grateful to Sofı ´a Blanco, Mo ´ nica Carrera, Laura Emilia Ferna ´ndez,
Manuel Marcos, Jesu ´ s Mateos, and Mo ´ nica Rodrı ´guez Romero for
methodological and technical contribution in label-free, TMT-labeling, and LC–MS/MS analysis described in this chapter.
The authors declare no conflict of interest.
References
1. Diz AP, Martı ´nez-Ferna ´ndez M, Rola ´nAlvarez E (2012) Proteomics in evolutionary
ecology: linking the genotype with the phenotype. Mol Ecol 21(5):1060–1080. https://doi.
org/10.1111/j.1365-294X.2011.05426.x
2. Calvete JJ (2014) Challenges and prospects of
proteomics of non-model organisms. J Proteomics 105:1–4. https://doi.org/10.1016/j.
jprot.2014.04.034
3. Diz AP, Calvete JJ (2016) Ecological proteomics: is the field ripe for integrating proteomics
into evolutionary ecology research? J Proteomics 135:1–3. https://doi.org/10.1016/j.
jprot.2016.01.020
4. Diz AP, Pa ´ez de la Cadena M, Rola ´n-Alvarez E
(2012) Proteomic evidence of a paedomorphic
evolutionary process within a marine snail species: a strategy for adapting to extreme ecological
conditions?
J
Evol
Biol
25
(12):2569–2581. https://doi.org/10.1111/
jeb.12001
5. Russell JJ, Theriot JA, Sood P, Marshall WF,
Landweber LF, Fritz-Laylin L, Polka JK,
Oliferenko S, Gerbich T, Gladfelter A,
Umen J, Bezanilla M, Lancaster MA, He S,
Gibson MC, Goldstein B, Tanaka EM, Hu
C-K, Brunet A (2017) Non-model model
organisms. BMC Biol 15(1):55. https://doi.
org/10.1186/s12915-017-0391-5
6. Mukherjee S, Stamatis D, Bertsch J,
Ovchinnikova G, Katta HY, Mojica A, Chen
I-MA, Kyrpides NC, Reddy T (2019) Genomes OnLine database (GOLD) v.7: updates
and new features. Nucleic Acids Res 47(D1):
D649–D659. https://doi.org/10.1093/nar/
gky977
7. Findlay GD, Swanson WJ (2010) Proteomics
enhances evolutionary and functional analysis
of reproductive proteins. BioEssays 32
(1):26–36.
https://doi.org/10.1002/bies.
200900127
8. Armengaud J, Trapp J, Pible O, Geffard O,
Chaumot A, Hartmann EM (2014)
Non-model organisms, a species endangered
by proteogenomics. J Proteomics 105:5–18.
https://doi.org/10.1016/j.jprot.2014.01.
007
9. Nesvizhskii AI (2014) Proteogenomics: concepts, applications and computational strategies. Nat Methods 11(11):1114–1125.
https://doi.org/10.1038/nmeth.3144
10. Washburn MP, Wolters D, Yates JR (2001)
Large-scale analysis of the yeast proteome by
multidimensional protein identification technology. Nat Biotechnol 19(3):242–247.
https://doi.org/10.1038/85686
11. Motoyama A, Yates JR (2008) Multidimensional LC separations in shotgun proteomics.
Anal Chem 80(19):7187–7193. https://doi.
org/10.1021/ac8013669
12. Rabilloud T, Chevallet M, Luche S, Lelong C
(2010) Two-dimensional gel electrophoresis in
proteomics: past, present and future. J Proteomics 73(11):2064–2077. https://doi.org/10.
1016/j.jprot.2010.05.016
13. Bantscheff M, Lemeer S, Savitski MM, Kuster
B (2012) Quantitative mass spectrometry in
proteomics: critical review update from 2007
to the present. Anal Bioanal Chem 404
(4):939–965.
https://doi.org/10.1007/
s00216-012-6203-4
14. Rauniyar N, Yates JR (2014) Isobaric labelingbased relative quantification in shotgun proteomics. J Proteome Res 13(12):5293–5309.
https://doi.org/10.1021/pr500880b
15. Arul AB, Robinson RAS (2019) Sample multiplexing strategies in quantitative proteomics.
Anal Chem 91(1):178–189. https://doi.org/
10.1021/acs.analchem.8b05626
16. Pappireddi N, Martin L, Wu ¨hr M (2019) A
review on quantitative multiplexed proteomics.
Chembiochem 20(10):1210–1224. https://
doi.org/10.1002/cbic.201800650
17. Karp NA, Spencer M, Lindsay H, O’Dell K,
Lilley KS (2005) Impact of replicate types on
proteomic expression analysis. J Proteome Res
4(5):1867–1871. https://doi.org/10.1021/
pr050084g
18. Karp NA, Lilley KS (2007) Design and analysis
issues in quantitative proteomics studies. Proteomics 2(1):42–50. https://doi.org/10.
1002/pmic.200700683
100
Angel P. Diz and Paula Sa ´ nchez-Marı ´n
Manuel Marcos, Jesu ´ s Mateos, and Mo ´ nica Rodrı ´guez Romero for
methodological and technical contribution in label-free, TMT-labeling, and LC–MS/MS analysis described in this chapter.
The authors declare no conflict of interest.
References
1. Diz AP, Martı ´nez-Ferna ´ndez M, Rola ´nAlvarez E (2012) Proteomics in evolutionary
ecology: linking the genotype with the phenotype. Mol Ecol 21(5):1060–1080. https://doi.
org/10.1111/j.1365-294X.2011.05426.x
2. Calvete JJ (2014) Challenges and prospects of
proteomics of non-model organisms. J Proteomics 105:1–4. https://doi.org/10.1016/j.
jprot.2014.04.034
3. Diz AP, Calvete JJ (2016) Ecological proteomics: is the field ripe for integrating proteomics
into evolutionary ecology research? J Proteomics 135:1–3. https://doi.org/10.1016/j.
jprot.2016.01.020
4. Diz AP, Pa ´ez de la Cadena M, Rola ´n-Alvarez E
(2012) Proteomic evidence of a paedomorphic
evolutionary process within a marine snail species: a strategy for adapting to extreme ecological
conditions?
J
Evol
Biol
25
(12):2569–2581. https://doi.org/10.1111/
jeb.12001
5. Russell JJ, Theriot JA, Sood P, Marshall WF,
Landweber LF, Fritz-Laylin L, Polka JK,
Oliferenko S, Gerbich T, Gladfelter A,
Umen J, Bezanilla M, Lancaster MA, He S,
Gibson MC, Goldstein B, Tanaka EM, Hu
C-K, Brunet A (2017) Non-model model
organisms. BMC Biol 15(1):55. https://doi.
org/10.1186/s12915-017-0391-5
6. Mukherjee S, Stamatis D, Bertsch J,
Ovchinnikova G, Katta HY, Mojica A, Chen
I-MA, Kyrpides NC, Reddy T (2019) Genomes OnLine database (GOLD) v.7: updates
and new features. Nucleic Acids Res 47(D1):
D649–D659. https://doi.org/10.1093/nar/
gky977
7. Findlay GD, Swanson WJ (2010) Proteomics
enhances evolutionary and functional analysis
of reproductive proteins. BioEssays 32
(1):26–36.
https://doi.org/10.1002/bies.
200900127
8. Armengaud J, Trapp J, Pible O, Geffard O,
Chaumot A, Hartmann EM (2014)
Non-model organisms, a species endangered
by proteogenomics. J Proteomics 105:5–18.
https://doi.org/10.1016/j.jprot.2014.01.
007
9. Nesvizhskii AI (2014) Proteogenomics: concepts, applications and computational strategies. Nat Methods 11(11):1114–1125.
https://doi.org/10.1038/nmeth.3144
10. Washburn MP, Wolters D, Yates JR (2001)
Large-scale analysis of the yeast proteome by
multidimensional protein identification technology. Nat Biotechnol 19(3):242–247.
https://doi.org/10.1038/85686
11. Motoyama A, Yates JR (2008) Multidimensional LC separations in shotgun proteomics.
Anal Chem 80(19):7187–7193. https://doi.
org/10.1021/ac8013669
12. Rabilloud T, Chevallet M, Luche S, Lelong C
(2010) Two-dimensional gel electrophoresis in
proteomics: past, present and future. J Proteomics 73(11):2064–2077. https://doi.org/10.
1016/j.jprot.2010.05.016
13. Bantscheff M, Lemeer S, Savitski MM, Kuster
B (2012) Quantitative mass spectrometry in
proteomics: critical review update from 2007
to the present. Anal Bioanal Chem 404
(4):939–965.
https://doi.org/10.1007/
s00216-012-6203-4
14. Rauniyar N, Yates JR (2014) Isobaric labelingbased relative quantification in shotgun proteomics. J Proteome Res 13(12):5293–5309.
https://doi.org/10.1021/pr500880b
15. Arul AB, Robinson RAS (2019) Sample multiplexing strategies in quantitative proteomics.
Anal Chem 91(1):178–189. https://doi.org/
10.1021/acs.analchem.8b05626
16. Pappireddi N, Martin L, Wu ¨hr M (2019) A
review on quantitative multiplexed proteomics.
Chembiochem 20(10):1210–1224. https://
doi.org/10.1002/cbic.201800650
17. Karp NA, Spencer M, Lindsay H, O’Dell K,
Lilley KS (2005) Impact of replicate types on
proteomic expression analysis. J Proteome Res
4(5):1867–1871. https://doi.org/10.1021/
pr050084g
18. Karp NA, Lilley KS (2007) Design and analysis
issues in quantitative proteomics studies. Proteomics 2(1):42–50. https://doi.org/10.
1002/pmic.200700683
100
Angel P. Diz and Paula Sa ´ nchez-Marı ´n