生物信息学1陈润生.ppt

生物信息学现状和重要研究方向,陈润生 E-mail : Tel: 86-10-64888543 Fax: 86-10-64871293 凌伦奖 E-mail : Tel: 86-10-64888544 中国科学院生物物理研究所 北京朝阳区大屯路15号,背景,Normal Male,FISH,Different probes used to mark each chomosome Computer identifies probe and give chromosome a false color,Trisomy 13 Patau Syndrome,Patau Syndrome,Cleft lip and palate Extra fingers & toes polydactylism Defects Heart Brain Kidney Most abort Live span 1 month,一. 什么是生物信息学？ Genome informatics is a scientific discipline that encompasses all aspects of genome information acquisition, processing, storage, distribution, analysis, and interpretation. 它是一个学科领域，包含着基因组信息的获取、处理、存储、分配 、分析和解释的所有方面。 (The U.S. Human Genome Project: The First Five Years FY 1991-1995, by NIH and DOE) 从美国的三个国家计划说起：曼哈顿计划；阿婆罗计划；人类基因组计划。 破译人类遗传密码就要读懂由30亿符号组成的100万页的“天书”,Genomes highlight the Finiteness of the “Parts” in Biology,Bacteria, 1.6 Mb, 1600 genes Science 269: 496,Eukaryote, 13 Mb, 6K genes Nature 387: 1,1995,1997,1998,Animal, 100 Mb, 20K genes Science 282: 1945,Human, 3 Gb, 100K genes ?,2000?,real thing, Apr 00,98 spoof,A Draft Sequence of the Rice Genome (Oryza sativa L. ssp. indica) Jun Yu,1,2,3,4 *Songnian Hu,1 *Jun Wang,1,2,5 * Gane Ka-Shu Wong,1,2,4 *Songgang Li,1,5 Bin Liu,1 Yajun Deng,1,6 Li Dai,1 Yan Zhou,2,7 Xiuqing Zhang,1,3 Mengliang Cao,8 Jing Liu,2 Jiandong Sun,1 Jiabin Tang,1,3 Yanjiong Chen,1,6 Xiaobing Huang,1 Wei Lin,2 Chen Ye,1 Wei Tong,1 Lijuan Cong,1 Jianing Geng,1 Yujun Han,1 Lin Li,1 Wei Li,1,9 Guangqiang Hu,1 Xiangang Huang,1 Wenjie Li,1 Jian Li,1 Zhanwei Liu,1 Long Li,1 Jianping Liu,1 Qiuhui Qi,1 Jinsong Liu,1 Li Li,1 Tao Li,1 Xuegang Wang,1 Hong Lu,1 Tingting Wu,1 Miao Zhu,1 Peixiang Ni,1 Hua Han,1 Wei Dong,1,3 Xiaoyu Ren,1 Xiaoli Feng,1,3 Peng Cui,1 Xianran Li,1 Hao Wang,1 Xin Xu,1 Wenxue Zhai,3 Zhao Xu,1 Jinsong Zhang,3 Sijie He,3 Jianguo Zhang,1 Jichen Xu,3 Kunlin Zhang,1,5 Xianwu Zheng,3 Jianhai Dong,2 Wanyong Zeng,3 Lin Tao,2 Jia Ye,2 Jun Tan,2 Xide Ren,1 Xuewei Chen,3 Jun He,2 Daofeng Liu,3 Wei Tian,2,6 Chaoguang Tian,1 Hongai Xia,1 Qiyu Bao,1 Gang Li,1 Hui Gao,1 Ting Cao,1 Juan Wang,1 Wenming Zhao,1 Ping Li,3 Wei Chen,1 Xudong Wang,3 Yong Zhang,1,5 Jianfei Hu,1,5 Jing Wang,1,5 Song Liu,1 Jian Yang,1 Guangyu Zhang,1 Yuqing Xiong,1 Zhijie Li,1 Long Mao,3 Chengshu Zhou,8 Zhen Zhu,3 Runsheng Chen,1,9 Bailin Hao,2,10 Weimou Zheng,1,10 Shouyi Chen,3 Wei Guo,11 Guojie Li,12 Siqi Liu,1,2 Ming Tao,1,2 Jian Wang,1,2 Lihuang Zhu,3 Longping Yuan,8 Huanming Yang 1,2,3 ,Science 2002 296: 79-92,A Draft Sequence of the Rice Genome (Oryza sativa L. ssp. indica) Jun Yu,1,2,3,4* Songnian Hu,1* Jun Wang,1,2,5* Gane Ka-Shu Wong,1,24*,Science 2002 296: 79-92 Rice is the most important crop for human consumption, providing staple food for more than half the worlds population. The euchromatic portion of the rice genome is estimated to be 430 Mb in size (1-3), which is the smallest of the cereal crops. It is 3.7 times larger than that of A. thaliana (4-6), and 6.7 times smaller than that of the human (7, 8). The well-established protocols for high-efficiency genetic transformation, widespread availability of high-density genetic and physical maps (9, 10), and high degrees of synteny among cereal genomes (11-15) combine to make rice a unique organism for studying the physiology, developmental biology, genetics, and evolution of plants. The International Rice Genome Sequencing Project (IRGSP) (16) has already delivered a substantial amount of sequence for the japonica (Nipponbare) subspecies, in bacterial artificial chromosome (BAC) and P1-derived artificial chromosome (PAC)-sized contigs. Working independently, Monsanto and Syngenta (17, 18) established proprietary working drafts for japonica, in April 2000 and February 2001, respectively. The Monsanto sequence has been used to assist in the efforts of the IRGSP.,Figure 9. Functional classification of rice genes, according to Gene Ontology Consortium, and assigned by homology to categorized A. thaliana genes. In this ontology, “biological process,“ “cellular location,“ and “molecular function“ are treated as independent attributes. Only 36.3% of the 25,426 predicted genes for A. thaliana are classified. For rice, only 20.4% of the 53,398 complete predictions, with both initial and terminal exons, could be classified.,计算机运算速度: 18个月增长一倍; DNA序列数据: 14个月增长一倍;,代表基因组研究进展的数据 近年来GenBank中的DNA碱基数目呈指数增加，大约每14个月增加一倍。到1999年12月其数目已达30亿，它们来自47000种生物。2000年4月DNA碱基数目是60亿。现在，2002年2月13日这一数目已达171亿（15465000记录）。各种生物的EST序列已达1082万条（2002年3月8日），其中人类的EST序列已超过417 万条（小鼠2525645），估计覆盖人类基因90以上；自1999年初单核苷酸多态性( SNPs,Single Nucleotide Polymorphisms )数据库出现以来，到2000年3月20日SNP的总数是26569，现在已超过412万（2002年1月24日）；自全长1.8Mb的嗜血流感杆菌（Haemophilus influenzae Rd）基因组序列于1995年发表（Fleischmann et al.，1995）以来，到2002年3月12日已有83个模式生物的完整基因组被测序完成，它们中有13个古细菌、63个原核真细菌、7个真核生物的完整基因组，其中包括酿酒酵母、线虫、拟南芥、果蝇和人。还有另外的100余个微生物基因组正在测试当中；,果蝇基因组包括1.2亿碱基对的编码区已于2000年2月测序并组装完成；人类基因组研究的标志性工作，包含三千三百万碱基对的人第22号染色体已于1999年11月完成测序，其结果发表在1999年12月2日的Nature 杂志上。从第22号染色体已鉴定出679个基因，其中55的基因是未知的。有35种疾病与该染色体突变相关，象免疫系统疾病、先天性心脏病和精神分裂症。作为人类基因组研究的里程碑性的工作，覆盖率为90的人完整基因组的“工作草图”已经在2000年4月底完成，到2003年将获得覆盖率为99的人类基因组全部序列。,分子生物学和遗传学的文献积累从60年代中期的接近10万篇迅速增长至60年代末期的20多万篇，即在3-4年间，翻了一番。此后，至80年代中期，上升至约30万篇，即平均每年增长6-7千篇。至90年代中，文献数已上升至40多万篇；即在10年中，平均每年增长1万篇。到2000年，则增长至约50万篇，即在约5年间，又增长了10万篇（根据有关PubMed数据整理）。,美国的核酸数据库GenBankBanson,D.A. et al. (1998) Nucleic Acids Res. 26, 1-7从1979年开始建设，1982年正式运行；欧洲分子生物学实验室的EMBL数据库也于1982年开始服务；日本于1984年开始建立国家级的核酸数据库DDBJ，并于1987年正式服务。从那个时候以来，DNA序列的数据已经从80年代初期的百把条序列，几十万碱基上升至现在的110亿碱基！这就是说，在短短的约18年间，数据量增长了近十万倍。,How many characters are in the “Heaven Book”? 3*109 10,000 books 1 book 100 pages 1 page 3,000 characters CCGGTCTCCCCGCCCGCGCGCGAAGTAAAGGCCCAGCGCAGCCCGCGCTCCTGCCCTGGGGCCTCGTCTTTCTCCAGGAAAACGTGGACCGCTCTCCGCCGACAGTCTCTTCCACAGACCCCTGTCGCCTTCGCCCCCCGGTCTCTTCCGGTTCTGTCTTTTCGCTGGCTCGATACGAACAAGGAAGTCGCCCCCAGCGAGCCCCGGCTCCCCCAGGCAGAGGCGGCCCCGGGGGCGGAGTCAACGGCGGAGGCACGCCCTCTGTGAAAGGGCGGGGCATGCAAATTCGAAATGAAAGCCCGGGAACGCCGAAGAAGCACGGGTGTAAGATTTCCCTTTTCAAAGGCGGGAGAATAAGAAATCAGCCCGAGAGTGTAAGGGCGTCAATAGCGCTGTGGACGAGACAGAGGGAATGGGGCAAGGAGCGAGGCTGGGGCTCTCACCGCGACTTGAATGTGGATGAGAGTGGGACGGTGACGGCGGGCGCGAAGGCGAGCGCATCGCTTCTCGGCCTTTTGGCTAAGATCAAGTGTAGTATCTGTTCTTATCAGTTTAATATCTGATACGTCCTCTATCCGAGGACAATATATTAAATGGATTGATCAATCCGCTTCAGCCTCCCGAGTAGCTGGGACTACAGACGGTGCCATCACGCCCAGCTCATTGTTGATTCCCGCCCCCTTGGTAGAGACGGGATTCCGCTATATTGCCTGGGCTGGTGTCGAACTCATAGAACAAAGGATCCTCCCTCCTGGGCCTGGGCGTGGGCTCGCAAAACGCTGGGATTCCCGGATTACAGGCGGGCGCACCACACCAGGAGCAAACACTTCCGGTTTTAAAAATTCAGTTTGTGATTGGCTGTCATTCAGTATTATGCTAATTAAGCATGCCCGGTTTTAAACCTCTTAAAACAACTTTTAAAATTACCTTTCCACCTAAAACGTTAAAATTTGTCAAGTGATAATATTCGACAAGCTGTTATTGCCAAACTATTTTCCTATTTGTTTCCTAATGGCATCGGAACTAGCGAAAGTTTCTCGCCATCAGTTAAAAGTTTGCGGCAGATGTAGACCTAGCAGAGGTGTGCGAGGAGGCCGTTAAGACTATACTTTCAGGGATCATTTCTATAGTGTGTTACTAGAGAAGTTTCTCTGAACGTGTAGAGCACCGAAAACCACGAGGAAGAGAGGTAGCGTTTTCATCGGGTTACCTAAGTGCAGTGTCCCCCCTGGCGCGCAATTGGGAACCCCACACGCGGTGTAGAAATATATTTTAAGGGCGCG (1250 characters) 关键是先要从一个个序列片段中得到这本天书,FROM SEQUENCE DATA OF DNA TO 3D-STRUCTURE OF PROTEIN,gene (coding regions, exons),primary sequence of protein,3D-structure of protein,biological function,“Junk DNA”,(uncoding regions, 95% of human genome) One of the largest challenges is identifying the unknown functions that almost certainly exist in much of the “junk” DNA.,?,生物信息学是把基因组DNA序列信息分析作为源头，破译隐藏在DNA序列中的遗传语言，特别是非编码区的实质；同时在发现了新基因信息之后进行蛋白质空间结构模拟和预测。,生物信息学的研究目标是揭示“基因组信息结构的复杂性及遗传语言的根本规律”。它是当今乃至下一世纪自然科学和技术科学领域中“基因组、“信息结构”和“复杂性”这三个重大科学问题的有机结合。,大规模基因组测序中的信息分析 -拼接与注释 大规模测序是基因组研究的最基本任务，它的每一个环节都与信息分析紧密相关。从测序仪的光密度采样与分析、碱基读出、载体标识与去除、拼接与组装、填补序列间隙、到重复序列标识、读框预测和基因标注的每一步都是紧密依赖基因组信息学的软件和数据库的。,Sequence Data Distribution,Sequencing and Data Processing Procedure,Basecalling,Repeat Mark ORF Prediction Gene Annotation,Finishing,Assemble,Vector Mark,COGs Swiss-port, PIR, GDB, GenBank,Sequencing,How to find the coding regions in rude DNA sequence?,By signals or By contents Among the types of functional sites in genomic DNA that researchers have sought to recognize are splice sites, start and stop codons, branch points, promoters and terminators of transcription, polyadenylation sites, ribosomal binding sites, topoisomerase II binding sites, topoisomerase I cleavage sites, and various transcription factor binding sites. Local sites such as these are called signals and methods for detecting them may be called signal sensors.,5 splice signal,3 splice signal,Human Splice Signal Motifs,/pictogram.html,By contents,Statistical method and Sequence Alignment Method eneven positional base frequence (D value) Neural network predicting the splicing sites Fractal dimension of exons and introns Complexity analysis How many different patterns are there in the area of the different DNA sequence? Method and Techniques in Cryptology Coincident Indexs Unicity Distance Hidden-Markov method(HMM) Glimmerv,-,-,Sequence Analysis Pairwise Alignment,“Classical” pairwise sequence alignment schemes use some form of Dynamic Programming (DP) DP solves an optimization problem by caching sub-problem solutions and reusing them rather than re-computing them Using DP, searching for optimal alignment of two sequences of length N (with gaps) has N2 sub-problems Therefore, computational complexity of finding optimal alignment is O(N2),Sequence Analysis Heuristic Pairwise Alignment,O(N2) is too slow for comparing long sequences against (all) entries in large databases Heuristic schemes allow trading off execution time vs. result guarantees FASTA Pearson et al., 1988 BLAST Altschul et al., 1990 Most heuristic schemes rely on searching for short sequences that match without gap insertions,Sequence Analysis BLAST,Basic Local Alignment Search Tool (BLAST) Altschul et al., 1990 BLAST is a heuristic pairwise sequence alignment scheme The most widely used tool for fast searches and alignments,Neural network method A improved back-propagation (BP) learning algorithm have been built in the study. One goal of this network is to find the splicing site between intron and exon.,Neural Network Procedure,x,l-1,y,W =synaptic weight vector of a neuron in layer l =threshold of a neuron in layer l V =vector of net internal activity levels of neurons Y =vector of function signals of neurons in layer l,(l),(l),(l),(l),Forward Computation input vector x desired response vextor d The net internal activity level for neuron j in layer l is,If neuron j is in the output layer (i.e.,l=L), set,Hence, compute the error signal,Backward Computation,vector of local gradients of neurons in layer l,e = error vector respresented by e , e , ., e as elements,1,2,q,for neuron j in output layer L,for neuron j in hidden layer l,Iteration,-,GU -AG,-,splicing sites,exon,exon,intron,pseudosplicing sites,-GU -AG -,success rate = 38/60 64%,Fractal dimension of exon and intron We introduce the mapping from nucleotide sequences to two-dimensional metric space by assigning each nucleotide a fixed vector and constructing a representation by joining these vectors end-to-end.,Fractal Dimension of Exon and Intron Sequences,D is the fractal dimension and there exists self-similarity in this range of the nucleotide sequence.,-CGCGGCGTGTGTTATA -,0 0.5 1 1.5 2 2.5 3 3.5,0,7,6,5,4,3,2,1,Intron Seq.,Exon Seq.,Random Seq.,End-to-end Range,Main Range,Geometric Range,lnN,and are average of and of each class of sequences, and are their standard deviations. The class of exon sequences is denoted as EX, and intron sequences IN, randomized exon sequences RE, and randomized intron sequences RI.,Complexity analysis,In our case complexity means that how many patterns of base connections are there in a window, which are from different parts of DNA sequences. Our results show that the complexity of exon is larger than the complexity of intron and 5-flanking and 3-flanking.,Relative Complexity in Exon, Intron and Flanks,Using the methods and techniques in cryptology,One could think that the DNA sequences are similar with the telegram, which has been used to transmit secrets in the field of commerce or military affairs, so we try to apply methods and techniques in cryptology to DNA sequence analysis. As the first step we introduce some parameters of cryptology to DNA sequence analysis.,Coincident index,In cryptology this parameter has been used to find the plain code in an enciphered text of a telegram. The part with the plain code is the high-value region of this parameter. We assume that exon is corresponding to the plain code and also has the high-value of the coincident index. Unicity distance,COINCIDENT INDEX OF EXON AND INTRON,The original presentation of coincident index is:,in which N is the number of characters in the sequence,L is the number of different kinds of character, and is the frequency of the lth character appearing in this sequence.,The coincident index introduced from cryptology is applied to DNA sequence analysis.,In case of mono-letter,the expressing of coincident index IC of DNA sequence is:,j=0,1,.,L-1; k=A,C,G,T. R=4 25 (25 1)=2400,In case of biletter,the expression of IC is:,j=0,1,.,L-1; k=AA,AC,AG,AT,CA,CC,.TG,TT,The Values of Coincident Index in HSHSC70 Sequence,Sequence Analysis Multiple Alignment,Pairwise alignment is a special case of aligning multiple sequences Significance of multiple alignment (MA): Summarize a family of aligned sequences Evaluate the probability a new sequence belongs to a known family Generate alignment in a family of sequences,Sequence Analysis Multiple Alignment (Contd.),Classic DP solution of pairwise alignment can be extended to MA by replacing 2D matrix with N-dimensional matrix But complexity goes up with N, and is impractical for N 10 or sequences longer than 200 characters or so MA is a hard problem (NP-hard) Most good MAs so far have been determined manually, at least to some extent One promising approach for MA uses Hidden Markov Models (HMM),ORF Prediction of the Contig by 5 Method,Composite Artificial Neural Network System,Auto-annotation Procedure,问题与挑战,1、基因组拼接中的重复序列处理； 2、基因标识的准确率； 3、基因的可变剪接； 4、蛋白质的空间结构和功能预测。,Finding pairwise overlaps,Each fragment may appear in more than one overlap,Resolving overlaps,Build larger pieces by combining overlaps,Schematic Gene Structure,Interspersed Repeats,Source: IHGSC Nature 409:860-921 (2001),某些例子,T. tengcongensis Complete Genome Analysis,The bacteria was designated as Thermoanaerobacter tengcongensis MB4 which was isolated from the hotspring in Tengcong area, Yunnan Province of China, by the scientists working in the institute of microbiology of Chinese Academy of Sciences four years ago. The cell morphology of the bacteria is baculiform, Gram reaction is negative(-), it can not form spore and also can not mobilize. The bacteria is anaerobes to oxygen tolerance, optimum temperature is 75oC, optimum pH 7.0. The genome of T. tengcongensis consists of a single circular chromosome of 2,689,441 base pairs(bp) with an average of 37.6% G+C content.,Circular representation of the genome of T. tengcongensis MB4,General feature of the T. tengcongensis MB4 genome,Functional annotation of T.tengcongensis,Total 2808 proteins 143 proteins belong to protein clusters with multiple functions, thus 320 Others include Blast no hits, Blast hits deduced and multiple clusters,Functional annotation of T.tengcongensis,Linear representation of the genome of T. tengcongensis MB4,The most similar bacteria with T. tengcongensis MB4,Bacillus halodurans C-125（59.9%, 1681/2808）; Bacillus subtilis （55.8%, 1566/2808）; Thermotoga maritima（48.7%, 1368/2808）; Escherichia coli K-12 MG1655（47.3%, 1327/2808）; Pseudomonas aeruginosa PA01（46.2%， 1298/2808）,30bp repeats: GTTTTTAGCCTACCTAAGAGGGATTGAAAC,About thermophilicity,1. 30 genes of T. tengcongensis only appear at thermophilic bacteria and archaea 1 reverse gyrase， 7 putative transposase， 14 uncharacterized ACR（Uncharacterized ArCR）， 2 MinD superfamily P-loop ATPase containing an inserted ferredoxin domain， 2 metal-dependent hydrolases of the beta- lactamase superfamily II， 2 uncharacterized Fe-S protein , 1 predicted methyltransferases, 1 predicted transcriptional regulator,2. GC contents of stable RNA,3. Amino acid composition,Phylogeny of T.tengcongensis by comparative sequence analysis of 16s rRNA,B. Complete genomic sequence of Shigella flexneri 2a,Shigella bacteria cause bacillary dysentery(细菌性痢疾), which is prevalent worldwide with high incidence in developing countries. Approximately o.2 billion of people are infected per year, with more than million cases of death. Its importance as human pathogen and the value of complete genome sequence information for drug discovery and vaccine development propelled us to analyze the genome sequence of Shigella flexneri. Now we have finished the complete genomic sequencing of Shigella flexneri 2a and have started its genomic comparison with non-pathogenic E coli K-12 and enterohaemorrhagic E coli O157:H7.,General feature of the Shigella flexneri 2a genome,最外边的两层是ORF标注，第三层是以10kb为窗口计算的整个基因组 的gc含量。第四层是重复序列，第五层是tRNA，第六层是rRNA。,痢疾杆菌福氏2A基因组标注,痢疾杆菌福氏2A基因组研究 比较基因组,痢疾杆菌福氏2A基因组研究 致病性探索,致病质粒(virulence plasmid),红色代表毒力相关基因 蓝色为与插入序列和转座酶有关的基因,痢疾杆菌福氏2A基因组研究 致病性探索,“毒力岛”(pathogenicity islands) 1. Known: SHE-1 (encoding the ShET1 enterotoxin and other autotransporter proteins) SHE-2 (encoding the aerobactin iron transport system) SHE-3 (virtually identical to SHE-2 but present in S. sonnei) 2. New: SHE-4 (Salmonella sit-like system for iron uptake) SHE-5 (about half of those ORFs in this region have homologies from Pseudomonas aeruginosa) SHE-6 (yfe gene products of Yersinea pestis),痢疾杆菌福氏2A基因组研究 致病性探索,“黑洞”(black hole) Example: The purE-linked kcp locus,痢疾杆菌