SFig. 1

SFig. 1

Labeling efficiency heat map for all observed pyQms scores >= 10 (n=1,971,982). For all peptides

that were identified in a given LC-MS/MS run, all possible 15N labeling efficiencies ranging from 0%

- 99% (in 1% steps) were matched against all MS1 spectra for charge states 1 - 5 using pyQms. A

total number of 35,134,500 possible isotopologues were matched against 321,051 MS1 spectra.

All matches with scores greater than 10 (pyQms M-Score) were counted for every matched

spectrum and isotopoloque. Shown are the results as heat map, labeling efficiency (x-axis) was

binned in 1 % steps, pyQms-score (y-axis) was binned in 0.1 steps and the frequency is illustrated

as the color for each bin.

SFig. 2

Protein mass density plot. Protein molecular masses were determined for proteins, for which a

ratio could be calculated and with a mass below 100 kDa (n=1498). The x-axis represents the

mass in kDa, the y-axis represents the frequency of proteins at a given mass.

SFig. 3

Retention time window length distribution density plot. Shown is the frequency of the length of the

retention time windows in minutes for 6037 peptides before (red) and after the alignment (blue).

Retention time windows are defined by the difference between the latest and the earliest

identification (PEP = 1 % in at least one distance-linkage combination. The grey node labeled with ¦Á

represents the root node. The grey nodes with labels 0.2 - 1.0 illustrate the size frequency

(obCoFreq) relation. Otherwise node labels represent cluster IDs (format: ID-{meta-clustering

iteration}); their content and detailed frequencies can be found in STable 5.

STable 1

Overview

?of

?all

?experiments

?conducted.

?

?

STable 2

High accuracy 15N amino acid masses in .xml format. This is suitable as an input for the X! Tandem

search engine.

STable 3

Protein ratios and standard deviations of all proteins in all performed experiments (log2). Shown

are all single experiments as well as the combined (all three repetitions) ratios of the experiments.

Additionally to the JGI4.3 Augustus 10.2 protein names, JGI3.1 protein names are given if the

peptides could be assigned to these protein models, as well as the following annotations: PFAM,

closest Arabidopsis thaliana TAIR10 BLAST hits, Panther (2) and KEGG (3). For all proteins the

sequence coverage (in percent) for each experiment is given, based on all proteotypic peptides

(number given in next column), which determine the protein ratio. Blank fields indicates missing

ratios in these experiments.

STable 4

BLAST comparison of proteins from communities 3860, 13558 and 12472 to transcriptome studies

(Fig. 5). The table includes all BLAST hits (sheets 1-4) of the used JGI4.3 Augustus 10.2

protein/DNA sequences against older C. reinhardtii genome versions (JGI3.1, JGI4 Augustus 5,

EST library) as well as against the A. thaliana reference proteome (TAIR 10). Further tables show

the mapping of all community proteins to the transcriptome studies, their corresponding regulation

and annotation (sheets 5-9). Additionally the manually curated protein/gene mappings, used for Fig.

5, are provided (sheets 10-13).

STable 5

Legend and information of clusters found by pyGCluster. All clusters found by pyGCluster (1) with

their corresponding ID are listed. A line of + separates each cluster. The identification number of

this cluster (ID) is given in the first line, the size is shown (L) and the frequencies for all used

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