collected at each time point per biological replicate. For chemical analysis, about one hundred milligrams of dry seeds per biological replicate were ground to powder using a mortar and pestle. The seed oil was extracted and analyzed as described by Hara and Radin [79]. After removing the oil using acetone, protein was extracted by a previously described method [80] and quantified by the BCA method [81]. To extract starch, soluble sugars were first eluted from seed flour by 80% ethanol at 70uC. After centrifu- gation, the residual pellet was homogenized in 0.2 mol/L KOH and the suspension was incubated at 95uC for 1 h to dissolve the starch. Following the addition of 1 mol/L acetic acid and centrifugation for 5 min at 16 000 g, the starch content of the supernatant was assayed using the anthrone sulfuric acid method [82]. Assays were performed with three biological replicates. The lipid composition of the samples was analyzed, following FAME derivatization, according to the method described by Li et al. [64], adding C17:0 as an internal standard. For this analysis we used an Agilent 7890A gas chromatograph system equipped with a flame ionization detector (FID) and an HP-88 column (30 m60.25 mm I.D., 0.20 mm film thickness), with chromatog- raphy conditions described by Wu et al. [83], coupled to a GCMS- QP2010 plus mass spectrometer (Shimadzu). The assay was performed with three biological replicates. The significance of between-sample differences in mean contents of the detected FAs was assessed using Student’s t test. Preparation of RNA The seven developmental points were during: the early stage of seed development (histodifferentiation) (S1, 14 DAP; whole seeds), early increase of seed dry-weight stage (S2, 19 DAP; whole seeds), rapid increase of seed coat dry-weight stage (S3, 25 DAP; kernels), early increase of kernel dry-weight stage (S4, 29 DAP; kernels), rapid increase of kernel dry-weight stage (S5, 35 DAP; kernels), late kernel dry-weight increase stage (S6, 41 DAP; kernels), and maturation or desiccation stage (S7, 45 DAP; kernels) (Figure 1A, 1B). Total RNA was extracted from the samples using an RNeasy Plant Mini Kit (QIAGEN; Cat. No. 74904), and the isolated RNA was subsequently treated with RNase-Free DNase I (Roche, http://www.roche.com). Digital Gene Expression Library Preparation and Sequencing Tag libraries of the samples of seeds in the seven developmental stages were prepared in parallel using an Illumina gene expression sample preparation kit and sequenced using the Illumina GAII platform at BGI-Shenzhen without replications (http://en. genomics.cn/navigation/index.action) (Methods S1). A prepro- cessed database of all possible CATG+17 nucleotide tag sequences was created using our genome reference database. Further information on the genomic sequences and the predicted protein-encoding genes is available at ftp:// Jatropha:9uebluesrjd7@ftp.genomics.org.cn and at the NCBI nucleotide database (Project ID: 63485). For annotation, all tags were mapped to the reference sequences, allowing no more than one nucleotide mismatch per tag. All the tags that mapped to reference sequences from multiple genes were filtered and the remaining tags were defined as unambiguous tags. As a result, we generated between 3.26 and 6.18 million raw tags for each of the seven samples (Table S5). After removing the low quality reads, the total number of tags per library ranged from 3.03 to 6.07 million and the number of tag entities with unique nucleotide sequences ranged from 83,820 to 167,765 (Table S5). For gene expression analysis, the number of expressed tags was calculated Gene Expression Profiles in Physic Nut Seeds and then normalized to TPM (number of transcripts per million tags) [27]. A 363 self-organizing map (SOM) of the gene expression data was constructed using GeneCluster 2.0 [84] (http://www. broadinstitute.org/cancer/software/genecluster2/gc2.html) with a variation filter (Max/Min$5) to eliminate genes whose expression did not change significantly across samples, and normalization of the means and variance (mean = 0 and variance = 1). The SOM algorithm was executed with the desired cluster range of 3–9 and the rest of the parameters left unchanged. They are 50000 iterations, seed range of 42, initialization of centroids to random vectors, bubble neighborhood, initial and final learning weights of.1 and .005, and initial and final sigmas determining the size of the update neighborhood of a centroid set to 5 and .5, respectively. Supporting Information Figure S1 Expression profiles of sucrose absorption and transporter genes. Frc, fructose; Glc, glucose; GPT, Glc- 6-P/phosphate translocator; INV, invertase; PEP, phosphoenol- pyruvate; 3-PGA, -phosphoglycerate; PLT, polyol transporter; PPT, phosphoenolpyruvate/phosphate translocator; STP, sugar transport protein; Suc, sucrose; SuSy, sucrose synthase; SUT, sucrose transporter; TPT, triose phosphate/phosphate transloca- tor; XPT, xylulose 5-phosphate/phosphate translocator; Xu-5-P, xylulose 5-phosphate. (TIF) Figure S2 Expression profiles of central metabolism- related genes. 1,3-BPG, 1,3-bisphosphoglycerate; DHAP, dihydroxyacetone-3-phosphate; E-4-P, erythrose-4-phosphate; Frc, fructose; GAP, glyceraldehyde-3-phosphate; Glc, glucose; 6- PG, 6-phosphogluconate; OAA, oxaloacetic acid; 6-PGL, 6- phosphogluconolactone; PEP, phosphoenolpyruvate; 2-PGA, 2- phosphoglycerate; 3-PGA, 3-phosphoglycerate; R-5-P, ribose-5- phosphate; PRPP, ribulose-1,5-bisphosphate; Ru-5-P, ribulose-5- phosphate; S-7-P, sedoheptulose-7-phosphate; UDP-Glc, uridine diphosphoglucose; Xu-5-P, xylulose-5-phosphate. (TIF) Figure S3 Expression profiles of starch metabolism- related genes. AGPL/S, ADP–glucose pyrophosphorylase large subunit/small subunit; AMY, alpha-amylase; BAM, beta-amylase; BE, starch branching enzyme; DPE, disproportionating enzyme; GBSS, granule-bound starch synthase; GWD, glucan water dikinase; ISA, isoamylase; MEX, maltose transporter; PHO, starch phosphorylase; PUL, pullulanase. (TIF) Figure S4 Expression profiles of fatty acid synthesis- related genes. Manual annotation according to acyl lipid metabolism genes in Arabidopsis (http://aralip.plantbiology.msu. edu/pathways and http://lipids.plantbiology.msu.edu/maps_list. htm?q = lipids/genesurvey/maps_list.htm). ACP, acyl carrier pro- tein; BC, biotin carboxylase; BCCP, biotin carboxyl carrier protein; CT, carboxyltransferase; ER, enoyl-ACP reductase; FATA, acyl-ACP thioesterase A; FATB, acyl-ACP thioesterase B; HAD, hydroxyacyl-ACP dehydrase; HDLAP, dihydrolipoa- mide acetyltransferase of PDHC; HOM-ACCase, homomeric acetyl-CoA carboxylase (ACCase); KAR, ketoacyl-ACP reductase; KAS, ketoacyl-ACP synthase; LPD, dihydrolipoamide dehydro- genase; MCMT, malonyl-CoA: ACP malonyltransferase; PDHC, pyruvate dehydrogenase complex; SAD, stearoyl-ACP desaturase. (TIF) PLoS ONE | www.plosone.org 10 May 2012 | Volume 7 | Issue 5 | e36522