The diversity of endophytic fungi in Tartary buckwheat (Fagopyrum tataricum) and its correlation with flavonoids and phenotypic traits

Abstract

Tartary buckwheat (Fagopyrum tataricum) is a significant medicinal crop, with flavonoids serving as a crucial measure of its quality. Presently, the artificial cultivation of Tartary buckwheat yields low results, and the quality varies across different origins. Therefore, it is imperative to identify an effective method to enhance the yield and quality of buckwheat. Endophytic fungi reside within plants and form a mutually beneficial symbiotic relationship, aiding plants in nutrient absorption, promoting host growth, and improving secondary metabolites akin to the host. In this study, high-throughput sequencing technology was employed to assess the diversity of endophytic fungi in Tartary buckwheat. Subsequently, a correlation analysis was performed between fungi and metabolites, revealing potential increases in flavonoid content due to endophytic fungi such as Bipolaris, Hymenula, and Colletotrichum. Additionally, a correlation analysis between fungi and phenotypic traits unveiled the potential influence of endophytic fungi such as Bipolaris, Buckleyzyma, and Trichosporon on the phenotypic traits of Tartary buckwheat. Notably, the endophytic fungi of the Bipolaris genus exhibited the potential to elevate the content of Tartary buckwheat metabolites and enhance crop growth. Consequently, this study successfully identified the resources of endophytic fungi in Tartary buckwheat, explored potential functional endophytic fungi, and laid a scientific foundation for future implementation of biological fertilizers in improving the quality and growth of Tartary buckwheat.

Keywords: Tartary buckwheat; endophytic fungi; flavonoids; high-throughput sequencing; phenotypic traits.

Figure 1

Distribution map of Tartary buckwheat. Xining City (XN), Lintao County (LT), Zhangchuan County (ZC), Wen County (WX), Taibai County (TB), Zhaojue County (ZJ), and Weining County (WN) are the seven wild buckwheat collection sites. Among them, XN belongs to China’s Qinghai Province (QH), LT, ZC, and WX belongs to China’s Gansu Province (GS), TB belongs to China’s Shaanxi Province (SX), ZJ belongs to China’s Sichuan Province (SC), WN belongs to China’s Guizhou Province (GZ).

Figure 2

Sparse curves and Venn diagram of 21 samples. The abscissa represents the ranking of operational taxonomic units (OTUs), while the ordinate represents the relative percentage of species at the classification level (A). The position of the abscissa of the extension end point of the sample curve represents the number of species in each sample. (B) The Venn diagram describes different and common OTUs in 7 different Tartary buckwheat materials (Zhaojue, ZJ; Wenxian, WX; Zhangchuan, ZC; Xining, XN; Lintao, LT; Taibai, TB; Weining, WN). (C) Different and common OTUs in roots, stems, and leaves.

Figure 3

Similarity ANOSIM analysis and PCoA analysis of the endophytic fungal community in Tartary buckwheat based on Bray-Curtis distance. (A,C) ANOSIM analysis and PCoA analysis of 7 different Tartary buckwheat materials. (B,D) ANOSIM analysis and PCOA analysis of different tissue parts (roots, stems, and leaves).

Figure 4

Composition of endophytic fungal community of Tartary buckwheat. The first four figures represent the composition of endophytic fungi at the phylum level (A), class level (B), order level (C), and genus level (D) for different samples. The following four figures represent the composition of endophytic fungi at the phylum level (E), class level (F), order level (G), and genus level (H) in different tissue parts.

Figure 5

Content map of flavonoids and polyphenols in 21 Tartary buckwheat samples (Zhaojue, ZJ; Wenxian, WX; Zhangchuan, ZC; Xining, XN; Lintao, LT; Taibai, TB; Weining, WN). (A) Flavone content in 21 Tartary buckwheat samples. (B) Polyphenol content in 21 Tartary buckwheat samples.

Figure 6

Chord diagram, heat maps, ANOSIM analyses, and PCA analyses of 22 flavonoid metabolites in ZC and LT roots, stems, and leaves. (A) The chord diagram shows the proportion of 22 flavonoids in the roots, stems, and leaves of ZC and TL. (B) The heat map intuitively reflects the differences in the content of 22 flavonoids in different samples. In the heat map, red indicates a content higher than the average, while blue indicates a content lower than the average. The darker the color, the more significant the difference. (C,D) ANOSIM and PCA analyses of flavonoid metabolite content in roots (R), stems (S), and leaves (L) of tissue samples from ZC and LT.

Figure 7

Analysis of differences in endophytic fungi between ZC and LT, as well as correlation between flavonoids and different endophytic fungi at the genus level. (A) LEfSe analysis shows the hierarchical relationships of the main taxonomic units in the sample community from phylum to genus (from inner circle to outer circle). The node size corresponds to the average relative abundance of the classification unit; A node with a red background indicates a higher abundance of the classification unit in ZC, while a node with a green background indicates a higher abundance of the classification unit in LT. The letters indicate the names of taxonomic units with significant differences between groups. (B) Percentage of endophytic fungi with genus level differences. (C) Association network diagram of endophytic fungi and flavonoid metabolites with significant correlation.

Figure 8

Association network diagram of Endophytic fungi with differences at the genus level and phenotypic traits with significant correlation.