(完整版)NCBI网站BLAST使用方法介绍

1、basic local alignment search toollushan wang2010.11.24 1、以生物学信息为主检索数据entrez 2、以序列为主检索相关信息blast 生物信息学时代blast相当于分子生物学进代的“pcr”技术dna polymerase replicationdna polymerase replicationnnnnnh2ohhhhhhopopoponnnnnh2ohohhhhhopopopo传统分子技术必然会让位于blast为主的生物信息技术sangers ddntp sequencingsangers ddntp sequencingwhat d

2、oes this sequence mean?限制酶目标基因重组 基因细胞转化宿主菌蛋白质分离纯化及性质测定传统分子生物学方法现代生物信息学方法几周的时间几分钟的时间blastweb accessblastvastentreztextsequencestructurewang ls, gao pj, cellulase,et al.bioinfomatics enter sequences herehuman genome statisticstaaccctaaccctaaccctaacccta

3、accctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaacccaaccctaaccctaaccctaaccctaaccctaaccctaacccctaaccctaaccctaaccctaaccctaacctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaaccctaacccctaaccctaaccctaaaccctaaaccctaaccctaaccctaaccctaaccctaaccccaaccccaaccccaaccccaaccccaaccccaaccc

4、taacccctaaccctaaccctaaccctaccctaaccctaaccctaaccctaaccctaaccctaacccctaacccctaaccctaaccctaaccctaaccctaaccctaaccctaacccctaaccctaaccctaaccctaaccctcgcggtaccctcagccggcccgcccgcccgggtctgacctgaggagaactgtgctccgccttcagagtaccaccgaaatctgtgcagaggacaacgcagctccgccctcgcggtgctctccgggtctgtgctgaggagaacgcaactccgccggcgca

5、ggcgcagagaggcgcgccgcgccggcgcaggcgcagacacatgctagcgcgtcggggtggaggcgtggcgcaggcgcagagaggcgcgccgcgccggcgcaggcgcagagacacatgctaccgcgtccaggggtggaggcgtggcgcaggcgcagagaggcgcaccgcgccggcgcaggcgcagagacacatgctagcgcgtccaggggtggaggcgtggcgcaggcgcagagacgcaagcctacgggcgggggttgggggggcgtgtgttgcaggagcaaagtcgcacggcgccgggct

6、ggggcggggggagggtggcgccgtgcacgcgcagaaactcacgtcacggtggcgcggcgcagagacgggtagaacctcagtaatccgaaaagccgggatcgaccgccccttgcttgcagccgggcactacaggacccgcttgctcacggtgctgtgccagggcgccccctgctggcgactagggcaactgcagggctctcttgcttagagtggtggccagcgccccctgctggcgccggggcactgcagggccctcttgcttactgtatagtggtggcacgccgcctgctggcagctagg

7、gacattgcagggtcctcttgctcaaggtgtagtggcagcacgcccacctgctggcagctggggacactgccgggccctcttgctccaacagtactggcggattatagggaaacacccggagcatatgctgtttggtctcagtagactcctaaatatgggattcctgggtttaaaagtaaaaaataaatatgtttaatttgtgaactgattaccatcagaattgtactgttctgtatcccaccagcaatgtctaggaatgcctgtttctccacaaagtgtttacttttggatttttgccag

8、tctaacaggtgaagccctggagattcttattagtgatttgggctggggcctggccatgtgtatttttttaaatttccactgatgattttgctgcatggccggtgttgagaatgactgcgcaaatttgccggatttcctttgctgttcctgcatgtagtttaaacgagattgccagcaccgggtatcattcaccatttttcttttcgttaacttgccgtcagcct 计算机怎么会读我们读不懂的数据？b basic l local a alignment s search t tool why use sequenc

9、e similarity? blast algorithm blast statistics blast output exampleswhy do we need sequence similarity searching? to identify and annotate sequences to evaluate evolutionary relationships other: model genomic structure (e.g., spidey) check primer specificity in silico: ncbis tool科学的方法：可以认我们研究我们不懂的数据

10、！比较的方法alzheimersdiseaseataxiatelangiectasiacolon cancerpancreaticcarcinomayeastbacteriawormflyhumanblast and molecular evolutionmlh1mutlblast screening先找到相似的序列先找到相似的序列再找出相似序列间的关系再找出相似序列间的关系global vs local alignmentseq 1seq 2seq 1seq 2global alignmentlocal alignment如何找出序列间的相似性？global vs local alignme

11、ntseq1: whereiswalternow (16aa)seq2: hewasherebutnowishere (21aa)globalseq1:1 w-hereiswalternow 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 blast standard blast traditional “contiguous” word hit posi

12、tion independent scoring nucleotide, protein and translations (blastn, blastp, blastx, tblastn, tblastx) megablast optimized for large batch searches can use discontiguous words psi-blast constructs pssms automatically; uses as query very sensitive protein search rps blast searches a database of pss

13、ms tool for conserved domain searches widely used similarity search tool heuristic approach based on smith waterman algorithm finds best local alignments provides statistical significance all combinations (dna/protein) query and database. . dna vs dna blastn dna translation vs protein blastx protein

14、 vs protein blastp protein vs dna translation tblastn dna translation vs dna translation tblastx www, standalone, and network clientsb basic l local a alignment s search t tooltranslated blastqueryquerydatabasedatabaseprogramprogramnpucleotideroteinnnnnppblastxtblastntblastxppppppppppppppppppppppppp

15、articularly useful for nucleotide sequences withoutprotein annotations, such as ests or genomic dnahow blast works make lookup table of “words” for query scan database for hits ungapped extensions of hits (initial hsps) gapped extensions (no traceback) gapped extensions (traceback; alignment details

16、)nucleotide wordsgtactggacatggaccctacaggaaquery:gtactggacat tactggacatg actggacatgg ctggacatgga tggacatggac ggacatggacc gacatggaccc acatggaccctmake a lookuptable of words11-mer. . .828megablast711blastnminimumdefaultword sizeprotein wordsgtqitvedlfyniatrrkalknquery: neighborhood wordsltv, mtv, isv,

17、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 default minimum requirements for a hit nucleotide blast requires one exact match protein blast requires two neighboring matches within 40 aagtqitvedlfyni sei yynatc

18、gccatgcttaattgggctt catgcttaatt neighborhood wordsone exact matchtwo matches -a 40 = blastp default blastpblastp summary yls hflsbjct 287 leetyakylhkgasyfvylslnmspeqldvnvhpskrivhflydqei 333 query 1 ietvyaaylpknthpflylsleispqnvdvnvhptkhevhflheesi 47gapped extension with trace backgapped extension wit

19、h trace backquery 1 ietvyaaylpknthpflylsleispqnvdvnvhptkhevhflheesi-lev 50 +e ya yl k f+ylsl +sp+ +dvnvhp+k vhfl+ i + +sbjct 287 leetyakylhkgasyfvylslnmspeqldvnvhpskrivhflydqeiatsi 337 final hspfinal hsp +e ya yl k f+ l +sp+ +dvnvhp+k v + i high-scoring pair (hsp)high-scoring pair (hsp)hfl 18hfv 15

20、hfs 14hwl 13nfl 13dfl 12hwv 10etc yls 15ylt 12 yvs 12yit 10etc neighborhood neighborhood wordswordsneighborhood neighborhood score thresholdscore thresholdt (-f) =11t (-f) =11query: ietvyaaylpknthpflylsleispqnvdvnvhptkhevhflheesilevexample query wordsexample query words高得分配对片段有空位延伸(trace back)scorin

21、g 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 通过比对，将字符串信息转换成数字信息，从而使人们或计算机易于分析，这种方法很简便，但是问题也常常出在此处。scoring systems - proteinsposition independent matricespam matrices (percen

22、t 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 separately from block

23、s 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 -1 -2 -3 -4 -

24、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 -3 -2 -3 -1 1

25、 -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 for more likely

26、substitutionsa better matrix - pam250arndcqeghilkmfpstwyva2r-26n002d0 -124c-2 -4 -4 -54q0112 -54e0 -113 -524g1 -301 -3 -105h-1221 -331 -26i-1 -2 -2 -2 -2 -2 -2 -3 -25l-2 -3 -3 -4 -6 -2 -3 -4 -226k-1310 -510 -20 -2 -35m-10 -2 -3 -5 -1 -2 -3 -22406f-4 -4 -4 -6 -4 -5 -5 -5 -212 -509p10 -1 -1 -30 -1 -10

27、 -2 -3 -1 -2 -56s10100 -101 -1 -1 -30 -2 -313t1 -100 -2 -100 -10 -20 -1 -2013w-62 -4 -7 -8 -5 -7 -7 -3 -5 -2 -3 -40 -6 -2 -517y-3 -4 -2 -40 -4 -4 -50 -1 -1 -4 -27 -5 -3 -3010v0 -2 -2 -2 -2 -2 -2 -1 -242 -22 -1 -1 -10-6-24empirical modelempirical modelposition-specific score matrixdaf-1serine/threoni

28、ne protein kinases catalytic loop174pssm scores54经验的model应用总是有局限的，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 -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

29、-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 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 -

30、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 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

31、 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 -4 451 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

32、 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 -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

33、 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 statisticshigh scores of local alignments between two random sequencesfollow the extreme value distributionscore (s)alignments(app

34、lies to ungapped alignments)e = kmne-s or e = mn2-sk = scale for search space = scale for scoring system s = bitscore = (s - lnk)/ln2expect valueexpect valuee = number of database hits you expect to find by chance, syour scoreexpected number of random hitsmore info: /blast/tutori

35、al/altschul-1.html other blast algorithms megablast discontiguous megablast psi-blast phi-blastmegablast: ncbis genome annotator long alignments of similar dna sequences greedy algorithm concatenation of query sequences faster than blastn; less sensitive适用于测序或者其他原因形成的轻微的差别的序列之间的比较 megablast & wo

36、rd sizetrade-off: sensitivity vs speed23blastp828megablast711blastnminimumdefaultword sizediscontiguous megablast uses discontiguous word matches better for cross-species comparisons与megablast不同的是主要用来比较来自不同物种之间的相似性较低的分歧序列 templates for discontiguous wordsw = 11, t = 16, coding: 1101101101101101w = 1

37、1, 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 = 12, t = 18, coding: 101101101101101101w = 12, t = 18, non-coding: 111010110010110111w

38、 = 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, li, m. patternhunter: faster and more sensitive homology search. bioinformatics marc

39、h, 2002; 18(3):440-5 w = word size; # matches in templatet = template lengthusing ncbi blastncbi molecular biology resources/the blast /basic blast processfirst: enter the sequencesecond: select databases and programbasic blast processthird:

40、blast buttonnucleotide databases: human and mouse human and mouse genomic and transcript now default separate sections in output for mrna and genomic direct links to map viewer for genomic sequencesmegablast, blastn servicenucleotide databases: traditionalservicesblastntblastntblastxblast databases:

41、 non-redundant proteinnr (non-redundant protein sequences) genbank cds translations np_, xp_ refseqs outside protein pir, swiss-prot, prf pdb (sequences from structures)pat protein patentsenv_nr environmental samplesservicesblastpblastxnucleotide databases: traditional nr (nt) traditional genbank nm

42、_ and xm_ refseqs refseq_rna refseq_genomic nc_ refseqs dbest est division est_human, mouse, others htgs htg division gss gss division wgs whole genome shotgun env_nt environmental samplesdatabases are mostly non-overlappingbasic blast processword size sp|p27476|nsr1_yeast nuclear localization seque

43、nce 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 sttsltssstsgssdkvyahqmvrtdsreqkldaflqplskpls-sqpqaivtedktd 418 s+s sss+s ss + + +s + + s s s+ + e k sbjct: 29 sssssesssssssssesesesesesesssss

44、sssdsesssssssdseseaetkkeeskds 88filteredunfilteredlow complexity filteringbasic blast: protein searchesuniversal form: proteinprotein blast pagelimiting database: organismorganism autocompletelimiting database: entrez queryallfilter not mammalsorganismgene_in_mitochondrionproperties2006:2007 modific

45、ation datenucleotidebiomol_mrnapropertiesbiomol_genomicpropertiesrun searchblast formatting page conserved domain resultsblast output: graphical overviewmouse oversort by taxonomytaxblast: taxonomy reportstaxblast: distance tree of resultsblast output: descriptionslink to entrezsorted by e values5 x

46、 10-14default e value cutoff 10gene linkoutblast output: alignmentsidentical matchpositive score(conservative)negative or zerogapposition specific iterative blastpsi-blast psi-blast位点特异性反复blast。psi-blast的特色是每次用profile搜索数据库后再利用搜索的结果重新构建profile，然后用新的profile再次搜索数据库，如此反复直至没有新的结果产生为止。 psi-blast先用带空位的blas

47、t搜索数据库，将获得的序列通过多序列比对来构建第一个profile。psi-blast自然地拓展了blast方法，能寻找蛋白质序列中的隐含模式，有研究表明这种方法可以有效的找到很多序列差异较大而结构功能相似的相关蛋白，甚至可以与一些结构比对方法，如threading相媲美。mlh1 and etr1gi|4557757|ref|np_000240.1| mutl protein homolog 1 homo sapiens msfvagvirrldetvvnriaageviqrpanaikemiencldakstsiqvivkegglkliqiqdngtgirk edldivcerfttskl

48、qsfedlasistygfrgealasishvahvtittktadgkcayrasysdgklkappk pcagnqgtqitvedlfyniatrrkalknpseeygkilevvgrysvhnagisfsvkkqgetvadvrtlpna stvdnirsifgnavsrelieigcedktlafkmngyisnanysvkkcifllfinhrlvestslrkaietvy aaylpknthpflylsleispqnvdvnvhptkhevhflheesilervqqhieskllgsnssrmyftqtllp glagpsgemvksttsltssstsgssdkvyah

49、qmvrtdsreqkldaflqplskplssqpqaivtedktdis sgrarqqdeemlelpapaevaaknqslegdttkgtsemsekrgptssnprkrhredsdvemveddsrkem taactprrriinltsvlslqeeineqghevlremlhnhsfvgcvnpqwalaqhqtklyllnttklseelf yqiliydfanfgvlrlsepaplfdlamlaldspesgwteedgpkeglaeyiveflkkkaemladyfslei deegnliglpllidnyvppleglpifilrlatevnwdeekecfesls

50、kecamfysirkqyiseestlsgqqsevpgsipnswkwtvehivykalrshilppkhftedgnilqlanlpdlykvferc gi|22095656|sp|o81122.1|etr1_maldo ethylene receptormlacnciepqwpadellmkyqyisdffialayfsipleliyfvkksavfpyrwvlvqfgafivlcgathlinlwtfsihsrtvamvmttakvltavvscatalmlvhiipdllsvktrelflknkaaeldremglirtqeetgrhvrmltheirstldrhtilkttlv

51、elgrtlaleecalwmptrtglelqlsytlrqqnpvgytvpihlpvinqvfssnravkisanspvaklrqlagrhipgevvavrvpllhlsnfqindwpelstkryalmvlmlpsdsarqwhvhelelvevvadqvavalshaaileesmrardllmeqnialdlarreaetairarndflavmnhemrtpmhaiialssllqeteltaeqrlmvetilrssnllatlindvldlsrledgslqleiatfnlhsvfrevhnmikpvasikrlsvtlniaadlpmyaigdekrlmqtilnvv

52、gnavkfskegsisitafvakseslrdfrapdffpvqsdnhfylrvqvkdsgsginpqdipklftkfaqtqalatrnsggsglglaickrfvnlmeghiwieseglgkgctatfivklgfpersnesklpfapklqanhvqtnfpglkvlvmddngvsrsvtkgllahlgcdvtavslidellhvisqehkvvfmdvsmpgidgyelavrihekftkrherpvlvaltgsidkitkencmrvgvdgvilkpvsvdkmrsvlsellehrvlfeamhuman mismatch repair prote

53、inapple ethylene receptor苹果乙烯受体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 resultsdefault statistics

54、 adjustmentfor compositional biasoff now by default. conflicts withcomp-based statsexpandautomatic short sequence adjustmente-value 20000word size 2matrixpam30comp stats offlow comp filter offnucleotide and proteinbasic blast: nucleotideuniversal form: nucleotidespeedsensitivitymorelesslessmorelinks

55、 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 identitiesflat query-anc

56、hored 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 seqalign , data lab

57、el 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 homo sapiens# dat

58、abase: 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 491ref|np_000240

59、.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 4 367 5e-55 215re

60、f|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 8 334 3 338 1e-54