Literature DB >> 33687710

A Primer and Guidelines for Shotgun Proteomic Analysis in Non-model Organisms.

Angel P Diz1,2, Paula Sánchez-Marín3.   

Abstract

During the last decade, we have witnessed outstanding advances in proteomics led mostly by great technological improvements in mass spectrometry field allowing high-throughput production of high-quality data used for massive protein identification and quantification. From a practical viewpoint, these advances have been mainly exploited in research projects involving model organisms with abundant genomic and proteomic information available in public databases. However, there is a growing number of organisms of high interest in different disciplines, such as ecological, biotechnological, and evolutionary research, yet poorly represented in these databases. Important advances in massive parallel sequencing technology and easy accessibility of this technology to many research laboratories have made nowadays possible to produce customized genomic and proteomic databases of any organism. Along this line, the use of proteogenomic approaches by combining in the same analysis the data obtained from different omic levels has emerged as a very useful and powerful strategy to run shotgun proteomic experiments specially focused on non-model organisms. In this chapter, we provide detailed procedures to undertake shotgun quantitative proteomic experiments following either a label-free or an isobaric labeling approach in non-model organisms, emphasizing also a few key aspects related to experimental design and data analysis.

Keywords:  Data normalization; Isobaric labeling; Label-free; Multiple testing correction methods; Pooling samples; Proteogenomics; Quantitative proteomics

Mesh:

Substances:

Year:  2021        PMID: 33687710     DOI: 10.1007/978-1-0716-1178-4_6

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  32 in total

Review 1.  Proteomics in evolutionary ecology: linking the genotype with the phenotype.

Authors:  Angel P Diz; Mónica Martínez-Fernández; Emilio Rolán-Alvarez
Journal:  Mol Ecol       Date:  2012-01-23       Impact factor: 6.185

Review 2.  Proteomics enhances evolutionary and functional analysis of reproductive proteins.

Authors:  Geoffrey D Findlay; Willie J Swanson
Journal:  Bioessays       Date:  2010-01       Impact factor: 4.345

3.  Proteomic evidence of a paedomorphic evolutionary process within a marine snail species: a strategy for adapting to extreme ecological conditions?

Authors:  A P Diz; M Páez de la Cadena; E Rolán-Alvarez
Journal:  J Evol Biol       Date:  2012-10-01       Impact factor: 2.411

4.  Large-scale analysis of the yeast proteome by multidimensional protein identification technology.

Authors:  M P Washburn; D Wolters; J R Yates
Journal:  Nat Biotechnol       Date:  2001-03       Impact factor: 54.908

5.  Challenges and prospects of proteomics of non-model organisms.

Authors:  Juan J Calvete
Journal:  J Proteomics       Date:  2014-06-13       Impact factor: 4.044

6.  Ecological proteomics: is the field ripe for integrating proteomics into evolutionary ecology research?

Authors:  Angel P Diz; Juan J Calvete
Journal:  J Proteomics       Date:  2016-03-01       Impact factor: 4.044

Review 7.  Proteogenomics: concepts, applications and computational strategies.

Authors:  Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2014-11       Impact factor: 28.547

8.  Non-model model organisms.

Authors:  James J Russell; Julie A Theriot; Pranidhi Sood; Wallace F Marshall; Laura F Landweber; Lillian Fritz-Laylin; Jessica K Polka; Snezhana Oliferenko; Therese Gerbich; Amy Gladfelter; James Umen; Magdalena Bezanilla; Madeline A Lancaster; Shuonan He; Matthew C Gibson; Bob Goldstein; Elly M Tanaka; Chi-Kuo Hu; Anne Brunet
Journal:  BMC Biol       Date:  2017-06-29       Impact factor: 7.431

Review 9.  Non-model organisms, a species endangered by proteogenomics.

Authors:  Jean Armengaud; Judith Trapp; Olivier Pible; Olivier Geffard; Arnaud Chaumot; Erica M Hartmann
Journal:  J Proteomics       Date:  2014-01-16       Impact factor: 4.044

10.  Genomes OnLine database (GOLD) v.7: updates and new features.

Authors:  Supratim Mukherjee; Dimitri Stamatis; Jon Bertsch; Galina Ovchinnikova; Hema Y Katta; Alejandro Mojica; I-Min A Chen; Nikos C Kyrpides; Tbk Reddy
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

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