References
- Badole SL, Patil KY, Rangari VD (2015) Antihyperglycemic activity of bioactive compounds from soybeans. In: Glucose intake and utilization in pre-diabetes and diabetes: Implications for cardiovascular disease. Academic Press, Boston, pp. 225-227
- Boersema PJ, Kahraman A, Picotti P (2015) Proteomics beyond large-scale protein expression analysis. Curr. Opin. Biotechnol. 34:162-170 https://doi.org/10.1016/j.copbio.2015.01.005
- Fait A, Angelovici R, Less H, et al (2006) Arabidopsis seed development and germination is associated with temporally distinct metabolic switches. Plant Physiol. 142:839-854 https://doi.org/10.1104/pp.106.086694
- Galili G, Avin-Wittenberg T, Angelovici R, Fernie AR (2014) The role of photosynthesis and amino acid metabolism in the energy status during seed development. Front. Plant Sci. 5:1-6
- Gallardo K, Firnhaber C, Zuber H, et al (2007) A combined proteome and ranscriptome analysis of developing Medicago truncatula seeds: Evidence for metabolic specialization of maternal and filial tissues. Mol. Cell. Proteomics 6:2165-2179 https://doi.org/10.1074/mcp.M700171-MCP200
- Gallardo K, Kurt C, Thompson R, Ochatt S (2006) In vitro culture of immature M. truncatula grains under conditions permitting embryo development comparable to that observed in vivo. Plant Sci. 170:1052-1058 https://doi.org/10.1016/j.plantsci.2005.12.021
- Gupta R, Min CW, Kim SW, et al (2020) A TMT-based quantitative proteome analysis to elucidate the TSWV induced signaling cascade in susceptible and resistant cultivars of Solanum lycopersicum. Plants 9:290 https://doi.org/10.3390/plants9030290
- Gupta R, Min CW, Kim SW, et al (2015) Comparative investigation of seed coats of brown- versus yellow-colored soybean seeds using an integrated proteomics and metabolomics approach. Proteomics 15:1706-1716 https://doi.org/10.1002/pmic.201400453
- Gupta R, Min CW, Kim YJ, Kim ST (2019) Identification of Msp1-induced signaling components in rice leaves by integrated proteomic and phosphoproteomic analysis. Int. J. Mol. Sci. 20:1-17 https://doi.org/10.3390/ijms20010001
- Gupta R, Min CW, Kramer K, et al (2018) A multi-omics analysis of Glycine max leaves reveals alteration in flavonoid and isoflavonoid metabolism upon ethylene and abscisic acid treatment. Proteomics 18:1-10
- Gupta R, Min CW, Wang Y, et al (2016) Expect the unexpected enrichment of "hidden proteome" of seeds and tubers by depletion of storage proteins. Front. Plant Sci. 7:1-7
- Gygi SP, Corthals GL, Zhang Y, et al (2000) Evaluation of two-dimensional gel electrophoresis-based proteome analysis technology. Proc. Natl. Acad. Sci. U. S. A. 97:9390-9395 https://doi.org/10.1073/pnas.160270797
- Han D, Jin J, Woo J, et al (2014) Proteomic analysis of mouse astrocytes and their secretome by a combination of FASP and stage tip-based, high pH, reversed-phase fractionation. Proteomics 14:1604-1609 https://doi.org/10.1002/pmic.201300495
- Jiao X, Sherman BT, Huang DW, et al (2012) DAVID-WS: A stateful web service to facilitate gene/protein list analysis. Bioinformatics 28:1805-1806 https://doi.org/10.1093/bioinformatics/bts251
- Kambhampati S, Aznar-Moreno JA, Hostetler C, et al. (2020) On the inverse correlation of protein and oil: Examining the effects of altered central carbon metabolism on seed composition using soybean fast neutron mutants. Metabolites 10:1-15
- Kim DK, Park J, Han D, et al. (2018) Molecular and functional signatures in a novel Alzheimer's disease mouse model assessed by quantitative proteomics. Mol. Neurodegener. 13:1-19 https://doi.org/10.1186/s13024-017-0233-5
- Kim ST, Cho KS, Jang YS, Kang KY (2001) Two-dimensional electrophoretic analysis of rice proteins by polyethylene glycol fractionation for protein arrays. Electrophoresis 22:2103-2109 https://doi.org/10.1002/1522-2683(200106)22:10<2103::AID-ELPS2103>3.0.CO;2-W
- Kim YJ, Lee HM, Wang Y, et al. (2013) Depletion of abundant plant RuBisCO protein using the protamine sulfate precipitation method. Proteomics 13: 2176-2179 https://doi.org/10.1002/pmic.201200555
- Kim YJ, Wang Y, Gupta R, et al. (2015) Protamine sulfate precipitation method depletes abundant plant seed-storage proteins: A case study on legume plants. Proteomics 15: 1760-1764 https://doi.org/10.1002/pmic.201400488
- Krishnan HB, Coe EH (2001) Seed Storage Proteins. In: Encyclopedia of Genetics. Academic Press, New York, pp.1782-1787
- Krishnan HB, Oehrle NW, Natarajan SS (2009) A rapid and simple procedure for the depletion of abundant storage proteins from legume seeds to advance proteome analysis: A case study using Glycine max. Proteomics 9:3174-3188 https://doi.org/10.1002/pmic.200800875
- Lambirth KC, Whaley AM, Blakley IC, et al. (2015) A comparison of transgenic and wild type soybean seeds: Analysis of transcriptome profiles using RNA-Seq. BMC Biotechnol. 15:89 https://doi.org/10.1186/s12896-015-0207-z
- Maclean B, Tomazela DM, Shulman N, et al. (2010) Skyline : an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26:966-968 https://doi.org/10.1093/bioinformatics/btq054
- Min CW, Gupta R, Agrawal GK, et al (2019) Concepts and strategies of soybean seed proteomics using the shotgun proteomics approach. Expert Rev. Proteomics 16:795-804 https://doi.org/10.1080/14789450.2019.1654860
- Min CW, Hyeon H, Gupta R, et al. (2020a) Integrated proteomics and metabolomics analysis highlights correlative metabolite-protein networks in soybean seeds subjected to warm-water soaking. J. Agric. Food Chem. 68:8057-8067 https://doi.org/10.1021/acs.jafc.0c00986
- Min CW, Kim YJ, Gupta R, et al. (2016) High-throughput proteome analysis reveals changes of primary metabolism and energy production under artificial aging treatment in Glycine max seeds. Appl. Biol. Chem. 59:841-853 https://doi.org/10.1007/s13765-016-0234-z
- Min CW, Lee SH, Cheon YE, et al. (2017) In-depth proteomic analysis of Glycine max seeds during controlled deterioration treatment reveals a shift in seed metabolism. J. Proteomics 169:125-135 https://doi.org/10.1016/j.jprot.2017.06.022
- Min CW, Park J, Bae JW, et al. (2020b) In-depth investigation of low-abundance proteins in matured and filling stages seeds of Glycine max employing a combination of protamine sulfate precipitation and TMT-based quantitative proteomic analysis. Cells 9:1517 https://doi.org/10.3390/cells9061517
- Min CW, Gupta R, Kim SW, et al. (2015) Comparative biochemical and proteomic analyses of soybean seed cultivars differing in protein and oil content. J. Agric. Food Chem. 63:7134-7142 https://doi.org/10.1021/acs.jafc.5b03196
- Niu L, Yuan H, Gong F, et al (2018) Protein extraction methods shape much of the extracted proteomes. Front. Plant Sci. 9:802 https://doi.org/10.3389/fpls.2018.00802
- Ohyama T, Ohtake N, Sueyoshi K, et al. (2017) Amino acid metabolism and transport in soybean plants. In: Amino acid - New insights and roles in plant and animal. IntechOpen, London
- Pajarillo EAB, Kim SH, Lee JY, et al (2015) Quantitative proteogenomics and the reconstruction of the metabolic pathway in Lactobacillus mucosae LM1. Korean J. Food Sci. Anim. Resour. 35:692-702 https://doi.org/10.5851/kosfa.2015.35.5.692
- Pandurangan S, Pajak A, Molnar SJ, et al. (2012) Relationship between asparagine metabolism and protein concentration in soybean seed. J. Exp. Bot. 63:3173-3184 https://doi.org/10.1093/jxb/ers039
- Plubell DL, Wilmarth PA, Zhao Y, et al. (2017) Extended multiplexing of tandem mass tags (TMT) labeling reveals age and high fat diet specific proteome changes in mouse epididymal adipose tissue. Mol. Cell. Proteomics 16:873-890 https://doi.org/10.1074/mcp.M116.065524
- Schmidt MA, Barbazuk WB, Sandford M, et al. (2011) Silencing of soybean seed storage proteins results in a rebalanced protein composition preserving seed protein content without major collateral changes in the metabolome and transcriptome. Plant Physiol. 156:330-345 https://doi.org/10.1104/pp.111.173807
- Thompson A, Kuhn K, Kienle S, et al. (2003) Tandem mass tags: A novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem. 75:1895-1904 https://doi.org/10.1021/ac0262560
- Tian T, Liu Y, Yan H, et al. (2017) AgriGO v2.0: A GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res. 45:W122-W129 https://doi.org/10.1093/nar/gkx382
- Tyanova S, Temu T, Cox J (2016a) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc. 11:2301-2319 https://doi.org/10.1038/nprot.2016.136
- Tyanova S, Temu T, Sinitcyn P, et al. (2016b) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13:731-740 https://doi.org/10.1038/nmeth.3901
- Wisniewski JR, Zougman A, Nagaraj N, Mann M (2009) Universal sample preparation method for proteome analysis. Nat. Methods 6:359-362 https://doi.org/10.1038/nmeth.1322
- Xu XP, Liu H, Tian L, et al (2015) Integrated and comparative proteomics of high-oil and high-protein soybean seeds. Food Chem. 172:105-116 https://doi.org/10.1016/j.foodchem.2014.09.035
- Yu SH, Kiriakidou P, Cox J (2020) Isobaric matching between runs and novel PSM-level normalization in MaxQuant strongly improve reporter ion-based quantification. bioRxiv.