Genomic and Transcriptomic Landscape and Evolutionary Dynamics of Heat Shock Proteins in Spotted Sea Bass (Lateolabrax maculatus) under Salinity Change and Alkalinity Stress
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Genome-Wide Identification and Annotation of Hsp Families in L. maculatus
2.2. Phylogenetic Analysis of Hsp Families
2.3. Expression of LmHsp Genes through Transcriptome Analysis
2.4. Protein-Protein Interaction and Co-Expression Analysis
2.5. Molecular Evolution Analysis
3. Results and Discussion
3.1. Genomic Landscape, Functional Domain, and Phylogeny of Hsp Superfamily in L. maculatus
3.2. Diverse Expression of LmHsp Genes among L. maculatus Normal Tissues
3.3. Regulated Expression of LmHsp Genes in Response to Salinity Change and Alkalinity Stress
3.4. Coordinated Regulation of LmHsp Co-Chaperones under Alkalinity Stress
3.5. Evolutionary Dynamics of LmHsp Families in L. maculatus
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Ritossa, F.M. A new puffing pattern induced by heat shock and DNP in Drosophila. Experientia 1962, 18, 515–523. [Google Scholar] [CrossRef]
- Whitley, D.; Goldberg, S.P.; Jordan, W.D. Heat shock proteins: A review of the molecular chaperones. J. Vasc. Surg. 1999, 29, 748–751. [Google Scholar] [CrossRef] [Green Version]
- Basu, N.; Todgham, A.E.; Ackerman, P.A.; Bibeau, M.R.; Nakano, K.; Schulte, P.M.; Iwama, G.K. Heat shock protein genes and their functional significance in fish. Gene 2002, 295, 173–183. [Google Scholar] [CrossRef]
- Feder, M.E.; Hofmann, G.E. Heat-shock proteins, molecular chaperones, and the stress response: Evolutionary and ecological physiology. Annu. Rev. Physiol. 1999, 61, 243–282. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dabbaghizadeh, A.; Tanguay, R.M. Structural and functional properties of proteins interacting with small heat shock proteins. Cell Stress Chaperones 2020, 25, 629–637. [Google Scholar] [CrossRef]
- Faust, O.; Abayev-Avraham, M.; Wentink, A.S.; Maurer, M.; Nillegoda, N.B.; London, N.; Bukau, B.; Rosenzweig, R. HSP40 proteins use class-specific regulation to drive HSP70 functional diversity. Nature 2020, 587, 489–494. [Google Scholar] [CrossRef] [PubMed]
- Bie, A.S.; Cömert, C.; Körner, R.; Corydon, T.J.; Palmfeldt, J.; Hipp, M.S.; Hartl, F.U.; Bross, P. An inventory of interactors of the human HSP60/HSP10 chaperonin in the mitochondrial matrix space. Cell Stress Chaperones 2020, 25, 407–416. [Google Scholar] [CrossRef]
- Genest, O.; Wickner, S.; Doyle, S.M. Hsp90 and Hsp70 chaperones: Collaborators in protein remodeling. J. Biol. Chem. 2019, 294, 2109–2120. [Google Scholar] [CrossRef] [Green Version]
- Rosenzweig, R.; Nillegoda, N.B.; Mayer, M.P.; Bukau, B. The Hsp70 chaperone network. Nat. Rev. Mol. Cell Biol. 2019, 20, 665–680. [Google Scholar] [CrossRef]
- Mayer, M.P.; Le Breton, L. Hsp90: Breaking the symmetry. Mol. Cell 2015, 58, 8–20. [Google Scholar] [CrossRef] [Green Version]
- Jiang, F.; Chang, G.; Li, Z.; Abouzaid, M.; Du, X.; Hull, J.; Ma, W.; Lin, Y. The HSP/co-chaperone network in environmental cold adaptation of Chilo suppressalis. Int. J. Biol. Macromol. 2021, 187, 780–788. [Google Scholar] [CrossRef] [PubMed]
- Chen, B.; Feder, M.E.; Kang, L. Evolution of heat-shock protein expression underlying adaptive responses to environmental stress. Mol. Ecol. 2018, 27, 3040–3054. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kim, B.M.; Rhee, J.S.; Jeong, C.B.; Seo, J.S.; Park, G.S.; Lee, Y.M.; Lee, J.S. Heavy metals induce oxidative stress and trigger oxidative stress-mediated heat shock protein (hsp) modulation in the intertidal copepod Tigriopus japonicus. Comp. Biochem. Physiol. C Toxicol. Pharmacol. 2014, 166, 65–74. [Google Scholar] [CrossRef] [PubMed]
- Cantinha, R.D.S.; Borrely, S.I.; Oguiura, N.; Pereira, C.A.d.B.; Rigolon, M.M.; Nakano, E. HSP70 expression in Biomphalaria glabrata snails exposed to cadmium. Ecotoxicol. Environ. Saf. 2017, 140, 18–23. [Google Scholar] [CrossRef]
- Ulaje, S.A.; Lluch-Cota, S.E.; Sicard, M.T.; Ascencio, F.; Cruz-Hernández, P.; Racotta, I.S.; Rojo-Arreola, L. Litopenaeus vannamei oxygen consumption and HSP gene expression at cyclic conditions of hyperthermia and hypoxia. J. Therm. Biol. 2020, 92, 102666. [Google Scholar] [CrossRef]
- Cheng, J.; Xun, X.; Kong, Y.; Wang, S.; Yang, Z.; Li, Y.; Kong, D.; Wang, S.; Zhang, L.; Hu, X.; et al. Hsp70 gene expansions in the scallop Patinopecten yessoensis and their expression regulation after exposure to the toxic dinoflagellate Alexandrium catenella. Fish Shellfish Immunol. 2016, 58, 266–273. [Google Scholar] [CrossRef]
- Hu, B.; Li, M.; Yu, X.; Xun, X.; Lu, W.; Li, X.; Li, Y.; Lou, J.; Wang, S.; Zhang, L.; et al. Diverse expression regulation of Hsp70 genes in scallops after exposure to toxic Alexandrium dinoflagellates. Chemosphere 2019, 234, 62–69. [Google Scholar] [CrossRef]
- Lei, Q.N.; Wu, Y.Y.; Liang, H.Y.; Wang, Z.X.; Zheng, Z.; Deng, Y.W. Molecular cloning and expression analysis of heat shock protein 20 (HSP20) from the pearl oyster Pinctada martensii. Genet. Mol. Res. 2016, 15, 10. [Google Scholar] [CrossRef]
- Xie, Y.; Song, L.; Weng, Z.; Liu, S.; Liu, Z. Hsp90, Hsp60 and sHsp families of heat shock protein genes in channel catfish and their expression after bacterial infections. Fish Shellfish Immunol. 2015, 44, 642–651. [Google Scholar] [CrossRef]
- Song, L.; Zhang, J.; Li, C.; Yao, J.; Jiang, C.; Li, Y.; Liu, S.; Liu, Z. Genome-wide identification of hsp40 genes in channel catfish and their regulated expression after bacterial infection. PLoS ONE 2014, 9, e115752. [Google Scholar] [CrossRef] [Green Version]
- Song, L.; Zhao, Y.; Song, Y.; Zhao, L.; Ma, C.; Zhao, J. Effects of saline-alkaline water on growth performance, nutritional processing, and immunity in Nile tilapia (Oreochromis niloticus). Aquaculture 2021, 544, 737036. [Google Scholar] [CrossRef]
- Islam, M.J.; Kunzmann, A.; Slater, M.J. Extreme winter cold-induced osmoregulatory, metabolic, and physiological responses in European seabass (Dicentrarchus labrax) acclimatized at different salinities. Sci. Total Environ. 2021, 771, 145202. [Google Scholar] [CrossRef]
- Islam, M.J.; Slater, M.J.; Kunzmann, A. What metabolic, osmotic and molecular stress responses tell us about extreme ambient heatwave impacts in fish at low salinities: The case of European seabass, Dicentracus labrax. Sci. Total Environ. 2020, 749, 141458. [Google Scholar] [CrossRef]
- Zhang, M.; Li, L.; Liu, Y.; Gao, X. Effects of sudden drop in salinity on osmotic pressure regulation and antioxidant defense mechanism of Scapharca subcrenata. Front. Physiol. 2020, 11, 884. [Google Scholar]
- Yokogawa, K.; Seki, S. Morphological and genetic differences between Japanese and Chinese sea bass of the genus Lateolabrax. Jpn. J. Ichthyol. 1995, 41, 437–445. [Google Scholar]
- Tian, Y.; Wen, H.; Qi, X.; Zhang, X.; Li, Y. Identification of mapk gene family in Lateolabrax maculatus and their expression profiles in response to hypoxia and salinity challenges. Gene 2019, 684, 20–29. [Google Scholar] [CrossRef]
- Wang, L.Y.; Tian, Y.; Wen, H.S.; Yu, P.; Liu, Y.; Qi, X.; Gao, Z.C.; Zhang, K.Q.; Li, Y. Slc4 gene family in spotted sea bass. (Lateolabrax maculatus): Structure, evolution, and expression profiling in response to alkalinity stress and salinity changes. Genes 2020, 11, 1271. [Google Scholar] [CrossRef]
- Schultz, J.; Copley, R.R.; Doerks, T.; Ponting, C.P.; Bork, P. SMART: A web-based tool for the study of genetically mobile domains. Nucleic Acids Res. 2000, 28, 231–234. [Google Scholar] [CrossRef]
- El-Gebali, S.; Mistry, J.; Bateman, A.; Eddy, S.R.; Luciani, A.; Potter, S.C.; Qureshi, M.; Richardson, L.J.; Salazar, G.A.; Smart, A.; et al. The Pfam protein families database in 2019. Nucleic Acids Res. 2019, 47, D427–D432. [Google Scholar] [CrossRef]
- Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An integrative toolkit developed for interactive analyses of big biological data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef]
- Edgar, R.C. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004, 32, 1792–1797. [Google Scholar] [CrossRef] [Green Version]
- Trifinopoulos, J.; Nguyen, L.T.; von Haeseler, A.; Minh, B.Q. W-IQ-TREE: A fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res. 2016, 44, W232–W235. [Google Scholar]
- Letunic, I.; Bork, P. Interactive tree of life (iTOL) v3: An online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 2016, 44, W242–W245. [Google Scholar] [CrossRef]
- Pertea, M.; Kim, D.; Pertea, G.M.; Leek, J.T.; Salzberg, S.L. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 2016, 11, 1650–1667. [Google Scholar] [CrossRef]
- Tian, Y.; Wen, H.; Qi, X.; Zhang, X.; Liu, S.; Li, B.; Sun, Y.; Li, J.; He, F.; Yang, W.; et al. Characterization of full-length transcriptome sequences and splice variants of Lateolabrax maculatus by single-molecule long-read sequencing and their involvement in salinity regulation. Front. Genet. 2019, 10, 1126. [Google Scholar] [CrossRef]
- Robinson, M.D.; McCarthy, D.J.; Smyth, G.K. EdgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26, 139–140. [Google Scholar] [CrossRef] [Green Version]
- Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13, 2498–2504. [Google Scholar] [CrossRef]
- Kumar, S.; Stecher, G.; Tamura, K. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 2016, 33, 1870–1874. [Google Scholar] [CrossRef] [Green Version]
- Gao, F.; Chen, C.; Arab, D.A.; Du, Z.; He, Y.; Ho, S. EasyCodeML: A visual tool for analysis of selection using CodeML. Ecol. Evol. 2019, 9, 3891–3898. [Google Scholar] [CrossRef] [Green Version]
- Yang, Z. PAML 4: Phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 2007, 24, 1586–1591. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kelley, L.A.; Mezulis, S.; Yates, C.M.; Wass, M.N.; Sternberg, M.J.E. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc. 2015, 10, 845–858. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Glasauer, S.M.; Neuhauss, S.C. Whole-genome duplication in teleost fishes and its evolutionary consequences. Mol. Genet. Genom. 2014, 289, 1045–1060. [Google Scholar] [CrossRef] [Green Version]
- Kriehuber, T.; Rattei, T.; Weinmaier, T.; Bepperling, A.; Haslbeck, M.; Buchner, J. Independent evolution of the core domain and its flanking sequences in small heat shock proteins. FASEB J. 2010, 24, 3633–3642. [Google Scholar] [CrossRef]
- Haslbeck, M.; Weinkauf, S.; Buchner, J. Small heat shock proteins: Simplicity meets complexity. J. Biol. Chem. 2019, 294, 2121–2132. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Brocchieri, L.; Macario, E.C.d.; Macario, A.J. Hsp70 genes in the human genome: Conservation and differentiation patterns predict a wide array of overlapping and specialized functions. BMC Evol. Biol. 2008, 8, 19. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Song, L.; Li, C.; Xie, Y.; Liu, S.; Zhang, J.; Yao, J.; Jiang, C.; Li, Y.; Liu, Z. Genome-wide identification of Hsp70 genes in channel catfish and their regulated expression after bacterial infection. Fish Shellfish Immunol. 2016, 49, 154–162. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kokou, F.; Con, P.; Barki, A.; Nitzan, T.; Slosman, T.; Mizrahi, I.; Cnaani, A. Short- and long-term low-salinity acclimation effects on the branchial and intestinal gene expression in the European seabass (Dicentrarchus labrax). Comp. Biochem. Physiol. A 2019, 231, 11–18. [Google Scholar] [CrossRef] [PubMed]
- Huang, X.; Li, S.; Gao, Y.; Zhan, A. Genome-wide identification, characterization and expression analyses of heat shock protein-related genes in a highly invasive ascidian Ciona savignyi. Front. Physiol. 2018, 9, 1043. [Google Scholar] [CrossRef] [Green Version]
- Hoter, A.; El-Sabban, M.E.; Naim, H.Y. The HSP90 Family: Structure, regulation, function, and implications in health and disease. Int. J. Mol. Sci. 2018, 19, 2560. [Google Scholar] [CrossRef] [Green Version]
- Murphy, M.E. The HSP70 family and cancer. Carcinogenesis 2013, 34, 1181–1188. [Google Scholar] [CrossRef] [Green Version]
Gene ID | p Value | Positive Selected Sites |
---|---|---|
Hspa1.1 | 1.0000 | / |
Hspa5 | 1.0000 | / |
Hspa12a | 0.0534 | 8 S 0.919 |
Hspa12b2 | 0.0000 | 32 P 0.958 *, 36 T 0.918, 39 V 0.935, 41 L 0.907, 43 G 0.923, 46 P 0.936, 49 R 0.906, 112 C 0.903, 321 D 0.995 **, 323 T 1.000 **, 327 I 0.907, 339 K 0.999 **, 340 A 0.998 **, 341 S 0.929, 343 E 0.999 **, 344 L 0.963 *, 346 A 1.000 **, 347 K 1.000 **, 351 R 0.998 **, 353 V 0.999 **, 355 F 0.997 **, 366 P 0.999 **, 367 M 0.997 **, 368 L 0.998 **, 370 K 0.999 **, 371 A 0.998 **, 372 V 0.963 *, 374 K 1.000 **, 375 A 0.999 **, 377 G 0.999 **, 379 T 1.000 **, 384 I 0.963 *, 408 S 1.000 **, 409 Q 1.000 **, 411 H 0.997 **, 418 L 1.000 **, 419 F 0.866, 420 D 0.997 ** |
Hspa13 | 0.0039 | / |
Hsp90aa1.2 | 0.0000 | 16 G 0.908, 22 D 0.916, 431 M 0.978 *, 432 H 0.996 **, 488 D 0.974 *, 489 M 0.982 *, 491 F 1.000 **, 492 V 0.974 * |
Hsp90b1 | 0.0000 | 723 S 0.983 *, 791 D 0.998 **, 965 H 0.981 *, 1099 E 0.940 |
Dnajb4 | 0.6613 | 239 N 0.861 |
Dnajb5_10016268 | 1.0000 | 289 Y 0.507 |
Dnajb11 | 1.0000 | / |
Dnajb12 | 1.0000 | / |
Dnajc5ga | 1.0000 | / |
Dnajc9_10000949 | 0.0079 | 77 R 0.825, 95 K 0.961 *, 96 E 0.990 *, 97 A 0.522, 109 V 0.978 *, 130 V 0.980 *, 141 K 0.930, 204 V 0.921, 205 Q 0.896, 206 H 0.944, 207 Q 0.791, 211 D 0.921, 216 S 0.596, 220 C 0.970*, 244 F 0.710, 269 A 0.614, 276 M 0.650, 283 D 0.911, 286 V 0.972 *, 318 S 0.661, 320 D 0.976 *, 338 N 0.994 **, 350 E 0.700 |
Dnajc9_10009927 | 1.0000 | / |
Dnajc22 | 1.0000 | / |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, X.; Liu, S.; Wang, Y.; Lu, W.; Zhang, Q.; Cheng, J. Genomic and Transcriptomic Landscape and Evolutionary Dynamics of Heat Shock Proteins in Spotted Sea Bass (Lateolabrax maculatus) under Salinity Change and Alkalinity Stress. Biology 2022, 11, 353. https://doi.org/10.3390/biology11030353
Li X, Liu S, Wang Y, Lu W, Zhang Q, Cheng J. Genomic and Transcriptomic Landscape and Evolutionary Dynamics of Heat Shock Proteins in Spotted Sea Bass (Lateolabrax maculatus) under Salinity Change and Alkalinity Stress. Biology. 2022; 11(3):353. https://doi.org/10.3390/biology11030353
Chicago/Turabian StyleLi, Xujian, Saisai Liu, Yapeng Wang, Wei Lu, Quanqi Zhang, and Jie Cheng. 2022. "Genomic and Transcriptomic Landscape and Evolutionary Dynamics of Heat Shock Proteins in Spotted Sea Bass (Lateolabrax maculatus) under Salinity Change and Alkalinity Stress" Biology 11, no. 3: 353. https://doi.org/10.3390/biology11030353
APA StyleLi, X., Liu, S., Wang, Y., Lu, W., Zhang, Q., & Cheng, J. (2022). Genomic and Transcriptomic Landscape and Evolutionary Dynamics of Heat Shock Proteins in Spotted Sea Bass (Lateolabrax maculatus) under Salinity Change and Alkalinity Stress. Biology, 11(3), 353. https://doi.org/10.3390/biology11030353