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Juanjuan Wang

Publications and source records attributed to Juanjuan Wang.

2 recordsLinked to original sources

Characterization of FLOWERING LOCUS T-related genes and their putative gene regulatory network in semi-winter Brassica napus cultivar Zhongshaung11.

In many species, FLOWERING LOCUS T (FT)-like genes promote the floral transition by integrating environmental signals, in particular photoperiod, and internal cues. Here we show that Brassica napus contains six FT-like genes and two pseudogenes belonging to three orthogroups. All B. napus FT-like genes induce early flowering when expressed at the shoot apical meristems of Arabidopsis thaliana ft mutants; however, BnaFT.C6 and non-orthologous FT-like genes do not encode fully functional mobile florigens. In the case of BnFT.C6, the functional change is associated with a T to C amino acid change that is restricted to semi-winter accessions. Expression of orthologs of FT is photoperiod-dependent, and two distal enhancers are conserved; however, the homeologs BnaFT.A7 and BnaFT.C6 show rearrangements of DNA motifs binding NF-Y/CO and NF-Y transcriptional activator complexes between the promoter and downstream enhancers. Motif rearrangements correlate with differences in tissue-specific expression. Furthermore, homeologs with rearranged motifs could not be transactivated by B. napus CO in transient assays, although they show LD photoperiod-dependent expression. We propose that differential diurnal expression of NF-Y genes contributes to the photoperiod-dependent regulation of B. napus FT genes.

Brassica napus

Bridging the Gap From Proteomics Technology to Clinical Application: Highlights From the 68th Benzon Foundation Symposium.

The 68th Benzon Foundation Symposium brought together leading experts to explore the integration of mass spectrometry-based proteomics and artificial intelligence to revolutionize personalized medicine. This report highlights key discussions on recent technological advances in mass spectrometry-based proteomics, including improvements in sensitivity, throughput, and data analysis. Particular emphasis was placed on plasma proteomics and its potential for biomarker discovery across various diseases. The symposium addressed critical challenges in translating proteomic discoveries to clinical practice, including standardization, regulatory considerations, and the need for robust "business cases" to motivate adoption. Promising applications were presented in areas such as cancer diagnostics, neurodegenerative diseases, and cardiovascular health. The integration of proteomics with other omics technologies and imaging methods was explored, showcasing the power of multimodal approaches in understanding complex biological systems. Artificial intelligence emerged as a crucial tool for the acquisition of large-scale proteomic datasets, extracting meaningful insights, and enhancing clinical decision-making. By fostering dialog between academic researchers, industry leaders in proteomics technology, and clinicians, the symposium illuminated potential pathways for proteomics to transform personalized medicine, advancing the cause of more precise diagnostics and targeted therapies.

Proteomics