Biomedical subjects

Siyuan Li

Publications and source records attributed to Siyuan Li.

3 recordsLinked to original sources

PubMed2026

Genomic and functional characterization of sugar transporters reveals potential roles in sugar accumulation in a modern sugarcane cultivar.

Sugarcane (Saccharum spp.) is a globally important sugar crop whose productivity depends on efficient sugar transport from source to sink organs. However, systematic identification and functional characterization of sugar transporters (STs) in sugarcane cultivars remain limited. Here, we identified 190 non-redundant ST genes in sugarcane cultivar Guitang 42 (GT42) and phylogenetically classified them into nine groups within the Monosaccharide Transporter (MST), Sucrose Transporter (SUT), and Sugars Will Eventually be Exported Transporters (SWEET) families. Comparative evolutionary analysis revealed significant lineage-specific expansions in the PMT, STP subfamilies, and SWEET families compared to diploid and wild relatives, likely driven by polyploidization and intensive selection for sugar yield. Transcriptomic profiling across tissues and internode elongation stages demonstrated marked tissue-specific and developmental expression patterns. Yeast complementation assays confirmed the transport activity of candidate MSTs, SUTs and SWEETs, with confocal microscopy verifying their distinct subcellular localization at the plasma membrane, tonoplast, or endoplasmic reticulum. Furthermore, transient overexpression of several candidate transporters (ScSWEET4-T2, ScSWEET15, and ScTST4-T1) in Nicotiana benthamiana modulated soluble sugar accumulation, and their expression in sugarcane protoplasts activated key sugar-responsive marker genes (ScGPT2 and ScWIP4). Together, our study establishes a systematic genomic framework and identifies candidate functional transporters that govern sugar partitioning and storage, providing valuable genetic targets for molecular breeding and quality enhancement in sugarcane.

Functional characterization↗

PubMed2025

ProgModule: A novel computational framework to identify mutation driver modules for predicting cancer prognosis and immunotherapy response.

BACKGROUND: Cancer originates from dysregulated cell proliferation driven by driver gene mutations. Despite numerous algorithms developed to identify genomic mutational signatures, they often suffer from high computational complexity and limited clinical applicability. METHODS: Here, we presented ProgModule, an advanced computational framework designed to identify mutation driver modules for cancer prognosis and immunotherapy response prediction. In ProgModule, we introduced the Prognosis-Related Mutually Exclusive Mutation (PRMEM) score, which optimizes the balance between exclusive mutation coverage and the incorporation of mutation combination mechanisms critical for cancer prognosis. RESULTS: Applying to BLCA and HNSC cohorts, ProgModule successfully identified driver modules that stratify patients into distinct prognostic subgroups, and the combination of these modules could serve as an effective prognostic biomarker. Extending our method to diverse cancers, ProgModule presented robust prognostic performance and stability across model parameters, including stopping criteria and network topology. Moreover, our analysis suggested that driver modules can predict immunotherapeutic benefit more effectively than existing signatures. Further analyses based on published CRISPR data indicated that genes within these modules may serve as potential therapeutic targets. CONCLUSIONS: Altogether, ProgModule emerges as a powerful tool for identifying mutation driver modules as prognostic and immunotherapy response biomarkers, and genes within these modules may be used as potential therapeutic targets for cancer, offering new insights into precision oncology.

Humans↗

PubMed2025

Discovery of a novel Betacoronavirus 1, cpCoV, in goats in China: The new risk of cross-species transmission.

Betacoronavirus is a causative agent of respiratory and enteric diseases in humans and animals. Several ruminants are recognized to be intermediate hosts in the transmission of emerging coronaviruses from reservoir hosts to humans. Here, we first report a novel Betacoronavirus isolated from goats suffering from diarrhea in China, putatively named caprine coronavirus (cpCoV). Full-genome characterization and nuclear acid comparisons demonstrated that this virus is an evolutionarily distinct Betacoronavirus belonging to the subgenus Embecovirus and is a Betacoronavirus 1 species. Notably, on phylogenetic trees based on complete genomes and RdRp, S, and N genes, the cpCoVs were grouped into a clade distinct from other Betacoronavirus strains and were closely related to the HKU23- and HKU23-associated coronaviruses. CpCoV possessed a unique genome organization with a truncated NS4a protein and an elongated NS4b protein that showed no significant matches in the GenBank database. The homology of the S and NS4a-4b genes between cpCoV and Embecovirus was less than 95%. Analysis revealed possible recombination events occurred during the evolution of cpCoV and HKU23, and there are striking similarities between the two viruses in evolutionary terms. In addition, cpCoV showed a narrow cell tropism, replicating in human- and bovine-origin cells in vitro, and caused diarrhea and enteric pathologic changes in goats and calves in vivo. We have provided epidemiological, virological, evolutionary, and experimental evidence that cpCoV is a novel etiological agent for enteric disease in goats. Evidently, a spilling-over event might have occurred between ruminants, including goats, camels, cattle, and wild animals. This study highlights the importance of identifying coronavirus diversity and inter-species transmission in ruminants worldwide, broadens our understanding of the ecology of coronaviruses, and aids in the prevention of animal-to-human transmission and outbreaks.

Animals↗