ABSTRACT
Comparative metabolomics plays a crucial role in investigating gene function, exploring metabolite evolution, and accelerating crop genetic improvement. However, a systematic platform for comparing intra- and cross-species metabolites is currently lacking. Here, we report the Plant Comparative Metabolome Database (PCMD; http://yanglab.hzau.edu.cn/PCMD), a multilevel comparison database based on predicted metabolic profiles in 530 plant species. PCMD serves as a platform for comparing metabolite characteristics at various levels, including species, metabolites, pathways, and biological taxonomy. The database also provides a series 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. In addition, PCMD establishes a unified system based on existing metabolite-related databases by standardizing metabolite numbering. PCMD is the most species-rich comparative plant metabolomics database currently available, and a case study demonstrated its capability to provide new insights into understanding plant metabolic diversity.
ABSTRACT
Domesticated herbivores are an important agricultural resource that play a critical role in global food security, particularly as they can adapt to varied environments, including marginal lands. An understanding of the molecular basis of their biology would contribute to better management and sustainable production. Thus, we conducted transcriptome sequencing of 100 to 105 tissues from two females of each of seven species of herbivore (cattle, sheep, goats, sika deer, horses, donkeys, and rabbits) including two breeds of sheep. The quality of raw and trimmed reads was assessed in terms of base quality, GC content, duplication sequence rate, overrepresented k-mers, and quality score distribution with FastQC. The high-quality filtered RNA-seq raw reads were deposited in a public database which provides approximately 54 billion high-quality paired-end sequencing reads in total, with an average mapping rate of ~93.92%. Transcriptome databases represent valuable resources that can be used to study patterns of gene expression, and pathways that are related to key biological processes, including important economic traits in herbivores.