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Taria S, Arora A, Krishna H, Manjunath KK, Meena S, Kumar S, Singh B, Krishna P, Malakondaiah AC, Das R, Alam B, Kumar S, Singh PK. Multivariate analysis and genetic dissection of staygreen and stem reserve mobilisation under combined drought and heat stress in wheat ( Triticum aestivum L.). Front Genet 2023; 14:1242048. [PMID: 37705611 PMCID: PMC10496116 DOI: 10.3389/fgene.2023.1242048] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 08/14/2023] [Indexed: 09/15/2023] Open
Abstract
Introduction: Abiotic stresses significantly reduce crop yield by adversely affecting many physio-biochemical processes. Several physiological traits have been targeted and improved for yield enhancement in limiting environmental conditions. Amongst them, staygreen and stem reserve mobilisation are two important mutually exclusive traits contributing to grain filling under drought and heat stress in wheat. Henceforth, the present study was carried out to identify the QTLs governing these traits and to identify the superiors' lines through multi-trait genotype-ideotype distance index (MGIDI) Methods: A mapping population consisting of 166 recombinant inbred lines (RILs) developed from a cross between HD3086 and HI1500 was utilized in this study. The experiment was laid down in alpha lattice design in four environmental conditions viz. Control, drought, heat and combined stress (heat and drought). Genotyping of parents and RILs was carried out with 35 K Axiom® array (Wheat breeder array). Results and Discussion: Medium to high heritability with a moderate to high correlation between traits was observed. Principal component analysis (PCA) was performed to derive latent variables in the original set of traits and the relationship of these traits with latent variables.From this study, 14 QTLs were identified, out of which 11, 2, and 1 for soil plant analysis development (SPAD) value, leaf senescence rate (LSR), and stem reserve mobilisation efficiency (SRE) respectively. Quantitative trait loci (QTLs) for SPAD value harbored various genes like Dirigent protein 6-like, Protein FATTY ACID EXPORT 3, glucan synthase-3 and Ubiquitin carboxyl-terminal hydrolase, whereas QTLs for LSR were found to contain various genes like aspartyl protease family protein, potassium transporter, inositol-tetrakisphosphate 1-kinase, and DNA polymerase epsilon subunit D-like. Furthermore, the chromosomal region for SRE was found to be associated with serine-threonine protein kinase. Serine-threonine protein kinases are involved in many signaling networks such as ABA mediated ROS signaling and acclimation to environmental stimuli. After the validation of QTLs in multilocation trials, these QTLs can be used for marker-assisted selection (MAS) in breeding programs.
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Affiliation(s)
- Sukumar Taria
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
- ICAR-Central Agroforestry Research Institute, Jhansi, Uttar Pradesh, India
| | - Ajay Arora
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Hari Krishna
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | | | - Shashi Meena
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Sudhir Kumar
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Biswabiplab Singh
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Pavithra Krishna
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | | | - Ritwika Das
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Badre Alam
- ICAR-Central Agroforestry Research Institute, Jhansi, Uttar Pradesh, India
| | - Sushil Kumar
- ICAR-Central Agroforestry Research Institute, Jhansi, Uttar Pradesh, India
| | - Pradeep Kumar Singh
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
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Ma J, Liu Y, Zhang P, Chen T, Tian T, Wang P, Che Z, Shahinnia F, Yang D. Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.). BMC PLANT BIOLOGY 2022; 22:607. [PMID: 36550393 PMCID: PMC9784057 DOI: 10.1186/s12870-022-03989-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes. RESULTS The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites. CONCLUSIONS Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.
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Grants
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- Key Sci & Tech Special Project of Gansu Province
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Affiliation(s)
- Jingfu Ma
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Yuan Liu
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peipei Zhang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
| | - Tao Chen
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Tian Tian
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peng Wang
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, Gansu, China
| | - Fahimeh Shahinnia
- Institute for Crop Science and Plant Breeding, Bavarian State Research Centre for Agriculture, Freising, Germany
| | - Delong Yang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China.
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Yang B, Chen N, Dang Y, Wang Y, Wen H, Zheng J, Zheng X, Zhao J, Lu J, Qiao L. Identification and validation of quantitative trait loci for chlorophyll content of flag leaf in wheat under different phosphorus treatments. FRONTIERS IN PLANT SCIENCE 2022; 13:1019012. [PMID: 36466250 PMCID: PMC9714299 DOI: 10.3389/fpls.2022.1019012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 10/14/2022] [Indexed: 06/17/2023]
Abstract
In wheat, the leaf chlorophyll content in flag leaves is closely related to the degree of phosphorus stress. Identifying major genes/loci associated with chlorophyll content in flag leaves under different phosphorus conditions is critical for breeding wheat varieties resistant to low phosphorus (P). Under normal, medium, and low phosphorus conditions, the chlorophyll content of flag leaves was investigated by a double haploid (DH) population derived from a cross between two popular wheat varieties Jinmai 47 and Jinmai 84, at different grain filling stages. Chlorophyll content of the DH population and parents decreased gradually during the S1 to the S3 stages and rapidly at the S4 stage. At the S4 stage, the chlorophyll content of the DH population under low phosphorus conditions was significantly lower than under normal phosphate conditions. Using a wheat 15K single-nucleotide polymorphism (SNP) panel, a total of 157 QTLs were found to be associated with chlorophyll content in flag leaf and were identified under three phosphorus conditions. The phenotypic variation explained (PVE) ranged from 3.07 to 31.66%. Under three different phosphorus conditions, 36, 30, and 48 QTLs for chlorophyll content were identified, respectively. Six major QTLs Qchl.saw-2B.1, Qchl.saw-3B.1, Qchl.saw-4D.1, Qchl.saw-4D.2, Qchl.saw-5A.9 and Qchl.saw-6A.4 could be detected under multiple phosphorus conditions in which Qchl.saw-4D.1, Qchl.saw-4D.2, and Qchl.saw-6A.4 were revealed to be novel major QTLs. Moreover, the closely linked SNP markers of Qchl.saw-4D.1 and Qchl.saw-4D.2 were validated as KASP markers in a DH population sharing the common parent Jinmai 84, showed extreme significance (P <0.01) in more than three environments under different phosphorus conditions, which has the potential to be utilized in molecular marker-assisted breeding for low phosphorus tolerance in wheat.
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Affiliation(s)
- Bin Yang
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
| | - Nan Chen
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
- College of Agronomy, Shanxi Agricultural University, Taiyuan, China
| | - Yifei Dang
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
- College of Agronomy, Shanxi Agricultural University, Taiyuan, China
| | - Yuzhi Wang
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
| | - Hongwei Wen
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
| | - Jun Zheng
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
| | - Xingwei Zheng
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
| | - Jiajia Zhao
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
| | - Jinxiu Lu
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
| | - Ling Qiao
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, China
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Borges CS, Vega R RA, Chakraborty S, Weindorf DC, Lopes G, Guimarães Guilherme LR, Curi N, Li B, Ribeiro BT. Pocket-sized sensor for controlled, quantitative and instantaneous color acquisition of plant leaves. JOURNAL OF PLANT PHYSIOLOGY 2022; 272:153686. [PMID: 35381493 DOI: 10.1016/j.jplph.2022.153686] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 01/07/2022] [Accepted: 03/23/2022] [Indexed: 06/14/2023]
Abstract
The color of plant leaves can be assessed qualitatively by color charts or after processing of digital images. This pilot study employed a novel pocket-sized sensor to obtain the color of plant leaves. In order to assess its performance, a color-dependent parameter (SPAD index) was used as the dependent variable, since there is a strong correlation between SPAD index and greenness of plant leaves. A total of 1,872 fresh and intact leaves from 13 crops were analyzed using a SPAD-502 meter and scanned using the Nix™ Pro color sensor. The color was assessed via RGB and CIELab systems. The full dataset was divided into calibration (70% of data) and validation (30% of data). For each crop and color pattern, multiple linear regression (MLR) analysis and multivariate modeling [least absolute shrinkage and selection operator (LASSO), and elastic net (ENET) regression] were employed and compared. The obtained MLR equations and multivariate models were then tested using the validation dataset based on r, R2, root mean squared error (RMSE), and mean absolute error (MAE). In both RGB and CIELab color systems, the Nix™ Pro color sensor was able to differentiate crops, and the SPAD indices were successfully predicted, mainly for mango, quinoa, peach, pear, and rice crops. Validation results indicated that ENET performed best in most crops (e.g., coffee, corn, mango, pear, rice, and soy) and very close to MLR in bean, grape, peach, and quinoa. The correlation between SPAD and greenness is crop-dependent. Overall, the Nix™ Pro color sensor was a fast, sensible and an easy way to obtain leaf color directly in the field, constituting a reliable alternative to digital camera imagery and associated image processing.
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Affiliation(s)
- Camila Silva Borges
- Department of Soil Science, Federal University of Lavras, Lavras, 37200-000, Minas Gerais State, Brazil
| | - Ruby Antonieta Vega R
- Department of Soil Science, Federal University of Lavras, Lavras, 37200-000, Minas Gerais State, Brazil
| | - Somsubhra Chakraborty
- Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur, India
| | - David C Weindorf
- Department of Earth and Atmospheric Sciences, Central Michigan University, Mount Pleasant, MI, USA
| | - Guilherme Lopes
- Department of Soil Science, Federal University of Lavras, Lavras, 37200-000, Minas Gerais State, Brazil
| | | | - Nilton Curi
- Department of Soil Science, Federal University of Lavras, Lavras, 37200-000, Minas Gerais State, Brazil
| | - Bin Li
- Department of Experimental Statistics, Louisiana State University, Baton Rouge, LA, USA
| | - Bruno Teixeira Ribeiro
- Department of Soil Science, Federal University of Lavras, Lavras, 37200-000, Minas Gerais State, Brazil.
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Yang B, Wen X, Wen H, Feng Y, Zhao J, Wu B, Zheng X, Yang C, Yang S, Qiao L, Zheng J. Identification of Genetic Loci Affecting Flag Leaf Chlorophyll in Wheat Grown under Different Water Regimes. Front Genet 2022; 13:832898. [PMID: 35368684 PMCID: PMC8965356 DOI: 10.3389/fgene.2022.832898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 01/25/2022] [Indexed: 11/29/2022] Open
Abstract
Chlorophyll content of the flag leaf is an important trait for drought resistance in wheat under drought stress. Understanding the regulatory mechanism of flag leaf chlorophyll content could accelerate breeding for drought resistance. In this study, we constructed a recombinant inbred line (RIL) population from a cross of drought-sensitive variety DH118 and drought-resistant variety Jinmai 919, and analyzed the chlorophyll contents of flag leaves in six experimental locations/years using the Wheat90K single-nucleotide polymorphism array. A total of 29 quantitative trait loci (QTLs) controlling flag leaf chlorophyll were detected with contributions to phenotypic variation ranging from 4.67 to 23.25%. Twelve QTLs were detected under irrigated conditions and 18 were detected under dryland (drought) conditions. Most of the QTLs detected under the different water regimes were different. Four major QTLs (Qchl.saw-3B.2, Qchl.saw-5A.2, Qchl.saw-5A.3, and Qchl.saw-5B.2) were detected in the RIL population. Qchl.saw-3B.2, possibly more suitable for marker-assisted selection of genotypes adapted to irrigated conditions, was validated by a tightly linked kompetitive allele specific PCR (KASP) marker in a doubled haploid population derived from a different cross. Qchl.saw-5A.3, a novel stably expressed QTL, was detected in the dryland environments and explained up to 23.25% of the phenotypic variation, and has potential for marker-assisted breeding of genotypes adapted to dryland conditions. The stable and major QTLs identified here add valuable information for understanding the genetic mechanism underlying chlorophyll content and provide a basis for molecular marker–assisted breeding.
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Affiliation(s)
- Bin Yang
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
- College of Agricultural Economics and Management, Shanxi Agricultural University, Taiyuan, China
| | - Xiaojie Wen
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongwei Wen
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
| | - Yanru Feng
- Institute of Crop Science and Resource Conservation (INRES), Crop Science, University of Bonn, Bonn, Germany
- Department of Agronomy and Crop Physiology, Institute for Agronomy and Plant Breeding, Justus Liebig University Giessen, Giessen, Germany
| | - Jiajia Zhao
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
| | - Bangbang Wu
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
| | - Xingwei Zheng
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
| | - Chenkang Yang
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
| | - Sanwei Yang
- College of Agricultural Economics and Management, Shanxi Agricultural University, Taiyuan, China
- *Correspondence: Sanwei Yang, ; Ling Qiao, ; Jun Zheng,
| | - Ling Qiao
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
- *Correspondence: Sanwei Yang, ; Ling Qiao, ; Jun Zheng,
| | - Jun Zheng
- Institute of Wheat Research, Shanxi Agricultural University/ State Key Laboratory of Sustainable Dryland Agriculture, Linfen, China
- *Correspondence: Sanwei Yang, ; Ling Qiao, ; Jun Zheng,
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Miao Y, Jing F, Ma J, Liu Y, Zhang P, Chen T, Che Z, Yang D. Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis. FRONTIERS IN PLANT SCIENCE 2022; 13:802310. [PMID: 35222467 PMCID: PMC8866663 DOI: 10.3389/fpls.2022.802310] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 01/06/2022] [Indexed: 05/21/2023]
Abstract
Grain weight is a key determinant for grain yield potential in wheat, which is highly governed by a type of quantitative genetic basis. The identification of major quantitative trait locus (QTL) and functional genes are urgently required for molecular improvements in wheat grain yield. In this study, major genomic regions and putative candidate genes for thousand grain weight (TGW) were revealed by integrative approaches with QTL linkage mapping, meta-analysis and transcriptome evaluation. Forty-five TGW QTLs were detected using a set of recombinant inbred lines, explaining 1.76-12.87% of the phenotypic variation. Of these, ten stable QTLs were identified across more than four environments. Meta-QTL (MQTL) analysis were performed on 394 initial TGW QTLs available from previous studies and the present study, where 274 loci were finally refined into 67 MQTLs. The average confidence interval of these MQTLs was 3.73-fold less than that of initial QTLs. A total of 134 putative candidate genes were mined within MQTL regions by combined analysis of transcriptomic and omics data. Some key putative candidate genes similar to those reported early for grain development and grain weight formation were further discussed. This finding will provide a better understanding of the genetic determinants of TGW and will be useful for marker-assisted selection of high yield in wheat breeding.
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Affiliation(s)
- Yongping Miao
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Fanli Jing
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Jingfu Ma
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Yuan Liu
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Peipei Zhang
- State Key Laboratory of Aridland Crop Science, Gansu, China
| | - Tao Chen
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Gansu, China
| | - Delong Yang
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
- *Correspondence: Delong Yang,
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Khan A, Ahmad M, Ahmed M, Iftikhar Hussain M. Rising Atmospheric Temperature Impact on Wheat and Thermotolerance Strategies. PLANTS 2020; 10:plants10010043. [PMID: 33375473 PMCID: PMC7823633 DOI: 10.3390/plants10010043] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 12/22/2020] [Accepted: 12/22/2020] [Indexed: 02/07/2023]
Abstract
Temperature across the globe is increasing continuously at the rate of 0.15–0.17 °C per decade since the industrial revolution. It is influencing agricultural crop productivity. Therefore, thermotolerance strategies are needed to have sustainability in crop yield under higher temperature. However, improving thermotolerance in the crop is a challenging task for crop scientists. Therefore, this review work was conducted with the aim of providing information on the wheat response in three research areas, i.e., physiology, breeding, and advances in genetics, which could assist the researchers in improving thermotolerance. The optimum temperature for wheat growth at the heading, anthesis, and grain filling duration is 16 ± 2.3 °C, 23 ± 1.75 °C, and 26 ± 1.53 °C, respectively. The high temperature adversely influences the crop phenology, growth, and development. The pre-anthesis high temperature retards the pollen viability, seed formation, and embryo development. The post-anthesis high temperature declines the starch granules accumulation, stem reserve carbohydrates, and translocation of photosynthates into grains. A high temperature above 40 °C inhibits the photosynthesis by damaging the photosystem-II, electron transport chain, and photosystem-I. Our review work highlighted that genotypes which can maintain a higher accumulation of proline, glycine betaine, expression of heat shock proteins, stay green and antioxidant enzymes activity viz., catalase, peroxidase, super oxide dismutase, and glutathione reductase can tolerate high temperature efficiently through sustaining cellular physiology. Similarly, the pre-anthesis acclimation with heat treatment, inorganic fertilizer such as nitrogen, potassium nitrate and potassium chloride, mulches with rice husk, early sowing, presoaking of a 6.6 mM solution of thiourea, foliar application of 50 ppm dithiothreitol, 10 mg per kg of silicon at heading and zinc ameliorate the crop against the high temperature. Finally, it has been suggested that modern genomics and omics techniques should be used to develop thermotolerance in wheat.
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Affiliation(s)
- Adeel Khan
- Department of Plant Breeding and Genetics, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi 46300, Pakistan; (A.K.); (M.A.)
| | - Munir Ahmad
- Department of Plant Breeding and Genetics, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi 46300, Pakistan; (A.K.); (M.A.)
| | - Mukhtar Ahmed
- Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden
- Department of Agronomy, PMAS Arid Agriculture University, Rawalpindi 46300, Pakistan
- Correspondence:
| | - M. Iftikhar Hussain
- Department of Plant Biology & Soil Science, Faculty of Biology, University of Vigo, Campus As Lagoas Marcosende, 36310 Vigo, Spain;
- CITACA, Agri-Food Research and Transfer Cluster, Campus da Auga, University of Vigo, 32004 Ourense, Spain
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Puttamadanayaka S, Harikrishna, Balaramaiah M, Biradar S, Parmeshwarappa SV, Sinha N, Prasad SVS, Mishra PC, Jain N, Singh PK, Singh GP, Prabhu KV. Mapping genomic regions of moisture deficit stress tolerance using backcross inbred lines in wheat (Triticum aestivum L.). Sci Rep 2020; 10:21646. [PMID: 33303897 PMCID: PMC7729395 DOI: 10.1038/s41598-020-78671-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 11/13/2020] [Indexed: 11/24/2022] Open
Abstract
Identification of markers associated with major physiological and yield component traits under moisture deficit stress conditions in preferred donor lines paves the way for marker-assisted selection (MAS). In the present study, a set of 183 backcross inbred lines (BILs) derived from the cross HD2733/2*C306 were genotyped using 35K Axiom genotyping array and SSR markers. The multi-trait, multi-location field phenotyping of BILs was done at three locations covering two major wheat growing zones of India, north-western plains zone (NWPZ) and central zone (CZ) under varying moisture regimes. A linkage map was constructed using 705 SNPs and 86 SSR polymorphic markers. A total of 43 genomic regions and QTL × QTL epistatic interactions were identified for 14 physiological and yield component traits, including NDVI, chlorophyll content, CT, CL, PH, GWPS, TGW and GY. Chromosomes 2A, 5D, 5A and 4B harbors greater number of QTLs for these traits. Seven Stable QTLs were identified across environment for DH (QDh.iari_6D), GWPS (QGWPS.iari_5B), PH (QPh.iari_4B-2, QPh.iari_4B-3) and NDVI (QNdvi1.iari_5D, QNdvi3.iari_5A). Nine genomic regions identified carrying major QTLs for CL, NDVI, RWC, FLA, PH, TGW and biomass explaining 10.32–28.35% of the phenotypic variance. The co-segregation of QTLs of physiological traits with yield component traits indicate the pleiotropic effects and their usefulness in the breeding programme. Our findings will be useful in dissecting genetic nature and marker-assisted selection for moisture deficit stress tolerance in wheat.
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Affiliation(s)
| | - Harikrishna
- ICAR-Indian Agricultural Research Institute, New Delhi, 110 012, India.
| | - Manu Balaramaiah
- ICAR-Indian Agricultural Research Institute, New Delhi, 110 012, India
| | - Sunil Biradar
- ICAR-Indian Agricultural Research Institute, New Delhi, 110 012, India
| | | | - Nivedita Sinha
- ICAR-Indian Agricultural Research Institute, New Delhi, 110 012, India
| | - S V Sai Prasad
- ICAR-Indian Agricultural Research Institute, New Delhi, 110 012, India
| | - P C Mishra
- Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, Madhya Pradesh, 482 004, India
| | - Neelu Jain
- ICAR-Indian Agricultural Research Institute, New Delhi, 110 012, India
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Li M, Liu Y, Ma J, Zhang P, Wang C, Su J, Yang D. Genetic dissection of stem WSC accumulation and remobilization in wheat (Triticum aestivum L.) under terminal drought stress. BMC Genet 2020; 21:50. [PMID: 32349674 PMCID: PMC7191701 DOI: 10.1186/s12863-020-00855-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 04/16/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The accumulation and remobilization of stem water soluble carbohydrates (WSC) are determinant physiological traits highly influencing yield potential in wheat against drought stress. However, knowledge gains of the genetic control are still limited. A hexaploid wheat population of 120 recombinant inbred lines were developed to identify quantitative trait loci (QTLs) and to dissect the genetic basis underlying eight traits related to stem WSC under drought stress (DS) and well-watered (WW) conditions across three environments. RESULTS Analysis of variance (ANOVA) revealed larger environmental and genotypic effects on stem WSC-related traits, indicating moderate heritabilities of 0.51-0.72. A total of 95 additive and 88 pairs of epistatic QTLs were identified with significant additive and epistatic effects, as well as QTL× water environmental interaction (QEI) effects. Most of additive QTLs and additive QEIs associated with drought-stressed environments functioned genetic effects promoting pre-anthesis WSC levels and stem WSC remobilization to developing grains. Compared to other genetic components, both genetic effects were performed exclusive contributions to phenotypic variations in stem WSC-related traits. Nineteen QTL clusters were identified on chromosomes 1B, 2A, 2B, 2D, 3B, 4B, 5A, 6A, 6B and 7A, suggestive of the genetic linkage or pleiotropy. Thirteen additive QTLs were detectable repeatedly across two of the three water environments, indicating features of stable expressions. Some loci were consistent with those reported early and were further discussed. CONCLUSION Stem WSC-related traits were inherited predominantly by additive and QEI effects with a moderate heritability. QTL cluster regions were suggestive of tight linkage or pleiotropy in the inheritance of these traits. Some stable and common loci, as well as closely linked molecular markers, had great potential in marker-assisted selection to improve stem WSC-related traits in wheat, especially under drought-stressed environments.
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Affiliation(s)
- Mengfei Li
- Gansu Provincial Key Lab of Aridland Crop Science, Lanzhou, 730070 Gansu China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070 Gansu China
| | - Yuan Liu
- Gansu Provincial Key Lab of Aridland Crop Science, Lanzhou, 730070 Gansu China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070 Gansu China
| | - Jingfu Ma
- Gansu Provincial Key Lab of Aridland Crop Science, Lanzhou, 730070 Gansu China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070 Gansu China
| | - Peipei Zhang
- Gansu Provincial Key Lab of Aridland Crop Science, Lanzhou, 730070 Gansu China
| | - Caixiang Wang
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070 Gansu China
| | - Junji Su
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070 Gansu China
| | - Delong Yang
- Gansu Provincial Key Lab of Aridland Crop Science, Lanzhou, 730070 Gansu China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070 Gansu China
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QTL Analysis for Drought Tolerance in Wheat: Present Status and Future Possibilities. AGRONOMY-BASEL 2017. [DOI: 10.3390/agronomy7010005] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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