Biology subjects

Qing-Yong, Y.

Publications and source records attributed to Qing-Yong, Y..

2 recordsLinked to original sources

bioRxiv2023

PCMD: A Multilevel Comparison Database of Intra- and Cross-species Metabolic Profiling in 530 Plant Species

Comparative metabolomics plays a crucial role in understanding gene function, exploring metabolite evolution, and improving crop genetic breeding. However, a systematic platform for comparing intra- and cross-species metabolites is currently lacking. In this study, we present the plant comparative metabolome database (PCMD; http://yanglab.hzau.edu.cn/PCMD), a comprehensive multi-level comparison database encompassing intra- and cross-species metabolic profiling in 530 plants. Remarkably, PCMD offers a multi-level platform for comparative metabolite analysis, allowing for the examination of metabolite characteristics across species at various levels including species, metabolites, pathways, and biological taxonomy. In addition, PCMD standardizes metabolite numbering, establishing a uniform system based on existing metabolite-related databases. The database also provides a range of user-friendly online tools, such as Species-comparison, Metabolites-enrichment, and ID conversion, enabling users to perform comparisons and enrichment analyses of metabolites across different species. PCMD stands out as the most comprehensive and species-rich comparative plant metabolomics database currently available, as demonstrated by two case studies that highlight its ability to supplement phylogenetic similarity mining among species through phylogenetic trees and offer new insights into the diversity and species-specificity of metabolites.

bioinformatics↗

bioRxiv2023

BnIR: a multi-omics collaborative resource and tool platform for Brassica napus biological study

In the post-GWAS era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we constructed a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms. Short SummaryIn this study, we developed BnIR (http://yanglab.hzau.edu.cn/BnIR), a multi-omics database for rapeseed that integrates six omics datasets and "variation-gene expression-phenotype" associations. The database is equipped with a range of multi-omics tools for streamlined browsing and analysis. Through multiple case studies, we demonstrated BnIRs potential to identify candidate genes associated with specific traits and investigate their regulatory mechanisms.

bioinformatics↗