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      Comparative Transcriptomics of Rice Genotypes with Contrasting Responses to Nitrogen Stress Reveals Genes Influencing Nitrogen Uptake through the Regulation of Root Architecture

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          Abstract

          The indiscriminate use of nitrogenous fertilizers continues unabated for commercial crop production, resulting in air and water pollution. The development of rice varieties with enhanced nitrogen use efficiency (NUE) will require a thorough understanding of the molecular basis of a plant’s response to low nitrogen (N) availability. The global expression profiles of root tissues collected from low and high N treatments at different time points in two rice genotypes, Pokkali and Bengal, with contrasting responses to N stress and contrasting root architectures were examined. Overall, the number of differentially expressed genes (DEGs) in Pokkali ( indica) was higher than in Bengal ( japonica) during low N and early N recovery treatments. Most low N DEGs in both genotypes were downregulated whereas early N recovery DEGs were upregulated. Of these, 148 Pokkali-specific DEGs might contribute to Pokkali’s advantage under N stress. These DEGs included transcription factors and transporters and were involved in stress responses, growth and development, regulation, and metabolism. Many DEGs are co-localized with quantitative trait loci (QTL) related to root growth and development, chlorate-resistance, and NUE. Our findings suggest that the superior growth performance of Pokkali under low N conditions could be due to the genetic differences in a diverse set of genes influencing N uptake through the regulation of root architecture.

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          Genome-wide analysis of the ERF gene family in Arabidopsis and rice.

          Genes in the ERF family encode transcriptional regulators with a variety of functions involved in the developmental and physiological processes in plants. In this study, a comprehensive computational analysis identified 122 and 139 ERF family genes in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa L. subsp. japonica), respectively. A complete overview of this gene family in Arabidopsis is presented, including the gene structures, phylogeny, chromosome locations, and conserved motifs. In addition, a comparative analysis between these genes in Arabidopsis and rice was performed. As a result of these analyses, the ERF families in Arabidopsis and rice were divided into 12 and 15 groups, respectively, and several of these groups were further divided into subgroups. Based on the observation that 11 of these groups were present in both Arabidopsis and rice, it was concluded that the major functional diversification within the ERF family predated the monocot/dicot divergence. In contrast, some groups/subgroups are species specific. We discuss the relationship between the structure and function of the ERF family proteins based on these results and published information. It was further concluded that the expansion of the ERF family in plants might have been due to chromosomal/segmental duplication and tandem duplication, as well as more ancient transposition and homing. These results will be useful for future functional analyses of the ERF family genes.
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            Variation in NRT1.1B contributes to nitrate-use divergence between rice subspecies.

            Asian cultivated rice (Oryza sativa L.) consists of two main subspecies, indica and japonica. Indica has higher nitrate-absorption activity than japonica, but the molecular mechanisms underlying that activity remain elusive. Here we show that variation in a nitrate-transporter gene, NRT1.1B (OsNPF6.5), may contribute to this divergence in nitrate use. Phylogenetic analysis revealed that NRT1.1B diverges between indica and japonica. NRT1.1B-indica variation was associated with enhanced nitrate uptake and root-to-shoot transport and upregulated expression of nitrate-responsive genes. The selection signature of NRT1.1B-indica suggests that nitrate-use divergence occurred during rice domestication. Notably, field tests with near-isogenic and transgenic lines confirmed that the japonica variety carrying the NRT1.1B-indica allele had significantly improved grain yield and nitrogen-use efficiency (NUE) compared to the variety without that allele. Our results show that variation in NRT1.1B largely explains nitrate-use divergence between indica and japonica and that NRT1.1B-indica can potentially improve the NUE of japonica.
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              Nitrate Transport, Sensing, and Responses in Plants.

              Nitrogen (N) is an essential macronutrient that affects plant growth and development. N is an important component of chlorophyll, amino acids, nucleic acids, and secondary metabolites. Nitrate is one of the most abundant N sources in the soil. Because nitrate and other N nutrients are often limiting, plants have developed sophisticated mechanisms to ensure adequate supply of nutrients in a variable environment. Nitrate is absorbed in the root and mobilized to other organs by nitrate transporters. Nitrate sensing activates signaling pathways that impinge upon molecular, metabolic, physiological, and developmental responses locally and at the whole plant level. With the advent of genomics technologies and genetic tools, important advances in our understanding of nitrate and other N nutrient responses have been achieved in the past decade. Furthermore, techniques that take advantage of natural polymorphisms present in divergent individuals from a single species have been essential in uncovering new components. However, there are still gaps in our understanding of how nitrate signaling affects biological processes in plants. Moreover, we still lack an integrated view of how all the regulatory factors identified interact or crosstalk to orchestrate the myriad N responses plants typically exhibit. In this review, we provide an updated overview of mechanisms by which nitrate is sensed and transported throughout the plant. We discuss signaling components and how nitrate sensing crosstalks with hormonal pathways for developmental responses locally and globally in the plant. Understanding how nitrate impacts on plant metabolism, physiology, and growth and development in plants is key to improving crops for sustainable agriculture.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                11 August 2020
                August 2020
                : 21
                : 16
                : 5759
                Affiliations
                School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA; rgarcia@ 123456agcenter.lsu.edu (R.S.G.); scoronejo@ 123456agcenter.lsu.edu (S.C.); ronald.tapia@ 123456ufl.edu (R.T.)
                Author notes
                [* ]Correspondence: psubudhi@ 123456agcenter.lsu.edu ; Tel.: +1-225-578-1303
                [†]

                Current address: Department of Horticultural Sciences, University of Florida, IFAS Gulf Coast Research and Education Center, Wimauma, FL 33598, USA.

                Author information
                https://orcid.org/0000-0003-0512-9076
                https://orcid.org/0000-0002-9493-7288
                Article
                ijms-21-05759
                10.3390/ijms21165759
                7460981
                32796695
                0781b03a-7201-4714-af28-05e5b7dcda08
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 08 July 2020
                : 07 August 2020
                Categories
                Article

                Molecular biology
                alternate splicing,gene expression,nitrogen use efficiency,oryza sativa l.,nitrogen stress,rna-seq,root architecture,transcription factors,transcriptome sequencing

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