Physiological basis of genetic variation in leaf photosynthesis among rice (Oryza sativa L.) introgression lines under drought and well-watered conditions
To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exch...
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| Published in | Journal of experimental botany Vol. 63; no. 14; pp. 5137 - 5153 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Oxford University Press [etc.]
01.09.2012
OXFORD UNIVERSITY PRESS Oxford University Press |
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| Online Access | Get full text |
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| Abstract | To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO2 to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g s), mesophyll conductance (g m), electron transport capacity (J max), and Rubisco carboxylation capacity (V cmax). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g s and g m. One previously mapped major QTL of photosynthesis was associated with variation in g s and g m, but also in J max and V cmax at flowering. Thus, g s and g m, which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background. |
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| AbstractList | To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO(2) to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g(s)), mesophyll conductance (g(m)), electron transport capacity (J(max)), and Rubisco carboxylation capacity (V(cmax)). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g(s) and g(m). One previously mapped major QTL of photosynthesis was associated with variation in g(s) and g(m), but also in J(max) and V(cmax) at flowering. Thus, g(s) and g(m), which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background.To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO(2) to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g(s)), mesophyll conductance (g(m)), electron transport capacity (J(max)), and Rubisco carboxylation capacity (V(cmax)). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g(s) and g(m). One previously mapped major QTL of photosynthesis was associated with variation in g(s) and g(m), but also in J(max) and V(cmax) at flowering. Thus, g(s) and g(m), which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background. To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO2 to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g s), mesophyll conductance (g m), electron transport capacity (J max), and Rubisco carboxylation capacity (V cmax). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g s and g m. One previously mapped major QTL of photosynthesis was associated with variation in g s and g m, but also in J max and V cmax at flowering. Thus, g s and g m, which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO2 to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g s), mesophyll conductance (g m), electron transport capacity (J max), and Rubisco carboxylation capacity (V cmax). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g s and g m. One previously mapped major QTL of photosynthesis was associated with variation in g s and g m, but also in J max and V cmax at flowering. Thus, g s and g m, which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background. To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO(2) to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g(s)), mesophyll conductance (g(m)), electron transport capacity (J(max)), and Rubisco carboxylation capacity (V(cmax)). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g(s) and g(m). One previously mapped major QTL of photosynthesis was associated with variation in g(s) and g(m), but also in J(max) and V(cmax) at flowering. Thus, g(s) and g(m), which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background. To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice ( Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO 2 to estimate parameters of a model that dissects photosynthesis into stomatal conductance ( g s ), mesophyll conductance ( g m ), electron transport capacity ( J max ), and Rubisco carboxylation capacity ( V cmax ). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g s and g m . One previously mapped major QTL of photosynthesis was associated with variation in g s and g m , but also in J max and V cmax at flowering. Thus, g s and g m , which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background. To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativaL.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO₂ to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g s), mesophyll conductance (g m), electron transport capacity (J max), and Rubisco carboxylation capacity (V cmax). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation ing sandg m. One previously mapped major QTL of photosynthesis was associated with variation ing sandg m, but also inJ maxandV cmaxat flowering. Thus,g sandg m, which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background. |
| Author | Stomph, Tjeerd-Jan Gu, Junfei Wang, Huaqi Struik, Paul C Yin, Xinyou |
| Author_xml | – sequence: 1 fullname: Gu, Junfei – sequence: 2 fullname: Yin, Xinyou – sequence: 3 fullname: Stomph, Tjeerd-Jan – sequence: 4 fullname: Wang, Huaqi – sequence: 5 fullname: Struik, Paul C |
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| Issue | 14 |
| Keywords | Monocotyledones Genetic variability Stomatal conductance Oryza sativa L genetic variation Plant leaf Introgression rice Modeling modelling Cereal crop Oryza sativa Mesophyll Gramineae Angiospermae Botany mesophyll conductance Spermatophyta Physiology Photosynthesis Drought |
| Language | English |
| License | CC BY 4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0/uk/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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| Snippet | To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.)... To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativaL.)... To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice ( Oryza sativa L.)... |
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| SubjectTerms | Agronomy. Soil science and plant productions Biological and medical sciences c-3 plants Carbon dioxide Carbon Dioxide - metabolism carbon-isotope discrimination carboxylation chlorophyll chlorophyll fluorescence measurements co2 diffusion combined gas-exchange Drought electron transfer filling period flowering fluorescence Fundamental and applied biological sciences. Psychology gas exchange Generalities. Genetics. Plant material genetic background Genetic resources, diversity Genetic Variation genetics Genetics and breeding of economic plants Genotypes Ideotypes internal conductance Interspecific and intergeneric hybridization, introgressions introgression leaves light intensity Mesophyll mesophyll conductance metabolism Models, Biological nitrogen Oryza Oryza - genetics Oryza - metabolism Oryza sativa Parametric models Photosynthesis Plant breeding: fundamental aspects and methodology Plant Leaves Plant Leaves - genetics Plant Leaves - metabolism Plant material Plant physiology and development Plant Transpiration Plants Quantitative Trait Loci RESEARCH PAPER ribulose-1,5-bisphosphate carboxylase ribulose-bisphosphate carboxylase Rice stomatal conductance Sunlight transpiration efficiency use efficiency |
| Title | Physiological basis of genetic variation in leaf photosynthesis among rice (Oryza sativa L.) introgression lines under drought and well-watered conditions |
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