Quantitative proteomic, physiological and biochemical analysis of cotyledon, embryo, leaf and pod reveals the effects of high temperature and humidity stress on seed vigor formation in soybean

Abstract

Background: Soybean developing seed is susceptible to high temperature and humidity (HTH) stress in the field, resulting in vigor reduction. Actually, the HTH in the field during soybean seed growth and development would also stress the whole plant, especially on leaf and pod, which in turn affect seed growth and development as well as vigor formation through nutrient supply and protection. Results: In the present study, using a pair of pre-harvest seed deterioration-sensitive and-resistant cultivars Ningzhen No. 1 and Xiangdou No. 3, the comprehensive effects of HTH stress on seed vigor formation during physiological maturity were investigated by analyzing cotyledon, embryo, leaf, and pod at the levels of protein, ultrastructure, and physiology and biochemistry. There were 247, 179, and 517 differentially abundant proteins (DAPs) identified in cotyledon, embryo, and leaf of cv. Xiangdou No. 3 under HTH stress, while 235, 366, and 479 DAPs were identified in cotyledon, embryo, and leaf of cv. Ningzhen No. 1. Moreover, 120, 144, and 438 DAPs between the two cultivars were identified in cotyledon, embryo, and leaf under HTH stress, respectively. Moreover, 120, 144, and 438 DAPs between the two cultivars were identified in cotyledon, embryo, and leaf under HTH stress, respectively. Most of the DAPs identified were found to be involved in major metabolic pathways and cellular processes, including signal transduction, tricarboxylic acid cycle, fatty acid metabolism, photosynthesis, protein processing, folding and assembly, protein biosynthesis or degradation, plant-pathogen interaction, starch and sucrose metabolism, and oxidative stress response. The HTH stress had less negative effects on metabolic pathways, cell ultrastructure, and physiology and biochemistry in the four organs of Xiangdou No. 3 than in those of Ningzhen No. 1, leading to produce higher vigor seeds in the former.

Comparative Transcriptomics and Proteomics Analyses of Leaves Reveals a Freezing Stress-Responsive Molecular Network in Winter Rapeseed (Brassica rapa L.)

“…The supernatant was centrifuged at 4°C for 15 min at 8,000 × g and used for catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD) activity analysis using Thermo Multiscan FC. The level of lipid peroxidation was evaluated by determining the malondialdehyde (MDA) content according to Wei et al (2020) . The samples were fully ground and extracted in a buffer of 0.67% thiobarbituric acid in 20% trichloroacetic acid (TCA) at 4°C and then centrifuged at 12,000 × g for 20 min.…”

“…The expressions of 12 candidate freezing-responsive genes and proteins were analyzed by qRT-PCR. The qRT-PCR was performed according to the protocol of Wei et al (2020) . All the primers are listed in Supplementary Table S1 .…”

“…Protein extraction was conducted using the method of cold TCA/acetone precipitation according to Wei et al (2020) , with minor modifications. Plant leaves (0.2 g) from four samples containing three biological replicates were ground to powder in liquid nitrogen and then dissolved in 2 ml lysis buffer containing 7 M urea, 2% SDS, 1 × protease inhibitor cocktail (Roche Ltd. Basel, Switzerland), followed by sonication on ice for 20 min and centrifugation at 12,000 rpm for 10 min at 4°C.…”

Elucidation of the miR164c-Guided Gene/Protein Interaction Network Controlling Seed Vigor in Rice

“…However, data processing using the MERLIN algorithm involves complex steps and is timeconsuming, and is therefore seldom used in omics studies (Marx et al, 2016). Moreover, most of the previous omics studies on seed vigor focused mainly on the identification of specific genes or proteins, and rarely focused on gene/protein network analysis (Daniel, 2017;Aragão et al, 2019;Wei et al, 2020). In this study, an interaction network that describes the association between miR164c target genes and DEGs/DEPs was predicted by an integrative analysis using the MERLIN algorithm and String database (Figure 9).…”

Germination response of black nightshade (Solanum nigrum) to temperature and the establishment of a thermal time model

“…The calculations of the germinability, germination potential (Wei et al 2020), and germination index (GI) (Chen et al 2016;Hayat et al 2020;Zhou et al 2016) were as follows:…”