Sporocarp-associated fungal co-occurrence networks in a corn field revealed by long-read high-throughput sequencing

Abstract

In forests, fungal sporocarps house the diverse fungicolous fungi; however, the relationships of sporocarps and associated fungal communities are rarely explored in agroecosystems. In a corn field near Gongzhuling City, Jilin Province, China, we found an epigeous sporocarp with agaricoid morphology that could grow next to the living corn plants. Using PacBio metabarcoding combined with an updated bioinformatic pipeline, we surveyed the fungal community profile along its cap, rhizomorph and hyphosphere soil at a much-improved taxonomic resolution. We identified the sporocarp, at a high probability, as Agrocybe dura, and this mushroom was significantly negatively correlated with Trichoderma hamatum and T. harzianum in the co-occurrence network. Fungal diversity in hyphosphere habitat was significantly higher than that in cap and rhizomorph habitats. Consistent with the pattern in fungal diversity, the node number, edge number, network diameter and average degree were significantly higher in hyphosphere habitat than other habitats. However, both the negative and positive cohesion were significantly higher in rhizomorph habitat than other habitats. Moreover, the z-c plot identified A. dura as the only network hub, linking multiple fungal species. The results give us a glimpse of the ecological relevance of saprobic mushrooms across the extensive northeastern black soil region of China. Our findings will aid in the assessment and forecasting of fungal diversity hotspots and their relationships with soil fertility in the ‘Golden Corn Belt’ of northeast China.

Graphical abstract

Keywords

PacBio metabarcoding / saprobic mushroom / species identification / co-occurrence network / corn field / northeast China

Highlight

	● We identified a sporocarp as Agrocybe dura growing next to a living corn using PacBio sequencing.
	● The mycoparasitism of Trichoderma spp. on A. dura were revealed by the co-occurrence network analysis.
	● For long-read HTS data, we updated a bioinformatic pipeline to enhance fungal taxonomic resolution.

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