Dynamic transcriptome analysis suggests the key genes regulating seed development and filling in Tartary buckwheat (Fagopyrum tataricum Garetn.)

Advancements in multi-omics for nutraceutical enhancement and traits improvement in buckwheat

Buckwheat (Fagopyrum spp.) is a typical pseudocereal, valued for its extensive nutraceutical potential as well as its centuries-old cultivation. Tartary buckwheat and common buckwheat have been used globally and become well-known nutritious foods due to their high quantities of: proteins, flavonoids, and minerals. Moreover, its increasing demand makes it critical to improve nutraceutical, traits and yield. In this review, bioactive compounds accumulated in buckwheat were comprehensively evaluated according to their chemical structure, properties, and physiological function. Biosynthetic pathways of flavonoids, phenolic acids, and fagopyrin were methodically summarized, with the regulation of flavonoid biosynthesis. Although there are classic synthesis pathways presented in the previous research, the metabolic flow of how these certain compounds are being synthesized in buckwheat still remains uncovered. The functional genes involved in the biosynthesis of flavonols, stress response, and plant development were identified based on multi-omics research. Furthermore, it delves into the applications of multi-omics in improving buckwheat's agronomic traits, including: yield, nutritional content, stress resilience, and bioactive compounds biosynthesis. While pangenomics combined with other omics to mine elite genes, the regulatory network and mechanism of specific agronomic traits and biosynthetic of bioactive components, and developing a more efficient genetic transformation system for genetic engineering require further investigation for the execution of breeding designs aimed at enhancing desirable traits in buckwheat. This critical review will provide a comprehensive understanding of multi-omics for nutraceutical enhancement and traits improvement in buckwheat.

Transcriptome and metabolome analyses reveal regulatory networks associated with nutrition synthesis in sorghum seeds

Cereal seeds are vital for food, feed, and agricultural sustainability because they store and provide essential nutrients to human and animal food and feed systems. Unraveling molecular processes in seed development is crucial for enhancing cereal grain yield and quality. We analyze spatiotemporal transcriptome and metabolome profiles during sorghum seed development in the inbred line 'BTx623'. Morphological and molecular analyses identify the key stages of seed maturation, specifying starch biosynthesis onset at 5 days post-anthesis (dpa) and protein at 10 dpa. Transcriptome profiling from 1 to 25 dpa reveal dynamic gene expression pathways, shifting from cellular growth and embryo development (1-5 dpa) to cell division, fatty acid biosynthesis (5-25 dpa), and seed storage compounds synthesis in the endosperm (5-25 dpa). Network analysis identifies 361 and 207 hub genes linked to starch and protein synthesis in the endosperm, respectively, which will help breeders enhance sorghum grain quality. The availability of this data in the sorghum reference genome line establishes a baseline for future studies as new pangenomes emerge, which will consider copy number and presence-absence variation in functional food traits.

Machine learning-based prediction model for distant metastasis of breast cancer

BACKGROUND

Breast cancer is the most prevalent malignancy in women. Advanced breast cancer can develop distant metastases, posing a severe threat to the life of patients. Because the clinical warning signs of distant metastasis are manifested in the late stage of the disease, there is a need for better methods of predicting metastasis.

METHODS

First, we screened breast cancer distant metastasis target genes by performing difference analysis and weighted gene co-expression network analysis (WGCNA) on the selected datasets, and performed analyses such as GO enrichment analysis on these target genes. Secondly, we screened breast cancer distant metastasis target genes by LASSO regression analysis and performed correlation analysis and other analyses on these biomarkers. Finally, we constructed several breast cancer distant metastasis prediction models based on Logistic Regression (LR) model, Random Forest (RF) model, Support Vector Machine (SVM) model, Gradient Boosting Decision Tree (GBDT) model and eXtreme Gradient Boosting (XGBoost) model, and selected the optimal model from them.

RESULTS

Several 21-gene breast cancer distant metastasis prediction models were constructed, with the best performance of the model constructed based on the random forest model. This model accurately predicted the emergence of distant metastases from breast cancer, with an accuracy of 93.6 %, an F1-score of 88.9 % and an AUC value of 91.3 % on the validation set.

CONCLUSION

Our findings have the potential to be translated into a point-of-care prognostic analysis to reduce breast cancer mortality.

Granule-bound starch synthase in plants: Towards an understanding of their evolution, regulatory mechanisms, applications, and perspectives

Amylose content (AC) is a significant quality trait in starchy crops, affecting their processing and application by the food and non-food industries. Therefore, fine-tuning AC in these crops has become a focus for breeders. Granule-bound starch synthase (GBSS) is the core enzyme that directly determines the AC levels. Several excellent reviews have summarized key progress in various aspects of GBSS research in recent years, but they mostly focus on cereals. Herein, we provide an in-depth review of GBSS research in monocots and dicots, focusing on the molecular characteristics, evolutionary relationships, expression patterns, molecular regulation mechanisms, and applications. We also discuss future challenges and directions for controlling AC in starchy crops, and found simultaneously increasing both the PTST and GBSS gene expression levels may be an effective strategy to increase amylose content.

Interkingdom multi-omics analysis reveals the effects of nitrogen application on growth and rhizosphere microbial community of Tartary buckwheat

Tartary buckwheat (Fagopyrum tataricum Gaertn.) is an important pseudocereal crop with excellent edible, nutritional and medicinal values. However, the yield of Tartary buckwheat (TB) is very low due to old-fashioned cultivation techniques, particularly unreasonable application of nitrogen fertilizer. To improve the understanding on the theories of nitrogen use in TB, the effects of nitrogen application on growth, as well as chemical properties and microbial community of rhizosphere soil were investigated in this study. Nitrogen application could promote the plant height, stem diameter, nitrogen accumulation and yield of TB. The relative abundance and diversity of bacteria and fungi in the rhizosphere soil of TB were improved by nitrogen fertilizer. Nitrogen application increased the abundance of beneficial bacteria such as Lysobacter and Sphingomonas in rhizosphere soil, and decreased the abundance of pathogenic fungi such as Fusarium and Plectosphaerella. The results indicated that nitrogen application changed the distribution of microbial communities in TB rhizosphere soil. Furthermore, the specific enriched or depleted microorganisms in the rhizosphere soil of four TB varieties were analyzed at OTU level. 87 specific nitrogen-responsive genes with sequence variation were identified in four varieties by integrating genomic re-sequencing and transcriptome analysis, and these genes may involve in the recruitment of specific rhizosphere microorganisms in different TB varieties. This study provided new insights into the effects of nitrogen application on TB growth and rhizosphere microbial community, and improved the understanding on the mechanisms of TB root-microbe interactions.

Global Transcriptome and Co-Expression Network Analyses Revealed Hub Genes Controlling Seed Size/Weight and/or Oil Content in Peanut

Cultivated peanut (Arachis hypogaea L.) is an important economic and oilseed crop worldwide, providing high-quality edible oil and high protein content. Seed size/weight and oil content are two important determinants of yield and quality in peanut breeding. To identify key regulators controlling these two traits, two peanut cultivars with contrasting phenotypes were compared to each other, one having a larger seed size and higher oil content (Zhonghua16, ZH16 for short), while the second cultivar had smaller-sized seeds and lower oil content (Zhonghua6, ZH6). Whole transcriptome analyses were performed on these two cultivars at four stages of seed development. The results showed that ~40% of the expressed genes were stage-specific in each cultivar during seed development, especially at the early stage of development. In addition, we identified a total of 5356 differentially expressed genes (DEGs) between ZH16 and ZH6 across four development stages. Weighted gene co-expression network analysis (WGCNA) based on DEGs revealed multiple hub genes with potential roles in seed size/weight and/or oil content. These hub genes were mainly involved in transcription factors (TFs), phytohormones, the ubiquitin-proteasome pathway, and fatty acid synthesis. Overall, the candidate genes and co-expression networks detected in this study could be a valuable resource for genetic breeding to improve seed yield and quality traits in peanut.

Comparative transcriptome and genome analysis unravels the response of Tatary buckwheat root to nitrogen deficiency

Tartary buckwheat (Fagopyrum tataricum Garetn.), a dicotyledonous herbaceous crop, has good adaptation to low nitrogen (LN) condition. The plasticity of roots drives the adaption of Tartary buckwheat under LN, but the detailed mechanism behind the response of TB roots to LN remains unclear. In this study, the molecular mechanism of two Tartary buckwheat genotypes' roots with contrasting sensitivity in response to LN was investigated by integrating physiological, transcriptome and whole-genome re-sequencing analysis. LN improved primary and lateral root growth of LN-sensitive genotype, whereas the roots of LN-insensitive genotype showed no response to LN. 2, 661 LN-responsive differentially expressed genes (DEGs) were identified by transcriptome analysis. Of these genes, 17 N transport and assimilation-related and 29 hormone biosynthesis and signaling genes showed response to LN, and they may play important role in Tartary buckwheat root development under LN. The flavonoid biosynthetic genes' expression was improved by LN, and their transcriptional regulations mediated by MYB and bHLH were analyzed. 78 transcription factors, 124 small secreted peptides and 38 receptor-like protein kinases encoding genes involved in LN response. 438 genes were differentially expressed between LN-sensitive and LN-insensitive genotypes by comparing their transcriptome, including 176 LN-responsive DEGs. Furthermore, nine key LN-responsive genes with sequence variation were identified, including FtNRT2.4, FtNPF2.6 and FtMYB1R1. This paper provided useful information on the response and adaptation of Tartary buckwheat root to LN, and the candidate genes for breeding Tartary buckwheat with high N use efficiency were identified.

Study on morphological traits, nutrient compositions and comparative metabolomics of diploid and tetraploid Tartary buckwheat sprouts during sprouting

Tartary buckwheat (TB) sprout is a kind of novel nutritional vegetable, but its consumption was limited by low biomass and thin hypocotyl. The tetraploid TB sprouts was considered to be able to solve this issue. However, the nutritional quality of tetraploid TB sprouts and differences between conventional (diploid) and tetraploid TB sprouts remain unclear. In this study, the morphological traits, nutrient compositions and metabolome changes of diploid and tetraploid TB sprouts were analyzed. The water, pigments and minerals contents of TB sprouts increased during sprouting, while the contents of total soluble protein, reducing sugar, cellulose, and total phenol decreased. Compared with diploid sprouts, tetraploid sprouts had higher biomass and thicker hypocotyl. Tetraploid sprouts had higher ash and carotenoid contents, but had lower phenol and flavonoid accumulation. 677 metabolites were identified in TB sprouts by UPLC-MS analysis, including 62 diseases-resistance metabolites and 43 key active ingredients. Some key bioactive metabolites, such as rimonabant, quinapril, 1-deoxynojirimycin and miglitol, were identified. 562 differential expressed metabolites (DEMs) were identified during sprouting with seven accumulation patterns, and five hormones were found to be involved in sprout development. Additionally, 209 DEMs between diploid and tetraploid sprouts were found, and some key bioactive metabolites were induced by chromosome doubling such as mesoridazine, amaralin, atractyloside A, rhamnetin and Qing Hau Sau. This work lays a basis for the development and utilization of TB sprouts and provides evidence for the selection of tetraploid varieties to produce sprouts with high biomass and quality.

Transcriptome and metabolome analyses reveal the key genes related to grain size of big grain mutant in Tartary Buckwheat (Fagopyrum tartaricum)

Grain size with high heritability and stability is an important selection target during Tartary buckwheat breeding. However, the mechanisms that regulate Tartary buckwheat grain development are unknown. We generated transcriptome and metabolome sequencing from 10 and 15 days past anthesis (DPA) grains of big grain mutant (bg1) and WT, and identified 4108 differentially expressed genes (DEGs) including 93 significantly up-regulated differential genes and 85 significantly down-regulated genes in both stages, simultaneously. Meanwhile, we identified DEGs involved in ubiquitin-proteasome pathway, HAI-KU (IKU) pathway, mitogen-activated protein kinase (MAPK) signaling pathway, plant hormone (auxin, brassinosteroids and cytokinins) transduction pathway and five transcription factor families, including APETALA (AP2), GROWTH-REGULATING FACTORS (GRF), AUXIN RESPONSE FACTOR (ARF), WRKY and MYB. Weighted gene co-expression network analysis (WGCNA) was performed and obtained 9 core DEGs. Conjoint analyses of transcriptome and metabolome sequencing screened out 394 DEGs. Using a combined comprehensive analysis, we identified 24 potential candidate genes that encode E3 ubiquitin-protein ligase HIP1, EMBRYO-DEFECTIVE (EMB) protein, receptor-like protein kinase FERONIA (FER), kinesin-4 protein SRG1, and so on, which may be associated with the big-grain mutant bg1. Finally, a quantitative real-time Polymerase Chain Reaction (qRT-PCR) assay was conducted to validate the identified DEGs. Our results provide additional knowledge for identification and functions of causal candidate genes responsible for the variation in grain size and will be an invaluable resource for the genetic dissection of Tartary buckwheat high-yield molecular breeding.