JIA-2019-11

2581 CUI Dong-nan et al. Journal of Integrative Agriculture 2019, 18(11): 2579–2588 monitored daily for neonate emergence in both photoperiod treatment groups. We counted the total number of hatchlings (D1) and unhatched eggs (D2) to calculate the diapause rate of locust eggs by the following formula: Diapause rate (%)=D2/(D1+D2)×100 2.5. Label-free quantification Three independent biological replicates were prepared in each treatment with 60 eggs per replicate. The egg samples were homogenized by lysis buffer that was composed of lysogeny broth, 8 mol L –1 urea, 2 mol L –1 thiourea, 4% CHAPS, 20 mmol L –1 Tris-base, 30 mmol L –1 dithiothreitol (DTT), and 2%Biolyte, pH 3−10. The sample was sonicated for 20 s every 5 min for a total of 30 min while on ice. Then it was centrifuged at 1 200×g for 10 min at 4°C and further centrifuged at 15 000×g for 10 min at 4°C. We added three volumes of acetone to the supernatant in order to precipitate proteins and desalt the sample. Next, the mixture was centrifuged two times at 15 000×g for 10 min. The supernatant was removed and the pellet was dissolved using lysogeny broth. After 5 min of incubation at 4°C, the sample was sonicated for 2 min. Protein concentrations were quantified by the Bradford method (Bradford 1976). LC−MS/MS analysis, identification and label-free quantitation of proteins were carried out as described previously (Han 2017). The fold change of proteins between the two photoperiod treatments was calculated by the ratio of diapause to non-diapause group means. 2.6. Bioinformatics analyses Gene-set enrichment was completed by KOBAS 3.0 (Xie et al. 2011). To enrich the identified proteins involved in the canonical pathway, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used. The GO database was used to facilitate the biological interpretation of the identified proteins in this study. GO enrichment analysis was carried out as described previously (Tu et al. 2015). 2.7. Quantitative real-time PCR (qRT-PCR) To further investigate the diapause mechanism at the gene level, total RNA was extracted from non-diapause and diapause eggs using a Quick-RNA™ MicroPrep Kit (Zymo, USA) according to the manufacturer’s instructions. Total RNA quantification was performed by a Nano Photometer (Implen, BRD) and the quality of RNAwas evaluated by 1.0% denaturing agarose gel electrophoresis and compared to the bands of the 28S and 18S rRNA. Reverse transcription was performed using a 5× All-In-One RT MasterMix Kit (ABM, Canada ) according to the manufacturer’s instructions. The mRNA levels of four important proteins, hexamerin- like protein 4, JHEH1, cytochrome P450, and heat shock protein (HSP) 20.7 were checked. qRT-PCR was performed with the SYBR Premix Ex Taq (TaKaRa, Japan) on the ABI 7500 Real-Time PCR System (ABI, USA). The actin gene was used as a reference control. Each plate was repeated four times in independent runs for all reference and selected genes. Gene expression was evaluated by the 2 –ΔΔC T method. The primers used in this paper are shown in Table 1. 2.8. Statistical analysis The differences in diapause rates and mRNA levels of four proteins were tested for statistical significances by independent sample t -test where P <0.05 was the threshold of significance. Results were expressed as mean±SE. Statistical analyses were performed using SPSS16.0 Software. 3. Results 3.1. Diapause rate The data showed that the long photoperiod regime produced virtually 100% non-diapause eggs, whereas the short photoperiod regime produced approximately 85% diapause and 15% non-diapause eggs (Fig. 1). Although samples from the diapause group contained a moderate number of non-diapause eggs, the high percentage of diapause eggs in these samples (~85%) still allowed us to identify differentially expressed proteins (DEPs) between the two groups during molecular analyses. 3.2. Identification of DEPs between non-diapause eggs and diapause eggs The total number of sequences identified by mass spectrometry of locust egg proteomes was 1 090. Among Table 1 Primers used in this study Genes Primers (5´→3´) Hexamerin-like protein 4-F CATCACAGCCAACTACACGG Hexamerin-like protein 4-R AACATCTGCCTGAGGGAGTG JHEH1-F CTCGGGCACAGCAAGTTCTA JHEH1-R CAGCAGTATGAGATTGAGCCAA Cytochrome P450-F CATTGCTCCTGAACTCTCTG Cytochrome P450-R GACTTGCTGGTTGTTTCTGAG HSP20.7-F CAGCCACAGTTCCTTTACTTTC HSP20.7-R TGCTTCCCTTCAATAACGAC Actin-F GTTACAAACTGGGACGACAT Actin-R AGAAAGCACAGCCTGAATAG