JIA-2019-11

2459 XU Bing-qin et al. Journal of Integrative Agriculture 2019, 18(11): 2457–2471 2.2. Analyzing the contents of RWC, MDA, proline, soluble sugar, and ABA level measurement of seedling leaves Foxtail millet leaf RWCs at the three-leaf stage were measured according to the protocols of Bingham (1974) and Lafitte (2002). The degree of lipid peroxidation can be estimated by the MDA production, which was determined according to the method of Hodges et al . (1999). The proline accumulation in leaves was measured using the ninhydrin method described by Bates et al . (1973). Total soluble sugar contents in leaves were determined spectrophotometrically using the protocol reported by Farhad et al . (2011). The quantitative determination of ABA and jasmonic acid (JA) in foxtail millet leaves used the ABA ELISA Quantification Kit (Agrisera, Sweden) and Plant JA ELISA Kit (J&L Biological, China) according the manufacturers’ instructions. 2.3. RNA-seq library preparation The 3 g fresh leaf samples collected after PEG 6000 treatment at 0 and 24 h (samples DM-1, DM-2, HN-1, and HN-2), with three biological replicates per cultivar, were used for t otal RNA extraction using a Sangon Biotech UNIQ-10 column Trizol Total RNA Isolation Kit (Sangon Biotech Co., Ltd., China) following manufacturer’s instructions. RNA quality was assessed using a 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA). A total of 10 μg of total RNA from each sample was used to build Illumina RNA- seq libraries to isolate poly(A) mRNA. RNA-seq libraries were sequenced with 150-bp paired-end sequencing on an Illumina HiSeq-TM 4000 System (Illumina Inc., San Diego, CA, USA) following the manufacturer’s protocol. 2.4. Mapping sequence reads to the reference genome The raw sequence data were filtered to remove the adaptor sequences, and low quality bases with more than 10% anonymous nucleotides (N) and more than 50% of bases possessing a value Q≤20 with Sickle (https://github.com/ najoshi/sickle). Clean reads were mapped to the foxtail millet reference genome (https://www.ncbi.nlm.nih.gov/ genome/?term=Setaria_italica) using the mapping software TopHat 2.1.1 (Kim et al . 2013) and assembled by Cufflinks (Trapnell et al . 2010). 2.5. Gene Ontology (GO) analysis of RNA-seq data and gene expression evaluation The gene expression level was calculated by the fragments per kilobase of transcript per million mapped reads (FPKM) method (Mortazavi et al . 2008). Differentially expressed genes (DEGs) were identified using EdgeR (version 3.0.0, Rversion 2.1.5), with an false discovery rate (FDR)≤0.05 and an absolute value of the log 2 ratio≥1. GO annotation was obtained for each differentially expressed genes (DEGs), using the web-based Agrico tool (Du et al . 2010). Their function categories were assigned based on KEGG3, Uniprot2, and the Cluster of Orthologous Groups (COG) databases. 2.6. Quantitative real-time PCR validation The expression levels of 10 selected DEGs were measured by quantitative real-time transcription PCR (qRT-PCR) with the corresponding primers (Appendix A). qRT-PCR was performed using the SYBR Premix Ex Taq II (TaKaRa, China) with the ABI 7500 Real-Time System (Applied Biosystems), as follows: 95°C for 2 min; 95°C for 30 s, 63°C for 30 s, and 40 cycles. The 18S rRNA was used as an internal control for qRT-PCR amplification, and we set all reactions in triplicate. The comparative C t method was used to quantify the expression levels of tested genes (Schefe et al . 2006). 2.7. Statistical analysis The data from the physiological analysis were evaluated by Duncan’s multiple test in the ANOVA Program of SPSS Statistics 22.0 Software (SPSS Inc., Chicago, IL, USA). Each data value was presented as a mean±standard deviation (SD). A P -value of 0.05 is considered to be the borderline of statistical significance. 3. Results 3.1. Physiological changes of leaves in the two cultivars under short-term osmotic stress treatment Relative water content (RWC) is usually considered as a measure of plant water status or cellular water deficit, and its change usually reflects drought resistance of varieties (Han 1990; Regan et al . 1993). In this study, RWCmeasurements were reduced by 2.03% in DM and 3.57% in HN showing that plants had sensed drought after 24 h of drought treatment (Harb et al . 2010). Subsequently, the RWC continued to decrease by 5.65% in DM and 10.76% in HN after 48 h; and by 13.99% in DM and 17.85% in HN after 72 h compared with that of the 0 h control (Fig. 1-A and Appendix B). The rate of decline of RWC in DM is more moderate than it is in HN. Soluble sugar and proline accumulation are the first responses of foxtail millet to drought stress for maintaining