Comparative transcriptomic analysis of hypothalamus-pituitary-liver axis in bighead carp (Hypophthalmichthys nobilis) with differential growth rate

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Abstract

Background: Growth rate is one of the most important features for aquaculture species and deciphering its regulation mechanism has great significance both in genetics and in economics. Hypothalamus-pituitary growth axis (HP growth axis) or neuro-endocrine axis plays a vital role in growth regulation in different aquaculture animals. Results: In this study, the HP and liver transcriptomes of two female groups (H and L) with phenotypically extreme growth rate were sequenced using RNA-Seq. A total of 30,524 and 22,341 genes were found expressed in the two tissues, respectively. The average expression levels for the two tissues were almost the same, but the median differed significantly. A differential expression analysis between H and L groups identified 173 and 204 differentially expressed genes (DEGs) in HP and liver tissue, respectively. Pathway analysis revealed that DEGs in HP tissue were enriched in regulation of cell proliferation and angiogenesis while in liver tissue these genes were overrepresented in sterol biosynthesis and transportation. Genomic overlapping analyses found that 4 and 5 DEGs were within growth-related QTL in HP and liver tissue respectively. A deeper analysis of these 9 genes revealed 3 genes were functionally linked to the trait of interest. The expression of 2075 lncRNAs in HP tissue and 1490 in liver tissue were also detected, and some of lncRNAs were highly expressed in the two tissues. Conclusions: Above all, the results of the present study greatly contributed to the knowledge of the regulation of growth and then assisted the design of new selection strategies for bighead carp with improved growth-related traits.

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Fu, B., Yu, X., Tong, J., Pang, M., Zhou, Y., Liu, Q., & Tao, W. (2019). Comparative transcriptomic analysis of hypothalamus-pituitary-liver axis in bighead carp (Hypophthalmichthys nobilis) with differential growth rate. BMC Genomics, 20(1). https://doi.org/10.1186/s12864-019-5691-4

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