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Liu X, Gao J, Zhang P, Shi T, Yan B, Azra MN, Baloch WA, Wang P, Gao H. De novo transcriptional analysis of the response to starvation stress in the white ridgetail prawn, Exopalaemon carinicauda. Genomics 2023; 115:110746. [PMID: 37977333 DOI: 10.1016/j.ygeno.2023.110746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 10/27/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023]
Abstract
To study the mechanism of the biomolecular response in Exopalaemon carinicauda to starvation stress, we subjected muscle tissue RNA samples from four stress points, including 0 d(control group), 10 d, 20 d, and 30 d, to starvation stress on white ridgetail prawn with a body weight of 1.41 + 0.42 g, aquaculture water temperature of 23-25 °C, salinity of 26, dissolved oxygen ≥5 mg/L, and pH 8-8.5, Then performed de novo transcriptome assembly and gene expression analysis using BGISEQ-500 with a tag-based digital gene expression (DGE) system. By de novo assembling at the four times, we obtained 28,167, 21,115, 24,497, and 27,080 reads, respectively. The results showed that the stress at 10 d led to no significant difference in the expressed genes, while the stress at 20 d and 30 d showed a significant increase (or decrease) in the expression of 97 (276) and 143 (410) genes, respectively, which were involved in 8 different metabolic pathways. In addition, we detected 2647 unigene transcription factors. Eleven upregulated and sixteen downregulated genes from the different starvation stress groups were choose to verify the reliability of the transcriptome data, and the results showed that the expression trends of these genes were consistent with the results shown by the transcriptome. The analysis of the experimental data and our discussion of the response mechanism of white ridgetail prawn under starvation stress provides a foundation for further screening of the key genes of starvation stress and may help to elucidate their functions.
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Affiliation(s)
- Xue Liu
- Jiangsu Key Laboratory of Marine Bioresources and Environment, Jiangsu Ocean University, Lianyungang 222005, China; Marine Resource Development institute of Jiangsu (Lianyungang), Jiangsu Lianyungang, 222005, China
| | - Jiayi Gao
- Jiangsu Key Laboratory of Marine Bioresources and Environment, Jiangsu Ocean University, Lianyungang 222005, China; Marine Resource Development institute of Jiangsu (Lianyungang), Jiangsu Lianyungang, 222005, China
| | - Pei Zhang
- Jiangsu Key Laboratory of Marine Bioresources and Environment, Jiangsu Ocean University, Lianyungang 222005, China; Marine Resource Development institute of Jiangsu (Lianyungang), Jiangsu Lianyungang, 222005, China
| | - Tingting Shi
- Jiangsu Key Laboratory of Marine Bioresources and Environment, Jiangsu Ocean University, Lianyungang 222005, China; Marine Resource Development institute of Jiangsu (Lianyungang), Jiangsu Lianyungang, 222005, China
| | - Binlun Yan
- Jiangsu Key Laboratory of Marine Bioresources and Environment, Jiangsu Ocean University, Lianyungang 222005, China; Marine Resource Development institute of Jiangsu (Lianyungang), Jiangsu Lianyungang, 222005, China; Co-Innovation Center of Jiangsu Marine Bio-industry Technology, Lianyungang, Jiangsu 222005, China; The Jiangsu Provincial Platform for Conservation and Utilization of Agricultural Germplasm, Nanjing, Jiangsu 210014, China
| | - Mohamad Nor Azra
- Institute of Climate Adaptation and Marine Biotechnology, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
| | - Wazir Ali Baloch
- Department of Freshwater Biology and Fisheries, University of Sindh, Jamshoro 76080, Pakistan.
| | - Panpan Wang
- Jiangsu Key Laboratory of Marine Bioresources and Environment, Jiangsu Ocean University, Lianyungang 222005, China; Marine Resource Development institute of Jiangsu (Lianyungang), Jiangsu Lianyungang, 222005, China; Co-Innovation Center of Jiangsu Marine Bio-industry Technology, Lianyungang, Jiangsu 222005, China; The Jiangsu Provincial Platform for Conservation and Utilization of Agricultural Germplasm, Nanjing, Jiangsu 210014, China
| | - Huan Gao
- Jiangsu Key Laboratory of Marine Bioresources and Environment, Jiangsu Ocean University, Lianyungang 222005, China; Marine Resource Development institute of Jiangsu (Lianyungang), Jiangsu Lianyungang, 222005, China; Co-Innovation Center of Jiangsu Marine Bio-industry Technology, Lianyungang, Jiangsu 222005, China; The Jiangsu Provincial Platform for Conservation and Utilization of Agricultural Germplasm, Nanjing, Jiangsu 210014, China.
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Yang F, Liu Z, Zhao M, Mu Q, Che T, Xie Y, Ma L, Mi L, Li J, Zhao Y. Skin transcriptome reveals the periodic changes in genes underlying cashmere (ground hair) follicle transition in cashmere goats. BMC Genomics 2020; 21:392. [PMID: 32503427 PMCID: PMC7275469 DOI: 10.1186/s12864-020-06779-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 05/13/2020] [Indexed: 02/06/2023] Open
Abstract
Background Cashmere goats make an outstanding contribution to the livestock textile industry and their cashmere is famous for its slenderness and softness and has been extensively studied. However, there are few reports on the molecular regulatory mechanisms of the secondary hair follicle growth cycle in cashmere goats. In order to explore the regular transition through the follicle cycle and the role of key genes in this cycle, we used a transcriptome sequencing technique to sequence the skin of Inner Mongolian cashmere goats during different months. We analyzed the variation and difference in genes throughout the whole hair follicle cycle. We then verified the regulatory mechanism of the cashmere goat secondary hair follicle growth cycle using fluorescence quantitative PCR. Results The growth cycle of cashmere hair could be divided into three distinct periods: a growth period (March–September), a regression period (September–December), and a resting period (December–March). The results of differential gene analyses showed that March was the most significant month. Cluster analysis of gene expression throughout the whole growth cycle further supported the key nodes of the three periods of cashmere growth, and the differential gene expression of keratin corresponding to the ground haircashmere growth cycle further supported the results from tissue slices. Quantitative fluorescence analysis showed that KAP3–1, KRTAP 8–1, and KRTAP 24–1 genes had close positive correlation with the cashmere growth cycle, and their regulation was consistent with the growth cycle of cashmere. Conclusion The growth cycle of cashmere cashmere could be divided into three distinct periods: a growth period (March–September), a regression period (September–December) and a resting period (December–March). March was considered to be the beginning of the cycle. KAP and KRTAP showed close positive correlation with the growth cycle of secondary hair follicle cashmere growth, and their regulation was consistent with the cashmere growth cycle. But hair follicle development-related genes are expressed earlier than cashmere growth, indicating that cycle regulation could alter the temporal growth of cashmere. This study laid a theoretical foundation for the study of the cashmere development cycle and provided evidence for key genes during transition through the cashmere cycle. Our study provides a theoretical basis for cashmere goat breeding.
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Affiliation(s)
- Feng Yang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Zhihong Liu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Meng Zhao
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Qing Mu
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Tianyu Che
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Yuchun Xie
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Lina Ma
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Lu Mi
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Jinquan Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China.
| | - Yanhong Zhao
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, 010018, China.
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