19. Diz AP, Skibinski DOF (2007) Evolution of
2-DE protein patterns in a mussel hybrid
zone. Proteomics 7(12):2111–2120. https://
doi.org/10.1002/pmic.200600954
20. Diz AP, Truebano M, Skibinski DOF (2009)
The consequences of sample pooling in proteomics: an empirical study. Electrophoresis 30
(17):2967–2975. https://doi.org/10.1002/
elps.200900210
21. Atasaral-S ¸ ahin S ¸ , Romero MR, Cueto R, Gonza ´lez-Lavı ´n N, Marcos M, Diz AP (2015) Subtle tissue and sex-dependent proteome
variation in mussel (Mytilus galloprovincialis)
populations of the Galician coast (NW Spain)
raised in a common environment. Proteomics
15(23–24):3993–4006. https://doi.org/10.
1002/pmic.201500241
22. Oberg AL, Vitek O (2009) Statistical design of
quantitative mass spectrometry-based proteomic experiments. J Proteome Res 8
(5):2144–2156. https://doi.org/10.1021/
pr8010099
23. Diz AP, Rola ´n-Alvarez E (2014) High proteome variation between ecotypes of Littorina
saxatilis cannot be explained by tissue heterogeneity or a common-garden  ecotype effect.
J Exp Mar Biol Ecol 451:69–73. https://doi.
org/10.1016/j.jembe.2013.11.002
24. Timp W, Timp G (2020) Beyond mass spectrometry, the next step in proteomics. Sci Adv
6(2):eaax8978.
https://doi.org/10.1126/
sciadv.aax8978
25. Doerr A (2019) Single-cell proteomics. Nat
Methods
16(1):20.
https://doi.org/10.
1038/s41592-018-0273-y
26. Drissi R, Dubois M-L, Boisvert F-M (2013)
Proteomics methods for subcellular proteome
analysis. FEBS J 280(22):5626–5634. https://
doi.org/10.1111/febs.12502
27. Romero MR, Pe ´rez-Figueroa A, Carrera M,
Swanson WJ, Skibinski DOF, Diz AP (2019)
RNA-seq coupled to proteomic analysis reveals
high sperm proteome variation between two
closely related marine mussel species. J Proteome
192:169–187.
https://doi.org/10.
1016/j.jprot.2018.08.020
28. Viner
R,
Scigelova
M,
Zeller
M,
Oppermann M, Moehring T, Zabrouskov V
(2016) Relative quantitation of TMT-labeled
proteomes – focus on sensitivity and precision.
Application note 566. Thermo Fisher Scientific
Inc., San Jose, CA
29. Viner R, Bomgarden R, Blank M, Rogers J
(2016) Increasing the multiplexing of protein
quantitation from 6- to 10-plex with reporter
ion isotopologues. ASMS13_W617_RViner_E
07/16S. Thermo Fisher Scientific Inc., San
Jose, CA
30. Matthiesen R (2013) Algorithms for databasedependent search of MS/MS data. In: Matthiesen R (ed) Mass spectrometry data analysis
in proteomics. Humana, Totowa, NJ, pp
119–138. https://doi.org/10.1007/978-162703-392-3_5
31. Wang X, Zhang B (2013) customProDB: an R
package to generate customized protein databases from RNA-Seq data for proteomics
search. Bioinformatics 29(24):3235–3237.
https://doi.org/10.1093/bioinformatics/
btt543
32. Moreira R, Pereiro P, Canchaya C, Posada D,
Figueras A, Novoa B (2015) RNA-Seq in Mytilus galloprovincialis: comparative transcriptomics and expression profiles among
different tissues. BMC Genomics 16(1).
https://doi.org/10.1186/s12864-015-18175
33. Diz AP, Romero MR, Pe ´rez-Figueroa A, Swanson WJ, Skibinski DOF (2018) RNA-seq data
from mature male gonads of marine mussels
Mytilus edulis and M. galloprovincialis. Data
Brief 21:167–175. https://doi.org/10.1016/
j.dib.2018.09.086
34. Medzihradszky KF, Chalkley RJ (2015) Lessons in de novo peptide sequencing by tandem
mass spectrometry. Mass Spectrom Rev 34
(1):43–63.
https://doi.org/10.1002/mas.
21406
35. Sa ´nchez-Marı ´n P, Ferna ´ndez-Gonza ´lez LE,
Mantilla-Aldana L, Diz AP, Beiras R (2017)
Shotgun proteomics analysis discards alkali
labile phosphate as a reliable method to assess
vitellogenin levels in Mytilus galloprovincialis.
Environ Sci Technol 51(13):7572–7580.
https://doi.org/10.1021/acs.est.7b01734
36. Ferna ´ndez-Gonza ´lez LE, Diz AP, GrueiroNoche G, Muniategui S, Beiras R, Sa ´nchezMarı ´n P (2020) No evidence that vitellogenin
protein expression is induced in marine mussels
after exposure to an estrogenic chemical. Sci
Total Environ. https://doi.org/10.1016/j.
scitotenv.2020.137638
37. Megger DA, Bracht T, Meyer HE, Sitek B
(2013) Label-free quantification in clinical proteomics. Biochim Biophys Acta 1834
(8):1581–1590. https://doi.org/10.1016/j.
bbapap.2013.04.001
38. Neilson KA, Ali NA, Muralidharan S,
Mirzaei M, Mariani M, Assadourian G, Lee A,
van Sluyter SC, Haynes PA (2011) Less label,
more free: approaches in label-free quantitative
mass
spectrometry.
Proteomics
11
Shotgun Proteomics in Non-model Organisms
101
2-DE protein patterns in a mussel hybrid
zone. Proteomics 7(12):2111–2120. https://
doi.org/10.1002/pmic.200600954
20. Diz AP, Truebano M, Skibinski DOF (2009)
The consequences of sample pooling in proteomics: an empirical study. Electrophoresis 30
(17):2967–2975. https://doi.org/10.1002/
elps.200900210
21. Atasaral-S ¸ ahin S ¸ , Romero MR, Cueto R, Gonza ´lez-Lavı ´n N, Marcos M, Diz AP (2015) Subtle tissue and sex-dependent proteome
variation in mussel (Mytilus galloprovincialis)
populations of the Galician coast (NW Spain)
raised in a common environment. Proteomics
15(23–24):3993–4006. https://doi.org/10.
1002/pmic.201500241
22. Oberg AL, Vitek O (2009) Statistical design of
quantitative mass spectrometry-based proteomic experiments. J Proteome Res 8
(5):2144–2156. https://doi.org/10.1021/
pr8010099
23. Diz AP, Rola ´n-Alvarez E (2014) High proteome variation between ecotypes of Littorina
saxatilis cannot be explained by tissue heterogeneity or a common-garden  ecotype effect.
J Exp Mar Biol Ecol 451:69–73. https://doi.
org/10.1016/j.jembe.2013.11.002
24. Timp W, Timp G (2020) Beyond mass spectrometry, the next step in proteomics. Sci Adv
6(2):eaax8978.
https://doi.org/10.1126/
sciadv.aax8978
25. Doerr A (2019) Single-cell proteomics. Nat
Methods
16(1):20.
https://doi.org/10.
1038/s41592-018-0273-y
26. Drissi R, Dubois M-L, Boisvert F-M (2013)
Proteomics methods for subcellular proteome
analysis. FEBS J 280(22):5626–5634. https://
doi.org/10.1111/febs.12502
27. Romero MR, Pe ´rez-Figueroa A, Carrera M,
Swanson WJ, Skibinski DOF, Diz AP (2019)
RNA-seq coupled to proteomic analysis reveals
high sperm proteome variation between two
closely related marine mussel species. J Proteome
192:169–187.
https://doi.org/10.
1016/j.jprot.2018.08.020
28. Viner
R,
Scigelova
M,
Zeller
M,
Oppermann M, Moehring T, Zabrouskov V
(2016) Relative quantitation of TMT-labeled
proteomes – focus on sensitivity and precision.
Application note 566. Thermo Fisher Scientific
Inc., San Jose, CA
29. Viner R, Bomgarden R, Blank M, Rogers J
(2016) Increasing the multiplexing of protein
quantitation from 6- to 10-plex with reporter
ion isotopologues. ASMS13_W617_RViner_E
07/16S. Thermo Fisher Scientific Inc., San
Jose, CA
30. Matthiesen R (2013) Algorithms for databasedependent search of MS/MS data. In: Matthiesen R (ed) Mass spectrometry data analysis
in proteomics. Humana, Totowa, NJ, pp
119–138. https://doi.org/10.1007/978-162703-392-3_5
31. Wang X, Zhang B (2013) customProDB: an R
package to generate customized protein databases from RNA-Seq data for proteomics
search. Bioinformatics 29(24):3235–3237.
https://doi.org/10.1093/bioinformatics/
btt543
32. Moreira R, Pereiro P, Canchaya C, Posada D,
Figueras A, Novoa B (2015) RNA-Seq in Mytilus galloprovincialis: comparative transcriptomics and expression profiles among
different tissues. BMC Genomics 16(1).
https://doi.org/10.1186/s12864-015-18175
33. Diz AP, Romero MR, Pe ´rez-Figueroa A, Swanson WJ, Skibinski DOF (2018) RNA-seq data
from mature male gonads of marine mussels
Mytilus edulis and M. galloprovincialis. Data
Brief 21:167–175. https://doi.org/10.1016/
j.dib.2018.09.086
34. Medzihradszky KF, Chalkley RJ (2015) Lessons in de novo peptide sequencing by tandem
mass spectrometry. Mass Spectrom Rev 34
(1):43–63.
https://doi.org/10.1002/mas.
21406
35. Sa ´nchez-Marı ´n P, Ferna ´ndez-Gonza ´lez LE,
Mantilla-Aldana L, Diz AP, Beiras R (2017)
Shotgun proteomics analysis discards alkali
labile phosphate as a reliable method to assess
vitellogenin levels in Mytilus galloprovincialis.
Environ Sci Technol 51(13):7572–7580.
https://doi.org/10.1021/acs.est.7b01734
36. Ferna ´ndez-Gonza ´lez LE, Diz AP, GrueiroNoche G, Muniategui S, Beiras R, Sa ´nchezMarı ´n P (2020) No evidence that vitellogenin
protein expression is induced in marine mussels
after exposure to an estrogenic chemical. Sci
Total Environ. https://doi.org/10.1016/j.
scitotenv.2020.137638
37. Megger DA, Bracht T, Meyer HE, Sitek B
(2013) Label-free quantification in clinical proteomics. Biochim Biophys Acta 1834
(8):1581–1590. https://doi.org/10.1016/j.
bbapap.2013.04.001
38. Neilson KA, Ali NA, Muralidharan S,
Mirzaei M, Mariani M, Assadourian G, Lee A,
van Sluyter SC, Haynes PA (2011) Less label,
more free: approaches in label-free quantitative
mass
spectrometry.
Proteomics
11
Shotgun Proteomics in Non-model Organisms
101