Primerprobe design Crucial for successful DNA RNA analysis

Primer/probe design Crucial for successful DNA & RNA analysis! • Main source of specificity for PCR

Using the genome Studying specific genes identified by WEB search • Using PCR to focus on specific genes/conditions

Primer/probe design Crucial for successful DNA & RNA analysis! • Main source of specificity for PCR • good primers only bind your sequence

Primer/probe design Crucial for successful DNA & RNA analysis! • Main source of specificity for PCR • good primers only bind your sequence • Also important for microarrays, sequencing, Southerns

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity: only want them to bind at one place

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity: only want them to bind at one place • Main concern: 3’ end should not bind

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Hairpins: may not melt (problem for RT) or may reform

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Hairpins • homoduplexes may not melt May be extended by DNA polymerase

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Hairpins • homoduplexes • heteroduplexes may not melt May be extended by DNA polymerase

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Should match!

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Should match! • Every site calculates them differently!

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Targeting specific locations • amplifying specific sequences

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Targeting specific locations • amplifying specific sequences • creating mutations: need mismatch towards 5’ end so 3’ end binds well

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Targeting specific locations • amplifying specific sequences • creating mutations: need mismatch towards 5’ end so 3’ end binds well • Add restriction sites at 5’ end: may need to reamplify an amplicon

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Targeting specific locations • amplifying specific sequences • creating mutations: need mismatch towards 5’ end so 3’ end binds well • Add restriction sites at 5’ end: may need to reamplify an amplicon • Use Vent or another polymerase with proof-reading , taq’s error frequency is too high.

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Targeting specific locations • Amplifying sequences from related organisms • If use protein alignments need to make degenerate primers; eg CCN means proline, so need to make primers with all 4 possibilities

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Targeting specific locations • Amplifying sequences from related organisms • If use protein alignments need to make degenerate primers; eg CCN means proline, so need to make primers with all 4 possibilities • Code. HOP is a way around this: have a perfect match for 10 -12 bases at 3’ end, then pick most likely candidates for the rest.

Primer/probe design • Also important for microarrays, sequencing, Southerns • Concerns • Specificity • Complementarity: • Melting T • Targeting specific locations • Amplifying sequences from related organisms • If use protein alignments need to make degenerate primers; eg CCN means proline, so need to make primers with all 4 possibilities • Code. HOP is a way around this: have a perfect match for 10 -12 bases at 3’ end, then pick most likely candidates for the rest. • Based on codon usage

Primer/probe design • Stem-loop primers for short RNAs where only have enough info for one primer

Optimizing PCR Choosing enzyme • Template (RNA or DNA? )

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity • Temperature stability

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity • Temperature stability • Processivity

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity • Temperature stability • Processivity • Km • d. NTP • DNA

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity • Temperature stability • Processivity • Km • d. NTP • DNA • Vmax

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity • Temperature stability • Processivity • Km • d. NTP • DNA • Vmax • Tolerance of imperfect conditions • Dirty DNA • d. NTP analogs or modified d. NTP • [Mg] (or other divalent cation)

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity • Temperature stability • Processivity • Km • d. NTP • DNA • Vmax • Tolerance of imperfect conditions • Dirty DNA • d. NTP analogs or modified d. NTP • [Mg] (or other divalent cation) • Fragment ends

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Fidelity • Temperature stability • Processivity • Km • d. NTP • DNA • Vmax • Tolerance of imperfect conditions • Dirty DNA • d. NTP analogs or modified d. NTP • [Mg] (or other divalent cation) • Fragment ends • Cost

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ): Reverse transcriptases from retroviruses make DNA copies of RNA • Tth DNA Polymerase from Thermus thermophilus reverse transcribes RNA in the presence of Mn 2+

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ): Reverse transcriptases from retroviruses make DNA copies of RNA • Tth DNA Polymerase from Thermus thermophilus reverse transcribes RNA in the presence of Mn 2+ • Then dilute rxn & add Mg 2+ to do PCR

Optimizing PCR Choosing enzyme • Template (RNA or DNA? ) • Tth DNA Polymerase from Thermus thermophilus reverse transcribes RNA in the presence of Mn 2+ • Then dilute rxn & add Mg 2+ to do PCR • Tfl DNA Polymerase from Thermus flavus has no RT activity: can mix with RNA & RT w/o activity then go directly to PCR after RT is done

Choosing enzyme • Template • Fidelity • Taq from Thermus aquaticus has no proof-reading

Choosing enzyme • Template • Fidelity • Taq from Thermus aquaticus has no proof-reading • goes faster, but error freq of 1 in 3000 • Vent from Thermococcus litoralis has error frequency of 1 in 30, 000

Choosing enzyme • Template • Fidelity • Taq from Thermus aquaticus has no proof-reading • goes faster, but error freq of 1 in 3000 • Vent from Thermococcus litoralis has error frequency of 1 in 30, 000 • Pfu from Pyrococcus furiosus has error frequency of 1 in 400, 000

Choosing enzyme • Template • Fidelity • Taq from Thermus aquaticus has no proof-reading • goes faster, but error freq of 1 in 3000 • Vent from Thermococcus litoralis has error frequency of 1 in 30, 000 • Pfu from Pyrococcus furiosus has error frequency of 1 in 400, 000 • Genetically engineered proof-reading Phusion from NEB has error frequency of 1 in 2, 000

Choosing enzyme • Template • Fidelity • Temperature stability • E. coli DNA polymerase I denatures at 75˚ C • T 1/2 of Taq @ 95˚ C is 0. 9 hours, < 0. 1 hour @ 100˚ C

Choosing enzyme • Template • Fidelity • Temperature stability • E. coli DNA polymerase I denatures at 75˚ C • T 1/2 of Taq @ 95˚ C is 0. 9 hours, < 0. 1 hour @ 100˚ C • T 1/2 of Phusion @ 96˚ C is >6 hours, 2 hours @ 98˚ C

Choosing enzyme • Template • Fidelity • Temperature stability • E. coli DNA polymerase I denatures at 75˚ C • T 1/2 of Taq @ 95˚ C is 0. 9 hours, < 0. 1 hour @ 100˚ C • T 1/2 of Phusion @ 96˚ C is >6 hours, 2 hours @ 98˚ C • T 1/2 of Vent @ 95˚ C is 6. 7 hours, 1. 8 hours @ 100˚ C

Choosing enzyme • Template • Fidelity • Temperature stability • E. coli DNA polymerase I denatures at 75˚ C • T 1/2 of Taq @ 95˚ C is 0. 9 hours, < 0. 1 hour @ 100˚ C • T 1/2 of Phusion @ 96˚ C is >6 hours, 2 hours @ 98˚ C • T 1/2 of Vent @ 95˚ C is 6. 7 hours, 1. 8 hours @ 100˚ C • T 1/2 of Deep Vent from Pyrococcus species GB-D (grows @ 104˚ C)is 23 hours @ 95˚ C, 8 hours @ 100˚ C

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Phusion is 10 x more processive than Pfu, 2 x more than Taq

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Phusion is 10 x more processive than Pfu, 2 x more than Taq • lets you make longer amplicons in shorter time

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Phusion is 10 x more processive than Pfu, 2 x more than Taq • lets you make longer amplicons in shorter time • Taq = 8 kb max cf 40 kb for Phusion

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • d. NTP: 13 µM for Taq, 60 µM for Vent

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • d. NTP: 13 µM for Taq, 60 µM for Vent • DNA: 2 n. M for Taq, 0. 01 n. M for Deep Vent

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax: >1, 000 nt/s when attached • Binding is limiting, processivity determines actual rate • 1000 bp/min is good for PCR

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax • Tolerance of imperfect conditions • Dirty DNA: in general, non-proofreading polymerases tolerate dirtier DNA than proof-readers except Phusion

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax • Tolerance of imperfect conditions • Dirty DNA: in general, non-proofreading polymerases tolerate dirtier DNA than proof-readers except Phusion • d. NTP analogs or modified d. NTP • non-proofreading polymerases do better, but varies according to the modification

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax • Tolerance of imperfect conditions • Dirty DNA: in general, non-proofreading polymerases tolerate dirtier DNA than proof-readers except Phusion • d. NTP analogs or modified d. NTP • non-proofreading polymerases do better, but varies according to the modification • [Mg]: Vent is more sensitive to [Mg] and needs 2 x more than Taq

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax • Tolerance of imperfect conditions • Fragment ends: proof-readers (eg Vent) give blunt ends

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax • Tolerance of imperfect conditions • Fragment ends: proof-readers (eg Vent) give blunt ends • Non-proof-readers (eg Taq) give a mix of blunt & 3’A

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax • Tolerance of imperfect conditions • Fragment ends: proof-readers (eg Vent) give blunt ends • Non-proof-readers (eg Taq) give a mix of blunt & 3’A • Can use 3’A for t: A cloning GAATTCAtcgca CTTAAGtagcgt

Choosing enzyme • Template • Fidelity • Temperature stability • Processivity (how far does it go before falling off) • Km • Vmax • Tolerance of imperfect conditions • Fragment ends: proof-readers (eg Vent) give blunt ends • Cost @ NEB: http: //www. neb. com/nebecomm/default. asp • Taq = $59. 00 for 400 units • Vent = $62. 00 for 200 units • Deep Vent = $90. 00 for 200 units • Phusion = $ 103. 00 for 100 units

Optimizing PCR • [enzyme] • [Template] • [Mg 2+] • Annealing Temperature • Denaturation temperature

Optimizing PCR • [enzyme] • 0. 4 -2 units/100 µl for proofreaders : start with 1

Optimizing PCR • [enzyme] • 0. 4 -2 units/100 µl for proofreaders : start with 1 • 1 -5 units/100 µl for non-proofreaders : start with 3

Optimizing PCR • [enzyme] • [Template] • 1 -10 ng/100 µl reaction for plasmids • 10 - 1000 ng/100 µl reaction for genomic DNA • Excess DNA can give extra bands, also brings more contaminants

Optimizing PCR • [enzyme] • [Template] • 1 -10 ng/100 µl reaction for plasmids • 10 - 1000 ng/100 µl reaction for genomic DNA • Excess DNA can give extra bands, also brings more contaminants • [d. NTP] • 50 -500 µM for Taq: start with 200, lower increases fidelity, higher increases yield • 200 -400 µM for proof-readers: if too low start eating

Optimizing PCR • [enzyme] • [Template] • [Mg 2+] • 0. 5 - 4 m. M for Taq: start with 1. 5; lower if extra bands, raise if low yield

Optimizing PCR • [enzyme] • [Template] • [Mg 2+] • 0. 5 - 4 m. M for Taq: start with 1. 5; lower if extra bands, raise if low yield • 1 - 8 m. M for proofreaders: start with 2, lower if extra bands, raise if low yield

Optimizing PCR • [enzyme] • [Template] • [Mg 2+] • Denaturation Temperature • Go as high as you can w/o killing enzyme before end • 94˚C for Taq • 96 -98˚C for Vent • 98˚C for Deep Vent & Phusion

Optimizing PCR • [enzyme] • [Template] • [Mg 2+] • Denaturation Temperature • Annealing Temperature • Start 5 ˚C below lowest primer Tm

Optimizing PCR • [enzyme] • [Template] • [Mg 2+] • Denaturation Temperature • Annealing Temperature • Start 5 ˚C below lowest primer Tm • Adjust up and down as needed

Optimizing PCR • [enzyme] • [Template] • [Mg 2+] • Denaturation Temperature • Annealing Temperature • Start 5 ˚C below lowest primer Tm • Adjust up and down as needed • # cycles: raise if no bands, lower if OK yield but extra bands

Optimizing PCR • Most common problems = wrong [DNA], dirty DNA, [Mg 2+] annealing temperature & # cycles

Optimizing PCR • Most common problems = wrong [DNA], dirty DNA, [Mg 2+] annealing temperature & # cycles • Can try “PCR enhancers” to overcome dirty DNA • Use Ammonium SO 4 in buffer cf KCl • Use molecules that alter Tm eg DMSO & formamide • Use molecules that stabilise Taq eg Betaine & BSA

Optimizing PCR • Most common problems = wrong [DNA], dirty DNA, [Mg 2+] annealing temperature & # cycles • If extra bands persist, use Taq bound to antibody • Inactive until denature antibody 7’ at 94˚ C

Optimizing PCR • Most common problems = wrong [DNA], dirty DNA, [Mg 2+] annealing temperature & # cycles • If extra bands persist, use Taq bound to antibody • Inactive until denature antibody 7’ at 94˚ C • Alternatively, try touch-down: start annealing @ too high & lower 1˚ C each cycle ( binds correct target first)

Statistics are to science as the lamp post is to the drunk leaning against it-- they are there for support not illumination. if you laid every statistician on the face of the earth end to end you wouldn't reach a conclusion. . . Probably. Did you hear about. . . The statistician who went out on a limb to obtain a nested design? Why did the statistician become a statistician? He found accountancy too exciting. “A statistician can have his head in an oven and his feet in ice, and he will say that on the average he feels fine. ” " What does a statistician call it when the heads of 10 rats are cut off and 1 survives? Nonsignificant. The first says, "So how do you like married life? " The other replies, "It's pretty good if you don't mind giving up that one degree of freedom!" A statistician was asked how her husband was and replied "Compared with whom? ” What do statistics professors get when they drink too much? Kurtosis of the Liver! If statisticians torture the data long enough, eventually it will confess. "I'm not an outlier -- I just haven't found my distribution yet!” You know how dumb the average person is? Well, by definition, half the population is dumber than that! Are statisticians normal?

Why are physicians held in higher esteem than statisticians? A physician makes an analysis of a complex illness whereas a statistician makes you ill with a complex analysis! "My life is an experiment I never had a chance to properly design. " -- Diana Ballard Did you hear about the statistician who was about to analyze data gathered from a nudist colony? He didn't know whether to use a one or a two-tailed test!!!! What is the difference between a statistician and a mortician? Nobody's dying to see the statistician! We all have heard that statisticians lie with statistics. What do insomniacs do with statistics? They kick them out of bed!!!! A statistician always HAS SOMETHING TO SAY with numbers while a politician always HAS TO SAY SOMETHING with numbers! Arguing with a statistician is a lot like wrestling with a pig. After a few hours, you begin to realize the pig likes it. A lottery is a tax on people who don't understand statistics!! Statistics is the taming of randomness.

The statistician was askedwhy he always used the urinal on the far end. He replied: “There is half the probability of being sprayed by someone else. What do you call a tea party with more than 30 people? A Z party!!! Statistics play an important role in genetics. For instance, statistics prove that numbers of offspring is an inherited trait. If your parent didn't have any kids, odds are you won't either. If a statistics course were a prerequisite for having sex, this country would not have a BIRTH CONTROL problem!! A team of statisticians from an Ivy League school recently discovered that the leading cause of divorce is marriage: everyone who has been divorced has been married first. 50% of marriages end in divorce. Thus if you don't file for divorce, your wife will. What's the difference between a dead possum and a dead statistician lying in the road? There are skid marks in front of the possum. Testing a statistical hypothesis is like flushing a water-saving toilet. . . It must be run past you a number of times before it becomes clear. Never show a bar chart at an AA meeting. Q: Did you hear about the statistician who was thrown in jail? A: He now has zero degrees of freedom. Q: How do you tell one bathroom full of statisticians from another? A: Check the p-value.

Legal proceedings are like statistics. If you manipulate them, you can prove anything – Arthur Hailey * Like dreams, statistics are a form of wish fulfillment – J. Baudrillard * There are two kinds of statistics: the kind you look up and the kind you make up "She was only the statistician's daughter, but she knew all the standard deviations. " The average American has one testicle, one breast and less that two legs! The average statistician is just plain mean. Facts are stubborn, but statistics are more pliable. Mark Twain Actual fact: A Norwegian professor of statistics bears the name of Just Gjessing. If I had only one day left to live, I would live it in my statistics class: it would seem so much longer. Studies have shown that the leading cause of death is life. ” Why did the statistician cross the interstate? To get data from the other side of the median. Have you heard about the statistics joke that went horribly wrong? Even the undergrads could understand it!!