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      De Novo Characterization of the Mung Bean Transcriptome and Transcriptomic Analysis of Adventitious Rooting in Seedlings Using RNA-Seq

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          Abstract

          Adventitious rooting is the most important mechanism underlying vegetative propagation and an important strategy for plant propagation under environmental stress. The present study was conducted to obtain transcriptomic data and examine gene expression using RNA-Seq and bioinformatics analysis, thereby providing a foundation for understanding the molecular mechanisms controlling adventitious rooting. Three cDNA libraries constructed from mRNA samples from mung bean hypocotyls during adventitious rooting were sequenced. These three samples generated a total of 73 million, 60 million, and 59 million 100-bp reads, respectively. These reads were assembled into 78,697 unigenes with an average length of 832 bp, totaling 65 Mb. The unigenes were aligned against six public protein databases, and 29,029 unigenes (36.77%) were annotated using BLASTx. Among them, 28,225 (35.75%) and 28,119 (35.62%) unigenes had homologs in the TrEMBL and NCBI non-redundant (Nr) databases, respectively. Of these unigenes, 21,140 were assigned to gene ontology classes, and a total of 11,990 unigenes were classified into 25 KOG functional categories. A total of 7,357 unigenes were annotated to 4,524 KOs, and 4,651 unigenes were mapped onto 342 KEGG pathways using BLAST comparison against the KEGG database. A total of 11,717 unigenes were differentially expressed (fold change>2) during the root induction stage, with 8,772 unigenes down-regulated and 2,945 unigenes up-regulated. A total of 12,737 unigenes were differentially expressed during the root initiation stage, with 9,303 unigenes down-regulated and 3,434 unigenes up-regulated. A total of 5,334 unigenes were differentially expressed between the root induction and initiation stage, with 2,167 unigenes down-regulated and 3,167 unigenes up-regulated. qRT-PCR validation of the 39 genes with known functions indicated a strong correlation (92.3%) with the RNA-Seq data. The GO enrichment, pathway mapping, and gene expression profiles reveal molecular traits for root induction and initiation. This study provides a platform for functional genomic research with this species.

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          Plant responses to drought, salinity and extreme temperatures: towards genetic engineering for stress tolerance.

          Abiotic stresses, such as drought, salinity, extreme temperatures, chemical toxicity and oxidative stress are serious threats to agriculture and the natural status of the environment. Increased salinization of arable land is expected to have devastating global effects, resulting in 30% land loss within the next 25 years, and up to 50% by the year 2050. Therefore, breeding for drought and salinity stress tolerance in crop plants (for food supply) and in forest trees (a central component of the global ecosystem) should be given high research priority in plant biotechnology programs. Molecular control mechanisms for abiotic stress tolerance are based on the activation and regulation of specific stress-related genes. These genes are involved in the whole sequence of stress responses, such as signaling, transcriptional control, protection of membranes and proteins, and free-radical and toxic-compound scavenging. Recently, research into the molecular mechanisms of stress responses has started to bear fruit and, in parallel, genetic modification of stress tolerance has also shown promising results that may ultimately apply to agriculturally and ecologically important plants. The present review summarizes the recent advances in elucidating stress-response mechanisms and their biotechnological applications. Emphasis is placed on transgenic plants that have been engineered based on different stress-response mechanisms. The review examines the following aspects: regulatory controls, metabolite engineering, ion transport, antioxidants and detoxification, late embryogenesis abundant (LEA) and heat-shock proteins.
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            Mechanism of auxin-regulated gene expression in plants.

            Plant hormones control most aspects of the plant life cycle by regulating genome expression. Expression of auxin-responsive genes involves interactions among auxin-responsive DNA sequence elements, transcription factors and trans-acting transcriptional repressors. Transcriptional output from these auxin signaling complexes is regulated by proteasome-mediated degradation that is triggered by interaction with auxin receptor-E3 ubiquitin ligases such SCF(TIR1). Auxin signaling components are conserved throughout land plant evolution and have proliferated and specialized to control specific developmental processes.
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              Validation of internal control for gene expression study in soybean by quantitative real-time PCR

              Background Normalizing to housekeeping gene (HKG) can make results from quantitative real-time PCR (qRT-PCR) more reliable. Recent studies have shown that no single HKG is universal for all experiments. Thus, a suitable HKG should be selected before its use. Only a few studies on HKGs have been done in plants, and none in soybean, an economically important crop. Therefore, the present study was conducted to identify suitable HKG(s) for normalization of gene expression in soybean. Results All ten HKGs displayed a wide range of Ct values in 21 sample pools, confirming that they were variably expressed. GeNorm was used to determine the expression stability of the HGKs in seven series sets. For all the sample pools analyzed, the stability rank was ELF1B, CYP2 > ACT11 > TUA > ELF1A > UBC2 > ACT2/7 > TUB > G6PD > UBQ10. For different tissues under the same developmental stage, the rank was ELF1B, CYP2 > ACT2/7 > UBC2 > TUA > ELF1A > ACT11 > TUB > G6PD > UBQ10. For the developmental stage series, the stability rank was ACT2/7, TUA > ELF1A > UBC2 > ELF1B > TUB > CYP2 > ACT11 > G6PD > UBQ10. For photoperiodic treatments, the rank was ACT11, ELF1B > CYP2 > TUA > ELF1A > UBC2 > ACT2/7 > TUB > G6PD > UBQ10. For different times of the day, the rank was ELF1A, TUA > ELF1B > G6PD > CYP2 > ACT11 > ACT2/7 > TUB > UBC2 > UBQ10. For different cultivars and leaves on different nodes of the main stem, the ten HKGs' stability did not differ significantly. ΔCt approach and 'Stability index' were also used to analyze the expression stability in all 21 sample pools. Results from ΔCt approach and geNorm indicated that ELF1B and CYP2 were the most stable HKGs, and UBQ10 and G6PD the most variable ones. Results from 'Stability index' analysis were different, with ACT11 and CYP2 being the most stable HKGs, and ELF1A and TUA the most variable ones. Conclusion Our data suggests that HKGs are expressed variably in soybean. Based on the results from geNorm and ΔCt analysis, ELF1B and CYP2 could be used as internal controls to normalize gene expression in soybean, while UBQ10 and G6PD should be avoided. To achieve accurate results, some conditions may require more than one HKG to be used for normalization.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 July 2015
                2015
                : 10
                : 7
                : e0132969
                Affiliations
                [001]School of Chemical and Biological Engineering, Key Laboratory of Extreme Environmental Microbial Resources and Engineering Gansu Province, Lanzhou Jiaotong University, 88 West Anning Road, Lanzhou, 730070, P.R. China
                Cankiri Karatekin University, TURKEY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SWL. Performed the experiments: RFS YL. Analyzed the data: SWL RFS. Contributed reagents/materials/analysis tools: SWL. Wrote the paper: SWL.

                Article
                PONE-D-15-13629
                10.1371/journal.pone.0132969
                4503682
                26177103
                35719eb6-f83a-4138-9c11-5031d29a62a5
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 29 March 2015
                : 19 June 2015
                Page count
                Figures: 6, Tables: 14, Pages: 32
                Funding
                This work was supported by the National Natural Science Foundation of China (31260090).
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. All sequences files are available from DDBJ/EMBL/GenBank under the accession number GBXO01000001-GBXO01078617.

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