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QTXNetwork Manual

1. General If Genome Scan I Significance level Output Candidate interval selection Putative QTidetecton OST Fitration window szem oF PPE ds Fig 2 8 Genome scan configuration for QTL Candidate Interval Selection The experimental wise type I error for candidate interval selection Putative QTL Detection The experimental wise type I error for putative QTL detection Filtration window size cM Define a window to distinguish two adjacent test statistic peaks whether they are two QTL or not 12 OTL Algorithm Configuration General Genome Scan ie Significance level I Output Testing window size cM Posey Cd W ACCE SE Canc Fig 2 9 Significance level configuration for QTL Testing window size cM Define a window adjacent to the testing interval one for each direction When scan the genome for putative QTL no marker will be selected as cofactor within the testing window Walk speed cM The space between two adjacent test point when testing for putative QTL along the genome QTL effects The significance level for QTL effects ee OTL Algorithm Configuration General Genome Scan Significance level Output a _ ee E E E Fig 2 10 Output configuration for QTL Show all peaks Choose this option to show all the markers in the linkage group otherwise onl
2. Fig 3 17 Heritability of epistatic effects ascribed to paired QTSs _genotype_value Ent ry G G GE 1 GHSE2 G GE3 QQ 3 3551 10 8276 10 5327 0 4795 qq 1 6795 0 6937 2 8295 T 6159 SuperiorLine 7 3701 14 1733 11 2021 8 5127 SuperiorLine 4 3354 8 1927 11 51350 L ued F1 0 6279 1 4955 0 6279 0 6279 SuperiorHybrid 11 1090 14 1733 14 9409 13 9984 y SuperiorHybrid 10 1362 13 7103 13 1500 16 0966 Fig 3 18 Genotypic values based on predicted effects of QTS for designed genotypes _superior_genotype GSL GL LL LA LAI LL L2 Sa GH GH SL S2 S3 SHI L SHE 2 SHEN QQ yo Q QQ QQ QQ qq q y yo Q QQ QQ M qq mn l b I 41 gg 2 2 M yo y QQ Q qq 1 yo y yo Y QQ QQ qq yo A QQ y U o a U 4 u W W amp amp om mg Q i i y QQ qq QQ QQ 1 nh Hio u u ua A Aaaa a a A A a a Fig 3 19 The superior and inferior genotypes designed for general environment or specific environment 4 User manual for QTT P M 4 1 Introduction on QTT P M QTT P M is one module of the software QTXNetwork for association mapping genetic variation of quantitative trait transcripts QTT quantitative trait proteins QTP and quantitative trait metabolites QTM with phenotypic variation The mixed linear model approach combining with Markov Chain Monte Carlo MCMC method are employed to perform association analysis and to predict and test genetic effects of significant QTTs QTPs and QTMs Parallel computing base on Graphics P
3. Fig 4 2 The popup window for creating new project for QTT P M QTI Hetwork iof x Root Help File Exec Plot Navigator x Fig 4 3 The window of QTXNetwork for performing QTT P M 4 2 2 Deleting QTT P M project Select the QTT P M project to delete in the Navigator pane and then click the fast button 34 4 2 3 Specifying data file In a QTT P M project window a button EJ for locate and import source file will occur in the toolbar we can locate and import data files genotype data file and phenotype data file for QTT P M in the popup window after clicking the button ej In this panel Fig 4 4 there are three sections to set input or output files Since there is no need for loading genetic map in association mapping for QTT P M only data of genotypes and phenotypes are required for loading If the genotype data and phenotype are saved in one file we need selecting Use TXT file option otherwise selecting Use GNO PNO files to input data files of genotypes and phenotypes individually The third is the Output report section where the output file name can be inputted Locate Resource Files Genetic map eeo a J Input data a GNO A PNO A _ Use TXT file Use GNO PNO files Output report Ss e Use PRE files Use LOC INT files He TALUS aliUliyy MESE ON s dU Cslillidleu CIIELLULPdLITIIMeraliuil PULTE graphical charts and rearranged
4. QTI Hetrork ioj x Root Help or Navigator x Fig 5 1 The main window of the QTXNetwork Create Project Project Type QT L QTS QTTPM GMDR__ project Nameffest id Project NAME decides the name ofthe project folder in which all assets ofthe project houses these assets include copies of source files e g map _pre either selected by user or generated by algorithm plus some configuration files A project folder resid es under root HOME folder If an empty NAME is specified a temporary auto name will be given you can later mov e this project under a desired name VF accom JE Cancel Fig 5 2 The popup window for creating new project for GMDR 44 QTI Hetwork Riel x Root Help File Exec Plot te Navigator x Fig 5 3 The window of QTXNetwork for performing GMDR 5 2 2 Deleting GMDR project Select the GMDR project to delete in the Navigator pane and then click the fast button 45 5 2 3 Specifying data file In a GMDR project window a button lt for locate and import source file will occur in the toolbar you can locate and import data files genotype data file and phenotype data file for GMDR in the popup window after clicking the button is In this panel there are three sections to set input or output files Fig 5 4 The first is the Genetic map section which will be used when Genetic linkage map is available Generally genetic map is not required
5. I IE denote summation of different types of epistasis effects and environment interaction effects respectively AEi or aei DEi or dei AAEi or aaei ADE or adei DAEi or daei DDEi ddei denote the i th environment specific genetic component effects of QTLs respectively In the Fig 2 14 V e V P denote the residual variance and the phenotypic variance respectively h 2 X denote the proportion of phenotypic variance contributed to the genetic effects of X respectively where X stand for one genetic component effect or summation of some genetic component effects such as h42 A D is the proportion of phenotypic variance contributed to additive and dominance effects of detected QTLs For the Fig 2 15 the first column is the serial number of each detected significant QTL the second is the flanking markers of QTL the third is the distance between QTL and the first marker of the relevant chromosome the fourth is the support interval of QTL position the succeeding 3 columns are predicted genetic effects standard error and significance probability value respectively The Fig 2 16 presents the proportions of phenotypic variance explained by the genetic component effects of detected QTLs in the Fig 2 15 The Fig 2 17 and the Fig 2 18 provide each epistasis effects epistasis environment interaction effects of detected paired QTLs the i th QTL j th QTL and proportion of phenotypic variance explained by these epistasis
6. This option sets the search dimension 1 5 and the max dimension is 5 Best SNP selection limit This option sets the number of best SNP combinations selected in each training set Permutation power This option set the number of permutations used in testing stage for each selected SNP combination If this option is set as n then 10 permutations will be performed for each SNP combination selected in training stage otherwise the pre setting 10 1 000 permutations will be performed for each SNP combination selected in training stage 5 4 Extract results of GMDR for GWAS After finishing analysis of GMDR you can extract the result file with GWAS format by executing the Extract under the Exec menu Fig 5 6 51
7. TraitBegin and TraitEnd The data source includes the environment if available the replication if available and the ID name of subjects as well as the observations obtained for traits studied The following is an example for the trait data body TraitBegin Env Rep Geno Trait 1 Trait 2 Trait 3 l l 1 2 44 74 10 04 l l 2 2 4 4 32 8 55 24 1 l 90 3 54 8 19 10 74 l 2 3 17 6 91 11 86 1 2 2 1 9 4 31 11 36 2 90 322 10 54 11 48 5 74 12 78 11 27 2 l 2 7 65 7 02 11 96 gt l 90 6 58 13 92 9 94 2 2 l 6 01 10 22 9 95 2 2 2 6 22 11 99 7 81 P 2 90 7 98 13 21 12 03 TraitEnd The second row includes the indicator strings and the names of the traits The number of source strings depends on the experimental design If both environments and replications are taken a maximum of three strings must be inputted the first string for environment Env the second string for replication Rep and the third string for subject Geno You can use whatever strings to express the sources because they are just used to indicate what the numbers are in the columns below them If the experiment is conducted without environmental factor or replications the corresponding column must be removed And also a 66 99 semicolon is required at the end of each observation data row 3 3 2 QTS algorithm and configuration Before conducting QTS we first need setting the QTS algorithm configuration Suppose a new
8. 12 The GG plot of QTL ap Line Epistasis aba a e meta system Circle Square with only epistatic with only additive E with only dominance ae main effect I effect A effet D rna with only epistasis x with only additive x E with only dominance x Green environment interaction effect environment interaction environment interaction IE effect AE effect DE Blue with both I and IE with both A and AE E with both D and DE Dark Not available iie no additive W with l no dominance related effect related effect Fig 2 13 The genetic indications for different symbols lines colors in GG plot 2 4 3 Understanding text report 15 In order to understand each item in report file we firstly define symbols or variables in the report file and then explain the report file using the Fig 2 14 2 20 coming from the F2 simulation data which can be found in the sample folder Sample QTL SimF2 pre of the QTX Network A or a D or d AE or ae DE or de denote additive effect dominance effect additive environment interaction effect dominance environment interaction effect respectively AA or aa AD or ad DA or da DD or dd AAE or aae ADE or ade DAE or dae DDE or dde denote additive additive epistasis effect additive dominance epistasis effect dominance additive epistasis effect dominance dominance epistasis effect and their interaction effects with environments respectively
9. 2 90 322 10 54 11 48 2 l l 5 74 12 78 11 27 2 l 2 7 65 7 02 11 96 2 1 90 6 58 13 92 994 2 2 1 6 01 10 22 9 95 2 2 2 6 22 11 99 7 81 5 2 2 90 7 98 13 21 12 03 TraitEnd The second row includes the indicator strings and the names of the traits The number of source strings depends on the experimental design If both environments and replications are taken a maximum of three strings must be included the first string for environment Env the second string for replication Rep 38 and the third string for subject Ind You can use whatever strings to express the sources because they are just used to indicate the conents in the columns below them If the experiment is conducted without environmental factor or replications the corresponding column must be removed And also a semicolon 66 99 is required at the end of each observation data row 4 3 2 QTT P M algorithm and configuration Before conducting QTT P M we first need setting the QTT P M algorithm configuration Suppose a new QTT project is created or a QTT project is opened in main window of the QTXNetwork click the QTT project in the Navigator panel Fig 4 5 to set the algorithm configuration then activate the command item Config under the Exec software menu Fig 4 6 a panel will be popped up for setting configuration Fig 4 7 Fig 4 8 4 QTX Hetwork JOf x Root Help File Plot O Run ew Config QTT_G QTT_PNO e
10. Root Help oF Navigator Fig 3 1 The main window of the QTXNetwork 19 Create Project epe Project Type QTTPM GMDR ProjectNamejors2 _ _ _ Project NAME decides the name ofthe project folder in which all assets ofthe project houses these assets include copies of source filesfe qg map pre either selected by user or generated by algorithm plus some configuration files A project folder resid es under root HOME folder fan empty NAME is specified a temporary auto name will be given you can later mov e this project under a desired name Accept E Cancel Fig 3 2 The popup window for creating new project for QTS QTI Hetrork Pie E Root Help File Exec Plot a Navigator x Fig 3 3 The window of QTXNetwork for performing QTS 3 2 2 Deleting QTS project Select the QTS project to delete in the Navigator pane and then click the fast button 20 3 2 3 Specifying data file In a QTS project window a button EJ for locate and import source file will occur in the toolbar we can locate and import data files genotype data file and phenotype data file for QTS in the popup window after clicking the button j In this panel there are three sections to set input or output files Fig 3 4 The first is the Genetic map section which will be used when Genetic linkage map is available Generally genetic map is not required for association mapping The
11. data file contains information on population type number of genotypes sampled from the population number of observations observations for both markers and quantitative traits etc It is composed of four parts general description marker data body trait data body and some comment lines General description This part is for specifying the basic features of the data file and is usually put in the front of the data file Like in the map file each item in general description is a key character string c6 39 followed by certain specification s Each key string must be started with an underline and no white space is allowed within it There are eight possible items for general description They can be arranged in any order A typical description for a data file looks like _Population DH _ Genotypes 200 _Observations 400 _Environments Yes _Replications No _TraitNumber 1 _TotalMarker 64 _MarkerCode P1 1 P2 2 F1 3 F1P1 4 F1P2 5 _Population specifies the population type used Some commonly used populations are listed as follows RI population derived from a cross between two pure line parents The specification word for RI population can be RI or RIL BC population derived from crossing F1 with one of the inbred parents The specification words for BC1 and BC2 populations are B1 and B2 respectively F2 population derived from selfing or sib mating F1 that is made by crossing two inbred lines Immortalize
12. effects respectively The Fig 2 19 provides predicted genotypic values based on genetic effects of detected QTLs for several designed genotypes QQ denoting the individual with homozygote alleles for all loci as in P4 qq denoting the individual with homozygote alleles for all detect loci as in P3 F1 denoting the individual with heterozygote alleles for all detected loci as in F of P1 x P2 SuperiorLine denoting predicted pure line with the highest genotypic value SuperiorLine denoting predicted pure line with the lowest genotypic value 16 SuperiorHybrid denoting predicted highest genotypic value SuperiorHybrid denoting predicted lowest genotypic value G designing genotype based on general genetic effects of QTLs G GETZ designing genotype based on general and i th environment specific genetic effects of QTLs For the Fig 2 20 GSL denotes designed general superior line with higher lower trait performance SL 4 i denotes designed superior line with higher lower trait performance in i th environment GSH denotes designed general superior hybrid with higher lower trait performance SH i denotes designed environment specific hybrid with higher lower trait performance in i th environment _variance_components population mean 100 0234 phenotypic variance 64 3907 Total Heritability 0 7534 n2 A D h 2 AE DE h 2 l h 2 lE Vi eVVv P 0 4414 0 1181 0 1425 0 0313 0 2466 h 2 A h 2 D h
13. epi ae cere cheer 44 3 Understandine text Topor sci ie ctedecrse ati arts tts cits hleue seta eSlasanttadeici icc Aiceeccaeeehates 5 User manual for GWAS GMDR Sol Introduction om GrwiA S52 WDD Ri sieberiana tet add conde es i atiasdaduaalbsiadancehe dae tees 5 2 Running GWAS GMDBR Dida Mo reae a Projece Ot Ca NUL Rs eee acide alata ae eta a olden eee deters eek 5 2 2 Deleting GMDR project 5 2 3 Specifying data file 5 2 4 Starting GMDR 5 3 Data file format and running 5 3 1 Data format configuration Of GMDR esseede Ei 5 3 2 GMDR algorithm and Configuration sesseanneninr anaiai n aAa A a aAA 5 4 Extract results of GMDR for GWAS uu ccc ec cece cecceccescccccecceccecceccscuccescescesceecescesceecescesscesesens II 1 Introduction on QTX QTXNetwork Figure 1 1 is GPU based computation software for linkage and association analyses of epistasis and environment interaction of complex traits It contains four functional modules Figure 1 2 quantitative trait locus QTL for linkage analysis quantitative trait SNP QTS for genome wide association analysis quantitative trait transcript protein metabolite QTT P M for transcriptome proteome metabolome association analysis and GMDR for data filtering which will be further used in Genome Wide Association Studies GWAS By using the massive parallel nature of multi GPUs this mapping tool can perform association analyses on large
14. for association mapping The second is the Input data section and you need input data files of genotypes and phenotypes individually The third is the Output report section where the output file name can be inputted Locate Resource Files Genetic map mj o O Input data GOJI A poj OOOO OA Output report Use PRE files Use LOCHNT files PRE file is output report generated by QTS algorithm which contains selected SNPs interactions among these SNPs and estimated effect of each interaction Further graphical charts and rearranged tables are based on this file if you want to perform QTS algorithm to search meaningful SNPs one of two type of input data must be supplied either one single TXT file or a pair of GNO and PNO files APRE report will be generated on completion of the searching and charts will be created If you only want to view charts and tables upon existing QTS output just supply the PRE report file You can supply input data either TXT or GNO PNO and output report PRE all together to view charts and tables based on the report while at the same time enabling you to perform new search based on the input probably with different parameters and setting from last time You can optionally supply SNP distance information MAP to affect generated charts You can supply none and just close this dialog you can supply source files at any later time 7 Fig 5 4 The window for inputting data files and output f
15. one 1 3725 0 6567 1 369e 002 1 9603 0 5567 4 302e 004 2 MK 102 1 5494 0 4465 5 215e 004 2 2231 0 5795 1 263e 004 3 H MK 134 1 6728 0 3501 1 783e 006 1 3635 0 4465 2 264e 003 3 42 MK 142 1 3860 0 4465 1 912e 003 1 0535 0 5135 4 020e 002 Fig 3 14 Mapping result ascribed to single SNP effects _1D heritability h 2 a h 2 d h 2 ae h2 ael h 2 ae 2 h 2 ae3 h 2 de h 2 del h 2 de2 h 2 de3 l 5 0 0123 0 0042 aa 0 0126 lt aa I 41 0 0062 0 0062 0 0159 0 0122 0 0354 2 22 0 0177 Sa 0 0132 0 0130 0 0266 sai a se a oe 2 as 0 0166 0 0245 0 0342 an 0 0391 oe ae gag i 0 0194 0 0129 ae on ae ae ae o aan Sa 3 42 s 0 0133 0 0085 a 0 0077 0 01177 0 0070 0 0209 a a Fig 3 15 Heritability ascribed to single QTS effects 1 effect Mi MPD Mj MDj 4 j Palwe A ik Pale M i lau D j alue AML al i i o a AAO AOS Lode00l LOL OGBE 369e 003 L00 D9063 2 18erO03 1 6820 07658 2 0 Ie WRAL JA KN 12162 DOI 4 38e A1889 O90 4 S3Te 004 L i HM IM 1 6623 GOAO 1 90e0 a 4255 0905 2682006 HE K J MMI o o e l o SA KN J MI LOO 04662 2 Be 4 JA MIN J M La 0 9083 1 572 004 Fig 3 16 Epistatic effects ascribed to paired QTSs 31 O hentdality Mi Myo a d a a el hel Kll Ald Alae A ae I os L AU AW A LW Hl P o NOT A Ml E a A in A Ml oo ia a o O O o MO Do Au
16. second is the Input data section if the genotype data and phenotype are saved in one file we need selecting Use TXT file option otherwise selecting Use GNO PNO files to input genotype data and phenotype files individually The third is the Output report section where the output file name can be inputted Locate Resource Files Genetic map we 8 J Input data GNO A PNO A O Use TXT file Use GNO PNO files Output report es Te Use PRE files _ Use LOC INT files HET ALIUTIS aul MESE SINF S dU Pstiillidleu ENGELLI CALI IIe raLiuil PUILTe graphical charts and rearranged tables are based on this file Ifyou wantto perform OTS algorithm to search meaningful SNPs one of two type of input data must be supplied either one single TXT file or a pair of GNO and PNO files A PRE report will be generated on completion ofthe searching and charts will be created Ifyou only want to view charts and tables upon existing OTS output just supply the PRE report file You can supply input datafeither TXT or GNO PNO and output report PRE all together to view charts and tables based on the report while atthe same time enabling you to perform new search based on the input probably with different parameters and setting from last time You can optionally supply SNP distance information MAP to affect generated charts You can supply none and just close this dialog you can suppl
17. 0 0 9999 Fig 4 13 Heritability ascribed to single transcript effects The Fig 4 14 the first column is the individual ID and the second is the predicted individual genotype values based on detected significant transcript 5 User manual for GWAS GMDR 5 1 Introduction on GWAS GMDR GWAS GMDR is a program which implements the GMDR algorithm specifically for analyzing Genome Wide Association Analysis GWAS data GWAS GMDR assumes that all the attributes are SNPs and accelerates the computation speed by the many core parallel computation technique of Graphics Processing Units GPU to overcome the memory and computation burdens of exhaustively searching among millions of SNPs so that detecting gene gene interactions become feasible in real GWAS data by GMDR 5 2 Running GWAS GMDR 5 2 1 Creating a project for GMDR The GMDR program kept in the folder exe MDR under the QTX Network can be run directly in command window or in explore window In default you can run it via the shell program QTXNetwork To run the GMDR you first need running the QTXNetwork for creating a new project for the GMDR by clicking the button SF in the main window of the QTXNetwork Fig 5 1 a window for creating new project will be popped up Fig 5 2 After selecting module type GMDR and specifying project name click the Accept button Fig 5 2 a GMDR project will be listed in the left pane named Navigator Fig 5 3 43
18. 2 I h 2 A AA h 2 AE hA2 DE h 2 lE h 2 AE AAE 0 3105 0 1310 0 1425 0 3614 0 0602 0 0579 0 0313 0 0803 Fig 2 14 Variance components and heritability ascribed different genetic components D_effct JL pi position range A SE P Vawe D SE P Value AE1 SE PValue AE2 SE P Value DEI SE P Vaue DE2 SE P Vale 1 3 MKOSUKO4 230 200 250 46532 03100 1152 050 4 3235 0 4895 3640e 020 18018 04325 1300 005 1 7867 04325 3618 005 30171 06568 4 383e 006 32326 00508 8 643e 007 4 MKISIKIG 350 320 380 42814 0 2879 9 438 0 060 11895 0 4747 1280 22881 06578 5061e 004 22414 0 6578 6 567e 004 A MK20UK29 530 490 560 36915 04516 31360016 20825 04154 5411 007 21064 04154 4009 007 Fig 2 15 Mapping result ascribed to single QTL effects _1D_heritability QTL h 2 a h 2 d h 2 ae h 2 ae1 h 2 ae2 h 2 de h 2 de1 h 2 de2 1 3 0 1681 0 0726 0 0261 0 0137 0 0124 0 0380 0 0177 0 0203 24 0 1423 00055 0 0199 0 0102 0 0098 36 0 0529 0 0341 0 0168 0 0172 Fig 2 16 Heritability ascribed to single QTL effects 17 D fea QTL menali posion range i QTL menal positon j ange AK SE Paue AD SE Paue DA SE PYaue OD SE Paue AEL SE Paue ME SE Peale ADE S Paue ADE 13 KILKU 230 200250 AA KIKI 70 0 670 730 23253 O36 98006 008 25103 6499 5166 005 14569 08407 2300 49161 09381 1070007 10547 05980 5731003 16644 0600 54ER 13 UKOHIKD 230 AA A MKAKA 350 320380 10728 04303 N 44605 67S LMN 24
19. 5 A B H A A H V MK7 A H B A H H General description This part is for specifying the basic features of the phenotype data file and is usually put in front of the data file Like in the map file each item in general description is a key character string followed by certain specifications Each key string must be started with an underline and no white space is allowed within it There are nine possible items for general description They can be arranged in any order A typical description for a phenotype data file looks like _ Population F2 Genotypes 200 Observations 600 _ Environments Yes _Replications No 23 _TraitNumber 1 _Chromosomes 3 Chrl Chr2 Chr3 _TotalMarker 165 50 50 65 _MarkerCode P1I A P2 B F1 H FIP1 C F1P2 D _Population specifies the population type used Some commonly used populations are listed as follows RI population inbreeding lines derived from a cross between two pure line parents The specification word for the inbreeding population can be RI or DH F2 population random matting population or selfing population of F hybrid crossing by inbred lines _Genotypes specifies the total number of unique subjects used in the mapping population _Observations specifies the total number of observations for each trait studied _Environments specifies the status of experimental design for environments If the experiment is conducted in multiple environments write the specification word Yes after th
20. 70 06015 OENE O60 Me AA KIKI 700 70 730 3 KAIKO 630 WOO 250 03975 122010100 06203 1 630003 39986 15933 1AZBeOtt 0036 09031 AIEO 14504 05437 TAAI 14770 05437 BOEM Fig 2 17 Epistatic effects ascribed to paired QTLs _2D_heritability QATLI QTLj h 2 aa h 2 ad h 2 da h 2 dd h 2 aae ht2 aae1 ht2 aae2 h 2 ade h 2 ade1 h 2 ade2 h 2 dae h 2 dae1 h 2 dae2 h 2 dde ht2 dde1 h 2 dde2 4 3 41 8 0 0210 0 0122 0 0044 00234 00053 00027 0007 00061 00030 0001 1 3 24 00045 00041 00106 00057 0 0049 e e 18 36 0 0255 0 0074 0 0310 0 0093 00042 0 0020 00021 00051 00024 0 0026 Fig 2 18 Heritability ascribed to epistatic effects of paired QTLs genotype _value ntry G G GE1 G GE2 4 o 2579 1 9718 1 4549 2 2 3352 6 6775 0 7330 uperiorLinet 9 2504 22 3634 13 2365 uperiorLinet 13 3343 10 3139 17 4592 1 o_ 1767 1 6332 2 0390 uperiorHybridt 12 1539 22 3634 1333 55143 uperorHybridt 17 4036 1 4 4994 20 5071 Fig 2 19 Genotypic values based on predicted effects of QTL for designed genotypes superior_genotype TL GSL GSL SL 1 SL 2 SL 1 SL 2 GSH GSH SH 1 SH 2 SH 1 SH 2 1 3 QQ qq qq QQ qq qq Qq qq qq QQ qq qq 4 qq 00 qq qq Q amp Q Q amp Q q Q amp Q aqq qq QQ QQ qq Qa QQ qq q OQ q Qq QQ Qq Qq Qq 1 8 Q0 QQ qq QQ qq QQ Qq Qq qq QQ Qq Qq Fig 2 20 The superior and inferior genotypes designed for general environment or specific
21. Genome scan configuration for QTT P M Candidate interval selection The experimental wise type I error for candidate interval selection Putative QTL Detection The experimental wise type I error for putative QTT P M detection QTX Significant Threshold The significant level for QTT P M effects 4 4 Saving and understanding pictures and report 4 4 1 Saving pictures After finishing analysis of QTT P M we can save figures in png or eps format by executing the Export GG for GxG plot or Export GE for GxE plot under the Plot menu Fig 4 9 Eel x QTxX Hetwork Root Help File Exec F al Export GG Export GE vy 83 Test QTT_GNO QTT_PNO gt RAW_PRE 22 OTT NET ta Mag My My My My gt QTT_GBE LOG x Fig 4 9 Saving picture by using Plot menu 41 4 4 2 Understanding the symbols in figure For the GxG plot of QTT Fig 4 10 the red circles denote the main effects of detected significant transcripts acorns Ny 2 Ye Ye 2 2 2 Oo Ga A Ha Aw G gt 8 V T T Fig 4 10 The GG plot of QTT 4 4 3 Understanding text report In order to understand each item in report file we firstly define symbols or variables in the report file then explain the report file using the Fig 4 11 4 14 coming from the simulation data which can be found in the sample folder Sample QTT SampleQTT pre of the QTXNetwork Q or q and QE or qe denote main effect and their interaction ef
22. L 2 3 1 Format of marker linkage map file This file contains information about the marker linkage map such as the number of chromosomes number and order of markers on each of the chromosomes flanking marker distances etc It consists of general description and map body General Description This part is in the front of map file A typical general description looks like _DistanceUnit cM _Chromosomes 4 _MarkerNumbers 6 4 7 9 There are a total of four possible items for general description They can be in any order Each item in general description is a key word followed by certain specification s Each key string must be started ce 99 with an underline and there should not be any list separator white space or table within the key string The specification s must be separated from the key word by at least one list separator and there must also be at least one list separator between any two neighboring specifications if two or more specifications are included for the item A key string and its specification s must be placed in the same line Both key strings and specification s if characters are not case insensitive _DistanceUnit specifies the unit of genetic distances used in the map file The specification string cM stands for centi Morgan and M stands for Morgan _Chromosomes is for specifying the total number of chromosomes or linkage groups involved in the map file _MarkerNumbers is for specifying the
23. Manual of QTXnetwork Content TATU TUCHL Oa OT Oy x fa ans sees te atsbine alesse este se ac tpmautslge ces darts asec aa nas aba osetetee caw eee ese 1 2 User Manual Or OT esr iecausd siete se seen etnias aatenee tan iatabiaee aetna ches ee ete 2 Z MMPOG uctor on CI rarat E A ea eons ET 2 PER O D a T AAA E A E O 2 Ziel Crean a proe oTr O Pire E A T 2 22 Dekio OTEP O C sesso cerca A N A Gael 3 ZS PEC Vino da Eara a a a E E E a A utes 3 DAS Cart OT D a A A 4 2 3 Data file format and running configuration Of QTL ccccccccccceeceeeeeeeeeeeeeeeeeeeeaeaeeaaeaaaaas 5 2 3 1 Format of marker linkage map file sruisrenccnenicierairanaia a aaka a E a 5 Did AFOMA Ol CAVA ea aa a a a 6 2 3 3 QTL algorithm and Configuration cccccccccccccccsssscsssssesseeessseseeseeeeeeeeeeeeeeeeeeeeeeeeeeeees 10 2 4 Saving and understanding pictures and reports ccccccceecsseceeeeccceececeeeeeeeeeeeeeeeeaaaaeaaaaeeeaes 14 OR AGE DAE 0 E E EA CORE eee A IAE A A A AI ATT A ETA rae 14 2 4 2 Understanding the symbols in fiQure cc cccccccsesceseesseseeeeseseseseeeeeeeeeceeeeeeeeeeeeeeeeeeees 14 TA U ndersandino tex TEPO ne en E aT O E ee O ee nn 15 JUser manual Tor OT orraa E EE E ATE EOE E E 19 DUCE OCUC Oron O Teea a i oe aie re anne ET a teaie Matstone 19 Died PRM T OT Steg aces een ees ee eee eee AA te hee eee 19 322 reality a project TOP OV 5 saaria le atte a ie ee ee ee Bl a tare 19 den 2 Deling OTS PO EC sucka a ee eas a ete ee 20 922d OPEC i
24. QTS project is created or a QTS project is opened in main window of the QTXNetwork click the QTS project in the Navigator panel Fig 3 5 to set the algorithm configuration then activate the command item Config under the Exec software menu Fig 3 6 a panel will be popped up for setting configuration Fig 3 7 Fig 3 8 25 QTX Hetwork OF x Root Help File Exec Plot or e p Run Navigator m A Config La C RAW Garo RAW_PNO gt RAW_PRE A REPORTS QTS_NET gt QTS_GBE Fig 3 6 Executing QTS under the Exec of the menu i QTS Algorithm Configuration Genome Scan Gibbs sample size 20 000 W Superior genotype prediction f Accept Iq Cancel Fig 3 7 General algorithm configuration for QTS Map Epistasis Choose this option to detect both single locus effect QTS and epistasis otherwise to detect QTS with single locus effects only High Order Epistasis We define the additive x dominance AD dominance x additive DA and dominance x dominance DD as the high order epistaiss This option is only available for setting F2 population Choose this option to detect QTL with additive A and dominance D effects and also epistasis with AA AD DA and DD effects otherwise to detect epistasis with only AA effect 26 Do 2D Genome Scan Choose this option to detect epistasis QTSs among markers with single locus effects and also without single loc
25. RAW_PRE Af REPORTS QTT_NET QTT_GBE Fig 4 6 Executing QTT P M under the Exec of the menu 39 OT T P M Algorithm Configuration General x Ome Scan Mapping Order EN E Permutation Time 7000 Accept Cancel Fig 4 7 General algorithm configuration for QTT P M Mapping Order Set the mapping order to decide mapping with or without two locus or three locus epistasis 1 denotes that the program only detects single locus effect QTT P M 2 denotes that the program detects both single locus effect QTT P M and two locus epistasis 3 denotes that the program not only detects single locus and two locus effect but also three locus epistasis Permutation Time Set the permutation time to conduct permutation test on significance of QTT P M effects Gibbs sample size Set this value to predict QTT P M effects by Monte Carlo Markov Chain method otherwise by mixed linear model approach Superior x Ome Prediction Choose this option to predict superior genotypes based on QTT P M effects Ref Yang J and Zhu J 2005 Predicting Superior Genotypes in Multiple Environments Based on QTL Effects Theoretical and Applied Genetics 110 1268 1274 40 QTT P M Algorithm Configuration General x Ome Scan Candidate interval selection 0 05 fe Putative QTL detection 0 05 keg QTX Significance Threshhold 0 05 be i Accept i Cancel Fig 4 8
26. RE A REPORTS QTT_NET QTT_GBE Fig 4 5 The window of QTXNetwork after creating or opening a QTT P M project Finally we can click the button Fig 4 5 to start the QTT analysis if all default algorithm parameters are used We can adjust QTT algorithmn configuration before running detailed information refer to the chapter 4 3 2 4 3 Data file format and running configuration of QTT P M 4 3 1 Data format For performing analyses with QTT P M two source data files are required a genotype data file and a phenotype data file The genotype data file contains expression variation for each genotype of all the subjects and the phenotype data file contains observation values of traits under study for all subjects Some sample files for briefly demonstrating the format of source data files for QTT P M in the sub directory Sample QTT where QTXNetwork has been installed The genotype data file with extension name of Gen and phenotype data files with extension name of Phe for QTT can be directly used by QTT P M The genotype data can be organized in two different formats which are summarized in Table 4 1 and 4 2 For the first one Table 4 1 the first line consists of the keyword Ind and molecular names the first column is for the ID or name of individual subjects In the second format the first line consists of the 36 keyword Mk and ID name of individual subjects the first column is for th
27. _Environments specifies the status of experimental design for environments After the key word _Environments write the specification word Yes for having multiple environments or No for only one environment 37 _Replications specifies the status of experimental design for replications or blocks If the experiment is conducted with replications or blocks write the specification word Yes after the keyword _Replications otherwise write No _TraitNumber specifies the total number of traits included in the phenotype data file _Chromosomes specifies the chromosome number and the names in marker file In QTT P M all molecular markers are regarded as lying in one chromosome thus the values after this keyword are 1 and Chr1 _TotalTranscript specifies the total number of the transcripts included in the marker data file and the number of markers in each chromosome The first number must be equal to the summation of all the markers Trait data body This part is between two key strings TraitBegin and TraitEnd The data source includes the environment if available the replication if available and the ID name of subjects as well as the observations obtained for traits studied The following is an example for the trait data body TraitBegin Env Rep Geno Trait 1 Trait 2 Trait 3 l l l 2 44 74 10 04 l l 2 2 4 4 32 8 55 1 1 90 3 54 8 19 10 74 l 2 1 3 17 6 91 11 86 l 2 2 1 9 4 31 11 36 1
28. atever strings to express the sources because they are just used to indicate what the numbers are in the columns below them If the experiment is conducted without environmental factor or replications the corresponding column must be removed And also a semicolon is required at the end of each observation data row The following is an example for the trait data body TraitBegin Env Rep Geno Trait 1 Trait 2 Trait 3 i l l 2 44 74 10 04 l l 2 2 4 4 32 8 55 1 1 90 3 54 8 19 10 74 l 2 1 3 17 6 91 11 86 l 2 2 1 9 4 31 11 36 1 2 90 322 10 54 11 48 2 1 1 5 74 12 78 11 27 2 1 2 7 65 7 02 11 96 2 1 90 6 58 13 92 994 2 2 l 6 01 10 22 9 95 2 2 2 6 22 11 99 7 81 2 2 90 7 98 13 21 12 03 TraitEnd 2 3 3 QTL algorithm and configuration Before conducting QTL we need setting the QTL algorithm configuration Suppose a new QTL project is created or a QTL project is opened in main window of the QTX Network click the QTL project in the Navigator panel Fig 2 5 to set the algorithm configuration then activate the command item Config under the Exec software menu Fig 2 6 a panel will be popped up for setting configuration Fig 2 7 Fig 2 8 Fig 2 9 Fig 2 10 10 QTX Hetwork Root Help File Exec Plot or Run Navigator A B test gt RAW_MA gt H RAW_TXT lei Es fe el a oiz Config Fig 2 6 Executing QTL under the Exec of the menu OTL Algorithm Confi
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30. d F2 IF2 population derived from randomly mating among individuals from DH or RI population See Ref Hua JP Xing YZ Xu CG Sun XL Yu SB and Zhang QF 2002 Genetic dissection of an elite rice hybrid revealed that heterozygotes are not always advantageous for performance Genetics 162 1885 1895 The specification word IF2DH is for IF2 population derived from DH population and IF2RI for that from RI population BxFy Population derived from F1 backcrossing to one of the inbred parents or selfing for several generations In each generation selfing backcrossing or creating double haploid is permitted There are several examples shown as the following figure Pl x P2 Pix P2 Plx P2 Plx P2 F P x Fl Flx P2 Flx P2 amp F2 P x Bl Plx B2 Pix B2 1 F3 P x BIBI B2B B2B amp amp double haploid F4 B1B1B1 B2B F B2B D _Genotypes specifies the total number of genotypes sampled from the mapping population _Observations specifies the total number of observations for each trait studied _Environments specifies the status of experimental design for environments If the experiment is conducted in multiple environments write the specification word Yes after the key word Environments otherwise write No _Replications specifies the status of experimental design for replications or blocks If the experiment is conducted with replications or blocks write the specification word Yes after the keyword _Replications ot
31. e ID or name of molecules The other data are the codes of different genotype in each molecular locus for all subjects These codes need to be defined in phenotype data file corresponding this genotype data file Table 4 1 The first type of genotype data format Ind MK1 MK2 MK3 MK4 MKS5 is MKm l 0 19 137 0 0 0 68 Sai 0 04 2 0 21 1 5 0 0 0 84 E 0 02 3 0 04 0 71 0 0 64 0 as 0 03 n 0 05 1 07 0 04 0 1 07 side 0 05 Table 4 2 The second type of genotype data format Mk l 2 3 4 5 7 n MK1 0 19 0 21 0 04 0 04 0 11 a 0 05 MK2 1 37 1 5 0 71 0 93 1 14 Va 1 07 MK3 0 0 0 0 0 02 ee 0 04 MK4 0 0 0 64 0 74 0 0 MKS 0 68 0 84 0 0 1 86 i 1 07 MKm 0 04 0 02 0 03 0 03 0 03 0 05 General description This part is for specifying the basic features of the phenotype data file and is 6G 39 usually put in front of the data file Each key string must be started with an underline _ and no white space 1s allowed within it There are seven possible items for general description They can be arranged in any order A typical description for a phenotype data file looks like _ Population EXP Observations 33 Chromosomes 1 Chr1 _TotalTranscript 119 119 _TraitNumber 6 _Environments No _Replications Yes _Population specifies the population type used In QTT P M mapping the genotype values are quantitative so we define the population type as EXP _Observations specifies the total number of observations for each trait studied
32. e key word _Environments otherwise write No _Replications specifies the status of experimental design for replications or blocks If the experiment is conducted with replications or blocks write the specification word Yes after the keyword _Replications otherwise write No _TraitNumber specifies the total number of traits included in the phenotype data file _Chromosomes specifies the chromosome number and the names in marker file If all molecular markers are regarded as lying in one chromosome thus the values after this keyword are 1 and Chr1 _TotalMarker specifies the total number of the markers included in the marker data file and the number of markers in each chromosome The first number must be equal to the summation of all the markers _MarkerCode defines a marker coding scheme There are five possible strings for the specifications Each of the strings looks like an equation but no white space is allowed within the string On the left side of the equation symbol is the marker phenotype specification P1 Markers of two alleles being the same as that of P or major allele P2 Markers of two alleles being the same as that of P2 or minor allele F1 Markers of two alleles being the same as that of F F1P1 Markers of two alleles undistinguishable between P1 type and F1 type F1P2 Markers of two alleles undistinguishable between P2 type and F1 type Trait data body This part is between two key strings
33. environment 18 3 User manual for QTS 3 1 Introduction on QTS QTS is one module of the software QTXNetwork for mapping SNP loci associated with genetic variation of quantitative traits of analyzed population This module was developed based on the framework of the QTLNetwork Bioinformatics 23 1527 1536 Bioinformatics 24 5 721 723 The mixed linear model approach combining with Markov Chain Monte Carlo MCMC method were employed to perform association analysis between quantitative traits and SNP loci predict and test genetic effects ascribed to significant SNP locus Parallel computing base on Graphics Processing Unit GPU has been used in some key time costive subroutines The QTS can be run on Window or Mac operation system with or without GPU hardware 3 2Running QTS 3 2 1 Creating a project for QTS The QTS program kept in the folder exe QTS under the QTXNetwork can be run directly in command window or in explore window In default we run it via the shell program QTX Network To run the QTS we first need running the QTXNetwork for creating a new project for the QTS by clicking the button SF in the main window of the QTXNetwork Fig 3 1 a window for creating new project will be popped up Fig 3 2 After selecting module type QTS and specifying project name click the Accept button Fig 3 2 a QTS project will be listed in the left pane named Navigator Fig 3 3 QTI Hetwork ioj x
34. est genotypic value SuperiorHybrid denoting predicted F with the highest genotypic value SuperiorHybrid denoting predicted F with the lowest genotypic value G designing genotype based on general genetic effects of QTS G GEi designing genotype based on general and i th environment specific genetic effects of QTSs For the Fig 3 19 GSL 4 denotes designed general superior line with higher lower trait performance SL i denotes designed superior line with higher lower trait performance in i th environment GSH denotes designed general superior hybrid with higher lower trait performance SH 4 i denotes designed environment specific hybrid with higher lower trait performance in i th environment 30 warlance_conponents population mean 100 6368 phenotypic variance 144 3982 Total Heritability 0 7678 h 2 AtD h 2 AE DE h 2 1 h 2 IE Y e V P 0 1046 0 0732 0 4624 0 0638 0 2322 h 2 A h 2 D h 2 1 h 2 AtAA h2 AR h 2 DE h 2 IE h2 AE AAE 0 0556 0 0490 0 4624 0 0625 0 0662 0 0070 0 0638 0 1301 Fig 3 13 Variance components and heritability ascribed different genetic components _lD_effect QTL SNPID A SE P Yalue D SE P Value AEI SE P Value AE SE P Value l 5 MKS 1 3339 0 3171 2 699e 005 1 41 MK41 0 9428 03171 2 94Te 003 0 9452 0 4466 3 429e 002 1 3273 0 5384 1 370e 002 2 22 IKT 1 6001 0 3291 1 173e 006
35. fect with environment respectively QQ or qq and QQE or qqe denote epistasis effect and their interaction effects with environments respectively QEi or qei QQEi or qqei denote the i th environment specific genetic component effects of transcript protein or metabolism respectively In the Fig 4 11 V e V P denote the residual variance and the phenotypic variance respectively h 2 X denote the proportion of phenotypic variance contributed to the genetic effects of X respectively where X stand for one genetic component effect or summation of some genetic component effects such as h 2 Q is the proportion of phenotypic variance contributed to main effect of detected QTT P M _variance_components population mean 0 7788 phenotypic variance 8 3179 Total Heritability 0 9999 n2 Q V eV P 0 9999 0 0001 Fig 4 11 Variance components and heritability ascribed different genetic components For the Fig 4 12 the first column is the serial number of each detected significant QTT P M the second is the QTT P M ID the succeeding 3 columns are predicted genetic effects standard error and significance probability value respectively The Fig 4 13 presents the proportions of phenotypic variance explained by the genetic component effects of detected QTT P M in the Fig 4 12 42 QTL interval T SE P Value 1 30 ST14 2 8840 0 4539 2141 010 Fig 4 12 Mapping result ascribed to single transcript effects QTL h 2 t 1 3
36. fic effect E Common Genetic effect E Environmental specific effect SimTrait Fig 3 12 The GE plot of QTS 3 4 3 Understanding text report DI ATATDIATODIA 2 22 3 2 3 34 3 42 1 5 3 2 I D TAA ADI DAT DDT AAT AD 2 22 3 34 In order to understand each item in report file we firstly define symbols or variables in the report file then explain the report file using the Fig 3 13 3 19 coming from the F2 simulation data which can be found in the sample folder Sample QTS SimF2_y600 pre of the QTXNetwork A or a D or d AE or ae DE or de denote additive effect dominance effect additive environment interaction effect dominance environment interaction effect respectively AA or aa AD or ad DA or da DD or dd AAE or aae ADE or ade DAE or dae DDE or dde denote additive additive epistasis effect additive dominance epistasis effect dominance additive epistasis effect dominance dominance epistasis effect and their interaction effects with environments respectively 29 I IE denote summation of different types of epistasis effects and environment interaction effects respectively AEi or aei DEi or dei AAEi or aaei ADEi or adei DAEi or daei DDEi ddei denote the i th environment specific genetic component effects of SNPs respectively In the Fig 3 13 V e V P denote the residual variance and the phenotypic variance respecti
37. guration _ General Genome Scan Significance level Output CE lel nigh order Epstass 3 Fig 2 7 General algorithm configuration for QTL Map Epistasis Choose this option to detect both single locus effect QTL and epistasis otherwise to detect QTL with single locus effects only High Order Epistasis We define the additive x dominance AD dominance x additive DA and dominance x dominance DD as the high order epistaiss This option is only available for setting F2 population Choose this option to detect QTL with additive A and dominance D effects and also epistasis with AA AD DA and DD effects otherwise to detect epistasis with only AA effect 11 2D Genome Scan Choose this option to detect epistasis QTLs with or without single locus effects Otherwise the program will only detect the epistasis interaction among QTLs with single locus effects Permutation Time Set the permutation time to conduct permutation test on significance of QTL effects Gibbs sample size Set this value to predict QTL effects by Monte Carlo Markov Chain method otherwise by mixed linear model approach Superior Genotype Prediction Choose this option to predict superior genotypes based on QTL effects Ref Yang J and Zhu J 2005 Predicting superior genotypes in multiple environments based on QTL effects Theoretical and Applied Genetics 110 1268 1274 OTL Algorithm Configuration
38. he marker data for different marker loci must be consistent with the order of markers on each chromosome determined in the map file Since electronic table software usually has a limit on the number of columns in spreadsheet we provide two types of arrangements for marker data Type I MarkerBegin Ind Mkl Mk2 Mk3 Mk4 Mk5 Mk6 Mk7 Mk amp Mk9 l l l 2 2 2 2 l l 2 l l l l 2 2 2 2 2 2 l l l l 2 2 90 1 1 2 2 2 2 2 1 1 MarkerEnd Type II MarkerBegin K Mk Mk1 Mk2 Mk3 Mk4 Mk5 Mk6 Mk7 Mk8 Mk9 1 MarkerEnd NM NNN NRF Re DION NO NO RF DW NNN SS SS W NN me me me FS N NO WO N RR Re ne nee NNR NN aN NO NO NO me ee RK N CO aN NO RR RB RKB N NNN OO GN NN RR rR NNR KF OC OO NO o oe N N N m m m me CC OO NNM NNN D O reer rR NNNNV RK OQO Trait data body This part is between two key strings TraitBegin and TraitEnd The data source includes the environment if available the replication if available and the ID name of subjects as well as the observations obtained for traits studied The second row includes the indicator strings and the names of the traits The number of source strings depends on the experimental design If both environments and replications are taken a maximum of three strings must be inputted the first string for environment Env the second string for replication Rep and the third string for subject Geno You can use wh
39. her phenotype data file format which does not include above key strings If the file does not include some covariates the data source only includes the ID name of subjects and the phenotype values obtained for traits studied The following is an example for the phenotype data file which seems much easier than the previous one SubjectId Trait Trait2 Subject 1 37 40640189 Subject2 1 38 286138 Subject3 1 36 91420189 Subject4 1 31 370838 Subject5 1 35 74930189 Subject6 1 35 572038 Subject7 0 22 91250189 Subject8 0 24 341 49 5 3 2 GMDR algorithm and configuration Before conducting GMDR you first need setting the GMDR algorithm configuration Suppose a new GMDR project is created or an existed GMDR project is opened in main window of the QTX Network click the GMDR project in the Navigator panel Fig 5 5 to set the algorithm configuration then activate the command item Algorithm Config under the Exec software menu Fig 5 6 a panel will be popped up for setting configuration Fig 5 7 QTX Hetwork Biel Ei Root Help File Exec Navigator x Halt 4 gt Sf ol DO test y Algorithm Config Fig 5 6 Executing GMDR under the Exec of the menu Configure GHDE algorithm SNP search dimension Best SNP selection limit Permutation power A Accs 9G cane Fig 5 7 General algorithm configuration for GMDR 50 SNP search dimension
40. herwise write No _TraitNumber specifies the total number of traits included in the data file _TotalMarker specifies the total number of the markers included in the data file This number must be equal to the summation of the numbers for MarkerNumbers in the map file _MarkerCode defines a marker coding scheme There are five possible strings for the specifications Each of the strings looks like an equation but no white space is allowed within the string On the left side of the equation symbol is the marker phenotype specification P1 Marker phenotype being the same as that of P1 P2 Marker phenotype being the same as that of P2 F1 Marker phenotype being the same as that of F1 F1IP1 Marker phenotype that is not P2 type P1 dominant or undistinguishable between P1 type and F1 type F1P2 Marker phenotype that is not P1 type P2 dominant or undistinguishable between P2 type and F1 type On the right side of the equation symbol is the code for the marker type The marker code should always be a single character a number or a letter The symbol dot is used to represent missing marker data or trait value It is not necessary to specify codes for all possible marker types except for F2 population For example if your marker data were collected from a DH population only the specifications for P1 and P2 types are enough Marker data body This part is embraced by two key strings MarkerBegin and MarkerEnd The order of t
41. ile 46 5 2 4 Starting GMDR For example suppose you open a GMDR projected named test and also specify the data files for this project The sample data files are the genotype data file sample MDR SampleData gen the phenotype data file sample MDR SampleData phe and the report file sample MDR SampleData pre respectively then the main window for the GMDR project will exhibits as the Fig 2 5 Finally you can click the button ai Fig 5 5 to start the GMDR analysis if all default algorithm parameters are used You can adjust GMDR algorithmn configuration before running detailed information refer to the chapter 5 3 2 QTxX Hetwork Root Help File Exec qP e amp Navigator x gt 5 41 gt ol ES test E MDR_PNO MDR_GNO Fig 5 5 The window of QTXNetwork after creating or opening a GMDR project 5 3 Data file format and running configuration of GMDR 5 3 1 Data format For performing analyses with GMDR two source data files are required a genotype data file and a phenotype data file The genotype data file contains marker information for each genotype the phenotype data file contains covariate values and observation values of traits under study for all individuals Some sample files are provided for briefly demonstrating the format of source data files for GMDR in the sub directory Sample MDR where QTXNetwork has been installed The genotype data file with extensio
42. ll program QTXNetwork To run the QTL you first need running the QTXNetwork for creating a new project for the QTL by clicking the button P in the main window of the QTXNetwork Fig 2 1 a window for creating new project will be popped up Fig 2 2 After selecting module type QTL and specifying project name click the Accept button Fig 2 2 a QTL project will be listed in the left pane named Navigator Fig 2 3 QTXI HNetwork EE EI Root Help oF Navigator x Fig 2 1 The main window of the QTXNetwork Create Project Project Type QTTP M project name Project NAME decides the name ofthe project folder in which all assets ofthe project houses these assets include copies of source files e g map _pre either selected by user or generated by algorithm plus some configuration files A project folder resid es under root HOME folder If an empty NAME is specified a temporary auto name will be given you can later mov e this project under a desired name A Accent 3 Cancer Fig 2 2 The popup window for creating new project for QTL QTI Hetwork Iof x Root Help File Exec Plot a Navigator Fig 2 3 The window of QTXNetwork for performing QTL 2 2 2 Deleting QTL project Select the QTL project to delete in the Navigator pane and then click the fast button 2 2 3 Specifying data file In a QTL
43. n name of Gen and phenotype data files with extension name of Phe for GMDR can be directly used by GMDR The genotype data can be organized in two different formats which are summarized in Table 5 1 and 5 2 For the first one Table 5 1 the first line consists of the keyword Ind and molecular marker 47 names the first column is for the ID or name of individual subjects In the second format the first line consists of the keyword Mk and ID name of individual subjects the first column is for the ID or name of molecular markers The other data are the codes of different genotype in each molecular marker locus for all individuals able 5 1 The first type of genotype data format Ind MKI1 MK2 MK3 MK4 MK5 bes MKm l H H A A A am A 2 H B H B B H 3 A A H H H Dut B n A A A A A ae H Note There are three types of markers A or 0 for QO genotype B or 2 for qq genotype and H or 1 for Og genotype Table 5 2 The second type of genotype data format Mk l 2 3 4 5 n MKI1 H H A A A B MK2 H B A A A B MK3 A H H A A B MKm A H B A H H General description This part is for specifying the basic features of the phenotype data file and is co 99 usually put in front of the data file Each key string must be started with an underline _ and no white space 1s allowed within it There are five possible items for general description They can be arranged in any order A typical description for a phenoty
44. number of markers on each of the chromosomes The order of the numbers must be consistent with that for genetic distance columns in the map body Map Body This part starts from key string MapBegin and ends at key string MapEnd A typical map body looks like MapBegin Marker Chl Ch2 Ch3 Ch4 1 0 00 0 00 0 00 0 00 2 9 84 11 26 7 45 9 85 3 10 22 8 69 9 10 10 93 4 8 25 9 87 10 66 10 70 5 9 79 10 16 10 10 6 7 47 8 34 11 30 7 11 21 9 30 8 123 9 11 78 MapEnd The strings Marker Ch1 Ch2 Ch3 Ch4 in the second row show the contents of the columns below them The Marker column first column is for the order of all markers on each chromosome the maximum order is equal to the number of markers on the chromosome that has the most markers among all the chromosomes The Ch1 column second column to Ch4 column last column each represents a chromosome or linkage group and contains genetic distances between adjacent markers on the chromosome Specifically the genetic distance for the first marker on each chromosome must be set to zero as the start point of the linkage map for the chromosome the distance for the second marker is between the first and the second markers the distance for the third marker is between the second and the third markers and so on The order of Ch1 column second column to Ch4 last column must be consistent with that for the numbers following the key string MarkerNumbers 2 3 2 Format of data file The
45. pe data file looks like _TotalMarkers 100 _ Observations 1800 _Chromosomes 3 Chr Chr3 Chr5 _TotalSnps 100 53 10 37 _TraitNumber 2 _TotalMarkers specifies the total number of markers included in the marker data file _Observations specifies the total number of subjects for each trait studied _Chromosomes specifies the chromosome number and the names in marker file If all molecular markers are regarded as lying in one chromosome thus the values after this keyword are 1 and Chr1 48 _TotalSnps specifies the total number of the markers included in the marker data file and the number of markers in each chromosome The first number must be equal to the summation of all the markers _TraitNumber specifies the total number of traits included in the phenotype data file Trait data body This part is betyouen two key strings TraitBegin and TraitEnd The data source includes the covariate values and the ID name of subjects as well as the phenotype values obtained for traits studied The following is an example for the trait data body TraitBegin Sex Age Height SubjectId Trait Trait l On 1 74 Subjectl 1 37 40640189 2 40 5 1 687 Subject2 1 38 286138 2 39 4 1 722 Subject3 1 36 91420189 2 50 2 1 697 Subject4 1 31 370838 l 52 2 1 78 Subject5 1 35 74930189 2 39 9 1 687 Subject6 1 35 572038 2 72 6 1 713 Subject7 0 22 91250189 1 36 2 1 685 Subject8 0 24 341 TraitEnd There is also anot
46. project window a button for locate resource files will occur in the toolbar you can locate and import data files a marker linkage map file and a data file which contains observations of the markers and the traits under studied for all individuals for QTL mapping in the popup window after clicking the button e In this panel there are three sections to set input or output files The first is the Genetic map section which contains information about the marker linkage map such as the number of chromosomes number and order of markers on each of the chromosomes flanking marker distances etc The second is the Input data section and you need input data files which integrated the observations of marker and the trait studied into one file The third is the Output report section where the output file name can be inputted Locate Resource Files Genetic map i Input data es Use TXT file Use GNO PNO files Output report Aoo Use PRE files Use LOC INT files a PRE file is output report generated by QTS algorithm which contains selected SNPs interactions among these SNPs and estimated effect of each interaction Further graphical charts and rearranged tables are based on this file If you want to perform QTS algorithm to search meaningful SNPs one of two type of input data must be supplied either one single TXT file or a pair of GNO and PNO files APRE report will be generated on comple
47. rocessing Unit GPU is used in some key time costive subroutines The QTT P M can also be run on Windows or Mac operation system with or without GPU hardware 4 2Running QTT P M 32 4 2 1 Creating a project for QTT P M The QTT P M program kept in the folder exe QTT under the QTXNetwork can be run directly in command window or in explore window In default we run it via the shell program QTX Network To run the QTT P M we first need running the QTXNetwork for creating a new project for the QTT P M by clicking the button SF in the main window of the QTXNetwork Fig 4 1 a window for creating new project will be popped up Fig 4 2 After selecting module type QTTPM and specifying project name click the Accept button Fig 4 2 a QTT P M project will be listed in the left pane named Navigator Fig 4 3 QTI Hetwork Root Help oF Navigator B Es Fig 4 1 The main window of the QTXNetwork 33 Create Project Project Type projectNamefest TT d Project NAME decides the name ofthe project folder in which all assets of the project houses these assets include copies of source files e g map pre either selected by user or generated by algorithm plus some configuration files A project folder resid es under root HOME folder lf an empty NAME is specified a temporary auto name will be given you can later mov e this project under a desired name Accept Cancel
48. scale omics data for complex traits QTX Hetwork Df x Root Help oF Navigator x Fig 1 1 The main window of the QTXNetwork gt Create mew project Create Project QTIL SES Project Type QT TPM GMDR project namer oooO Project NAME decides the name ofthe project folder in which all assets ofthe project houses these assets include copies of source fileste g map pre either selected by user or generated by algorithm plus some configuration files A project folder resid es under root HOME folder Ifan empty NAME is specified a temporary auto name will be given you can later mow e this project under a desired name Accept Cancel Fig 1 2 The popup window for creating new project for QTL QTS QTT P M or GMDR 2 User Manual for QTL 2 1 Introduction on QTL QTL is one module of the software QTXNetwork for mapping quantitative trait loci QTL with epistasis effects and QTL by environment QE interaction effects in DH RI BC1 BC F2 IF2 and BxFy populations and for graphical presentation of QTL mapping results The software is developed based on the MCIM Mixed model based Composite Interval Mapping method and programmed by C programming language 2 2 Running QTL 2 2 1 Creating a project for QTL The QTL program kept in the folder exe QTL under the QTXNetwork can be run directly in command window or in explore window In default you can run it via the she
49. ta file contains observation values of traits under study for all individuals We provide some sample files for briefly demonstrating the format of source data files for QTS in the sub directory Sample QTS where QTXNetwork has been installed The genotype data file with extension name of Gen and phenotype data files with extension name of Phe for QTS can be directly used by QTS The genotype data can be organized in two different formats which are summarized in Table 3 1 and 3 2 For the first one Table 3 1 the first line consists of the keyword Ind and molecular marker 22 names the first column is for the ID or name of individual subjects In the second format the first line consists of the keyword Mk and ID name of individual subjects the first column is for the ID or name of molecular markers The other data are the codes of different genotype in each molecular marker locus for all individuals these codes should be defined in phenotype data file corresponding this genotype data file It should be noted that the the I in Ind and the M in Mk should be as capital letter the others are small letters Table 3 1 The first type of genotype data format Ind MKI1 MK2 MK3 MK4 MK5 k MKm l H H A A A i A 2 H B H B B H 3 A A H H H m B n A A A A A H Table 3 2 The second type of genotype data format Mk l 2 3 4 5 n MK1 H H A A A B MK2 H B A A A B MK3 A H H A A B MK4 A B H A A B MK
50. tables are based on this file Ifyou wantto perform OTS algorithm to search meaningful SNPs one of two type of input data must be supplied either one single TXT file or a pair of GNO and PNO files A PRE report will be generated on completion ofthe searching and charts will be created Ifyou only want to view charts and tables upon existing OTS output just supply the PRE report file You can supply input datafeither TXT or GNO PNO and output reporti PRE all together to view charts and tables based on the report while atthe same time enabling you to perform new search based on the input probably with different parameters and setting from last time You can optionally supply SNP distance information MAP to affect generated charts You can supply none and just close this dialog you can supply source files at any later tirna Accept Cancel Fig 4 4 The window for inputting data files and output file 4 2 4 Starting QTT P M 35 For example suppose we open a QTT projected named test and also specify the data files for this project The sample data files are the genotype data file sample QTT SampleQTT gen the phenotype data file sample QTT SampleQTT phe and the report file sample QTT SampleQTT pre respectively then the main window for the QTT project will exhibits as the Fig 4 5 QTX Hetwork Pije Root Help File Exec Plot or a gt Navigator x QTT_GNO QTT_PNO gt RAW_P
51. tion of the searching and charts will be created If you only want to view charts and tables upon existing QTS output just supply the PRE report file You can supply input data either TXT or GNO PNO and output report PRE all together to view charts and tables based on the report while at the same time enabling you to perform new search based on the input probably with different parameters and setting from last time You can optionally supply SNP distance information MAP to affect generated charts You can supply none and just close this dialog you can supply source files at any later time T Fig 2 4 The window for inputting data files and output file 2 2 4 Starting QTL For example suppose you open a QTL projected named test and also specify the data files for this project The sample data files are the map file sample QTL SimF2 map the data file sample QTL SimF2 txt and the report file sample QTL simF2 pre respectively then the main window for the QTL project will exhibits as the Fig 2 5 Finally you can click the button Fig 2 5 to start the QTL analysis if all default algorithm parameters are used You can adjust QTL algorithm configuration before running detailed information refer to the chapter 3 3 Root Help File Exec Plot gator ris dizia Fig 2 5 The window of QTXNetwork after creating or opening a QTL project 2 3 Data file format and running configuration of QT
52. us effects Otherwise the program will only detect the epistasis interaction QTSs among markers with single locus effects Permutation Time Set the permutation time to conduct permutation test on significance of QTS effects Gibs sample size Set this value to predict QTS effects by Monte Carlo Markov Chain method otherwise by mixed linear model approach Superior Genotype Prediction Choose this option to predict superior genotypes based on QTS effects Ref Yang J and Zhu J 2005 Predicting Superior Genotypes in Multiple Environments Based on QTL Effects Theoretical and Applied Genetics 110 1268 1274 QTS Algorithm Configuration General Candidate interval selection 0 05 Kg Putative OTS detection 0 05 be QTS Significance Threshhold 0 05 Kg i Accept J Cancel Fig 3 8 Genome scan configuration for QTS Candidate Interval Selection The experimental wise type I error for candidate interval selection Putative QTS Detection The experimental wise type I error for putative QTS detection QTL Effects The significant level for QTS effects 3 4 Saving and understanding pictures and report 3 4 1 Saving pictures After finishing analysis of QTS we can save figures in png or eps format by executing the Export GG for GxG plot or Export GE for GxE plot under the Plot menu Fig 3 9 27 QTI Hetwork olx Root Help File Exec of al Export GG Export GE Navigator
53. vely h 2 X denote the proportion of phenotypic variance contributed to the genetic effects of X respectively where X stand for one genetic component effect or summation of some genetic component effects such as h42 A D is the proportion of phenotypic variance contributed to additive and dominance effects of detected QTSs For the Fig 3 14 the first column is the serial number of each detected significant SNP the second is the SNP ID the succeeding 3 columns are predicted genetic effects standard error and significance probability value respectively The Fig 3 15 presents the proportions of phenotypic variance explained by the genetic component effects of detected QTSs in the Fig 3 14 The Fig 3 16 and the Fig 3 17 provide each epistasis effects epistasis environment interaction effects of detected paired QTSs the i th SNP j th SNP and proportion of phenotypic variance explained by these epistasis effects respectively The Fig 3 18 provides predicted genotypic values based on genetic effects of detected QTSs for several designed genotypes QQ denoting the individual with homozygote alleles for all loci as in P qq denoting the individual with homozygote alleles for all detect loci as in P3 F1 denoting the individual with heterozygote alleles for all detected loci as in F of P x P3 SuperiorLine denoting predicted pure line with the highest genotypic value SuperiorLine denoting predicted pure line with the low
54. x C QTS_NET x QTS_GBE x v test at RAW_GNO wi RAW PNO gt RAW PRE gt A REPORTS z 3 gt amp QTS_GBE X y K Fig 3 9 Saving picture by using Plot menu 3 4 2 Understanding the symbols in figure For the GxG plot of QTS Fig 3 10 there are different color circles squares and lines in plot which denote different type genetic effects of QTS detailed definition is presented in the Fig 3 11 Ay P gt Ye Fig 3 10 The GG plot of QTS 28 Graphic Line Epistasis Shape QTL meta system Circle Square with only epistatic with only additive E with only dominance a main effect I effect A effet D na with only epistasis x with only additive x E with only dominance x Green environment interaction effect environment interaction environment interaction IE effect AE effect DE Blue with both I and IE with both A and AE E with both D and DE Dark N tavaiabie WiN no additive W ii no dominance related effect related effect Fig 3 11 The genetic indications for different symbols lines colors in GG plot In the GxE plot of QTS Fig 3 12 the X axis are additive A dominance D and epistasis AA AD DA DD effects ascribed to detected QTSs the Y axis is the values of effects the pink rectangle bars stand for genetic main effects the green line with one integer n on top denote the n th environment speci
55. y show the markers near QTL Output precision The maximum number of decimal places to display value in the output 13 2 4 Saving and understanding pictures and reports 2 4 1 Saving pictures After finishing analysis of QTL we can save figures in png or eps format by executing the Export GG for GxG plot under the Plot menu Fig 2 11 QTX Hetwork Root Help File Exec Pl olx ers a C Eaa rt GG Navigator x 4 gt of Ad o 5 test B RAW_MAP f RAW_TXT gt f RAW_PRE A REPORTS QTM_NET Fig 2 11 Saving picture by using Plot menu 2 4 2 Understanding the symbols in figure For the GxG plot of QTL Fig 2 12 there are different color circles squares and lines in plot which denote different type genetic effects of QTL Fig 2 13 14 K01 0 002 MKO2 10 00 MKO3 20 00 413 X MKO4 30 00 MKO5 40 00 Ch1mko6 50 00 MKQO7 60 00 A MKO8 70 00 1 8 4 MKO9 80 00 MK10 90 00 K11 100 00 K12 0 00 MK13 10 00 MK14 20 00 MK15 30 00 MK16 o00 f a Ch2mk17 50 00 MK18 60 00 MK19 70 00 MK20 80 00 MK21 90 00 K22 100 00 K23 0 00 MK24 10 00 MK25 20 00 MK26 30 00 MK27 40 00 Ch3mk28 50 00 3 60 MK29 60 00 MK30 70 00 MK31 80 00 MK32 90 00 K33 100 00 im iral Fig 2
56. y source files at any later tira Accept Cancel Fig 3 4 The window for inputting data files and output file 21 3 2 4 Starting QTS For example suppose we open a QTS projected named test and also specify the data files for this project The sample data files are the genotype data file sample QTS SimF2_ 600 gen the phenotype data file sample QTS SimF2 600 phe and the report file sample QTS SimF2_ 600 pre respectively then the main window for the QTS project will exhibits as the Fig 3 5 QTI Hetwork Me x Root Help File Exec Plot O RAW_GNO RAW_PNO gt RAW_PRE A REPORTS QTS_NET OTS_GBE Fig 3 5 The window of QTXNetwork after creating or opening a QTS project Finally we can click the button Fig 3 5 to start the QTS analysis if all default algorithm parameters are used We can adjust QTS algorithmn configuration before running detailed information refer to the chapter 3 3 2 3 3Data file format and running configuration of QTS 3 3 1 Data format For performing analyses with QTS two source data files are required a genotype data file or together with a marker linkage map file not requisite and a phenotype data file The linkage map file contains information about the order and genetic distances of all observed markers on the chromosomes or linkage groups The genotype data file contains marker information for each genotype the phenotype da

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