A RNA-Seq Analysis of the Rat Supraoptic Nucleus Transcriptome: Effects of Salt Loading on Gene Expression.

Magnocellular neurons (MCNs) in the hypothalamo-neurohypophysial system (HNS) are highly specialized to release large amounts of arginine vasopressin (Avp) or oxytocin (Oxt) into the blood stream and play critical roles in the regulation of body fluid homeostasis. The MCNs are osmosensory neurons and are excited by exposure to hypertonic solutions and inhibited by hypotonic solutions. The MCNs respond to systemic hypertonic and hypotonic stimulation with large changes in the expression of their Avp and Oxt genes, and microarray studies have shown that these osmotic perturbations also cause large changes in global gene expression in the HNS. In this paper, we examine gene expression in the rat supraoptic nucleus (SON) under normosmotic and chronic salt-loading SL) conditions by the first time using "new-generation", RNA sequencing (RNA-Seq) methods. We reliably detect 9,709 genes as present in the SON by RNA-Seq, and 552 of these genes were changed in expression as a result of chronic SL. These genes reflect diverse functions, and 42 of these are involved in either transcriptional or translational processes. In addition, we compare the SON transcriptomes resolved by RNA-Seq methods with the SON transcriptomes determined by Affymetrix microarray methods in rats under the same osmotic conditions, and find that there are 6,466 genes present in the SON that are represented in both data sets, although 1,040 of the expressed genes were found only in the microarray data, and 2,762 of the expressed genes are selectively found in the RNA-Seq data and not the microarray data. These data provide the research community a comprehensive view of the transcriptome in the SON under normosmotic conditions and the changes in specific gene expression evoked by salt loading.

Whole transcriptome organisation in the dehydrated supraoptic nucleus.

The supraoptic nucleus (SON) is part of the central osmotic circuitry that synthesises the hormone vasopressin (Avp) and transports it to terminals in the posterior lobe of the pituitary. Following osmotic stress such as dehydration, this tissue undergoes morphological, electrical and transcriptional changes to facilitate the appropriate regulation and release of Avp into the circulation where it conserves water at the level of the kidney. Here, the organisation of the whole transcriptome following dehydration is modelled to fit Zipf's law, a natural power law that holds true for all natural languages, that states if the frequency of word usage is plotted against its rank, then the log linear regression of this is -1. We have applied this model to our previously published euhydrated and dehydrated SON data to observe this trend and how it changes following dehydration. In accordance with other studies, our whole transcriptome data fit well with this model in the euhydrated SON microarrays, but interestingly, fit better in the dehydrated arrays. This trend was observed in a subset of differentially regulated genes and also following network reconstruction using a third-party database that mines public data. We make use of language as a metaphor that helps us philosophise about the role of the whole transcriptome in providing a suitable environment for the delivery of Avp following a survival threat like dehydration.

Hypothalamic transcriptome plasticity in two rodent species reveals divergent differential gene expression but conserved pathways.

We have addressed the question of how different rodent species cope with the life-threatening homeostatic challenge of dehydration at the level of transcriptome modulation in the supraoptic nucleus (SON), a specialised hypothalamic neurosecretory apparatus responsible for the production of the antidiuretic peptide hormone arginine vasopressin (AVP). AVP maintains water balance by promoting water conservation at the level of the kidney. Dehydration evokes a massive increase in the regulated release of AVP from SON axon terminals located in the posterior pituitary, and this is accompanied by a plethora of changes in the morphology, electrophysiological properties, biosynthetic and secretory activity of this structure. Microarray analysis was used to generate a definitive catalogue of the genes expressed in the mouse SON, and to describe how the gene expression profile changes in response to dehydration. Comparison of the genes differentially expressed in the mouse SON as a consequence of dehydration with those of the rat has revealed many similarities, pointing to common processes underlying the function-related plasticity in this nucleus. In addition, we have identified many genes that are differentially expressed in a species-specific manner. However, in many cases, we have found that the hyperosmotic cue can induce species-specific alterations in the expression of different genes in the same pathway. The same functional end can be served by different means, via differential modulation, in different species, of different molecules in the same pathway. We suggest that pathways, rather than specific genes, should be the focus of integrative physiological studies based on transcriptome data.

Whole transcriptome organisation in the dehydrated supraoptic nucleus

The supraoptic nucleus (SON) is part of the central osmotic circuitry that synthesises the hormone vasopressin (Avp) and transports it to terminals in the posterior lobe of the pituitary. Following osmotic stress such as dehydration, this tissue undergoes morphological, electrical and transcriptional changes to facilitate the appropriate regulation and release of Avp into the circulation where it conserves water at the level of the kidney. Here, the organisation of the whole transcriptome following dehydration is modelled to fit Zipf's law, a natural power law that holds true for all natural languages, that states if the frequency of word usage is plotted against its rank, then the log linear regression of this is -1. We have applied this model to our previously published euhydrated and dehydrated SON data to observe this trend and how it changes following dehydration. In accordance with other studies, our whole transcriptome data fit well with this model in the euhydrated SON microarrays, but interestingly, fit better in the dehydrated arrays. This trend was observed in a subset of differentially regulated genes and also following network reconstruction using a third-party database that mines public data. We make use of language as a metaphor that helps us philosophise about the role of the whole transcriptome in providing a suitable environment for the delivery of Avp following a survival threat like dehydration.