Analysis of Germin-like Protein Genes (OsGLPs) Family in Rice Using Various In silico Approaches

Ilyas, Muhammad; Irfan, Muhammad; Mahmood, Tariq; Hussain, Hazrat; Rehman, Latifur; Naeem, Ijaz; Khaliq-ur-Rahman,

doi:10.2174/1574893614666190722165130

Cited by 17 publications

(32 citation statements)

References 76 publications

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“…Considering the functional characterization and expression analysis of GLP genes in rice, previous studies have mainly focused on Oryza Sativa Japonica as compared to other sub-species (Indica and Javanica) of rice crop [9,20,21]. Moreover, not many studies have compared the genomic responses of OsGLP genes across tolerant and sensitive rice varieties under abiotic stresses mainly including salt and drought stress.…”

Section: Discussionmentioning

confidence: 99%

“…In silico assessment in Japonica rice cultivar suggested that OsGLP genes from chromosome 3 and 8 are functionally more linked as compared to other OsGLPs by regulating in a combinatorial manner to deal with various abiotic stress conditions. [21]. Although such studies indicated the salt and drought stress responsive nature of OsGLPs, however, not many reports are available on the comparative expression analysis of OsGLPs in multiple rice varieties under these stresses.…”

Section: Introductionmentioning

confidence: 99%

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Germin Like Protein Genes Exhibit Modular Expression During Salt and Drought Stress in Elite Rice Cultivars

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O'Shea

Hyder

et al. 2021

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Germin-like proteins (GLPs) are ubiquitous plant proteins, which play significant role in plant responses against various abiotic stresses. However, the potential functions of GLPs in rice (Oryza Sativa) against salt and drought stress are still unclear. In this study, transcriptional variation of 8 OsGLP genes (OsGLP3-6, OsGLP4-1, OsGLP8-4, OsGLP8-7, OsGLP8-10, OsGLP8-11 and OsGLP8-12) was analyzed in leaves and roots of two economically important Indica rice cultivars, KS282 and Super Basmati under salt and drought stress at early seedling stage. The relative expression analysis from qRT-PCR indicated the highest increase in expression of OsGLP3-6 in leaves and roots of both rice varieties with a significantly higher expression in KS282. Moreover, relative change in expression of OsGLP8-7, OsGLP8-10 and OsGLP8-11 under salt stress and OsGLP8-7 under drought stress was also commonly higher in leaves and roots of KS282 as compared to Super Basmati. Whereas, OsGLP3-7 and OsGLP8-12 after salt stress and OsGLP8-4 and OsGLP8-12 after drought stress were observed with higher relative expression in roots of Super Basmati than KS282. Importantly, the OsGLP3-6 and OsGLP4-1 from chromosome 3 and 4 respectively showed higher expression in leaves whereas most of the OsGLP genes from chromosome 8 exhibited higher expression in roots. Overall, as a result of this comparative analysis, OsGLP genes showed both general and specific expression profiles depending upon a specific rice variety, stress condition as well as tissue type. These results will increase our understanding of role of OsGLP genes in rice crop and provide useful information for the further in-depth research on their regulatory mechanisms in response to these stress conditions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Germin Like Protein Genes Exhibit Modular Expression During Salt and Drought Stress in Elite Rice Cultivars

Anum

O'Shea

Hyder

et al. 2021

Preprint

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“…We used four metrics to quantify the predictive results [37, 40, 51–74] and thereby evaluate the proposed method.…”

Section: Methodsmentioning

confidence: 99%

ORS‐Pred: An optimized reduced scheme‐based identifier for antioxidant proteins

et al. 2021

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Antioxidant proteins can terminate a chain of reactions caused by free radicals and protect cells from damage. To identify antioxidant proteins rapidly, a computational model was proposed based on the optimized recoding scheme, sequence information and machine learning methods. First, over 600 recoding schemes were collected to build a scheme set. Then, the original sequence was recoded as a reduced expression whose g‐gap dipeptides (g = 0, 1, 2) were used as the features of proteins. Furthermore, a random forest method was used to evaluate the classification ability of the obtained dipeptide features. After going through all schemes, the best predictive performance scheme was chosen as the optimized reduction scheme. Finally, for the RF method, a grid search strategy was used to select a better parameter combination to identify antioxidant proteins. In the experiment, the present method correctly recognized 90.13–99.87% of the antioxidant samples. Other experimental results also proved that the present method was efficient to identify antioxidant proteins. Finally, we also developed a web server that was freely accessible to researchers.

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“…We use sensitivity (SN), specificity (SP), accuracy (ACC), Matthews correlation coefficient (MCC) to measure the quality of the classifier for DS1 and DS2 (Amanat et al, 2020;Chen et al, 2020;Ikram et al, 2020;Ilyas et al, 2020;Kong et al, 2020;Liang and Zhang, 2020;Lv et al, 2020bLv et al, , 2021b. The calculation formula is as formula (3).…”

Section: Performance Evaluationmentioning

confidence: 99%

Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities

et al. 2021

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Antimicrobial peptides (AMPs) are considered as potential substitutes of antibiotics in the field of new anti-infective drug design. There have been several machine learning algorithms and web servers in identifying AMPs and their functional activities. However, there is still room for improvement in prediction algorithms and feature extraction methods. The reduced amino acid (RAA) alphabet effectively solved the problems of simplifying protein complexity and recognizing the structure conservative region. This article goes into details about evaluating the performances of more than 5,000 amino acid reduced descriptors generated from 74 types of amino acid reduced alphabet in the first stage and the second stage to construct an excellent two-stage classifier, Identification of Antimicrobial Peptides by Reduced Amino Acid Cluster (iAMP-RAAC), for identifying AMPs and their functional activities, respectively. The results show that the first stage AMP classifier is able to achieve the accuracy of 97.21 and 97.11% for the training data set and independent test dataset. In the second stage, our classifier still shows good performance. At least three of the four metrics, sensitivity (SN), specificity (SP), accuracy (ACC), and Matthews correlation coefficient (MCC), exceed the calculation results in the literature. Further, the ANOVA with incremental feature selection (IFS) is used for feature selection to further improve prediction performance. The prediction performance is further improved after the feature selection of each stage. At last, a user-friendly web server, iAMP-RAAC, is established at http://bioinfor.imu.edu.cn/iampraac.

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Analysis of Germin-like Protein Genes (OsGLPs) Family in Rice Using Various In silico Approaches

Cited by 17 publications

References 76 publications

Germin Like Protein Genes Exhibit Modular Expression During Salt and Drought Stress in Elite Rice Cultivars

Germin Like Protein Genes Exhibit Modular Expression During Salt and Drought Stress in Elite Rice Cultivars

ORS‐Pred: An optimized reduced scheme‐based identifier for antioxidant proteins

Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities

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