Abstract
Circadian rhythms are innate biological systems that control everyday behavior and physiology. Furthermore, bilateral interaction between the host's circadian rhythm and the gut microbes influences a variety of health ramifications, including metabolic diseases, obesity, and mental health including GALT physiology and the microbiome population. Therefore, we are studying the correlation between differential gene expression in the chicken brain and microbiota abundance during circadian rhythms. To understand this, we raised freshly hatched chicks under two photoperiod treatments: normal photoperiod (NP = 12/12 LD) and extended photoperiod (EP 23/1 LD). The chicks were randomly assigned to one of two treatments. After 21 days of circadian entrainment, the chicks were euthanized at nine time points spaced six hours apart over 48 h to characterize the brain transcriptomes. Each sample's RNA was extracted, and 36 mRNA libraries were generated and sequenced using Illumina technology, followed by data processing, count data generation, and differential gene expression analysis. We generated an average of 17.5 million reads per library for 237.9 M reads. When aligned to the Galgal6 reference genome, 11,867 genes had detectable expression levels, with a common dispersion value of 0.105. To identify the genes that follow 24 h rhythms, counts per million data were performed in DiscoRhythm. We discovered 577 genes with Cosinor and 417 with the JTK cycle algorithm that exhibit substantial rhythms. We used weighted gene co-expression network analysis (WGCNA) to analyze the correlation between differentially expressed genes and microbiota abundance. The most enriched pathways included aldosterone-regulated sodium reabsorption, endocrine and other factor-regulated calcium reabsorption, GABAergic synapse, oxidative phosphorylation, serotonergic synapse, dopaminergic synapse and circadian entrainment. This study builds on our previous study, and adds new findings about the specific interactions and co-regulation of the brain transcriptome and the gut microbiota. The interaction between gut microbiota and host gene expression highlights the potential benefits of microbiome-modulation approaches to improve gut health and performance in poultry.
Keywords:
RNA-sequencing; WGCNA; biological rhythms; chicken; co-expression; gut microbes.
