Diurnal oscillations in human salivary microRNA and microbial transcription
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA479866 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7474390.fastq.gz | Fastqsanger.gz | |||
| SRR7474400.fastq.gz | Fastqsanger.gz | |||
| SRR7474410.fastq.gz | Fastqsanger.gz | |||
| SRR7474420.fastq.gz | Fastqsanger.gz | |||
| SRR7474430.fastq.gz | Fastqsanger.gz |
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Project description:We investigated daily oscillations in salivary miRNA and microbial RNA to explore relationships between these components of the gut-brain-axis and their implications in human health. Nine subjects provided 120 saliva samples at designated times, on repeated days. Samples were divided into three sets for exploration and cross-validation. Identification and quantification of host miRNA and microbial RNA was performed using next generation sequencing. Eleven miRNAs and 11 microbial RNAs demonstrated consistent diurnal oscillation across the first 2 sample sets and accurately predicted collection time in the hold-out set based on multivariate logistic regression modeling. Associations among five circadian miRNAs and four circadian microbial RNAs were observed.
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Project description:The microbiome plays a vital role in human health and disease. Interaction between human hosts and the microbiome occurs through a number of mechanisms, including transcriptomic regulation by microRNA (miRNA). In animal models, circadian variations in miRNA and microbiome elements have been described, but patterns of co-expression and potential diurnal interaction in humans have not. We investigated daily oscillations in salivary miRNA and microbial RNA to explore relationships between these components of the gut-brain-axis and their implications in human health. Nine subjects provided 120 saliva samples at designated times, on repeated days. Samples were divided into three sets for exploration and cross-validation. Identification and quantification of host miRNA and microbial RNA was performed using next generation sequencing. Three stages of statistical analyses were used to identify circadian oscillators: 1) a two-way analysis of variance in the first two sample sets identified host miRNAs and microbial RNAs whose abundance varied with collection time (but not day); 2) multivariate modeling identified subsets of these miRNAs and microbial RNAs strongly-associated with collection time, and evaluated their predictive ability in an independent hold-out sample set; 3) regulation of circadian miRNAs and microbial RNAs was explored in data from autistic children with disordered sleep (n = 77), relative to autistic peers with typical sleep (n = 63). Eleven miRNAs and 11 microbial RNAs demonstrated consistent diurnal oscillation across sample sets and accurately predicted collection time in the hold-out set. Associations among five circadian miRNAs and four circadian microbial RNAs were observed. We termed the 11 miRNAs CircaMiRs. These CircaMiRs had 1,127 predicted gene targets, with enrichment for both circadian gene targets and metabolic signaling processes. Four CircaMiRs had "altered" expression patterns among children with disordered sleep. Thus, novel and correlated circadian oscillations in human miRNA and microbial RNA exist and may have distinct implications in human health and disease.
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