欢迎访问作物学报，今天是
作物学报

作物学报 ›› 2011, Vol. 37 ›› Issue (06): 965-974.doi: 10.3724/SP.J.1006.2011.00965

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

大豆基因组和转录组的核基因密码子使用偏好性分析

张乐1,金龙国1,罗玲1,王跃平1,董志敏1,孙守红2,邱丽娟1,*   

  1. 1 国家农作物基因资源与遗传改良重大科学工程 / 农业部作物种质资源利用重点开放实验室 / 中国农业科学院作物科学研究所，北京100081; 2 中国科学院遗传与发育研究所，北京100101
  • 收稿日期:2010-12-23 修回日期:2011-03-28 出版日期:2011-06-12 网络出版日期:2011-04-12
  • 通讯作者: 邱丽娟, E-mail: qiu_lijuan@263.net
  • 基金资助:

    本研究由国家高技术研究发展计划(863计划)项目(2006AA10A110)，国家自然科学基金项目(30871621)和国家转基因生物新品种培育科技重大专项重点课题(2009ZX08009-088B)资助。

Analysis of Nuclear Gene Codon Bias on Soybean Genome and Transcriptome

ZHANG Le1,JIN Long-Guo1,LUO Ling1,WANG Yue-Ping1,DONG Zhi-Min1,SUN Shou-Hong2,QIU Li-Juan1,*   

  1. 1 National Key Facility for Crop Gene Resources and Genetic Improvement / Key Laboratory of Germplasm Utilization, Ministry of Agriculture, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 2 Chinese Academy of Sciences, Beijing 100101, China
  • Received:2010-12-23 Revised:2011-03-28 Published:2011-06-12 Published online:2011-04-12
  • Contact: 邱丽娟, E-mail: qiu_lijuan@263.net

PDF

2916

被引次数

50

摘要： 研究大豆核基因密码子的使用模式，探讨影响其密码子组成和编码特点的因素，为运用基因工程技术提高改良大豆提供理论依据。以大豆基因组的46 430个高置信编码基因和2 071条大豆全长转录本序列为数据来源，应用CodonW软件对大豆全基因组密码子组成、同义密码子使用频率和全长转录组编码区密码子使用各项参数的计算和统计分析发现，基因的表达水平与编码区G+C和GC3s含量均呈极显著正相关，且G+C和GC3s含量越高的基因密码子使用偏好性越高，并确定了UCC和GCC为大豆最优密码子。编码区长度分组分析表明，密码子使用偏好性随编码区长度的增加而降低，编码区较长的基因则趋向于随机使用密码子，且在转录组数据范围内，编码区长度介于400~600 bp的基因表达水平最高。大豆叶片和种子中特异表达基因的密码子使用偏好性和基因表达水平较为接近，但种子特异表达基因的G+C和GC3s含量均显著高于叶片特异表达基因，而其芳香族氨基酸含量则极显著低于叶片特异表达基因。

关键词: 大豆, 基因组, 转录组, 密码子

Abstract: Research of soybean nuclear gene codon composition, usage pattern and influencing factors can provide theoretical basis for applying genetic engineering techonology to improve soybean varieties. A total of 46 430 high confidence coding sequences predicted from soybean genome and 2 071 full-length transcripts were used to analyze the composition and characteristics of soybean nuclear gene codons. CodonW software was applied to calculate the nucleotide composition, relative synonymous codon usage and other parameters of soybean genome and transcriptome. The result indicted that gene expression level was significantly and positively correlated with G+C and GC3s contents, and genes with high G+C and GC3s contents had high codon preference. UCC and GCC were identified as optimal codons in soybean. Analysis of coding sequences with different length showed that codon preference reduced as the coding sequence (CDS) length increased, and longer CDS tend to select codons randomly. CDS length between 400 to 600 bp had the highest expression level among the transcriptome data. The preference and expression level were almost the same between leaf-specific and seed-specific genes. But seed-specific genes had significantly higher G+C and GC3s contents than leaf-specific genes, and the contents of aromatic amino acids encoded by seed-specific genes were highly significantly lower than these by leaf-specific genes.

Key words: Soybean, Genome, Transcriptome, Codon

[1]Carlini D B, Stephan W. In vivo introduction of unpreferred synonymous codons into the Drosophila Adh gene results in reduced levels of ADH protein. Genetics, 2003, 163: 239–243
[2]Sharp P M, Matassi G. Codon usage and genome evolution. Curr Opin Genet Dev, 1994, 4: 851–860
[3]Stenico M, Lloyd A T, Sharp P M. Codon usage in Caenorhabditis elegans: delineation of translational selection and mutational biases. Nucl Acid Res, 1994, 22: 2437–2446
[4]Olejniczak M, Uhlenbeck O C. tRNA residues that have coevolved with their anticodon to ensure uniform and accurate codon recognition. Biochinmie, 2006, 88: 943–950
[5]Holmouist G P, Flipske J. Organization of mutations along the genome: a prime determinant of genome evolution. Trends Ecol Evol, 1994, 9: 65–69
[6]Bernard I G. The human genome: Organization and evolutionary history. Annu Rev Genet, 1995, 29: 445–476
[7]Shi X-F(石秀凡), Huang J-F(黄京飞), Liu S-Q(柳树群), Liu C-Q(刘次全). The feature of synonymous codon bias and GC-content relationship in human genes. Prog Biochem Biophys (生物化学与生物物理进展), 2002, 29(3): 411–414 (in Chinese with English abstract)
[8]Xia X. Mutation and selection on the anticodon of tRNA genes in vertebrate mitochondrial genomes. Gene, 2005, 345: 13–20
[9]Chen S L, Lee W, Hottes A K, Shapiro L, McAdams H H. Codon usage between genomes is constrained by genome-wide mutational processes. Pro Natl Acad Sci, 2004, 101: 3480–3485
[10]Romero H, Zavala A, Musto H, Bernaerdi G. The influence of translational selection on codon usage in fishes from the family Cyprinidae. Gene, 2003, 317: 141–147
[11]Moriyama E N, Powell J R. Gene length and codon usage bias in Drosophila melanogaster, Saccharomyces cervisiae and Escherichia coli. Nucl Acids Res, 1998, 26: 3188–3193
[12]Knight R D, Freeland S J, Landweber L F. A simple model based on mutation and selection explains trends in codon and amino-acid usage and GC composition within and across genomes. Genome Biol, 2001, 2: RESERCH0010
[13]Gupta S K, Majumdar S K, Bhattacharya T, Ghosh T C. Studies on the relationships between the synonymous codon usage and protein secondary structural units. Biochem Biophys Res Commun, 2000, 269: 692–696
[14]Goldman N, Yang Z. A codon-based model of nucleotide substitution for protein-coding DNA sequences. Molr Biol Evol, 1994, 11: 725–736
[15]Schmidt W. Phylogeny reconstruction for protein sequences based on amino acid properties. J Mol Evol, 1995, 41: 522–530
[16]Arumuganathan K, Earle E D. Nuclear DNA content of some important plant species. Plant Mol Rep, 1991, 9: 208–218
[17]Jeremy S, Steven B C, Jessica S, Ma J X, Mitros T, Nelson W, Hyten D L, Song Q J, Thelen J J, Cheng J L, Xu D, Hellsten U, May G D, Yu Y, Sakarai T, Umezawa T, Bhattacharyya M K, Sandhu D, Valliyodan B, Lindquist E, Peto M, Grant D, Shu S Q, Abernathy B, Du J C, Tian Z X, Zhu L C, Gill N, Joshi T, Libault M, Sethuraman A, Zhang X C, Shinozak K, Nguyen H T, Wing R A, Cregan P, Specht J, Crimwood J, Rokhsar D, Stavey G, Shoemaker R C, Jackson S A. Genome sequence of the palaeopolyploid soybean. Nature, 2010, 463: 178–183
[18]Cao H-Y(曹慧颖), Zhang R(张锐), Guo S-D(郭三堆). High level expression of human thymosin α1 concatemer in transgenic tomato plants. Sci Agric Sin (中国农业科学), 2009, 42(7): 2291–2296 (in Chinese with English abstract)
[19]Zou Y-M(邹永梅), Shi J-S(施季森), Zhu-Ge Q(诸葛强), Huang M-R(黄敏仁). Reacting the silencing genes in the transgenic plants. Mol Plant Breed (分子植物育种), 2006, 4(1): 95–102 (in Chinese with English abstract)
[20]Dong Z-M(董志敏), Li Y-H(李英慧), Zhang B-S(张宝石), Guan R-X(关荣霞), Chang R-Z(常汝镇), Qiu L-J(邱丽娟). An improved SMART method to construction full-length cDNA library for large clones. Soybean Sci (大豆科学), 2006, (5): 1-4 (in Chinese with English abstract)
[21]Wang Y-P(王跃平), Li Y-H(李英慧), Chen X-T(陈雄庭), Chang R-Z(常汝镇), Qiu L-J(邱丽娟). Construction and characterization of the filling stage’s seed cDNA library from Suinong14 (Glycine max). Chin J Oil Crop Sci (中国油料作物学报), 2008, 30(1): 40–45 (in Chinese with English abstract)
[22]Sharp P M, Haney T M F, Mosurski K R. Codon usage in yeast: cluster analysis clearly differentiates highly and lowly expressed genes. Nucl Acids Res, 1986, 14: 5125–5143
[23]Liu Q, Feng Y, Xue Q. Analysis of factors shaping codon usage in the mitochondrion genome of Oryza sativa. Mitochondrion, 2004, 4: 313–320
[24]Sau K, Gupta S K, Sau S, Mandal S C, Ghosh T C. Factors influencing synonymous codon and amino acid usage biases in Mimivirus. Biosystems, 2006, 85: 107–113
[25]Wright F. The effective number of codons used in a gene. Gene, 1990, 87: 23–29
[26]Gupta S K, Bhattacharyya T K, Ghosh T C. Synonymous codon usage in lactococcus lactis: mutational bias versus translational selection. Biomol Struct Dyn, 2004, 21: 1–9
[27]Peixoto L, Zavala A, Romero H, Musto H. The strength of translational selection for codon usage varies in three relicons of Sinorhizobium melioti. Gene, 2003, 320: 109–116
[28]Romero H, Zavala A, Musto H. Codon usage in Chlamydia trachomatis is the result of strand-specific mutational biases and a complex pattern of selective forces. Nucl Acids Res, 2000, 28: 2084–2090
[29]Duret L, Mouchiroud D. Expression pattern and, surprisingly, gene length shape codon usage in Caenorhabdits, Drosophila, and Arabidopsis. Proc Natl Acad Sci, 1999, 96: 4482–4487
[30]Sharp P M, Li W H. The codon adaptation index-a measure of directional synonymous codon usage bias, and its potential applications. Nucl Acids Res, 1987, 15: 1281–1295
[31]Wei C, Brent M R. Using ESTs to improve the accuracy of de novo gene prediction. BMC Bioinformatics, 2006, 7: 327-337
[32]Kwan A L, Li L, Kulp D C, Dutcher S K, Stormo G D. Improving gene-finding in Chlamydomonas reinhardtii Green Genie2. BMC Genomics, 2009, 10: 210–220
[33]Sharp P M, Cowe E, Higgins D G, Shield D C, Wolfe K H, Wright F. Codon usage patterns in Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Drosophila melanogaster and Homo sapiens; a review of the considerable within-species diversity. Nucl Acids Res, 1988, 16: 8207–8211
[34]Stoletzki N, Eyre-Walker A. Synonymous codon usage in Escherichia coli: selection for translational accuracy. Mol Biol Evol, 2007, 24: 374–381
[35]Morton B R, Wright S I. Selective constraints on codon usage of nuclear genes from Arabidopsis thaliana. Mol Biol Evol, 2007, 24: 122–129
[36]Cutter A D, Wasmath J D, Blaxter M L. The evolution of biased codon and amino acid usage in nematode genomes. Mol Biol Evol, 2006, 23: 2303–2315
[37]Duret L, Mouchiroud D. Expression pattern and, surprisingly, gene length shape codon usage in Caenorhabditis, Drosophila, and Arabidopsis. PNAS, 1999, 96: 4482–4487
[38]Vicario S, Mason C E, White K P, Powell J R. Developmental stage and level of codon usage bias in drosophila. Mol Biol Evol, 2008, 25: 2269–2277
[39]D’Onofrio G, Mouchiroud D, Aissani B, Gautier C, Bernardi G. Correlations between the compositional properties of human genes, codon usage, and amino acid composition of proteins. J Mol Evol, 1991, 32: 504–510
[40]Moriyama E N, Powell J R. Codon usage bias and tRNA abundance in Drosophila. J Mol Evol, 1997, 45: 514–523
[41]Holmquist G P, Filipski J. Organization of mutations along the genome: a prime determinant of genome evolution. Trends Ecol Evol, 1994, 9: 65–69
[42]Perlak F J, Deaton R W, Armstrong T A, Fuchs R L, Sims S R, Greenplate J T, Fischhoff D A. Insect resistant cotton plants. Biol Technol, 1990, 8: 939–943
[1] 习千辉, 徐梓瑗, 刘梦梦, 王宏艺, 郎凯琳, 井震海, 陈锋, 赵磊. 小麦籽粒铜含量的全基因组关联分析及候选基因预测[J]. 作物学报, 2026, 52(6): 1604-1617.
[2] 王亚, 赵宜婷, 王宙, 杨俊芳, 张宏斌, 曹越. 转录组-代谢组联合分析蓖麻蜡质合成相关基因[J]. 作物学报, 2026, 52(6): 1774-1787.
[3] 毛嘉琦, 黄朋雨, 赵佳佳, 郑兴卫, 武棒棒, 郝宇琼, 屈非, 刘成, 马朋涛, 郑军. 山西小麦品种白粉病抗性评价及抗病基因分子检测[J]. 作物学报, 2026, 52(6): 1669-1681.
[4] 陈雪燕, 何华川, 李政嘉, 董新盼, 李藕琪, 刘小云, 李丹萍, 陈志伟, 刘国霞, 吕胜源, 吴印莹, 赵振东, 曹新有, 万何平. 水培盐碱复合胁迫下‘济麦60’苗期根系有机酸分泌动态变化及其转录调控机制[J]. 作物学报, 2026, 52(6): 1859-1875.
[5] 金昱何, 王雪菲, 徐张一娃, 缪怡宁, 蒋云杰, 伊莹, 缪德麟, 朱静仪, 钟一帆, 陈铭亨, 方芳, 刘鹏. 外源激素对低温胁迫下大豆叶片叶绿素荧光参数及抗氧化酶系统的影响[J]. 作物学报, 2026, 52(6): 1817-1829.
[6] 唐宽强, 李公允, 宋美毅, 赵雪, 常春玲. 大豆株高性状全基因组关联分析及预测模型构建[J]. 作物学报, 2026, 52(6): 1743-1756.
[7] 邹仪妹, 徐敏, 汪海洋, 姚辉, 王加峰, 刘浩, 任代胜. 两系不育系水稻幼苗根系响应盐胁迫的转录因子调控网络鉴定[J]. 作物学报, 2026, 52(6): 1728-1742.
[8] 蔡兆琴, 何观咏, 何文, 阮丽霞, 梁振华, 李永珍, 李恒锐, 陈会鲜. 木薯分枝发育过程的动态转录组分析与关键基因发掘[J]. 作物学报, 2026, 52(5): 1430-1441.
[9] 姚术, 郭凯悦, 翟慧慧, 姚佳慧, 邓文琪, 闫玲, 黄驰, 高阳, 俞嫣然, 赵振邦, 李英慧, 王晓波, 李佳佳. 大豆苗期耐低铁综合评价及优异种质筛选[J]. 作物学报, 2026, 52(5): 1373-1387.
[10] 杨欣雨, 崔文涛, 迪力尼格尔·阿力木, 汪凯翔, 吴鹏昊, 任姣姣. 玉米穗上叶片数全基因组关联分析和全基因组选择[J]. 作物学报, 2026, 52(5): 1573-1590.
[11] 张曦, 王广恩, 李邵琦, 刘祎, 李俊兰, 钱玉源. 基于转录组测序解析陆海杂交姊妹系马克隆值差异的形成机制[J]. 作物学报, 2026, 52(5): 1442-1458.
[12] 韩亚鑫, 何冠华, 张小琼, 张登峰, 李永祥, 刘旭洋, 王天宇, 黎裕, 邹华文, 李春辉. 基于RNA-Seq和BSA-Seq联合分析挖掘玉米侧根密度基因资源[J]. 作物学报, 2026, 52(5): 1341-1352.
[13] 谷春苗, 王润风, 黄璐, 刘浩, 鲁清, 李海芬, 李少雄, 何双呈, 洪彦彬, 陈小平, 谭斌, 余倩霞. 花生WOX基因家族的全基因组分析及不定芽再生候选基因的鉴定[J]. 作物学报, 2026, 52(5): 1326-1340.
[14] 闫安, 蒋昆炜, 王蓉圆, 田林, 张璐, 王韵, 徐建龙. 水稻剑叶小维管束数基因SVN7的鉴定与克隆[J]. 作物学报, 2026, 52(5): 1364-1372.
[15] 田立涛, 丁宁, 王树林, 齐恩芳, 张荣, 王蕊蕊, 马利雯, 李建武, 杨江伟. 马铃薯Argonaute基因家族鉴定及晚疫病诱导表达分析[J]. 作物学报, 2026, 52(4): 1116-1126.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备15008789号-2