Insights into starch synthesis and amino acid composition of common buckwheat in response to phosphate fertilizer management strategies.

To investigate the response and the regulatory mechanism of common buckwheat starch, amylose, and amylopectin biosynthesis to P management strategies, field experiments were conducted in 2021 and 2022 using three phosphorus (P) levels. Results revealed that the application of 75 kg hm-2 phosphate fertilizer significantly enhanced amylopectin and total starch content in common buckwheat, leading to improved grain weight and starch yield, and decreased starch granule size. The number of upregulated differentially expressed proteins induced by phosphate fertilizer increased with the application rate, with 56 proteins identified as shared differential proteins between different P levels, primarily associated with carbohydrate and amino acid metabolism. Phosphate fertilizer inhibited amylose synthesis by downregulating granule-bound starch synthase protein expression and promoted amylopectin accumulation by upregulating 1,4-alpha-glucan branching enzyme and starch synthase proteins expression. Additionally, Phosphate fertilizer primarily promoted the accumulation of hydrophobic and essential amino acids. These findings elucidate the mechanism of P-induced starch accumulation and offer insights into phosphate fertilizer management and high-quality cultivation of common buckwheat.

Effects of nitrogen fertilizer on the physicochemical, structural, functional, thermal, and rheological properties of mung bean (Vigna radiata) protein.

Nitrogen fertilizer can affect the seed quality of mung bean. However, the effects of nitrogen fertilizer on the properties of mung bean protein (MBP) remain unclear. We investigated the effects of four nitrogen fertilization levels on the physicochemical, structural, functional, thermal, and rheological properties of MBP. The results showed that the amino acid and protein contents of mung bean flour were maximized under 90 kg ha-1 of applied nitrogen treatment. Nitrogen fertilization can alter the secondary and tertiary structure of MBP. The main manifestations are an increase in the proportion of ß-sheet, the exposure of more chromophores and hydrophobic groups, and the formation of loose porous aggregates. These changes improved the solubility, oil absorption capacity, emulsion activity, and foaming stability of MBP. Meanwhile, Thermodynamic and rheological analyses showed that the thermal stability, apparent viscosity, and gel elasticity of MBP were all increased under nitrogen fertilizer treatment. Correlation analysis showed that protein properties are closely related to changes in structure. In conclusion, nitrogen fertilization can improve the protein properties of MBP by modulating the structure of protein molecules. This study provides a theoretical basis for the optimization of mung bean cultivation and the further development of high-quality mung bean protein foods.

Effects of biochar coupled with chemical and organic fertilizer application on physicochemical properties and in vitro digestibility of common buckwheat (Fagopyrum esculentum Moench) starch.

Common buckwheat starch, a functional ingredient, has wide food and non-food applications. Excessive chemical fertilizer application during grain cultivation decreases quality. This study examined the effects of different combinations of chemical fertilizer, organic fertilizer, and biochar treatment on the physicochemical properties and in vitro digestibility of starch. The amendment of both organic fertilizer and biochar was observed to have a greater impact on the physicochemical properties and in vitro digestibility of common buckwheat starch in comparison to organic fertilizer amendment solely. The combined application of biochar, chemical, and organic nitrogen in an 80:10:10 ratio significantly increased the amylose content, light transmittance, solubility, resistant starch content, and swelling power of the starch. Simultaneously, the application reduced the proportion of amylopectin short chains. Additionally, this combination decreased the size of starch granules, weight-average molecular weight, polydispersity index, relative crystallinity, pasting temperature, and gelatinization enthalpy of the starch compared to the utilization of chemical fertilizer alone. The correlation between physicochemical properties and in vitro digestibility was analyzed. Four principal components were obtained, which accounted for 81.18 % of the total variance. These findings indicated that the combined application of chemical fertilizer, organic fertilizer, and biochar would improve common buckwheat grain quality.

Proteomics characterization of the synthesis and accumulation of starch and amino acid driven by high-nitrogen fertilizer in common buckwheat.

The accumulation of starches and amino acid content of common buckwheat is promoted by Nitrogen (N), but the molecular mechanism is not clear. N applications with 0 (control group) and 180 kg/ha were designed. High-N significantly improved grain fullness and increased the starch, amylopectin and amylose content. The number of upregulated differentially expressed proteins (DEPs) induced by N gradually increased with the filling progress. N resulted in 139, 341 and 472DEPs significant upregulation at 10d, 20d and 30d and they were mainly related to the 'Starch and sucrose metabolism', 'Protein processing in endoplasmic reticulum' and 'Ribosome' by kyoto encyclopedia of genes and genomes analysis. High-N induced one sucrose synthase, two alpha-amylases and six alpha-glucan phosphorylases significant upregulation at 30d and one alpha-amylases upregulation at 10d, and the expression levels of these proteins showed a significant linear relationship with starch and amylose contents. N promoted the arginine and lysine biosynthesis at the late filling stage. These results elucidated that the mechanism of N promoted common buckwheat starches and amino acid accumulation. The identified crucial proteins may improve buckwheat quality.

How Does the Environment Affect Wheat Yield and Protein Content Response to Drought? A Meta-Analysis.

Wheat (Triticum aestivum L.) is one of the most significant cereal crops grown in the semi-arid and temperate regions of the world, but few studies comprehensively explore how the environment affects wheat yield and protein content response to drought by means of meta-analysis. Therefore, we collected data about grain yield (GY), grain protein yield (GPY), grain protein content (GPC), and grain nitrogen content (GNC), and conducted a meta-analysis on 48 previously published data sets that originate from 15 countries. Our results showed that drought significantly decreased GY and GPY by 57.32 and 46.04%, but significantly increased GPC and GNC by 9.38 and 9.27%, respectively. The responses of wheat GY and GNC to drought were mainly related to the drought type, while the GPY was mainly related to the precipitation. The yield reduction due to continuous drought stress (CD, 83.60%) was significantly greater than that of terminal drought stress (TD, 26.43%). The relationship between the precipitation and GPY increased in accordance with linear functions, and this negative drought effect was completely eliminated when the precipitation was more than 513 mm. Sandy soils and high nitrogen application level significantly mitigated the negative effects of drought, but was not the main factor affecting the drought response of wheat. Compared with spring wheat, the drought resistance effect of winter wheat was more obvious. Evaluation of these models can improve our quantitative understanding of drought on wheat yield and food security, minimizing the negative impact of drought on crop production.

Dynamic Quantitative Trait Loci Mapping for Plant Height in Recombinant Inbred Line Population of Upland Cotton.

Plant height (PH) is a key plant architecture trait for improving the biological productivity of cotton. Ideal PH of cotton is conducive to lodging resistance and mechanized harvesting. To detect quantitative trait loci (QTL) and candidate genes of PH in cotton, a genetic map was constructed with a recombinant inbred line (RIL) population of upland cotton. PH phenotype data under nine environments and three best linear unbiased predictions (BLUPs) were used for QTL analyses. Based on restriction-site-associated DNA sequence (RAD-seq), the genetic map contained 5,850 single-nucleotide polymorphism (SNP) markers, covering 2,747.12 cM with an average genetic distance of 0.47 cM. Thirty-seven unconditional QTL explaining 1.03-12.50% of phenotypic variance, including four major QTL and seven stable QTL, were identified. Twenty-eight conditional QTL explaining 3.27-28.87% of phenotypic variance, including 1 major QTL, were identified. Importantly, five QTL, including 4 stable QTL, were both unconditional and conditional QTL. Among the 60 PH QTL (including 39 newly identified), none of them were involved in the whole period of PH growth, indicating that QTL related to cotton PH development have dynamic expression characteristics. Based on the functional annotation of Arabidopsis homologous genes and transcriptome data of upland cotton TM-1, 14 candidate genes were predicted within 10 QTL. Our research provides valuable information for understanding the genetic mechanism of PH development, which also increases the economic production of cotton.

Genome-wide association and differential expression analysis of salt tolerance in Gossypium hirsutum L at the germination stage.

BACKGROUND: Salinity is a major abiotic stress seriously hindering crop yield. Development and utilization of tolerant varieties is the most economical way to address soil salinity. Upland cotton is a major fiber crop and pioneer plant on saline soil and thus its genetic architecture underlying salt tolerance should be extensively explored. RESULTS: In this study, genome-wide association analysis and RNA sequencing were employed to detect salt-tolerant qualitative-trait loci (QTLs) and candidate genes in 196 upland cotton genotypes at the germination stage. Using comprehensive evaluation values of salt tolerance in four environments, we identified 33 significant single-nucleotide polymorphisms (SNPs), including 17 and 7 SNPs under at least two and four environments, respectively. The 17 stable SNPs were located within or near 98 candidate genes in 13 QTLs, including 35 genes that were functionally annotated to be involved in salt stress responses. RNA-seq analysis indicated that among the 98 candidate genes, 13 were stably differentially expressed. Furthermore, 12 of the 13 candidate genes were verified by qRT-PCR. RNA-seq analysis detected 6640, 3878, and 6462 differentially expressed genes at three sampling time points, of which 869 were shared. CONCLUSIONS: These results, including the elite cotton accessions with accurate salt tolerance evaluation, the significant SNP markers, the candidate genes, and the salt-tolerant pathways, could improve our understanding of the molecular regulatory mechanisms under salt stress tolerance and genetic manipulation for cotton improvement.

Genome-Wide Association Study Identifies Candidate Genes Related to Seed Oil Composition and Protein Content in Gossypium hirsutum L.

Cotton (Gossypium spp.) is a leading natural fiber crop and an important source of vegetable protein and oil for humans and livestock. To investigate the genetic architecture of seed nutrients in upland cotton, a genome-wide association study (GWAS) was conducted in a panel of 196 germplasm resources under three environments using a CottonSNP80K chip of 77,774 loci. Relatively high genetic diversity (average gene diversity being 0.331) and phenotypic variation (coefficient of variation, CV, exceeding 3.9%) were detected in this panel. Correlation analysis revealed that the well-documented negative association between seed protein (PR) and oil may be to some extent attributable to the negative correlation between oleic acid (OA) and PR. Linkage disequilibrium (LD) was unevenly distributed among chromosomes and subgenomes. It ranged from 0.10-0.20 Mb (Chr19) to 5.65-5.75 Mb (Chr25) among the chromosomes and the range of Dt-subgenomes LD decay distances was smaller than At-subgenomes. This panel was divided into two subpopulations based on the information of 41,815 polymorphic single-nucleotide polymorphism (SNP) markers. The mixed linear model considering both Q-matrix and K-matrix [MLM(Q+K)] was employed to estimate the association between the SNP markers and the seed nutrients, considering the false positives caused by population structure and the kinship. A total of 47 SNP markers and 28 candidate quantitative trait loci (QTLs) regions were found to be significantly associated with seven cottonseed nutrients, including protein, total fatty acid, and five main fatty acid compositions. In addition, the candidate genes in these regions were analyzed, which included three genes, Gh_D12G1161, Gh_D12G1162, and Gh_D12G1165 that were most likely involved in the control of cottonseed protein concentration. These results improved our understanding of the genetic control of cottonseed nutrients and provided potential molecular tools to develop cultivars with high protein and improved fatty acid compositions in cotton breeding programs through marker-assisted selection.

Genome-wide analysis of codon usage bias in four sequenced cotton species.

Codon usage bias (CUB) is an important evolutionary feature in a genome which provides important information for studying organism evolution, gene function and exogenous gene expression. The CUB and its shaping factors in the nuclear genomes of four sequenced cotton species, G. arboreum (A2), G. raimondii (D5), G. hirsutum (AD1) and G. barbadense (AD2) were analyzed in the present study. The effective number of codons (ENC) analysis showed the CUB was weak in these four species and the four subgenomes of the two tetraploids. Codon composition analysis revealed these four species preferred to use pyrimidine-rich codons more frequently than purine-rich codons. Correlation analysis indicated that the base content at the third position of codons affect the degree of codon preference. PR2-bias plot and ENC-plot analyses revealed that the CUB patterns in these genomes and subgenomes were influenced by combined effects of translational selection, directional mutation and other factors. The translational selection (P2) analysis results, together with the non-significant correlation between GC12 and GC3, further revealed that translational selection played the dominant role over mutation pressure in the codon usage bias. Through relative synonymous codon usage (RSCU) analysis, we detected 25 high frequency codons preferred to end with T or A, and 31 low frequency codons inclined to end with C or G in these four species and four subgenomes. Finally, 19 to 26 optimal codons with 19 common ones were determined for each species and subgenomes, which preferred to end with A or T. We concluded that the codon usage bias was weak and the translation selection was the main shaping factor in nuclear genes of these four cotton genomes and four subgenomes.