Pacbio Library Construction And Single-molecule Sequencing
Garlic samples at DS0 and DS3 were selected for single-molecule sequencing. SMRT libraries were prepared according to the Isoform Sequencing protocol (Iso-Seq™). First, equal amounts of RNA (1 µg per sample) from 6 single plants were pooled together and 3 µg was used for reverse transcription (RT) using a Clontech SMARTer cDNA synthesis kit. Second, the optimal amplification cycle number was utilized to generate large-scale double-strand cDNA. Third, after dsDNA was obtained, a BluePippin System was used to select the DNA size for subsequent re-amplification. Finally, three libraries (1–2, 2–3, and 3–6 kb) generated by the products were subjected to an Iso-Seq SMRTBell library preparation (https://pacbio.secure.force.com/SamplePrep). Three libraries were sequenced on the PacBio RSII platform using P5-C3 chemistry.
Data analysis of PacBio sequencing reads
The sequence data was analyzed using SMRT analysis software (www.pacb.com/products-and-services/analytical-software/devnet/). Circular consensus sequence (CCS) reads were generated by using the following parameters: min_predicted_accuracy, 0.8; max_length, 15000; min_length, 50; min_passes, 0; max_drop_fraction, 0.8. According to the parameter minSeqLength 100, CCS reads were classified into full-length and non-full-length sequences. Non-redundant sequences were obtained using CD-HIT software (31), which were identified as transcripts. The coding domains (CDs) of the full-length transcript were predicted by TransDecoder software, and a total of 36,776 transcripts with protein-encoding functions were obtained. The CDs were subjected to functional annotation by searching against six public databases, including eukaryotic ortholog groups (KOG), National Center for Biotechnology Information (NCBI) non-redundant (NR) protein sequences, Kyoto Encyclopedia of Genes and Genomes ortholog (KEGG), Swiss-Prot protein, Gene Ontology (GO), and protein family (PFAM) databases.
Illumina RNA-sequencing library construction
The total RNA from all garlic samples was subjected to Illumina RNA sequencing individually. The total RNA from all garlic samples was subjected to Illumina RNA sequencing individually. Firstly, the purified RNA was randomly broken into short fragments using fragmentation buffer to construct cDNA libraries. Second, the short-fragmented RNA was used as a template to synthesize single-stranded cDNA with six-base random primers (Random hexamers), which generates double-stranded cDNA in the presence of buffer, dNTPs, RNaseH and DNA Polymerase I. Finally, after adapter was added to purified double-stranded cDNA, PCR amplification was performed to obtain the final sequencing library.
Expression level analysis of genes
The expression of each gene in all garlic samples was quantified in Bowtie2 (32) using the transcriptome generated by PacBio sequencing as reference transcriptome. To analyze the expression level of each gene in all samples, RSEM (33) was performed to estimate the expected number of fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM).
Protein extraction and quantification
Proteins from all garlic samples were extracted using cell lysis buffer (P0013), which contains 20 mM Tris (pH 7.5), 150 mM NaCl, 1% Triton X-100, and various inhibitors such as sodium pyrophosphate, EDTA and β-glycerophosphate. The protein in all garlic samples was quantified using label-free quantitation, in which the relative content of a corresponding protein was obtained using MaxQuant software to analyze quantitative information of peptides generated by LC-MS detection. Differentially abundant proteins (DAPs) were generated using Perseus software (34).
Extraction of green pigment from garlic
(1) Garlic peeled, crushed (2) added 2% citric acid (3) 80 °C water bath heated for 30 min (4) methanol leached (5) filtration (anhydrous Na2SO4 dehydration) (6) petroleum ether extraction degreased (7) 35 °C rotary evaporation concentration (8) added 95% Ethanol precipitation protein (9) centrifugation (10) suction filtration (11) rotary evaporation to remove some solvent (12) crude extraction concentrate.
Garlic green intensity definition and detection method
A Total of 20.00 g garlic bulb was weighed, then mashed after germination. 2% citric acid was added then the sample was stirred evenly and heated at 80 °C in a water bath for 30 min, then cooled to room temperature. Samples were then made up to 50 mL with 95% ethanol, and the leaching was performed for 24 h at 4 °C. The supernatant was measured for absorbance A at 440 nm and 590 nm after filtration. Definition of green intensity: Green intensity = A590(440) × 10.
Treatment of garlic with sodium azide
A total of 1 g garlic bulb was weighed and soaked in sodium azide solution at a concentration of 0.1 mol/L or 0.5 mol/L for 24 h at room temperature. Garlic was also soaked in deionized water as a control. After draining, samples were stored at 4 °C, and the green intensity of garlic was measured at DS0, DS1, DS2 and DS3.
Effect of salicylic acid on the greening of garlic
Equal sizes of garlic were picked, adding different concentrations of salicylic acid (SA) according to the quality of garlic after peeling and slicing. Garlic extracts without salicylic acid were used as a control. The green intensity of the garlic was measured after treatment with different concentrations of salicylic acid.
The pyrrolyl compound porphobilinogen (PBG) content detection
Total 1.00 g germinated garlic bulbs as added to 5 mL of phosphate buffer pH 6.8, and the mixture was centrifuged at 12000 r/min for 10 min. The supernatant was added to Ehrlich's reagent for color development, and the absorbance was measured at 553 nm.
Method for determining organic acid content
Organic acid extraction: 1.00 g of garlic bulb was added to 2 mL of deionized water then ground to a slurry of germinated garlic bulbs. 3 mL deionized water was used to wash the sample into a centrifuge tube before centrifugation at 9000r/min for 30 min. The supernatant was filtered through a microporous membrane (0.45 Μm) before the determination of organic acids in the TCA cycle.
Detection method: UV detector, Alltiman C18 Column (250 mm × 4.6 mm, 5 µm) column, flow rate: 0.4 mL/min, injection volume: 20 µL, detection wavelength: 214 nm, column temperature: 30 °C, mobile phase: 5% methanol 0.01 mol/L H3PO4-KH2PO4 buffer (pH = 2.35).
Construction of a weighted gene co-expression network
After the data was standardized or processed accordingly, weighted gene co-expression network analysis (WGCNA) was performed (35). First, in order to ensure the results of weighted gene co-expression network construction were reliable, all samples were clustered and outlier samples were filtered. Second, the soft threshold power (soft power) in accordance with standard scale-free networks was selected, by which the adjacencies between genes of all samples were calculated by a power function. Then, the adjacency was transformed into a topological overlap matrix (TOM), and the corresponding dissimilarity (1-TOM) was calculated and the scale-free topology network was constructed from the dissimilarity values. Gene modules in the resulting networks were accomplished with the dynamic tree cut method (http://www.coxdocs.org/doku.php?id=perseus:start).
GO term and KEGG pathway enrichment analyses
Gene Ontology (GO, www.geneontology.org) is an international standard classification system for gene function. It facilitates study of the distribution of genes in Gene Ontology groups and elucidation of the functional representation of genes in different modules. The analysis method of GO enrichment was top GO and the GO term enrichment p-values were calculated using the Fisher's exact test in the TopGO R package (http://www.bioconductor.org/packages/release/bioc/html/topGO.html).
Different genes in vivo coordinate with each other to perform their biological function, and KEGG pathway analysis helps to further understand the biological functions of genes. KEGG is the main public database for pathways. A pathway's significant enrichment analysis uses KEGG Pathway as a unit to apply hypergeometric tests to find a pathway that is significantly enriched in significant differentially expressed genes compared to the entire genomic background (36).
N is the total number of genes and n is the number of differentially expressed genes in N. M is the number of genes annotated as a particular Pathway and m is the number of differentially expressed genes annotated as a particular Pathway.