4.5 Article

Developing controlled environment screening for high-temperature tolerance in cotton that accurately reflects performance in the field

期刊

FUNCTIONAL PLANT BIOLOGY
卷 39, 期 8, 页码 670-678

出版社

CSIRO PUBLISHING
DOI: 10.1071/FP12094

关键词

chlorophyll fluorescence; heat stress; light intensity; membrane permeability; photosynthesis; Rubisco

资金

  1. CSIRO
  2. Cotton Catchment Communities Co-operative Research Corporation
  3. Australian Cotton Research and Development Corporation
  4. Australian Postgraduate Award

向作者/读者索取更多资源

In this study we investigated the heat tolerance of high yielding Australian cotton (Gossypium hirsutum L.) cultivars using a multi-level approach encompassing physiological assays and measurements of performance. Two cultivars with known field performance were evaluated for heat tolerance under optimal (32 degrees C) and high (42 degrees C) temperatures in a growth cabinet with a cell membrane integrity assay. Impacts of temperature on growth were evaluated with leaf level measurements of gas exchange and chlorophyll fluorescence. To extend the multi-level approach, the expression of a Rubisco activase regulating gene (GhRCA alpha 2) was also determined. Consistent with previously determined differences in the field, cultivar Sicot 53 outperformed Sicala 45 for the cell membrane integrity assay; this finding was reflective of cultivar differences in gas exchange and chlorophyll fluorescence. Cultivar differences were also consistent for expression of GhRCA alpha 2, which may also help explain differences in physiological performance, particularly photosynthesis. This study reaffirmed that physiological and molecular assays were sufficiently sensitive to resolve genotypic differences in heat tolerance and that these differences translate to physiological performance. By comparing performance under high temperatures in the growth cabinet and field, this approach validates the use of rapid screening tools in conjunction with a multi-level approach for heat tolerance detection.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Agronomy

Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: Application of SUFI-2 algorithm in northeast Australia

Brian Collins, Ullah Najeeb, Qunying Luo, Daniel K. Y. Tan

Summary: For the first time, the SUFI-2 method was used to calibrate the phenology module of the APSIM-wheat model for spring wheat cultivars in northeast Australia. Results showed that adjusting sowing times can significantly shorten crop cycles and increase grain yields, with photoperiod and vernalisation sensitivities being major contributors to uncertainties in the simulated values.

JOURNAL OF AGRONOMY AND CROP SCIENCE (2022)

Article Agronomy

Physiological traits for evaluating heat-tolerance of Australian spring wheat cultivars at elevated CO2

Anowarul Bokshi, Rebecca J. Thistlethwaite, Edward D. Chaplin, Erasmus Kirii, Richard M. Trethowan, Daniel K. Y. Tan

Summary: High temperatures and increasing CO2 concentrations pose a major threat to global wheat production. This research evaluated Australian wheat cultivars for heat tolerance and identified physiological traits associated with adaptation to high temperatures. The findings provide valuable candidates for breeding and selecting wheat cultivars that can better adapt to changing climate conditions.

JOURNAL OF AGRONOMY AND CROP SCIENCE (2022)

Article Agronomy

Model for Predicting Rice Yield from Reflectance Index and Weather Variables in Lowland Rice Fields

Chinaza B. Onwuchekwa-Henry, Floris Van Ogtrop, Rose Roche, Daniel K. Y. Tan

Summary: This study assessed the effectiveness of Canopeo and GreenSeeker-NDVI tools for in-season estimation of rice yield in Cambodia. The Canopeo index-weather model was found to be a flexible and effective tool for predicting rice yield and managing agricultural resources.

AGRICULTURE-BASEL (2022)

Article Ecology

Genomic prediction of cotton fibre quality and yield traits using Bayesian regression methods

Zitong Li, Shiming Liu, Warren Conaty, Qian-Hao Zhu, Philippe Moncuquet, Warwick Stiller, Iain Wilson

Summary: Genomic selection has become an important breeding technology for crop improvement. This study focuses on cotton and aims to develop a GP-based breeding system to enhance efficiency. By genotyping 1385 breeding lines using a high-density SNP chip, the study found that combining genomic and pedigree information resulted in the highest prediction accuracies.

HEREDITY (2022)

Article Biochemistry & Molecular Biology

The Conservation of Long Intergenic Non-Coding RNAs and Their Response to Verticillium dahliae Infection in Cotton

Li Chen, Enhui Shen, Yunlei Zhao, Hongmei Wang, Iain Wilson, Qian-Hao Zhu

Summary: This study utilized publicly available RNA-seq datasets to identify the conservativeness and divergence of lincRNAs in different cotton species and their role in responding to biotic stresses. The study provided new insights into the relationship between the conservativeness and Vd responsiveness of lincRNAs and identified candidate lincRNAs for further functional characterization in disease response.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2022)

Article Genetics & Heredity

Genome-Wide Identification of m6A Writers, Erasers and Readers in Poplar 84K

Xiaochen Sun, Wenli Wu, Yanfang Yang, Iain Wilson, Fenjuan Shao, Deyou Qiu

Summary: This study provides a comprehensive analysis of m(6)A pathway genes in Poplar 84K, including gene structures, promoter analysis, and expression profiles. The results show tissue-specific expression patterns of m(6)A pathway genes in leaves, xylem, phloem, and roots. Additionally, the transcription factor LBD15 regulates the expression of several m(6)A pathway genes. These findings contribute to the understanding of the functions and epigenetic regulation mechanisms of these genes in Poplar 84K.
Article Plant Sciences

CRISPR/Cas9-mediated saturated mutagenesis of the cotton MIR482 family for dissecting the functionality of individual members in disease response

Qian-Hao Zhu, Shuangxia Jin, Yuman Yuan, Qing Liu, Xianlong Zhang, Iain Wilson

Summary: This study successfully generated a collection of cotton miR482 mutants using CRISPR/Cas9 technology, resulting in lower disease index in response to pathogen infection. The study provides a valuable resource for the cotton community to uncover the role of miR482-NLR module(s) in the interaction between cotton and different pathogens.

PLANT DIRECT (2022)

Editorial Material Plant Sciences

Editorial: Trends in cotton breeding: Meeting the challenges of the 21st century

Linghe Zeng, Iain Wilson, Fred M. Bourland

FRONTIERS IN PLANT SCIENCE (2022)

Article Biochemistry & Molecular Biology

Optimization of Isolation and Transformation of Protoplasts from Uncaria rhynchophylla and Its Application to Transient Gene Expression Analysis

Yingying Shao, Detian Mu, Limei Pan, Iain W. Wilson, Yajie Zheng, Lina Zhu, Zhiguo Lu, Lingyun Wan, Jine Fu, Shugen Wei, Lisha Song, Deyou Qiu, Qi Tang

Summary: An optimized protocol for the isolation, purification, and transient gene expression of Uncaria rhynchophylla protoplasts was developed, resulting in a highly efficient protoplast-based transient expression system with a transfection rate of 71%.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2023)

Article Green & Sustainable Science & Technology

Multi-Trait Selection of Quinoa Ideotypes at Different Levels of Cutting and Spacing

Syed Riaz Ahmed, Zeba Ali, Iram Ijaz, Zafran Khan, Nimra Gul, Soha Pervaiz, Hesham F. Alharby, Daniel K. Y. Tan, Muhammad Sayyam Tariq, Maria Ghaffar, Amir Bibi, Khalid Rehman Hakeem

Summary: Climate change has impacted the global food supply chain, causing serious concerns for food security. This study aimed to assess the effects of environmental factors, cutting levels, and spacing on quinoa biomass and quality. The results showed significant interactions between cutting, genotype, and year, as well as cutting, space, and genotype for most morphological traits. Cutting level 3 and spacing level 2 were found to be the most effective in achieving maximum biomass and quality traits.

SUSTAINABILITY (2023)

Article Agronomy

Response of Photosynthesis in Wheat (Triticum aestivum L.) Cultivars to Moderate Heat Stress at Meiosis and Anthesis Stages

Jie Zhang, Daniel K. Y. Tan, Hiba Shaghaleh, Tingting Chang, Yousef Alhaj Hamoud

Summary: High temperature significantly affects wheat production. This study evaluated the response and recovery of four wheat cultivars under heat stress and found significant differences in adaptability among the cultivars. Berkut and PBW343 showed stronger adaptability to heat stress.

AGRONOMY-BASEL (2023)

Article Biochemistry & Molecular Biology

Evaluation of Reference Genes for Normalizing RT-qPCR and Analysis of the Expression Patterns of WRKY1 Transcription Factor and Rhynchophylline Biosynthesis-Related Genes in Uncaria rhynchophylla

Detian Mu, Yingying Shao, Jialong He, Lina Zhu, Deyou Qiu, Iain W. Wilson, Yao Zhang, Limei Pan, Yu Zhou, Ying Lu, Qi Tang

Summary: This study reports the stability of reference genes in Uncaria rhynchophylla and their potential role in alkaloid production. The researchers evaluated the expression stability of ten candidate reference genes under stress-related experimental treatments and found that S-adenosylmethionine decarboxylase (SAM) exhibited higher stability. Using SAM as a reference gene, they examined the expression patterns of key alkaloid biosynthetic genes and a transcription factor under stress treatments. The results indicate that the transcription factor WRKY1 may coordinate the expression of tryptophan decarboxylase (TDC), providing a potential method for enhancing alkaloid production in the future through synthetic biology.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2023)

Article Biochemistry & Molecular Biology

Reference Genes Screening and Gene Expression Patterns Analysis Involved in Gelsenicine Biosynthesis under Different Hormone Treatments in Gelsemium elegans

Yao Zhang, Detian Mu, Liya Wang, Xujun Wang, Iain W. Wilson, Wenqiang Chen, Jinghan Wang, Zhaoying Liu, Deyou Qiu, Qi Tang

Summary: Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used to analyze Gelsemium elegans leaf tissue and identify suitable reference genes for data normalization. The optimal stable reference genes varied among the different treatments and at least two reference genes were required for accurate quantification. The expression patterns of 15 genes related to gelsenicine biosynthesis pathway were determined using RT-qPCR and three of these genes showed a strong correlation with the amount of gelsenicine measured. This research is crucial for future molecular analyses of G. elegans, a medically important plant species.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2023)

Review Biotechnology & Applied Microbiology

Optimal planting density of Agave for maximising aboveground biomass: A systematic literature review

William Crawford, Daniel K. Y. Tan, Floris Van Ogtrop

Summary: This study assessed the research available on Agave planting density and suggested an optimum planting density for the highest dry aboveground productivity using PRISMA. The meta-analysis found that the optimal planting density of Agave is approximately 2,600 plants ha(-1), which provides optimal dry aboveground biomass of 28.8 Mg ha(-1) yr(-1).

FRONTIERS IN CHEMICAL ENGINEERING (2022)

Review Horticulture

Key Determinants of the Physiological and Fruit Quality Traits in Sweet Cherries and Their Importance in a Breeding Programme

Viola Devasirvatham, Daniel K. Y. Tan

Summary: Australia's sweet cherry industry is thriving, with increasing production and revenue from both local and export markets. However, challenges such as self-incompatibility and the influence of environmental factors on plant traits need to be addressed. By understanding these traits and employing advanced breeding techniques, such as haplotype breeding, the efficiency and quality of sweet cherry breeding can be improved.

HORTICULTURAE (2022)

暂无数据