Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

Abstract

Background: The Tibetan highland fish, Gymnocypris przewalskii, migrates from Lake Qinghai to its spawning grounds every summer. This seasonal reproduction is critically regulated by intrinsic and extrinsic signals. However, the molecular mechanisms that process environmental oscillations to initiate the seasonal mating are largely unknown.

Results: A transcriptomic analysis was conducted on the brain and gonad of male and female G. przewalskii in reproductive and nonreproductive seasons. We obtained 2034, 760, 1158 and 17,856 differentially expressed genes between the reproductively active and dormant female brain, male brain, ovary and testis. Among these genes, DIO2 was upregulated in the reproductively active brain and gonad of both males and females. Neuroactive ligand-receptor genes were activated in male and female brain. Functional enrichment analysis suggested that retinol metabolism was uniquely stimulated in reproductively active males. Genes involved in GnRH signaling and sex hormone synthesis exhibited higher expression levels in brain and gonad during the reproductive season. A co-expression network classified all the genes into 9 modules. The network pinpointed CDC42 as the hub gene that connected the pathways in responsible for modulating reproduction in G. przewalskii. Meanwhile, the sex pheromone receptor gene prostaglandin receptor was identified to link to multiple endocrine receptors, such as GnRHR2 in the network.

Conclusions: The current study profiled transcriptomic variations between reproductively active and dormant fish, highlighting the potential regulatory mechanisms of seasonal reproduction in G. przewalskii. Our data suggested that the seasonal regulation of reproduction in G. przewalskii was controlled by the external stimulation of photoperiodic variations. The activated transcription of neuroendocrine and sex hormone synthesis genes contributed to seasonal reproduction regulation in G. przewalskii, which was presumably influenced by the increased day-length during the breeding season.

Keywords: Day-length; Neuroendocrine; RNA-seq; Reproductive migration; Seasonality; Tibetan highland fish; WGCNA.

Fig. 1

a Sampling sites. The sampling map was created using ArcGIS v10.1 (ESRI, CA, USA), and processed using Adobe Illustrator CS5 (Adobe System Inc., San Francisco, CA, USA). Data used in the map was downloaded from National Science & Technology Infrastructure of China (http://lake.geodata.cn) and http://www.statsilk.com/maps. Fish photo in (a) belongs to Dr. Kai Zhao. b Annual water temperature (y-axis on the right) and hours of light time (y-axis on left). The water temperature was measured about 0–0.7 m beneath the water surface of the Lake Qinghai. No data on water temperature was available in Jan and Feb due to the icing in the winter of the Lake Qinghai. The light hours reach the peak in May, and keep as the long day during from May to Aug. The decrease in light hours from Jun to Aug is primarily due to the rainy season in the summer. The environmental and ecological data collected from 1988 to 2004 [20]

Fig. 2

Annotation information of the G. przewalskii reference transcriptome. a Annotated unigenes by 4 public libraries. b Percentage of species similarity. c E-value distribution. d Functional classification of unigenes by the KOG database

Fig. 3

Analysis of DEGs between NRS and RS. a Number of DEGs shown by Venn diagram. (b-c) Cluster analysis and heatmap in gonad b and brain c of male and female samples from the RS and NRS. d RT-qPCR validation of DEGs obtained by RNA-seq. The y axis represents the log2FoldChange(RS/NRS). RS and NRS represent the average expression values of 3 biological replicates from each group

Fig. 4

Functional enrichment of DEGs. a KEGG classifications of DEGs from brain and gonad. b Transcriptional comparison of genes in retinol metabolism in brain and testis between NRS and RS. c Expression levels of genes in neuroactive ligand-receptor interaction

Fig. 5

Construction of the coexpression network. a Correlation coefficients between each group and the gene expression in the module. The x-axis and y-axis represented the group and the module, respectively. The secondary KEGG categories that most significantly enriched pathways belonged to were labeled in the parentheses under module names. The grey module contained genes that were unable to classify into any other modules, therefore, the enrichment analysis was not conducted in genes of the grey module. The red and green colors indicated the highest positive and negative correlation between sample groups and modules. The correlation coefficient (1st line) and p-value (2nd line) were labeled. NRSFB: 3 samples of female brain in NRS; NRSFG: 3 samples of female gonad in NRS; NRSMB: 3 samples of male brain in NRS; NRSMG: 3 samples of male gonad in NRS; RSFB: 3 samples of female brain in RS; RSFG: 3 samples of female gonad in RS; RSMB: 3 samples of male brain in RS; RSMG: 3 samples of male gonad in RS. b KEGG functional enrichment of genes in the darkgreen and theh royalblue modules. c Network of genes in the darkgreen module with weight greater than 0.25. The node and edge represent the gene and weight between two genes. The red and green colors of the nodes indicated the high and low connectivity to other nodes. The larger node size also denoted the higher connectivity as well. The hub genes were labeled in red