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Zhu T, Du J, Song H, Lei C, Cen Y, Wang C, Li S. Whole genome resequencing reveals the correlation between selection signatures and adaptability of Micropterus salmoides to artificial fed. Sci Rep 2024; 14:30058. [PMID: 39627258 PMCID: PMC11614881 DOI: 10.1038/s41598-024-80904-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Accepted: 11/22/2024] [Indexed: 12/06/2024] Open
Abstract
Largemouth bass (Micropterus salmoides, LMB) is an important aquaculture species due to its excellent flesh quality and environmental adaptability. It has been continuously introduced to many countries and cultured for decades. Here, an LMB population was used for selective breeding to improve growth rate and feed adaptability. After five generations of breeding, the growth rate improved by 38%, and feed adaptability improved by 22% compared to the non-breeding population. To study the underlying genetic mechanism, 100 LMB from the breeding population and 100 from the non-breeding population were sampled for whole-genome resequencing. The population genetics analysis shows that the breeding population has a higher inbreeding coefficient and linkage disequilibrium (LD) level, a lower nucleic acid diversity and effective population size (Ne). Using [Formula: see text] (fixation index), we found that the average [Formula: see text] value between the two populations was 0.07, with the highest [Formula: see text] value reaching 0.38, which overlaps with the trypsin gene. Additionally, other genes exhibiting high [Formula: see text] values are associated with functions such as neural development, glucose metabolism, and growth. Using [Formula: see text] and nucleic acid diversity as criteria, we identified 698 genes that are positively selected in the breeding population, and gene functional enrichment analysis shows that 36 genes are related to the olfactory receptor pathway. Overall, our study found that multiple genes were selected in the LMB breeding population. These genes may be associated with adaptation and digestion of artificial feed in fish.
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Affiliation(s)
- Tao Zhu
- Key Laboratory of Tropical and Subtropical Fishery Resources Application and Cultivation, Ministry of Agriculture and Rural Affairs, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China
- College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China
| | - Jinxing Du
- Key Laboratory of Tropical and Subtropical Fishery Resources Application and Cultivation, Ministry of Agriculture and Rural Affairs, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China
| | - Hongmei Song
- Key Laboratory of Tropical and Subtropical Fishery Resources Application and Cultivation, Ministry of Agriculture and Rural Affairs, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China
| | - Caixia Lei
- Key Laboratory of Tropical and Subtropical Fishery Resources Application and Cultivation, Ministry of Agriculture and Rural Affairs, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China
| | - Yingshen Cen
- Foshan Jiyurunda Fishery Technology Co. Ltd., Foshan, 528247, China
| | - Chenghui Wang
- College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China
| | - Shengjie Li
- Key Laboratory of Tropical and Subtropical Fishery Resources Application and Cultivation, Ministry of Agriculture and Rural Affairs, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
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Pan W, Liang M, You Y, Li Z, Weng S, He J, Guo C. Viral genomic methylation and the interspecies evolutionary relationships of ranavirus. PLoS Pathog 2024; 20:e1012736. [PMID: 39585924 PMCID: PMC11627377 DOI: 10.1371/journal.ppat.1012736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Revised: 12/09/2024] [Accepted: 11/05/2024] [Indexed: 11/27/2024] Open
Abstract
Ranaviruses are capable of infecting both wild and farmed fish, amphibians, and reptiles, leading to significant economic losses and ecological risks. Currently, ranaviruses have been found in at least 175 species spanning six continents. Except for Singapore grouper iridovirus (SGIV), ranavirus genomes are generally regarded as highly methylated. Nevertheless, our comprehension of the methylation characteristics within ranaviruses remains limited. Despite the numerous genomes currently included in the GenBank database, a complete phylogenetic tree for ranaviruses has not yet been determined, and interspecific evolutionary relationships among ranaviruses have not been thoroughly investigated. In this study, the whole-genome methylation profile of mandarin fish ranavirus (MRV; a ranavirus) was investigated, revealing a methylation level of 16.04%, and hypomethylation of the MRV genome was detrimental to viral replication, speculating the genome methylation may play an important role in MRV replication. Furthermore, by combining with whole-genome DNA sequence phylogenetic analyses, we propose the possibility of an interspecies evolutionary relationship among ranaviruses, with the presence of four distinct evolutionary lineages within ranavirus evolution: "SGIV, SCRAV(MRV/LMBV), EHNV/ENARV/ATV, and CMTV/FV3", which might be also supported by the genomic collinearity, natural host range and host habitats. Furthermore, ranavirus genomic methylation levels may provide additional evidence for this hypothesis, but further proof is needed. Our work enhances the understanding of the role of genome methylation in ranaviruses and is beneficial for the prevention and control of ranavirus diseases; simultaneously, the proposed evolutionary hypothesis of ranavirus provides novel insights and ideas for exploring the evolutionary trajectory of viruses.
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Affiliation(s)
- Weiqiang Pan
- School of Marine Sciences, State Key Laboratory for Biocontrol / Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory of Aquatic Economic Animals & Guangdong Provincial Observation and Research Station for Marine Ranching of the Lingdingyang Bay, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Mincong Liang
- School of Marine Sciences, State Key Laboratory for Biocontrol / Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory of Aquatic Economic Animals & Guangdong Provincial Observation and Research Station for Marine Ranching of the Lingdingyang Bay, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yanlin You
- School of Marine Sciences, State Key Laboratory for Biocontrol / Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory of Aquatic Economic Animals & Guangdong Provincial Observation and Research Station for Marine Ranching of the Lingdingyang Bay, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhimin Li
- School of Marine Sciences, State Key Laboratory for Biocontrol / Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory of Aquatic Economic Animals & Guangdong Provincial Observation and Research Station for Marine Ranching of the Lingdingyang Bay, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Shaoping Weng
- School of Marine Sciences, State Key Laboratory for Biocontrol / Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory of Aquatic Economic Animals & Guangdong Provincial Observation and Research Station for Marine Ranching of the Lingdingyang Bay, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jianguo He
- School of Marine Sciences, State Key Laboratory for Biocontrol / Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory of Aquatic Economic Animals & Guangdong Provincial Observation and Research Station for Marine Ranching of the Lingdingyang Bay, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Changjun Guo
- School of Marine Sciences, State Key Laboratory for Biocontrol / Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Province Key Laboratory of Aquatic Economic Animals & Guangdong Provincial Observation and Research Station for Marine Ranching of the Lingdingyang Bay, Sun Yat-sen University, Guangzhou, Guangdong, China
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Gao K, He Z, Xiong J, Chen Q, Lai B, Liu F, Chen P, Chen M, Luo W, Huang J, Ding W, Wang H, Pu Y, Zheng L, Jiao Y, Zhang M, Tang Z, Yue Q, Yang D, Yan T. Population structure and adaptability analysis of Schizothorax o'connori based on whole-genome resequencing. BMC Genomics 2024; 25:145. [PMID: 38321406 PMCID: PMC10845765 DOI: 10.1186/s12864-024-09975-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 01/04/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Schizothorax o'connori is an endemic fish distributed in the upper and lower reaches of the Yarlung Zangbo River in China. It has experienced a fourth round of whole gene replication events and is a good model for exploring the genetic differentiation and environmental adaptability of fish in the Qinghai-Tibet Plateau. The uplift of the Qinghai-Tibet Plateau has led to changes in the river system, thereby affecting gene exchange and population differentiation between fish populations. With the release of fish whole genome data, whole genome resequencing has been widely used in genetic evolutionary analysis and screening of selected genes in fish, which can better elucidate the genetic basis and molecular environmental adaptation mechanisms of fish. Therefore, our purpose of this study was to understand the population structure and adaptive characteristics of S. o'connori using the whole-genome resequencing method. RESULTS The results showed that 23,602,746 SNPs were identified from seven populations, mostly distributed on chromosomes 2 and 23. There was no significant genetic differentiation between the populations, and the genetic diversity was relatively low. However, the Zangga population could be separated from the Bomi, Linzhi, and Milin populations in the cluster analysis. Based on historical dynamics analysis of the population, the size of the ancestral population of S. o'connori was affected by the late accelerated uplift of the Qinghai Tibet Plateau and the Fourth Glacial Age. The selected sites were mostly enriched in pathways related to DNA repair and energy metabolism. CONCLUSION Overall, the whole-genome resequencing analysis provides valuable insights into the population structure and adaptive characteristics of S. o'connori. There was no obvious genetic differentiation at the genome level between the S. o'connori populations upstream and downstream of the Yarlung Zangbo River. The current distribution pattern and genetic diversity are influenced by the late accelerated uplift of the Qinghai Tibet Plateau and the Fourth Ice Age. The selected sites of S. o'connori are enriched in the energy metabolism and DNA repair pathways to adapt to the low temperature and strong ultraviolet radiation environment at high altitude.
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Affiliation(s)
- Kuo Gao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Zhi He
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Jinxin Xiong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Qiqi Chen
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Bolin Lai
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Fei Liu
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Ping Chen
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Mingqiang Chen
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Wenjie Luo
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Junjie Huang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Wenxiang Ding
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Haochen Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Yong Pu
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Li Zheng
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Yuanyuan Jiao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Mingwang Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Ziting Tang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
| | - Qingsong Yue
- Huadian Tibet Hydropower Development Co.,Ltd, Dagu Hydropower Station, Sangri, 856200, Shannan, China
| | - Deying Yang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
| | - Taiming Yan
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
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