NCBI網(wǎng)站BLAST使用方法介紹課件

1、BLASTBasic Local Alignment Search ToolLushan Wang2010.11.24生物信息的獲取方式1、以生物學(xué)信息為主檢索數(shù)據(jù)Entrez2、以序列為主檢索相關(guān)信息BLAST生物信息學(xué)時代BLAST相當(dāng)于分子生物學(xué)進(jìn)代的“PCR”技術(shù)DNA Polymerase Replication傳統(tǒng)分子技術(shù)必然會讓位于BLAST為主的生物信息技術(shù)Sangers ddNTP SequencingWhat does this sequence mean?限制酶目標(biāo)基因重組 基因細(xì)胞轉(zhuǎn)化宿主菌蛋白質(zhì)分離純化及性質(zhì)測定傳統(tǒng)分子生物學(xué)方法現(xiàn)代生物信息學(xué)方法BLASTGene

2、family Or Protein FamilyFunction annotation幾周的時間幾分鐘的時間BLASTWeb AccessBLASTVASTEntrezTextSequenceStructureWang LS, Gao PJ, cellulase,et al.Bioinfomatics databaseENTER Sequences HereHuman genome statisticsTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCT

3、AACCCTAACCCAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAACCCTAACCCTAACCCTAACCCTAACCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAACCCTAACCCTAAACCCTAAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCAACCCCAACCCCAACCCCAACCCCAACCCCAACCCTAACCCCTAACCCTAACCCTAACCCTACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAAC

4、CCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCCTAACCCTAACCCTAACCCTAACCCTCGCGGTACCCTCAGCCGGCCCGCCCGCCCGGGTCTGACCTGAGGAGAACTGTGCTCCGCCTTCAGAGTACCACCGAAATCTGTGCAGAGGACAACGCAGCTCCGCCCTCGCGGTGCTCTCCGGGTCTGTGCTGAGGAGAACGCAACTCCGCCGGCGCAGGCGCAGAGAGGCGCGCCGCGCCGGCGCAGGCGCAGACACATGCTAGCGCGTCGGGGTGGAGGCGTGGCGC

5、AGGCGCAGAGAGGCGCGCCGCGCCGGCGCAGGCGCAGAGACACATGCTACCGCGTCCAGGGGTGGAGGCGTGGCGCAGGCGCAGAGAGGCGCACCGCGCCGGCGCAGGCGCAGAGACACATGCTAGCGCGTCCAGGGGTGGAGGCGTGGCGCAGGCGCAGAGACGCAAGCCTACGGGCGGGGGTTGGGGGGGCGTGTGTTGCAGGAGCAAAGTCGCACGGCGCCGGGCTGGGGCGGGGGGAGGGTGGCGCCGTGCACGCGCAGAAACTCACGTCACGGTGGCGCGGCGCAGAGACGGGTA

6、GAACCTCAGTAATCCGAAAAGCCGGGATCGACCGCCCCTTGCTTGCAGCCGGGCACTACAGGACCCGCTTGCTCACGGTGCTGTGCCAGGGCGCCCCCTGCTGGCGACTAGGGCAACTGCAGGGCTCTCTTGCTTAGAGTGGTGGCCAGCGCCCCCTGCTGGCGCCGGGGCACTGCAGGGCCCTCTTGCTTACTGTATAGTGGTGGCACGCCGCCTGCTGGCAGCTAGGGACATTGCAGGGTCCTCTTGCTCAAGGTGTAGTGGCAGCACGCCCACCTGCTGGCAGCTGGGGACACTGCC

7、GGGCCCTCTTGCTCCAACAGTACTGGCGGATTATAGGGAAACACCCGGAGCATATGCTGTTTGGTCTCAGTAGACTCCTAAATATGGGATTCCTGGGTTTAAAAGTAAAAAATAAATATGTTTAATTTGTGAACTGATTACCATCAGAATTGTACTGTTCTGTATCCCACCAGCAATGTCTAGGAATGCCTGTTTCTCCACAAAGTGTTTACTTTTGGATTTTTGCCAGTCTAACAGGTGAAGCCCTGGAGATTCTTATTAGTGATTTGGGCTGGGGCCTGGCCATGTGTATTTTTTTAA

8、ATTTCCACTGATGATTTTGCTGCATGGCCGGTGTTGAGAATGACTGCGCAAATTTGCCGGATTTCCTTTGCTGTTCCTGCATGTAGTTTAAACGAGATTGCCAGCACCGGGTATCATTCACCATTTTTCTTTTCGTTAACTTGCCGTCAGCCT 計算機(jī)怎么會讀我們讀不懂的數(shù)據(jù)？Basic Local Alignment Search Tool Why use sequence similarity? BLAST algorithm BLAST statistics BLAST output ExamplesWhy Do We Nee

9、d Sequence Similarity Searching?To identify and annotate sequencesTo evaluate evolutionary relationshipsOther:model genomic structure (e.g., Spidey)check primer specificity in silico: NCBIs tool科學(xué)的方法：可以認(rèn)我們研究我們不懂的數(shù)據(jù)！比較的方法3000 Myr1000 Myr540 MyrAlzheimersDiseaseAtaxiatelangiectasiaColon cancerPancreat

10、iccarcinomaYeastBacteriaWormFlyHumanBLAST and Molecular EvolutionMLH1MutLBLAST Screening先找到相似的序列再找出相似序列間的關(guān)系Global vs Local AlignmentSeq 1Seq 2Seq 1Seq 2Global alignmentLocal alignment如何找出序列間的相似性？Global vs Local AlignmentSeq1: WHEREISWALTERNOW (16aa)Seq2: HEWASHEREBUTNOWISHERE (21aa)GlobalSeq1:1 W-HE

11、REISWALTERNOW 16 W HERE Seq2:1 HEWASHEREBUTNOWISHERE 21LocalSeq1: 1 W-HERE 5 Seq1: 1 W-HERE 5 W HERE W HERESeq2: 3 WASHERE 9 Seq2: 15 WISHERE 21The Flavors of BLASTStandard BLASTtraditional “contiguous” word hitposition independent scoring nucleotide, protein and translations (blastn, blastp, blastx

12、, tblastn, tblastx)Megablastoptimized for large batch searchescan use discontiguous wordsPSI-BLASTconstructs PSSMs automatically; uses as queryvery sensitive protein searchRPS BLASTsearches a database of PSSMstool for conserved domain searchesWidely used similarity search toolHeuristic approach base

13、d on Smith Waterman algorithmFinds best local alignmentsProvides statistical significanceAll combinations (DNA/Protein) query and database.DNA vs DNA blastnDNA translation vs Protein blastxProtein vs Protein blastpProtein vs DNA translation tblastnDNA translation vs DNA translation tblastx www, stan

14、dalone, and network clientsBasic Local Alignment Search ToolTranslated BLASTQueryDatabaseProgramNPucleotideroteinNNNNPPblastxtblastntblastxPPPPPPPPPPPPPPPPPPPPPPPPParticularly useful for nucleotide sequences withoutprotein annotations, such as ESTs or genomic DNAHow BLAST WorksMake lookup table of “

15、words” for queryScan database for hitsUngapped extensions of hits (initial HSPs)Gapped extensions (no traceback)Gapped extensions (traceback; alignment details)Nucleotide WordsGTACTGGACATGGACCCTACAGGAAQuery:GTACTGGACAT TACTGGACATG ACTGGACATGG CTGGACATGGA TGGACATGGAC GGACATGGACC GACATGGACCC ACATGGACC

16、CTMake a lookuptable of words11-mer. . .828megablast711blastnminimumdefaultWORD SIZEProtein WordsGTQITVEDLFYNIATRRKALKNQuery: Neighborhood WordsLTV, MTV, ISV, LSV, etc.GTQ TQI QIT ITV TVE VED EDL DLF .Make a lookuptable of wordsWord size = 3 (default)Word size can only be 2 or 3 -f 11 = blastp defau

17、lt Minimum Requirements for a Hit Nucleotide BLAST requires one exact match Protein BLAST requires two neighboring matches within 40 aaGTQITVEDLFYNI SEI YYNATCGCCATGCTTAATTGGGCTT CATGCTTAATT neighborhood wordsone exact matchtwo matches -A 40 = blastp default BLASTP Summary YLS HFLSbjct 287 LEETYAKYL

18、HKGASYFVYLSLNMSPEQLDVNVHPSKRIVHFLYDQEI 333 Query 1 IETVYAAYLPKNTHPFLYLSLEISPQNVDVNVHPTKHEVHFLHEESI 47Gapped extension with trace backQuery 1 IETVYAAYLPKNTHPFLYLSLEISPQNVDVNVHPTKHEVHFLHEESI-LEV 50 +E YA YL K F+YLSL +SP+ +DVNVHP+K VHFL+ I + +Sbjct 287 LEETYAKYLHKGASYFVYLSLNMSPEQLDVNVHPSKRIVHFLYDQEIATS

19、I 337 Final HSP +E YA YL K F+ L +SP+ +DVNVHP+K V + I High-scoring pair (HSP)HFL 18HFV 15 HFS 14HWL 13NFL 13DFL 12HWV 10etc YLS 15YLT 12 YVS 12YIT 10etc Neighborhood wordsNeighborhood score thresholdT (-f) =11Query: IETVYAAYLPKNTHPFLYLSLEISPQNVDVNVHPTKHEVHFLHEESILEVexample query words高得分配對片段有空位延伸(tra

20、ce back)Scoring Systems - Nucleotides A G C TA +1 3 3 -3G 3 +1 3 -3C 3 3 +1 -3T 3 3 3 +1Identity matrixCAGGTAGCAAGCTTGCATGTCA| | | raw score = 19-9 = 10CACGTAGCAAGCTTG-GTGTCA -r 1 -q -3 通過比對，將字符串信息轉(zhuǎn)換成數(shù)字信息，從而使人們或計算機(jī)易于分析，這種方法很簡便，但是問題也常常出在此處。Scoring Systems - ProteinsPosition Independent MatricesPAM Ma

21、trices (Percent Accepted Mutation) Derived from observation; small dataset of alignments Implicit model of evolution All calculated from PAM1 PAM250 widely usedBLOSUM Matrices (BLOck SUbstitution Matrices) Derived from observation; large dataset of highly conserved blocks Each matrix derived separat

22、ely from blocks with a defined percent identity cutoff BLOSUM62 - default matrix for BLASTPosition Specific Score Matrices (PSSMs)PSI- and RPS-BLASTA 4R -1 5 N -2 0 6D -2 -2 1 6C 0 -3 -3 -3 9Q -1 1 0 0 -3 5E -1 0 0 2 -4 2 5G 0 -2 0 -1 -3 -2 -2 6H -2 0 1 -1 -3 0 0 -2 8I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 L

23、 -1 -2 -3 -4 -1 -2 -3 -4 -3 2 4K -1 2 0 -1 -3 1 1 -2 -1 -3 -2 5M -1 -1 -2 -3 -1 0 -2 -3 -2 1 2 -1 5F -2 -3 -3 -3 -2 -3 -3 -3 -1 0 0 -3 0 6P -1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4 7S 1 -1 1 0 -1 0 0 0 -1 -2 -2 0 -1 -2 -1 4T 0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 1 5W -3 -3 -4 -4 -2 -2 -3 -2 -2

24、 -3 -2 -3 -1 1 -4 -3 -2 11Y -2 -2 -2 -3 -2 -1 -2 -3 2 -1 -1 -2 -1 3 -3 -2 -2 2 7V 0 -3 -3 -3 -1 -2 -2 -3 -3 3 1 -2 1 -1 -2 -2 0 -3 -1 4X 0 -1 -1 -1 -2 -1 -1 -1 -1 -1 -1 -1 -1 -1 -2 0 0 -2 -1 -1 -1 A R N D C Q E G H I L K M F P S T W Y V XBLOSUM62DFNegative for less likely substitutionsDYFPositive fo

25、r more likely substitutionsA Better Matrix - PAM250empirical modelempirical modelPosition-Specific Score MatrixDAF-1Serine/Threonine protein kinases catalytic loop174PSSM scores54經(jīng)驗(yàn)的MODEL應(yīng)用總是有局限的，所以有了PSSM A R N D C Q E G H I L K M F P S T W Y V 435 K -1 0 0 -1 -2 3 0 3 0 -2 -2 1 -1 -1 -1 -1 -1 -1 -1

26、 -2 436 E 0 1 0 2 -1 0 2 -1 0 -1 -1 0 0 0 -1 0 0 -1 -1 -1 437 S 0 0 -1 0 1 1 0 1 1 0 -1 0 0 0 2 0 -1 -1 0 -1 438 N -1 0 -1 -1 1 0 -1 3 3 -1 -1 1 -1 0 0 -1 -1 1 1 -1 439 K -2 1 1 -1 -2 0 -1 -2 -2 -1 -2 5 1 -2 -2 -1 -1 -2 -2 -1 440 P -2 -2 -2 -2 -3 -2 -2 -2 -2 -1 -2 -1 0 -3 7 -1 -2 -3 -1 -1 441 A 3 -2

27、 1 -2 0 -1 0 1 -2 -2 -2 0 -1 -2 3 1 0 -3 -3 0 442 M -3 -4 -4 -4 -3 -4 -4 -5 -4 7 0 -4 1 0 -4 -4 -2 -4 -1 2 443 A 4 -4 -4 -4 0 -4 -4 -3 -4 4 -1 -4 -2 -3 -4 -1 -2 -4 -3 4 444 H -4 -2 -1 -3 -5 -2 -2 -4 10 -6 -5 -3 -4 -3 -2 -3 -4 -5 0 -5 445 R -4 8 -3 -4 0 -1 -2 -3 -2 -5 -4 0 -3 -2 -4 -3 -3 0 -4 -5 446

28、D -4 -4 -1 8 -6 -2 0 -3 -3 -5 -6 -3 -5 -6 -4 -2 -3 -7 -5 -5 447 I -4 -5 -6 -6 -3 -4 -5 -6 -5 3 5 -5 1 1 -5 -5 -3 -4 -3 1 448 K 0 0 1 -3 -5 -1 -1 -3 -3 -5 -5 7 -4 -5 -3 -1 -2 -5 -4 -4 449 S 0 -3 -2 -3 0 -2 -2 -3 -3 -4 -4 -2 -4 -5 2 6 2 -5 -4 -4 450 K 0 3 0 1 -5 0 0 -4 -1 -4 -3 4 -3 -2 2 1 -1 -5 -4 -4

29、 451 N -4 -3 8 -1 -5 -2 -2 -3 -1 -6 -6 -2 -4 -5 -4 -1 -2 -6 -4 -5 452 I -3 -5 -5 -6 0 -5 -5 -6 -5 6 2 -5 2 -2 -5 -4 -3 -5 -3 3 453 M -4 -4 -6 -6 -3 -4 -5 -6 -5 0 6 -5 1 0 -5 -4 -3 -4 -3 0 454 V -3 -3 -5 -6 -3 -4 -5 -6 -5 3 3 -4 2 -2 -5 -4 -3 -5 -3 5 455 K -2 1 1 4 -5 0 -1 -2 1 -4 -2 4 -3 -2 -3 0 -1

30、-5 -2 -3 456 N 1 1 3 0 -4 -1 1 0 -3 -4 -4 3 -2 -5 -2 2 -2 -5 -4 -4 457 D -3 -2 5 5 -1 -1 1 -1 0 -5 -4 0 -2 -5 -1 0 -2 -6 -4 -5 458 L -3 -1 0 -3 0 -3 -2 3 -4 -2 3 0 1 1 -2 -2 -3 5 -1 -3Position-Specific Score Matrixcatalytic loop ./blastpgp -i NP_499868.2 -d nr -j 3 -Q NP_499868.pssm Local Alignment

31、StatisticsHigh scores of local alignments between two random sequencesfollow the Extreme Value DistributionScore (S)Alignments(applies to ungapped alignments)E = Kmne-S or E = mn2-SK = scale for search space = scale for scoring system S = bitscore = (S - lnK)/ln2Expect ValueE = number of database hi

32、ts you expect to find by chance, Syour scoreexpected number of random hitsMore info: /BLAST/tutorial/Altschul-1.html Other BLAST Algorithms MegablastDiscontiguous MegablastPSI-BLASTPHI-BLASTMegablast: NCBIs Genome Annotator Long alignments of similar DNA sequencesGreedy algorithmConcatenation of que

33、ry sequencesFaster than blastn; less sensitive適用于測序或者其他原因形成的輕微的差別的序列之間的比較 MegaBLAST & Word SizeTrade-off: sensitivity vs speed23blastp828megablast711blastnminimumdefaultWORD SIZEDiscontiguous MegablastUses discontiguous word matchesBetter for cross-species comparisons與megablast不同的是主要用來比較來自不同物種之間的相似性

34、較低的分歧序列 Templates for Discontiguous WordsW = 11, t = 16, coding: 1101101101101101W = 11, t = 16, non-coding: 1110010110110111W = 12, t = 16, coding: 1111101101101101W = 12, t = 16, non-coding: 1110110110110111W = 11, t = 18, coding: 101101100101101101W = 11, t = 18, non-coding: 111010010110010111W =

35、 12, t = 18, coding: 101101101101101101W = 12, t = 18, non-coding: 111010110010110111W = 11, t = 21, coding: 100101100101100101101W = 11, t = 21, non-coding: 111010010100010010111W = 12, t = 21, coding: 100101101101100101101W = 12, t = 21, non-coding: 111010010110010010111 Reference: Ma, B, Tromp, J

36、, Li, M. PatternHunter: faster and more sensitive homology search. Bioinformatics March, 2002; 18(3):440-5 W = word size; # matches in templatet = template lengthUsing NCBI BLASTNCBI Molecular Biology Resourceshttp:/The BLAST homepage/Basic BLAST processFirst: Enter the sequenceSecond: Select Databa

37、ses and programBasic BLAST processThird: BLAST buttonNucleotide Databases: Human and MouseHuman and mouse genomic and transcript now defaultSeparate sections in output for mRNA and genomicDirect links to Map Viewer for genomic sequencesMegablast, blastn serviceNucleotide Databases: TraditionalServic

38、esblastntblastntblastxBLAST Databases: Non-redundant proteinnr (non-redundant protein sequences)GenBank CDS translationsNP_, XP_ RefSeqsOutside ProteinPIR, Swiss-Prot, PRFPDB (sequences from structures)pat protein patentsenv_nr environmental samplesServicesblastpblastxNucleotide Databases: Tradition

39、alnr (nt)Traditional GenBankNM_ and XM_ RefSeqsrefseq_rnarefseq_genomicNC_ RefSeqsdbest EST Divisionest_human, mouse, othershtgs HTG divisiongss GSS divisionwgswhole genome shotgunenv_ntenvironmental samplesDatabases are mostly non-overlappingBasic BLAST processWord Size sp|P27476|NSR1_YEAST NUCLEAR

40、 LOCALIZATION SEQUENCE BINDING PROTEIN (P67) Length = 414 Score = 40.2 bits (92), Expect = 0.013 Identities = 35/131 (26%), Positives = 56/131 (42%), Gaps = 4/131 (3%)Query: 362 STTSLTSSSTSGSSDKVYAHQMVRTDSREQKLDAFLQPLSKPLSSQPQAIVTEDKTD 418 S+S SSS+S SS + + +S + + S S S+ + E K Sbjct: 29 SSSSSESSSSSSS

41、SSESESESESESESSSSSSSSDSESSSSSSSDSESEAETKKEESKDS 88FilteredUnfilteredLow Complexity FilteringBasic BLAST: Protein SearchesUniversal Form: ProteinProtein BLAST PageLimiting Database: OrganismOrganism autocompleteLimiting Database: Entrez Queryallfilter NOT mammalsorganismgene_in_mitochondrionPropertie

42、s2006:2007 Modification DateNucleotidebiomol_mrnaPropertiesbiomol_genomicPropertiesRun SearchBLAST Formatting Page Conserved Domain ResultsBLAST Output: Graphical Overviewmouse overSort by taxonomyTaxBLAST: Taxonomy ReportsTaxBLAST: Distance tree of resultsBLAST Output: DescriptionsLink to entrezSor

43、ted by e values5 X 10-14Default e value cutoff 10Gene LinkoutBLAST Output: AlignmentsIdentical matchpositive score(conservative)Negative or zerogapPosition Specific Iterative BLASTPSI-BLASTPSI-BLAST位點(diǎn)特異性反復(fù)BLAST。PSI-BLAST的特色是每次用profile搜索數(shù)據(jù)庫后再利用搜索的結(jié)果重新構(gòu)建profile，然后用新的profile再次搜索數(shù)據(jù)庫，如此反復(fù)直至沒有新的結(jié)果產(chǎn)生為止。PSI

44、-BLAST先用帶空位的BLAST搜索數(shù)據(jù)庫，將獲得的序列通過多序列比對來構(gòu)建第一個profile。PSI-BLAST自然地拓展了BLAST方法，能尋找蛋白質(zhì)序列中的隱含模式，有研究表明這種方法可以有效的找到很多序列差異較大而結(jié)構(gòu)功能相似的相關(guān)蛋白，甚至可以與一些結(jié)構(gòu)比對方法，如threading相媲美。MLH1 and ETR1gi|4557757|ref|NP_000240.1| MutL protein homolog 1 Homo sapiens MSFVAGVIRRLDETVVNRIAAGEVIQRPANAIKEMIENCLDAKSTSIQVIVKEGGLKLIQIQDNGTGIRK

45、 EDLDIVCERFTTSKLQSFEDLASISTYGFRGEALASISHVAHVTITTKTADGKCAYRASYSDGKLKAPPK PCAGNQGTQITVEDLFYNIATRRKALKNPSEEYGKILEVVGRYSVHNAGISFSVKKQGETVADVRTLPNA STVDNIRSIFGNAVSRELIEIGCEDKTLAFKMNGYISNANYSVKKCIFLLFINHRLVESTSLRKAIETVY AAYLPKNTHPFLYLSLEISPQNVDVNVHPTKHEVHFLHEESILERVQQHIESKLLGSNSSRMYFTQTLLP GLAGPSGEMVKSTTS

46、LTSSSTSGSSDKVYAHQMVRTDSREQKLDAFLQPLSKPLSSQPQAIVTEDKTDIS SGRARQQDEEMLELPAPAEVAAKNQSLEGDTTKGTSEMSEKRGPTSSNPRKRHREDSDVEMVEDDSRKEM TAACTPRRRIINLTSVLSLQEEINEQGHEVLREMLHNHSFVGCVNPQWALAQHQTKLYLLNTTKLSEELF YQILIYDFANFGVLRLSEPAPLFDLAMLALDSPESGWTEEDGPKEGLAEYIVEFLKKKAEMLADYFSLEI DEEGNLIGLPLLIDNYVPPLEGLPIFILRLA

47、TEVNWDEEKECFESLSKECAMFYSIRKQYISEESTLSGQQSEVPGSIPNSWKWTVEHIVYKALRSHILPPKHFTEDGNILQLANLPDLYKVFERC gi|22095656|sp|O81122.1|ETR1_MALDO Ethylene receptorMLACNCIEPQWPADELLMKYQYISDFFIALAYFSIPLELIYFVKKSAVFPYRWVLVQFGAFIVLCGATHLINLWTFSIHSRTVAMVMTTAKVLTAVVSCATALMLVHIIPDLLSVKTRELFLKNKAAELDREMGLIRTQEETGRHVRMLTHE

48、IRSTLDRHTILKTTLVELGRTLALEECALWMPTRTGLELQLSYTLRQQNPVGYTVPIHLPVINQVFSSNRAVKISANSPVAKLRQLAGRHIPGEVVAVRVPLLHLSNFQINDWPELSTKRYALMVLMLPSDSARQWHVHELELVEVVADQVAVALSHAAILEESMRARDLLMEQNIALDLARREAETAIRARNDFLAVMNHEMRTPMHAIIALSSLLQETELTAEQRLMVETILRSSNLLATLINDVLDLSRLEDGSLQLEIATFNLHSVFREVHNMIKPVASIKRLSVTLNIAADLPMY

49、AIGDEKRLMQTILNVVGNAVKFSKEGSISITAFVAKSESLRDFRAPDFFPVQSDNHFYLRVQVKDSGSGINPQDIPKLFTKFAQTQALATRNSGGSGLGLAICKRFVNLMEGHIWIESEGLGKGCTATFIVKLGFPERSNESKLPFAPKLQANHVQTNFPGLKVLVMDDNGVSRSVTKGLLAHLGCDVTAVSLIDELLHVISQEHKVVFMDVSMPGIDGYELAVRIHEKFTKRHERPVLVALTGSIDKITKENCMRVGVDGVILKPVSVDKMRSVLSELLEHRVLFEAMHuman Misma

50、tch Repair ProteinApple ethylene receptor蘋果乙烯受體PSI-BLAST: Iteration 1PSI-BLAST:Iteration 4Plant ethylene receptors, bacterial two-component regulatory system kinasesRPS-BLAST: Conserved DomainsHistidine Kinase-like ATPase DomainAlgorithm parameters: ProteinAdjust to set stringencyMay limit resultsDe

51、fault statistics adjustmentfor compositional biasOff now by default. Conflicts withcomp-based statsExpandAutomatic Short Sequence Adjustmente-value 20000Word Size 2MatrixPAM30Comp Stats OffLow Comp FilterOffNucleotide and ProteinBasic BLAST: NucleotideUniversal Form: NucleotideSpeedSensitivityMoreLe

52、ssLessMoreLinks to Map ViewerChromosome 1Chromosome 9BLAST Formatting OptionsProtein Formatting PageShowAlignmentPSSMPssmWithParametersBioseqasHTMLPlain TextASN.1XMLAlignment ViewPairwisePairwise with dots for identitiesQuery-anchored with dots for identitiesQuery-anchored with letters for identitie

53、sFlat query-anchored with dots for identitiesFlat-query anchored with letters for identitiesHit tableStructured formats: XML and ASN.11gi|730028|sp|P40692|MLH1_HUMANDNA mismatch repair protein Mlh1 (MutL protein homolog 1)P4069275611568.9406101756175600000756Seq-annot := desc user type str Hist Seqa

54、lign , data label str Hist Seqalign , data bool TRUE , user type str Blast Type , data label id 0 , data int 0 , user type str BLAST database title , data label str Non-redundant SwissProtXMLASN.1The Hit Table# BLASTP 2.2.17 (Aug-26-2007)# Query: gi|4557757|ref|NP_000240.1| MutL protein homolog 1 Ho

55、mo sapiens# Database: swissprot# Fields: query id, subject ids, % identity, % positives, alignment length, mismatches, gap opens, q. start, q. end, s. start, s. end, evalue, bit score# 80 hits foundref|NP_000240.1|gi|4557757 gi|1709056|sp|P38920|MLH1_YEAST 36.68 56.91 796 426 18 8 756 5 769 7e-138 4

56、91ref|NP_000240.1|gi|4557757 gi|48474996|sp|Q9P7W6|MLH1_SCHPO 37.24 54.04 768 371 16 8 756 9 684 8e-122 437ref|NP_000240.1|gi|4557757 gi|25090753|sp|Q8RA70|MUTL_THETN 37.44 54.62 390 231 7 8 394 4 383 5e-59 229ref|NP_000240.1|gi|4557757 gi|25090732|sp|Q8KAX3|MUTL_CHLTE 35.95 54.05 370 229 5 8 375 4

57、367 5e-55 215ref|NP_000240.1|gi|4557757 gi|127552|sp|P23367.2|MUTL_ECOLI 35.99 58.11 339 202 7 8 334 3 338 8e-55 214ref|NP_000240.1|gi|4557757 gi|29427778|sp|Q8FAK9|MUTL_ECOL6 35.99 58.11 339 202 7 8 334 3 338 1e-54 214ref|NP_000240.1|gi|4557757 gi|20455084|sp|Q8XDN4|MUTL_ECO57 35.99 58.11 339 202 7

58、 8 334 3 338 1e-54 214ref|NP_000240.1|gi|4557757 gi|59798328|sp|Q72PF7|MUTL_LEPIC 36.27 55.20 375 221 8 6 375 2 363 3e-54 213ref|NP_000240.1|gi|4557757 gi|13431695|sp|P57886|MUTL_PASMU 35.48 58.94 341 213 6 8 345 3 339 4e-54 212ref|NP_000240.1|gi|4557757 gi|1171080|sp|P44494|MUTL_HAEIN 35.74 59.87 3

59、19 198 6 8 323 3 317 5e-54 212ref|NP_000240.1|gi|4557757 gi|20455102|sp|Q8ZIW4|MUTL_YERPE 36.01 58.63 336 207 6 8 339 3 334 6e-54 212ref|NP_000240.1|gi|4557757 gi|20455152|sp|Q9JYT2|MUTL_NEIMB 33.96 55.35 374 224 8 8 376 4 359 2e-53 210ref|NP_000240.1|gi|4557757 gi|20139217|sp|Q9KAC1|MUTL_BACHD 35.3

60、9 55.90 356 214 6 8 362 4 344 2e-53 209ref|NP_000240.1|gi|4557757 gi|31076794|sp|Q87L05|MUTL_VIBPA 35.33 58.38 334 210 5 8 338 3 333 3e-53 209ref|NP_000240.1|gi|4557757 gi|20455150|sp|Q9JTS2|MUTL_NEIMA 36.94 58.28 314 183 5 8 316 4 307 5e-53 209ref|NP_000240.1|gi|4557757 gi|56749233|sp|Q6GHD9|MUTL_S