Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F₂ generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F₂, F_2:3, F_2:4, and F_2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

Common buckwheat (Fagopyrum esculentum M.) belongs to the eudicot family Polygonaceae, Fagopyrum Mill, and its seeds have high nutritional value. The mechanism of seed development of common buckwheat remains unclear at the molecular level and no genes related to seed size have been identified. In this study, we performed genome-wide transcriptome sequencing and analysis using common buckwheat seeds at 5 days post anthesis (DPA) and 10 DPA from two cultivars (large-seeded and small-seeded). A total of 259,895 transcripts were assembled, resulting in 187,034 unigenes with average length of 1097 bp and N50 of 1538 bp. Based on gene expression profiles, 9127 differentially expressed genes (DEGs) were identified and analyzed in GO enrichment and KEGG analysis. In addition, genes related to seed size in the IKU pathway, ubiquitin-proteasome pathway, MAPK signaling pathway, TFs and phytohormones were identified and analyzed. AP2 and bZIP transcription factors, BR-signal and ABA were considered to be important regulators of seed size. This study provides a valuable genetic resource for future identification and functional analysis of candidate genes regulating seed size in common buckwheat and will be useful for improving seed yield in common buckwheat through molecular breeding in the future.

To disclose the relationship between lignin content and lodging resistance, field experiments were conducted in 2012 and 2013 to investigate the dynamic changes of lignin content, the activities of four enzymes involved in lignin metabolism in culm, as well as the snapping resistance and lodging index of buckwheat. The lignin content and activities of phenylalanine ammonia-lyase (PAL), tyrosine ammonia-lyase (TAL), cinnamyl alcohol dehydrogenase (CAD), and 4-coumarate: CoA ligase (4CL) were tested with the 2 nd internode of four cultivars with different lodging resistance. The snapping resistance and culm lodging index were determined at anthesis, grain filling, and maturity stages. The lignin content varied significantly among cultivars. The XD cultivar, which showed high resistance to culm snapping and lodging, had higher lignin content and higher activity of PAL, TAL, 4CL, and CAD than other cultivars. The lignin content was significantly negatively correlated with the actual lodging percent ( r = -0.844, P < 0.01) and the lodging index ( r = -0.832, P < 0.05), and was significantly positively correlated with the snapping resistance ( r = 0.873, P < 0.01). The activities of PAL, TAL, 4CL, and CAD were positively correlated with lignin content with correlation coefficients of 0.984 ( P 0.05), 0.927 ( P < 0.01), and 0.862 ( P < 0.01), respectively. In conclusion, our results indicate that the activities of PAL and 4CL were the key enzymes that influenced the lignin content, and that the lignin content can be used as main indicators to evaluate the lodging resistance of buckwheat.

Soybean (Glycine max) is an important crop, rich in proteins, vegetable oils and several other phytochemicals, which is often affected by light during growth. However, the specific regulatory mechanisms of leaf development under shade conditions have yet to be understood. In this study, the transcriptome and metabolome sequencing of leaves from the shade-tolerant soybean ‘Nanxiadou 25′ under natural light (ND1) and 50% shade rate (SHND1) were carried out, respectively. A total of 265 differentially expressed genes (DEGs) were identified, including 144 down-regulated and 121 up-regulated genes. Meanwhile, KEGG enrichment analysis of DEGs was performed and 22 DEGs were significantly enriched in the top five pathways, including histidine metabolism, riboflavin metabolism, vitamin B6 metabolism, glycerolipid metabolism and cutin, suberine and wax biosynthesis. Among all the enrichment pathways, the most DEGs were enriched in plant hormone signaling pathways with 19 DEGs being enriched. Transcription factors were screened out and 34 differentially expressed TFs (DETFs) were identified. Weighted gene co-expression network analysis (WGCNA) was performed and identified 10 core hub genes. Combined analysis of transcriptome and metabolome screened out 36 DEGs, and 12 potential candidate genes were screened out and validated by quantitative real-time polymerase chain reaction (qRT-PCR) assay, which may be related to the mechanism of shade tolerance in soybean, such as ATP phosphoribosyl transferase (ATP-PRT2), phosphocholine phosphatase (PEPC), AUXIN-RESPONSIVE PROTEIN (IAA17), PURPLE ACID PHOSPHATASE (PAP), etc. Our results provide new knowledge for the identification and function of candidate genes regulating soybean shade tolerance and provide valuable resources for the genetic dissection of soybean shade tolerance molecular breeding.

Soybeans are the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) for soybean quality traits and mining related candidate genes are of great significance for the molecular breeding of soybean quality traits and understanding the genetic mechanism of protein/fat metabolism. In this study, the F₂ population was derived from the high-protein material Changjiang Chun 2 and Jiyu 166. On the basis of a genetic linkage map constructed in our previous study, the QTL of crude protein content, crude oil content and fatty acid fractions were detected using the multiple-QTL model (MQM) mapping method. The results show that a total of 92 QTL were obtained affecting quality traits under three environments, including 14 QTL of crude oil content, 9 QTL of crude protein content, and 20, 20, 11, 10 and 8 QTL for the content of palmitic, stearic, oleic, linoleic and linolenic acids, respectively. Sixteen QTL clusters were identified, among which Loci01.1, Loci06.1 and Loci11.1 were identified as stable QTL clusters with phenotypic contribution rates of 16.5%, 16.4% and 12.1%, respectively, and candidate genes were mined in their regions. A total of 32 candidate genes related to soybean quality were finally screened via GO enrichment and gene annotation. The present study lies the foundations for understanding the genetic mechanism and elite germplasm innovation of seed quality in soybean.