Characterization of the cytokinin-responsive transcriptome in rice

Abstract Background Cytokinin activates transcriptional cascades important for development and the responses to biotic and abiotic stresses. Most of what is known regarding cytokinin-regulated gene expression comes from studies of the dicotyledonous plant Arabidopsis thaliana. To expand the understanding of the cytokinin-regulated transcriptome, we employed RNA-Seq to analyze gene expression in response to cytokinin in roots and shoots of the monocotyledonous plant rice. Results We identified over 4,600 and approximately 2,400 genes differentially expressed in response to cytokinin in roots and shoots respectively. There were some similarities in the sets of cytokinin-regulated genes identified in rice and Arabidopsis, including an up-regulation of genes that act to reduce cytokinin function. Consistent with this, we found that the preferred DNA-binding motif of a rice type-B response regulator is similar to those from Arabidopsis. Analysis of the genes regulated by cytokinin in rice revealed a large number of transcription factors, receptor-like kinases, and genes involved in protein degradation, as well as genes involved in development and the response to biotic stress. Consistent with the over-representation of genes involved in biotic stress, there is a substantial overlap in the genes regulated by cytokinin and those differentially expressed in response to pathogen infection, suggesting that cytokinin plays an integral role in the transcriptional response to pathogens in rice, including the induction of a large number of WRKY transcription factors. Conclusions These results begin to unravel the complex gene regulation after cytokinin perception in a crop of agricultural importance and provide insight into the processes and responses modulated by cytokinin in monocots

Analysis of pollen-specific alternative splicing in Arabidopsis thaliana via semi-quantitative PCR

Alternative splicing enables a single gene to produce multiple mRNA isoforms by varying splice site selection. In animals, alternative splicing of mRNA isoforms between cell types is widespread and supports cellular differentiation. In plants, at least 20% of multi-exon genes are alternatively spliced, but the extent and significance of tissue-specific splicing is less well understood, partly because it is difficult to isolate cells of a single type. Pollen is a useful model system to study tissue-specific splicing in higher plants because pollen grains contain only two cell types and can be collected in large amounts without damaging cells. Previously, we identified pollen-specific splicing patterns by comparing RNA-Seq data from Arabidopsis pollen and leaves. Here, we used semi-quantitative PCR to validate pollen-specific splicing patterns among genes where RNA-Seq data analysis indicated splicing was most different between pollen and leaves. PCR testing confirmed eight of nine alternative splicing patterns, and results from the ninth were inconclusive. In four genes, alternative transcriptional start sites coincided with alternative splicing. This study highlights the value of the low-cost PCR assay as a method of validating RNA-Seq results

Many rice genes are differentially spliced between roots and shoots but cytokinin has minimal effect on splicing

Abstract Alternatively spliced genes produce multiple spliced isoforms, called transcript variants. In differential alternative splicing, transcript variant abundance differs across sample types. Differential alternative splicing is common in animal systems and influences cellular development in many processes, but its extent and significance is not as well known in plants. To investigate differential alternative splicing in plants, we examined RNA‐Seq data from rice seedlings. The data included three biological replicates per sample type, approximately 30 million sequence alignments per replicate, and four sample types: roots and shoots treated with exogenous cytokinin delivered hydroponically or a mock treatment. Cytokinin treatment triggered expression changes in thousands of genes but had negligible effect on splicing patterns. However, many genes were differentially spliced between mock‐treated roots and shoots, indicating that our methods were sufficiently sensitive to detect differential splicing between data sets. Quantitative fragment analysis of reverse transcriptase‐PCR products made from newly prepared rice samples confirmed 9 of 10 differential splicing events between rice roots and shoots. Differential alternative splicing typically changed the relative abundance of splice variants that co‐occurred in a data set. Analysis of a similar (but less deeply sequenced) RNA‐Seq data set from Arabidopsis showed the same pattern. In both the Arabidopsis and rice RNA‐Seq data sets, most genes annotated as alternatively spliced had small minor variant frequencies. Of splicing choices with abundant support for minor forms, most alternative splicing events were located within the protein‐coding sequence and maintained the annotated reading frame. A tool for visualizing protein annotations in the context of genomic sequence (ProtAnnot) together with a genome browser (Integrated Genome Browser) were used to visualize and assess effects of differential splicing on gene function. In general, differentially spliced regions coincided with conserved protein domains, indicating that differential alternative splicing is likely to affect protein function between root and shoot tissue in rice

Air pollution exposure is associated with the gut microbiome as revealed by shotgun metagenomic sequencing

Animal work indicates exposure to air pollutants may alter the composition of the gut microbiota. This study examined relationships between air pollutants and the gut microbiome in young adults residing in Southern California. Our results demonstrate significant associations between exposure to air pollutants and the composition of the gut microbiome using whole-genome sequencing. Higher exposure to 24-hour O3 was associated with lower Shannon diversity index, higher Bacteroides caecimuris, and multiple gene pathways, including L-ornithine de novo biosynthesis as well as pantothenate and coenzyme A biosynthesis I. Among other pollutants, higher NO2 exposure was associated with fewer taxa, including higher Firmicutes. The percent variation in gut bacterial composition that was explained by air pollution exposure was up to 11.2% for O3 concentrations, which is large compared to the effect size for many other covariates reported in healthy populations. This study provides the first evidence of significant associations between exposure to air pollutants and the compositional and functional profile of the human gut microbiome. These results identify O3 as an important pollutant that may alter the human gut microbiome