Topics in Bioinformatics Computational Proteomics and Metabolomics
Topics in Bioinformatics Computational Proteomics and Metabolomics BINF 6010
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This 121 page Class Notes was uploaded by Crystal Abshire on Sunday October 25, 2015. The Class Notes belongs to BINF 6010 at University of North Carolina - Charlotte taught by Jennifer Weller in Fall. Since its upload, it has received 11 views. For similar materials see /class/229042/binf-6010-university-of-north-carolina-charlotte in BioInformatics at University of North Carolina - Charlotte.
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BINF 60108010 Fall 2008 Molecular Biotechnology and Genomics Lecture 20 Nov 11th 2008 Lecturer Dr Weller Course Web pages httpwebpaqesuncceduiweller2 Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC Agenda Data Analysis of RAP and V es Practice files for both RAPD and STR have been posted on the class vveu page STR data analysis There are some practice files available folder ltCgtAppliedBiosystemsGeneMapperExamp leDataMicrosatellite These files were generated with the ABI STR kit so the colors and some of the loci are not exactly what we did in class Use the table on the next page tO define the Klt39 for the project Our data will re ruire that 7 cu set u a different kit D6S264 D6S1574 D6S276 D58408 D68308 D6S287 D6S292 D6S434 D58426 D581981 D6S257 D6S446 D58641 D58433 D58406 D584OO D68309 Blue Blue Blue Blue Blue Green Green Green Green Yellow Yellow Yellow Yellow Red Red Red Red 108130 246172 201 233 240285 326354 104138 154176 201 245 274298 112125 167195 212234 299339 6999 168196 221 243 307333 Meta Data Start GeneMapper 40 I Open Panel manager Create the Kit I Define the panel of markers I I Define each marker size and dye I Define a Project I Define size standards I I Add Sample files to Project I Proceed to analysis Note on Practice When you get real data you will have to set up a custom Panel and define a new size standard using ROX we did not use any commercial kit we used a different dye on the standards For the practice part you will use the provided files GeneScan500LIZ GeneMapper Manager 5 I3 gmuler 7 if i Z 5 7 f 1 1 39F rujlsclm BREW Elmug ITahIEQEriIIgs Flmge ngsl Matias Biz Qla39ld aldsl Elmwar Ilns1nn13rrr Analwala Tara D scrmItn 1 3 MlmzMIEJIIM Factn39g Po clznz LHEISSNBU Hgm 1 3733 EIU JZIII39IM39quot V E39UC39E39CIU3913 IDI ICI 339 Cl IJI39I39I IT UCI E39 HILIEEIBIEHIIE C39BI39S JH E39UUIU IE I IIIEI 32 I 19111 MILIEISB39BHIIB jFBIIIIII39S39PTEIWZ EIE 395 mt ram 139 T 55quotquot 739 Clam l Em a lmnn I Emmi J lama I Dgne I Panel Manager Start Project screen ools Panel Manager lDropdwn for Import Panels quot MlcrosalLlllleTutonalfolder Once folder appears click OK SizeReference Data Preject Panel File 9 Add samples Select from Folderon disk IuLUIIaI Data Microsatellite ADD m n w E y GeneSca E E Lmsrnnarv F El LMSMW UV 5 2 hi SNaPshntTulnlla E a Pvmel rm 9 nskallalmn Slanuams 2 5 FucusTmuna Setting size reference Project window Lr39w w ahi thihml w gt u Ega El Enigma i mw Tmb Hun A are a a 3 H m i4 nalys39s MethOd 39 iiilF rEHrl L l lmm JH Emuegmnrw H fl39u 39l39l l39l39lg 39 r V gt For practice use Default JeEmsnn l 39 For new set Choose None 3 h ITIJEELEEIJELR39I E039 HDI39IZ39 Emmi rJ tatad Hum Nore I h IIII2EI EIFIEZI mm sarmlr rJtamr Hun Ire I I 1 l 4 males am Editing an Analysis Method Analysis Method New Microsatellite OK Qumwmp jgignr E Prnjecls Mimi s HEW I TahleSE ngs F Io1 Qe ingsl Nahital Biz Qlanrlamsl Flame Linarum Ins1nr11en139 Anagram Twang scmll 1 373 D JJIwloll Huemalcnila Vra uPuznmcu MIEIEIEHIHIIIE I I39ElJrI LBSISWBI J EDGECID 110 22 CI 3951 ill 3931 MllIIZCEEIIEJII i39lgtFyeljrl E39IJEIEIJE l9 I il 39 7 3 E l39l39l l f Micrusatellilna Clk39 Cancel Dgne Type sets the algorithm and presents the fields a 39 New I Dunn I E HK BIEHE I Import Create the Method 7 Start with General metadata am mm Give it a name yours and Iutorial by preterence Illele Paaknetemrl Psakauilrlvl OualllvFlagsl Analysis Memw punn If this is to be exported to a LIMS system then Instrument information would be im portant WWW Mm Now selectAllele tab Forthe tutorial use the Miorosatellite Binset Bin a runnwmr mm Bin i mm Rtpumpe r on My spam mum mlquot Villa luv mm quotput at mm mum y n u an e quotmama m H a For new data you can also on nimiun in lu 2a use these values iii iii If you had a new locus you might have to mr ZZ gum i customize mmm mmm Assigning dyepeaks WEE Editor Microsatelle Gunterall Allele FNHDIWWWH Faun LHUtlllffl nyuullrgFluuzj Peak Detection Alg nrithm Eagle it Minimum P Bel Height F l Lrl Jmfl12 Eacbaw39DEd aults m Next tab Peak Detector 39 Start with Basic the others add more parameters that you can explore later The minimum peak height has to do with level above baseline in fluorescent units fu For the 310 and 3100 the manufacturers setting is 35fu for baseline set it at 50 fu to give 2 sd above that Automatic gives 10X the noise setting Note that the channels have different amounts of noise CI lei C a nnel Peak Quality Generall Allele lF39eskElE lectnr P93 Elm I Dualrlg39Flagsl A homozygous peak ShOUId be Signal ml 2X the height of a heterozygous Hummous mlnneakhelgh39l 2mm peak and you want a real peak to Amiga Mind Editor Hicrnlaheli Helmmousmlnpeakiheight be significantly above background HETEI ngG39IE DEIIEFIEE umpeahnelgmrana 39 The amount of both peaks for a Peak morphology heterozygote should be equal quotaxia akwidwbase ai39 l 39 9Unless the sample is polyploid PullUPI FIESK P F39EquotE age l Peak morphology this is based Nlalanumher on Gaussian fitting For PCR 1quot WW39E39BS 3973 bands you want the bin to include a A usually Fanhawljarfaults Not all organisms are diploid 9K Save QC and cutoffs 23 This provides a set of weighting Genarall male I Paaknmactm FeakQualiH DUEWFIBQSI values for a number of peak analysis Mind Editor Hicmsatclitc 39g 39giffjquot neme an 139 heightratioshape criteria here 39 iuiuiiuh all except out of bin allele have Spectral Fullup U5 C DI39III39UI Concordance 115 Emmm M mpaakHeighl i M been given the same importance Single Peakmmact CHIStale ll gum ppm f g Peak Haimthtaliu I15 C I39IE39 Hasenalr lele fl 0th DTEIII I F iIIQiB DB BplitF39eaH l 5 PWT lEthUII J j 77 Once the final QV has been Emma FM 395 m mel m 3935 determined the final step is to give GEWPEQMW W E 1quot FWDUm a cutoff for accepting a call Factory Defaults g m Save the settings At this point you are done with the editor Analyzing Data Back to the Project alkmz nghtllldnkrl L L JJEEJ we Em amuse 11m we um screen 3919 393 E E 5 l E quotquot E quot quot quotMmquot 3 1 331 Select the Samples tab 7 1 er 5mm gt L l MWHH 511115 grmnlynpg rmyriamja IIHZmI I39n lm39E il39fn5T r I n maanjza Imam 4 MethOdi h rut2 IJ RE E Mme Eamnlv rJ Eurm V More Mlcrosatelllte Default 1 I rut2Eu1r IElrra Hm39 5mm m earrm Jnne mm H I for practice Microsatellite type and None for bin set for your own IA data ProgressSlab Ifquot l Then Select a Panel click on the top cell in the column A Select window opens Expand the Microsatellite Tutorial folder Double click on Tutorial Panel 9 is entered in the first cell Begin the actual analysis Finally for the Size Standard column assignment Click on top cell in column Select GS500LIZ from the list for the tutorial The top cells are now assigned Click and drag to highlight all three From EDIT 9 Fill down CtrlD Under Analysis 9 Analyze You now have a project that results must be saved to so when the dialog box comes up provide a name MyNameMicrosateliteTutoriaI for example Analyzing Eac sample 9 anaw sequentially results saved to project track with indicator Sample in green is currently in use Failed samples have been tried and faim new circle Successful sizing is indicated by the SQ column cell going green square Yellow triangle is a warning check these Analysis Complete in lower left corner Binning Create the bin set definitions then apply them From Project window 9 Tools Panel Manager M the icon name the BinSet as the Microsatellite Tutorial BinSet I tthe 39 39 Tutorial folder A dialog asks which one Microsatellite Tutorial BinSet type 9 OK Click the New unset icon Select Binning target Expand the Tutorial sampw vldv am 9 The markers in the folder are dioplaycd The Add Reference Data icon is enabled r 7 Marker Name Dye Color Min Size Max Size ControlAllele number alleles etc Create new Bin set Select Bins 9 Add Reference Data In Dialog Box a folder the current project is seen in the lower pane with othe VWJWN that used this panel gselect project clickAdd to list Project moves to the right ClickAdd then OK in Panei Manager Seiect BinS or OptionS Aiieie Naming Rounded basepair 7 Auto Bin options Auto Bin 7 OK 7 Checkthe binsby Viewing seiect a m r er Retevenoe aiieiesvmere bars are Wm Go smves an Vraxts To see the electropherogram select me sample then you can edit create or delete the bin options under Bins menu or rightclick in the pane for a New bin or on me pin to editdelete it 7 To Chan e the Range you can drag the handies on the boundary mes Now Bin Data review Either Sample plot view or Genotype plot views are possible Samples Plot from Project window Display based on name or row number 7 n x Elle gm ylzw nails Alleles zln 4 14 Plot setting Wig pm a IIIgm air WM gal Microsate 39 m5 WEI mugs l T see Default we le sanx emmelr aml los so abes you Mammy 1 i m A a m m as m mUSHOOK at All dyes are eaCh dye shown alone The entire size range in bp is shown FUIIVieW M llll inllli thh l m use m Genotypes view From Project screen 9 Genotypes tab Select genotype sample by row er The marker size range of the selected marker is when 5bp Bins are shown Labels are now shown on xaxis Editing Allele Calls Start in Plot Window drop down menu underAlleles 9 Editing Mode 9 Peak Selection g sumplu rm JElLl Elle gun Mew Inuls Alleles min Access labels in single i i IIIIIE rim rim l dye mode under WW 9 labels 9 either horizontal or vertical Click on the peak to be edited right click for editing options Labeled peaks edit or t mama m rummer ele e Unlabeled peak add an 2 allele call 1 M l 1 ll L I I Al l I Hi AChange History is l quot recorded GQ scores are i grayed out Editing MarkerBin Calls Start in Plot Window drop down menu underAlleles 9 Editing Mode 9 Binning g sumplu pm 49A Elle Edit Mew unis Alleles Hell El IIIIIE HE rim l WWJUIEJ39MIJ m WWW Ei llliirrii ll l r l To change a marker size range click a red triangle marker and enter new values OR drag the handles To change a bin select it then right click and enter new information or delete it or drag the range handles To move a bin select then click and drag BINF 60108010 Fall 2008 Molecular Biotechnology and Genomics Lecture 22 Nov 20th 2008 Lecturer Dr Weller Course Web pages httpwebpaqesuncceduiweler2 Fall 2008 Agenda Hormones flyby Baculovirus expression systems Directed Mutagenesis and Protein Engineering Testing Eukaryotic Expression of constructs Fall 2008 Hormones of the human body htrnhwww h rml Anenuvluhe Pusenuvluhe Hormones are small molecules carried to the site of action by the circulatory system Peptide hormones lYhymm vh mum Steroid hormones Adrenal hormones Secreted by endocrine glands that act as chemical messengers respond Transport to the nucleus N K followed by gene activation Anterior pituitary ctivation of a cell surface tly Cells with the correct receptors will by A protein dIrec Alteration of cell membrane permeability Fall 2008 Hormone functions Hormones are involved in regulatory processes to control metabolism growth water balance etc Nervous system amines like catecholamine dopamine serotonin peptides 2 25aa Ionic communication ion flux chemical transfer of transmitters Endocrine system steroids and modified lipids Fall 2008 4 Classes of Hormones Modified amino acid Peptide and Glycoprotein hormones Melatonin 5methoxyNacetyltryptamine Example Oxytocin hypothalamus to brain and uterus neurotransmitter Example Thyrotropin pituitary to thyroid antidiuretic hormone Insulin is produced by the pancreas acts on muscles regulates carbohydrate metabolism Steroid hormones Glucocorticoids mineralocorticoids aldosterone salt and water metabolism Estrogens like estradiol Modified Fatty Acids stress responses Protaglandins 020 with a 5carbon ring Fall 2008 Melatonin is derived from Trp it is made in the pineal gland light responsive cmquot I39mI C photoreceptor ganglia lt binds to G a protein coupled receptors About half of human disease drugs target this class ofTI I I receptors In 39 I can W e CHMLen ChillLuquot luau 6 Fall 2008 Figure 3 Biasynthetic pathway of steroid synthesis Estradiol is a glucocorticoid critical for sexual function and for bone growth Derived from cholesterol as shown to the right Cholesterol Progesterone l7 ahydmxyv icolmcos emlds Androstenedione t 7ahydroxylt pregnenolone Dehydroepi androsterone Esvrndlol Esrrone 111mm 393 I The ER IS a type nuclear receptor vr wisps when ligandfree it is a monomer in the E quot 39 cytosol When the ligand binds it dimerizes and translocates to the 39 nucleus where it binds DNA activating genes a Fall 2008 7 Prostaglandins cause inflammatory responses regulating swelling blood pressure uterine muscle contraction gastric secretion and asthmatic response They act locally Afatty acid is cyclized by PGHS in a cyclooxygenase activity COX The prostaglandin synthase is on the lumenal surface of the er isoform 1 and the nuclear envelope isoform 2 which is induced by agents like cytokines mitogens and endotoxins r coda nruhid onarte w W v m lip 39lkhnldw a winningHm h Wn w 12minquot If 2 D W r n 14 u m L L mcng a 39U39 39 W tg E Froslaglm ln 433 I an r r MIJ LII In A wVW 5HydropemuyA atosatelru ule I 39DOH hudughm n tugnth kH a Platelet awmam aura 39 aggregation 0 he 39Wtaoe r I Prustiglandln H f L 3139 Thromboxane 1 5 0 335356 9 VW chad3 I 9H K unmarrian A Amigo 39I PLA 13 39A k 3 Activation tquot Prostaglandins 1quot I EHIr wvwoc yaw Lila ag I In amatory DH signaling no DH Pmstaqntlln liqiw u 39 mum 4 w mm aquot mt mhu pmstaglnndinl Thfbl l b l A Fall 2008 PLA2 is phospholipase 2 they are membrane proteins that hydrolyze phospholipids at the sn2 position and release araohidonio acid coxI mm rpmou 1 Ii null J l mu hlwid39 amndu i h I i I L li 39 x 1 d quot nildvpulllt 39 39 Shaman 31 paHli 39u a m i mquot mun 1 riding V I 1i not 1 Cmnulwidu 39 nun mm 39 a Mltmnnk Jud con 1 rm musingJ1 1 drnlml A summm h unamth MIINIIDIKK ind mmmhm nqn anln Mn no pntuuhndin lullM Baculovirus Insect Protein production Baculoviruses infect only invertebrates The types discussed here prefer cells in the midgul of insects The infection cycles includes two forms Infectious nucleocapsid particles that bud off from the living host cell Polyhedric clusters of trapped particles in a protective protein matrix released after cell death Dumping I luluIv Du Fall 2008 Iullnry Blind IThoFon an 111 Mid out I 1110 lInd out Rodshaped viruses Two genera granuloviruses and nucleopolyhedroviruses GVs one nucleocapsidenvelope NPVs multiple nucleocapsids per envelope NCs are occluded in a matrix of granulin in GVs 1 each and polyhedrin in NPVs 1 Polyhedrin is dissolved by the alkaline conditions in the stomach Baculuvirus Mulyticapsid nucleupolyhedrovirus Buddad Virus Dccluded Virus Occlusion Body and ew Palomar Input cupslds was view Biological hl llplm Membrane I 5 ram 5 gm I 3719mm male scale EDD39Olll39 i il SEEMS AZA Fall 2008 Wikipedia cartoon 11 A budding virus 8 internal nucleocapsids occluded virions various orientations of protein Fall 2008 ASM images from viral gallery A Nerma trachea stewed mh Hematuxyhn a d Eesh arm a s1aheu thh mmunuperuxwdase AaTT C Tracheaf mmfemed aNae suh p Traehea epnhehum TE 2 D Trachea frum whirled arvae Expressmg AaTT at suh T The Expressed mm s mum seeh W the ytup asm elf TE eeHs The SWEIHEH nude TN are devmd enhe tuxm E Fat may elf Wanted arvae asu have SWEIHEH nude Fbe F Fat budyfrum HDrHHfE Ed arva parayzed hwmeeheh T BMQWDDmg JDanW 3 Fat budyfmm arva suh p bythe RV vah Was mcubated thh a serum dep eted elf Aa TrspEmfu ahuhemes H 0 Fat may frum Named aNae Expressmg AaTT arruwheads at suh p SeaTe bah 2mm AeD a d SEIwn E4 he Journal 0 Bltpenmemal Beogy 2m 253772545 2mm FaH ZEIEIE Ii 39 Baculovirus bioengineering Example species Autographa californica multiple nuclear polyhedrosis virus AcMNPV The host is the alfalfa looper but the virus is promiscuous Cell culture line from the fall armyworm Spodoptera frugiperda The promoter for the polyhedrin gene polyh is the strongest known among higher organisms not required for virus reproduction so transgenes can replace it Cotransfection of cells needs to include a plasmid with the transgene and a separate virus Fall 2008 14 Transfer Vector Pt I l Directs integration site selection lnsert gene Of interest we homologous recombination Into ACMNPV genome Linearize to Improve recomb freq Transfer vector 330 59 AcMNVP Pt quot X Requires cellular enzymes Pt I ACMN VP viral genome l RecombinantAcMNVP i Pt 15 Detecting recombinants Select regions of clear plaques No polyhedrin so packagingocclusion does not occur 9 lysis instead There are several detection options Colony lifts followed by filter hybridization Colony picks followed by PCR Include the lacZ gene under the control of another AcMNVP late promoter in the construct turn on late in the lytic cycle Add XGal 9 causes colonies to turn blue Subsequent rounds of infection leads to Significant protein yield in 45 days Fall 2008 16 Increasing Frequency of Recombinants Goal make only recombinants via e bl Strategy disrupt two genes with rare cloning site so only double crossover events 9 viable vector R E L136 1 BSU3 LBS 9 Add transfer vector then select Baculovirus Commercial products orinterferon Adenosine deaminase Anthrax antigen Bamyloid precursor protein Binterferon Bovine rhodopsin Bluetongue virus neutralization Ag Cystic fibrosis transmembrane conductance regulator Dengue virus Type1 Ag Erythopoietin GPC receptors HIV1 env protein HSC capsid protein Human AlkPhos Human DNA Pol1 Human Pancreatic lipase Fall 2008 Inf virus hemagglutinin lLK2 Lassa virus protein Malaria proteins Mouse Monocloncal Ab Multidrug transporter protein Poliovirus proteins Pseudorabies virus glycoprotein 50 Rabies virus glycoprotein RSV Ag Simian rotavirus capsid Ag TPA tPA Tissue plasminogen activator tPA A clotdissolving enzyme produced by cells in the walls of blood vessels Used to dissolve clots blocking coronary arteries in heart attack and cranial arteries A secreted Serine protease that converts Plasminogen a proenzyme that is also a serine protease to the active form plasmin one chain becomes two after cleavage linked by S S bonds Tissue plasminogen alor Dasminogen sciv mm 1 7 z 2 activator tPA T PLASMINDGEN A i Factor Xla Xllay I Kalliki eii i PLASMIN Urokinase agrantiplasmii i dzrmacroglobulin FIBRIN X FIBRIN DEGRADATION 4 DUCTS THROMB N 439 Thrombii iractivatable fibrii iolysis inhibitor tPA modules Cterminal domain functional catalytic module the serine protease Ser Pr domain Active site residues are Ser Asp Hi The activity incr ases when ound to brin at the F1 domain and the Cterminal kringle o 39 The serine proteas domain is connected to F1 EG KR KR by a disulphide bridge lfplasmin cleaves the chain the activity is Increase KR1 receptor binding liver KR2 brin binding low af nity Fibronectin linger brin binding high af nity Epidermal growth factor hepatic clearance a Glycosylation sites A th m mummam 7a m mlase IPA Molmlvwdgm as M J Fibwneclln Fingev new MFA Malnculuwalgm m m Tmmvlase Imam M W39 Wism 75 m Sh Do sel Co Bacmid Shuttle Vector uttle vector bacmid An E coli plasmid with A 5 segment of chromosomal AcMNVP DNA between polyh promoter and the gene oriE A lacZ gene with att site that does not disrupt the frame A Kanr gene A 3 segment of chromosomal AcMNVP past polyh bet before polyAtermination signals cloning insert verification plasmid amplification ection in E coli transfect E coli with the plasmid and AcMNVP DNA Double recombination gives recombinant AcMNVP with the GOI Fall 2008 but not polyhedrin With Kan selection this is maintained in E coli since it has the origin of replication 22 ACM N PV In bacteria select for white colonies KanR Amps TetS 9 only recomb bacmids Baomid Shuttle Donor Plasmid Note insertion from donor plasmid disrupts LaCZ inframe transcript will result from the promoter in front of the GOI Modifications in insect cells Modification types and signals are not always the same for example some sugar groups common in mammals are not in insect cells N linked Galactose and Sialic acid Strategy Modify insect lines to express the necessary transferases Butthe correct residues are not always selected Protein processing rules differ between insect and mammalian cells Furin a mammalian protease was coexpressed in insect cells correctly converted a preprotein to the mature form Fa2008 24 Furin activity Cleavage of membrane and secreted proteins by furin in the transGolgi network is a common mechanism which is often required for biological activation Endoproteolysis is mediated by a multibasic motif with the consensus sequence RXKPR V I 5mm quotw Min 391 Hounds MINNIE lmlzn 4 3pm V litrurlnhu l 1 r ICE cl BET l in GPREAEBWAAPS um 7 gm 5 galquot PRRAE gm 7 F um LMAAP 4 I l lFIZFJ39ll R 52 l HEWl 313 am mm momma 1r w 7 an F kWAAFS Mammalian cell factories A number of cell lines are used for transient expression to test constructs COS are African green monkey kidney cells BHK are baby hamster kidney cells HEK 239 are human embryonic kidney cells For stable and highyield expression CHO Chinese hamster ovary cells Mammalian expression vector intron promoter polyadenylation Selectable Marker terminati n From a virus like SV4O Note if you use a different oriE and a different SM in each plasmid it is possible to express two different polypeptides in the same cell Expression is not always equal One vector is often preferentially lost A better option is to clone two genes on the same plasmid separated by an IRES internal ribosome entry site for independent translation Translation control elements GOI Sequence elements include K Kozak initiation 8 signal secretion T affinity tag P proteolytic cleavage SC stop codon Fall 2008 28 pTKbeta vector pUClQ EcoRl HSV thymidine kinase promoter SV40 late 168198 splice signals Notl lacZ Notl SV40 late polyadenylation signal Xbal Hind pUC19 The lacZ gene may be excised by Notl and replaced with alternative sequences Reporter plasmid permitting visual detection of beta galactosidase activity by histochemical staining Designed to express low levels of beta galactosidase or an alternative gene product May be used as a reference plasmid in transfection experiments or to monitor the effect of transacting factors Mlarurward20pr1mer Miapurwdprimer psExapr1mer RmpRiprDmDLEr TKiprnmntEr 1a2a MscI 283 TRTRiprnmnter EstEI 813 an BglII s40 Hmplclllln StuI 1085 Ml ipriFwdiprlmer DTKbeLa 7481 bp pBR322urJg1n Dial 2037 EEDRV 2385 511 2513 lacZ NW sv4oPRLerminatur Eavrevprimer SacI 321a Selectable Markers in Mammalian Expression Vectors Many antibiotic resistance markers are effective in both bacterial and mammalian cells Neo is the neomycin gene A modified antibiotic G418 or Geneticin is used in the media 9 the substrate eukaryotic cells are sensitive to Some selectable markers also increase plasmid copy number DHFRMTX is dihydrofolate reductase methotrexate DHFR is required to synthesize purines MTX is a competitive inhibitor of DHFR The cell responds to MTX by overproducing DHFR usually by amplifying the gene copy number Fall 2008 30 Selective markers in mammalian cells XyIA Blasticidin S Bleomycin Geneticin Histidinol Hygromycin B MSX MTX PALA Puromycin DNA damage Inh Prot Synth Breaks DNA Inh protein syn cytotoxic inh prot synth Inh Gln synth Inh DNA synth Inh purine synth Inh protein synth Adenine deaminase BastS deaminases BIebinding prot Neomycin phosphotransferase Histidinol dehydrogenase Hygro B phosphotransferase Gln Synthetase dihydrofolate reductase Cytosine deaminase Puro N acetyltransferase Deaminates XyIA Deaminates Blast S Binds to Bleomycin Phosphorylates Gen ox Histidinol to His phosphorylates Hygro B overproducers of GS sunive overproducers of DHFR sunive 09 U so C decreases acetylates puromycin Protein engineering Nonrandom engineering considers that codons specify amino acids amino acids define proteins primary information content proteins fold into 2 3 and 4D structural information Structural information encompasses functional information AND parameters information Meaning effects of EVOLUTION and ongoing natural selection Limited success is due to the extent of our knowledge the tools available and our vision of the possible Fall 2008 32 Proteins and evolution Venebrate 3 0L Monocot hemoglobin Annelid 59 Nematode V Hemoglobin V Protozoan a 71 7 quot 739 9 Algal A 2 quot r 7 V v 7 B t I a k gig jug quot ac ena f 4 25 7 7 v v Leer We Ancestral Fungal kg 5quot39 at I I r J oxygsrgtg39iEdmg Leghemoglobin subunit MYOQ0bin of hemoglobin Fall 2008 33 Natural Selection The sickle cell trait the Val 9 Glu change makes Hb fold differently so the proteins stack differently so cell morphology is different 9 resistant to malarial infection Fall 2008 34 Goals in Modifying Proteins Desirable properties Optimize the catalytic efficiency of an enzyme VmaxKm Increase the Km the affinity of an enzyme for the substrate Increase the Vmax the maximal conversion rate of substrates to products Alter the thermal or pH tolerance Modify reactivity for altered solvent properties Remove cofactor requirements Change the specificity Alter allosteric regulatory properties feedback Fall 2008 35 Strategy for Modifying Proteins Directed mutagenesis Alterations are instituted at the DNA level Guided by existing knowledge of structure and conformational changes stabilization properties Changes may require compensatory changes in the sequence Fall 2008 36 Mutagenesis methods Directed Methods Oligonucleotide mutagenesis with the M13 virus PCRamplified Oligonucleotide directed Random Methods Degenerate Oligonucleotide primers Incorporation of nucleotide analogs Errorprone PCR use of particular enzymes Mn skewed dNTPs DNA shuffling recombination of allozymes usually by restriction enzyme fragments followed by ligation Fall 2008 37 M13 based oligonucleotide directed mutagene WI sthnul l 39l11i u39Zquot i pen 1 J 39739 i z i i Why Klenow EMILIHI AH In llll nhhlhtltl linl rm tw39rtna fquot quotquotwi39ri39 Mll lviynl 14va quotquotquotlquotquotquotquotquot 39 39 oSince half the strands are the strand you m predict that 50 of total will be positives Ony 15 are why A quot2 ATTIMSIL I39f l H 3 wk stnahd quot11 ll wplm Lilyu I win flungll 91214 l Tlal l39rlIil l39d Uni LIIL RHJIIII Hi i39 in r 4quot l L 3 L 19 h t g lru Ilv2 d39li39l l Mini 39539 ni39ipunlld Iiiz uh39 L a1 fgamp L ii 1 r c i l 1 we i I I 53 ili IL39HIJI mi n rl l lmrltl in vitro 3 l r11 Fi 3 1 1 2u 31 fl j 39 A 713 T quotJ u k M in h J l 1 NM hugA l Tmm u v 3939Il5lulw 7 n39n39 39l39 11 5 winiru L I ii Ml 1i r lru Use a mutant host E coli dUTPase and uracyl Nglycosylase or dut ungj dUTPase39 allows dUTP pools to increase so misincorporation of U for T occurs in the DNA made by the cells Uracil Nglycosylase39 means the cells are defective in removing those Uracyls After making the recombinant put back into ung This destroys the original strand having the Uracyls leaving only the mutant to be copied Oligodirected on plasmids Insert the target genes into the MOS of a vector that has one functional Tetr one nonfunctional Ampr resulting from a single nt change usual suspects Transform bacteria grow up with antibiotic Purify the plasmid DNA separate the two strands Add three oligos complementary to one of the strands One alters the GOI at a chosen site One corrects the defective Ampr gene One causes a Tetr gene to become nonfunctional Add T4 DNA polymerase the dNTPs and T4 DNA ligase Transform select for Ampr TetS plaques Fall 2008 40 Oligodirected mutagenesis Oligo with position of Change W Separate strands add indicated oligos add T4 DNA pol T4 DNA ligase dNTPs Fall 2008 41 Anneal mumgem Denture rimers J39C iATGV PCR 12w mums Wm Pfu polymemsa Tnnsfarms The original plasmid is methylated but the PCR copies are not Using a methylsensitive RE in the nal step means the original material is digested but the modi ed ones are not OIigonucleotidedirected mutagenesis SL 6 Hum mm s p I H 4 4 39 F 1 2 4 m mm m paiymerase v PCR a El PCRZ ip c mm warn mm u get 5mm andszwdastkmmams mm am round pox 4 mm Tallvn ymemsg spuHFE J J 50 x v Do 2 PCR reactions 1 3 24 They have overlap so if you com 39 products and then PCRbased bIne the se 1 4 half the resulting products will have mutation from 2 and the other halffrom 3 Random mutagenesis with degenerate oligos Inpul plmsplmmnmlllm mum Hum w w r Making degenerate oligos generats all possible variants for a particular nucleotide type at every position Dmmm m quotm i dvantages 1 detailed info of particular residues Symltrn column not required 2 unexpected may be surprisingly good A A Synxhwzm ultgunurlentirli Random mutagenesis using degenerate oligos and PCR Shown here three sites where the nt has been changed After PCR products are denatured then reannealed The GOI is flanked by RE A and B sites so the product is restricted and cloned into a vector with those sites Errorprone PCR mutagenesis A r 39 L a error rate 1 PCR Remova of5 exonuclease l activity increases the rate 40 0 0 Some reaction conditions also increase the ra e Taq is known to be quite 6 errorprone so its use will produce about 01 0 Ow mutations randomly distributed O o o o Random mutagenesis using nucleotide analogs Insert GOI into a MCS next to two adjacent RE sites after digestion 339 and 539 recessed ends are produced Next to cloned DNA is a recessed 339 end l m r Add Exolll degrades from 339 recessed ends but not 339 protruding ends Wuhan T 39 t t39 v 39 ermrna e reac ron F Fill in gap with Klenow 4 dNTPs 1 dNTP analogue 1 77 7 g Transform Ecoi 333 V 39r lelliiww 39 y 7 3 During replication the nucleotide analog will direct the incorporation of a new I lt r nucleotide Puntmum l 1nunItlllnnmun Ell l l quotA39r Al39 I39 V c I AI39 31m was I mucuan IllInn Emu rmlnnrll munr um um r m quotM BINF 60108010 Fall 2008 Molecular Biotechnology and Genomics Lecture 17 Oct 23rd 2008 Lecturer Dr Weller Course Web pages httpwebpaqesuncceduiweller2 Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC Agenda DNA Diagnostic systems ForensicsIdentification Microsatellites RAPD AFLP Molecular diagnosis of genetic disease Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC Simple STRs FESFPS A single repeat sequence o ATTTn THO1 Has nonconsensu alleles TCAT5 11 93 TCAT4CATTCAT5 Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC Compound STRs HUMGABRB15 2 or more types of repeat sequences GATA512GATC24TATC12 vWA compound and nonconsensus alleles ATCT2GTCT34ATCT913 152 ATCT2GTCT4 ATCT5 AT ATCT4 Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC OON 0L08 OSL 0L09 lNIEI J99 39JCI 800E Ilezl or VLOL39 vmViauvwooHma vo vm v vm 9399ELOL 939VVLOL NEIAEI OJ quot8VLOLViVOOLZVLOJVO VLOIVL VLOI9399ELOL939VVLOL CICIO OJ mob 7VOVO VICLVL VLOI mm Wm xueauee seouenbes leedeJ elqngeA ILLSLZG SELLS xeldwoo Identification in Humans DNA forensic applications use tetrant repeats The PCR reaction is more reliable no slippage The size separation of alleles makes the calls more accurate This assumes you pick the size of the amplicon well Some trinucleotides are assUCIaIeu WIUI diseases Forensics tries to avoid personal data not needed for identity How many do you need the level of polymorphism of each STR in the target populations Most variation is in the number of repeat elements Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC Developing the markers Rules for marker development Find unique sequence that flanks the repeat elements The unique sequence must be conserved in the target population Have the shortest possible amplicon length So the difference provided by the repeats gives good resolution of alleles lf multiplex markers are to be used then the above rule may be modified so that sets of alleles don t ovedap Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC Allele Flanking region has unique and conserved sequence TOF r39pK pnmers Fall 2008 Dr Weller BINF 6010 ITSC 8010 8 UNCC Allele 5 Fall 2008 PCR Primer Binding Sites Dr Weller BINF 6010 ITSC 8010 UNCC Allele 5 Fall 2008 Polymerase Chain Reaction Dr Weller BINF 6010 ITSC 8010 UNCC TH01 A simple locus 0 I AATG 511 Allele 5 II 169 bp 6 IIIIII 173 bp 7 IIIIIII 177 bp 8 IIIIIIII 181 bp 9 IIIIIIIII 185 bp 10 IIIIIIIIII 189 bp 11IIIIIIIIIII193 bp Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC AmpFISTR Gel images of microsatellite data 7 1 with 1 hquot QL S mggg may nhn UNCC IIIIllllIlllllIIIIIIIIIIIIIIIllllllllllIIlIllllllllIIIIlII1IIIIIIIIIIIIlllllllllllllllllll 100 110 120 130 140 150 160 1W3 1813 190 200 210 220 230 2413 250 260 2T0 280 2 0331350 l va ll FGA IWWMRWBMEWEWW H WM am am 4m 2m E I II In I ll l IE HIE li E IIIIllllIIIIIIIIIIIIIIIIIIIIlllllllllllllllllllllllllllIIIIIIIIIIIIIIIIIIIIIlllllllllllllllllll 100 110 120 130 140 150 100 170 100 190 200 210 220 230 240 250 200 270 200 290 0301350 l 000 FBA FY990618mA1399 4009 FY990618002994A 2000 mm mm 5m 501k 43930 mm b 5m Weller BINF 6010 ITSC 8010 13 0m UNCC Frequencies Databases and Matches To a s ecified deree of scientific certaint assign the source of specimen K2 John Doe as the contributor of the DNA in specimen Q1 The population matters that is the probability of selecting an unrelated individual at random who matches the DNA of specimen Q1 depends on the genetic background of the individual For some loci a frequency might be 1 in 1000000 in the AfricanAmerican population and 1 in 110000000 in the Southwestern Latino population HOW do we make a quantitauvc StaLClllcnt that expresses the rarity of the DNA profile seen in the evidence What is the chance that the pattern appears by coincidence Fall 2008 Dr Weller BINF 6010 ITSC 8010 14 UNCC Profiler Plus ID Specimen DSSll79 DZISll DISS51 D58818 D13S317 D78820 1212 2930 1520 812 1212 811 From the first kit we get 9 alleles and from the second 6 alleles but two are the same so a total of 13 independent loci COfiler Spechnen D7S820 Q1 811 Fall 2008 Dr Weller BINF 6010 ITSC 8010 15 UNCC Frequency compendium Database The set of alleles can be compared to what has been observed in other experiments using one of a number of population databases D3Sl358 African Southwest Southeast American Caucasian Hispanic 39 39 Allele 1N2101 1N2031 1N2091 1N1911 Q m 0 0123 00120 0 0131 M 01214 01404 00790 0 0838 E m M m m 01 Fall 2008 Dr Weller BINF 6010 ITSC 8010 16 N00 D3Sl358 African Southwest Southeast American Caucasian Hispanic Hispanic Allele N 210 N 203 N 209 N 191 00119 00123 00120 00131 g 00119 00123 00120 00131 E M 00123 00120 m M m m m w E M m m oooo HNNo mHuH NHHN menuw oooo OHNo wNmH KamaN laomo oooo HHNo UO JBD l acwa lUi b l o o N w o o 4 4 o o w V a o o H a o o H N w o o H N o o o H w H Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC Homozygous Locus For locus D381358 we mc a WNW a is homozygous for allele 16 In one population the frequency of allele u s 03071 The likelihood of each allele being 16 is then 0307103071 00943 In a homozygous case the fr h allele frequency squared Fall 2008 Dr Weller BINF 6010 ITSC 8010 18 UNCC Fall 2008 African Southwest Southeast American Caucasian Hispanic Hispanic Allele 1N1801 N 196 1N2031 1N2401 11 00139 00128 00123 00104 0 0128 00123 0 0104 M 00123 00104 0 0128 0 0123 M Dr Weller BINF 6010 ITSC 8010 UNCC Heterozygous Loci For locus vWA the sample had alleles 15 17 From the database the frequency of allele 15 in the selected I o ulation 02361 From the database the frequency of allele17 in the sam le o ulation 01833 The genotype frequency is then 02362 x 01833 x 2 00866 Since for a heterozygous allele we have Frequency 1 x Frequency 2 x 2 Genotype frequency Fall 2008 Dr Weller BINF 6010 ITSC 8010 20 UNCC HardyWeinberg reminder Both allele and genotype frequencies in a population remain constant or are in equilibrium from generation to generation unless speci c disturbing in uences are introduced 2 39 A p2 q2 q2 1 saw 0102030405060708091 at 09 00 07 06 05 0A 03 02 01 0 04 Data is not available for all possible genotype combinations so we use allele frequency instead of genotype frequencies as the basis of likelinooo comparisons e is used as a measure of the effects c rNion subuvso p2 p 1 p 6 is applied at any homozygous locus Fall 2008 Dr Weller BINF 6010 ITSC 8010 21 Profile Frequencies If the loci are independent then the frequency of the complete profile is the product of the individual frequencies 00943 X 00866 000817 D381358 VWA Or 1 in 122 individuals in this population is likely to have this combination of alleles Fall 2008 Dr Weller BINF 6010 ITSC 8010 22 UNCC CODIV loci results Of the 13 loci used in the US recommended by the FBI and used by the states the match probabilities end up being very small eg 154 1017 or 1 in 61016 Some samples may be mixed so you have to take into account the number of possible alleles present in that case Potential contributor alleles NN12 Thus for 4 alleles at a locus 452 10 persons Fall 2008 Dr Weller BINF 6010 ITSC 8010 23 UNCC Reporting p values In order to report how confident you are in the report that a pattern might occur by chance p 2 frequency of finding the profile 1 p 2 frequency of not finding the profile 1 p n 2 frequency of not finding the profile 1n a populatlon of n people 1 p n3 1 or confidence level p31 1 001 Multiply frequency of all loci and determine p for each database then take the most common value of p Increase p by a factor of 10 Determine ifp g 1 1 or W Use n 28ooooooo or 001 99 confidence level Fall 2008 Dr Weller BINF 6010 ITSC 8010 24 UNCC Online Resources h0rt Iandem Repeat DNA Internet DataBase Recent Ugda es NIST Standard Reference Database SRD 130 V gt mr identity testing The anthnrs are snlely respnnsible m the inhrma nn herein 39 W quot7 Ltler Somme Dlvman nun Rulzberg umMe39mI 7mg 5 but 4 n JunReam x mmwmmmmy l Created 1 Jul 2 2r 1137510932 and Dawn J Re mm mvuIlmbIe helpmm Sn org2m e General Information a 39 mm Pager a Pub cadum and Presentadom l mm MST Human Idenu n Pm39ecl Team 0 NLLF ded Pm acts 9 39 39 2 Vlalen als o u a Trmmn u I o atth sues o Glossarv ofcommenlx used terms m Smlt eel and Eurogean Cure Luci as Ce alleles and PCR roduct 511 e o c SIR A an e u Seq ence Informatan IannmateQ 39 goers o u o 25 anAllallc Panem Dr Weller BINF 6010 ITSC 8010 UNCC Fall 2008 Population Survey The studies in this table are grouped by the kits used aud by either populatiou location country of racial origin or racial group A reference munber followed by in mu i J 39 39 ui iuuiilo i 139 l 39 39 l or example Morocco 3106 indicates Lhree Morocco studies are included in reference 31 1 j 1 W North A icau 2152146 12x6 2364 4x2 America American 4xl5 1456 181 El Salvador 77 Hispanic 246 11x5 2364 4x2 4x25 184 Bahamas 1 Canada 2 56x2 Costa Rica 157 Jamaica 1 Mexico 1131 210 2180 190 201mm Native 2x4 2x34 23 4 American 56x3 5033 Trinidad 1 his 2x2111546 13x5 2354 4x2 Caucasian 4xl514 Fuii 7 08 Dr 112 BINF 60131119quot 8010 26 A V Wider maids jammy J d Weep2m 5 1 CI Text Search and Display Interface Our arms In cunstmctTPMD are In snare 39Text Display usem genutypmg mfurmatmn rnemdrng data 7 cumams me data and uf genuwped mrcrdsateurte marker u t PMD 5 ungma auere mfurmatmn germ ypmg resuurces and aburatury mmmunr mkmsa eme suppdns fur prumutmg gendtyprng and gene markers mare dumng er preva ent drseases Map Disp ay TFMD cuntams rnrerdsareurre rnanlters E The make data m TFMD mum ALDIIIIJIJIIIF rm me me an EU udeuude re eats are be searched and arsprayed d sued b fuur uuah ed enutvpmg accurdmg m eymgenene genene 11 aburatunes and presented wun userefnend y and Werner maps mare web mterfaces fur researeners Download ew y deve uped TFMD grapmc Duwn uadTPMD rnanlter d re atabase mm at ke s Prdvrde prutucu s standard makers and Caucasran but alsu facmate he usequmksfrumDrYuheShanJuu smb ct nd d nrd dredrnmdnry used w rnrerdsateurte markers fur renned rna seamquot Query and pdsmdnar eandrdate dumng dr drsease mam WHY ATGC was EMMY em and exprarns me purpuse scape dr Prease key m pmbe dr deds name ex 0552501ATAsADozAFM095m5rnquotSearch g researen and expemed acmevemems dr ueryquot man Chck dd m sndwme resun Or Chck m quotchmmusume quot m Ms 3 To me TPMD A Go a me markers dn trus cnrdm s Nader Amds Researcn 2005 Vu 33 i V D rssue D174eD177 anu have any cummem and duesudn abumTFMD Wynnhaveanycummeman uuesuunabumTF MD Cumzmus Cumamu L u medunFeb usznus r M new NaunnarHeaunResearenrnsumes AH ndms reserved Fall 2008 Dr Weller BINF 6010 ITSC 8010 UNCC E i 3 mugmmencgmmau Chromosome 22 Lucus name mm Het heterozygosity Marker 39 TPMD Genet1c distance In Kasambi cM culumn quuws the publication in The Centerfor Medmal Genetwcs at Marsh eld CHnIc r 1n the co umn etic distance 39Kosambi cM39 means no data In The Center for Medwcat Genetics at Marsh eld Clinic lULdHUlI w u 39 W in compared to that of D228686 The uorescence in 39FLU39 cotumn is the abel at 539end of primers quot 39 39 395 39 39 39 39 The genomic n 133101 and quot391 gt V alletotyplng n u Fall 2008 Omenvise Dr Wel Ier iflquot1f5 86W Weevgoa gm P UNCC Cinulail 3n iataoass ENFSI DNA WG STR Population Database dertaken an extensive Study Collecting STRadata from 24 European e ropean Netw rk of Forensic Science Institutes ENFSl has un populations 5700 profiles using the AMPFLSTR SGM Plus system is which has become one o the standar STR multiplexes to be used within Europe for the purpose of constructing national DNA criminal intelligence databases This allele proportion frequency 5 DNA we srR 39 a can be used to Calculate mat probabilities of DNA population a a ase s all Europe regardless of their specific country of Orlgln been quantified by estimating Fst 1 showing match probabilities of database a further referred o as the 39ENF I profiles from cosmopolitan Caucasian populations acros Differences in allele proportions between populations of the different countries have that the effect is small Fst is approximately 0001 Nevertheless the e ect cannot simply be ignored because DNA profiles derived from a European database will tend to be lower than those derived from an appropriate cognate population database In order to take account or both sampling error and population subsstructuring effects various methods can be applied including the Balding size bias correction 2 the aiding and Nichols Fst correction 3 and an upper bound of a 95 confidence 39nterval 41 which are summarized among rs in a recent publication 5 The task of this website is to make the ENFSI DNA we STR Population Database generally available so that it can be used by forensic laboratories to ena e the calculation of a match probability for a sample using the above mentioned adjustment factors VT 7 rpm m my I Perform Calculation vEnter Pru le 017139 3 va I1h I Us 1311 18 I139J n un gt I I I ii I ll l I ll ll I I ll I ll ll I l F5T om rl VSelect Countries 29 Dr Weller BINF 6010 ITSC 8010 UNCC Pa 2008 Dr WeHerB NF 6010 TSC 8010 UNCC RAPD method Randomly Amplified Polymorphic DNA one of the arbitrarily primed PCR methods No prior sequencespecific information 9 apply directly to any genome An arbitrary short usually a 10mer up to 20mers primer is used in a PCR reaction on gDNA A number of discrete products will result each comes from a region where there are two segments complementary to the primer on opposite strands close enough for effective amplification to occur under the reaction conditions chosen Small amounts of input DNA are needed long a thermocycler and a separationdetection system Polymorphisms based presenceabsence of primer binding sites are identified You cannot knowthe number of alleles or whether a single locus is being profiled without furtherwork so this is usually used in screening diversity not in individual identification Fall 2008 Dr Weller BINF 6010 ITSC 8010 31 UNCC RAPD Markers Dominant markers Change in a primer binding site means no band Changes to sequence within the fragment are invisible Length changes require followup to identify as related alleles Fall 2008 Dr Weller BINF 6010 ITSC 8010 32 UNCC PCR Polymmsu Chaln ReaclIon 51 a Human 9mm mm m 111I1rluclrnl llr A tulrml I Luilw 139 L 7 1 B gym 1 UII mu 1wmdl 8 IJIII39HI 391 t wlmm 3 391 quotAPB 1w 211111114111 1 MIN Ming quot Cullwy J E 39L a I 1 igun 2 An 156789101112 mivcconlm Z V DIME 131 1020 1132 mm M b 1 1110 11123 1043 11141 1011 102111 and 1040 EMBRAG EM ERAS 1 M 1m Md m EMBRAz 12 1E b V mum m ullclc ohwn ml with m cummimx 5 and pnmur lam1mg 13141516171319202121 2311 lplil39lcu un ImrJutl l39m39 primer 1 11 me I and IJ muer d 39cslcd 1111 EL39uRlHmdlll mm 2 and U l c quot In 39 C 1011 1 015 1032101101210174L1nd1030 1311uncs I4 RAPD downsides These are very sensitive to changes in the template quality concentrations of reagents thermocycler gradients and phase of the moon probably SCARs can be used to make stable markers out of these Gel purify the band sequence the product extend the length of the primers Reduces the complexity of the pattern obtained so the information content of the attern 39oes down Fall 2008 Dr Weller BINF 6010 ITSC 8010 34 UNCC with the signal amplification 0 Amplified Fragment Length Polymorphism This combines the sequence fsilgecglificity of restriction enzyme sequence recognition The procedure starts with DNA purification and then uses DNA digestion with two restriction enzymes the method can be tuned at this point by the Fall 2008 selection of the enzymes Adaptors are ligated to the sticky ends that have been generated these are 22 bases long and provide known PCR amplification sites PCR is performed only fragments of a length to be amplified under the chosen conditions will be seen with primers complementaryt of the number of fragments also Fragme W aw Wparww w a gs and visualized o adaptors but with extensions into the unknown sequence allows tuning l Primer1 STAGACTGCGTACC M39H39 CA Msel site 5 g Adapter CTCAGGACTCAT GMTCCTGAGTA Adapter EcoRI site GTAGACTGCGTACC AM 5 cmcmmccnsc mm c Fragment TTA AAT AAT 11135 Primer 1 Keygene protocol Fg FgeMecalcontentsltechnigueslgenotygingghg LMLMLWV x n L A L J D k I w L 39L N JL M L 3 JUL LA I39k N L M 51 A I A M zoubp 3DDbp Aoobp Dznobp zsoh H Am D u n f D quot lV xL vamir 7 A QLR D D N AMA k w N LLF L JLi N 1 WA Add N s by ht z n 30th t lwwwfaoor ldocre l007ae216yae216523I ZSDbp Ehp Size Bases gt uwmuusmwm 2 Relative Fluorescent Units gt GeneMapper software from ABI and GeneMarker software from SoftGenetics FaH2008 Mother Generation 2 if Ml In gqg Qnmnhvl Ea nwanailmn MW 7 an awn L 1 was I u lill I 3 l 1quot l ilt Agt l l It 1 l at 13 1 tgt t l I l x l 4 g I ll IltX X Al rl X 8 I ll l l4 1 x t z 7 11 x 1 1 x I l l l W I 39 L quot quot IA391 J JJwm Avg w M mam k my u w w W M b D E FE W I I Ros E manm v Rhaynrmmmumm a a I 1 4 m m AFLP Considerations Advantages disadvantages highly sensitive hihl re roducible reg eatable technically demanding A huge amount of data results For some fun if you want to predict what sorts of patterns you should get when doing AFLP here is an in silico tool to use insilicoehuegAFLPinfohtml Fall 2008 Dr Weller BINF 6010 ITSC 8010 39 UNCC Molecular Diagnosis of Genetic Disease Generally there is a locus or gene who variants are known for singlegene diseases Sicklecell disease Huntingtons disease For complex diseases there may be several implicated regions in linkage disequilibrium with the phenotype rather than specific sequence variants Fall 2008 Dr Weller BINF 6010 ITSC 8010 40 UNCC Sequence per se Fish out a desired region from a sam le and sequence it Use an oligonucleotide on a solid support that captures a neigthrIng conserved sequence You might clone this if unique sequence needed for restriction or PCR primer recognition is not available for example if a lot of repetitive sequence is in the region Use the plasmid sequencing primer sites to obtain the sequence information To sequence both alleles if the platform available does not let you see more than one Fall 2008 Dr Weller BINF 6010 ITSC 8010 41 UNCC Desert Hedvehov Mutation This is a missense mutation of ATG9 ACG at the initial Met of the first exon of the DHH gene signaling molecules regulating morphogenesis Reference F Umehara et aI AmJHumGenet Nov 2000 l Glut 39GL lL ll K l V G l l l39t l t39 I L IL39L 1 i V l 39leleLlG Sisier Fall 2008 42 Sequence Test Use PCR to select out the sequence of interest as a fragment then apply a second test to be sure it is the correct fragment Length test Restriction digestion of the product leads to 2 products of the expected size Hybridization of probe to product Response to Primers test Oligonucleotide ligation assays 5 nuclease assays Fall 2008 Dr Weller BINF 6010 ITSC 8010 43 UNCC CAPS Assay Cleaved Amplified Polymorphic Sequences CAPS polymorphisms are differences in restriction fragment lengths caused by SNPs or indels 9 chanie RE sites in PCR am licons Locusspecific CAPS assay ampli catinn 7 digestinn 7 gal Separatinn l 4 4 7 HT i oi k O O ll ll Fall 2008 E I 44 CAPS Markers Advantages Most CAPS markers are codominant and locusspecific Most CAPS genotypes are easily scored and interpreted CAPS markers are robust different labs can get the same results The CAPS assay is automatable Developing CAPS markers Se uence the cloned DNA containing the gene Design primers and amplify 800 2000bp DNA fragments Targeting introns or 339 untranslated regions should increase the chance of finding polymorphisms Sequence the PCR product from targeted genotypes determine which REs to use Separately digest the amplicons with one or more restriction emzymes Screen the digested amplicons for polymorphism You can use gels stained with ethidium bromide Fall 2008 Dr Weller BINF 6010 ITSC 8010 45 UNCC Molecular diagnostics genetic disease CAPS used for a specific example In Sicklecell anemia the GLU Val mutation removes a Cvn l RE site CCTNAGG After amplification and restriction a different banding patter appears HbA HbS 5ProGuGu vs 5ProVaGu CCTGAGGAG CCTGTGGAG SI AA AS 88 i l l l l l l l Ill ll 3 GE Eilg l 256 El as Cvnlsites 201 a Ea Ea Ea 181 88 El n5 3 F Fall 2008 Dr Weller BINF 6010 ITSC 8010 46 I UNCC Single basesensitive assay What if the important difference does not give rise to a change in a RE site What if the change is too small to be determined with a hybridizationbased assay The oligonucleotide ligation assay Fall 2008 Dr Weller BINF 6010 ITSC 8010 47 UNCC
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