弯枝藻属rbcL基因的适应性进化分析
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摘要
为探讨淡水红藻的叶绿体基因及其适应性进化特征,选取弯枝藻属(Compsopogon)及相近外类群的rbc L基因共17条,利用PAML 4.9软件,对弯枝藻属rbc L基因编码蛋白进行生物信息学分析,并分别采用分支模型、位点模型以及分支-位点模型对基因的选择位点进行检测。结果表明,弯枝藻属rbc L基因编码蛋白的二级结构主要由α螺旋和β折叠构成,结构稳定。采用最大似然法构建的系统发育树表明,内类群为单一物种,分为3个小分支,具有一定地理分布规律。在3种进化模型中均未检测到统计上显著的正选择位点,表明绝大多数位点处于负选择压力下。因此,弯枝藻属rbc L基因未发生适应性进化。
In order to reveal the chloroplast gene and adaptive evolution characters of Rhodophyta, the 17 rbc L genes of Compsopogon and the similar group of freshwater red algae were selected, the bioinformatics of proteins encoded by rbc L genes of Compsopogon were analyzed by using software PAML4.9, and the selection sites of genes were detected by using branch model, site model and branch-site models. The results showed that the secondary structure of protein encoded by rbc L of Compsopogon was mainly composed of α helix and β folding, so its structure was very stable. The phylogenetic tree with the maximum likelihood method showed that the inner group had only one species, could be divided into three small branches, and they had obvious geographical distribution. No significant positively selected sites were detected under all three evolutionary models, indicating that most of the sites were under negative selection pressure. Therefore, there is no adaptive evolution of rbc L gene in Compsopogon.
In order to reveal the chloroplast gene and adaptive evolution characters of Rhodophyta, the 17 rbc L genes of Compsopogon and the similar group of freshwater red algae were selected, the bioinformatics of proteins encoded by rbc L genes of Compsopogon were analyzed by using software PAML4.9, and the selection sites of genes were detected by using branch model, site model and branch-site models. The results showed that the secondary structure of protein encoded by rbc L of Compsopogon was mainly composed of α helix and β folding, so its structure was very stable. The phylogenetic tree with the maximum likelihood method showed that the inner group had only one species, could be divided into three small branches, and they had obvious geographical distribution. No significant positively selected sites were detected under all three evolutionary models, indicating that most of the sites were under negative selection pressure. Therefore, there is no adaptive evolution of rbc L gene in Compsopogon.
引文
[1]SKUJA H. Comments on fresh-water rhodophyceae[J]. Bot Rev, 1938,4(12):665–676. doi:10.1007/BF02869845.
[2]KUMANO S. Freshwater red Algae of the World[M]. Bristol, England:Biopress Limited, 2002:223–228.
[3]SHI Z X. Flora Slgarum Sinicarum Aquae Dulcis, Vol. 13, Rhodophyta Phaeophyta[M]. Beijing:Science Press, 2006:1–34.施之新.中国淡水藻志,第13卷,红藻门,褐藻门[M].北京:科学出版社, 2006:1–34.
[4]GAO Y F, NAN F R, FENG J, et al. Review of systematics of Compsopogonales(Rhodophyta)[J].WorldSci-TechnolResDevel,2015,37(3):314–318. doi:10.16507/j.issn.1006-6055.2015.03.021.高一帆,南芳茹,冯佳,等.弯枝藻目Compsopogonales系统分类研究进展[J].世界科技研究与发展,2015,37(3):314–318.doi:10.16507/j.issn.1006-6055.2015.03.021.
[5]NECCHI O Jr, FO A S G, SALOMAKI E D, et al. Global sampling reveals low genetic diversity within Compsopogon(Compsopogonales,Rhodophyta)[J].EurJPhycol,2013,48(2):152–162.doi:10.1080/09670262.2013.783626.
[6]KAPRALOV M V, FILATOV D A. Widespread positive selection in the photosynthetic Rubisco enzyme[J]. BMC Evol Biol, 2007, 7:73.doi:10.1186/1471-2148-7-73.
[7]SAGE R F, SEEMANN J R. Regulation of ribulose-1,5-bisphosphate carboxylase/oxygenase activity in response to reduced light intensity in C4 plants[J]. Plant Physiol, 1993, 102(1):21–28. doi:10.1104/pp.102.1.21.
[8]SIQUEIRA A S, LIMA A R J, DALL’AGNOL L T, et al. Comparative modeling and molecular dynamics suggest high carboxylase activity of the Cyanobium sp. CACIAM14 rbc L protein[J]. J Mol Model, 2016,22:68. doi:10.1007/s00894-016-2943-y.
[9]HARTMAN F C, HARPEL M R. Structure, function, regulation, and assemblyofD-ribulose-1,5-bisphosphatecarboxylase/oxygenase[J].AnnuRevBiochem,1994,63:197–234.doi:10.1146/annurev.bi.63.070194.001213.
[10] GONG C Y, NAN F R, FENG J, et al. Adaptive evolutionary analysis on rbc L gene of Batrachospermales[J]. Oceanol Limnol Sin, 2017, 48(3):527–535. doi:10.11693/hyhz20161200277.巩超彦,南芳茹,冯佳,等.串珠藻目植物rbc L基因的适应性进化分析[J].海洋与湖沼, 2017, 48(3):527–535. doi:10.11693/hyhz20161200277.
[11] NEI M, KUMAR S. Molecular Evolution and Phylogenetics[M]. New York:Oxford University Press, 2000:238–273.
[12] ZHOU Y, WANG B, GAO L, et al. Adaptive evolution and coevolution of the rbc L gene in xeric Pteridaceae ferns[J]. Plant Sci J, 2011, 29(4):409–416. doi:10.3724/SP.J.1142.2011.40409.周媛,王博,高磊,等.凤尾蕨科旱生蕨类rbc L基因的适应性进化和共进化分析[J].植物科学学报,2011,29(4):409–416.doi:10.3724/SP.J.1142.2011.40409.
[13] ZHANG L J, CHEN J, WANG T. Adaptive evolution in the chloroplast gene rps4 in ferns[J]. Bull Bot Res, 2010, 30(1):42–50.张丽君,陈洁,王艇.蕨类植物叶绿体rps4基因的适应性进化分析[J].植物研究, 2010, 30(1):42–50.
[14] XIONG Y, ZHAO C Y, YANG Q S, et al. In silico cloning, bioinformaticsandadaptiveevolutionanalysisofrbc LgeneinArtemisia annua[J].Biotechnology,2014,24(6):50–56.doi:10.3969/j.issn.1004-311X.2014.06.0137-7.熊勇,赵春艳,杨青松,等.黄花蒿rbc L基因电子克隆、生物信息学及适应性进化分析[J].生物技术,2014,24(6):50–56.doi:10.3969/j.issn.1004-311X.2014.06.0137-7.
[15] LIU N, WANG Q B, CHEN J, et al. Adaptive evolution and structure modeling of rbc L gene in Ephedra[J]. Chin Sci Bull, 2010, 55(22):2341–2346. doi:10.1007/s11434-010-3023-9.刘念,王庆彪,陈婕,等.麻黄属rbc L基因的适应性进化检测与结构模建[J].科学通报,2010,55(14):1341–1346.doi:10.1007/s11434-010-3023-9.
[16] JIANG B, GAO L, LI J, et al. Adaptive evolution of the chloroplast genome in AA-genome Oryza species[J]. Chin Sci Bull, 2014, 59(20):1975–1983. doi:10.1360/N972014-00127.姜斌,高磊,李佳,等.稻属AA型物种叶绿体基因组的适应性进化[J].科学通报,2014,59(20):1975–1983.doi:10.1360/N972014-00127.
[17] THOMPSON J D, GIBSON T J, PLEWNIAK F, et al. The CLUSTAL_X windows interface:Flexible strategies for multiple sequence alignment aidedbyqualityanalysistools[J].NuclAcidsRes,1997,25(24):4876–4882. doi:10.1093/nar/25.24.4876.
[18] KUMARS,STECHERG,TAMURAK.MEGA7:Molecularevolutionary genetics analysis version 7.0 for bigger datasets[J]. Mol Biol Evol, 2016, 33(7):1870–1874. doi:10.1093/molbev/msw054.
[19] POSADA D, CRANDALL K A. MODELTEST:Testing the model of DNA substitution[J]. Bioinformatics, 1998, 14(9):817–818. doi:10.1093/bioinformatics/14.9.817.
[20] GUINDON S, DUFAYARD J F, LEFORT V, et al. New algorithms and methodstoestimatemaximum-likelihoodphylogenies:Assessing the performance of PhyML 3.0[J]. Syst Biol, 2010, 59(3):307–321. doi:10.1093/sysbio/syq010.
[21] RANNALA B, YANG Z. Probability distribution of molecular evolutionary trees:A new method of phylogenetic inference[J]. J Mol Evol,1996, 43(3):304–311. doi:10.1007/BF02338839.
[22] BURLAND T G. DNASTAR’s Lasergene sequence analysis software[M]//MISENERS,KRAWETZSA.BioinformaticsMethodsand Protocols:MethodsinMolecularBiology?,Vol.132.Totowa,NJ:Humana Press, 2000:71–91. doi:10.1385/1-59259-192-2:71.
[23] XIONG Y, ZHAO C Y, YANG Q S, et al. Molecular cloning, bioinformatics analysis of rbc L gene in Bellis perennis[J]. N Hort, 2015, 39(4):89–95. doi:10.11937/bfyy.201504021.熊勇,赵春艳,杨青松,等.雏菊rbc L基因的克隆及其生物信息学分析[J].北方园艺,2015,39(4):89–95.doi:10.11937/bfyy.201504021.
[24] YANGZ.ComputationalMolecularEvolution[M].Oxford:Oxford University Press, 2006:56–167.
[25] YANG Z H, SWANSON W J, VACQUIER V D. Maximum-likelihood analysisofmolecularadaptationinabalonespermlysinreveals variableselectivepressuresamonglineagesandsites[J].MolBiol Evol,2000,17(10):1446–1455.doi:10.1093/oxfordjournals.molbev.a026245.
[26] WONG W S, YANG Z H, GOLDMAN N, et al. Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequencesandforidentifyingpositivelyselectedsites[J].Genetics,2004, 168(2):1041–1051. doi:10.1534/genetics.104.031153.
[27] YANGZ.PAML:Aprogrampackageforphylogeneticanalysisby maximum likelihood[J]. Comput Appl Biosci, 1997, 13(5):555–556.
[28] YANGZ.Likelihoodratiotestsfordetectingpositiveselectionand applicationtoprimatelysozymeevolution[J].MolBiolEvol,1998,15(5):568–573. doi:10.1093/oxfordjournals.molbev.a025957.
[29] YANG Z H, BIELAWSKI J P. Statistical methods for detecting molecular adaptation[J]. Trends Ecol Evol, 2000, 15(12):496–503. doi:10.1016/S0169-5347(00)01994-7.
[30] ZHANGJZ,NIELSENR,YANGZH.Evaluationofanimproved branch-sitelikelihoodmethodfordetectingpositiveselectionatthe molecular level[J]. Mol Biol Evol, 2005, 22(12):2472–2479. doi:10.1093/molbev/msi237.
[31] LIQ,JIL,XIESL.PhylogeneticanalysisofBatrachospemales(Florideophyceae,Rhodophyta)basedonchloroplastrbc Lsequences[J]. Acta Hydrobiol Sin, 2010, 34(1):20–28. doi:10.3724/SP.J.1035.2010.00020.李强,吉莉,谢树莲.串珠藻目植物的系统发育:基于rbc L序列的证据[J].水生生物学报, 2010, 34(1):20–28. doi:10.3724/SP.J.1035.2010.00020.
[32] KNIGHT S, ANDERSSON I, BR?NDéN C I. Crystallographic analysis ofribulose1,5-bisphosphatecarboxylasefromspinachat2·4?resolution:Subunit interactions and active site[J]. J Mol Biol, 1990,215(1):113–160. doi:10.1016/S0022-2836(05)80100-7.
[33] SUZUKI Y, NEI M. Reliabilities of parsimony-based and likelihoodbasedmethodsfordetectingpositiveselectionatsingleaminoacid sites[J].MolBiolEvol,2001,18(12):2179–2185.doi:10.1093/oxfordjournals.molbev.a003764.
[34] SUZUKI Y, NEI M. Simulation study of the reliability and robustness ofthestatisticalmethodsfordetectingpositiveselectionatsingle amino acid sites[J]. Mol Biol Evol, 2002, 19(11):1865–1869. doi:10.1093/oxfordjournals.molbev.a004010.
[35] ZHANGJ.Frequentfalsedetectionofpositiveselectionbythe likelihood method with branch-site models[J]. Mol Biol Evol, 2004,21(7):1332–1339. doi:10.1093/molbev/msh117.
[2]KUMANO S. Freshwater red Algae of the World[M]. Bristol, England:Biopress Limited, 2002:223–228.
[3]SHI Z X. Flora Slgarum Sinicarum Aquae Dulcis, Vol. 13, Rhodophyta Phaeophyta[M]. Beijing:Science Press, 2006:1–34.施之新.中国淡水藻志,第13卷,红藻门,褐藻门[M].北京:科学出版社, 2006:1–34.
[4]GAO Y F, NAN F R, FENG J, et al. Review of systematics of Compsopogonales(Rhodophyta)[J].WorldSci-TechnolResDevel,2015,37(3):314–318. doi:10.16507/j.issn.1006-6055.2015.03.021.高一帆,南芳茹,冯佳,等.弯枝藻目Compsopogonales系统分类研究进展[J].世界科技研究与发展,2015,37(3):314–318.doi:10.16507/j.issn.1006-6055.2015.03.021.
[5]NECCHI O Jr, FO A S G, SALOMAKI E D, et al. Global sampling reveals low genetic diversity within Compsopogon(Compsopogonales,Rhodophyta)[J].EurJPhycol,2013,48(2):152–162.doi:10.1080/09670262.2013.783626.
[6]KAPRALOV M V, FILATOV D A. Widespread positive selection in the photosynthetic Rubisco enzyme[J]. BMC Evol Biol, 2007, 7:73.doi:10.1186/1471-2148-7-73.
[7]SAGE R F, SEEMANN J R. Regulation of ribulose-1,5-bisphosphate carboxylase/oxygenase activity in response to reduced light intensity in C4 plants[J]. Plant Physiol, 1993, 102(1):21–28. doi:10.1104/pp.102.1.21.
[8]SIQUEIRA A S, LIMA A R J, DALL’AGNOL L T, et al. Comparative modeling and molecular dynamics suggest high carboxylase activity of the Cyanobium sp. CACIAM14 rbc L protein[J]. J Mol Model, 2016,22:68. doi:10.1007/s00894-016-2943-y.
[9]HARTMAN F C, HARPEL M R. Structure, function, regulation, and assemblyofD-ribulose-1,5-bisphosphatecarboxylase/oxygenase[J].AnnuRevBiochem,1994,63:197–234.doi:10.1146/annurev.bi.63.070194.001213.
[10] GONG C Y, NAN F R, FENG J, et al. Adaptive evolutionary analysis on rbc L gene of Batrachospermales[J]. Oceanol Limnol Sin, 2017, 48(3):527–535. doi:10.11693/hyhz20161200277.巩超彦,南芳茹,冯佳,等.串珠藻目植物rbc L基因的适应性进化分析[J].海洋与湖沼, 2017, 48(3):527–535. doi:10.11693/hyhz20161200277.
[11] NEI M, KUMAR S. Molecular Evolution and Phylogenetics[M]. New York:Oxford University Press, 2000:238–273.
[12] ZHOU Y, WANG B, GAO L, et al. Adaptive evolution and coevolution of the rbc L gene in xeric Pteridaceae ferns[J]. Plant Sci J, 2011, 29(4):409–416. doi:10.3724/SP.J.1142.2011.40409.周媛,王博,高磊,等.凤尾蕨科旱生蕨类rbc L基因的适应性进化和共进化分析[J].植物科学学报,2011,29(4):409–416.doi:10.3724/SP.J.1142.2011.40409.
[13] ZHANG L J, CHEN J, WANG T. Adaptive evolution in the chloroplast gene rps4 in ferns[J]. Bull Bot Res, 2010, 30(1):42–50.张丽君,陈洁,王艇.蕨类植物叶绿体rps4基因的适应性进化分析[J].植物研究, 2010, 30(1):42–50.
[14] XIONG Y, ZHAO C Y, YANG Q S, et al. In silico cloning, bioinformaticsandadaptiveevolutionanalysisofrbc LgeneinArtemisia annua[J].Biotechnology,2014,24(6):50–56.doi:10.3969/j.issn.1004-311X.2014.06.0137-7.熊勇,赵春艳,杨青松,等.黄花蒿rbc L基因电子克隆、生物信息学及适应性进化分析[J].生物技术,2014,24(6):50–56.doi:10.3969/j.issn.1004-311X.2014.06.0137-7.
[15] LIU N, WANG Q B, CHEN J, et al. Adaptive evolution and structure modeling of rbc L gene in Ephedra[J]. Chin Sci Bull, 2010, 55(22):2341–2346. doi:10.1007/s11434-010-3023-9.刘念,王庆彪,陈婕,等.麻黄属rbc L基因的适应性进化检测与结构模建[J].科学通报,2010,55(14):1341–1346.doi:10.1007/s11434-010-3023-9.
[16] JIANG B, GAO L, LI J, et al. Adaptive evolution of the chloroplast genome in AA-genome Oryza species[J]. Chin Sci Bull, 2014, 59(20):1975–1983. doi:10.1360/N972014-00127.姜斌,高磊,李佳,等.稻属AA型物种叶绿体基因组的适应性进化[J].科学通报,2014,59(20):1975–1983.doi:10.1360/N972014-00127.
[17] THOMPSON J D, GIBSON T J, PLEWNIAK F, et al. The CLUSTAL_X windows interface:Flexible strategies for multiple sequence alignment aidedbyqualityanalysistools[J].NuclAcidsRes,1997,25(24):4876–4882. doi:10.1093/nar/25.24.4876.
[18] KUMARS,STECHERG,TAMURAK.MEGA7:Molecularevolutionary genetics analysis version 7.0 for bigger datasets[J]. Mol Biol Evol, 2016, 33(7):1870–1874. doi:10.1093/molbev/msw054.
[19] POSADA D, CRANDALL K A. MODELTEST:Testing the model of DNA substitution[J]. Bioinformatics, 1998, 14(9):817–818. doi:10.1093/bioinformatics/14.9.817.
[20] GUINDON S, DUFAYARD J F, LEFORT V, et al. New algorithms and methodstoestimatemaximum-likelihoodphylogenies:Assessing the performance of PhyML 3.0[J]. Syst Biol, 2010, 59(3):307–321. doi:10.1093/sysbio/syq010.
[21] RANNALA B, YANG Z. Probability distribution of molecular evolutionary trees:A new method of phylogenetic inference[J]. J Mol Evol,1996, 43(3):304–311. doi:10.1007/BF02338839.
[22] BURLAND T G. DNASTAR’s Lasergene sequence analysis software[M]//MISENERS,KRAWETZSA.BioinformaticsMethodsand Protocols:MethodsinMolecularBiology?,Vol.132.Totowa,NJ:Humana Press, 2000:71–91. doi:10.1385/1-59259-192-2:71.
[23] XIONG Y, ZHAO C Y, YANG Q S, et al. Molecular cloning, bioinformatics analysis of rbc L gene in Bellis perennis[J]. N Hort, 2015, 39(4):89–95. doi:10.11937/bfyy.201504021.熊勇,赵春艳,杨青松,等.雏菊rbc L基因的克隆及其生物信息学分析[J].北方园艺,2015,39(4):89–95.doi:10.11937/bfyy.201504021.
[24] YANGZ.ComputationalMolecularEvolution[M].Oxford:Oxford University Press, 2006:56–167.
[25] YANG Z H, SWANSON W J, VACQUIER V D. Maximum-likelihood analysisofmolecularadaptationinabalonespermlysinreveals variableselectivepressuresamonglineagesandsites[J].MolBiol Evol,2000,17(10):1446–1455.doi:10.1093/oxfordjournals.molbev.a026245.
[26] WONG W S, YANG Z H, GOLDMAN N, et al. Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequencesandforidentifyingpositivelyselectedsites[J].Genetics,2004, 168(2):1041–1051. doi:10.1534/genetics.104.031153.
[27] YANGZ.PAML:Aprogrampackageforphylogeneticanalysisby maximum likelihood[J]. Comput Appl Biosci, 1997, 13(5):555–556.
[28] YANGZ.Likelihoodratiotestsfordetectingpositiveselectionand applicationtoprimatelysozymeevolution[J].MolBiolEvol,1998,15(5):568–573. doi:10.1093/oxfordjournals.molbev.a025957.
[29] YANG Z H, BIELAWSKI J P. Statistical methods for detecting molecular adaptation[J]. Trends Ecol Evol, 2000, 15(12):496–503. doi:10.1016/S0169-5347(00)01994-7.
[30] ZHANGJZ,NIELSENR,YANGZH.Evaluationofanimproved branch-sitelikelihoodmethodfordetectingpositiveselectionatthe molecular level[J]. Mol Biol Evol, 2005, 22(12):2472–2479. doi:10.1093/molbev/msi237.
[31] LIQ,JIL,XIESL.PhylogeneticanalysisofBatrachospemales(Florideophyceae,Rhodophyta)basedonchloroplastrbc Lsequences[J]. Acta Hydrobiol Sin, 2010, 34(1):20–28. doi:10.3724/SP.J.1035.2010.00020.李强,吉莉,谢树莲.串珠藻目植物的系统发育:基于rbc L序列的证据[J].水生生物学报, 2010, 34(1):20–28. doi:10.3724/SP.J.1035.2010.00020.
[32] KNIGHT S, ANDERSSON I, BR?NDéN C I. Crystallographic analysis ofribulose1,5-bisphosphatecarboxylasefromspinachat2·4?resolution:Subunit interactions and active site[J]. J Mol Biol, 1990,215(1):113–160. doi:10.1016/S0022-2836(05)80100-7.
[33] SUZUKI Y, NEI M. Reliabilities of parsimony-based and likelihoodbasedmethodsfordetectingpositiveselectionatsingleaminoacid sites[J].MolBiolEvol,2001,18(12):2179–2185.doi:10.1093/oxfordjournals.molbev.a003764.
[34] SUZUKI Y, NEI M. Simulation study of the reliability and robustness ofthestatisticalmethodsfordetectingpositiveselectionatsingle amino acid sites[J]. Mol Biol Evol, 2002, 19(11):1865–1869. doi:10.1093/oxfordjournals.molbev.a004010.
[35] ZHANGJ.Frequentfalsedetectionofpositiveselectionbythe likelihood method with branch-site models[J]. Mol Biol Evol, 2004,21(7):1332–1339. doi:10.1093/molbev/msh117.