Edited by: Paul Andrew Haynes, Macquarie University, Australia
Reviewed by: Bronwyn Jane Barkla, Universidad Nacional Autónoma de México, Mexico; Benjamin Schwessinger, University of California Davis, USA; Roque Bru-Martinez, Universidad de Alicante, Spain
*Correspondence: Gregory S. Ladics, DuPont Agricultural Biotechnology, Pioneer Hi-Bred, Wilmington, DE 19880, USA. e-mail:
This article was submitted to Frontiers in Plant Proteomics, a specialty of Frontiers in Plant Science.
This is an open-access article distributed under the terms of the
Soybean (
Soybeans accumulate protein and oil during development, making the mature soybean seed a valuable commodity. For 2008/09, the farm value of soybeans in the United States neared $30 billion (
Much of what we know about the protein component of mature soybean has come from various offline separation techniques like polyacrylamide gel electrophoresis, with or without isoelectric focusing, coupled with antibody or dye based detection methods. Two-dimensional (2-D) gels utilizing appropriate immobilized pH gradients that zoom to either acidic or basic pH ranges have been very successful at separating acidic and basic subunits of glycinin as well as the α and β subunits of β-conglycinin (Mooney et al.,
Quantification of proteins by mass spectrometry can be achieved using a technique called multiple reaction monitoring (MRM), during which signals from the endogenous protein are compared to those from a synthetic heavy-labeled internal standard (Kirkpatrick et al.,
Recently, to begin to understand the natural variation of the allergenic protein levels in soybean, Houston et al. (
Unless stated otherwise, all reagents were purchased through Research Products International, Mount Prospect, IL, USA.
Four commercially available non-GM soybean varieties (92B12, 92M10, 92M72, and 93B15 were utilized for this study. A similarity matrix using all the markers available that are in common between the varieties was conducted and it was found that the lines have anywhere from 62 to 71% similarity. The study design included six sites located in the commercial soybean-growing regions of North America: Quitman, GA, USA; Richland, IA, USA; Larned, KS, USA; York, NE, USA; Branchton, ON, Canada; and Hereford, PA, USA. The field phase of this study was conducted during the 2007 growing season. The mean temperature during the day for each site was as follows: GA (90.5°F); IA (81.5°F); KS (86.5°F); NE (80.3°F); ON (77.5°F); PA (86.8°F). The mean temperature during the night for each site was as follows: GA (68.2°F); IA (60.5°F); KS (59.2°F); NE (58.7°F); ON (53.5°F); PA (58.2°F). Average rainfall for each site is as follows: GA (4.98″); IA (4.79″); KS (2.23″); NE (3.45″); ON (1.99″); PA (2.87″). A randomized complete block design containing three blocks, with each block containing the 92B12, 92M10, 92M72, and 93B15 commercial soybean varieties, was utilized at each site. Each soybean variety was planted in a two-row plot, which was bordered on either side by one row of non-GM commercial soybean variety of similar relative maturity. Sites were surrounded by at least 10 feet of bare ground buffer area. All plants grew well at all locations and harvesting was conducted at typical maturity/dryness levels. Typical would refer to 95% of pods on the plant are mature and seed weight adjusted to 13% seed water content. Seed samples for each cultivar (300 g from each block) were harvested and pooled. There was no morphology/physiology differences among the seeds collected from the different locations. The pools were ground and a portion removed for each cultivar. Samples were shipped at ambient temperatures to the University of Missouri for analysis. Samples were stored at room temperature in the dark until extracted.
Protein was isolated in quadruplicate from 0.25 g of soybean meal using the extraction method described in (Stevenson et al.,
Twenty-five microliters of precipitated protein was collected by centrifugation at 16,000 ×
The remaining aliquot of frozen protein was thawed at 4°C, vortexed to make homogenous and 10 μg of each sample was portioned into 1.5 mL polypropylene tubes. For each, the volume was brought to 10.0 μL using 8 M urea buffer. Disulfide bonds were reduced with 15.0 μL of reduction solution (16.7 mM dithiothreitol (DTT), 6.7 ng/μL BSA in 50 mM ammonium bicarbonate) for 1 h at room temperature. Reduced cysteines were carboxyamidomethylated with 5.0 μL alkylation solution (300 mM iodoacetamide in 50 mM ammonium bicarbonate) at room temperature in the dark for 1 h. Urea was diluted to 0.67 M and iodoacetamide was neutralized with equimolar DTT by adding 90 μL of neutralization solution (16.7 mM DTT in 50 mM ammonium bicarbonate) and incubating at room temperature for 15 min. Samples were chilled to 4°C and 10.0 μL of cold trypsin solution (20 ng/μL sequencing grade – modified, Promega, Madison, WI, USA) in 50 mM ammonium bicarbonate) added. Digestion was allowed to proceed for 16 h at 37°C. AQUA™ peptides (Sigma Life Science, The Woodlands, TX, USA) in 50% acetonitrile (ACN), 1.0% (v/v) formic acid were added to the completed digests, which were frozen and evaporated to dryness using a CentriVap before being stored at −80°C.
AQUA™ peptides were synthesized by Sigma-Aldrich Co. LLC., to greater than 95% purity, and were portioned in 0.5 nmol aliquots and stored lyophilized at −20°C until use. AQUA™ peptides were dissolved to 2.5 pmol/μL using 50% (v/v) ACN (Sigma-Aldrich, Saint Louis, MO, USA), 1.0% (v/v) formic acid (Acros Organics, New Jersey, USA) with 5 × 10 s of vortexing max speed. Portions of 100 pmol were made by aliquoting 40 μL to separate tubes and storing at −80°C after centrifugal evaporation. Prior to use, peptide aliquots were dissolved in 50% (v/v) ACN, 1.0% (v/v) formic acid in an appropriate volume so that when mixed together, the final AQUA™ concentration is 50 fmol/μL (except for glycinin G1, which was at 100 fmol/μL). AQUA™ peptides at these concentrations were added to completed digests at 2 μL/μg of digested material.
All sample digests were dissolved to 200 ng/μL with 5% (v/v) ACN, 0.1% (v/v) formic acid with vortexing (3 × 10 s max speed). Insoluble debris was pelleted with centrifugation at 21,000 ×
Selected Reaction Monitoring results were provided by LCQuan 2.6 (Thermo Fisher Scientific, 2009). Peak detection and integration were performed using the ICIS algorithm with five points of smoothing, and a baseline window of 20. All other values were left as default. Results were exported from LCQuan as tab delimited text files which were imported into MS-Excel (2007) for calculations. Response ratios (unlabeled peptide area/labeled peptide area) were multiplied by the mole amount of each AQUA™ present per microgram of sample to obtain endogenous mole quantities. Endogenous mole quantities were multiplied by the molecular weight of the protein (Table
Linear ranges of detection for all unlabeled peptides of interest were determined with a twofold dilution series of soybean total protein digest using 0.5 M urea buffer (similar to final digest buffer) and AQUA™ internal standards at 100 fmol on column. Injection amounts for the dilution series were from 2 μg down to 125 ng on column. Using the peptide area ratios (unlabeled/labeled) attained from this initial standard curve, linear ranges were determined for each peptide by manually inspecting the response ratio changes between dilutions, using a twofold change in area ratio as an indicator of a perfect response between two dilutions. Slight deviations from this ideality were accounted for by ensuring the internal standard peptide was within 10-fold of the endogenous peptide signal (response of 10–0.1) for all peptides. Final quantitative analyses were performed with labeled standards at these concentrations. In most cases 100 fmol/μg of soy digest was appropriate. AQUA™ internal standard peptides were also analyzed for their linearity of response using a twofold dilution series from 2 pmol/injection down to 0.061 fmol/injection. This dilution was performed using total soy protein digest material at 200 ng/μL (typical endogenous peptide concentrations). All peptides, endogenous and AQUA™, were used within their linear ranges.
Technical variation was quantified by coefficient of variation (%CV). The %CV for a single variable (i.e., soybean allergen) aims to describe the measurement dispersion of the variable in a way that does not depend on the variable’s measurement unit. The higher the %CV is, the greater the measurement dispersion is in the variable. For each soybean allergen, %CV was calculated for each cultivar in each site using the following formula:
where %CV
For a given variable, genotypic variation and environmental variation were quantified relative to residual variation using ANOVA-based
where
A PCA analysis was conducted to explore the patterns of multivariate data and a biplot (Gabriel,
Small technical variation was observed for Glycinin G1, Glycinin G2, and KTI 1 with an average %CV less than 10 and a majority of %CV values being 5–15. Medium technical variation was observed for Beta conglycinin α subunit, Gly m Bd 28k, Glycinin G3, Glycinin G4, and KTI 3 with average %CV of less than 15 and a majority of the %CV values being 5–25.
Genotypic and environmental variation assessed using %CV are shown in Figure
Variable | Effect | NumDF | DenDF | ProbF | |
---|---|---|---|---|---|
Glycinin G1 | Site | 5 | 15 | 12.88 | <0.0001 |
Glycinin G1 | Cultivar | 3 | 15 | 5.61 | 0.0088 |
Glycinin G2 | Site | 5 | 15 | 22.67 | <0.0001 |
Glycinin G2 | Cultivar | 3 | 15 | 1.39 | 0.2850 |
Glycinin G3 | Site | 5 | 15 | 26.72 | <0.0001 |
Glycinin G3 | Cultivar | 3 | 15 | 6.62 | 0.0046 |
Glycinin G4 | Site | 5 | 15 | 18.07 | <0.0001 |
Glycinin G4 | Cultivar | 3 | 15 | 6.11 | 0.0063 |
Beta conglycinin alpha | Site | 5 | 15 | 15.38 | <0.0001 |
Beta conglycinin alpha | Cultivar | 3 | 15 | 0.92 | 0.4558 |
KTI 1 | Site | 5 | 15 | 9.67 | 0.0003 |
KTI 1 | Cultivar | 3 | 15 | 61.57 | <0.0001 |
KTI 3 | Site | 5 | 15 | 70.54 | <0.0001 |
KTI 3 | Cultivar | 3 | 15 | 6.00 | 0.0068 |
Gly m Bd 28k | Site | 5 | 15 | 19.07 | <0.0001 |
Gly m Bd 28k | Cultivar | 3 | 15 | 4.47 | 0.0197 |
The levels of Glycinin G1 and G2 were affected by the environment and to a lesser extent by the cultivar (Table
The levels of Glycinin G4 were affected by the environment (Table
The total allergen content was similar between Ontario, Georgia, Nebraska, and Iowa (Figure
The following can be seen from Figure
In this study, eight allergens were quantified in 24 samples with each sample measured four times. In order to perform this ambitious study we addressed the individual seed variability by taking large samplings to average this component. This was performed using standard procedure for random sampling of material from test plots. It should also be noted that subsequent quantification was performed on single representative AQUA™ peptides as explained in the Section
Once protein was extracted, processing from protein dissolution to calculations for absolute quantity took approximately 6 days, with an average percent coefficient of variance for the experiment at 10.0%. In order to achieve this rapid turnover, some assumptions had to be made. Firstly, we assumed that replicate injections could be forgone if replicate extractions were performed for each sample. The experimental design employed replicate extractions to assess variation at the protein extraction level. Assuming that the variation at the extraction level was greater than the variation at the injection level (largely controlled for with AQUA™ peptides, and previously assessed at 3–5%), we were satisfied that we were accounting for the majority of experimental variation by comparing replicate extractions without replicate injections. Secondly, we assumed that single point quantification can accurately assess peptide abundance. For our quantification experiments, protein quantities were calculated based on a single simultaneous measurement of both AQUA™ and endogenous peptide intensities. Ideally, the analysis would be repeated for each sample using a dilution strategy, where the AQUA™ peptide or the endogenous matrix is diluted and subsequent measurements are made of these samples to assess the linearity of response. To avoid this necessity, we assessed the linearity of our endogenous peptides with a twofold dilution series from 2.0 to 0.0625 μg/injection (2.0 μg maximum capacity peptide traps) of a Williams 82 soybean protein sample using a constant amount of AQUA™ peptide for all dilutions. The ratio of endogenous: AQUA™ peak areas were used to assess linearity. The scatter plot of “measured fold change” versus “actual fold change” shows slopes that on average are within 5.70 ± 3.82% of the optimal value of 1, with an average
Lastly, our strategy assumed that monitoring one proteotypic peptide is sufficient to represent the whole protein. This assumption is mostly an assumption of complete protein digestion. Although digestion conditions were monitored by Coomassie SDS-PAGE to ensure all proteins were digested to peptides, this approach is not as quantitative as MRM. Ideally, if a protein is subjected to proteolysis using trypsin, the entire protein will be reduced to peptides by cleavage at all Lys and Arg residues. However, this is not necessarily the case. Studies have shown that a number of exceptions exist, which prevent cleavage, or prevent complete cleavage. For example, trypsin was perceived to not cleave at a Lys or Arg when a Pro immediately follows it (Keil,
It has been shown that 50–70% of total seed protein is contributed by the storage proteins glycinin and β-conglycinin with their individual percentages varying drastically between studies (Wolf et al.,
Quantitation of the β-conglycinin fraction was by far the most incomplete which is largely because peptides for β-conglycinin subunits α′ and β were not analyzed in this study, thereby vastly under-representing the β-conglycinin fraction. Secondly, the peptide used for β-conglycinin α may be under represented due to the presence of an “illegitimate” cleavage site (Keil,
The levels of allergens have been previously reported to vary between non-GM varieties. For example, in a study of non-GM soybean varieties involving skin reactivity and
These examples give an indication of variation in the allergen levels of various non-GM soybean brought about by breeding. Further research is needed to establish a “baseline” of allergen levels from a composite of both the genetic and even broader environmental factors. Toward this goal, we report here a comparison of genetic versus environmental variation in the expression of eight soybean allergens. While the genetic variation in this study was limited (i.e., early, edible ancestors of soybean were not studied), the environmental component was vast – spanning three agriculturally relevant climate zones (4–6) covering a large range of North America. The results indicate a greater influence of environment on allergen variation, although this was dependent upon the allergen in question, suggesting that protein function is the determining factor in a “genetic versus environmental” discussion. At this point in time, it is apparent that currently one cannot simply speculate or predict how allergens will respond to either a changing genetic background or environment.
While scientifically interesting, this does not directly address the concerns of regulatory safety. The current human health safety evaluation of GM food crops involves an evaluation of endogenous allergen levels using serum IgE screening when its’ non-GM equivalent is a commonly allergenic food (e.g., soybean; Holzhauser et al.,
Severin E. Stevenson, Carlotta A. Woods, and Jay J. Thelen claim no conflicts of interest. Gregory Ladics, Bonnie Hong, and Xiaoxiao Kong are employed by Pioneer Hi-Bred, a DuPont Business that makes GM crops.
Nomenclature |
Peptide information |
Protein information |
|||||
---|---|---|---|---|---|---|---|
ID no. | Peptide name | Protein represented | Peptide sequence | Calculated (Da) | Observed (Th) | Glyma no. | Protein MW (g/mol)monoisotopic (M+H)1+ |
SA2 | GlyG1-2 | G1 subunit (Bx) | VLIVPQNFVVAAR | 1425.857604 | 713.4 | Glyma03g32030.1 | 55671.6 |
SA4 | GlyG2-2 | G2 subunit (A2) | NLQGENEEEDSGAIVTVK | 1931.919212 | 966.5 | Glyma03g32020.1, Glyma03g32020.2 | 54356.887636, 41045.114403 |
SA6 | GlyG3-2 | G3 subunit (A) | FYLAGNQEQEFLQYQPQK | 2231.076708 | 1116.0 | Glyma19g34780.1 | 54207.863911 |
SA7 | GlyG4 | G4 subunit (A5) | VESEGGLIQTWNSQHPELK | 2152.066872 | 718.0 | Glyma10g04280.1 | 63758.458975 |
SA10 | Bcon α | Alpha subunit | LITLAIPVNKPGR | 1391.873253 | 464.6 | Glyma20g28650.1, Glyma20g28650.2, Glyma20g28660.1 | 70263.437646, 63248.763394, 70263.437646 |
SA11 | KTI 3-1 | KTI 3 | FIAEGHPLSLK | 1211.678251 | 404.6 | Glyma08g45530.1 | 14517.404983 |
SA13 | KTI 1 | KTI 1 | DTVDGWFNIER | 1351.627676 | 676.3 | Glyma01g10900.1 | 22432.404593 |
SA14 | AllGly28 | 28 kDa | DGPLEFFGFSTSAR | 1530.7223 | 765.9 | Glyma11g15870.1 | 52882.740099 |
Precursor (Th) | Precursor charge | Product (Th) | Product charge | Ion type | |
---|---|---|---|---|---|
NLQGENEEEDSGAIVTVK | 966.4632 | 2 | 1390.669 | 1 | y13 |
NLQGENEEEDSGAIVTVK | 966.4632 | 2 | 1276.626 | 1 | y12 |
NLQGENEEEDSGAIVTVK | 966.4632 | 2 | 1147.584 | 1 | y11 |
NLQGENEEEDSGAIVTVK | 966.4632 | 2 | 1018.541 | 1 | y10 |
NLQGENEEEDSGAIVTVK | 966.4632 | 2 | 889.4984 | 1 | y9 |
NLQGENEEEDSGAIVTVK[HeavyK] | 970.4703 | 2 | 1398.683 | 1 | y13 |
NLQGENEEEDSGAIVTVK[HeavyK] | 970.4703 | 2 | 1284.64 | 1 | y12 |
NLQGENEEEDSGAIVTVK[HeavyK] | 970.4703 | 2 | 1155.598 | 1 | y11 |
NLQGENEEEDSGAIVTVK[HeavyK] | 970.4703 | 2 | 1026.555 | 1 | y10 |
NLQGENEEEDSGAIVTVK[HeavyK] | 970.4703 | 2 | 897.5126 | 1 | y9 |
FIAEGHPLSLK | 404.5642 | 3 | 460.3124 | 1 | y4 |
FIAEGHPLSLK | 404.5642 | 3 | 557.3652 | 1 | y5 |
FIAEGHPLSLK | 404.5642 | 3 | 694.4241 | 1 | y6 |
FIAEGHPLSLK | 404.5642 | 3 | 751.4456 | 1 | y7 |
FIAEGHPLSLK | 404.5642 | 3 | 880.4882 | 1 | y8 |
FIAEGHPLSLK | 404.5642 | 3 | 951.5253 | 1 | y9 |
FIAEGHPLSLK[HeavyK] | 407.2356 | 3 | 468.3266 | 1 | y4 |
FIAEGHPLSLK[HeavyK] | 407.2356 | 3 | 565.3794 | 1 | y5 |
FIAEGHPLSLK[HeavyK] | 407.2356 | 3 | 702.4383 | 1 | y6 |
FIAEGHPLSLK[HeavyK] | 407.2356 | 3 | 759.4598 | 1 | y7 |
FIAEGHPLSLK[HeavyK] | 407.2356 | 3 | 888.5023 | 1 | y8 |
FIAEGHPLSLK[HeavyK] | 407.2356 | 3 | 959.5394 | 1 | y9 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 854.444 | 2 | y15 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 962.4813 | 2 | y17 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 486.2917 | 1 | y4 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 1367.67 | 1 | y11 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 1239.611 | 1 | y10 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 1138.563 | 1 | y9 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 740.8805 | 2 | y12 |
VESEGGLIQTWNSQHPELK | 718.0271 | 3 | 445.1924 | 1 | b3 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 858.4511 | 2 | y15 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 966.4884 | 2 | y17 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 494.3059 | 1 | y4 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 1375.684 | 1 | y11 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 1247.625 | 1 | y10 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 1146.578 | 1 | y9 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 744.8876 | 2 | y12 |
VESEGGLIQTWNSQHPELK[HeavyK] | 720.6985 | 3 | 445.1924 | 1 | b3 |
LITLAIPVNKPGR | 464.6292 | 3 | 457.2876 | 1 | y4 |
LITLAIPVNKPGR | 464.6292 | 3 | 571.3305 | 1 | y5 |
LITLAIPVNKPGR | 464.6292 | 3 | 670.3989 | 1 | y6 |
LITLAIPVNKPGR | 464.6292 | 3 | 767.4517 | 1 | y7 |
LITLAIPVNKPGR | 464.6292 | 3 | 880.5358 | 1 | y8 |
LITLAIPVNKPGR | 464.6292 | 3 | 951.5729 | 1 | y9 |
LITLAIPVNKPGR | 464.6292 | 3 | 1064.657 | 1 | y10 |
LITLAIPVNKPGR | 464.6292 | 3 | 1165.705 | 1 | y11 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 467.2959 | 1 | y4 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 581.3388 | 1 | y5 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 680.4072 | 1 | y6 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 777.46 | 1 | y7 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 890.544 | 1 | y8 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 961.5811 | 1 | y9 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 1074.665 | 1 | y10 |
LITLAIPVNKPGR[HeavyR] | 467.9653 | 3 | 1175.713 | 1 | y11 |
FYLAGNQEQEFLQYQPQK | 1116.042 | 2 | 663.3455 | 1 | y5 |
FYLAGNQEQEFLQYQPQK | 1116.042 | 2 | 791.4041 | 1 | y6 |
FYLAGNQEQEFLQYQPQK | 1116.042 | 2 | 904.4882 | 1 | y7 |
FYLAGNQEQEFLQYQPQK | 1116.042 | 2 | 1051.557 | 1 | y8 |
FYLAGNQEQEFLQYQPQK | 1116.042 | 2 | 1180.599 | 1 | y9 |
FYLAGNQEQEFLQYQPQK | 1116.042 | 2 | 372.2236 | 1 | y3 |
FYLAGNQEQEFLQYQPQK[HeavyK] | 1120.0491 | 2 | 671.3597 | 1 | y5 |
FYLAGNQEQEFLQYQPQK[HeavyK] | 1120.0491 | 2 | 799.4183 | 1 | y6 |
FYLAGNQEQEFLQYQPQK[HeavyK] | 1120.0491 | 2 | 912.5023 | 1 | y7 |
FYLAGNQEQEFLQYQPQK[HeavyK] | 1120.0491 | 2 | 1059.571 | 1 | y8 |
FYLAGNQEQEFLQYQPQK[HeavyK] | 1120.0491 | 2 | 1188.613 | 1 | y9 |
FYLAGNQEQEFLQYQPQK[HeavyK] | 1120.0491 | 2 | 380.2378 | 1 | y3 |
VLIVPQNFVVAAR | 713.4324 | 2 | 425.3117 | 1 | b3 |
VLIVPQNFVVAAR | 713.4324 | 2 | 501.2797 | 2 | y9 |
VLIVPQNFVVAAR | 713.4324 | 2 | 1001.552 | 1 | y9 |
VLIVPQNFVVAAR | 713.4324 | 2 | 326.2433 | 1 | b2 |
VLIVPQNFVVAAR | 713.4324 | 2 | 904.4994 | 1 | y8 |
VLIVPQNFVVAAR | 713.4324 | 2 | 1100.621 | 1 | y10 |
VLIVPQNFVVAAR | 713.4324 | 2 | 776.4408 | 1 | y7 |
VLIVPQNFVVAAR[HeavyR] | 718.4365 | 2 | 425.3117 | 1 | b3 |
VLIVPQNFVVAAR[HeavyR] | 718.4365 | 2 | 506.2838 | 2 | y9 |
VLIVPQNFVVAAR[HeavyR] | 718.4365 | 2 | 1011.56 | 1 | y9 |
VLIVPQNFVVAAR[HeavyR] | 718.4365 | 2 | 326.2433 | 1 | b2 |
VLIVPQNFVVAAR[HeavyR] | 718.4365 | 2 | 914.5076 | 1 | y8 |
VLIVPQNFVVAAR[HeavyR] | 718.4365 | 2 | 1110.629 | 1 | y10 |
VLIVPQNFVVAAR[HeavyR] | 718.4365 | 2 | 786.4491 | 1 | y7 |
DTVDGWFNIER | 676.3174 | 2 | 531.288 | 1 | y4 |
DTVDGWFNIER | 676.3174 | 2 | 921.4572 | 1 | y7 |
DTVDGWFNIER | 676.3174 | 2 | 678.3564 | 1 | y5 |
DTVDGWFNIER | 676.3174 | 2 | 1036.484 | 1 | y8 |
DTVDGWFNIER | 676.3174 | 2 | 864.4357 | 1 | y6 |
DTVDGWFNIER[HeavyR] | 681.3216 | 2 | 541.2963 | 1 | y4 |
DTVDGWFNIER[HeavyR] | 681.3216 | 2 | 931.4655 | 1 | y7 |
DTVDGWFNIER[HeavyR] | 681.3216 | 2 | 688.3647 | 1 | y5 |
DTVDGWFNIER[HeavyR] | 681.3216 | 2 | 1046.492 | 1 | y8 |
DTVDGWFNIER[HeavyR] | 681.3216 | 2 | 874.444 | 1 | y6 |
DGPLEFFGFSTSAR | 765.8648 | 2 | 1148.536 | 1 | y10 |
DGPLEFFGFSTSAR | 765.8648 | 2 | 1019.494 | 1 | y9 |
DGPLEFFGFSTSAR | 765.8648 | 2 | 872.4255 | 1 | y8 |
DGPLEFFGFSTSAR | 765.8648 | 2 | 725.3571 | 1 | y7 |
DGPLEFFGFSTSAR | 765.8648 | 2 | 1415.695 | 1 | y13 |
DGPLEFFGFSTSAR | 765.8648 | 2 | 1358.673 | 1 | y12 |
DGPLEFFGFSTSAR | 765.8648 | 2 | 1261.621 | 1 | y11 |
DGPLEFFGFSTSAR[HeavyR] | 770.8689 | 2 | 1158.545 | 1 | y10 |
DGPLEFFGFSTSAR[HeavyR] | 770.8689 | 2 | 1029.502 | 1 | y9 |
DGPLEFFGFSTSAR[HeavyR] | 770.8689 | 2 | 882.4338 | 1 | y8 |
DGPLEFFGFSTSAR[HeavyR] | 770.8689 | 2 | 735.3654 | 1 | y7 |
DGPLEFFGFSTSAR[HeavyR] | 770.8689 | 2 | 1425.703 | 1 | y13 |
DGPLEFFGFSTSAR[HeavyR] | 770.8689 | 2 | 1368.682 | 1 | y12 |
DGPLEFFGFSTSAR[HeavyR] | 770.8689 | 2 | 1271.629 | 1 | y11 |
We thank Kevin Wright of Pioneer Hi-Bred International for R code to produce PCA biplots.