Improving the quality of protein identification in non-model species. Characterization of Quercus ilex seed and Pinus radiata needle proteomes by using SEQUEST and custom databases

Romero-Rodríguez, M. Cristina; Pascual, Jesús; Valledor, Luís; Jorrín‐Novo, Jesús V.

doi:10.1016/j.jprot.2014.01.027

Cited by 56 publications

(48 citation statements)

References 26 publications

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“…Although the concatenation of these databases results in a very large database with many homologous entries, our results demonstrate that the combination of proteomic and transcriptomic resources is essential to make adequate biological interpretations. In agreement with previous studies, we show that the sole use of the VPDB—or any other publicly available database for protein identification—is inefficient in non-model species, since they are under-represented in most databases, resulting in poor identification rates (Romero-Rodríguez et al, 2014). …”

Section: Discussionsupporting

confidence: 91%

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis

Grossmann¹,

Fernández

Chaubey

et al. 2017

Front. Plant Sci.

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Performing proteomic studies on non-model organisms with little or no genomic information is still difficult. However, many specific processes and biochemical pathways occur only in species that are poorly characterized at the genomic level. For example, many plants can reproduce both sexually and asexually, the first one allowing the generation of new genotypes and the latter their fixation. Thus, both modes of reproduction are of great agronomic value. However, the molecular basis of asexual reproduction is not well understood in any plant. In ferns, it combines the production of unreduced spores (diplospory) and the formation of sporophytes from somatic cells (apogamy). To set the basis to study these processes, we performed transcriptomics by next-generation sequencing (NGS) and shotgun proteomics by tandem mass spectrometry in the apogamous fern D. affinis ssp. affinis. For protein identification we used the public viridiplantae database (VPDB) to identify orthologous proteins from other plant species and new transcriptomics data to generate a “species-specific transcriptome database” (SSTDB). In total 1,397 protein clusters with 5,865 unique peptide sequences were identified (13 decoy proteins out of 1,410, protFDR 0.93% on protein cluster level). We show that using the SSTDB for protein identification increases the number of identified peptides almost four times compared to using only the publically available VPDB. We identified homologs of proteins involved in reproduction of higher plants, including proteins with a potential role in apogamy. With the increasing availability of genomic data from non-model species, similar proteogenomics approaches will improve the sensitivity in protein identification for species only distantly related to models.

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Section: Discussionsupporting

confidence: 91%

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis

Grossmann¹,

Fernández

Chaubey

et al. 2017

Front. Plant Sci.

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“…Our data show that comprehensive proteomic profiling of plant proteins, such as gluten, is not limited by the proteomics methodology, but by access to appropriate genetic data in a form usable for proteomic informatics pipelines which can handle highly polymorphic proteins with regards amino acid substitutions, which have both repeating sequences and deletions (Vensel et al, 2011; Kasarda et al, 2013; Romero-Rodríguez et al, 2014). Such integrated approaches will be required to unravel why certain wheat cultivars, such as Hereward, have better than expected bread making quality and hence identify novel targets for crop improvement.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Proteomic Profiling of Wheat Gluten Using a Combination of Data-Independent and Data-Dependent Acquisition

et al. 2017

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Wheat is the most important food crop in the world, the unique physiochemical properties of wheat gluten enabling a diverse range of food products to be manufactured. However, genetic and environmental factors affect the technological properties of gluten in unpredictable ways. Although newer proteomic methods have the potential to offer much greater levels of information, it is the older gel-based methods that remain most commonly used to identify compositional differences responsible for the variation in gluten functionality, in part due to the nature of their primary sequences. A combination of platforms were investigated for comprehensive gluten profiling: a QTOF with a data independent schema, which incorporated ion mobility (DIA-IM-MS) and a data dependent acquisition (DDA) workflow using a linear ion trap quadrupole (LTQ) instrument. In conjunction with a manually curated gluten sequence database a total of 2736 gluten peptides were identified with only 157 peptides identified by both platforms. These data showed 127 and 63 gluten protein accessions to be inferred with a minimum of one and three unique peptides respectively. Of the 63 rigorously identified proteins, 26 were gliadin species (4 ω-, 14 α-, and 8 γ-gliadins) and 37 glutenins (including 29 LMW glutenin and 8 HMW glutenins). Of the HMW glutenins, three were 1Dx type and five were 1Bx type illustrating the challenge of unambiguous identification of highly polymorphic proteins without cultivar specific gene sequences. The capacity of the platforms to sequence longer peptides was crucial to achieving the number of identifications, the combination of QTOF-LTQ technology being more important than extraction method to obtain a comprehensive profile. Widespread glutamine deamidation, a post-translational modification, was observed adding complexity to an already highly polymorphic mixture of proteins, with numerous insertions, deletions and substitutions. The data shown is the most comprehensive and detailed proteomic profile of gluten to date.

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“…The MS/MS data were processed employing Proteome Discoverer 1.4 (Thermo) and identified using SEQUEST algorithm against a selection of NCBI taxa corresponding to Viridiplantae proteins (83269 entries). Furthermore, all available Pine and Picea protein, gene, nucleotide and EST sequences were downloaded from NCBI on early 2013 and then trimmed, contiged, 6-frame translated, and identified following the procedure described by Romero-Rodríguez et al (34) to develop two specific databases belonging to Pinus and Picea genus (34063 and 67647 entries respectively) that were employed as an independent database. All sequences were downloaded the same date.…”

Section: Methodsmentioning

confidence: 99%

“…The results of high-throughput proteomic analyses rely on an adequate mass spectrometry and the availability of specific databases. Because Pinus radiata is a nonmodel species, we needed to combine standard with custom-built Pinus databases (34) to identify the proteins obtained in LTQ-Orbitrap instrument. This approach allowed the identification of 1646 protein species.…”

Section: Integrated Proteomic Metabolomic and Phenotypic Analyses Rmentioning

confidence: 99%

Integrated Physiological, Proteomic, and Metabolomic Analysis of Ultra Violet (UV) Stress Responses and Adaptation Mechanisms in Pinus radiata

Pascual

Cañal

Escandón

et al. 2017

Molecular & Cellular Proteomics

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Globally expected changes in environmental conditions, especially the increase of UV irradiation, necessitate extending our knowledge of the mechanisms mediating tree species adaptation to this stress. This is crucial for designing new strategies to maintain future forest productivity. Studies focused on environmentally realistic dosages of UV irradiation in forest species are scarce. are commercially relevant trees and not much is known about their adaptation to UV. In this work, UV treatment and recovery of plants with dosages mimicking future scenarios, based on current models of UV radiation, were performed in a time-dependent manner. The combined metabolome and proteome analysis were complemented with measurements of + physiological parameters and gene expression. Sparse PLS analysis revealed complex molecular interaction networks of molecular and physiological data. Early responses prevented phototoxicity by reducing photosystem activity and the electron transfer chain together with the accumulation of photoprotectors and photorespiration. Apart from the reduction in photosynthesis as consequence of the direct UV damage on the photosystems, the primary metabolism was rearranged to deal with the oxidative stress while minimizing ROS production. New protein kinases and proteases related to signaling, coordination, and regulation of UV stress responses were revealed. All these processes demonstrate a complex molecular interaction network extending the current knowledge on UV-stress adaptation in pine.

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Improving the quality of protein identification in non-model species. Characterization of Quercus ilex seed and Pinus radiata needle proteomes by using SEQUEST and custom databases

Cited by 56 publications

References 26 publications

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis

Comprehensive Proteomic Profiling of Wheat Gluten Using a Combination of Data-Independent and Data-Dependent Acquisition

Integrated Physiological, Proteomic, and Metabolomic Analysis of Ultra Violet (UV) Stress Responses and Adaptation Mechanisms in Pinus radiata

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