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Blood, Vol. 109, Issue 8, 3260-3269, April 15, 2007
Comparative gene expression profiling of in vitro differentiated megakaryocytes and erythroblasts identifies novel activatory and inhibitory platelet membrane proteins
Blood Macaulay et al.
109: 3260
Supplemental materials for: Macaulay et al, Vol 109, Issue 8, 3260-3269
Files in this Data Supplement:
- Table S1. List of all megakaryocyte–up-regulated transcripts encoding proteins with transmembrane domains (PDF, 68.9 KB)
- Table S2. Microarray results (XLS, 1.72 MB)
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Worksheet 1: microarray results and stats. This sheet contains the list of array features which passed the quality control (QC) step in the analysis of the data, and thus comprises a list of genes which were “present” in MKs and EBs.
Column headers:
ID: WTSI Hver 2.1.1 unique feature identifier
Gene description: description of the gene represented by that microarray feature
Fold change MK/EB: average fold difference between MKs and EBs. Genes up-regulated in the MK have fold changes greater than 2, whereas those up-regulated in EBs have fold changes less than 0.5.
Present (of 20): the number of arrays in which that particular feature passed QC. In total, 20 arrays were hybridized. Only features which passed QC in 11 or more arrays were considered.
Present (%): as above but represented as a percentage
Pval.lme.fdr: We used this statistic to determine whether features were differentially expressed between MKs and EBs. Differentially expressed transcripts have pval.lme.fdr values less than 0.05 (in addition to a fold change less than 2)
Those features which were determined to be differentially expressed by subsequent statistical analysis are color coded. Those up-regulated in EBs are colored red, whereas those up-regulated in the MKs are colored green.
Worksheets 2 and 3: MK– and EB–up-regulated genes
These sheets contain the lists of transcripts which were determined to be differentially expressed between MKs and EBs.
Column headers as above, HGNC and Ensembl Ids have also been added.
In addition, these lists have been compared with data generated in other studies of the platelet and MK transcriptome1,2 and proteome3-7 (for the MK–up-regulated genes) well as erythroid EST libraries (Hembase)8,9 and a study of the red blood cell proteome10 (for the EB–up-regulated genes).
REFERENCES
1. Gnatenko DV, Dunn JJ, McCorkle SR, Weissmann D, Perrotta PL, Bahou WF. Transcript profiling of human platelets using microarray and serial analysis of gene expression. Blood. 2003;101:2285-2293.
2. Tenedini E, Fagioli ME, Vianelli N, et al. Gene expression profiling of normal and malignant CD34-derived megakaryocytic cells. Blood. 2004;104:3126-3135.
3. Martens L, Van Damme P, Van Damme J, et al. The human platelet proteome mapped by peptide-centric proteomics: a functional protein profile. Proteomics. 2005;5:3193-3204.
4. Lewandrowski U, Moebius J, Walter U, Sickmann A. Elucidation of N-glycosylation sites on human platelet proteins: a glycoproteomic approach. Mol Cell Proteomics. 2006;5:226-233.
5. Moebius J, Zahedi RP, Lewandrowski U, Berger C, Walter U, Sickmann A. The human platelet membrane proteome reveals several new potential membrane proteins. Mol Cell Proteomics. 2005;4:1754-1761.
6. Garcia A, Prabhakar S, Brock CJ, et al. Extensive analysis of the human platelet proteome by two-dimensional gel electrophoresis and mass spectrometry. Proteomics. 2004;4:656-668.
7. O’Neill EE, Brock CJ, von Kriegsheim AF, et al. Towards complete analysis of the platelet proteome. Proteomics. 2002;2:288-305.
8. Goh SH, Lee YT, Bouffard GG, Miller JL. Hembase: browser and genome portal for hematology and erythroid biology. Nucleic Acids Res. 2004;32:D572-D574.
9. Gubin AN, Njoroge JM, Bouffard GG, Miller JL. Gene expression in proliferating human erythroid cells. Genomics. 1999;59:168-177.
10. Pasini EM, Kirkegaard M, Mortensen P, Lutz HU, Thomas AW, Mann M. In-depth analysis of the membrane and cytosolic proteome of red blood cells. Blood. 2006;108:791-801.
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