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      Comparative Transcriptome Analysis Revealed Genes Commonly Responsive to Varied Nitrate Stress in Leaves of Tibetan Hulless Barley

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          Abstract

          Nitrogen (N) deprivation or excess can lead to dramatic phenotype change, disrupt important biological processes, and ultimately limit plant productivity. To explore genes in Tibetan hulless barley responsive to varied N stress, we utilized a comparative transcriptomics method to investigate gene expression patterns under three nitrate treatments. The transcriptome of the control (optimal-nitrate, ON) sample was compared with that of free-nitrate (FN), low-nitrate (LN), and high-nitrate (HN) treatment samples, identifying 2428, 1274, and 1861 genes, respectively, that exhibited significant differences in transcript abundance. Among these, 9 genes encoding ribulose bisphosphate carboxylases exhibited up-regulated expression under varied N stress. We further compared FN vs. ON and LN vs. ON to investigate the impact of stress degree on gene expression. With the aggravation of stress, more genes were differentially expressed and thus possibly involved in the response to nitrogen deficiency. Cluster and functional enrichment analysis indicated that the differentially expressed genes (DEGs) in FN were highly enriched in response to stress, defense response, and gene expression regulation. Comprehensive comparison analysis further suggested that Tibetan hulless barley could respond to varied N stress by regulating multiple common biological processes and pathways such as nitrogen metabolism, carbon metabolism, and photosynthesis. A large number of specific DEGs involved in diverse biological processes were also detected, implying differences in the potential regulatory patterns of low- and high-N stress response. Notably, we also identified some NIN-like proteins and other transcription factors significantly modulated by these stresses, suggesting the involvement of these transcription factors in N stress response. To our knowledge, this study is the first investigation of the Tibetan hulless barley transcriptome under N stress. The identified N-stress-related genes may provide resources for genetic improvement and promote N use efficiency.

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          Most cited references30

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          RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

          Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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            Plant nitrogen assimilation and use efficiency.

            Crop productivity relies heavily on nitrogen (N) fertilization. Production and application of N fertilizers consume huge amounts of energy, and excess is detrimental to the environment; therefore, increasing plant N use efficiency (NUE) is essential for the development of sustainable agriculture. Plant NUE is inherently complex, as each step-including N uptake, translocation, assimilation, and remobilization-is governed by multiple interacting genetic and environmental factors. The limiting factors in plant metabolism for maximizing NUE are different at high and low N supplies, indicating great potential for improving the NUE of current cultivars, which were bred in well-fertilized soil. Decreasing environmental losses and increasing the productivity of crop-acquired N requires the coordination of carbohydrate and N metabolism to give high yields. Increasing both the grain and N harvest index to drive N acquisition and utilization are important approaches for breeding future high-NUE cultivars.
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              Nitrogen uptake, assimilation and remobilization in plants: challenges for sustainable and productive agriculture.

              Productive agriculture needs a large amount of expensive nitrogenous fertilizers. Improving nitrogen use efficiency (NUE) of crop plants is thus of key importance. NUE definitions differ depending on whether plants are cultivated to produce biomass or grain yields. However, for most plant species, NUE mainly depends on how plants extract inorganic nitrogen from the soil, assimilate nitrate and ammonium, and recycle organic nitrogen. Efforts have been made to study the genetic basis as well as the biochemical and enzymatic mechanisms involved in nitrogen uptake, assimilation, and remobilization in crops and model plants. The detection of the limiting factors that could be manipulated to increase NUE is the major goal of such research. An overall examination of the physiological, metabolic, and genetic aspects of nitrogen uptake, assimilation and remobilization is presented in this review. The enzymes and regulatory processes manipulated to improve NUE components are presented. Results obtained from natural variation and quantitative trait loci studies are also discussed. This review presents the complexity of NUE and supports the idea that the integration of the numerous data coming from transcriptome studies, functional genomics, quantitative genetics, ecophysiology and soil science into explanatory models of whole-plant behaviour will be promising.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                21 July 2016
                2016
                : 7
                : 1067
                Affiliations
                [1] 1Tibet Academy of Agricultural and Animal Husbandry Sciences Lhasa, China
                [2] 2State Key Laboratory of Barley and Yak Genetic Resources and Improvement Lhasa, China
                [3] 3Institute of Agricultural Resources and Environment Science, Tibet Academy of Agricultural and Animal Husbandry Sciences Lhasa, China
                [4] 4Agricultural Research Institute, Tibet Academy of Agricultural and Animal Husbandry Sciences Lhasa, China
                [5] 5Zunyi Academy of Agricultural Sciences Zunyi, China
                [6] 6Best Biological Technology Co., LTD Chengdu, China
                Author notes

                Edited by: Shabir Hussain Wani, Sher-e-Kashmir University of Agricultural Sciences and Technology-Kashmir, India

                Reviewed by: Rudra Deo Tripathi, CSIR-National Botanical Research Institute, India; Rohit Joshi, International Center for Genetic Engineering and Biotechnology, India

                *Correspondence: Tashi Nyima nima_zhaxi@sina.com

                This article was submitted to Crop Science and Horticulture, a section of the journal Frontiers in Plant Science

                †These authors have contributed equally to this work.

                Article
                10.3389/fpls.2016.01067
                4954818
                27493653
                8f0c8fcc-015a-4a18-9f1b-dbbb49747c70
                Copyright © 2016 Wei, Zeng, Qin, Wang, Bai, Xu, Yuan, Tang and Nyima.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 May 2016
                : 06 July 2016
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 37, Pages: 10, Words: 5922
                Funding
                Funded by: National Science and Technology Support Program
                Award ID: 2012BAD03B01
                Funded by: Tibet Autonomous Region Financial Special Fund
                Award ID: 2015CZZX001
                Award ID: 2015ZC001
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                tibetan hulless barley,nitrogen stress,comparative transcriptomics,differential gene expression,transcription factors

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