基因组注释详解.ppt

单击此处编辑母版文本样式,第二级,第三级,第四级,第五级,*,单击此处编辑母版标题样式,单击此处编辑母版文本样式,第二级,第三级,第四级,第五级,单击此处编辑母版标题样式,单击此处编辑母版文本样式,第二级,第三级,第四级,第五级,单击此处编辑母版标题样式,*,基 因 组 注 释,基因组测序相关技术发展,1981,1986,1989,1991,1994,1998,2000,2002,2003,2006,2007,2008,In the coming future,2009,2010,2005,Affy launches Gene Expression microarrays,Rise of,Genbank databases from DNA sequencing,ABI commercializes first automated DNA sequencer,Low hanging fruit:cystic fibrosis mutation,identified,3700 DNA Analyzer in Human Genome Project;DNA sequencing goes industrial,First microarray publication-on Arabidopsis,ILMN launches gene expression arrays,Human Genome Project&Celera Genomics completes first draft genome,Hapmap project launched,Hapmap 1,st,phase data release,Affy&ILMN both launched 100K genotyping arrays,Rise of,Genome Wide Association Studies(GWAS),Roche GS FLX,launched,ILMN bought Solexa;launches GA,ABI,SOLiD 1.0,Launched!,The Sequencing,Shake up!,SOLiD 3.0:,100GB out of the box!,The 3,rd,Generation Sequencing will be launched,ILMN HiSeq 2000 launched,2,30X,的覆盖率,(Solexa or SOLiD),序列,预处理（质量控制）,基因组分型技术,SNP,、,Indel,、,CNV,、染色体结构变异,及注释,与,表型相关的全基因组关联分析和功能连锁性分析,实 验,数据分析,30X,以上的覆盖率,(Solexa,or SOLiD),序列,预处理（质量控制）,甲基化位点检测及注释,6,高通量测序服务,转录组测序,(RNA-seq sequencing),microRNA,测序,(microRNA sequencing),实 验,数据分析,mRNA,打断、反转录、加接头,De novo,454,构建转录图谱,Reference,barcode,建库,Solexa,，,SOLiD,序列,预处理（质量控制）,表达丰度统计,注释,(,功能、代谢通路、表达差异比较,),未知转录本的分析,实 验,数据分析,microRNA,提取、两头加接头、反转录、建库,(Solexa,or SOLiD),序列,预处理（质量控制）,已知,microRNA,丰度统计,未知,microRNA,预测及丰度统计,7,高通量测序服务,元基因组测序,(meta-genome sequencing),未知病毒检测,(Unknown,virus detecting),实 验,数据分析,DNA,提取、建库,序列,预处理（质量控制）,拼接、注释,(,功能、代谢通路,),丰度统计、比较元基因组,实 验,数据分析,低量,RNA,、,DNA,处理、建库,与宿主、微生物、病毒数据库比较,未知病毒的发现及预测,8,两种测序策略：,基于,BAC,的方法：,先把基因组打碎成200300,kb,的片段并制成,BAC,文库，再选择一些,BAC,进一步打碎成3,kb,左右的小片段，测序并拼接。,全基因组鸟枪法：,把基因组直接打碎成3,kb,左右的小片段，测序并拼接。,9,基于,BAC,的方法,全基因组,DNA,随机打成大片段,选择并克隆,大片段排序，选择,再打碎，克隆，测序，拼接,10,全基因组鸟枪法,基因组,DNA,随机打碎,测序并拼接,11,12,拼接软件的新需求,能充分利用正反向测序的配对信息,避免重复序列造成的错误拼接,能处理数以百万甚至千万计的数据,程序并行化,高效率比对,能逐步拼接,13,基因组注释,Sequence,GENESCAN,ORF Finder,GENEMARK,Gene Prediction,Blastn,Fasta,Homology,Search,Transcription,Regulatory,Region,Domain Identify,(HMMER,BLIMPS),Transmembrane,(TMAP,TMHMM),Localization Sites,(Psort),Physical&Chemical Para,(PI/MW,EXTCOEF),Post-translational,modifications,(NetNGlyc),Protein Annotation,Gene Ontology,Pathway,Predicted Gene,Or Gene,14,原核（,Prokaryote,）基因,编码区,启动子,转录起始位点,非翻译区,被转录区,起始密码子,终止密码子,5,3,上游,转录终止位点下游,15,基因组注释,Sequence,GENESCAN,ORF Finder,GENEMARK,Gene Prediction,Blastn,Fasta,Homology,Search,Transcription,Regulatory,Region,Domain Identify,(HMMER,BLIMPS),Transmembrane,(TMAP,TMHMM),Localization Sites,(Psort),Physical&Chemical Para,(PI/MW,EXTCOEF),Post-translational,modifications,(NetNGlyc),Protein Annotation,Gene Ontology,Pathway,Predicted Gene,Or Gene,16,开放阅读框,ORF,(,Open Reading Frame,),一段序列 从起始密码子（,start codon,）开始,到终止密码子（,stop codon,）结束，而且其中不包含其它终止密码子。,17,微生物基因发现要解决的问题,微生物基因组中,80%-90%,的序列参与编码,主要问题：如果有两个或更多重叠的阅读框，哪一个是基因,(,假定只可能有一个,),最可靠的方法,同源搜索,(,使用,BLAST,或,FASTA,等,),主要困难：在无已知同源性信息的情况下寻找基因,18,预测软件,GetORF,WebAccess,bioweb.pasteur.fr/seqanal/interfaces/getorf.html,Application(Download Emboss),19,20,21,GETORF:Advanced Options,i.Code to use,：选择不同的,codon usage table,，包含有：,(1)Standard (2)Standard(with alternative initiation codons)(3)Vertebrate Mitochondrial (4)Yeast Mitochondrial (5)Mold,Protozoan,Coelenterate Mitochondrial and Mycoplasma/Spiroplasma (6)Invertebrate Mitochondrial(7)Ciliate Macronuclear and Dasycladacean(8)Echinoderm Mitochondrial(9)Euplotid Nuclear(10)Bacterial(11)Alternative Yeast Nuclear(12)Ascidian Mitochondrial(13)Flatworm Mitochondrial(14)Blepharisma Macronuclear(15)Chlorophycean Mitochondrial(16)Trematode Mitochondrial(17)Scenedesmus obliquus(18)Thraustochytrium Mitochondrial,22,GETORF:Advanced Options,ii.,最小的开放阅读框由多少个核甘酸组成，预设值为,30,，也就是,10,个氨基酸。,iii.Type of output,：可选择不同的输入结果，包含有：,(1)Translation of regions between STOP codons(2)Translation of regions between START and STOP codons(3)Nucleic sequences between STOP codons(4)Nucleic sequences between START and STOP codons(5)Nucleotides flanking START codons(6)Nucleotides flanking initial STOP codons(7)Nucleotides flanking ending STOP codons,23,fasta,gcg,phylip,embl,swiss,ncbi,nbrf,genbank,ig,codata,strider,acedb,staden,text,fitch,msf,clustal,phylip,phylip3,asn1,24,Metagenomics,Community Genomics,Environmental Genomics,Who is there?,diversity&abundance,What they are doing?,Metabolic&interaction,Why they are there?,Ecological relations,Species complexity,Acid mine drainage,1 100 1000 10000,Sea water,Human gut,Soil,The cultivation-independent analysis of the collective,genomes of microbial populations obtained,directly from the environment,25,The Complexity of Metagenomics,A,A,B,C,D,A,Isolated genome single source of DNA,Metagenome multiple source of DNA,X,26,Genome Annotation,Metagenomics?,reads,assemblies,genes,annotation,Traditional genomics,reads,assemblies,ORFs,annotation,Metagenomics,?,Huge,Multiple organisms,Fragmental,Huge,Partial ORFs,Wrong ORFs,Q:Solution?A:Clustering.,Protein families,Novel families,ORF validation,Huge,Multiple organisms,Uneven coverage,27,真核生物的基因的完整结构及它的表达过程,transcription,RNA splicing,protein,translation,exon1,DNA,exon2,exon3,intron1,intron2,promoter,gt,gt,ag,ag,upstream,downstream,5UTR,3UTR,gt,gt,ag,ag,Primary RNA,transcript,3,5,Mature RNA,UTS,uga,uaa,uag,3 aaa,5,28,基 因 识 别,找出在一段,DNA,序列中，是否存在,ORF,，亦及,“,基因,”,。,判明基因的结构,包括起止位置,外显子,/,内含子边界,启动子,polyA,区域,非转译区（,UTR,）等。,预测真基因和,“,假基因,”,（,pseudogene,）及可能的剪切位点。,29,基于同源性的基因预测法,“,从头开始,”,(Ab initio),预测法,综合使用以上两种方法,:,如,TwinScan,其它方法,:,如数字信号处理，,Z,曲线,等,基因预测方法分类,30,基于序列相似性的基因预测,将基因组序列与,EST,（,expressed sequence tag,，表达序列标记,),或,cDNA,等相比较,(,用,Sim4,等方法,),从而找出与,mRNA,相对应的区域。,将基因组序列与蛋白质数据库相比较,(,用,BLASTX,等方法,),，从而找出可能的编码区。,将预测得到的多肽与蛋白质数据库相比较,将基因组序列与同源性相近物种的基因组相比较,找出保守区域。,31,优点：,基于已有的生物学数据,因此结果更有生物学意义,缺点,:,受限于已有的生物学数据,数据库可能存在的误差,对于相似程度应如何定义,基于同源性的基因预测法优缺点,32,同源搜索,Homology Search,a.,序列局部相似比较。试图发现有生物意义保守序列，而不一定要全局相似。可以由局部相似得出两序列可能有相同功能或功能相关。,b.,比较得到的是相似性，并非同源性，我们必须根据相似性结合其他证据做出判断。,33,Blast,Web:,www.ncbi.nlm.nih.gov/blast/,Application:www.ncbi.nlm.nih.gov/BLAST/download.shtml,34,如何正确看待比较结果,BLAST,找出的结果仅仅是表示两条序列之间有局部相似，与同源性关系不大，认定功能相同或相关也不是充分的。一定要结合其他的分析结果判断。,BLAST,结果中相似部分需要认真仔细观察。看看相似的部分是生物上功能重要的保守部分，还是一些无关紧要的重复序列,结合已知的信息（比如该蛋白不可能有某种功能和可能有某种功能），注意在比较中排在后面的是否与其他已知信息相符的记录,统计上有意义与生物上有意义是有差别的,35,同样或相似的功能蛋白或基因,36,与已知的功能相关之蛋白基因,No Hits,并不是表明找不到同源,accaggttacccggttaaccttacccagatttac,|,accaggtaaccaggttaactttactcagatttac,默认,WordSize=11,如果找不到,11,个完全匹配的就无法延伸出,Hits,可以修改,WordSize,但是,wordsize,越小会导致搜索速度慢,找到无用的匹配也会增多,解决方案：,PatternHunter,ssearch(fasta),40,注意二,:,通过同源比对进行蛋白功能注释：,Gene Duplication,引入的同源比对判断误差，并不是匹配分数最高的就是功能类似,解决方案,:,需要引入物种进化树辅助判断,41,隐马科夫模型（,Hidden Markov Model,，,HMM,）*,人工神经网络（,Neural Network,）,动态规划法,决策树,语言学方法,线性判别法,“,从头开始,”,基因预测法：,42,GENE Prediction,GENESCAN,genes.mit.edu/GENSCAN.html,GENEMARK,opal.biology.gatech.edu/GeneMark/eukhmm.cgi,FGENESH,Genome Browser,56,Sequence and Analysis of Rice Chromosome 4,57,58,General structural features of rice chromosome 4,Statistics of Annotated Chromosome 4,Total Genes,4,658,Average gene size(bp),2,779,Gene density(bp per gene),7,441,Average exon per gene,4.4,Average exon size(bp),340,Average intron size(bp),376,Average BAC GC(%),44.16,Average gene GC(%),47.22,Average intergenic GC(%),42.30,Average exon GC(%),53.0,Average intron GC(%),39.0,59,Classification of repetitive sequences on chromosome 4,Number of repeats,Length of repeats,Percentage of length,retrotransposon,8951,4,016,126,55.60%,transposon,3471,913,102,12.60%,MITES,13885,1,448,638,20.00%,other repeat,5693,851,199,11.80%,total,32000,7,229,065,-,60,61,62,Functional classification,Cellular metabolism,555,11.92%,Transcription,259,5.56%,Signalling,256,5.51%,Transport,198,4.14%,Plant defence,161,3.47%,Protein fate,85,1.84%,Growth,81,1.76%,Other,3063,65.76%,Total,4658,63,64,Indica Guangluai4,Japonica Nipponbare,Total length(bp),2,319,728,2,426,015,Number of genes,388,415,Gene density(bp per gene),5,979,5,846,Average exons per gene,5.2,5.1,Average introns per gene,4.2,4.1,Average exon size(bp),281,306,Average intron size(bp),320,316,Number of SNPs,9,056,9,056,SNPs in exon,1,495,2,132,SNPs in intron,1,655,1,974,SNPs in intergenic region,5,906,4,950,Number of Indels,63,138,Indels 10Kb,3,11,Indels 1-10Kb,37,25,Indels 90),Reference,Get CDSs,Predicted GeneCollection,GeneCollection,GeneDB,Formatdb,GeneDB,Formatdb,GeneBBH,ClustWPro,CalDs/Dn,Classification,GO classification,Kegg Pathway,66,乳酸菌比较基因组,67,68,69,70,新一代,DNA,序列分析技术,Genome Sequencer 20,GS 20,2005,GS FLX,2007,454 life Sciences/Roach,2.Solexa Genome Analysis System,Solexa,Solexa Ltd/illumina,3.Sequencing by Oligonucleotide Ligation and Detection,SOLiD,2007 Summer,Agencourt/ABI,71,新技术平台的比较,Sequencer,Read length,High-throughput,Running time,Cost,454 GS-20,100 bp,20 Mb/run,200 k reads/run,5.5 h,5000-7000 USD/run,0.00025USD/bp,454 GS-FLX,200-250 bp,100 Mb/run,500 k reads/run,7-8 h,-1030,Solexa,25-35 bp,1000 Mb/run,28 m reads/run,2-3d,3000 USD/run,Solid,25-50 bp,100 Mb,2-4 m reads/run,1 d,?,ABI 3730Xl,700 bp,70 kb/run,96 reads/run,2 h,150 USD/run,0.0025USD/bp,72,深度测序数据分析流程,73,Thank You!,