GWAS of 2 cuticular wax-associated traits, this study reveals comprehensively the genetic architecture in maize cuticular wax metabolism and provides a valuable reference for the genetic improvement of stress tolerance in maize.
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Affiliation(s)
- Liping Xu
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
| | - Jiaxin Hao
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Mengfan Lv
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Peipei Liu
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Qidong Ge
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Sainan Zhang
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Jianping Yang
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Hongbin Niu
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Yiru Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yadong Xue
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Xiaoduo Lu
- Institute of Advanced Agricultural Technology, Qilu Normal University, Jinan 250200, China
| | - Jihua Tang
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
| | - Jun Zheng
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Mingyue Gou
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
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10
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Chu L, Yang K, Chen C, Zhao B, Hou Y, Wang W, Zhao P, Wang K, Wang B, Xiao Y, Li Y, Li Y, Song Q, Liu B, Fan R, Bohra A, Yu J, Sonnenschein EC, Varshney RK, Tian Z, Jian J, Wan P. Chromosome-level reference genome and resequencing of 322 accessions reveal evolution, genomic imprint and key agronomic traits in adzuki bean. Plant Biotechnol J 2024. [PMID: 38497586 DOI: 10.1111/pbi.14337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 02/22/2024] [Accepted: 03/02/2024] [Indexed: 03/19/2024]
Abstract
Adzuki bean (Vigna angularis) is an important legume crop cultivated in over 30 countries worldwide. We developed a high-quality chromosome-level reference genome of adzuki bean cultivar Jingnong6 by combining PacBio Sequel long-read sequencing with short-read and Hi-C technologies. The assembled genome covers 97.8% of the adzuki bean genome with a contig N50 of approximately 16 Mb and a total of 32 738 protein-coding genes. We also generated a comprehensive genome variation map of adzuki bean by whole-genome resequencing (WGRS) of 322 diverse adzuki beans accessions including both wild and cultivated. Furthermore, we have conducted comparative genomics and a genome-wide association study (GWAS) on key agricultural traits to investigate the evolution and domestication. GWAS identified several candidate genes, including VaCycA3;1, VaHB15, VaANR1 and VaBm, that exhibited significant associations with domestication traits. Furthermore, we conducted functional analyses on the roles of VaANR1 and VaBm in regulating seed coat colour. We provided evidence for the highest genetic diversity of wild adzuki (Vigna angularis var. nipponensis) in China with the presence of the most original wild adzuki bean, and the occurrence of domestication process facilitating transition from wild to cultigen. The present study elucidates the genetic basis of adzuki bean domestication traits and provides crucial genomic resources to support future breeding efforts in adzuki bean.
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Affiliation(s)
- Liwei Chu
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
- College of Life and Health, Dalian University, Dalian, Liaoning, China
| | - Kai Yang
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | | | - Bo Zhao
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Yanan Hou
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | | | - Pu Zhao
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Kaili Wang
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Binhu Wang
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Ying Xiao
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Yongqiang Li
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Yisong Li
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, USDA-ARS, Beltsville, Maryland, USA
| | - Biao Liu
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Ruoxi Fan
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | - Abhishek Bohra
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Jianping Yu
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
| | | | - Rajeev K Varshney
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Jianbo Jian
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Ping Wan
- College of Plant Science and Technology, Key Laboratory of New Technology in Agricultural Application, Beijing University of Agriculture, Beijing, China
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11
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Habib Z, Ijaz S, Haq IU, Hashem A, Avila-Quezada GD, Abd_Allah EF, Khan NA. Empirical phenotyping and genome-wide association study reveal the association of panicle architecture with yield in Chenopodium quinoa. Front Microbiol 2024; 15:1349239. [PMID: 38562468 PMCID: PMC10982352 DOI: 10.3389/fmicb.2024.1349239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/27/2024] [Indexed: 04/04/2024] Open
Abstract
Chenopodium quinoa manifests adaptability to grow under varying agro-climatic scenarios. Assessing quinoa germplasm's phenotypic and genetic variability is a prerequisite for introducing it as a potential candidate in cropping systems. Adaptability is the basic outcome of ecological genomics of crop plants. Adaptive variation predicted with a genome-wide association study provides a valuable basis for marker-assisted breeding. Hence, a panel of 72 quinoa plants was phenotyped for agro morphological attributes and association-mapping for distinct imperative agronomic traits. Inter simple sequence repeat (ISSR) markers were employed to assess genetic relatedness and population structure. Heatmap analysis showed three genotypes were early maturing, and six genotypes were attributed for highest yield. The SD-121-07 exhibited highest yield per plant possessing green, glomerulate shaped, compact density panicle with less leaves. However, SJrecm-03 yielded less exhibiting pink, intermediate shape, intermediate density panicles with less leaves. The phenotyping revealed strong correlation of panicle architecture with yield in quinoa. A genome-wide association study unraveled the associations between ISSR makers and agro-morphological traits. Mixed linear modes analysis yielded nine markers associated with eight traits at p ≤ 0.01. Moreover, ISSR markers significantly associated with panicle shape and leafiness were also associated with yield per plant. These findings contribute to the provision of authenticity for marker-assisted selection that ultimately would support quinoa breeding programs.
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Affiliation(s)
- Zakia Habib
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan
| | - Siddra Ijaz
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan
| | - Imran Ul Haq
- Department of Plant Pathology, University of Agriculture, Faisalabad, Pakistan
| | - Abeer Hashem
- Botany and Microbiology Department, College of Science, King Saud University, Riyadh, Saudi Arabia
| | | | - Elsayed Fathi Abd_Allah
- Plant Production Department, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Nasir Ahmad Khan
- Department of Plant Pathology, University of Agriculture, Faisalabad, Pakistan
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12
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Zong C, Zhao J, Wang Y, Wang L, Chen Z, Qi Y, Bai Y, Li W, Wang W, Ren H, Du W, Gai J. Identification of Gene-Allele System Conferring Alkali-Tolerance at Seedling Stage in Northeast China Soybean Germplasm. Int J Mol Sci 2024; 25:2963. [PMID: 38474209 DOI: 10.3390/ijms25052963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/22/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Salinization of cultivated soils may result in either high salt levels or alkaline conditions, both of which stress crops and reduce performance. We sampled genotypes included in the Northeast China soybean germplasm population (NECSGP) to identify possible genes that affect tolerance to alkaline soil conditions. In this study, 361 soybean accessions collected in Northeast China were tested under 220 mM NaHCO3:Na2CO3 = 9:1 (pH = 9.8) to evaluate the alkali-tolerance (ATI) at the seedling stage in Mudanjiang, Heilongjiang, China. The restricted two-stage multi-locus model genome-wide association study (RTM-GWAS) with gene-allele sequences as markers (6503 GASMs) based on simplified genome resequencing (RAD-sequencing) was accomplished. From this analysis, 132 main effect candidate genes with 359 alleles and 35 Gene × Environment genes with 103 alleles were identified, explaining 90.93% and 2.80% of the seedling alkali-tolerance phenotypic variation, respectively. Genetic variability of ATI in NECSGP was observed primarily within subpopulations, especially in ecoregion B, from which 80% of ATI-tolerant accessions were screened out. The biological functions of 132 candidate genes were classified into eight functional categories (defense response, substance transport, regulation, metabolism-related, substance synthesis, biological process, plant development, and unknown function). From the ATI gene-allele system, six key genes-alleles were identified as starting points for further study on understanding the ATI gene network.
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Affiliation(s)
- Chunmei Zong
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Jinming Zhao
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Yanping Wang
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Lei Wang
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Zaoye Chen
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Yuxin Qi
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Yanfeng Bai
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Wen Li
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Wubin Wang
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Haixiang Ren
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Weiguang Du
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Junyi Gai
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
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13
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Liang X, Li J, Yang Y, Jiang C, Guo Y. Designing salt stress-resilient crops: Current progress and future challenges. J Integr Plant Biol 2024; 66:303-329. [PMID: 38108117 DOI: 10.1111/jipb.13599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 12/10/2023] [Accepted: 12/15/2023] [Indexed: 12/19/2023]
Abstract
Excess soil salinity affects large regions of land and is a major hindrance to crop production worldwide. Therefore, understanding the molecular mechanisms of plant salt tolerance has scientific importance and practical significance. In recent decades, studies have characterized hundreds of genes associated with plant responses to salt stress in different plant species. These studies have substantially advanced our molecular and genetic understanding of salt tolerance in plants and have introduced an era of molecular design breeding of salt-tolerant crops. This review summarizes our current knowledge of plant salt tolerance, emphasizing advances in elucidating the molecular mechanisms of osmotic stress tolerance, salt-ion transport and compartmentalization, oxidative stress tolerance, alkaline stress tolerance, and the trade-off between growth and salt tolerance. We also examine recent advances in understanding natural variation in the salt tolerance of crops and discuss possible strategies and challenges for designing salt stress-resilient crops. We focus on the model plant Arabidopsis (Arabidopsis thaliana) and the four most-studied crops: rice (Oryza sativa), wheat (Triticum aestivum), maize (Zea mays), and soybean (Glycine max).
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Affiliation(s)
- Xiaoyan Liang
- State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
| | - Jianfang Li
- State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100194, China
| | - Yongqing Yang
- State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100094, China
| | - Caifu Jiang
- State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100094, China
- Frontiers Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
| | - Yan Guo
- State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100094, China
- Frontiers Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
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14
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Lu Q, Huang L, Liu H, Garg V, Gangurde SS, Li H, Chitikineni A, Guo D, Pandey MK, Li S, Liu H, Wang R, Deng Q, Du P, Varshney RK, Liang X, Hong Y, Chen X. A genomic variation map provides insights into peanut diversity in China and associations with 28 agronomic traits. Nat Genet 2024; 56:530-540. [PMID: 38378864 DOI: 10.1038/s41588-024-01660-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 01/09/2024] [Indexed: 02/22/2024]
Abstract
Peanut (Arachis hypogaea L.) is an important allotetraploid oil and food legume crop. China is one of the world's largest peanut producers and consumers. However, genomic variations underlying the migration and divergence of peanuts in China remain unclear. Here we reported a genome-wide variation map based on the resequencing of 390 peanut accessions, suggesting that peanuts might have been introduced into southern and northern China separately, forming two cultivation centers. Selective sweep analysis highlights asymmetric selection between the two subgenomes during peanut improvement. A classical pedigree from South China offers a context for the examination of the impact of artificial selection on peanut genome. Genome-wide association studies identified 22,309 significant associations with 28 agronomic traits, including candidate genes for plant architecture and oil biosynthesis. Our findings shed light on peanut migration and diversity in China and provide valuable genomic resources for peanut improvement.
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Affiliation(s)
- Qing Lu
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China.
| | - Lu Huang
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Hao Liu
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Vanika Garg
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Sunil S Gangurde
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Haifen Li
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Annapurna Chitikineni
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Dandan Guo
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Manish K Pandey
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Shaoxiong Li
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Haiyan Liu
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Runfeng Wang
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Quanqing Deng
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Puxuan Du
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China
| | - Rajeev K Varshney
- WA State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia.
| | - Xuanqiang Liang
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China.
| | - Yanbin Hong
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China.
| | - Xiaoping Chen
- Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Centre of National Centre of Oilseed Crops Improvement, Guangzhou, China.
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15
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Li Y, Zhao W, Tang J, Yue X, Gu J, Zhao B, Li C, Chen Y, Yuan J, Lin Y, Li Y, Kong F, He J, Wang D, Zhao TJ, Wang ZY. Identification of the domestication gene GmCYP82C4 underlying the major quantitative trait locus for the seed weight in soybean. Theor Appl Genet 2024; 137:62. [PMID: 38418640 DOI: 10.1007/s00122-024-04571-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/30/2024] [Indexed: 03/02/2024]
Abstract
KEY MESSAGE A major quantitative trait locus (QTL) for the hundred-seed weight (HSW) was identified and confirmed in the two distinct soybean populations, and the target gene GmCYP82C4 underlying this locus was identified that significantly associated with soybean seed weight, and it was selected during the soybean domestication and improvement process. Soybean is a major oil crop for human beings and the seed weight is a crucial goal of soybean breeding. However, only a limited number of target genes underlying the quantitative trait loci (QTLs) controlling seed weight in soybean are known so far. In the present study, six loci associated with hundred-seed weight (HSW) were detected in the first population of 573 soybean breeding lines by genome-wide association study (GWAS), and 64 gene models were predicted in these candidate QTL regions. The QTL qHSW_1 exhibits continuous association signals on chromosome four and was also validated by region association study (RAS) in the second soybean population (409 accessions) with wild, landrace, and cultivar soybean accessions. There were seven genes in qHSW_1 candidate region by linkage disequilibrium (LD) block analysis, and only Glyma.04G035500 (GmCYP82C4) showed specifically higher expression in flowers, pods, and seeds, indicating its crucial role in the soybean seed development. Significant differences in HSW trait were detected when the association panels are genotyped by single-nucleotide polymorphisms (SNPs) in putative GmCYP82C4 promoter region. Eight haplotypes were generated by six SNPs in GmCYP82C4 in the second soybean population, and two superior haplotypes (Hap2 and Hap4) of GmCYP82C4 were detected with average HSW of 18.27 g and 18.38 g, respectively. The genetic diversity of GmCYP82C4 was analyzed in the second soybean population, and GmCYP82C4 was most likely selected during the soybean domestication and improvement process, leading to the highest proportion of Hap2 of GmCYP82C4 both in landrace and cultivar subpopulations. The QTLs and GmCYP82C4 identified in this study provide novel genetic resources for soybean seed weight trait, and the GmCYP82C4 could be used for soybean molecular breeding to develop desirable seed weight in the future.
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Affiliation(s)
- Yang Li
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Wenqian Zhao
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Jiajun Tang
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Xiuli Yue
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Jinbao Gu
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China
| | - Biyao Zhao
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China
| | - Cong Li
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China
| | - Yanhang Chen
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China
| | - Jianbo Yuan
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China
| | - Yan Lin
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China
| | - Yan Li
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Fanjiang Kong
- Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Jin He
- College of Agriculture, Guizhou University, Guiyang, China
| | - Dong Wang
- Key Laboratory of Molecular Biology and Gene Engineering in Jiangxi Province, College of Life Science, Nanchang University, Nanchang, China
| | - Tuan-Jie Zhao
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China.
| | - Zhen-Yu Wang
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, China.
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16
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Wang L, Niu F, Wang J, Zhang H, Zhang D, Hu Z. Genome-Wide Association Studies Prioritize Genes Controlling Seed Size and Reproductive Period Length in Soybean. Plants (Basel) 2024; 13:615. [PMID: 38475461 DOI: 10.3390/plants13050615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 02/12/2024] [Accepted: 02/14/2024] [Indexed: 03/14/2024]
Abstract
Hundred-seed weight (HSW) and reproductive period length (RPL) are two major agronomic traits critical for soybean production and adaptation. However, both traits are quantitatively controlled by multiple genes that have yet to be comprehensively elucidated due to the lack of major genes; thereby, the genetic basis is largely unknown. In the present study, we conducted comprehensive genome-wide association analyses (GWAS) of HSW and RPL with multiple sets of accessions that were phenotyped across different environments. The large-scale analysis led to the identification of sixty-one and seventy-four significant QTLs for HSW and RPL, respectively. An ortholog-based search analysis prioritized the most promising candidate genes for the QTLs, including nine genes (TTG2, BZR1, BRI1, ANT, KLU, EOD1/BB, GPA1, ABA2, and ABI5) for HSW QTLs and nine genes (such as AGL8, AGL9, TOC1, and COL4) and six known soybean flowering time genes (E2, E3, E4, Tof11, Tof12, and FT2b) for RPL QTLs. We also demonstrated that some QTLs were targeted during domestication to drive the artificial selection of both traits towards human-favored traits. Local adaptation likely contributes to the increased genomic diversity of the QTLs underlying RPL. The results provide additional insight into the genetic basis of HSW and RPL and prioritize a valuable resource of candidate genes that merits further investigation to reveal the complex molecular mechanism and facilitate soybean improvement.
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Affiliation(s)
- Le Wang
- State Key Laboratory of Black Soils Conservation and Utilization, Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin 150081, China
| | - Fu'an Niu
- Institute of Crop Breeding and Cultivation, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China
| | - Jinshe Wang
- National Innovation Centre for Bio-Breeding Industry, Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Hengyou Zhang
- State Key Laboratory of Black Soils Conservation and Utilization, Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin 150081, China
| | - Dan Zhang
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Zhenbin Hu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705, USA
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17
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Shao L, Qiao P, Wang J, Peng Y, Wang Y, Dong W, Li J. Comparative analysis of jujube and sour jujube gave insight into their difference in genetic diversity and suitable habitat. Front Genet 2024; 15:1322285. [PMID: 38380425 PMCID: PMC10878421 DOI: 10.3389/fgene.2024.1322285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/16/2024] [Indexed: 02/22/2024] Open
Abstract
Jujube (Ziziphus jujuba var. jujuba Mill.) and sour jujube (Z. jujuba var. spinosa (Bunge) Hu ex H.F.Chow.) are economically, nutritionally, and ecologically significant members of the Rhamnaceae family. Despite their importance, insufficient research on their genetics and habitats has impeded effective conservation and utilization. To address this knowledge gap, we conducted plastome sequencing, integrated distribution data from China, and assessed genetic diversity and suitable habitat. The plastomes of both species exhibited high conservation and low genetic diversity. A new-found 23 bp species-specific Indel in the petL-petG enabled us to develop a rapid Indel-based identification marker for species discrimination. Phylogenetic analysis and dating illuminated their genetic relationship, showing speciation occurred 6.9 million years ago, in a period of dramatic global temperature fluctuations. Substantial variations in suitable climatic conditions were observed, with the mean temperature of the coldest quarter as the primary factor influencing distributions (-3.16°C-12.73°C for jujube and -5.79°C to 4.11°C for sour jujube, suitability exceeding 0.6). Consequently, distinct conservation strategies are warranted due to differences in suitable habitats, with jujube having a broader distribution and sour jujube concentrated in Northern China. In conclusion, disparate habitats and climatic factors necessitate tailored conservation approaches. Comparing genetic diversity and developing rapid species-specific primers will further enhance the sustainable utilization of these valuable species.
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Affiliation(s)
- Lingzhi Shao
- School of Biology and Food Science, Hebei Normal University for Nationalities, Chengde, China
| | - Ping Qiao
- Dexing Research and Training Center of Chinese Medical Sciences, China Academy of Chinese Medical Sciences, Dexing, China
- State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jingyi Wang
- State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yanfang Peng
- School of Biology and Food Science, Hebei Normal University for Nationalities, Chengde, China
| | - Yiheng Wang
- State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China
| | - Wenpan Dong
- Laboratory of Systematic Evolution and Biogeography of Woody Plants, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, China
| | - Jie Li
- School of Biology and Food Science, Hebei Normal University for Nationalities, Chengde, China
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18
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Kohli M, Bansal H, Mishra GP, Dikshit HK, Reddappa SB, Roy A, Sinha SK, Shivaprasad K, Kumari N, Kumar A, Kumar RR, Nair RM, Aski M. Genome-wide association studies for earliness, MYMIV resistance, and other associated traits in mungbean ( Vigna radiata L. Wilczek) using genotyping by sequencing approach. PeerJ 2024; 12:e16653. [PMID: 38288464 PMCID: PMC10823994 DOI: 10.7717/peerj.16653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 11/20/2023] [Indexed: 02/01/2024] Open
Abstract
Yellow mosaic disease (YMD) remains a major constraint in mungbean (Vigna radiata (L.)) production; while short-duration genotypes offer multiple crop cycles per year and help in escaping terminal heat stress, especially during summer cultivation. A comprehensive genotyping by sequencing (GBS)-based genome-wide association studies (GWAS) analysis was conducted using 132 diverse mungbean genotypes for traits like flowering time, YMD resistance, soil plant analysis development (SPAD) value, trichome density, and leaf area. The frequency distribution revealed a wide range of values for all the traits. GBS studies identified 31,953 high-quality single nucleotide polymorphism (SNPs) across all 11 mungbean chromosomes and were used for GWAS. Structure analysis revealed the presence of two genetically distinct populations based on ΔK. The linkage disequilibrium (LD) varied throughout the chromosomes and at r2 = 0.2, the mean LD decay was estimated as 39.59 kb. Two statistical models, mixed linear model (MLM) and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) identified 44 shared SNPs linked with various candidate genes. Notable candidate genes identified include FPA for flowering time (VRADI10G01470; chr. 10), TIR-NBS-LRR for mungbean yellow mosaic India virus (MYMIV) resistance (VRADI09G06940; chr. 9), E3 ubiquitin-protein ligase RIE1 for SPAD value (VRADI07G28100; chr. 11), WRKY family transcription factor for leaf area (VRADI03G06560; chr. 3), and LOB domain-containing protein 21 for trichomes (VRADI06G04290; chr. 6). In-silico validation of candidate genes was done through digital gene expression analysis using Arabidopsis orthologous (compared with Vigna radiata genome). The findings provided valuable insight for marker-assisted breeding aiming for the development of YMD-resistant and early-maturing mungbean varieties.
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Affiliation(s)
- Manju Kohli
- Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India
- Genetics, Indian Agricultural Research Institute, Delhi, Delhi, India
| | - Hina Bansal
- Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India
| | | | | | | | - Anirban Roy
- Division of Plant Pathology, Indian Agricultural Research Institute, New Delhi, Delhi, India
| | - Subodh Kumar Sinha
- Biotechnology, National Institute of Plant Biotechnology, New Delhi, Delhi, India
| | - K.M. Shivaprasad
- Genetics, Indian Agricultural Research Institute, Delhi, Delhi, India
| | - Nikki Kumari
- Genetics, Indian Agricultural Research Institute, Delhi, Delhi, India
| | - Atul Kumar
- Division of Seed Science and Technology, Indian Agricultural Research Institute, New Delhi, Delhi, India
| | - Ranjeet R. Kumar
- Biochemistry, Indian Agricultural Research Institute, New Delhi, Delhi, India
| | | | - Muraleedhar Aski
- Genetics, Indian Agricultural Research Institute, Delhi, Delhi, India
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19
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Biová J, Kaňovská I, Chan YO, Immadi MS, Joshi T, Bilyeu K, Škrabišová M. Natural and artificial selection of multiple alleles revealed through genomic analyses. Front Genet 2024; 14:1320652. [PMID: 38259621 PMCID: PMC10801239 DOI: 10.3389/fgene.2023.1320652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 11/17/2023] [Indexed: 01/24/2024] Open
Abstract
Genome-to-phenome research in agriculture aims to improve crops through in silico predictions. Genome-wide association study (GWAS) is potent in identifying genomic loci that underlie important traits. As a statistical method, increasing the sample quantity, data quality, or diversity of the GWAS dataset positively impacts GWAS power. For more precise breeding, concrete candidate genes with exact functional variants must be discovered. Many post-GWAS methods have been developed to narrow down the associated genomic regions and, ideally, to predict candidate genes and causative mutations (CMs). Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. With higher diversity and more extensive GWAS datasets, there is an increased chance of multiple alleles with independent CMs in a single causal gene. This can be caused by the presence of samples from geographically isolated regions that arose during natural or artificial selection. This simple fact is a complicating factor in GWAS-driven discoveries. Currently, none of the existing association methods address this issue and need to identify multiple alleles and, more specifically, the actual CMs. Therefore, we developed a tool that computes a score for a combination of variant positions in a single candidate gene and, based on the highest score, identifies the best number and combination of CMs. The tool is publicly available as a Python package on GitHub, and we further created a web-based Multiple Alleles discovery (MADis) tool that supports soybean and is hosted in SoyKB (https://soykb.org/SoybeanMADisTool/). We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. Finally, we identified a candidate gene for the pod color L2 locus and predicted the existence of multiple alleles that potentially cause loss of pod pigmentation. In this work, we show how a genomic analysis can be employed to explore the natural and artificial selection of multiple alleles and, thus, improve and accelerate crop breeding in agriculture.
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Affiliation(s)
- Jana Biová
- Department of Biochemistry, Faculty of Science, Palacký University in Olomouc, Olomouc, Czechia
| | - Ivana Kaňovská
- Department of Biochemistry, Faculty of Science, Palacký University in Olomouc, Olomouc, Czechia
| | - Yen On Chan
- MU Institute for Data Science and Informatics, University of Missouri-Columbia, Columbia, MO, United States
- Christopher S. Bond Life Sciences Center, University of Missouri-Columbia, Columbia, MO, United States
| | - Manish Sridhar Immadi
- Department of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, MO, United States
| | - Trupti Joshi
- MU Institute for Data Science and Informatics, University of Missouri-Columbia, Columbia, MO, United States
- Christopher S. Bond Life Sciences Center, University of Missouri-Columbia, Columbia, MO, United States
- Department of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, MO, United States
- Department of Biomedical Informatics, Biostatistics and Medical Epidemiology, University of Missouri-Columbia, Columbia, MO, United States
| | - Kristin Bilyeu
- United States Department of Agriculture-Agricultural Research Service, Plant Genetics Research Unit, Columbia, MO, United States
| | - Mária Škrabišová
- Department of Biochemistry, Faculty of Science, Palacký University in Olomouc, Olomouc, Czechia
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20
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Naqvi RZ, Mahmood MA, Mansoor S, Amin I, Asif M. Omics-driven exploration and mining of key functional genes for the improvement of food and fiber crops. Front Plant Sci 2024; 14:1273859. [PMID: 38259913 PMCID: PMC10800452 DOI: 10.3389/fpls.2023.1273859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 12/08/2023] [Indexed: 01/24/2024]
Abstract
The deployment of omics technologies has obtained an incredible boost over the past few decades with the advances in next-generation sequencing (NGS) technologies, innovative bioinformatics tools, and the deluge of available biological information. The major omics technologies in the limelight are genomics, transcriptomics, proteomics, metabolomics, and phenomics. These biotechnological advances have modernized crop breeding and opened new horizons for developing crop varieties with improved traits. The genomes of several crop species are sequenced, and a huge number of genes associated with crucial economic traits have been identified. These identified genes not only provide insights into the understanding of regulatory mechanisms of crop traits but also decipher practical grounds to assist in the molecular breeding of crops. This review discusses the potential of omics technologies for the acquisition of biological information and mining of the genes associated with important agronomic traits in important food and fiber crops, such as wheat, rice, maize, potato, tomato, cassava, and cotton. Different functional genomics approaches for the validation of these important genes are also highlighted. Furthermore, a list of genes discovered by employing omics approaches is being represented as potential targets for genetic modifications by the latest genome engineering methods for the development of climate-resilient crops that would in turn provide great impetus to secure global food security.
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Affiliation(s)
- Rubab Zahra Naqvi
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Muhammad Arslan Mahmood
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Shahid Mansoor
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
- International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan
| | - Imran Amin
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Muhammad Asif
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
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21
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Souza R, Rouf Mian MA, Vaughn JN, Li Z. Introgression of a Danbaekkong high-protein allele across different genetic backgrounds in soybean. Front Plant Sci 2023; 14:1308731. [PMID: 38173927 PMCID: PMC10761420 DOI: 10.3389/fpls.2023.1308731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024]
Abstract
Soybean meal is a major component of livestock feed due to its high content and quality of protein. Understanding the genetic control of protein is essential to develop new cultivars with improved meal protein. Previously, a genomic region on chromosome 20 significantly associated with elevated protein content was identified in the cultivar Danbaekkong. The present research aimed to introgress the Danbaekkong high-protein allele into elite lines with different genetic backgrounds by developing and deploying robust DNA markers. A multiparent population consisting of 10 F5-derived populations with a total of 1,115 recombinant inbred lines (RILs) was developed using "Benning HP" as the donor parent of the Danbaekkong high-protein allele. A new functional marker targeting the 321-bp insertion in the gene Glyma.20g085100 was developed and used to track the Danbaekkong high-protein allele across the different populations and enable assessment of its effect and stability. Across all populations, the high-protein allele consistently increased the content, with an increase of 3.3% in seed protein. A total of 103 RILs were selected from the multiparent population for yield testing in five environments to assess the impact of the high-protein allele on yield and to enable the selection of new breeding lines with high protein and high yield. The results indicated that the high-protein allele impacts yield negatively in general; however, it is possible to select high-yielding lines with high protein content. An analysis of inheritance of the Chr 20 high-protein allele in Danbaekkong indicated that it originated from a Glycine soja line (PI 163453) and is the same as other G. soja lines studied. A survey of the distribution of the allele across 79 G. soja accessions and 35 Glycine max ancestors of North American soybean cultivars showed that the high-protein allele is present in all G. soja lines evaluated but not in any of the 35 North American soybean ancestors. These results demonstrate that G. soja accessions are a valuable source of favorable alleles for improvement of protein composition.
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Affiliation(s)
- Renan Souza
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, United States
| | - M. A. Rouf Mian
- Soybean and Nitrogen Fixation Research Unit, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Raleigh, NC, United States
| | - Justin N. Vaughn
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, United States
- Genomics and Bioinformatics Research Unit, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Athens, GA, United States
| | - Zenglu Li
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, United States
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22
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He S, Li G, Zhang J, Ding Y, Wu H, Xie J, Wu H, Yang Z. The effect of environmental factors on the genetic differentiation of Cucurbita ficifolia populations based on whole-genome resequencing. BMC Plant Biol 2023; 23:647. [PMID: 38102604 PMCID: PMC10722772 DOI: 10.1186/s12870-023-04602-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Accepted: 11/10/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Cucurbita ficifolia is one of the squash species most resistant to fungal pathogens, and has especially high resistance to melon Fusarium wilt. This species is therefore an important germplasm resource for the breeding of squash and melon cultivars. RESULTS Whole-genome resequencing of 223 individuals from 32 populations in Yunnan Province, the main cucurbit production area in China, was performed and 3,855,120 single-nucleotide polymorphisms (SNPs) and 1,361,000 InDels were obtained. SNP analysis suggested that levels of genetic diversity in C. ficifolia were high, but that different populations showed no significant genetic differentiation or geographical structure, and that individual C. ficifolia plants with fruit rinds of a similar color did not form independent clusters. A Mantel test conducted in combination with geographical distance and environmental factors suggested that genetic distance was not correlated with geographical distance, but had a significant correlation with environmental distance. Further associations between the genetic data and five environmental factors were analyzed using whole-genome association analysis. SNPs associated with each environmental factor were investigated and genes 250 kb upstream and downstream from associated SNPs were annotated. Overall, 15 marker-trait-associated SNPs (MTAs) and 293 genes under environmental selection were identified. The identified genes were involved in cell membrane lipid metabolism, macromolecular complexes, catalytic activity and other related aspects. Ecological niche modeling was used to simulate the distribution of C. ficifolia across time, from the present and into the future. We found that the area suitable for C. ficifolia changed with the changing climate in different periods. CONCLUSIONS Resequencing of the C. ficifolia accessions has allowed identification of genetic markers, such as SNPs and InDels. The SNPs identified in this study suggest that environmental factors mediated the formation of the population structure of C. ficifolia in China. These SNPs and Indels might also contribute to the variation in important pathways of genes for important agronomic traits such as yield, disease resistance and stress tolerance. Moreover, the genome resequencing data and the genetic markers identified from 223 accessions provide insight into the genetic variation of the C. ficifolia germplasm and will facilitate a broad range of genetic studies.
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Affiliation(s)
- Shuilian He
- College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
- Key Laboratory of Vegetable Biology of Yunnan Province, College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
| | - Gengyun Li
- College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
| | - Jing Zhang
- College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
| | - Yumei Ding
- College of Food Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
| | - Hongzhi Wu
- College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
| | - Junjun Xie
- College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
| | - Hang Wu
- College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China
| | - Zhengan Yang
- College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China.
- Key Laboratory of Vegetable Biology of Yunnan Province, College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China.
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23
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Mastrangelo AM, Roncallo P, Matny O, Čegan R, Steffenson B, Echenique V, Šafář J, Battaglia R, Barabaschi D, Cattivelli L, Özkan H, Mazzucotelli E. A new wild emmer wheat panel allows to map new loci associated with resistance to stem rust at seedling stage. Plant Genome 2023:e20413. [PMID: 38087443 DOI: 10.1002/tpg2.20413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 09/26/2023] [Accepted: 10/18/2023] [Indexed: 01/21/2024]
Abstract
Wheat stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is a major wheat disease worldwide. A collection of 283 wild emmer wheat [Triticum turgidum L. subsp. dicoccoides (Körn. ex Asch. & Graebn.) Thell] accessions, representative of the entire Fertile Crescent region where wild emmer naturally occurs, was assembled, genotyped, and characterized for population structure, genetic diversity, and rate of linkage disequilibrium (LD) decay. Then, the collection was employed for mapping Pgt resistance genes, as a proof of concept of the effectiveness of genome-wide association studies in wild emmer. The collection was evaluated in controlled conditions for reaction to six common Pgt pathotypes (TPMKC, TTTTF, JRCQC, TRTTF, TTKSK/Ug99, and TKTTF). Most resistant accessions originated from the Southern Levant wild emmer lineage, with some showing a resistance reaction toward three to six tested races. Association analysis was conducted considering a 12K polymorphic single-nucleotide polymorphisms dataset, kinship relatedness between accessions, and population structure. Eleven significant marker-trait associations (MTA) were identified across the genome, which explained from 17% to up to 49% of phenotypic variance with an average 1.5 additive effect (based on the 1-9 scoring scale). The identified loci were either effective against single or multiple races. Some MTAs colocalized with known Pgt resistance genes, while others represent novel resistance loci useful for durum and bread wheat prebreeding. Candidate genes with an annotated function related to plant response to pathogens were identified at the regions linked to the resistance and defined according to the estimated small LD (about 126 kb), as typical of wild species.
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Affiliation(s)
- Anna Maria Mastrangelo
- Research Centre for Cereal and Industrial Crops, Council for Agricultural Research and Economics (CREA), Foggia, Italy
| | - Pablo Roncallo
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Departamento de Agronomía, Universidad Nacional del Sur (UNS)-CONICET, Bahía Blanca, Argentina
| | - Oadi Matny
- Department of Plant Pathology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Radim Čegan
- Centre of Plant Structural and Functional Genomics, Institute of Experimental Botany of the Czech Academy of Sciences, Olomouc, Czech Republic
- Department of Plant Developmental Genetics, Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic
| | - Brian Steffenson
- Department of Plant Pathology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Viviana Echenique
- Centro de Recursos Naturales Renovables de la Zona Semiárida (CERZOS), Departamento de Agronomía, Universidad Nacional del Sur (UNS)-CONICET, Bahía Blanca, Argentina
| | - Jan Šafář
- Centre of Plant Structural and Functional Genomics, Institute of Experimental Botany of the Czech Academy of Sciences, Olomouc, Czech Republic
| | - Raffaella Battaglia
- Research Centre for Genomics and Bioinformatics, Council for Agricultural Research and Economics (CREA), Fiorenzuola d'Arda, Italy
| | - Delfina Barabaschi
- Research Centre for Genomics and Bioinformatics, Council for Agricultural Research and Economics (CREA), Fiorenzuola d'Arda, Italy
| | - Luigi Cattivelli
- Research Centre for Genomics and Bioinformatics, Council for Agricultural Research and Economics (CREA), Fiorenzuola d'Arda, Italy
| | - Hakan Özkan
- Faculty of Agriculture, Department of Field Crops, University of Çukurova, Adana, Turkey
| | - Elisabetta Mazzucotelli
- Research Centre for Genomics and Bioinformatics, Council for Agricultural Research and Economics (CREA), Fiorenzuola d'Arda, Italy
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24
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Chen J, Liu Y, Liu M, Guo W, Wang Y, He Q, Chen W, Liao Y, Zhang W, Gao Y, Dong K, Ren R, Yang T, Zhang L, Qi M, Li Z, Zhao M, Wang H, Wang J, Qiao Z, Li H, Jiang Y, Liu G, Song X, Deng Y, Li H, Yan F, Dong Y, Li Q, Li T, Yang W, Cui J, Wang H, Zhou Y, Zhang X, Jia G, Lu P, Zhi H, Tang S, Diao X. Pangenome analysis reveals genomic variations associated with domestication traits in broomcorn millet. Nat Genet 2023; 55:2243-2254. [PMID: 38036791 PMCID: PMC10703678 DOI: 10.1038/s41588-023-01571-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 10/17/2023] [Indexed: 12/02/2023]
Abstract
Broomcorn millet (Panicum miliaceum L.) is an orphan crop with the potential to improve cereal production and quality, and ensure food security. Here we present the genetic variations, population structure and diversity of a diverse worldwide collection of 516 broomcorn millet genomes. Population analysis indicated that the domesticated broomcorn millet originated from its wild progenitor in China. We then constructed a graph-based pangenome of broomcorn millet based on long-read de novo genome assemblies of 32 representative accessions. Our analysis revealed that the structural variations were highly associated with transposable elements, which influenced gene expression when located in the coding or regulatory regions. We also identified 139 loci associated with 31 key domestication and agronomic traits, including candidate genes and superior haplotypes, such as LG1, for panicle architecture. Thus, the study's findings provide foundational resources for developing genomics-assisted breeding programs in broomcorn millet.
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Affiliation(s)
- Jinfeng Chen
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
| | - Yang Liu
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Minxuan Liu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wenlei Guo
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yongqiang Wang
- Institute of Cotton, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Qiang He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weiyao Chen
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yi Liao
- College of Horticulture, South China Agricultural University, Guangzhou, China
| | - Wei Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuanzhu Gao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Kongjun Dong
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China
| | - Ruiyu Ren
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China
| | - Tianyu Yang
- Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China
| | - Liyuan Zhang
- Chifeng Academy of Agricultural and Animal Husbandry Sciences, Chifeng, China
| | - Mingyu Qi
- Chifeng Academy of Agricultural and Animal Husbandry Sciences, Chifeng, China
| | - Zhiguang Li
- Chifeng Academy of Agricultural and Animal Husbandry Sciences, Chifeng, China
| | - Min Zhao
- Chifeng Academy of Agricultural and Animal Husbandry Sciences, Chifeng, China
| | - Haigang Wang
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, China
| | - Junjie Wang
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, China
| | - Zhijun Qiao
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, China
| | - Haiquan Li
- Institute of Millet Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Yanmiao Jiang
- Institute of Millet Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Guoqing Liu
- Institute of Millet Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Xiaoqiang Song
- High Latitude Crops Institute to Shanxi Academy, Shanxi Agricultural University (Shanxi Academy of Agricultural Sciences), Datong, China
| | - Yarui Deng
- High Latitude Crops Institute to Shanxi Academy, Shanxi Agricultural University (Shanxi Academy of Agricultural Sciences), Datong, China
| | - Hai Li
- High Latitude Crops Institute to Shanxi Academy, Shanxi Agricultural University (Shanxi Academy of Agricultural Sciences), Datong, China
| | - Feng Yan
- Qiqihar Sub-academy of Heilongjiang Academy of Agricultural Sciences, Qiqihar, China
| | - Yang Dong
- Qiqihar Sub-academy of Heilongjiang Academy of Agricultural Sciences, Qiqihar, China
| | - Qingquan Li
- Qiqihar Sub-academy of Heilongjiang Academy of Agricultural Sciences, Qiqihar, China
| | - Tao Li
- Institute of Crop Sciences, Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Hohhot, China
| | - Wenyao Yang
- Institute of Crop Sciences, Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Hohhot, China
| | - Jianghui Cui
- College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Hongru Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yongfeng Zhou
- 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, China
| | - Xiaoming Zhang
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Guanqing Jia
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ping Lu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hui Zhi
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Sha Tang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
| | - Xianmin Diao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
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25
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Hu Y, Liu Y, Wei JJ, Zhang WK, Chen SY, Zhang JS. Regulation of seed traits in soybean. aBIOTECH 2023; 4:372-385. [PMID: 38106437 PMCID: PMC10721594 DOI: 10.1007/s42994-023-00122-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 10/18/2023] [Indexed: 12/19/2023]
Abstract
Soybean (Glycine max) is an essential economic crop that provides vegetative oil and protein for humans, worldwide. Increasing soybean yield as well as improving seed quality is of great importance. Seed weight/size, oil and protein content are the three major traits determining seed quality, and seed weight also influences soybean yield. In recent years, the availability of soybean omics data and the development of related techniques have paved the way for better research on soybean functional genomics, providing a comprehensive understanding of gene functions. This review summarizes the regulatory genes that influence seed size/weight, oil content and protein content in soybean. We also provided a general overview of the pleiotropic effect for the genes in controlling seed traits and environmental stresses. Ultimately, it is expected that this review will be beneficial in breeding improved traits in soybean.
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Affiliation(s)
- Yang Hu
- State Key Lab of Plant Genomics, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Yue Liu
- State Key Lab of Plant Genomics, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Jun-Jie Wei
- State Key Lab of Plant Genomics, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Wan-Ke Zhang
- State Key Lab of Plant Genomics, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
| | - Shou-Yi Chen
- State Key Lab of Plant Genomics, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
| | - Jin-Song Zhang
- State Key Lab of Plant Genomics, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049 China
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26
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Lemay MA, de Ronne M, Bélanger R, Belzile F. k-mer-based GWAS enhances the discovery of causal variants and candidate genes in soybean. Plant Genome 2023; 16:e20374. [PMID: 37596724 DOI: 10.1002/tpg2.20374] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 07/19/2023] [Indexed: 08/20/2023]
Abstract
Genome-wide association studies (GWAS) are powerful statistical methods that detect associations between genotype and phenotype at genome scale. Despite their power, GWAS frequently fail to pinpoint the causal variant or the gene controlling a given trait in crop species. Assessing genetic variants other than single-nucleotide polymorphisms (SNPs) could alleviate this problem. In this study, we tested the potential of structural variant (SV)- and k-mer-based GWAS in soybean by applying these methods as well as conventional SNP/indel-based GWAS to 13 traits. We assessed the performance of each GWAS approach based on loci for which the causal genes or variants were known from previous genetic studies. We found that k-mer-based GWAS was the most versatile approach and the best at pinpointing causal variants or candidate genes. Moreover, k-mer-based analyses identified promising candidate genes for loci related to pod color, pubescence form, and resistance to Phytophthora sojae. In our dataset, SV-based GWAS did not add value compared to k-mer-based GWAS and may not be worth the time and computational resources invested. Despite promising results, significant challenges remain regarding the downstream analysis of k-mer-based GWAS. Notably, better methods are needed to associate significant k-mers with sequence variation. Our results suggest that coupling k-mer- and SNP/indel-based GWAS is a powerful approach for discovering candidate genes in crop species.
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Affiliation(s)
- Marc-André Lemay
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
| | - Maxime de Ronne
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
| | - Richard Bélanger
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
| | - François Belzile
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
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27
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Niu J, Ma S, Zheng S, Zhang C, Lu Y, Si Y, Tian S, Shi X, Liu X, Naeem MK, Sun H, Hu Y, Wu H, Cui Y, Chen C, Long W, Zhang Y, Gu M, Cui M, Lu Q, Zhou W, Peng J, Akhunov E, He F, Zhao S, Ling HQ. Whole-genome sequencing of diverse wheat accessions uncovers genetic changes during modern breeding in China and the United States. Plant Cell 2023; 35:4199-4216. [PMID: 37647532 PMCID: PMC10689146 DOI: 10.1093/plcell/koad229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/25/2023] [Accepted: 08/08/2023] [Indexed: 09/01/2023]
Abstract
Breeding has dramatically changed the plant architecture of wheat (Triticum aestivum), resulting in the development of high-yielding varieties adapted to modern farming systems. However, how wheat breeding shaped the genomic architecture of this crop remains poorly understood. Here, we performed a comprehensive comparative analysis of a whole-genome resequencing panel of 355 common wheat accessions (representing diverse landraces and modern cultivars from China and the United States) at the phenotypic and genomic levels. The genetic diversity of modern wheat cultivars was clearly reduced compared to landraces. Consistent with these genetic changes, most phenotypes of cultivars from China and the United States were significantly altered. Of the 21 agronomic traits investigated, 8 showed convergent changes between the 2 countries. Moreover, of the 207 loci associated with these 21 traits, more than half overlapped with genomic regions that showed evidence of selection. The distribution of selected loci between the Chinese and American cultivars suggests that breeding for increased productivity in these 2 regions was accomplished by pyramiding both shared and region-specific variants. This work provides a framework to understand the genetic architecture of the adaptation of wheat to diverse agricultural production environments, as well as guidelines for optimizing breeding strategies to design better wheat varieties.
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Affiliation(s)
- Jianqing Niu
- Hainan Yazhou Bay Seed Laboratory, Hainan, Sanya 572024, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shengwei Ma
- Hainan Yazhou Bay Seed Laboratory, Hainan, Sanya 572024, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shusong Zheng
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Chi Zhang
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Yaru Lu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yaoqi Si
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuiquan Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoli Shi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaolin Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Muhammad Kashif Naeem
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Hua Sun
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yafei Hu
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Huilan Wu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yan Cui
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Chunlin Chen
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Wenbo Long
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yue Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Mengjun Gu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Man Cui
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qiao Lu
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenjuan Zhou
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Junhua Peng
- Huazhi Bio-tech Company Ltd., Changsha, Hunan 410125, China
| | - Eduard Akhunov
- Wheat Genetic Resources Center, Kansas State University, Manhattan, KS 66506, USA
| | - Fei He
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shancen Zhao
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Hong-Qing Ling
- Hainan Yazhou Bay Seed Laboratory, Hainan, Sanya 572024, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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28
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Bu M, Fan W, Li R, He B, Cui P. Lipid Metabolism and Improvement in Oilseed Crops: Recent Advances in Multi-Omics Studies. Metabolites 2023; 13:1170. [PMID: 38132852 PMCID: PMC10744971 DOI: 10.3390/metabo13121170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 11/09/2023] [Accepted: 11/15/2023] [Indexed: 12/23/2023] Open
Abstract
Oilseed crops are rich in plant lipids that not only provide essential fatty acids for the human diet but also play important roles as major sources of biofuels and indispensable raw materials for the chemical industry. The regulation of lipid metabolism genes is a major factor affecting oil production. In this review, we systematically summarize the metabolic pathways related to lipid production and storage in plants and highlight key research advances in characterizing the genes and regulatory factors influencing lipid anabolic metabolism. In addition, we integrate the latest results from multi-omics studies on lipid metabolism to provide a reference to better understand the molecular mechanisms underlying oil anabolism in oilseed crops.
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Affiliation(s)
- Mengjia Bu
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Fan
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Ruonan Li
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Bing He
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Peng Cui
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
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29
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Wu T, Wen H, Zhang X, Jia H, Xu C, Song W, Jiang B, Yuan S, Sun S, Wu C, Han T. Genome-wide association study for temperature response and photo-thermal interaction of flowering time in soybean using a panel of cultivars with diverse maturity groups. Theor Appl Genet 2023; 136:245. [PMID: 37962664 DOI: 10.1007/s00122-023-04496-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/26/2023] [Indexed: 11/15/2023]
Abstract
KEY MESSAGE A total of 101 QTNs were found to be associated with soybean flowering time responses to photo-thermal conditions; three candidate genes with non-synonymous substitutions were identified: Glyma.08G302500 (GmHY5), Glyma.08G303900 (GmPIF4c), and Glyma.16G046700 (GmVRN1). The flowering transition is a crucial component of soybean (Glycine max L. Merr.) development. The transition process is regulated by photoperiod, temperature, and their interaction. To examine the genetic architecture associated with temperature- and photo-thermal-mediated regulation of soybean flowering, we here performed a genome-wide association study using a panel of 201 soybean cultivars with maturity groups ranging from MG 000 to VIII. Each cultivar was grown in artificially controlled photoperiod and different seasons in 2017 and 2018 to assess the thermal response (TR) and the interactive photo-thermal response (IPT) of soybean flowering time. The panel contained 96,299 SNPs with minor allele frequencies > 5%; 33, 19, and 49 of these SNPs were significantly associated with only TR, only IPT, and both TR and IPT, respectively. Twenty-one SNPs were located in or near previously reported quantitative trait loci for first-flowering; 16 SNPs were located within 200 kb of the main-effect flowering genes GmFT2a, GmFT2b, GmFT3a, GmFT3b, GmFT5a, GmFT5b, GmCOL2b, GmPIF4b, and GmPIF4c, or near homologs of the known Arabidopsis thaliana flowering genes BBX19, VRN1, TFL1, FUL, AGL19, SPA1, HY5, PFT1, and EDF1. Natural non-synonymous allelic variations were identified in the candidate genes Glyma.08G302500 (GmHY5), Glyma.08G303900 (GmPIF4c), and Glyma.16G046700 (GmVRN1). Cultivars with different haplotypes showed significant variations in TR, IPT, and flowering time in multiple environments. The favorable alleles, candidate genes, and diagnostic SNP markers identified here provide valuable information for future improvement of soybean photo-thermal adaptability, enabling expansion of soybean production regions and improving plant resilience to global climate change.
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Affiliation(s)
- Tingting Wu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Huiwen Wen
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xinyue Zhang
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Hongchang Jia
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe, 164300, China
| | - Cailong Xu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Wenwen Song
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Bingjun Jiang
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Shan Yuan
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Shi Sun
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Cunxiang Wu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Tianfu Han
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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30
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Yocca AE, Platts A, Alger E, Teresi S, Mengist MF, Benevenuto J, Ferrão LFV, Jacobs M, Babinski M, Magallanes-Lundback M, Bayer P, Golicz A, Humann JL, Main D, Espley RV, Chagné D, Albert NW, Montanari S, Vorsa N, Polashock J, Díaz-Garcia L, Zalapa J, Bassil NV, Munoz PR, Iorizzo M, Edger PP. Blueberry and cranberry pangenomes as a resource for future genetic studies and breeding efforts. Hortic Res 2023; 10:uhad202. [PMID: 38023484 PMCID: PMC10673653 DOI: 10.1093/hr/uhad202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 10/01/2023] [Indexed: 12/01/2023]
Abstract
Domestication of cranberry and blueberry began in the United States in the early 1800s and 1900s, respectively, and in part owing to their flavors and health-promoting benefits are now cultivated and consumed worldwide. The industry continues to face a wide variety of production challenges (e.g. disease pressures), as well as a demand for higher-yielding cultivars with improved fruit quality characteristics. Unfortunately, molecular tools to help guide breeding efforts for these species have been relatively limited compared with those for other high-value crops. Here, we describe the construction and analysis of the first pangenome for both blueberry and cranberry. Our analysis of these pangenomes revealed both crops exhibit great genetic diversity, including the presence-absence variation of 48.4% genes in highbush blueberry and 47.0% genes in cranberry. Auxiliary genes, those not shared by all cultivars, are significantly enriched with molecular functions associated with disease resistance and the biosynthesis of specialized metabolites, including compounds previously associated with improving fruit quality traits. The discovery of thousands of genes, not present in the previous reference genomes for blueberry and cranberry, will serve as the basis of future research and as potential targets for future breeding efforts. The pangenome, as a multiple-sequence alignment, as well as individual annotated genomes, are publicly available for analysis on the Genome Database for Vaccinium-a curated and integrated web-based relational database. Lastly, the core-gene predictions from the pangenomes will serve useful to develop a community genotyping platform to guide future molecular breeding efforts across the family.
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Affiliation(s)
- Alan E Yocca
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, United States
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, United States
| | - Adrian Platts
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, United States
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, United States
| | - Elizabeth Alger
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, United States
| | - Scott Teresi
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, United States
- Genetics and Genome Sciences, Michigan State University, East Lansing, MI, 48824, United States
| | - Molla F Mengist
- Plants for Human Health Institute, North Carolina State University, Kannapolis, NC United States
| | - Juliana Benevenuto
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, United States
| | - Luis Felipe V Ferrão
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, United States
| | - MacKenzie Jacobs
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, United States
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, United States
| | - Michal Babinski
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, United States
| | | | - Philipp Bayer
- University of Western Australia, Perth 6009Australia
| | | | - Jodi L Humann
- Department of Horticulture, Washington State University, Pullman, WA, 99163, United States
| | - Dorrie Main
- Department of Horticulture, Washington State University, Pullman, WA, 99163, United States
| | - Richard V Espley
- The New Zealand Institute for Plant and Food Research Limited (PFR), Auckland, New Zealand
| | - David Chagné
- The New Zealand Institute for Plant and Food Research Limited (PFR), Palmerston, New Zealand
| | - Nick W Albert
- The New Zealand Institute for Plant and Food Research Limited (PFR), Palmerston, New Zealand
| | - Sara Montanari
- The New Zealand Institute for Plant and Food Research Limited (PFR), Motueka, New Zealand
| | - Nicholi Vorsa
- SEBS, Plant Biology, Rutgers University, New Brunswick NJ 01019United States
| | - James Polashock
- SEBS, Plant Biology, Rutgers University, New Brunswick NJ 01019United States
| | - Luis Díaz-Garcia
- Department of Viticulture and Enology, University of California, Davis, Davis, CA 95616, United States
| | - Juan Zalapa
- Department of Viticulture and Enology, University of California, Davis, Davis, CA 95616, United States
| | - Nahla V Bassil
- National Clonal Germplasm Repository, USDA-ARS, Corvallis, OR 97333, United States
| | - Patricio R Munoz
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, United States
| | - Massimo Iorizzo
- Plants for Human Health Institute, North Carolina State University, Kannapolis, NCUnited States
- Department of Horticulture, North Carolina State University, Kannapolis, NCUnited States
| | - Patrick P Edger
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, United States
- Genetics and Genome Sciences, Michigan State University, East Lansing, MI, 48824, United States
- MSU AgBioResearch, Michigan State University, East Lansing, MI, 48824, United States
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31
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Wei S, Yong B, Jiang H, An Z, Wang Y, Li B, Yang C, Zhu W, Chen Q, He C. A loss-of-function mutant allele of a glycosyl hydrolase gene has been co-opted for seed weight control during soybean domestication. J Integr Plant Biol 2023; 65:2469-2489. [PMID: 37635359 DOI: 10.1111/jipb.13559] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 08/28/2023] [Indexed: 08/29/2023]
Abstract
The resultant DNA from loss-of-function mutation can be recruited in biological evolution and development. Here, we present such a rare and potential case of "to gain by loss" as a neomorphic mutation during soybean domestication for increasing seed weight. Using a population derived from a chromosome segment substitution line of Glycine max (SN14) and Glycine soja (ZYD06), a quantitative trait locus (QTL) of 100-seed weight (qHSW) was mapped on chromosome 11, corresponding to a truncated β-1, 3-glucosidase (βGlu) gene. The novel gene hsw results from a 14-bp deletion, causing a frameshift mutation and a premature stop codon in the βGlu. In contrast to HSW, the hsw completely lost βGlu activity and function but acquired a novel function to promote cell expansion, thus increasing seed weight. Overexpressing hsw instead of HSW produced large soybean seeds, and surprisingly, truncating hsw via gene editing further increased the seed size. We further found that the core 21-aa peptide of hsw and its variants acted as a promoter of seed size. Transcriptomic variation in these transgenic soybean lines substantiated the integration hsw into cell and seed size control. Moreover, the hsw allele underwent selection and expansion during soybean domestication and improvement. Our work cloned a likely domesticated QTL controlling soybean seed weight, revealed a novel genetic variation and mechanism in soybean domestication, and provided new insight into crop domestication and breeding, and plant evolution.
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Affiliation(s)
- Siming Wei
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bin Yong
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hongwei Jiang
- College of Agriculture, Northeast Agricultural University, Harbin, 150030, China
- Jilin Academy of Agricultural Sciences, Changchun, 130022, China
| | - Zhenghong An
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yan Wang
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
| | - Bingbing Li
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ce Yang
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Weiwei Zhu
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qingshan Chen
- College of Agriculture, Northeast Agricultural University, Harbin, 150030, China
| | - Chaoying He
- State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
- China National Botanical Garden, Beijing, 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- The Innovative Academy of Seed Design, the Chinese Academy of Sciences, Beijing, 100101, China
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Sharma N, Raman H, Wheeler D, Kalenahalli Y, Sharma R. Data-driven approaches to improve water-use efficiency and drought resistance in crop plants. Plant Sci 2023; 336:111852. [PMID: 37659733 DOI: 10.1016/j.plantsci.2023.111852] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 08/23/2023] [Accepted: 08/29/2023] [Indexed: 09/04/2023]
Abstract
With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.
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Affiliation(s)
- Niharika Sharma
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia.
| | - Harsh Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia
| | - David Wheeler
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia
| | - Yogendra Kalenahalli
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, Telangana 502324, India
| | - Rita Sharma
- Department of Biological Sciences, BITS Pilani, Pilani Campus, Rajasthan 333031, India
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Liu Y, Yi C, Fan C, Liu Q, Liu S, Shen L, Zhang K, Huang Y, Liu C, Wang Y, Tian Z, Han F. Pan-centromere reveals widespread centromere repositioning of soybean genomes. Proc Natl Acad Sci U S A 2023; 120:e2310177120. [PMID: 37816061 PMCID: PMC10589659 DOI: 10.1073/pnas.2310177120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/06/2023] [Indexed: 10/12/2023] Open
Abstract
Centromere repositioning refers to a de novo centromere formation at another chromosomal position without sequence rearrangement. This phenomenon was frequently encountered in both mammalian and plant species and has been implicated in genome evolution and speciation. To understand the dynamic of centromeres on soybean genome, we performed the pan-centromere analysis using CENH3-ChIP-seq data from 27 soybean accessions, including 3 wild soybeans, 9 landraces, and 15 cultivars. Building upon the previous discovery of three centromere satellites in soybean, we have identified two additional centromere satellites that specifically associate with chromosome 1. These satellites reveal significant rearrangements in the centromere structures of chromosome 1 across different accessions, consequently impacting the localization of CENH3. By comparative analysis, we reported a high frequency of centromere repositioning on 14 out of 20 chromosomes. Most newly emerging centromeres formed in close proximity to the native centromeres and some newly emerging centromeres were apparently shared in distantly related accessions, suggesting their emergence is independent. Furthermore, we crossed two accessions with mismatched centromeres to investigate how centromere positions would be influenced in hybrid genetic backgrounds. We found that a significant proportion of centromeres in the S9 generation undergo changes in size and position compared to their parental counterparts. Centromeres preferred to locate at satellites to maintain a stable state, highlighting a significant role of centromere satellites in centromere organization. Taken together, these results revealed extensive centromere repositioning in soybean genome and highlighted how important centromere satellites are in constraining centromere positions and supporting centromere function.
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Affiliation(s)
- Yang Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
| | - Congyang Yi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
- College of Advanced Agricultural Sciences, University of the Chinese Academy of Sciences, Beijing100049, China
| | - Chaolan Fan
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
| | - Qian Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
- College of Advanced Agricultural Sciences, University of the Chinese Academy of Sciences, Beijing100049, China
| | - Shulin Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
| | - Lisha Shen
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
| | - Kaibiao Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
- College of Advanced Agricultural Sciences, University of the Chinese Academy of Sciences, Beijing100049, China
| | - Yuhong Huang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
- College of Advanced Agricultural Sciences, University of the Chinese Academy of Sciences, Beijing100049, China
| | - Chang Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
- College of Advanced Agricultural Sciences, University of the Chinese Academy of Sciences, Beijing100049, China
| | - Yingxiang Wang
- Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou510642, China
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
| | - Fangpu Han
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing100101, China
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Chan YO, Biová J, Mahmood A, Dietz N, Bilyeu K, Škrabišová M, Joshi T. Genomic Variations Explorer (GenVarX): a toolset for annotating promoter and CNV regions using genotypic and phenotypic differences. Front Genet 2023; 14:1251382. [PMID: 37928239 PMCID: PMC10623549 DOI: 10.3389/fgene.2023.1251382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 09/27/2023] [Indexed: 11/07/2023] Open
Abstract
The rapid growth of sequencing technology and its increasing popularity in biology-related research over the years has made whole genome re-sequencing (WGRS) data become widely available. A large amount of WGRS data can unlock the knowledge gap between genomics and phenomics through gaining an understanding of the genomic variations that can lead to phenotype changes. These genomic variations are usually comprised of allele and structural changes in DNA, and these changes can affect the regulatory mechanisms causing changes in gene expression and altering the phenotypes of organisms. In this research work, we created the GenVarX toolset, that is backed by transcription factor binding sequence data in promoter regions, the copy number variations data, SNPs and Indels data, and phenotypes data which can potentially provide insights about phenotypic differences and solve compelling questions in plant research. Analytics-wise, we have developed strategies to better utilize the WGRS data and mine the data using efficient data processing scripts, libraries, tools, and frameworks to create the interactive and visualization-enhanced GenVarX toolset that encompasses both promoter regions and copy number variation analysis components. The main capabilities of the GenVarX toolset are to provide easy-to-use interfaces for users to perform queries, visualize data, and interact with the data. Based on different input windows on the user interface, users can provide inputs corresponding to each field and submit the information as a query. The data returned on the results page is usually displayed in a tabular fashion. In addition, interactive figures are also included in the toolset to facilitate the visualization of statistical results or tool outputs. Currently, the GenVarX toolset supports soybean, rice, and Arabidopsis. The researchers can access the soybean GenVarX toolset from SoyKB via https://soykb.org/SoybeanGenVarX/, rice GenVarX toolset, and Arabidopsis GenVarX toolset from KBCommons web portal with links https://kbcommons.org/system/tools/GenVarX/Osativa and https://kbcommons.org/system/tools/GenVarX/Athaliana, respectively.
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Affiliation(s)
- Yen On Chan
- MU Institute for Data Science and Informatics, University of Missouri-Columbia, Columbia, MO, United States
| | - Jana Biová
- Department of Biochemistry, Faculty of Science, Palacky University in Olomouc, Olomouc, Czechia
| | - Anser Mahmood
- Division of Plant Science and Technology, University of Missouri-Columbia, Columbia, MO, United States
| | - Nicholas Dietz
- Division of Plant Science and Technology, University of Missouri-Columbia, Columbia, MO, United States
| | - Kristin Bilyeu
- Division of Plant Science and Technology, University of Missouri-Columbia, Columbia, MO, United States
- Plant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Columbia, MO, United States
| | - Mária Škrabišová
- Department of Biochemistry, Faculty of Science, Palacky University in Olomouc, Olomouc, Czechia
| | - Trupti Joshi
- MU Institute for Data Science and Informatics, University of Missouri-Columbia, Columbia, MO, United States
- Christopher S. Bond Life Sciences Center, University of Missouri-Columbia, Columbia, MO, United States
- Department of Electrical Engineering and Computer Science, University of Missouri-Columbia, Columbia, MO, United States
- Department of Biomedical Informatics, Biostatistics and Medical Epidemiology, University of Missouri-Columbia, Columbia, MO, United States
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Potapova NA, Zlobin AS, Perfil’ev RN, Vasiliev GV, Salina EA, Tsepilov YA. Population Structure and Genetic Diversity of the 175 Soybean Breeding Lines and Varieties Cultivated in West Siberia and Other Regions of Russia. Plants (Basel) 2023; 12:3490. [PMID: 37836230 PMCID: PMC10575349 DOI: 10.3390/plants12193490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/23/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023]
Abstract
Soybean is a leguminous plant cultivated in many countries and is considered important in the food industry due to the high levels of oil and protein content in the beans. The high demand for soybeans and its products in the industry requires the expansion of cultivation areas. Despite climatic restrictions, West Siberia is gradually expanding its area of soybean cultivation. In this study, we present the first analysis of the population structure and genetic diversity of the 175 soybean Glycine max breeding lines and varieties cultivated in West Siberia (103 accessions) and other regions of Russia (72 accessions), and we compare them with the cultivated soybean varieties from other geographical locations. Principal component analysis revealed several genetic clusters with different levels of genetic heterogeneity. Studied accessions are genetically similar to varieties from China, Japan, and the USA and are genetically distant to varieties from South Korea. Admixture analysis revealed four ancestry groups based on genetic ancestry and geographical origin, which are consistent with the regions of cultivation and origin of accessions and correspond to the principal component analysis result. Population statistics, including nucleotide diversity, Tajima's D, and linkage disequilibrium, are comparatively similar to those observed for studied accessions of a different origin. This study provides essential population and genetic information about the unique collection of breeding lines and varieties cultivated in West Siberia and other Russian regions to foster further evolutionary, genome-wide associations and functional breeding studies.
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Affiliation(s)
- Nadezhda A. Potapova
- Kurchatov Genomic Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
- Institute for Information Transmission Problems (Kharkevich Institute) of the Russian Academy of Sciences, 127051 Moscow, Russia
| | - Alexander S. Zlobin
- Kurchatov Genomic Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
- Federal Research Center, Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
| | - Roman N. Perfil’ev
- Federal Research Center, Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
| | - Gennady V. Vasiliev
- Kurchatov Genomic Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
- Federal Research Center, Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
| | - Elena A. Salina
- Kurchatov Genomic Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
- Federal Research Center, Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
| | - Yakov A. Tsepilov
- Kurchatov Genomic Center, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
- Federal Research Center, Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
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36
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Gao L, Kantar MB, Moxley D, Ortiz-Barrientos D, Rieseberg LH. Crop adaptation to climate change: An evolutionary perspective. Mol Plant 2023; 16:1518-1546. [PMID: 37515323 DOI: 10.1016/j.molp.2023.07.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/20/2023] [Accepted: 07/26/2023] [Indexed: 07/30/2023]
Abstract
The disciplines of evolutionary biology and plant and animal breeding have been intertwined throughout their development, with responses to artificial selection yielding insights into the action of natural selection and evolutionary biology providing statistical and conceptual guidance for modern breeding. Here we offer an evolutionary perspective on a grand challenge of the 21st century: feeding humanity in the face of climate change. We first highlight promising strategies currently under way to adapt crops to current and future climate change. These include methods to match crop varieties with current and predicted environments and to optimize breeding goals, management practices, and crop microbiomes to enhance yield and sustainable production. We also describe the promise of crop wild relatives and recent technological innovations such as speed breeding, genomic selection, and genome editing for improving environmental resilience of existing crop varieties or for developing new crops. Next, we discuss how methods and theory from evolutionary biology can enhance these existing strategies and suggest novel approaches. We focus initially on methods for reconstructing the evolutionary history of crops and their pests and symbionts, because such historical information provides an overall framework for crop-improvement efforts. We then describe how evolutionary approaches can be used to detect and mitigate the accumulation of deleterious mutations in crop genomes, identify alleles and mutations that underlie adaptation (and maladaptation) to agricultural environments, mitigate evolutionary trade-offs, and improve critical proteins. Continuing feedback between the evolution and crop biology communities will ensure optimal design of strategies for adapting crops to climate change.
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Affiliation(s)
- Lexuan Gao
- CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Michael B Kantar
- Department of Tropical Plant & Soil Sciences, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Dylan Moxley
- Department of Botany and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Daniel Ortiz-Barrientos
- School of Biological Sciences and Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, Brisbane, QLD, Australia
| | - Loren H Rieseberg
- Department of Botany and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada.
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Cai Z, Xian P, Cheng Y, Yang Y, Zhang Y, He Z, Xiong C, Guo Z, Chen Z, Jiang H, Ma Q, Nian H, Ge L. Natural variation of GmFATA1B regulates seed oil content and composition in soybean. J Integr Plant Biol 2023; 65:2368-2379. [PMID: 37655952 DOI: 10.1111/jipb.13561] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 08/30/2023] [Indexed: 09/02/2023]
Abstract
Soybean (Glycine max) produces seeds that are rich in unsaturated fatty acids and is an important oilseed crop worldwide. Seed oil content and composition largely determine the economic value of soybean. Due to natural genetic variation, seed oil content varies substantially across soybean cultivars. Although much progress has been made in elucidating the genetic trajectory underlying fatty acid metabolism and oil biosynthesis in plants, the causal genes for many quantitative trait loci (QTLs) regulating seed oil content in soybean remain to be revealed. In this study, we identified GmFATA1B as the gene underlying a QTL that regulates seed oil content and composition, as well as seed size in soybean. Nine extra amino acids in the conserved region of GmFATA1B impair its function as a fatty acyl-acyl carrier protein thioesterase, thereby affecting seed oil content and composition. Heterogeneously overexpressing the functional GmFATA1B allele in Arabidopsis thaliana increased both the total oil content and the oleic acid and linoleic acid contents of seeds. Our findings uncover a previously unknown locus underlying variation in seed oil content in soybean and lay the foundation for improving seed oil content and composition in soybean.
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Affiliation(s)
- Zhandong Cai
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
- Guangdong Provincial Key Laboratory of Utilization and Conservation of Food and Medicinal Resources in Northern Region, Shaoguan University, Shaoguan, 512000, China
- Department of Grassland Science, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, 510642, China
| | - Peiqi Xian
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Yanbo Cheng
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Yuan Yang
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Yakun Zhang
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Zihang He
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Chuwen Xiong
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Zhibin Guo
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Zhicheng Chen
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Huiqian Jiang
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Qibin Ma
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
| | - Hai Nian
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, China
| | - Liangfa Ge
- Guangdong Sub-center of National Center for Soybean Improvement, South China Agricultural University, Guangzhou, 510642, China
- Department of Grassland Science, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, 510642, China
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Chien PS, Chen PH, Lee CR, Chiou TJ. Transcriptome-wide association study coupled with eQTL analysis reveals the genetic connection between gene expression and flowering time in Arabidopsis. J Exp Bot 2023; 74:5653-5666. [PMID: 37419660 DOI: 10.1093/jxb/erad262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 07/06/2023] [Indexed: 07/09/2023]
Abstract
Genome-wide association study (GWAS) has improved our understanding of complex traits, but challenges exist in distinguishing causation versus association caused by linkage disequilibrium. Instead, transcriptome-wide association studies (TWAS) detect direct associations between expression levels and phenotypic variations, providing an opportunity to better prioritize candidate genes. To assess the feasibility of TWAS, we investigated the association between transcriptomes, genomes, and various traits in Arabidopsis, including flowering time. The associated genes formerly known to regulate growth allometry or metabolite production were first identified by TWAS. Next, for flowering time, six TWAS-newly identified genes were functionally validated. Analysis of the expression quantitative trait locus (eQTL) further revealed a trans-regulatory hotspot affecting the expression of several TWAS-identified genes. The hotspot covers the FRIGIDA (FRI) gene body, which possesses multiple haplotypes differentially affecting the expression of downstream genes, such as FLOWERING LOCUS C (FLC) and SUPPRESSOR OF OVEREXPRESSION OF CO 1 (SOC1). We also revealed multiple independent paths towards the loss of function of FRI in natural accessions. Altogether, this study demonstrates the potential of combining TWAS with eQTL analysis to identify important regulatory modules of FRI-FLC-SOC1 for quantitative traits in natural populations.
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Affiliation(s)
- Pei-Shan Chien
- Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan
| | - Pin-Hua Chen
- Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan
| | - Cheng-Ruei Lee
- Institute of Ecology and Evolutionary Biology, National Taiwan University, Taipei, Taiwan
- Institute of Plant Biology, National Taiwan University, Taipei, Taiwan
| | - Tzyy-Jen Chiou
- Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan
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Lin YP, Chen HW, Yeh PM, Anand SS, Lin J, Li J, Noble T, Nair R, Schafleitner R, Samsononova M, Bishop-von-Wettberg E, Nuzhdin S, Ting CT, Lawn RJ, Lee CR. Demographic history and distinct selection signatures of two domestication genes in mungbean. Plant Physiol 2023; 193:1197-1212. [PMID: 37335936 DOI: 10.1093/plphys/kiad356] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 05/10/2023] [Accepted: 06/03/2023] [Indexed: 06/21/2023]
Abstract
Domestication is the long and complex process underlying the evolution of crops, in which artificial directional selection transformed wild progenitors into the desired form, affecting genomic variation and leaving traces of selection at targeted loci. However, whether genes controlling important domestication traits follow the same evolutionary pattern expected under the standard selective sweep model remains unclear. With whole-genome resequencing of mungbean (Vigna radiata), we investigated this issue by resolving its global demographic history and targeted dissection of the molecular footprints of genes underlying 2 key traits representing different stages of domestication. Mungbean originated in Asia, and the Southeast Asian wild population migrated to Australia about 50 thousand generations ago. Later in Asia, the cultivated form diverged from the wild progenitor. We identified the gene associated with the pod shattering resistance trait, VrMYB26a, with lower expression across cultivars and reduced polymorphism in the promoter region, reflecting a hard selective sweep. On the other hand, the stem determinacy trait was associated with VrDet1. We found that 2 ancient haplotypes of this gene have lower gene expression and exhibited intermediate frequencies in cultivars, consistent with selection favoring independent haplotypes in a soft selective sweep. In mungbean, contrasting signatures of selection were identified from the detailed dissection of 2 important domestication traits. The results suggest complex genetic architecture underlying the seemingly simple process of directional artificial selection and highlight the limitations of genome-scan methods relying on hard selective sweeps.
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Affiliation(s)
- Ya-Ping Lin
- Institute of Ecology and Evolutionary Biology, National Taiwan University, Taipei 10617, Taiwan
- World Vegetable Center, Tainan 74199, Taiwan
| | - Hung-Wei Chen
- Institute of Ecology and Evolutionary Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Pei-Min Yeh
- Institute of Ecology and Evolutionary Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Shashi S Anand
- Institute of Ecology and Evolutionary Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Jiunn Lin
- Institute of Plant Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Juan Li
- Institute of Ecology and Evolutionary Biology, National Taiwan University, Taipei 10617, Taiwan
- Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland
- Swiss Institute for Bioinformatics, 1015 Lausanne, Switzerland
| | - Thomas Noble
- Australian Department of Agriculture and Fisheries, Warwick, Queensland 4370, Australia
| | - Ramakrishnan Nair
- World Vegetable Center South and Central Asia, ICRISAT Campus, Patancheru, Hyderabad, Telangana 502324, India
| | | | - Maria Samsononova
- Mathematical Biology and Bioinformatics Laboratory, Peter the Great St. Petersburg Polytechnic University, 19525 St. Petersburg, Russia
| | - Eric Bishop-von-Wettberg
- Mathematical Biology and Bioinformatics Laboratory, Peter the Great St. Petersburg Polytechnic University, 19525 St. Petersburg, Russia
- Department of Plant and Soil Science and Gund Institute for the Environment, University of Vermont, Burlington, VT 05405, USA
| | - Sergey Nuzhdin
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Chau-Ti Ting
- Department of Life Science, National Taiwan University, Taipei 10617, Taiwan
| | - Robert J Lawn
- College of Science & Engineering, James Cook University, Townsville, Queensland 4814, Australia
| | - Cheng-Ruei Lee
- Institute of Ecology and Evolutionary Biology, National Taiwan University, Taipei 10617, Taiwan
- Institute of Plant Biology, National Taiwan University, Taipei 10617, Taiwan
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40
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Lee Y, Woo DU, Kang YJ. SoyDBean: a database for SNPs reconciliation by multiple versions of soybean reference genomes. Sci Rep 2023; 13:15712. [PMID: 37735613 PMCID: PMC10514325 DOI: 10.1038/s41598-023-42898-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 09/15/2023] [Indexed: 09/23/2023] Open
Abstract
Due to the development of sequence technology and decreased cost, many whole genome sequences have been obtained. As a result, extensive genetic variations have been discovered from many populations and germplasms to understand the genetic diversity of soybean (Glycine max [L.] Merr.). However, assessing the quality of variation is essential because the published variants were collected using different bioinformatic methods and parameters. Furthermore, despite the enhanced genome contiguity and more efficient filling of "N" stretches in the new reference genome, there remains a dearth of endeavors to verify the caliber of variations present in it. The primary goal of this research was to discern a dependable set of SNPs that can withstand reconciliation across multiple reference genomes. Additionally, the investigation aimed to reconfirm the variations through the utilization of numerous whole genome sequencing data obtained from publicly available databases. Based on the result, we created datasets that comprised the thoroughly verified SNP coordinates between the reference assemblies. The resulting "SoyDBean" database is now publicly accessible through the following URL: http://soydbean.plantprofile.net/ .
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Affiliation(s)
- Yejin Lee
- Division of Bio and Medical Bigdata Department (BK4 Program), Gyeongsang National University, 501, Jinju-daero, Jinju-si, Gyeongsangnam-do, 52828, Republic of Korea
- Division of Life Science Department, Gyeongsang National University, Jinju, Republic of Korea
| | - Dong U Woo
- Division of Bio and Medical Bigdata Department (BK4 Program), Gyeongsang National University, 501, Jinju-daero, Jinju-si, Gyeongsangnam-do, 52828, Republic of Korea
- Division of Life Science Department, Gyeongsang National University, Jinju, Republic of Korea
| | - Yang Jae Kang
- Division of Bio and Medical Bigdata Department (BK4 Program), Gyeongsang National University, 501, Jinju-daero, Jinju-si, Gyeongsangnam-do, 52828, Republic of Korea.
- Division of Life Science Department, Gyeongsang National University, Jinju, Republic of Korea.
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Shi H, Li T, Su M, Wang H, Li Q, Lang X, Ma Y. Identification of copy number variation in Tibetan sheep using whole genome resequencing reveals evidence of genomic selection. BMC Genomics 2023; 24:555. [PMID: 37726692 PMCID: PMC10510117 DOI: 10.1186/s12864-023-09672-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 09/12/2023] [Indexed: 09/21/2023] Open
Abstract
BACKGROUND Copy number variation (CNV) is an important source of structural variation in the mammalian genome. CNV assays present a new method to explore the genomic diversity of environmental adaptations in animals and plants and genes associated with complex traits. In this study, the genome-wide CNV distribution characteristics of 20 Tibetan sheep from two breeds (10 Oula sheep and 10 Panou sheep) were analysed using whole-genome resequencing to investigate the variation in the genomic structure of Tibetan sheep during breeding. RESULTS CNVs were detected using CNVnator, and the overlapping regions of CNVs between individual sheep were combined. Among them, a total of 60,429 CNV events were detected between the indigenous sheep breed (Oula) and the synthetic sheep breed (Panou). After merging the overlapping CNVs, 4927 CNV regions (CNVRs) were finally obtained. Of these, 4559 CNVRs were shared by two breeds, and there were 368 differential CNVRs. Deletion events have a higher percentage of occurrences than duplication events. Functional enrichment analysis showed that the shared CNVRs were significantly enriched in 163 GO terms and 62 KEGG pathways, which were mainly associated with organ development, neural regulation, immune regulation, digestion and metabolism. In addition, 140 QTLs overlapped with some of the CNVRs at more than 1 kb, such as average daily gain QTL, body weight QTL, and total lambs born QTL. Many of the CNV-overlapping genes such as PPP3CA, SSTR1 and FASN, overlap with the average daily weight gain and carcass weight QTL regions. Moreover, VST analysis showed that XIRP2, ABCB1, CA1, ASPA and EEF2 differed significantly between the synthetic breed and local sheep breed. The duplication of the ABCB1 gene may be closely related to adaptation to the plateau environment in Panou sheep, which deserves further study. Additionally, cluster analysis, based on all individuals, showed that the CNV clustering could be divided into two origins, indicating that some Tibetan sheep CNVs are likely to arise independently in different populations and contribute to population differences. CONCLUSIONS Collectively, we demonstrated the genome-wide distribution characteristics of CNVs in Panou sheep by whole genome resequencing. The results provides a valuable genetic variation resource and help to understand the genetic characteristics of Tibetan sheep. This study also provides useful information for the improvement and breeding of Tibetan sheep in the future.
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Affiliation(s)
- Huibin Shi
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
- Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou, 730070, China
- College of Animal Science & Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, 450046, China
| | - Taotao Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
- Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou, 730070, China
| | - Manchun Su
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
- Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou, 730070, China
| | - Huihui Wang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
- Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou, 730070, China
| | - Qiao Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
- Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou, 730070, China
| | - Xia Lang
- Institute of Animal & Pasture Science and Green Agriculture, Gansu Academy of Agricultural Science, Lanzhou, 730070, China
| | - Youji Ma
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
- Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou, 730070, China.
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Tian X, Sang Z, Lan Z, Liu W, Feng Y, Hu J, Chen F, Liu Y. Fine-Scale analysis of both wild and cultivated horned galls provides insight into their quality differentiation. BMC Plant Biol 2023; 23:426. [PMID: 37710158 PMCID: PMC10500821 DOI: 10.1186/s12870-023-04442-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 09/06/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND Galla chinensis is a traditional Chinese medicine (TCM) produced due to the interaction between the Fordinae aphids and the Rhus plant species. Horned galls with high tannin content are the most widely cultivated gall type, and Wufeng county of Hubei province in China is the center of cultivation. However, long-term artificial cultivation and domestication of horned galls to meet the increasing production demand have led to quality degradation. Understanding the reasons underlying quality degradation is urgent for horned gall production and application. The present study used a combination of metabolic, genetic, and ecological analyses to investigate the quality and genetic differentiation of the horned galls under long-term domestication as well as the potential relationships between them. RESULTS Analysis of gallic acid content and other three phenotypic traits (fresh weight, gall size, and wall thickness) revealed quality differentiation of horned galls collected from five locations in Wufeng, in which the cultivated samples from Wang Jiaping (WJP) showed the highest degradation. Genetic differentiation between the cultivated and wild Rhus chinensis trees in WJP, and between WJP and the other populations was detected based on SSR molecular markers, however, no significant difference in genetic structure was seen for the aphid populations. Among the various ecological factors examined, temperature was identified as the primary one affecting the quality of horned galls. CONCLUSIONS Both genetic and ecological factors caused quality differentiation of horned galls. The collection of diverse germplasm of host trees and aphids will help reduce the quality degradation of horned galls in Wufeng.
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Affiliation(s)
- Xufang Tian
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, People's Republic of China
| | - Ziyang Sang
- Forestry Science Research Institute of Wufeng County, Yichang, 443400, People's Republic of China
| | - Zhaohui Lan
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, People's Republic of China
| | - Wei Liu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, People's Republic of China
| | - Ying Feng
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, People's Republic of China
| | - Juan Hu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, People's Republic of China
| | - Faju Chen
- Biotechnology Research Center, China Three Gorges University, Yichang, 443002, People's Republic of China
| | - Yifei Liu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, People's Republic of China.
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Chu D, Zhang Z, Hu Y, Fang C, Xu X, Yuan J, Zhang J, Tian Z, Wang G. Genome-wide scan for oil quality reveals a coregulation mechanism of tocopherols and fatty acids in soybean seeds. Plant Commun 2023; 4:100598. [PMID: 37029487 PMCID: PMC10504561 DOI: 10.1016/j.xplc.2023.100598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 03/24/2023] [Accepted: 04/04/2023] [Indexed: 06/01/2023]
Abstract
Tocopherols (vitamin E) play essential roles in human health because of their antioxidant activity, and plant-derived oils are the richest sources of tocopherols in the human diet. Although soybean (Glycine max) is one of the main sources of plant-derived oil and tocopherol in the world, the relationship between tocopherol and oil in soybean seeds remains unclear. Here, we focus on dissecting tocopherol metabolism with the long-term goal of increasing α-tocopherol content and soybean oil quality. We first collected tocopherol and fatty acid profiles in a soybean population (>800 soybean accessions) and found that tocopherol content increased during soybean domestication. A strong positive correlation between tocopherol and oil content was also detected. Five tocopherol pathway-related loci were identified using a metabolite genome-wide association study strategy. Genetic variations in three tocopherol pathway genes were responsible for total tocopherol content and composition in the soybean population through effects on enzyme activity, mainly caused by non-conserved amino acid substitution or changes in gene transcription level. Moreover, the fatty acid regulatory transcription factor GmZF351 directly activated tocopherol pathway gene expression, increasing both fatty acid and tocopherol contents in soybean seeds. Our study reveals the functional differentiation of tocopherol pathway genes in soybean populations and provides a framework for development of new soybean varieties with high α-tocopherol content and oil quality in seeds.
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Affiliation(s)
- Danni Chu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China; College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100039, China
| | - Zhifang Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Yang Hu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China; College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100039, China
| | - Chao Fang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Xindan Xu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Jia Yuan
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Jinsong Zhang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China; College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100039, China
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China; College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100039, China.
| | - Guodong Wang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China; College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100039, China.
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Song J, Xu R, Guo Q, Wu C, Li Y, Wang X, Wang J, Qiu LJ. An omics strategy increasingly improves the discovery of genetic loci and genes for seed-coat color formation in soybean. Mol Breed 2023; 43:71. [PMID: 37663546 PMCID: PMC10471558 DOI: 10.1007/s11032-023-01414-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 08/13/2023] [Indexed: 09/05/2023]
Abstract
The phenotypic color of seeds is a complex agronomic trait and has economic and biological significance. The genetic control and molecular regulation mechanisms have been extensively studied. Here, we used a multi-omics strategy to explore the color formation in soybean seeds at a big data scale. We identified 13 large quantitative trait loci (QTL) for color with bulk segregating analysis in recombinant inbreeding lines. GWAS analysis of colors and decomposed attributes in 763 germplasms revealed associated SNP sites perfectly falling in five major QTL, suggesting inherited regulation on color during natural selection. Further transcriptomics analysis before and after color accumulation revealed 182 differentially expression genes (DEGs) in the five QTL, including known genes CHS, MYB, and F3'H involved in pigment accumulation. More DEGs with consistently upregulation or downregulation were identified as shared regulatory genes for two or more color formations while some DEGs were only for a specific color formation. For example, five upregulated DEGs in QTL qSC-3 were in flavonoid biosynthesis responsible for black and brown seed. The DEG (Glyma.08G085400) was identified in the purple seed only, which encodes gibberellin 2-beta-dioxygenase in the metabolism of colorful terpenoids. The candidate genes are involved in flavonoid biosynthesis, transcription factor regulation, gibberellin and terpenoid metabolism, photosynthesis, ascorbate and aldarate metabolism, and lipid metabolism. Seven differentially expressed transcription factors were also speculated that may regulate color formation, including a known MYB. The finds expand QTL and gene candidates for color formation, which could guide to breed better cultivars with designed colors. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01414-z.
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Affiliation(s)
- Jian Song
- Yangtze University, Jingzhou, 434025 Hubei P.R. China
| | - Ruixin Xu
- Yangtze University, Jingzhou, 434025 Hubei P.R. China
| | - Qingyuan Guo
- Yangtze University, Jingzhou, 434025 Hubei P.R. China
| | - Caiyu Wu
- Yangtze University, Jingzhou, 434025 Hubei P.R. China
| | - Yinghui Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Xuewen Wang
- Department of Genetics, University of Georgia, Athens, GA 30602 USA
| | - Jun Wang
- Yangtze University, Jingzhou, 434025 Hubei P.R. China
| | - Li-Juan Qiu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
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Cui L, Cheng H, Yang Z, Xia C, Zhang L, Kong X. Comparative Analysis Reveals Different Evolutionary Fates and Biological Functions in Wheat Duplicated Genes ( Triticum aestivum L.). Plants (Basel) 2023; 12:3021. [PMID: 37687268 PMCID: PMC10489728 DOI: 10.3390/plants12173021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/20/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023]
Abstract
Wheat (Triticum aestivum L.) is a staple food crop that provides 20% of total human calorie consumption. Gene duplication has been considered to play an important role in evolution by providing new genetic resources. However, the evolutionary fates and biological functions of the duplicated genes in wheat remain to be elucidated. In this study, the resulting data showed that the duplicated genes evolved faster with shorter gene lengths, higher codon usage bias, lower expression levels, and higher tissue specificity when compared to non-duplicated genes. Our analysis further revealed functions of duplicated genes in various biological processes with significant enrichment to environmental stresses. In addition, duplicated genes derived from dispersed, proximal, tandem, transposed, and whole-genome duplication differed in abundance, evolutionary rate, gene compactness, expression pattern, and genetic diversity. Tandem and proximal duplicates experienced stronger selective pressure and showed a more compact gene structure with diverse expression profiles than other duplication modes. Moreover, genes derived from different duplication modes showed an asymmetrical evolutionary pattern for wheat A, B, and D subgenomes. Several candidate duplication hotspots associated with wheat domestication or polyploidization were characterized as potential targets for wheat molecular breeding. Our comprehensive analysis revealed the evolutionary trajectory of duplicated genes and laid the foundation for future functional studies on wheat.
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Affiliation(s)
- Licao Cui
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (L.C.); (H.C.); (Z.Y.); (C.X.); (L.Z.)
- College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang 330045, China
| | - Hao Cheng
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (L.C.); (H.C.); (Z.Y.); (C.X.); (L.Z.)
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Life Sciences, Northwest A&F University, Yangling 712100, China
| | - Zhe Yang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (L.C.); (H.C.); (Z.Y.); (C.X.); (L.Z.)
| | - Chuan Xia
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (L.C.); (H.C.); (Z.Y.); (C.X.); (L.Z.)
| | - Lichao Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (L.C.); (H.C.); (Z.Y.); (C.X.); (L.Z.)
| | - Xiuying Kong
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (L.C.); (H.C.); (Z.Y.); (C.X.); (L.Z.)
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Hou M, Cao Y, Zhang X, Zhang S, Jia T, Yang J, Han S, Wang L, Li J, Wang H, Zhang L, Wu X, Duan C, Li H. Genome-wide association study of maize resistance to Pythium aristosporum stalk rot. Front Plant Sci 2023; 14:1239635. [PMID: 37662167 PMCID: PMC10470045 DOI: 10.3389/fpls.2023.1239635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 07/28/2023] [Indexed: 09/05/2023]
Abstract
Stalk rot, a severe and widespread soil-borne disease in maize, globally reduces yield and quality. Recent documentation reveals that Pythium aristosporum has emerged as one of the dominant causal agents of maize stalk rot. However, a previous study of maize stalk rot disease resistance mechanisms and breeding had mainly focused on other pathogens, neglecting P. aristosporum. To mitigate crop loss, resistance breeding is the most economical and effective strategy against this disease. This study involved characterizing resistance in 295 inbred lines using the drilling inoculation method and genotyping them via sequencing. By combining with population structure, disease resistance phenotype, and genome-wide association study (GWAS), we identified 39 significant single-nucleotide polymorphisms (SNPs) associated with P. aristosporum stalk rot resistance by utilizing six statistical methods. Bioinformatics analysis of these SNPs revealed 69 potential resistance genes, among which Zm00001d051313 was finally evaluated for its roles in host defense response to P. aristosporum infection. Through virus-induced gene silencing (VIGS) verification and physiological index determination, we found that transient silencing of Zm00001d051313 promoted P. aristosporum infection, indicating a positive regulatory role of this gene in maize's antifungal defense mechanism. Therefore, these findings will help advance our current understanding of the underlying mechanisms of maize defense to Pythium stalk rot.
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Affiliation(s)
- Mengwei Hou
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Yanyong Cao
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Xingrui Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shulin Zhang
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Tengjiao Jia
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Jiwei Yang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Shengbo Han
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Lifeng Wang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Jingjing Li
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Hao Wang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Lili Zhang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Xiaolin Wu
- College of Life Science, Henan Agricultural University, Zhengzhou, China
| | - Canxing Duan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huiyong Li
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
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Chen C, Zhang K, Liu F, Wang X, Yao Y, Niu X, He Y, Hong J, Liu F, Gao Q, Zhang Y, Li Y, Wang M, Lin J, Fan Y, Ren K, Shen L, Gao B, Ren X, Yang W, Georgiev MI, Zhang X, Zhou M. Resequencing of global Lotus corniculatus accessions reveals population distribution and genetic loci, associated with cyanogenic glycosides accumulation and growth traits. BMC Biol 2023; 21:176. [PMID: 37592232 PMCID: PMC10433565 DOI: 10.1186/s12915-023-01670-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 07/27/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Lotus corniculatus is a widely distributed perennial legume whose great adaptability to different environments and resistance to barrenness make it an excellent forage and ecological restoration plant. However, its molecular genetics and genomic relationships among populations are yet to be uncovered. RESULT Here we report on a genomic variation map from worldwide 272 L. corniculatus accessions by genome resequencing. Our analysis suggests that L. corniculatus accessions have high genetic diversity and could be further divided into three subgroups, with the genetic diversity centers were located in Transcaucasia. Several candidate genes and SNP site associated with CNglcs content and growth traits were identified by genome-wide associated study (GWAS). A non-synonymous in LjMTR was responsible for the decreased expression of CNglcs synthesis genes and LjZCD was verified to positively regulate CNglcs synthesis gene CYP79D3. The LjZCB and an SNP in LjZCA promoter were confirmed to be involved in plant growth. CONCLUSION This study provided a large number of genomic resources and described genetic relationship and population structure among different accessions. Moreover, we attempt to provide insights into the molecular studies and breeding of CNglcs and growth traits in L. corniculatus.
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Affiliation(s)
- Cheng Chen
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- National Nanfan Research Institute, Chinese Academy of Agricultural Sciences, Sanya, 572024, China
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Kaixuan Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Fu Liu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Xia Wang
- Annoroad Gene Technology (Beijing) Co., Ltd., Beijing, 100177, China
| | - Yang Yao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xiaolei Niu
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresource, College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Yuqi He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jun Hong
- National Herbage Gempiasm Bank of China, National Animal Husbandry Service, Beijing, 100125, China
| | - Fang Liu
- National Herbage Gempiasm Bank of China, National Animal Husbandry Service, Beijing, 100125, China
| | - Qiu Gao
- National Herbage Gempiasm Bank of China, National Animal Husbandry Service, Beijing, 100125, China
| | - Yi Zhang
- National Herbage Gempiasm Bank of China, National Animal Husbandry Service, Beijing, 100125, China
| | - Yurong Li
- National Herbage Gempiasm Bank of China, National Animal Husbandry Service, Beijing, 100125, China
| | - Meijuan Wang
- National Herbage Gempiasm Bank of China, National Animal Husbandry Service, Beijing, 100125, China
| | - Jizhen Lin
- National Herbage Gempiasm Bank of China, National Animal Husbandry Service, Beijing, 100125, China
| | - Yu Fan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Kui Ren
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Lunhao Shen
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Bin Gao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xue Ren
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Weifei Yang
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Milen I Georgiev
- Laboratory of Metabolomics, The Stephan Angeloff Institute of Microbiology, Bulgarian Academy of Sciences, Plovdiv, Bulgaria
- Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
| | - Xinquan Zhang
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China.
| | - Meiliang Zhou
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
- National Nanfan Research Institute, Chinese Academy of Agricultural Sciences, Sanya, 572024, China.
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Rani R, Raza G, Ashfaq H, Rizwan M, Razzaq MK, Waheed MQ, Shimelis H, Babar AD, Arif M. Genome-wide association study of soybean ( Glycine max [L.] Merr.) germplasm for dissecting the quantitative trait nucleotides and candidate genes underlying yield-related traits. Front Plant Sci 2023; 14:1229495. [PMID: 37636105 PMCID: PMC10450938 DOI: 10.3389/fpls.2023.1229495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 08/29/2023]
Abstract
Soybean (Glycine max [L.] Merr.) is one of the most significant crops in the world in terms of oil and protein. Owing to the rising demand for soybean products, there is an increasing need for improved varieties for more productive farming. However, complex correlation patterns among quantitative traits along with genetic interactions pose a challenge for soybean breeding. Association studies play an important role in the identification of accession with useful alleles by locating genomic sites associated with the phenotype in germplasm collections. In the present study, a genome-wide association study was carried out for seven agronomic and yield-related traits. A field experiment was conducted in 2015/2016 at two locations that include 155 diverse soybean germplasm. These germplasms were genotyped using SoySNP50K Illumina Infinium Bead-Chip. A total of 51 markers were identified for node number, plant height, pods per plant, seeds per plant, seed weight per plant, hundred-grain weight, and total yield using a multi-locus linear mixed model (MLMM) in FarmCPU. Among these significant SNPs, 18 were putative novel QTNs, while 33 co-localized with previously reported QTLs. A total of 2,356 genes were found in 250 kb upstream and downstream of significant SNPs, of which 17 genes were functional and the rest were hypothetical proteins. These 17 candidate genes were located in the region of 14 QTNs, of which ss715580365, ss715608427, ss715632502, and ss715620131 are novel QTNs for PH, PPP, SDPP, and TY respectively. Four candidate genes, Glyma.01g199200, Glyma.10g065700, Glyma.18g297900, and Glyma.14g009900, were identified in the vicinity of these novel QTNs, which encode lsd one like 1, Ergosterol biosynthesis ERG4/ERG24 family, HEAT repeat-containing protein, and RbcX2, respectively. Although further experimental validation of these candidate genes is required, several appear to be involved in growth and developmental processes related to the respective agronomic traits when compared with their homologs in Arabidopsis thaliana. This study supports the usefulness of association studies and provides valuable data for functional markers and investigating candidate genes within a diverse germplasm collection in future breeding programs.
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Affiliation(s)
- Reena Rani
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Ghulam Raza
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Hamza Ashfaq
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Rizwan
- Plant Breeding and Genetics Division, Nuclear Institute of Agriculture (NIA), Tando Jam, Pakistan
| | - Muhammad Khuram Razzaq
- Soybean Research Institute, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, China
| | - Muhammad Qandeel Waheed
- Plant Breeding and Genetics Division, Nuclear Institute for Agriculture and Biology (NIAB), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Hussein Shimelis
- School of Agricultural, Earth and Environmental Sciences, African Centre for Crop Improvement, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Allah Ditta Babar
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Arif
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
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Song B, Ning W, Wei D, Jiang M, Zhu K, Wang X, Edwards D, Odeny DA, Cheng S. Plant genome resequencing and population genomics: Current status and future prospects. Mol Plant 2023; 16:1252-1268. [PMID: 37501370 DOI: 10.1016/j.molp.2023.07.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023]
Abstract
Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.
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Affiliation(s)
- Bo Song
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Weidong Ning
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; Huazhong Agricultural University, College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Wuhan, Hubei, China
| | - Di Wei
- Biotechnology Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 53007, China
| | - Mengyun Jiang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Kun Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Xingwei Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Damaris A Odeny
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) - Eastern and Southern Africa, Nairobi, Kenya
| | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
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50
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Yocca AE, Platts A, Alger E, Teresi S, Mengist MF, Benevenuto J, Ferrão LFV, Jacobs M, Babinski M, Magallanes-Lundback M, Bayer P, Golicz A, Humann JL, Main D, Espley RV, Chagné D, Albert NW, Montanari S, Vorsa N, Polashock J, Díaz-Garcia L, Zalapa J, Bassil NV, Munoz PR, Iorizzo M, Edger PP. Blueberry and cranberry pangenomes as a resource for future genetic studies and breeding efforts. bioRxiv 2023:2023.07.31.551392. [PMID: 37577683 PMCID: PMC10418200 DOI: 10.1101/2023.07.31.551392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Domestication of cranberry and blueberry began in the United States in the early 1800s and 1900s, respectively, and in part owing to their flavors and health-promoting benefits are now cultivated and consumed worldwide. The industry continues to face a wide variety of production challenges (e.g. disease pressures) as well as a demand for higher-yielding cultivars with improved fruit quality characteristics. Unfortunately, molecular tools to help guide breeding efforts for these species have been relatively limited compared with those for other high-value crops. Here, we describe the construction and analysis of the first pangenome for both blueberry and cranberry. Our analysis of these pangenomes revealed both crops exhibit great genetic diversity, including the presence-absence variation of 48.4% genes in highbush blueberry and 47.0% genes in cranberry. Auxiliary genes, those not shared by all cultivars, are significantly enriched with molecular functions associated with disease resistance and the biosynthesis of specialized metabolites, including compounds previously associated with improving fruit quality traits. The discovery of thousands of genes, not present in the previous reference genomes for blueberry and cranberry, will serve as the basis of future research and as potential targets for future breeding efforts. The pangenome, as a multiple-sequence alignment, as well as individual annotated genomes, are publicly available for analysis on the Genome Database for Vaccinium - a curated and integrated web-based relational database. Lastly, the core-gene predictions from the pangenomes will serve useful to develop a community genotyping platform to guide future molecular breeding efforts across the family.
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Affiliation(s)
- Alan E. Yocca
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Adrian Platts
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Elizabeth Alger
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
| | - Scott Teresi
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
- Genetics and Genome Sciences, Michigan State University, East Lansing, MI, 48824, USA
| | - Molla F. Mengist
- Plants for Human Health Institute, North Carolina State University, Kannapolis, NC USA
| | - Juliana Benevenuto
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA
| | - Luis Felipe V. Ferrão
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA
| | - MacKenzie Jacobs
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Michal Babinski
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
| | | | - Philipp Bayer
- University of Western Australia, Perth 6009 Australia
| | | | - Jodi L Humann
- Department of Horticulture, Washington State University, Pullman, WA, 99163, USA
| | - Dorrie Main
- Department of Horticulture, Washington State University, Pullman, WA, 99163, USA
| | - Richard V. Espley
- The New Zealand Institute for Plant and Food Research Limited (PFR), Auckland, New Zealand
| | - David Chagné
- The New Zealand Institute for Plant and Food Research Limited (PFR), Palmerston, New Zealand
| | - Nick W. Albert
- The New Zealand Institute for Plant and Food Research Limited (PFR), Palmerston, New Zealand
| | - Sara Montanari
- The New Zealand Institute for Plant and Food Research Limited (PFR), Motueka, New Zealand
| | - Nicholi Vorsa
- SEBS, Plant Biology, Rutgers University, New Brunswick NJ 01019 USA
| | - James Polashock
- SEBS, Plant Biology, Rutgers University, New Brunswick NJ 01019 USA
| | - Luis Díaz-Garcia
- USDA-ARS, VCRU, Department of Horticulture, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Juan Zalapa
- USDA-ARS, VCRU, Department of Horticulture, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Nahla V. Bassil
- USDA-ARS, National Clonal Germplasm Repository, Corvallis, OR 97333, USA
| | - Patricio R. Munoz
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA
| | - Massimo Iorizzo
- Plants for Human Health Institute, North Carolina State University, Kannapolis, NC USA
- Department of Horticulture, North Carolina State University, Kannapolis, NC USA
| | - Patrick P. Edger
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
- Genetics and Genome Sciences, Michigan State University, East Lansing, MI, 48824, USA
- MSU AgBioResearch, Michigan State University, East Lansing, MI, 48824, USA
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