Complete mitogenome mapping of potato late blight pathogen, <i>Phytophthora infestans</i> A<sub>2</sub> mating type

Patil, Virupaksh U.; Vanishree, G.; Pattanayak, Debasis; Sharma, Shubham; Bhardwaj, Vinay; Singh, B. P.; Chakrabarti, S. K.

doi:10.1080/23802359.2017.1280699

Cited by 6 publications

(6 citation statements)

References 15 publications

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“…The mtDNA of P. infestans is ~40 kb in size with 53 predicted protein-coding genes (Avila-Adame et al, 2006 ; Patil et al, 2017 ), much smaller compared to its nuclear counterpart. In addition to the common features of uniparental inheritance (probably maternal inheritance), rapid mutation, and non-recombination (Avila-Adame et al, 2006 ), P. infestans mtDNA is easy to work with and has shown spatial heterogeneity of genetic polymorphism (Yang et al, 2013 ), making it a useful material to study the thermal adaptation of species.…”

Section: Introductionmentioning

confidence: 99%

Mitochondrial Genome Contributes to the Thermal Adaptation of the Oomycete Phytophthora infestans

et al. 2022

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As a vital element of climate change, elevated temperatures resulting from global warming present new challenges to natural and agricultural sustainability, such as ecological disease management. Mitochondria regulate the energy production of cells in responding to environmental fluctuation, but studying their contribution to the thermal adaptation of species is limited. This knowledge is needed to predict future disease epidemiology for ecology conservation and food security. Spatial distributions of the mitochondrial genome (mtDNA) in 405 Phytophthora infestans isolates originating from 15 locations were characterized. The contribution of MtDNA to thermal adaptation was evaluated by comparative analysis of mtDNA frequency and intrinsic growth rate, relative population differentiation in nuclear and mtDNA, and associations of mtDNA distribution with local geography climate conditions. Significant variation in frequency, intrinsic growth rate, and spatial distribution was detected in mtDNA. Population differentiation in mtDNA was significantly higher than that in the nuclear genome, and spatial distribution of mtDNA was strongly associated with local climatic conditions and geographic parameters, particularly air temperature, suggesting natural selection caused by a local temperature is the main driver of the adaptation. Dominant mtDNA grew faster than the less frequent mtDNA. Our results provide useful insights into the evolution of pathogens under global warming. Given its important role in biological functions and adaptation to local air temperature, mtDNA intervention has become an increasing necessity for future disease management. To secure ecological integrity and food production under global warming, a synergistic study on the interactive effect of changing temperature on various components of biological and ecological functions of mitochondria in an evolutionary frame is urgently needed.

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Section: Introductionmentioning

confidence: 99%

Mitochondrial Genome Contributes to the Thermal Adaptation of the Oomycete Phytophthora infestans

et al. 2022

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“…The authors of ( Patil et al., 2017 ) compared three ML methods, RF, SVM, and ANN, for spotting blight disease in potato leaf images. These techniques were trained and tested using the PlantVillage dataset and from the University of Agricultural Sciences India.…”

Section: Ai-based Automated Vegetables Disease Detection Classificationmentioning

confidence: 99%

Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations

Jafar,

Bibi,

Naqvi

et al. 2024

Front. Plant Sci.

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Accurate and rapid plant disease detection is critical for enhancing long-term agricultural yield. Disease infection poses the most significant challenge in crop production, potentially leading to economic losses. Viruses, fungi, bacteria, and other infectious organisms can affect numerous plant parts, including roots, stems, and leaves. Traditional techniques for plant disease detection are time-consuming, require expertise, and are resource-intensive. Therefore, automated leaf disease diagnosis using artificial intelligence (AI) with Internet of Things (IoT) sensors methodologies are considered for the analysis and detection. This research examines four crop diseases: tomato, chilli, potato, and cucumber. It also highlights the most prevalent diseases and infections in these four types of vegetables, along with their symptoms. This review provides detailed predetermined steps to predict plant diseases using AI. Predetermined steps include image acquisition, preprocessing, segmentation, feature selection, and classification. Machine learning (ML) and deep understanding (DL) detection models are discussed. A comprehensive examination of various existing ML and DL-based studies to detect the disease of the following four crops is discussed, including the datasets used to evaluate these studies. We also provided the list of plant disease detection datasets. Finally, different ML and DL application problems are identified and discussed, along with future research prospects, by combining AI with IoT platforms like smart drones for field-based disease detection and monitoring. This work will help other practitioners in surveying different plant disease detection strategies and the limits of present systems.

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“…The mtDNA of P. infestans is ∼40 kb in size with 53 predicted protein-coding genes (Avila-Adame et al, 2006;Patil et al, 2017), much smaller compared to its nuclear counterpart. In addition to the common features of uniparental inheritance (probably maternal inheritance), rapid mutation, and non-recombination (Avila-Adame et al, 2006), P. infestans mtDNA is easy to work with and has shown spatial heterogeneity of genetic polymorphism (Yang et al, 2013), making it a useful material to study the thermal adaptation of species.…”

Section: Introductionmentioning

confidence: 98%

Mitochondrial genome contributes to the thermal adaptation of the oomycete Phytophthora infestans

Shen

Waheed

Wang

et al. 2022

Preprint

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As a vital element of climate change, elevated temperature resulted from global warming presents new challenges to natural and agricultural sustainability such as ecological disease management. Mitochondria regulate energy production of cells in responding to environmental fluctuation but studying their contribution to the thermal adaptation of species is limited. This knowledge is needed to predict future disease epidemiology for ecology conservation and food security. Spatial distributions of mitochondrial genome (mtDNA) in 405 Phytophthora infestans isolates originating from 15 locations were characterized. mtDNA contribution to thermal adaptation was evaluated by comparative analysis of mtDNA frequency and intrinsic growth rate, relative population differentiation in nuclear and mtDNA and associations of mtDNA distribution in with local geography climate conditions. Significant variation in frequency, intrinsic growth rate and spatial distribution was detected in mtDNA. Population differentiation in mtDNA was significantly higher than that in nuclear genome, and spatial distribution of mtDNA was strongly associated with local climatic conditions and geographic parameters particularly air temperature, suggesting natural selection caused by local temperature is the main driver of the adaptation. Dominant mtDNA grew faster than the less frequent mtDNA. Our results provide useful insight into the evolution of pathogens under global warming. Given its important role in biological functions and adaptation to local air temperature, mtDNA intervention has become an increasing necessity in future disease management. To secure ecological integrity and food production under global warming, synergistic study in the interactive effect of changing temperature on various components of biological and ecological functions of mitochondria in an evolutionary frame is urgently needed.

show abstract

Complete mitogenome mapping of potato late blight pathogen, Phytophthora infestans A₂ mating type

Cited by 6 publications

References 15 publications

Mitochondrial Genome Contributes to the Thermal Adaptation of the Oomycete Phytophthora infestans

Mitochondrial Genome Contributes to the Thermal Adaptation of the Oomycete Phytophthora infestans

Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations

Mitochondrial genome contributes to the thermal adaptation of the oomycete Phytophthora infestans

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Complete mitogenome mapping of potato late blight pathogen, Phytophthora infestans A2 mating type

Cited by 6 publications

References 15 publications

Mitochondrial Genome Contributes to the Thermal Adaptation of the Oomycete Phytophthora infestans

Mitochondrial Genome Contributes to the Thermal Adaptation of the Oomycete Phytophthora infestans

Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations

Mitochondrial genome contributes to the thermal adaptation of the oomycete Phytophthora infestans

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Product

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Complete mitogenome mapping of potato late blight pathogen, Phytophthora infestans A₂ mating type