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Huiming Li

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Open access Aug 2026

Multi-omics reveals rhizosphere soil metabolismte-microbiota interactions in different varieties of sorghum under nutrient-deficient stress

Soil microorganisms and metabolites are the central elements of rhizosphere microenvironment, with substantial effects on nutrient acquisition, stress resilience, and yield performance in sorghum. In this study, root antioxidant enzyme activity, malondialdehyde (MDA) content, and soil properties from Jinnuo 101 and Jinnuo 102 were compared under low-nutrient condition. Changes in bacterial community structure and metabolite composition of rhizosphere and bulk soils from two sorghum cultivars were characterized using 16S rDNA high-throughput sequencing and liquid chromatography-mass spectrometry (LC-MS). Jinnuo 102 exhibits greater tolerance to low-nutrient stress conditions compared with Jinnuo 101. Under low-nutrient stress, Actinobacteria, Acidobacteria, and Bacillobacteria were significantly more abundant in sorghum rhizosphere soil than bulk soil. The Jinnuo 102 rhizosphere soil presented significantly higher Actinobacteria abundance, whereas Jinnuo 101 was significantly enriched in Cyanobacteria (P < 0.05). Metabolic pathway analysis identified the significant upregulation of “Biosynthesis of phenylpropanoids”,“Glycerophospholipid metabolism”, “Tryptophan metabolism”, and “ABC transporters”, along with the evident downregulation of “Linoleic acid metabolism” in rhizosphere soil. Biosynthesis of phenylpropanoids was significantly upregulated in rhizosphere soil of Jinnuo 102. The upregulated rhizosphere metabolites were mainly terpenoids, fatty amides or fatty acids, phenolic acids, and carbohydrates. Higher level of phenolic acids was observed in Jinnuo 102. The study reveals that tolerant sorghum enhances low-nutrient resistance by coordinately upregulating phenylpropanoid pathways and enriching beneficial rhizosphere bacteria. Theseresults provide a theoretical basis for improving sorghum tolerance to nutrientpoor conditions through regulating microbe-metabolite interactions.

Suxian Yan, Huiming Li, Yu-Zhong Cheng et al. · Frontiers in Soil Science · 0 citations

Open access Aug 2026

Genome-Wide Association Studies of Agronomic and Yield Traits in Sweet Corn (Zea mays L. var. saccharata)

Sweet corn is a globally important dual-purpose crop for both food and fresh vegetables. The plant architecture and ear-related traits directly determine its yield potential and field ecological adaptability. To elucidate the genetic architecture of these traits and identify superior alleles for breeding, we conducted a genome-wide association study (GWAS) on 11 agronomic traits using 30,597 high-quality SNP markers in a panel of 101 elite sweet corn inbred lines. Population genetic structure was analyzed using sparse non-negative matrix factorization (sNMF) and discriminant analysis of principal components (DAPC) algorithms, revealing three main clusters and six subpopulations. The clustering pattern was highly consistent with germplasm origin. Association mapping with the fixed and random Circulating Probability Unification (FarmCPU) model identified 16 significant marker–trait associations (MTAs), distributed across seven target agronomic traits. The phenotypic variance explained (PVE) by individual loci ranged from 8.0% to 16.0%. Among these, five stable MTAs across environments, a novel ERN locus (SNP25518) specific to sweet corn, and most association intervals overlapped with previously reported quantitative trait loci (QTLs). Within the ±0.15 Mb (defined by LD decay) flanking windows around the significant SNP loci, a total of 236 candidate genes were annotated, which are primarily involved in hormone signaling, carbon and nitrogen metabolism, cell division, and plant growth and development. In summary, this study dissected the genetic basis of key agronomic traits in sweet corn and provides a foundation for marker-assisted selection and functional validation.

Yan-Chao Du, Jing-Wen Xu, Huiming Li et al. · Plants · 0 citations