Multiomics was used to clarify the mechanism by which air pollutants affect chronic obstructive pulmonary disease: A human cohort study.

Exposure to air pollutants has been associated with various adverse health outcomes, including chronic obstructive pulmonary disease (COPD). However, the precise underlying mechanism by which air pollution impacts COPD through remains insufficiently understood. To elucidated the molecular mechanism by which air pollutant exposure contributes to alterations in the gut microbiome and metabolism in AECOPD patients, we employed metagenomics and untargeted metabolomics to analyse the gut microbial, faecal, and serum metabolites. The correlations among air pollutants, gut microbes, serum metabolites, and blood biochemical markers were assessed using generalised additive mixed models and Spearman correlation analysis. The findings revealed that for every 10 µg/m3 increase in PM2.5 concentration, the α-diversity of the gut flora decreased by 2.16% (95% CI: 1.80%-2.53%). We found seven microorganisms that were significantly associated with air pollutants, of which Enterococcus faecium, Bacteroides fragilis, Ruthenibacterium lactatiformans, and Subdoligranulum sp.4_3_54A2FAA were primarily associated with glycolysis. We identified 13 serum metabolites and 17 faecal metabolites significantly linked to air pollutants. Seven of these metabolites, which were strongly associated with air pollutants and blood biochemical indices, were found in both serum and faecal samples. Some of these metabolites, such as 2,5-furandicarboxylic acid, C-8C1P and melatonin, were closely associated with disturbances in lipid and fatty acid metabolism in AECOPD patients. These findings underscore the impact of air pollutants on overall metabolism based on influencing gut microbes and metabolites in AECOPD patients. Moreover, these altered biomarkers establish the biologic connection between air pollutant exposure and AECOPD outcomes.The identification of pertinent biomarkers provides valuable insights for the development of precision COPD prevention strategies.

RNA-seq analyses of multiple meristems of soybean: novel and alternative transcripts, evolutionary and functional implications.

BACKGROUND: Soybean is one of the most important crops, providing large amounts of dietary proteins and edible oil, and is also an excellent model for studying evolution of duplicated genes. However, relative to the model plants Arabidopsis and rice, the present knowledge about soybean transcriptome is quite limited. RESULTS: In this study, we employed RNA-seq to investigate transcriptomes of 11 soybean tissues, for genome-wide discovery of truly expressed genes, and novel and alternative transcripts, as well as analyses of conservation and divergence of duplicated genes and their functional implications. We detected a total of 54,132 high-confidence expressed genes, and identified 6,718 novel transcriptional regions with a mean length of 372 bp. We also provided strong evidence for alternative splicing (AS) events for ~15.9% of the genes with two or more exons. Among them, 1,834 genes exhibited stage-dependent AS, and 202 genes had tissue-biased exon-skipping events. We further defined the conservation and divergence in expression patterns between duplicated gene pairs from recent whole genome duplications (WGDs); differentially expressed genes, tissue preferentially expressed genes, transcription factors and specific gene family members were identified for shoot apical meristem and flower development. CONCLUSIONS: Our results significantly improved soybean gene annotation, and also provide valuable resources for functional genomics and studies of the evolution of duplicated genes from WGDs in soybean.