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Roth L, Binder M, Kirchgessner N, Tschurr F, Yates S, Hund A, Kronenberg L, Walter A. From Neglecting to Including Cultivar-Specific Per Se Temperature Responses: Extending the Concept of Thermal Time in Field Crops. PLANT PHENOMICS (WASHINGTON, D.C.) 2024; 6:0185. [PMID: 38827955 PMCID: PMC11142864 DOI: 10.34133/plantphenomics.0185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/08/2024] [Indexed: 06/05/2024]
Abstract
Predicting plant development, a longstanding goal in plant physiology, involves 2 interwoven components: continuous growth and the progression of growth stages (phenology). Current models for winter wheat and soybean assume species-level growth responses to temperature. We challenge this assumption, suggesting that cultivar-specific temperature responses substantially affect phenology. To investigate, we collected field-based growth and phenology data in winter wheat and soybean over multiple years. We used diverse models, from linear to neural networks, to assess growth responses to temperature at various trait and covariate levels. Cultivar-specific nonlinear models best explained phenology-related cultivar-environment interactions. With cultivar-specific models, additional relations to other stressors than temperature were found. The availability of the presented field phenotyping tools allows incorporating cultivar-specific temperature response functions in future plant physiology studies, which will deepen our understanding of key factors that influence plant development. Consequently, this work has implications for crop breeding and cultivation under adverse climatic conditions.
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Affiliation(s)
- Lukas Roth
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - Martina Binder
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - Norbert Kirchgessner
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - Flavian Tschurr
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - Steven Yates
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - Andreas Hund
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zürich, Switzerland
| | | | - Achim Walter
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zürich, Switzerland
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2
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Roth L, Kronenberg L, Aasen H, Walter A, Hartung J, van Eeuwijk F, Piepho HP, Hund A. High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:2084-2099. [PMID: 38134290 DOI: 10.1093/jxb/erad481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 12/19/2023] [Indexed: 12/24/2023]
Abstract
Crop growth and phenology are driven by seasonal changes in environmental variables, with temperature as one important factor. However, knowledge about genotype-specific temperature response and its influence on phenology is limited. Such information is fundamental to improve crop models and adapt selection strategies. We measured the increase in height of 352 European winter wheat varieties in 4 years to quantify phenology, and fitted an asymptotic temperature response model. The model used hourly fluctuations in temperature to parameterize the base temperature (Tmin), the temperature optimum (rmax), and the steepness (lrc) of growth responses. Our results show that higher Tmin and lrc relate to an earlier start and end of stem elongation. A higher rmax relates to an increased final height. Both final height and rmax decreased for varieties originating from the continental east of Europe towards the maritime west. A genome-wide association study (GWAS) indicated a quantitative inheritance and a large degree of independence among loci. Nevertheless, genomic prediction accuracies (GBLUPs) for Tmin and lrc were low (r≤0.32) compared with other traits (r≥0.59). As well as known, major genes related to vernalization, photoperiod, or dwarfing, the GWAS indicated additional, as yet unknown loci that dominate the temperature response.
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Affiliation(s)
- Lukas Roth
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zurich, Switzerland
| | - Lukas Kronenberg
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zurich, Switzerland
| | - Helge Aasen
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zurich, Switzerland
- Agroscope, Earth Observation of Agroecosystems Team, Division Agroecology and Environment, Reckenholzstrasse 191, 8046 Zurich, Switzerland
| | - Achim Walter
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zurich, Switzerland
| | - Jens Hartung
- University of Hohenheim, Institute for Crop Science, Biostatistics Unit, Fruwirthstrasse 23, D-70593 Stuttgart, Germany
| | - Fred van Eeuwijk
- Wageningen University and Research, Biometris, PO Box 16, 6700 AA Wageningen, The Netherlands
| | - Hans-Peter Piepho
- University of Hohenheim, Institute for Crop Science, Biostatistics Unit, Fruwirthstrasse 23, D-70593 Stuttgart, Germany
| | - Andreas Hund
- ETH Zurich, Institute of Agricultural Sciences, Universitätstrasse 2, 8092 Zurich, Switzerland
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3
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Chedid E, Avia K, Dumas V, Ley L, Reibel N, Butterlin G, Soma M, Lopez-Lozano R, Baret F, Merdinoglu D, Duchêne É. LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0116. [PMID: 38026470 PMCID: PMC10655830 DOI: 10.34133/plantphenomics.0116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 10/30/2023] [Indexed: 12/01/2023]
Abstract
The strong societal demand to reduce pesticide use and adaptation to climate change challenges the capacities of phenotyping new varieties in the vineyard. High-throughput phenotyping is a way to obtain meaningful and reliable information on hundreds of genotypes in a limited period. We evaluated traits related to growth in 209 genotypes from an interspecific grapevine biparental cross, between IJ119, a local genitor, and Divona, both in summer and in winter, using several methods: fresh pruning wood weight, exposed leaf area calculated from digital images, leaf chlorophyll concentration, and LiDAR-derived apparent volumes. Using high-density genetic information obtained by the genotyping by sequencing technology (GBS), we detected 6 regions of the grapevine genome [quantitative trait loci (QTL)] associated with the variations of the traits in the progeny. The detection of statistically significant QTLs, as well as correlations (R2) with traditional methods above 0.46, shows that LiDAR technology is effective in characterizing the growth features of the grapevine. Heritabilities calculated with LiDAR-derived total canopy and pruning wood volumes were high, above 0.66, and stable between growing seasons. These variables provided genetic models explaining up to 47% of the phenotypic variance, which were better than models obtained with the exposed leaf area estimated from images and the destructive pruning weight measurements. Our results highlight the relevance of LiDAR-derived traits for characterizing genetically induced differences in grapevine growth and open new perspectives for high-throughput phenotyping of grapevines in the vineyard.
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Affiliation(s)
- Elsa Chedid
- INRAE,
University of Strasbourg, UMR SVQV, 28, rue de Herrlisheim, 68000 Colmar, France
| | - Komlan Avia
- INRAE,
University of Strasbourg, UMR SVQV, 28, rue de Herrlisheim, 68000 Colmar, France
| | - Vincent Dumas
- INRAE,
University of Strasbourg, UMR SVQV, 28, rue de Herrlisheim, 68000 Colmar, France
| | - Lionel Ley
- INRAE, UEAV, 28, rue de Herrlisheim, 68000 Colmar, France
| | - Nicolas Reibel
- INRAE, UEAV, 28, rue de Herrlisheim, 68000 Colmar, France
| | - Gisèle Butterlin
- INRAE,
University of Strasbourg, UMR SVQV, 28, rue de Herrlisheim, 68000 Colmar, France
| | - Maxime Soma
- INRAE, Aix-Marseille Université, UMR RECOVER, 3275 Route de Cézanne, 13182 Aix-en-Provence, France
| | - Raul Lopez-Lozano
- INRAE,
Avignon Université, UMR EMMAH, UMT CAPTE, 228, route de l’aérodrome, 84914 Avignon, France
| | - Frédéric Baret
- INRAE,
Avignon Université, UMR EMMAH, UMT CAPTE, 228, route de l’aérodrome, 84914 Avignon, France
| | - Didier Merdinoglu
- INRAE,
University of Strasbourg, UMR SVQV, 28, rue de Herrlisheim, 68000 Colmar, France
| | - Éric Duchêne
- INRAE,
University of Strasbourg, UMR SVQV, 28, rue de Herrlisheim, 68000 Colmar, France
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4
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Orlovskaya OA, Vakula SI, Yatsevich KK, Khotyleva LV, Kilchevsky AV. Effect of NAM-1 genes on the protein content in grain and productivity indices in common wheat lines with foreign genetic material introgressions in the conditions of Belarus. Vavilovskii Zhurnal Genet Selektsii 2023; 27:197-206. [PMID: 37293448 PMCID: PMC10244585 DOI: 10.18699/vjgb-23-26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 01/26/2023] [Accepted: 01/30/2023] [Indexed: 06/10/2023] Open
Abstract
Modern varieties of common wheat (Triticum aestivum L.) bred mainly for high productivity are often of low grain quality. The identification of NAM-1 alleles associated with high grain protein content in wheat relatives has enhanced the significance of distant hybridization for the nutritional value of T. aestivum L. grain. In this work we aimed to study the allelic polymorphism of the NAM-A1 and NAM-B1 genes in wheat introgression lines and their parental forms and evaluate the effects of various NAM-1 variants on the grain protein content and productivity traits in the field conditions of Belarus. We studied parental varieties of spring common wheat, the accessions of tetraploid and hexaploid species of the genus Triticum and 22 introgression lines obtained using them (2017-2021 vegetation periods). Full-length NAM-A1 nucleotide sequences of T. dicoccoides k-5199, T. dicoccum k-45926, T. kiharae, and T. spelta k-1731 accessions were established and registered with the international molecular database GenBank. Six combinations of NAM-A1/B1 alleles were identified in the accessions studied and their frequency of occurrence varied from 40 to 3 %. The cumulative contribution of NAM-A1 and NAM-B1 genes to the variability of economically important wheat traits ranged from 8-10 % (grain weight per plant and thousand kernel weight) to up to 72 % (grain protein content). For most of the traits studied, the proportion of variability determined by weather conditions was small (1.57-18.48 %). It was shown that, regardless of weather conditions, the presence of a functional NAM-B1 allele ensures a high level of grain protein content; at the same time, it does not significantly decrease thousand kernel weight. The genotypes combining the NAM- A1d haplotype and a functional NAM-B1 allele demonstrated high levels of productivity and grain protein content. The results obtained demonstrate the effective introgression of a functional NAM-В1 allele of related species increasing the nutritional value of common wheat.
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Affiliation(s)
- O A Orlovskaya
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus, Minsk, Belarus
| | - S I Vakula
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus, Minsk, Belarus
| | - K K Yatsevich
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus, Minsk, Belarus
| | - L V Khotyleva
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus, Minsk, Belarus
| | - A V Kilchevsky
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus, Minsk, Belarus
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5
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Taniguchi S, Sakamoto T, Imase R, Nonoue Y, Tsunematsu H, Goto A, Matsushita K, Ohmori S, Maeda H, Takeuchi Y, Ishii T, Yonemaru JI, Ogawa D. Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice. FRONTIERS IN PLANT SCIENCE 2022; 13:998803. [PMID: 36582650 PMCID: PMC9792801 DOI: 10.3389/fpls.2022.998803] [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: 07/20/2022] [Accepted: 11/28/2022] [Indexed: 06/17/2023]
Abstract
Unmanned aerial vehicles (UAVs) are powerful tools for monitoring crops for high-throughput phenotyping. Time-series aerial photography of fields can record the whole process of crop growth. Canopy height (CH), which is vertical plant growth, has been used as an indicator for the evaluation of lodging tolerance and the prediction of biomass and yield. However, there have been few attempts to use UAV-derived time-series CH data for field testing of crop lines. Here we provide a novel framework for trait prediction using CH data in rice. We generated UAV-based digital surface models of crops to extract CH data of 30 Japanese rice cultivars in 2019, 2020, and 2021. CH-related parameters were calculated in a non-linear time-series model as an S-shaped plant growth curve. The maximum saturation CH value was the most important predictor for culm length. The time point at the maximum CH contributed to the prediction of days to heading, and was able to predict stem and leaf weight and aboveground weight, possibly reflecting the association of biomass with duration of vegetative growth. These results indicate that the CH-related parameters acquired by UAV can be useful as predictors of traits typically measured by hand.
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Affiliation(s)
- Shoji Taniguchi
- Research Center for Agricultural Information Technology, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Toshihiro Sakamoto
- Institute for Agro-Environmental Sciences, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Ryoji Imase
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Yasunori Nonoue
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Hiroshi Tsunematsu
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Akitoshi Goto
- Research Center for Agricultural Information Technology, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Kei Matsushita
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Sinnosuke Ohmori
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Hideo Maeda
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Yoshinobu Takeuchi
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Takuro Ishii
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Jun-ichi Yonemaru
- Research Center for Agricultural Information Technology, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
| | - Daisuke Ogawa
- Institute of Crop Science, National Agricultural and Food Research Organization (NARO), Tsukuba, Japan
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6
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Anderegg J, Kirchgessner N, Kronenberg L, McDonald BA. Automated Quantitative Measurement of Yellow Halos Suggests Activity of Necrotrophic Effectors in Septoria tritici Blotch. PHYTOPATHOLOGY 2022; 112:2560-2573. [PMID: 35793150 DOI: 10.1094/phyto-11-21-0465-r] [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] [Indexed: 06/15/2023]
Abstract
Many necrotrophic plant pathogens utilize host-selective toxins or necrotrophic effectors during the infection process. We hypothesized that the chlorotic yellow halos frequently observed around necrotic lesions caused by the wheat pathogen Zymoseptoria tritici could result from the activity of necrotrophic effectors interacting with the products of toxin sensitivity genes. As an initial step toward testing this hypothesis, we developed an automated image analysis (AIA) workflow that could quantify the degree of yellow halo formation occurring in wheat leaves naturally infected by a highly diverse pathogen population under field conditions. This AIA based on statistical learning was applied to more than 10,000 naturally infected leaves collected from 335 wheat cultivars grown in a replicated field experiment. We estimated a high heritability (h2 = 0.71) for the degree of yellow halo formation, suggesting that this quantitative trait has a significant genetic component. Using genome-wide association mapping, we identified six chromosome segments significantly associated with the yellow halo phenotype. Most of these segments contained candidate genes associated with targets of necrotrophic effectors in other necrotrophic pathogens. Our findings conform with the hypothesis that toxin sensitivity genes could account for a significant fraction of the observed variation in quantitative resistance to Septoria tritici blotch. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
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Affiliation(s)
- Jonas Anderegg
- Plant Pathology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
| | - Norbert Kirchgessner
- Crop Science Group, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Lukas Kronenberg
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Bruce A McDonald
- Plant Pathology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
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7
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Orlovskaya OA, Vakula SI, Yatsevich KK, Khotyleva LV, Kilchevsky AV. Productivity and grain nutritional value traits in wheat genotypes with different NAM-B1 gene allelic variations. DOKLADY OF THE NATIONAL ACADEMY OF SCIENCES OF BELARUS 2022. [DOI: 10.29235/1561-8323-2022-66-5-517-524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The identification of a functional NAM-B1 allele associated with a high content of grain protein and essential microelements in wheat relatives increased the distant hybridization significance for bread wheat nutritional value. The allelic polymorphism of the NAM-B1 gene in 22 wheat lines with a genetic material of T. dicoccoides, T. dicoccum, T. spelta, T. kiharаe and their parental forms and the effects of NAM-B1 gene allelic variations on the content of grain protein and essential microelements and productivity traits (vegetation period 2017–2021) were evaluated. The functional NAM-B1 allele was identified only in the samples of wheat relatives among the parental forms. All parental varieties and most of introgressive lines (77.3 %) had a non-functional allele. The genotypes with the functional NAM-B1 allele were characterized by a higher plant height and tillering, but by lower spike productivity compared to the non-functional allele genotypes. The presence of the functional NAM-B1 allele provided a high level of grain protein and zinc content and never decreased significantly a thousand-kernel weight across all studied environments. The functional NAM-B1 allele introgression could be a resource for improving the grain wheat nutritional value.
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Affiliation(s)
- O. A. Orlovskaya
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus
| | - S. I. Vakula
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus
| | - K. K. Yatsevich
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus
| | - L. V. Khotyleva
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus
| | - A. V. Kilchevsky
- Institute of Genetics and Cytology of the National Academy of Sciences of Belarus
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8
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Pérez-Valencia DM, Rodríguez-Álvarez MX, Boer MP, Kronenberg L, Hund A, Cabrera-Bosquet L, Millet EJ, Eeuwijk FAV. A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data. Sci Rep 2022; 12:3177. [PMID: 35210494 PMCID: PMC8873425 DOI: 10.1038/s41598-022-06935-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 01/20/2022] [Indexed: 12/19/2022] Open
Abstract
High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data. In a first stage, we correct for design features and spatial trends per time point. In a second stage, we focus on the longitudinal modelling of the spatially corrected data, thereby taking advantage of shared longitudinal features between genotypes and plants within genotypes. We propose a flexible hierarchical three-level P-spline growth curve model, with plants/plots nested in genotypes, and genotypes nested in populations. For selection of genotypes in a plant breeding context, we show how to extract new phenotypes, like growth rates, from the estimated genotypic growth curves and their first-order derivatives. We illustrate our approach on HTP data from the PhenoArch greenhouse platform at INRAE Montpellier and the outdoor Field Phenotyping platform at ETH Zürich.
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Affiliation(s)
- Diana M Pérez-Valencia
- BCAM-Basque Center for Applied Mathematics, Mazarredo 14, 48009, Bilbao, Spain. .,Departamento de Matemáticas, Universidad del País Vasco UPV/EHU, 48940, Leioa, Spain.
| | - María Xosé Rodríguez-Álvarez
- BCAM-Basque Center for Applied Mathematics, Mazarredo 14, 48009, Bilbao, Spain.,IKERBASQUE, Basque Foundation for Science, 48009, Bilbao, Spain.,Department of Statistics and Operations Research, Universidade de Vigo, 36310, Vigo, Spain
| | - Martin P Boer
- Biometris, Wageningen University & Research, 6708 PB, Wageningen, The Netherlands
| | - Lukas Kronenberg
- Crop Science, Institute of Agricultural Sciences, ETH Zürich, 8092, Zürich, Switzerland.,Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zürich, 8092, Zürich, Switzerland
| | - Andreas Hund
- Crop Science, Institute of Agricultural Sciences, ETH Zürich, 8092, Zürich, Switzerland
| | | | - Emilie J Millet
- Biometris, Wageningen University & Research, 6708 PB, Wageningen, The Netherlands.,LEPSE, Univ Montpellier, INRAE, Institut Agro, 34060, Montpellier, France
| | - Fred A van Eeuwijk
- Biometris, Wageningen University & Research, 6708 PB, Wageningen, The Netherlands
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9
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Mu Q, Guo T, Li X, Yu J. Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range. THE NEW PHYTOLOGIST 2022; 233:1768-1779. [PMID: 34870847 DOI: 10.1111/nph.17904] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 11/21/2021] [Indexed: 06/13/2023]
Abstract
Phenotypic plasticity is observed widely in plants and often studied with reaction norms for adult plant or end-of-season traits. Uncovering genetic, environmental and developmental patterns behind the observed phenotypic variation under natural field conditions is needed. Using a sorghum (Sorghum bicolor) genetic population evaluated for plant height in seven natural field conditions, we investigated the major pattern that differentiated these environments. We then examined the physiological relevance of the identified environmental index by investigating the developmental trajectory of the population with multistage height measurements in four additional environments and conducting crop growth modelling. We found that diurnal temperature range (DTR) during the rapid growth period of sorghum development was an effective environmental index. Three genetic loci (Dw1, Dw3 and qHT7.1) were consistently detected for individual environments, reaction-norm parameters across environments and growth-curve parameters through the season. Their genetic effects changed dynamically along the environmental gradient and the developmental stage. A conceptual model with three-dimensional reaction norms was proposed to showcase the interconnecting components: genotype, environment and development. Beyond genomic and environmental analyses, further integration of development and physiology at the whole-plant and molecular levels into complex trait dissection would enhance our understanding of mechanisms underlying phenotypic variation.
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Affiliation(s)
- Qi Mu
- Department of Agronomy, Iowa State University, Ames, IA, 50011, USA
| | - Tingting Guo
- Department of Agronomy, Iowa State University, Ames, IA, 50011, USA
| | - Xianran Li
- Department of Agronomy, Iowa State University, Ames, IA, 50011, USA
| | - Jianming Yu
- Department of Agronomy, Iowa State University, Ames, IA, 50011, USA
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10
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Xiao Q, Bai X, Zhang C, He Y. Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review. J Adv Res 2022; 35:215-230. [PMID: 35003802 PMCID: PMC8721248 DOI: 10.1016/j.jare.2021.05.002] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 05/05/2021] [Accepted: 05/09/2021] [Indexed: 01/22/2023] Open
Abstract
Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In recent years, genome-wide association studies (GWASs) have been applied extensively to interpret relationships between genes and traits. Successful GWAS application requires comprehensive genomic and phenotypic data from large populations. Although multiple high-throughput DNA sequencing approaches are available for the generation of genomics data, the capacity to generate high-quality phenotypic data is lagging far behind. Traditional methods for plant phenotyping mostly rely on manual measurements, which are laborious, inaccurate, and time-consuming, greatly impairing the acquisition of phenotypic data from large populations. In contrast, high-throughput phenotyping has unique advantages, facilitating rapid, non-destructive, and high-throughput detection, and, in turn, addressing the shortcomings of traditional methods. Aim of Review: This review summarizes the current status with regard to the integration of high-throughput phenotyping and GWAS in plants, in addition to discussing the inherent challenges and future prospects. Key Scientific Concepts of Review: High-throughput phenotyping, which facilitates non-contact and dynamic measurements, has the potential to offer high-quality trait data for GWAS and, in turn, to enhance the unraveling of genetic structures of complex plant traits. In conclusion, high-throughput phenotyping integration with GWAS could facilitate the revealing of coding information in plant genomes.
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Affiliation(s)
- Qinlin Xiao
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
| | - Xiulin Bai
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
| | - Chu Zhang
- School of Information Engineering, Huzhou University, Huzhou 313000, China
| | - Yong He
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
- Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
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11
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Xie Y, Zeng W, Wang C, Xu D, Guo H, Xiong H, Fang H, Zhao L, Gu J, Zhao S, Ding Y, Liu L. Fine Mapping of qd1, a Dominant Gene that Regulates Stem Elongation in Bread Wheat. Front Genet 2021; 12:793572. [PMID: 34912380 PMCID: PMC8667865 DOI: 10.3389/fgene.2021.793572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 11/12/2021] [Indexed: 11/13/2022] Open
Abstract
Stem elongation is a critical phase for yield determination and, as a major trait, is targeted for manipulation for improvement in bread wheat (Triticum aestivum L.). In a previous study, we characterized a mutant showing rapid stem elongation but with no effect on plant height at maturity. The present study aimed to finely map the underlying mutated gene, qd1, in this mutant. By analyzing an F2 segregating population consisting of 606 individuals, we found that the qd1 gene behaved in a dominant manner. Moreover, by using the bulked segregant RNA sequencing (BSR-seq)-based linkage analysis method, we initially mapped the qd1 gene to a 13.55 Mb region on chromosome 4B (from 15.41 to 28.96 Mb). This result was further confirmed in F2 and BC3F2 segregating populations. Furthermore, by using transcriptome sequencing data, we developed 14 Kompetitive Allele-Specific PCR (KASP) markers and then mapped the qd1 gene to a smaller and more precise 5.08 Mb interval from 26.80 to 31.88 Mb. To develop additional markers to finely map the qd1 gene, a total of 4,481 single-nucleotide polymorphisms (SNPs) within the 5.08 Mb interval were screened, and 25 KASP markers were developed based on 10x-depth genome resequencing data from both wild-type (WT) and mutant plants. The qd1 gene was finally mapped to a 1.33 Mb interval from 28.86 to 30.19 Mb on chromosome 4B. Four candidate genes were identified in this region. Among them, the expression pattern of only TraesCS4B02G042300 in the stems was concurrent with the stem development of the mutant and WT. The qd1 gene could be used in conjunction with molecular markers to manipulate stem development in the future.
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Affiliation(s)
- Yongdun Xie
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Weiwei Zeng
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Chaojie Wang
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Daxing Xu
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Huijun Guo
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Hongchun Xiong
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Hanshun Fang
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Linshu Zhao
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Jiayu Gu
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Shirong Zhao
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Yuping Ding
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
| | - Luxiang Liu
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Center of Space Mutagenesis for Crop Improvement, Beijing, China
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Langridge P, Reynolds M. Breeding for drought and heat tolerance in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:1753-1769. [PMID: 33715017 DOI: 10.1007/s00122-021-03795-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 02/16/2021] [Indexed: 05/02/2023]
Abstract
Many approaches have been adopted to enhance the heat and drought tolerance of wheat with mixed success. An assessment of the relative merits of different strategies is presented. Wheat is the most widely grown crop globally and plays a key role in human nutrition. However, it is grown in environments that are prone to heat and drought stress, resulting in severely reduced yield in some seasons. Increased climate variability is expected to have a particularly adverse effect of wheat production. Breeding for stable yield across both good and bad seasons while maintaining high yield under optimal conditions is a high priority for most wheat breeding programs and has been a focus of research activities. Multiple strategies have been explored to enhance the heat and drought tolerance of wheat including extensive genetic analysis and modify the expression of genes involved in stress responses, targeting specific physiological traits and direct selection under a range of stress scenarios. These approaches have been combined with improvements in phenotyping, the development of genetic and genomic resources, and extended screening and analysis techniques. The results have greatly expanded our knowledge and understanding of the factors that influence yield under stress, but not all have delivered the hoped-for progress. Here, we provide an overview of the different strategies and an assessment of the most promising approaches.
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Affiliation(s)
- Peter Langridge
- School of Agriculture Food and Wine, University of Adelaide, Glen Osmond, SA, 5064, Australia.
- Wheat Initiative, Julius-Kühn-Institute, 14195, Berlin, Germany.
| | - Matthew Reynolds
- International Maize and Wheat Improvement Centre (CIMMYT), Int. AP 6-641, 06600, Mexico, D.F., Mexico
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Smith DT, Potgieter AB, Chapman SC. Scaling up high-throughput phenotyping for abiotic stress selection in the field. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:1845-1866. [PMID: 34076731 DOI: 10.1007/s00122-021-03864-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 05/13/2021] [Indexed: 05/18/2023]
Abstract
High-throughput phenotyping (HTP) is in its infancy for deployment in large-scale breeding programmes. With the ability to measure correlated traits associated with physiological ideotypes, in-field phenotyping methods are available for screening of abiotic stress responses. As cropping environments become more hostile and unpredictable due to the effects of climate change, the need to characterise variability across spatial and temporal scales will become increasingly important. The sensor technologies that have enabled HTP from macroscopic through to satellite sensors may also be utilised here to complement spatial characterisation using envirotyping, which can improve estimations of genotypic performance across environments by better accounting for variation at the plot, trial and inter-trial levels. Climate change is leading to increased variation at all physical and temporal scales in the cropping environment. Maintaining yield stability under circumstances with greater levels of abiotic stress while capitalising upon yield potential in good years, requires approaches to plant breeding that target the physiological limitations to crop performance in specific environments. This requires dynamic modelling of conditions within target populations of environments, GxExM predictions, clustering of environments so breeding trajectories can be defined, and the development of screens that enable selection for genetic gain to occur. High-throughput phenotyping (HTP), combined with related technologies used for envirotyping, can help to address these challenges. Non-destructive analysis of the morphological, biochemical and physiological qualities of plant canopies using HTP has great potential to complement whole-genome selection, which is becoming increasingly common in breeding programmes. A range of novel analytic techniques, such as machine learning and deep learning, combined with a widening range of sensors, allow rapid assessment of large breeding populations that are repeatable and objective. Secondary traits underlying radiation use efficiency and water use efficiency can be screened with HTP for selection at the early stages of a breeding programme. HTP and envirotyping technologies can also characterise spatial variability at trial and within-plot levels, which can be used to correct for spatial variations that confound measurements of genotypic values. This review explores HTP for abiotic stress selection through a physiological trait lens and additionally investigates the use of envirotyping and EC to characterise spatial variability at all physical scales in METs.
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Affiliation(s)
- Daniel T Smith
- The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia
| | - Andries B Potgieter
- Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Scott C Chapman
- The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia.
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