Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-22T18:36:33.820Z Has data issue: false hasContentIssue false

Population genetic structure and selective pressure on the mitochondrial ATP6 gene of the Japanese sand lance Ammodytes personatus Girard

Published online by Cambridge University Press:  17 April 2019

Zhaochao Deng
Affiliation:
Fishery College, Zhejiang Ocean University, Zhoushan, Zhejiang 316002, China
Xiuliang Wang
Affiliation:
Fishery College, Zhejiang Ocean University, Zhoushan, Zhejiang 316002, China
Shengyong Xu
Affiliation:
Fishery College, Zhejiang Ocean University, Zhoushan, Zhejiang 316002, China
Tianxiang Gao
Affiliation:
Fishery College, Zhejiang Ocean University, Zhoushan, Zhejiang 316002, China
Zhiqiang Han*
Affiliation:
Fishery College, Zhejiang Ocean University, Zhoushan, Zhejiang 316002, China
*
Author for correspondence: Zhiqiang Han, E-mail: [email protected]

Abstract

Thermoregulation has been suggested to influence mitochondrial DNA (mtDNA) evolution. Previous studies revealed that the mitochondrial protein-coding genes of fish living in temperate climates have smaller dN/dS (Non-synonymous substitution rate/Synonymous substitution rate) than tropical species. However, it is unknown whether different geographic populations of one fish species experience stronger selective pressures between cold and warm climates. The biological characteristics of the Japanese sand lance, Ammodytes personatus in the North-western Pacific is well-suited for assessing the performance of mtDNA evolution among separate geographic populations. In this study, we focused on the mitochondrial ATP6 gene of A. personatus using 174 individuals from eight different sea temperature populations. Two distinct haplotype lineages and a significant population structure (P = 0.016) were found in this species. The frequencies of the two lineages varied with the changes of annual sea temperature. The southern lineage (lineage A, dN/dS = 0.0384) showed a larger dN/dS value than the northern lineage (lineage B, dN/dS = 0.0167), suggesting that sea temperature greatly influences the evolution of the two lineages. The result provides robust evidence of local adaptation between populations in A. personatus.

Type
Research Article
Copyright
Copyright © Marine Biological Association of the United Kingdom 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Benjamini, Y and Hochberg, Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society 57, 289300.Google Scholar
Benzinger, TH, Pratt, AW and Kitzinger, C (1961) The thermostatic control of human metabolic heat production. Proceedings of the National Academy of Sciences USA 47, 730739.Google Scholar
Brand, MD (2000) Uncoupling to survive? The role of mitochondrial inefficiency in ageing. Experimental Gerontology 35, 811820.Google Scholar
da Fonseca, RR, Johnson, WE, O'Brien, SJ, Ramos, MJ and Antunes, A (2008) The adaptive evolution of the mammalian mitochondrial genome. BMC Genomics 9, 119.Google Scholar
Delport, W, Poon, AFY, Frost, SDW and Kosakovsky Pond, SL (2010) Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology. Bioinformatics 26, 24552457.Google Scholar
Dickson, KA and Graham, JB (2004) Evolution and consequences of endothermy in fishes. Physiological and Biochemical Zoology 77, 9981018.Google Scholar
Dowling, DK, Friberg, U and Lindell, J (2008) Evolutionary implications of non-neutral mitochondrial genetic variation. Trends in Ecology and Evolution 23, 546554.Google Scholar
Edgar, RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research 32, 17921797.Google Scholar
Elliott, JM (1976) The energetics of feeding, metabolism and growth of brown trout (Salmo trutta l.) in relation to body weight, water temperature and ration size. Journal of Animal Ecology 45, 923948.Google Scholar
Excoffier, L and Lischer, HEL (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources 10, 564567.Google Scholar
Fu, YX (1997) Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147, 915925.Google Scholar
Gleason, LU and Burton, RS (2016) Genomic evidence for ecological divergence against a background of population homogeneity in the marine snail Chlorostoma funebralis. Molecular Ecology 25, 35573573.Google Scholar
Hamada, T (1985) Fishery biology of the sand-lance (Ammodytes personatus Girard) in Japan. Suisan kenkyu sosho 36, 86.Google Scholar
Han, Z, Yanagimoto, T, Zhang, Y and Gao, T (2012) Phylogeography study of Ammodytes personatus in northwestern Pacific: Pleistocene isolation, temperature and current conducted secondary contact. PLoS ONE 7, e37425.Google Scholar
Hashimoto, H (1991) Population ecology of Japanese sandeel. Journal of the Faculty of Applied Biological Science – Hiroshima University 30, 135192.Google Scholar
Jacobsen, MW, da Fonseca, RR, Bernatchez, L and Hansen, MM (2016) Comparative analysis of complete mitochondrial genomes suggests that relaxed purifying selection is driving high nonsynonymous evolutionary rate of the NADH2 gene in whitefish (Coregonus ssp.). Molecular Phylogenetics and Evolution 95, 161170.Google Scholar
Ji, YP, Gao, TX, Chen, YC and Yanagimoto, T (2006) A comparative study on the morphology and genetics of sandeel populations. Periodical of Ocean University of China 36, 7788.Google Scholar
Johnson, JA and Kelsch, SW (1998) Effects of evolutionary thermal environment on temperature-preference relationships in fishes. Environmental Biology of Fishes 53, 447458.Google Scholar
Kim, JK, Park, JY and Kim, YS (2006) Genetic diversity, relationships and demographic history of three geographic populations of Ammodytes personatus (Ammodytidae) from Korea inferred from mitochondrial DNA control region and 16s rRNA sequence data. Korean Journal of Genetics 28, 343351.Google Scholar
Kosakovsky Pond, SL, Posada, D, Gravenor, MB, Woelk, CH and Frost, SDW (2006) GARD: a genetic algorithm for recombination detection. Bioinformatics 22, 30963098.Google Scholar
Lin, JQ (1994) On the ecological character and resources of the caplin, myctophids and sand launces. Marine Sciences 18, 2325.Google Scholar
Mishmar, D, Ruiz-Pesini, E, Golik, P, Macaulay, V, Clark, AG, Hosseini, S, Brandon, M, Easley, K, Chen, E, Brown, MD, Sukernik, RI, Olckers, A and Wallace, DC (2003) Natural selection shaped regional mtDNA variation in humans. Proceedings of the National Academy of Sciences USA 100, 171176.Google Scholar
Neill, WH and Miller, JM (1994) Ecophysiology of marine fish recruitment: a conceptual framework for understanding interannual variability. Netherlands Journal of Sea Research 32, 135152.Google Scholar
Ren, G, Hu, J, Bao, Z, Jiang, X and Gao, T (2009) Isolation and characterization of eleven polymorphic microsatellite markers of sand lance (Ammodytes personatus). Conservation Genetics 10, 18371839.Google Scholar
Rogers, AR and Harpending, H (1992) Population growth makes waves in the distribution of pairwise genetic differences. Molecular Biology and Evolution 9, 552569.Google Scholar
Ruiz-Pesini, E, Mishmar, D, Brandon, M, Procaccio, V and Wallace, DC (2004) Effects of purifying and adaptive selection on regional variation in human mtDNA. Science 303, 223226.Google Scholar
Sambrook, J, Fritsch, EF and Maniatis, T (1982) Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory 49, 895909.Google Scholar
Savolainen, P, Zhang, Y, Luo, J, Lundeberg, J and Leitner, T (2002) Genetic evidence for an East Asian origin of domestic dogs. Science 298, 16101613.Google Scholar
Shen, YY, Shi, P, Sun, YB and Zhang, YP (2009) Relaxation of selective constraints on avian mitochondrial DNA following the degeneration of flight ability. Genome Research 19, 17601765.Google Scholar
Silva, G, Lima, FP, Martel, P and Castilho, R (2014) Thermal adaptation and clinal mitochondrial DNA variation of European anchovy. Proceedings of the Royal Society B: Biological Sciences 281, 20141093.Google Scholar
Sun, YB, Shen, YY, Irwin, DM and Zhang, YP (2011) Evaluating the roles of energetic functional constraints on teleost mitochondrial-encoded protein evolution. Molecular Biology and Evolution 28, 3944.Google Scholar
Tajima, F (1989) Statistical-method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585595.Google Scholar
Tamura, K and Nei, M (1993) Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Molecular Biology and Evolution 10, 512526.Google Scholar
Tamura, K, Peterson, D, Peterson, N, Stecher, G, Nei, M and Kumar, S (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution 28, 27312739.Google Scholar
Tamura, K, Stecher, G, Peterson, D, Filipski, A and Kumar, S (2013) Mega6: molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution 30, 27252729.Google Scholar
Teacher, AG, André, C, Merilä, J and Wheat, CW (2012) Whole mitochondrial genome scan for population structure and selection in the Atlantic herring. BMC Evolutionary Biology 12, 248.Google Scholar
Tomiyama, M and Yanagibashi, S (2004) Effect of temperature, age class, and growth on induction of aestivation in Japanese sandeel (Ammodytes personatus) in Ise bay, central Japan. Fisheries Oceanography 13, 8190.Google Scholar
Xu, S, Luosang, J, Hua, S, He, J, Ciren, A, Wang, W, Tong, X, Liang, Y, Wang, J and Zheng, X (2007) High altitude adaptation and phylogenetic analysis of Tibetan horse based on the mitochondrial genome. Journal of Genetics and Genomics 34, 720729.Google Scholar
Xu, SY, Sun, DR, Song, N, Gao, TX, Han, ZQ and Shui, BN (2017) Local adaptation shapes pattern of mitochondrial population structure in Sebastiscus marmoratus. Environmental Biology of Fishes 100, 763774.Google Scholar
Yang, ZH (2007) PAML 4: phylogenetic analysis by maximum likelihood. Molecular Biology and Evolution 24, 15861591.Google Scholar
Supplementary material: Image

Deng et al. supplementary material

Deng et al. supplementary material 1

Download Deng et al. supplementary material(Image)
Image 1.4 MB