Integrated transcriptomic and proteomic characterization of a chromosome segment substitution line reveals a new regulatory network controlling the seed storage profile of soybean

Abstract

Soybean is a major crop that provides oil and protein worldwide. Soybean products have been consumed for centuries in many different kinds of food. The regulatory network that controls the accumulation of fatty acids (FAs) and storage proteins (SSPs) in seeds is poorly understood. To gain new insights into the molecular mechanisms that contribute to high‐quality seeds, seed FA and SSP contents were analyzed for the effects of chromosome segment substitution in a wild soybean line (CSSL). High‐throughput transcriptomics and tandem mass tag (TMT)‐based quantitative proteomics were performed on the dry seeds of the CSSL and parent lines. In total, 665 differentially expressed genes (DEGs) and 83 differentially accumulated proteins (DAPs) were identified. Of these 27 DEGs and 23 DAPs were found to regulate the seed storage profile. These genes encode proteins involved in photosynthesis, protein processing, protein sorting, and storage protein accumulation. Data are presented showing that FA synthesis was decreased by the regulation of SSP‐accumulation‐related genes and proteins. Taken together, the results provide new insights into the regulation network involved in the accumulation of seed storage compounds involving both source and sink processes that may be used as markers in future soybean breeding programs.

Meta-Analysis and Multiomics of a Chromosome Segment Substitution Line Reveal Candidate Genes Associated with Seed Hardness in Soybean

“…CSSL populations have been widely used to map QTLs in crops such as maize, 22 rice, 23 and wheat. 24 Recently, high-throughput transcriptomics and TMT-based quantitative proteomics were performed on dry seeds from soybean CSSLs and parental lines, 14 and 665 DEGs and 83 differentially accumulated proteins (DAPs) were identified. In the present study, the seed hardness of each CCSL in the population was determined in 2019 and 2020, and materials with sufficiently stable hardness phenotypes were identified, enabling research into the genetic basis of this trait.…”

“…The soybean reference genome (Wm82.a2.v1) and annotation data set were downloaded from Phytozome (https:// phytozome-next.jgi.doe.gov/info/Gmax_Wm82_a2_v1). For details of processing and quality control measures, see Han et al 14 Differentially expressed genes (DEGs) between SN14 and R75 before and after soaking in water were identified using DESeq2 15 with the screening criteria |log 2 FoldChange| > 1 and false discovery rate (FDR)-adjusted P-value < 0.05. The raw sequencing data have been deposited in the National Center for Biotechnology Information (NCBI) database under the accession PRJNA999195.…”

“…The filtrate was redissolved in 0.1% trifluoroacetic acid (TFA) solution and desalted using a Thermo desalting spin column for use in peptide quantification. 14 TMT Labeling of Peptides. Peptides (100 μg) were labeled according to the instructions of the Thermo Fisher Tandem Mass Tag (TMT) Labeling Kit.…”

“…Peptides were separated and analyzed by DDA mass spectrometry on a Q-Exactive HF-X mass spectrometer (Thermo Scientific) for 90 min. Details of the procedure are given in Han et al…”

“…Hierarchical clustering was used to group proteins by abundance level. Methods and software for sequence annotation, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and construction of protein–protein interaction (PPI) networks have been detailed previously …”