Identification and Expression of  SAUR  Genes in the CAM Plant  Agave

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Abstract

Agave species are important crassulacean acid metabolism (CAM) plants and widely cultivated in tropical areas for producing tequila spirit and fiber. The hybrid H11648 of Agave (( A. amaniensis × A. angustifolia) × A. amaniensis) is the main cultivar for fiber production in Brazil, China, and African countries. Small Auxin Up-regulated RNA ( SAUR) genes have broad effect on auxin signaling-regulated plant growth and development, while only few SAUR genes have been reported in Agave species. In this study, we identified 43, 60, 24, and 21 SAUR genes with full-length coding regions in A. deserti, A. tequilana, A. H11648, and A. americana, respectively. Although phylogenetic analysis revealed that rice contained a species-specific expansion pattern of SAUR gene, no similar phenomena were observed in Agave species. The in silico expression indicated that SAUR genes had a distinct expression pattern in A. H11648 compared with other Agave species; and four SAUR genes were differentially expressed during CAM diel cycle in A. americana. Additionally, an expression analysis was conducted to estimate SAUR gene expression during different leaf developmental stages, abiotic and biotic stresses in A. H11648. Together, we first characterized the SAUR genes of Agave based on previously published transcriptome datasets and emphasized the potential functions of SAUR genes in Agave’s leaf development and stress responses. The identification of which further expands our understanding on auxin signaling-regulated plant growth and development in Agave species.

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Prediction of protein subcellular localization.

Chin-Sheng Yu, Yu-Ching Chen, Chih-Hao Lu … (2006)

Because the protein's function is usually related to its subcellular localization, the ability to predict subcellular localization directly from protein sequences will be useful for inferring protein functions. Recent years have seen a surging interest in the development of novel computational tools to predict subcellular localization. At present, these approaches, based on a wide range of algorithms, have achieved varying degrees of success for specific organisms and for certain localization categories. A number of authors have noticed that sequence similarity is useful in predicting subcellular localization. For example, Nair and Rost (Protein Sci 2002;11:2836-2847) have carried out extensive analysis of the relation between sequence similarity and identity in subcellular localization, and have found a close relationship between them above a certain similarity threshold. However, many existing benchmark data sets used for the prediction accuracy assessment contain highly homologous sequences-some data sets comprising sequences up to 80-90% sequence identity. Using these benchmark test data will surely lead to overestimation of the performance of the methods considered. Here, we develop an approach based on a two-level support vector machine (SVM) system: the first level comprises a number of SVM classifiers, each based on a specific type of feature vectors derived from sequences; the second level SVM classifier functions as the jury machine to generate the probability distribution of decisions for possible localizations. We compare our approach with a global sequence alignment approach and other existing approaches for two benchmark data sets-one comprising prokaryotic sequences and the other eukaryotic sequences. Furthermore, we carried out all-against-all sequence alignment for several data sets to investigate the relationship between sequence homology and subcellular localization. Our results, which are consistent with previous studies, indicate that the homology search approach performs well down to 30% sequence identity, although its performance deteriorates considerably for sequences sharing lower sequence identity. A data set of high homology levels will undoubtedly lead to biased assessment of the performances of the predictive approaches-especially those relying on homology search or sequence annotations. Our two-level classification system based on SVM does not rely on homology search; therefore, its performance remains relatively unaffected by sequence homology. When compared with other approaches, our approach performed significantly better. Furthermore, we also develop a practical hybrid method, which combines the two-level SVM classifier and the homology search method, as a general tool for the sequence annotation of subcellular localization.

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Plant cell wall-mediated immunity: cell wall changes trigger disease resistance responses.

Eva Miedes, Antonio J. Molina, Laura Bacete … (2018)

Plants have evolved a repertoire of monitoring systems to sense plant morphogenesis and to face environmental changes and threats caused by different attackers. These systems integrate different signals into overreaching triggering pathways which coordinate developmental and defence-associated responses. The plant cell wall, a dynamic and complex structure surrounding every plant cell, has emerged recently as an essential component of plant monitoring systems, thus expanding its function as a passive defensive barrier. Plants have a dedicated mechanism for maintaining cell wall integrity (CWI) which comprises a diverse set of plasma membrane-resident sensors and pattern recognition receptors (PRRs). The PRRs perceive plant-derived ligands, such as peptides or wall glycans, known as damage-associated molecular patterns (DAMPs). These DAMPs function as 'danger' alert signals activating DAMP-triggered immunity (DTI), which shares signalling components and responses with the immune pathways triggered by non-self microbe-associated molecular patterns that mediate disease resistance. Alteration of CWI by impairment of the expression or activity of proteins involved in cell wall biosynthesis and/or remodelling, as occurs in some plant cell wall mutants, or by wall damage due to colonization by pathogens/pests, activates specific defensive and growth responses. Our current understanding of how these alterations of CWI are perceived by the wall monitoring systems is scarce and few plant sensors/PRRs and DAMPs have been characterized. The identification of these CWI sensors and PRR-DAMP pairs will help us to understand the immune functions of the wall monitoring system, and might allow the breeding of crop varieties and the design of agricultural strategies that would enhance crop disease resistance.

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SAUR Inhibition of PP2C-D Phosphatases Activates Plasma Membrane H+-ATPases to Promote Cell Expansion in Arabidopsis.

Angela Spartz, Hong Ren, Mee Park … (2014)

The plant hormone auxin promotes cell expansion. Forty years ago, the acid growth theory was proposed, whereby auxin promotes proton efflux to acidify the apoplast and facilitate the uptake of solutes and water to drive plant cell expansion. However, the underlying molecular and genetic bases of this process remain unclear. We have previously shown that the SAUR19-24 subfamily of auxin-induced SMALL AUXIN UP-RNA (SAUR) genes promotes cell expansion. Here, we demonstrate that SAUR proteins provide a mechanistic link between auxin and plasma membrane H(+)-ATPases (PM H(+)-ATPases) in Arabidopsis thaliana. Plants overexpressing stabilized SAUR19 fusion proteins exhibit increased PM H(+)-ATPase activity, and the increased growth phenotypes conferred by SAUR19 overexpression are dependent upon normal PM H(+)-ATPase function. We find that SAUR19 stimulates PM H(+)-ATPase activity by promoting phosphorylation of the C-terminal autoinhibitory domain. Additionally, we identify a regulatory mechanism by which SAUR19 modulates PM H(+)-ATPase phosphorylation status. SAUR19 as well as additional SAUR proteins interact with the PP2C-D subfamily of type 2C protein phosphatases. We demonstrate that these phosphatases are inhibited upon SAUR binding, act antagonistically to SAURs in vivo, can physically interact with PM H(+)-ATPases, and negatively regulate PM H(+)-ATPase activity. Our findings provide a molecular framework for elucidating auxin-mediated control of plant cell expansion. © 2014 American Society of Plant Biologists. All rights reserved.

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Journal

Journal ID (nlm-ta): Genes (Basel)

Journal ID (iso-abbrev): Genes (Basel)

Journal ID (publisher-id): genes

Title: Genes

Publisher: MDPI

ISSN (Electronic): 2073-4425

Publication date (Electronic): 23 July 2019

Publication date Collection: July 2019

Volume: 10

Issue: 7

Electronic Location Identifier: 555

Affiliations

[1 ]School of Agriculture, Yunnan University, Kunming 650504, China

[2 ]Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China

[3 ]College of Forestry, Hainan University, Haikou 570228, China

[4 ]College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China

[5 ]College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China

[6 ]Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA

Author notes

[* ]Correspondence: hxalong@ 123456gmail.com (X.H.); yikexian@ 123456126.com (K.Y.)

[†]

These authors have contributed equally to this work.

Author information

Gang Deng https://orcid.org/0000-0002-0136-2535

Xing Huang https://orcid.org/0000-0003-3950-0080

Thomas Gbokie Jr. https://orcid.org/0000-0002-8750-824X

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Publisher ID: genes-10-00555

DOI: 10.3390/genes10070555

PMC ID: 6679190

PubMed ID: 31340544

SO-VID: ab0b0108-bd6b-4e61-aa53-cd476716a3ed

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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/).

Identification and Expression of SAUR Genes in the CAM Plant Agave

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Most cited references 46

Prediction of protein subcellular localization.

Plant cell wall-mediated immunity: cell wall changes trigger disease resistance responses.

SAUR Inhibition of PP2C-D Phosphatases Activates Plasma Membrane H+-ATPases to Promote Cell Expansion in Arabidopsis.

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