Computational analysis of genes encoding for molecular determinants of arsenic tolerance in rice (<i>Oryza sativa</i> L.) to engineer low arsenic content varieties

Das, Chandan K.; Bastia, D. K.; Sc, Swain; Mahapatra, SS

doi:10.5958/2249-5266.2018.00031.0

Cited by 7 publications

(5 citation statements)

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“…Expression of Os03g0820400 (TFmatrixID_0216) was induced by cold more than four-fold in rice cold tolerant cultivar Oro (da Maia) [ 51 ]; Os10g0377300 (TFmatrixID_0298) was typed as candidate genes related to low-temperature tolerance [ 52 ]; whereas Os12g0123700 (TFmatrixID_0381) and Os02g0170300 (TFmatrixID_0529) were found to be cold-responsive in rice and Oryza ofcinalis [ 53 ]. Among other abiotic stresses, binding sites recognised by TFs involved in plant responses to drought [ 54 , 55 , 56 , 57 ], salt [ 58 , 59 , 60 ], arsenic [ 61 ], cadmium [ 62 ], nitrogen [ 63 , 64 ] or iron [ 65 ] deficiency were identified ( Table 1 ; Table S3 ). Binding sites of TFs that play a role in plant response to pathogen attack, such as viruses [ 66 ], bacteria [ 67 ] or fungi [ 68 ], were also present.…”

Section: Resultsmentioning

confidence: 99%

“…Among other developmental processes, some of the identified TFs play a role in shaping the root architecture [ 81 , 82 ] ( Table S4 ). A wide range of TFs that may bind the promoter of Os01g0701400 were identified as related to abiotic stresses, including response to arsenic [ 61 , 83 ], cold [ 84 ], drought [ 55 , 56 , 57 , 85 , 86 , 87 ], phosphate deficiency [ 88 ] and submergence [ 89 ]. On the other hand, four genes that belong to the AP2 family ( Os03g0183200 , Os07g0617000 , Os09g0286600 and Os09g0287000 ), were previously described as induced by infection of Xanthomonas oryzae pv.…”

Section: Resultsmentioning

confidence: 99%

“…The highest number of TF-binding sites were found in the promoter region of Os06g0565100 (1309) ( Table S1 ) and also the highest number of TFs specific only for this MAX1 homolog was identified ( Table S7 ). Similar to the previous genes that were analysed, Os06g0565100 may be also under control of TFs involved in plant response to bacteria [ 120 , 121 ], fungi [ 67 , 68 , 122 , 123 , 124 ] and insects [ 125 , 126 ], as well as cold [ 52 , 53 , 84 , 127 , 128 ], drought [ 54 , 55 , 56 , 57 , 86 , 87 , 114 ], cadmium [ 62 , 129 ], submergence [ 91 , 130 , 131 ], salt [ 85 , 132 ], arsenic [ 61 , 83 ], or iron [ 133 ], nitrogen [ 63 , 64 , 94 , 134 ] and phosphorus [ 88 ] deficiency. In the promoter region of Os06g0565100 motifs recognised by TFs are related to flower [ 116 , 135 ] and root [ 81 , 115 , 136 ] development, or controlling shoot architecture [ 137 ].…”

Section: Resultsmentioning

confidence: 99%

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Diverse Roles of MAX1 Homologues in Rice

Marzec

Situmorang

Brewer

et al. 2020

Genes

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Cytochrome P450 enzymes encoded by MORE AXILLARY GROWTH1 (MAX1)-like genes produce most of the structural diversity of strigolactones during the final steps of strigolactone biosynthesis. The diverse copies of MAX1 in Oryza sativa provide a resource to investigate why plants produce such a wide range of strigolactones. Here we performed in silico analyses of transcription factors and microRNAs that may regulate each rice MAX1, and compared the results with available data about MAX1 expression profiles and genes co-expressed with MAX1 genes. Data suggest that distinct mechanisms regulate the expression of each MAX1. Moreover, there may be novel functions for MAX1 homologues, such as the regulation of flower development or responses to heavy metals. In addition, individual MAX1s could be involved in specific functions, such as the regulation of seed development or wax synthesis in rice. Our analysis reveals potential new avenues of strigolactone research that may otherwise not be obvious.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Diverse Roles of MAX1 Homologues in Rice

Marzec

Situmorang

Brewer

et al. 2020

Genes

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“…Different stresses including abiotic and biotic stresses adversely affect the growth, development and yield performance of crop plants. Biotic stresses are primarily caused by plant pathogens and insect pests causing significant loss in crop production (Das et al, 2018a and2018b;Das et al, 2021;Kumar et al, 2021a;Kumar et al, 2021b). Plants have evolved two different kinds of molecular circuits against invading pathogens namely PAMP (Pathogen associated molecular patterns)-triggered immunity (PTI) and effector-triggered immunity (ETI) in addition to physical and chemical barriers.…”

Section: Resultsmentioning

confidence: 99%

Deciphering the Molecular Architecture of a Candidate R-gene (BjuWRR1) Product Mediating White Rust Resistance in Brassica juncea

Das¹,

Nayak²,

Pati³

et al. 2021

IJBSM

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In this investigation, a three-dimensional model of a R-gene encoded product BjuWRR1 which is known to play a role in white rust resistance in Brassica juncea was developed to synthesize innovative ways for evolving white rust resistant cultivars. The model was built from the amino acid sequence of BjuWRR1 using structural template information of a disease resistance protein (RPP13-like protein 4 of Arabidopsis thaliana) with the help of homology-based modelling approach. Built models were validated for their stereochemical parameters and structural descriptors using Ramachandran plot analysis, protein structure analysis and ERRAT analysis. Structural analysis of BjuWRR1 model revealed that it is composed of three distinct domains namely a coiled-coil domain, a central NB-ARC nucleotide binding domain and a hypervariable leucine-rich repeat domain. Further, canonical conserved motifs such as P-loop, Kinase2-motif and HD-motif were found in the NB-ARC domain. The built model would help in understanding the molecular basis of plant-immunity against white rust pathogen by understanding the significance of inter-domain interactions in BuWRR1 in triggering the activation of downstream defense response against the white rust pathogen by promoting oligomerization of coiled-coil domains through stabilized hydrophobic interactions and interaction with NB-ARC domain. Presence of patches of charged residues in each domain of BjuWRR1 indicated their possible role in intra-molecular interaction with other domains. Therefore, this model can help in designing functional genomic studies to understand the role of intra-molecular interaction in BjuWRR1 to mediate resistance against white rust pathogen.

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“…In this study, the interactions between As and other ions were analyzed under non-stress and stress conditions for rice core collections, including temperate japonica, tropical japonica, indica , and aus , to elucidate the impact of environmental and genotypic differences. In addition, it was attempted to identify the genetic factors regulating As genes through a transcriptome-wide association study on 23 genes known to transport, detoxify, or stress-response (Yang et al, 2012 ; Nguyen et al, 2014 ; Most and Papenbrock, 2015 ; Yamaji et al, 2015 ; Hwang et al, 2016 , 2017 ; Shi et al, 2016 ; Das et al, 2017 , 2018a , b ; Salt, 2017 ; Latowski et al, 2018 ; Sun et al, 2018 ; Wang et al, 2019 ; Tiwari et al, 2020 ; Singh et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Genome-Scale Profiling and High-Throughput Analyses Unravel the Genetic Basis of Arsenic Content Variation in Rice

Lee

Kim²,

Shin³

et al. 2022

Front. Plant Sci.

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Ionomics, the study of the composition of mineral nutrients and trace elements in organisms that represent the inorganic component of cells and tissues, has been widely studied to explore to unravel the molecular mechanism regulating the elemental composition of plants. However, the genetic factors of rice subspecies in the interaction between arsenic and functional ions have not yet been explained. Here, the correlation between As and eight essential ions in a rice core collection was analyzed, taking into account growing condition and genetic factors. The results demonstrated that the correlation between As and essential ions was affected by genetic factors and growing condition, but it was confirmed that the genetic factor was slightly larger with the heritability for arsenic content at 53%. In particular, the cluster coefficient of japonica (0.428) was larger than that of indica (0.414) in the co-expression network analysis for 23 arsenic genes, and it was confirmed that the distance between genes involved in As induction and detoxification of japonica was far than that of indica. These findings provide evidence that japonica populations could accumulate more As than indica populations. In addition, the cis-eQTLs of AIR2 (arsenic-induced RING finger protein) were isolated through transcriptome-wide association studies, and it was confirmed that AIR2 expression levels of indica were lower than those of japonica. This was consistent with the functional haplotype results for the genome sequence of AIR2, and finally, eight rice varieties with low AIR2 expression and arsenic content were selected. In addition, As-related QTLs were identified on chromosomes 5 and 6 under flooded and intermittently flooded conditions through genome-scale profiling. Taken together, these results might assist in developing markers and breeding plans to reduce toxic element content and breeding high-quality rice varieties in future.

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Computational analysis of genes encoding for molecular determinants of arsenic tolerance in rice (Oryza sativa L.) to engineer low arsenic content varieties

Cited by 7 publications

References 0 publications

Diverse Roles of MAX1 Homologues in Rice

Diverse Roles of MAX1 Homologues in Rice

Deciphering the Molecular Architecture of a Candidate R-gene (BjuWRR1) Product Mediating White Rust Resistance in Brassica juncea

Genome-Scale Profiling and High-Throughput Analyses Unravel the Genetic Basis of Arsenic Content Variation in Rice

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