1
|
Wang Z, Yung WS, Gao Y, Huang C, Zhao X, Chen Y, Li MW, Lam HM. From phenotyping to genetic mapping: identifying water-stress adaptations in legume root traits. BMC PLANT BIOLOGY 2024; 24:749. [PMID: 39103780 DOI: 10.1186/s12870-024-05477-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 08/01/2024] [Indexed: 08/07/2024]
Abstract
BACKGROUND Climate change induces perturbation in the global water cycle, profoundly impacting water availability for agriculture and therefore global food security. Water stress encompasses both drought (i.e. water scarcity) that causes the drying of soil and subsequent plant desiccation, and flooding, which results in excess soil water and hypoxia for plant roots. Terrestrial plants have evolved diverse mechanisms to cope with soil water stress, with the root system serving as the first line of defense. The responses of roots to water stress can involve both structural and physiological changes, and their plasticity is a vital feature of these adaptations. Genetic methodologies have been extensively employed to identify numerous genetic loci linked to water stress-responsive root traits. This knowledge is immensely important for developing crops with optimal root systems that enhance yield and guarantee food security under water stress conditions. RESULTS This review focused on the latest insights into modifications in the root system architecture and anatomical features of legume roots in response to drought and flooding stresses. Special attention was given to recent breakthroughs in understanding the genetic underpinnings of legume root development under water stress. The review also described various root phenotyping techniques and examples of their applications in different legume species. Finally, the prevailing challenges and prospective research avenues in this dynamic field as well as the potential for using root system architecture as a breeding target are discussed. CONCLUSIONS This review integrated the latest knowledge of the genetic components governing the adaptability of legume roots to water stress, providing a reference for using root traits as the new crop breeding targets.
Collapse
Affiliation(s)
- Zhili Wang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Wai-Shing Yung
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Yamin Gao
- College of Resources and Environment, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Cheng Huang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Key Laboratory of the Ministry of Education for Crop Physiology and Molecular Biology, College of Agronomy, Hunan Agricultural University, Changsha, 410128, China
| | - Xusheng Zhao
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Yinglong Chen
- The UWA Institute of Agriculture, & School of Agriculture and Environment, The University of Western Australia, Perth, WA, 6001, Australia
| | - Man-Wah Li
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Hon-Ming Lam
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China.
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.
| |
Collapse
|
2
|
Nakhforoosh A, Hallin E, Karunakaran C, Korbas M, Stobbs J, Kochian L. Visualization and Quantitative Evaluation of Functional Structures of Soybean Root Nodules via Synchrotron X-ray Imaging. PLANT PHENOMICS (WASHINGTON, D.C.) 2024; 6:0203. [PMID: 39021394 PMCID: PMC11254386 DOI: 10.34133/plantphenomics.0203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 05/26/2024] [Indexed: 07/20/2024]
Abstract
The efficiency of N2-fixation in legume-rhizobia symbiosis is a function of root nodule activity. Nodules consist of 2 functionally important tissues: (a) a central infected zone (CIZ), colonized by rhizobia bacteria, which serves as the site of N2-fixation, and (b) vascular bundles (VBs), serving as conduits for the transport of water, nutrients, and fixed nitrogen compounds between the nodules and plant. A quantitative evaluation of these tissues is essential to unravel their functional importance in N2-fixation. Employing synchrotron-based x-ray microcomputed tomography (SR-μCT) at submicron resolutions, we obtained high-quality tomograms of fresh soybean root nodules in a non-invasive manner. A semi-automated segmentation algorithm was employed to generate 3-dimensional (3D) models of the internal root nodule structure of the CIZ and VBs, and their volumes were quantified based on the reconstructed 3D structures. Furthermore, synchrotron x-ray fluorescence imaging revealed a distinctive localization of Fe within CIZ tissue and Zn within VBs, allowing for their visualization in 2 dimensions. This study represents a pioneer application of the SR-μCT technique for volumetric quantification of CIZ and VB tissues in fresh, intact soybean root nodules. The proposed methods enable the exploitation of root nodule's anatomical features as novel traits in breeding, aiming to enhance N2-fixation through improved root nodule activity.
Collapse
Affiliation(s)
| | - Emil Hallin
- Global Institute for Food Security, Saskatoon, SK S7N 4L8, Canada
| | | | | | - Jarvis Stobbs
- Canadian Light Source Inc., Saskatoon, SK S7N 2V3, Canada
| | - Leon Kochian
- Global Institute for Food Security, Saskatoon, SK S7N 4L8, Canada
| |
Collapse
|
3
|
Islam MS, Ghimire A, Lay L, Khan W, Lee JD, Song Q, Jo H, Kim Y. Identification of Quantitative Trait Loci Controlling Root Morphological Traits in an Interspecific Soybean Population Using 2D Imagery Data. Int J Mol Sci 2024; 25:4687. [PMID: 38731906 PMCID: PMC11083680 DOI: 10.3390/ijms25094687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/23/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
Roots are the hidden and most important part of plants. They serve as stabilizers and channels for uptaking water and nutrients and play a crucial role in the growth and development of plants. Here, two-dimensional image data were used to identify quantitative trait loci (QTL) controlling root traits in an interspecific mapping population derived from a cross between wild soybean 'PI366121' and cultivar 'Williams 82'. A total of 2830 single-nucleotide polymorphisms were used for genotyping, constructing genetic linkage maps, and analyzing QTLs. Forty-two QTLs were identified on twelve chromosomes, twelve of which were identified as major QTLs, with a phenotypic variation range of 36.12% to 39.11% and a logarithm of odds value range of 12.01 to 17.35. Two significant QTL regions for the average diameter, root volume, and link average diameter root traits were detected on chromosomes 3 and 13, and both wild and cultivated soybeans contributed positive alleles. Six candidate genes, Glyma.03G027500 (transketolase/glycoaldehyde transferase), Glyma.03G014500 (dehydrogenases), Glyma.13G341500 (leucine-rich repeat receptor-like protein kinase), Glyma.13G341400 (AGC kinase family protein), Glyma.13G331900 (60S ribosomal protein), and Glyma.13G333100 (aquaporin transporter) showed higher expression in root tissues based on publicly available transcriptome data. These results will help breeders improve soybean genetic components and enhance soybean root morphological traits using desirable alleles from wild soybeans.
Collapse
Affiliation(s)
- Mohammad Shafiqul Islam
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea; (M.S.I.); (A.G.); (L.L.); (W.K.); (J.-D.L.); (H.J.)
- Department of Integrative Biology, Kyungpook National University, Daegu 41566, Republic of Korea
- Department of Agriculture, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
| | - Amit Ghimire
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea; (M.S.I.); (A.G.); (L.L.); (W.K.); (J.-D.L.); (H.J.)
- Department of Integrative Biology, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Liny Lay
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea; (M.S.I.); (A.G.); (L.L.); (W.K.); (J.-D.L.); (H.J.)
- Department of Integrative Biology, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Waleed Khan
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea; (M.S.I.); (A.G.); (L.L.); (W.K.); (J.-D.L.); (H.J.)
- Department of Integrative Biology, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Jeong-Dong Lee
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea; (M.S.I.); (A.G.); (L.L.); (W.K.); (J.-D.L.); (H.J.)
- Department of Integrative Biology, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville Agricultural Research Center, Beltsville, MD 20705, USA;
| | - Hyun Jo
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea; (M.S.I.); (A.G.); (L.L.); (W.K.); (J.-D.L.); (H.J.)
| | - Yoonha Kim
- Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea; (M.S.I.); (A.G.); (L.L.); (W.K.); (J.-D.L.); (H.J.)
- Department of Integrative Biology, Kyungpook National University, Daegu 41566, Republic of Korea
- Upland Field Machinery Research Center, Kyungpook National University, Daegu 41566, Republic of Korea
| |
Collapse
|
4
|
Lee D, Lara L, Moseley D, Vuong TD, Shannon G, Xu D, Nguyen HT. Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean ( Glycine max (L.) Merr.). FRONTIERS IN PLANT SCIENCE 2023; 14:1294659. [PMID: 38023839 PMCID: PMC10646508 DOI: 10.3389/fpls.2023.1294659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023]
Abstract
The nutritional value of soybean [Glycine max (L.) Merr.] for animals is influenced by soluble carbohydrates, such as sucrose and stachyose. Although sucrose is nutritionally desirable, stachyose is an antinutrient causing diarrhea and flatulence in non-ruminant animals. We conducted a genome-wide association study of 220 soybean accessions using 21,317 single nucleotide polymorphisms (SNPs) from the SoySNP50K iSelect Beadchip data to identify significant SNPs associated with sucrose and stachyose content. Seven significant SNPs were identified for sucrose content across chromosomes (Chrs.) 2, 8, 12, 17, and 20, while thirteen significant SNPs were identified for stachyose content across Chrs. 2, 5, 8, 9, 10, 13, 14, and 15. Among those significant SNPs, three sucrose-related SNPs on Chrs. 8 and 17 were novel, while twelve stachyose-related SNPs on Chrs. 2, 5, 8, 9, 10, 13, 14, and 15 were novel. Based on Phytozome, STRING, and GO annotation, 17 and 24 candidate genes for sucrose and stachyose content, respectively, were highly associated with the carbohydrate metabolic pathway. Among these, the publicly available RNA-seq Atlas database highlighted four candidate genes associated with sucrose (Glyma.08g361200 and Glyma.17g258100) and stachyose (Glyma.05g025300 and Glyma.13g077900) content, which had higher gene expression levels in developing seed and multiple parts of the soybean plant. The results of this study will extend knowledge of the molecular mechanism and genetic basis underlying sucrose and stachyose content in soybean seed. Furthermore, the novel candidate genes and SNPs can be valuable genetic resources that soybean breeders may utilize to modify carbohydrate profiles for animal and human usage.
Collapse
Affiliation(s)
- Dongho Lee
- Fisher Delta Research, Extension, and Education Center, Division of Plant Science and Technology, University of Missouri, Portageville, MO, United States
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Laura Lara
- Agrícola Los Alpes, Chimaltenango, Guatemala
| | - David Moseley
- Dean Lee Research and Extension Center, LSU AgCenter, Alexandria, LA, United States
| | - Tri D. Vuong
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Grover Shannon
- Fisher Delta Research, Extension, and Education Center, Division of Plant Science and Technology, University of Missouri, Portageville, MO, United States
| | - Dong Xu
- Department of Electrical Engineering and Computer Sciences, Christopher S. Bond Life Science Center, University of Missouri, Columbia, MO, United States
| | - Henry T. Nguyen
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| |
Collapse
|
5
|
Chandnani R, Qin T, Ye H, Hu H, Panjvani K, Tokizawa M, Macias JM, Medina AA, Bernardino K, Pradier PL, Banik P, Mooney A, V Magalhaes J, T Nguyen H, Kochian LV. Application of an Improved 2-Dimensional High-Throughput Soybean Root Phenotyping Platform to Identify Novel Genetic Variants Regulating Root Architecture Traits. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0097. [PMID: 37780968 PMCID: PMC10538525 DOI: 10.34133/plantphenomics.0097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 09/05/2023] [Indexed: 10/03/2023]
Abstract
Nutrient-efficient root system architecture (RSA) is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency. Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition. Here, we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water. We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers, which can be erroneously quantified as root tips. This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms. There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips (95% correlation), when the background was cleaned of nonroot materials compared to root images without the background corrected (79%). Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips. Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth, total root length and surface area, and root system volume and surface area of thicker roots (DOF1-like zinc finger transcription factor, protein of unknown function, and C2H2 zinc finger protein). We also identified a putative negative regulator (gibberellin 20 oxidase 3) of the total number of lateral roots.
Collapse
Affiliation(s)
- Rahul Chandnani
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
- NRGene Canada, 110 Research Dr Suite 101, Saskatoon, SK, Canada
| | - Tongfei Qin
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Heng Ye
- Division of Plant Sciences and Technology, University of Missouri, Columbia, MO 65211, USA
| | - Haifei Hu
- School of Biological Sciences, The University of Western Australia, Crawley, WA 6009, Australia
- Rice Research Institute, Guangdong Academy of Agricultural Sciences & Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China(Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs & Guangdong Key Laboratory of New Technology in Rice Breeding & Guangdong Rice Engineering Laboratory, Guangdong, China
| | - Karim Panjvani
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Mutsutomo Tokizawa
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Javier Mora Macias
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Alma Armenta Medina
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | | | - Pierre-Luc Pradier
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Pankaj Banik
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Ashlyn Mooney
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | | | - Henry T Nguyen
- Division of Plant Sciences and Technology, University of Missouri, Columbia, MO 65211, USA
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Leon V Kochian
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK, Canada
| |
Collapse
|
6
|
Griffiths M, Liu AE, Gunn SL, Mutan NM, Morales EY, Topp CN. A temporal analysis and response to nitrate availability of 3D root system architecture in diverse pennycress ( Thlaspi arvense L.) accessions. FRONTIERS IN PLANT SCIENCE 2023; 14:1145389. [PMID: 37426970 PMCID: PMC10327891 DOI: 10.3389/fpls.2023.1145389] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 05/23/2023] [Indexed: 07/11/2023]
Abstract
Introduction Roots have a central role in plant resource capture and are the interface between the plant and the soil that affect multiple ecosystem processes. Field pennycress (Thlaspi arvense L.) is a diploid annual cover crop species that has potential utility for reducing soil erosion and nutrient losses; and has rich seeds (30-35% oil) amenable to biofuel production and as a protein animal feed. The objective of this research was to (1) precisely characterize root system architecture and development, (2) understand plastic responses of pennycress roots to nitrate nutrition, (3) and determine genotypic variance available in root development and nitrate plasticity. Methods Using a root imaging and analysis pipeline, the 4D architecture of the pennycress root system was characterized under four nitrate regimes, ranging from zero to high nitrate concentrations. These measurements were taken at four time points (days 5, 9, 13, and 17 after sowing). Results Significant nitrate condition response and genotype interactions were identified for many root traits, with the greatest impact observed on lateral root traits. In trace nitrate conditions, a greater lateral root count, length, density, and a steeper lateral root angle was observed compared to high nitrate conditions. Additionally, genotype-by-nitrate condition interaction was observed for root width, width:depth ratio, mean lateral root length, and lateral root density. Discussion These findings illustrate root trait variance among pennycress accessions. These traits could serve as targets for breeding programs aimed at developing improved cover crops that are responsive to nitrate, leading to enhanced productivity, resilience, and ecosystem service.
Collapse
|
7
|
Liyanage DK, Torkamaneh D, Belzile F, Balasubramanian P, Hill B, Thilakarathna MS. The Genotypic Variability among Short-Season Soybean Cultivars for Nitrogen Fixation under Drought Stress. PLANTS (BASEL, SWITZERLAND) 2023; 12:1004. [PMID: 36903865 PMCID: PMC10005650 DOI: 10.3390/plants12051004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/16/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
Soybean fixes atmospheric nitrogen through the symbiotic rhizobia bacteria that inhabit root nodules. Drought stress negatively affect symbiotic nitrogen fixation (SNF) in soybean. The main objective of this study was to identify allelic variations associated with SNF in short-season Canadian soybean varieties under drought stress. A diversity panel of 103 early-maturity Canadian soybean varieties was evaluated under greenhouse conditions to determine SNF-related traits under drought stress. Drought was imposed after three weeks of plant growth, where plants were maintained at 30% field capacity (FC) (drought) and 80% FC (well-watered) until seed maturity. Under drought stress, soybean plants had lower seed yield, yield components, seed nitrogen content, % nitrogen derived from the atmosphere (%Ndfa), and total seed nitrogen fixed compared to those under well-watered conditions. Significant genotypic variability among soybean varieties was found for yield, yield parameters, and nitrogen fixation traits. A genome-wide association study (GWAS) was conducted using 2.16 M single nucleotide single nucleotide polymorphisms (SNPs) for different yield and nitrogen fixation related parameters for 30% FC and their relative performance (30% FC/80% FC). In total, five quantitative trait locus (QTL) regions, including candidate genes, were detected as significantly associated with %Ndfa under drought stress and relative performance. These genes can potentially aid in future breeding efforts to develop drought-resistant soybean varieties.
Collapse
Affiliation(s)
- Dilrukshi Kombala Liyanage
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Québec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC G1V 0A6, Canada
| | - François Belzile
- Département de Phytologie, Université Laval, Québec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC G1V 0A6, Canada
| | - Parthiba Balasubramanian
- Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB T1J 4B1, Canada
| | - Brett Hill
- Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB T1J 4B1, Canada
| | - Malinda S. Thilakarathna
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| |
Collapse
|
8
|
Chen Z, Wang L, Cardoso JA, Zhu S, Liu G, Rao IM, Lin Y. Improving phosphorus acquisition efficiency through modification of root growth responses to phosphate starvation in legumes. FRONTIERS IN PLANT SCIENCE 2023; 14:1094157. [PMID: 36844096 PMCID: PMC9950756 DOI: 10.3389/fpls.2023.1094157] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
Phosphorus (P) is one of the essential macronutrients for plant growth and development, and it is an integral part of the major organic components, including nucleic acids, proteins and phospholipids. Although total P is abundant in most soils, a large amount of P is not easily absorbed by plants. Inorganic phosphate (Pi) is the plant-available P, which is generally immobile and of low availability in soils. Hence, Pi starvation is a major constraint limiting plant growth and productivity. Enhancing plant P efficiency can be achieved by improving P acquisition efficiency (PAE) through modification of morpho-physiological and biochemical alteration in root traits that enable greater acquisition of external Pi from soils. Major advances have been made to dissect the mechanisms underlying plant adaptation to P deficiency, especially for legumes, which are considered important dietary sources for humans and livestock. This review aims to describe how legume root growth responds to Pi starvation, such as changes in the growth of primary root, lateral roots, root hairs and cluster roots. In particular, it summarizes the various strategies of legumes to confront P deficiency by regulating root traits that contribute towards improving PAE. Within these complex responses, a large number of Pi starvation-induced (PSI) genes and regulators involved in the developmental and biochemical alteration of root traits are highlighted. The involvement of key functional genes and regulators in remodeling root traits provides new opportunities for developing legume varieties with maximum PAE needed for regenerative agriculture.
Collapse
Affiliation(s)
- Zhijian Chen
- Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Linjie Wang
- Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | | | - Shengnan Zhu
- Life Science and Technology School, Lingnan Normal University, Zhanjiang, China
| | - Guodao Liu
- Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Idupulapati M. Rao
- International Center for Tropical Agriculture (CIAT), Cali, Colombia
- International Centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya
| | - Yan Lin
- Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
- Institute of Bioengineering, Guangdong Academy of Sciences, Guangzhou, China
| |
Collapse
|
9
|
Genome-Wide Association Studies of Seven Root Traits in Soybean ( Glycine max L.) Landraces. Int J Mol Sci 2023; 24:ijms24010873. [PMID: 36614316 PMCID: PMC9821504 DOI: 10.3390/ijms24010873] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/07/2022] [Accepted: 12/08/2022] [Indexed: 01/05/2023] Open
Abstract
Soybean [Glycine max (L.) Merr.], an important oilseed crop, is a low-cost source of protein and oil. In Southeast Asia and Africa, soybeans are widely cultivated for use as traditional food and feed and industrial purposes. Given the ongoing changes in global climate, developing crops that are resistant to climatic extremes and produce viable yields under predicted climatic conditions will be essential in the coming decades. To develop such crops, it will be necessary to gain a thorough understanding of the genetic basis of agronomic and plant root traits. As plant roots generally lie beneath the soil surface, detailed observations and phenotyping throughout plant development present several challenges, and thus the associated traits have tended to be ignored in genomics studies. In this study, we phenotyped 357 soybean landraces at the early vegetative (V2) growth stages and used a 180 K single-nucleotide polymorphism (SNP) soybean array in a genome-wide association study (GWAS) conducted to determine the phenotypic relationships among root traits, elucidate the genetic bases, and identify significant SNPs associated with root trait-controlling genomic regions/loci. A total of 112 significant SNP loci/regions were detected for seven root traits, and we identified 55 putative candidate genes considered to be the most promising. Our findings in this study indicate that a combined approach based on SNP array and GWAS analyses can be applied to unravel the genetic basis of complex root traits in soybean, and may provide an alternative high-resolution marker strategy to traditional bi-parental mapping. In addition, the identified SNPs, candidate genes, and diverse variations in the root traits of soybean landraces will serve as a valuable basis for further application in genetic studies and the breeding of climate-resilient soybeans characterized by improved root traits.
Collapse
|
10
|
Belzile F, Jean M, Torkamaneh D, Tardivel A, Lemay MA, Boudhrioua C, Arsenault-Labrecque G, Dussault-Benoit C, Lebreton A, de Ronne M, Tremblay V, Labbé C, O’Donoughue L, St-Amour VTB, Copley T, Fortier E, Ste-Croix DT, Mimee B, Cober E, Rajcan I, Warkentin T, Gagnon É, Legay S, Auclair J, Bélanger R. The SoyaGen Project: Putting Genomics to Work for Soybean Breeders. FRONTIERS IN PLANT SCIENCE 2022; 13:887553. [PMID: 35557742 PMCID: PMC9087807 DOI: 10.3389/fpls.2022.887553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 03/24/2022] [Indexed: 06/15/2023]
Abstract
The SoyaGen project was a collaborative endeavor involving Canadian soybean researchers and breeders from academia and the private sector as well as international collaborators. Its aims were to develop genomics-derived solutions to real-world challenges faced by breeders. Based on the needs expressed by the stakeholders, the research efforts were focused on maximizing realized yield through optimization of maturity and improved disease resistance. The main deliverables related to molecular breeding in soybean will be reviewed here. These include: (1) SNP datasets capturing the genetic diversity within cultivated soybean (both within a worldwide collection of > 1,000 soybean accessions and a subset of 102 short-season accessions (MG0 and earlier) directly relevant to this group); (2) SNP markers for selecting favorable alleles at key maturity genes as well as loci associated with increased resistance to key pathogens and pests (Phytophthora sojae, Heterodera glycines, Sclerotinia sclerotiorum); (3) diagnostic tools to facilitate the identification and mapping of specific pathotypes of P. sojae; and (4) a genomic prediction approach to identify the most promising combinations of parents. As a result of this fruitful collaboration, breeders have gained new tools and approaches to implement molecular, genomics-informed breeding strategies. We believe these tools and approaches are broadly applicable to soybean breeding efforts around the world.
Collapse
Affiliation(s)
- François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Martine Jean
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Aurélie Tardivel
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Marc-André Lemay
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Chiheb Boudhrioua
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | | | | | - Amandine Lebreton
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Maxime de Ronne
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Vanessa Tremblay
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Caroline Labbé
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Louise O’Donoughue
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Vincent-Thomas Boucher St-Amour
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Tanya Copley
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | - Eric Fortier
- Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada
| | | | - Benjamin Mimee
- Agriculture and Agri-Food Canada, St-Jean-sur-Richelieu, QC, Canada
| | - Elroy Cober
- Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Tom Warkentin
- Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Éric Gagnon
- Semences Prograin Inc., Saint-Césaire, QC, Canada
- Sevita Genetics, Inkerman, ON, Canada
| | | | | | - Richard Bélanger
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| |
Collapse
|
11
|
Sandhu KS, Merrick LF, Sankaran S, Zhang Z, Carter AH. Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs. Front Genet 2022. [PMCID: PMC8814369 DOI: 10.3389/fgene.2021.829131] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The last decade witnessed an unprecedented increase in the adoption of genomic selection (GS) and phenomics tools in plant breeding programs, especially in major cereal crops. GS has demonstrated the potential for selecting superior genotypes with high precision and accelerating the breeding cycle. Phenomics is a rapidly advancing domain to alleviate phenotyping bottlenecks and explores new large-scale phenotyping and data acquisition methods. In this review, we discuss the lesson learned from GS and phenomics in six self-pollinated crops, primarily focusing on rice, wheat, soybean, common bean, chickpea, and groundnut, and their implementation schemes are discussed after assessing their impact in the breeding programs. Here, the status of the adoption of genomics and phenomics is provided for those crops, with a complete GS overview. GS’s progress until 2020 is discussed in detail, and relevant information and links to the source codes are provided for implementing this technology into plant breeding programs, with most of the examples from wheat breeding programs. Detailed information about various phenotyping tools is provided to strengthen the field of phenomics for a plant breeder in the coming years. Finally, we highlight the benefits of merging genomic selection, phenomics, and machine and deep learning that have resulted in extraordinary results during recent years in wheat, rice, and soybean. Hence, there is a potential for adopting these technologies into crops like the common bean, chickpea, and groundnut. The adoption of phenomics and GS into different breeding programs will accelerate genetic gain that would create an impact on food security, realizing the need to feed an ever-growing population.
Collapse
Affiliation(s)
- Karansher S. Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
- *Correspondence: Karansher S. Sandhu,
| | - Lance F. Merrick
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
| | - Sindhuja Sankaran
- Department of Biological System Engineering, Washington State University, Pullman, WA, United States
| | - Zhiwu Zhang
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
| | - Arron H. Carter
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States
| |
Collapse
|
12
|
Belzile F, Torkamaneh D. Designing a Genome-Wide Association Study: Main Steps and Critical Decisions. Methods Mol Biol 2022; 2481:3-12. [PMID: 35641755 DOI: 10.1007/978-1-0716-2237-7_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In this introductory chapter, we seek to provide the reader with a high-level overview of what goes into designing a genome-wide association study (GWAS) in the context of crop plants. After introducing some general concepts regarding GWAS, we divide the contents of this overview into four main sections that reflect the key components of a GWAS: assembly and phenotyping of an association panel, genotyping, association analysis and candidate gene identification. These sections largely reflect the structure of the chapters which follow later in the book, and which provide detailed discussions of these various steps. In each section, in addition to providing external references from the literature, we also often refer the reader to the appropriate chapters in this book in which they can further explore a topic. We close by summarizing some of the key questions that a prospective user of GWAS should answer prior to undertaking this type of experiment.
Collapse
Affiliation(s)
- François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Quebec City, QC, Canada.
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada.
| |
Collapse
|
13
|
Yoosefzadeh-Najafabadi M, Torabi S, Tulpan D, Rajcan I, Eskandari M. Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods. FRONTIERS IN PLANT SCIENCE 2021; 12:777028. [PMID: 34880894 PMCID: PMC8647880 DOI: 10.3389/fpls.2021.777028] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/18/2021] [Indexed: 05/12/2023]
Abstract
In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.
Collapse
Affiliation(s)
| | - Sepideh Torabi
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Dan Tulpan
- Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| |
Collapse
|
14
|
Mandozai A, Moussa AA, Zhang Q, Qu J, Du Y, Anwari G, Al Amin N, Wang P. Genome-Wide Association Study of Root and Shoot Related Traits in Spring Soybean ( Glycine max L.) at Seedling Stages Using SLAF-Seq. FRONTIERS IN PLANT SCIENCE 2021; 12:568995. [PMID: 34394134 PMCID: PMC8355526 DOI: 10.3389/fpls.2021.568995] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 07/08/2021] [Indexed: 05/19/2023]
Abstract
Root systems can display variable genetic architectures leading to nutrient foraging or improving abiotic stress tolerance. Breeding for new soybean varieties with efficient root systems has tremendous potential in enhancing resource use efficiency and plant adaptation for challenging climates. In this study, root related traits were analyzed in a panel of 260 spring soybean with genome-wide association study (GWAS). Genotyping was done with specific locus amplified fragment sequencing (SLAF-seq), and five GWAS models (GLM, MLM, CMLM, FaST-LMM, and EMMAX) were used for analysis. A total of 179,960 highly consistent SNP markers distributed over the entire genome with an inter-marker distance of 2.36 kb was used for GWAS analysis. Overall, 27 significant SNPs with a phenotypic contribution ranging from 20 to 72% and distributed on chromosomes 2, 6, 8, 9, 13, 16 and 18 were identified and two of them were found to be associated with multiple root-related traits. Based on the linkage disequilibrium (LD) distance of 9.5 kb for the different chromosomes, 11 root and shoot regulating genes were detected based on LD region of a maximum 55-bp and phenotypic contribution greater than 22%. Expression analysis revealed an association between expression levels of those genes and the degree of root branching number. The current study provides new insights into the genetic architecture of soybean roots, and the underlying SNPs/genes could be critical for future breeding of high-efficient root system in soybean.
Collapse
|