Due to the relatively brief domestication history of sugar beet (Beta vulgaris ssp. vulgaris), our understanding of the genomic diversity and functional genes in its cultivars is limited, resulting in slow breeding progress. To address this issue, a total of 306 germplasm materials of major cultivars and breeding lines from China, the USA, and Europe were selected for genome resequencing. We investigated population structure and genetic diversity and performed selective scanning of genomic regions, identifying six novel genes associated with important agronomic traits: the candidate genes DFAX2 and P5CS for skin roughness; the candidate genes FRO5, GL24, and PPR91 for root yield and sugar yield, and the pleiotropic candidate gene POLX for flourishing growth vigour, plant height, crown size, flesh coarseness, and sugar yield. In addition, we constructed a protein–protein interaction network map and a phenotype-gene network map, which provide valuable information for identifying and characterizing functional genes affecting agronomic traits in sugar beet. Overall, our study sheds light on the future improvement of sugar beet agronomic traits at the molecular level.

Soilborne diseases caused by Rhizoctonia solani, Fusarium oxysporum f. sp. betae, Aphanomyces cochlioides, and Pythium spp. constrain sugar-beet production worldwide, with yield losses exceeding 50% in severely affected fields. These pathogens frequently co-occur, yet most biological control and microbiome studies address them individually, and recommendations from model crops often fail to translate to sugar beet’s distinctive root biology and rotation systems. This critical review synthesises evidence on the rhizosphere microbiome as a plant protection resource, organising the literature by agronomic applicability: crop rotation, organic amendments, soil physicochemical management, microbial inoculants and synthetic communities, and microbiome-informed breeding and diagnostics. For each strategy, we state the evidence directness (direct sugar-beet field trials, greenhouse data, cross-crop extrapolation, or mechanistic inference) and evaluate the gap between experimental efficacy and field-ready recommendations. Direct field evidence remains limited: the best-characterised example is Rhizoctonia-suppressive soil linked to non-ribosomal peptide synthetase (NRPS)-producing Pseudomonadaceae and Burkholderiaceae, with 2,4-DAPG-producing Pseudomonas populations also being correlated with disease suppression in sugar-beet seedlings, plus one integrated fungicide-biocontrol field trial. We identify multi-pathogen challenge experiments, multi-site field validation of synthetic communities, and microbiome-informed breeding as priority research gaps. Rhizosphere microbiome management should be integrated into existing disease programmes rather than deployed as a stand-alone replacement.