optimisation and validation of pcr method for hla gene

Linköping University | Department of Physics, Chemistry and Biology

Bachelor’s Thesis, 16 hp | Educational Program: Chemical Biology

Spring term 2020 | LITH-IFM-G-EX—20/3892--SE

Optimisation and Validation of

PCR Method for HLA Gene

Expression to Enable PCR System

Transfer and Master Mix Change

Paulina Odlander

Examiner: Lars-Göran Mårtensson

Supervisor: Josephine Overmyr, Dynamic Code AB

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Abstract

98% - 99,85% of patients diagnosed with celiac disease, gluten intolerance, carry either human

leukocyte antigen (HLA) genes DQ2 or DQ8, which is why detection of these serotypes is the

most relevant method in determining celiac disease risk or diagnosis. If suffering from celiac

disease, getting diagnosed and being put on a gluten restrictive or gluten-free diet is a health

profit. Not doing so can lead to deteriorating absorption of nutrients in the intestine leading to

malnutrition, and also long-term complications such as cancer, infertility, autoimmunity and

weakening of the bone tissue.

Health Tech company Dynamic Code AB provides a PCR test for determination of HLA DQ-

genes connected to development of celiac disease. The PCR method is probe based and in real

time and is at this time carried through on the, somewhat outdated, PCR instrument from

Thermo Fisher/Applied Biosystems called 7300 Real-Time PCR System. The run time for this

analysis on the instrument is 1 hour and 50 minutes. The Master Mix in use is TaqMan™ Gene

Expression Master Mix, from the same manufacturer.

Moving on to a more modern PCR instrument is a natural step for the company and is favourable

in several regards, one of them being the run time that will be cut by 50 minutes, allowing for

more samples to be analysed in the same amount of time. The objective is to move the HLA

analysis to Thermo Fisher’s QuantStudio™ 6 and 7 Flex Systems and at the same time change

the Master Mix to SolisFast® Probe qPCR Mix (Purple) from Solis BioDyne, in order to

achieve better accuracy as this Master Mix is more compatible with the latter instrument, along

with reducing reagent cost as it is less expensive.

In order to find the optimal primer and probe concentration for each target included in the HLA

analysis, their concentrations were varied and tested with the new Master Mix on the new

instrument.

PCR instrument transfer and Master Mix change was successful and validation experiments

showed a 98,9% accuracy for the new method compared to the original method.

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Abbreviations

ABI 7300 or 7300 – Applied Biosystems 7300 Real-Time PCR System

HLA – Human leukocyte antibody

IPC – Internal positive control

PCR – Polymerase chain reaction

QS – QuantStudio™ 6 or 7 Flex System

Solis - SolisFAST® Probe qPCR Mix (Purple)

TaqMan - TaqMan™ Gene Expression Master Mix

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Table of Contents 1. Introduction ..................................................................................................................................... 1

1.1. Goal ......................................................................................................................................... 2

1.2. Purpose .................................................................................................................................... 2

2. Theoretical Background .................................................................................................................. 3

2.1. Celiac Disease ......................................................................................................................... 3

2.1.1. Human Leukocyte Antibody ............................................................................................... 3

2.2. Polymerase Chain Reaction ..................................................................................................... 5

2.2.1. The Components .................................................................................................................. 6

2.3. Internal Positive Control ......................................................................................................... 8

2.4. The Reaction............................................................................................................................ 8

2.4.1. Initial Denaturation .............................................................................................................. 9

2.4.2. Replication step ................................................................................................................... 9

2.4.3. Final extension step ........................................................................................................... 10

2.5. Amplification Plot ................................................................................................................. 10

2.6. Ct-value .................................................................................................................................. 11

2.7. Passive Reference Dye, Reporter Dye and Master Mix: Changes on Ct-values ................... 11

3. Methodology ................................................................................................................................. 13

3.1. DNA Samples ........................................................................................................................ 13

3.2. Negative and Positive Controls ............................................................................................. 13

3.2.1. Negative Controls .............................................................................................................. 13

3.2.2. Positive Controls ............................................................................................................... 13

3.3. Reaction Components ............................................................................................................ 14

3.3.2. PCR-mix: TaqMan™ Gene Expression Master Mix ........................................................ 15

3.3.3. PCR-mix: SolisFast® Probe qPCR Mix (Purple) .............................................................. 16

3.4. Oligonucleotide Mixes .......................................................................................................... 17

3.5. PCR Optimisation and Validation ......................................................................................... 18

4. Method .......................................................................................................................................... 20

4.1. Optimisation of Primers and Probes ...................................................................................... 20

4.2. Validation of Modified PCR Method .................................................................................... 20

5. Results ........................................................................................................................................... 21

5.1. Mix 1: DQA1_05................................................................................................................... 21

5.1.1. Mix 1: IPC ......................................................................................................................... 22

5.1.2. Mix 1: Probe 1 ................................................................................................................... 23

5.1.3. Mix 1: Probe 2 ................................................................................................................... 23

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5.2. Mix 2: DQA1_02................................................................................................................... 24

5.2.1. Mix 2: DQB1_02 ............................................................................................................... 24

5.2.2. Mix 2: Probe 1 ................................................................................................................... 25

5.2.3. Mix 2: Probe 2 ................................................................................................................... 25

5.3. Mix 3: DQA1_03................................................................................................................... 26

5.3.2. Mix 3: Probe 1 ................................................................................................................... 27

5.3.3. Mix 3: Probe 2 ................................................................................................................... 28

5.4. Mix 4: DQB1*0302 B ........................................................................................................... 28

5.4.1. Mix 4: IPC ......................................................................................................................... 29

5.4.2. Mix 4: Probe 1 ................................................................................................................... 29

5.4.3. Mix 4: Probe 2 ................................................................................................................... 29

5.5. Validation .............................................................................................................................. 30

5.5.1. Mix 1 ................................................................................................................................. 30

5.5.2. Mix 2 ................................................................................................................................. 30

5.5.3. Mix 3 ................................................................................................................................. 30

5.5.4. Mix 4 ................................................................................................................................. 30

5.6. Final Primer and Probe Concentrations ................................................................................. 31

5.7. Final Affirmation of Genotypes ............................................................................................ 32

6. Discussion ..................................................................................................................................... 36

7. Conclusion ..................................................................................................................................... 38

8. Acknowledgments ......................................................................................................................... 39

9. References ..................................................................................................................................... 40

Appendix A ........................................................................................................................................... 42

1. PCR-plate Setups ....................................................................................................................... 42

Appendix B ........................................................................................................................................... 44

1. PCR Amplification Plots – Optimisation experiments .............................................................. 44

2. PCR Amplification Plots – Validation experiments .................................................................. 50

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1. Introduction

The polymerase chain reaction (PCR) technique is still the most fundamental strategy being

used for gene amplification by scientists all over the world. The technique enables detection of

foreign pathogens e.g. virus and bacteria in biological material, such as human cells. PCR can

also be used to perform genotyping, which refers to the process of determining differences in

genes. Both gene amplification and genotyping are used for medical purposes in detection of

infectious diseases or when determining risk factors for development of genetically caused

disorders.

One genetically caused disorder in humans are in focus in this project - the risk for

genetically disposed coeliac disease. Through genotyping of the specific genes playing the big

role in development of the disease, it is possible to determine the potential risk for a specific

individual to develop it.

Besides the PCR instrument itself, one of the central reagents used in a PCR is the so-called

Master Mix, in which samples are placed, which contains some of the crucial components

needed to perform the reaction.

The health-tech company Dynamic Code AB performs PCR tests for determining risk for

coeliac disease on the 7300 Real-Time PCR System from Applied Biosystems (ABI 7300) which

is a part of ThermoFisher Scientific, a PCR instrument that has been on the market for many

years. Although the instrument still is reliable, switching to the more modern instruments

QuantStudio™ 6 and 7 Flex System (QS) from Applied Biosystems, run time for each analysis

can be cut almost in half, which means almost double the number of samples can analysed in

the same amount of time. By changing the instrument to the QS, it also becomes possible to

scale up the production thanks to the interchangeable well formats, from 96-well to 384-well,

which is not possible for the ABI 7300, an upscale which is relevant for Dynamic Code AB.

Besides this, the QS, compared to the ABI 7300, has a greater sensitivity in detecting small

changes in reactions and overall well-to-well and instrument-to-instrument data is improved.

Changing the PCR instrument will greatly improve the operation at Dynamic Code.

The two methods will be referred to as the ‘original method’, the one currently in use by the

company, carried through on the ABI 7300, and the ‘new method’ or ‘optimised method’, which

is going to be the optimised method, carried through on the QS.

Data obtained from a PCR can be greatly influenced by the Master Mix used in terms of

sensitivity, specificity, accuracy and dynamic range, and specific Master Mixes are optimised

for usage with specific instruments to achieve optimal accuracy in test results. The TaqMan™

Gene Expression Master Mix from Thermo Fisher (TaqMan) is optimised for and

recommended to use with ABI 7300 and SolisFAST® Probe qPCR Mix (Solis) from Solis

Biodyne has compatibility with the QS system. Thus, changing the Master Mix along with the

instrument transfer is essential to attain accurate and precise results. The new Master Mix is, in

addition to this, more affordable which together with the compatibility aspect makes the enzyme

change an important matter for the company.

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1.1. Goal

The goal of the project is to successfully transfer analysis for detecting human leukocyte

antibody (HLA) genes, from an old PCR instrument to a latter one, changing the Master Mix

and optimising the method through adjustments of parameters, in specific, primer and probe

concentrations. The method will be validated, and results should be equal or at least comparable

to the original method.

The objective is to not have the Ct-values generated from the analysis with the new method

differ too far off from the corresponding Ct-values generated from the original method, so that

patient diagnosis based on Ct-values does not have to be re-evaluated and changed.

1.2. Purpose

The purpose of the project is to streamline the testing procedure by cutting down the time for

which a PCR run requires as well as cutting down on reagent cost. Moving on from the outdated

PCR machine to the more relevant version is also eagerly awaited and a natural transition to

make.

Table 1: Planned changes.

Change from Change to

PCR instrument Applied Biosystems 7300

Real-Time PCR System

(Thermo Fisher)

QuantStudio™ 6 and 7 Flex

Systems (Thermo Fisher)

Run time 1 hour 50 minutes 1 hour

Master Mix TaqMan™ Gene Expression

Master Mix from Thermo

Fisher

SolisFast® Probe qPCR Mix

(Purple) from Solis BioDyne

Passive Reference Dye ROX Mustang purple

DNA polymerase AmpliTaq Gold DNA

Polymerase

SolisFAST® DNA Polymerase

Probe used TaqMan® TaqMan®

Instrument compatibility 7300 System QuantStudio™

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2. Theoretical Background

2.1. Celiac Disease

Celiac disease is a chronic autoimmune disease that causes ingestion of gluten protein to start

an inflammation that damages the intestinal tract of the small intestine, which can lead to

deteriorating absorption of nutrients in the intestine leading to malnutrition, and also long term

complications such as cancer, infertility, autoimmunity and weakening of the bone tissue

(Megiorni et al. 2009). Since celiac disease is a genetic condition, the spread of individuals

carrying the genetic variation that causes celiac disease is uneven distributed throughout the

world, although it exists on all continents (Lindfors et al. 2019) with an average occurrence of

approximately 1%-2% in Europe (Catassi et al. 2007). Although the disease is common, a vast

majority of genetically predisposed individuals do remain undiagnosed, ostensibly due to a

vague symptom picture or a complete lack of symptoms (Megiorni et al. 2008). There is a health

profit in getting diagnosed and being put on a gluten restrictive or gluten-free diet, which to this

date is the only effective treatment (Tack et al. 2010), which is why Dynamic Code is providing

a test for detection of celiac disease.

The test detects the presence of DQ2.5-, DQ2.2- and DQ8-alleles (genetic predisposition),

by gene amplification through PCR. Specific antibodies for tTG-IgA and total-IgA in the

sample (to rule out igA-sufficency) is also detected through enzyme-linked immunosorbent

assay (ELISA)-based analysis. Anti-tissue transglutaminase, i.e. Anti-tTG, and anti-endomysial

antibodies, i.e. EmA, is detected through serologic screening, e.g. ELISA, and the presence of

these indicates on an active phase of celiac disease in the patient (Megiornia et al. 2008).

2.1.1. Human Leukocyte Antibody

The majority of the genetic risk factors for developing celiac disease lie within the over 200

genes located in the region for the major histocompatibility complex (MHC), in humans titled

human leukocyte antibody (HLA), on chromosome 6.

The HLA complex, which is the most gene-dense region in the entire genome, codes for

around ten thousand different cell surface peptides, i.e. antigens, especially located on dendritic

cells, B lymphocytes and macrophages, that can be recognised by T cells that produce immune

responses to fight foreign pathogens, thus playing a crucial role in the immune system (Shen

et. al, 2010; Williams 2001). If immune cells recognise self-antigens as foreign antigens,

autoimmune diseases, such as celiac disease, can occur.

The MHC is divided into three class regions, I, II and III. Within class II lies loci for HLA DQ-

genes, which will be in focus in this report. The HLA-DQ gene complex furthermore consists

of two genes, HLA-DQA1 and HLA-DQB1. Further, the gene complex and the genes combine

in different serotypes and haplotypes, some of them listed in Table 2.

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Table 2: Genetic variants in the HLA gene complex that can cause celiac disease.

Name Type Serotypes Haplotypes

HLA-DQ Gene complex 2, 8 -

HLA-DQA1 Gene - 03, 05

HLA-DQB1 Gene - 02, 0302

Table 3: Combinations of allelic variants of the DQA1 and DQB1 alleles and the risk the combinations compose in

developing celiac disease (Megiorni et. al 2007).

HLA-DQ heterodimer Risk for developing

celiac disease

DQ2.5 and DQ8 Very high

DQ2.5 (with a double dose of DQB1*02) Very high

DQ8 High

DQ2.5 (single dose of DQB1*02) High

DQ2.x (double dose of DQB1*02) High

DQ2.x (single dose of DQB1*02) Low

DQX.5 Extremely low

DQX.x Extremely low

In almost all cases, genetically predisposed individual’s express HLA-DQ2 or HLA-DQ8

variants (Table 3), which makes detection of these serotypes the most relevant method in

determining celiac disease risk or diagnosis (Megorini et. al 2008; Brown, Guandalini, Semrad

& Kupfer 2019; Cecilio & Bonatto 2015). Both genes code for α/β heterodimers involved in

mediating the activation of CD4+, gluten-specific T-cells, with gut-homing potential possibly

leading to lymphocytic elimination of epithelial cells (Jabri & Sollid 2017).

The two HLA genes, DQ2 and DQ8, account for approximately 98% - 99,84% of patient

diagnosis, based on a large European collaborative study, one American study and one Italian

study (Karell et al. 2003; Megiorni et al. 2009; Pietzak et. al 2009), and approximately 95% of

patients carry allelic variants DQA1*05 and DQB1*02 in DQ2 gene, or DQA1*03 and

DQB1*0302 in DQ8 gene (Megiorni et. al 2007), although heterozygosity for either of the DQ2

or DQ8 alleles also induce a risk. Detection of the sensible DQ genes does not predict

development of celiac disease but their absence means a negative prediction of the disease to

close to 100% (Wolters & Wijmenga 2008).

The HLA complex is the most convoluted and polymorphic genetic system in the entire human

genome to ever be discovered. One single locus can be possessed by (for HLA-A, HLA-B,

HLA-C and DRB1) hundreds of different allelic variants (Williams 2001), each variant

determining which antigens will be presented on the cell surface. Because of the redundancy in

allelic variants, the chance that an individual will possess the same allele on both chromosomes

is small, resulting in a wide variation of genotypes within the human population. Furthermore,

the two alleles operate in co-dominance, making the variance even more complex. Some of

these allelic variants (presented in Table 2 and Table 3) are known to cause celiac disease.

HLA class I and II genes show significant sequence homology due to their mutual descend

from the same common ancestor as a result of former gene duplication events. The genes have

closely related pseudogenes (defect, non-functional genes) which errors prevent successful

transcription and translation. These facts make primer designing for PCR diagnosis a critically

important matter to accomplish locus specific amplification in molecular diagnosis. HLA allele

identification is to be considered the most complex problem in molecular diagnostics, with

more than 1300 known HLA alleles (Williams 2001).

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2.2. Polymerase Chain Reaction

The polymerase chain reaction (PCR) allows for exponential amplification of specific DNA

fragments through repeating of cycles under specific conditions (Harris 1998). The reaction is

continued until desired amount of product is acquired, often around 40 cycles. After 40 cycles,

one single DNA molecule could theoretically have generated over a thousand billion copies (240

= 1,099,511,627,776). Although, in reality, amplification efficiency is not always 100% but

rather 90-105% (Johnson et. al 2013).

PCR is an artificial mimic of when a cell, in vivo, replicates its DNA. Although a cell uses

the aid of helicase to separate the double strand and RNA primase to add primers to the strand,

the procedure is not far off from what occurs during a PCR.

PCR has several fields of applications within molecular biology, such as gene expression,

genotyping (detecting), mutagenesis, sequencing, cloning, etc. In this study, the DNA yield is

used to detect variants of the HLA genes. In fact, the study of allelic sequence variation within

the HLA locus via PCR was in 1986, only the year after the PCR method first was invented,

the inception to forensic analysis based on PCR (Saiki et. al 1986).

The technique advanced into what is called quantitative PCR (qPCR) (also known as real time

PCR but not to be confused with reverse transcriptase PCR as both tend to be abbreviated RT-

PCR). qPCR allows for real time analysis of quantity of PCR product by measuring relative

fluorescence emitted from unspecific fluorescent dye or fluorescent-labelled target-specific

probes, which will be directly proportional to the amount PCR product being produced (more

on probe-based qPCR under ‘Probe’) (Maddocks & Jenkins 2016).

From here on, mentions of “PCR” in this report will be referring to quantitative PCR.

Figure 1: Real-time quantitative PCR (qPCR) and TaqMan® probe chemistry mechanism.

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2.2.1. The Components

Needed to carry out a quantitative polymerase chain reaction are, besides the PCR instrument

itself and the PCR plate (often 96-well) or PCR tube, following reagents: template DNA,

primers, dNTPs, Mg2+, reaction buffer, polymerase and nuclease free water, and some sort of

reporter molecule. These components together are what is commonly called a Master Mix.

First of all, a template of what is actually being replicated and amplified is necessary. This is

often referred to as the ‘sample’. Template DNA can be derived from a eukaryotic cell, in that

case often in the shape of linear DNA originated in the nucleus, or from a prokaryotic cell in

the shape of a circular bacterial plasmid, or even a virus (the template can in this case even be

derived from RNA and must be converted into complementary DNA through reverse

transcription)(Pfaffl 2010; Maddocks & Jenkins 2016; National Laboratory of Enteric

Pathogens et. al 1991).

Either form, the genomic material of interest must be extracted from whatever cell or capsid

it resides in and purified, before it can be used as a template in PCR analysis.

In a cell, when single stranded DNA is exposed and ready to be transcribed, a primer needs to

be attached to the strand to act as an indicator on where in the genome the transcription is to be

initiated and simply as a primer for nucleotides to further be added to during elongation of the

strand. The primer, a short nucleic acid strand, is added by the enzyme RNA primase in the cell.

The same is true for DNA amplification through PCR: it is only possible under the aid of

primers, a forward and a reversed. This is where synthetic primers, also called oligonucleotides,

come in use.

These are synthetic DNA segments, around 15-30 nucleotides in length, designed to

complementary attach to those particular parts in the template DNA where the start of

transcription is desired (Harris 1998). The primers will run in the opposite direction to the

template DNA, and in turn also run in opposite directions to each other. This means one primer

will run in the forward direction, from the 3’ end, and one primer also 3’ to 5’ but in the reverse

direction to the other primer.

Amplification of two or more target sequences simultaneously is also possible through

multiplex PCR by adding multiple sets of primers to the Master Mix along with different probes

to detect each sequence through its unique fluorescence signal (Basu 2015).

Attaining PCR product is rarely the problem, it is attaining specific PCR product that is the

tricky part. Primer design is a crucial part in PCR (especially in multiplex PCR where several

targets are being amplified in a single reaction) as primers need to be specific enough to not

attach to unwanted parts in the genome (or even to another primer in the mixture, called a primer

dimer) so that random regions in the DNA get amplified. Each primer pair (forward primer and

reverse primer) should enable effective amplification of strictly one amplicon. Very short

primers are often not specific as they risk to complement not only the target sequence and thus

misprime, while long primers mean hybridisation rate will be reduced and by extension, yield

will be small (Basu 2015).

When primers have attached to the exposed single stranded DNA, it is time for the

hybridisation, that is, the annealing of complementary nucleic acids to the template DNA to

extend the forming DNA strand. The hybridisation is catalysed, both in the cell and in a

polymerase chain reaction, by an enzyme called a polymerase (Ishino & Ishino 2014).

The polymerase commonly used in PCR, Taq polymerase, is a thermostable DNA

polymerase isolated from the extreme thermophile bacteria Thermus aquaticus which, thanks

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to its resistance to high temperatures (while DNA denatures during denaturation steps in PCR,

Taq polymerase stays intact and active), small size, and absence of nuclease activity, makes it

applicable for the field of application (Chien et. al 1976).

Taq polymerase binds to the 3’ end of the primer and synthesises approximately 1 kb each

minute (2 kb the first, initial minute) at an optimal elongation temperature of 70-80 °C (Lorenz

2012), through extension of both primers in 3’ to 5’ direction to the template.

Figure 2: Primers (blue and orange) annealed to template DNA (bold), and Taq polymerase elongating the chain in 3' to

5' direction to the template DNA (arrows).

Deoxynucleotide triphosphates (dNTPs) come in the form of dATP, dTTP, dGTP and dCTP,

each representing one of the four nitrogenous bases adenine, thymine, guanine and cytosine,

and each binding through hydrogen bonding to its corresponding base in the template DNA.

These are the building blocks required to build the new DNA string and need to be in equal

concentration in the Master Mix (Harris 1998).

For proper function, the polymerase needs magnesium cations, which act as a cofactor to the

enzyme as the ions, through interactions with the active site in DNA polymerase and the dNTPs,

catalyses the formation of phosphodiester bonds between the dNTP and the primer on the 3’

end. In addition, the magnesium ions stabilise the structure through bindings and decreases the

negative charge.

As for the other components in the Master Mix, the concentration of magnesium ions can

greatly impact the outcome of the PCR product. An excessive amount of magnesium may lead

to non-specific amplicons due to increase in polymerisation activity, but decrease in overall

reliability and consistency, while an insufficient amount of magnesium will do the opposite and

reduce polymerisation but increase infallibility.

Contribution of magnesium ions to the mixture often come in the form of MgCl2 or MgSO4

and are usually included in the reaction buffer (Slack et. al 2011).

KCl and Tris are often main reagents in the reaction buffer, which key tasks are to contain the

pH balance and maintain ion levels. pH value for the buffer at room temperature is 8.2 to 9 but

when temperature increases, pH for Tris (and thus the buffer) decreases. When the reaction

temperature rises to 72 °C, which is optimal extension temperature for Taq polymerase, pH

decreases to 7.0-7.5, which also is the optimal pH for Taq (Harris 1998). This way the buffer

maintains optimal reaction conditions throughout the PCR.

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As stated by the name, quantitative PCR gives the opportunity for quantitative analysis of DNA,

i.e. it is possible to determine how much amplicon has been created in real time throughout the

reaction, in comparison to regular PCR, where yield has to be analysed post reaction through,

for example, gel electrophoresis.

Measurement of quantity of the amplicon in real time is made possible through fluorescent

labelling of the PCR product, either with fluorescent dye or fluorescent probes. Fluorescence

emission is measured after each cycle and the signal is proportional to the amount of PCR

product generated.

As opposed to dye-based qPCR, where fluorescent dye binds non-specifically to DNA and

therefore gives non-specific signals, probe-based qPCR is designed to complementary bind to

desirable sequences in the DNA. Just like primer designing is a crucial part of a successful PCR,

so is probe designing. Properly designed probes enable accurate and dependable detection,

which is the basis for qPCR (Basu 2015).

The probe is tagged with a fluorescent reporter. Its emission gives rise to fluorescence

resonance energy transfer (FRET), which is the basis of real-time detection. On the probe, close

to the reporter, is a quencher molecule. When the quencher is present, fluorescens emission

from the reporter is quenched. Then Taq polymerase extends the DNA chain, it hydrolyses the

probe with its exonuclease activity. When the reporter dissociates from the primer and distance

itself from the quencher, fluorescence is emitted and recorded by the detector. Every tagged

molecule sends out its own signal which means signal generated is in direct proportion to the

number of molecules being synthesised – the more molecules, the more intense signal (Wong

et. al 2015).

2.3. Internal Positive Control

An internal positive control (IPC) is sometimes included in the PCR mix so as to detect any

PCR inhibiting substances in the DNA samples (naturally present or added as a result of

contamination in the lab during sample processing and nucleic acid purification), a faulty

sampling or otherwise degradation of the DNA, minimising the risk for false-negative results

or decreased sensitivity (Schrader et. al 2012).

The control sequence is amplified along with the other target sequences and detected with

a different probe to rule out failed amplification in cases where the target sequence could not

be detected.

2.4. The Reaction

The reaction consists of three stages, as displayed in Figure 3: an initial denaturation,

performed just at the beginning of the reaction, followed by a cycling of three temperatures

during the replication step, and ended with a final extension.

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Figure 3: A typical PCR program with its cycles and temperatures.

2.4.1. Initial Denaturation

During the initial denaturation, double-stranded DNA denatures under high temperature to form

two single strands of DNA. The temperature is set to around 94 °C to 98 °C. For G-C rich

template DNA, the temperature is set closer to 98 °C due to a phenomenon called base-stacking,

which bases guanine and cytosine contributes to. Base-stacking energy contributes to DNA

stabilisation which is why G-C rich DNA will require a higher temperature to denature

(Yakovchuk et. al 2006). Initial denaturation temperature is also dependent on the optimal

temperature for the DNA polymerase activity.

Formation of secondary structures within the template DNA due to unbroken hydrogen

bonds may prevent proper primer annealing and disruption of the polymerase. However, too

high melting temperature may also cause the polymerase to denature, resulting in lower product

yield.

The initial denaturation, performed once before the cycling begins, is of importance because

it ensures that all double stranded DNA is separated into single strands so that primers can

anneal to the target sequence. The high temperature also helps with inactivating possible

nucleases in the sample, that otherwise risk to degrade DNA and primers (Lorenz 2012).

2.4.2. Replication step

DNA amplification takes place during the cycling process in the replication step. Denaturation,

primer annealing and extension/elongation is alternated in thermal cycles, around 40 of them.

After denaturation for approximately a minute, temperature is lowered to around 50-65 °C

(5 °C below the melting temperature for the primers is optimal), thus entering the annealing

step. Now, primers have the time to anneal to their target sequences on the DNA template and

extension of the new DNA strand can begin. The temperature is once again increased, this time

to around 72 °C, to meet the optimal annealing temperature for the polymerase. During the

elongation, the polymerase extends the primer in 5’ to 3’ direction, creating a complementary

DNA strand to the template.

After each cycle, the amount of product created is doubled (at least theoretically). Cycling

is ended when desired amount of product is reached (Lorenz 2012).

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2.4.3. Final extension step

When desired amount of product is reached, the final extension takes place, during which

uncompleted amplicon is given extended time to finish. During this time, if Taq polymerase is

used, the addition of 3’ adenine residue overhang is added to the amplicons – a useful

modification for some subsequent steps when gene cloning (Lorenz 2012).

2.5. Amplification Plot

Figure 4: A typical amplification plot showing eight amplification curves generated from five samples. Two target

sequences were amplified, “purple” and “orange”. All samples showed substantial amplification for target “purple” and

all of them did at some point cross the threshold value, 0.05. Only in three samples was target “orange” amplified, though

not efficient enough for any of the samples to cross the threshold value, 0.2.

From the amplification plot generated by the QuantStudio™ Real-Time PCR Software, each

sample will appear as a sperate curve (as long as they give rise to any fluorescence emission)

and plotted with the number of cycles in the PCR on the x-axis against the normalised

fluorescence intensity on the y-axis. Rn (normalised reporter) is the fluorescence of the reporter

dye divided by the fluorescence of a passive reference and ΔRn is given when subtracting the

baseline (the initial cycles where little change in fluorescence signal is reported) from Rn.

In Figure 4, two thresholds have been set, one to 0.2 and one to 0.05 (orange and purple).

The thresholds are specific to the targets analysed. In this particular case, five samples were

analysed for two target sequences. All the five samples showed successful amplification of one

of the target sequences but only three of those samples also showed amplification of the other

target sequence. Although, none of these three samples (orange) had a high enough amplicon

concentration to cross the 0.2 threshold.

The higher concentration of the copied target sequence in the beginning of the reaction, the

sooner the fluorescence signal will be detected. It will require less cycles of amplification to

detect a signal from a sample that contain high concentrations of the target sequence.

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2.6. Ct-value

Ct-values are obtained from a table in the PCR software. The Ct-value for a sample equals the

x-value (cycle number) at which the curve crosses the threshold and is a relative measure of the

targets’ concentration. If a sample generates a low Ct-value, thus showing substantial

amplification in an early cycle, it means the concertation of the target sequence initially was

high, compared to a sample with a higher Ct-value. A sample with a high Ct-value needed more

cycles to amplify the target sequence, hence the target sequence initially existed in a lower

concentration.

2.7. Passive Reference Dye, Reporter Dye and Master Mix: Changes on Ct-values

A passive reference dye’s function is to provide an internal fluorescence to act as a reference to

the reporter dyes to be normalised against. Normalisation is needed to account for fluctuations

in fluorescence due to changes in volume or concentration.

Depending on the Master Mix composition, there is a great chance fluorescence signals will

vary, even though there is no change in concentration of probe, reference dye or template DNA.

This is because factors such as pH and salt concentrations within the master mixes can vary and

thereby affect the fluorescence signals generated. This is displayed in Figure 5, accessed from

Applied Biosystems application note “Real-time PCR: Understanding Ct”, which can be

downloaded through their website.

Although, in this project, changing the Master Mix also meant changing the passive

reference dye, from ROX to MP, and since the Rn value is defined as the ratio of the reporter

dye (FAM/NED/VIC) divided by the reference dye (ROX/MP), this change in reference dye

most definitely will have an impact on the Rn values. Having the Rn values changed (and

thereby also the Ct-values) does not mean sensitivity of the reaction was compromised.

Figure 5: Difference in fluorescence (VIC and ROX) due to different Master Mixes. The y-axis shows the emission

intensity and the x-axis shows the emission wavelength of the fluorophore. Picture from ABI’s “Real-time PCR:

Understanding Ct”.

12

As fluorescence intensity may vary with different Master Mixes, so may the Ct-values, even

though the sensitivity of the Master Mixes is the same (Figure 6). It is important to notice that

variations in Ct-values do not reflect the performance of the reaction, however, when

implementing a different method of analysis, it is beneficial to not have the Ct-values change

since patient diagnosis is based on Ct-values and that would mean that algorithms and manual

evaluations will have to be changed, or else diagnosis will be incorrect.

Figure 6: Ct-values (x-intercept) differ between the two Master Mixes even though the target concentration was identical.

Threshold are in both reactions set the same. Ct-value for Master Mix A is 14 and Ct-values for Master Mix B is around

12,5. Picture from ABI’s “Real-time PCR: Understanding Ct”.

In addition, a change in Master Mix and/or passive reference dye might also lead to an increase

in standard deviation of the Ct-values of the samples in the PCR assay, which is not favourable

as that will result in lower confidence when distinguishing between target concentrations with

small differences.

In the original method with ABI 7300 and TaqMan, the passive internal reference dye was ROX

which is supposed to give superb precision on Applied Biosystems qPCR instruments (such as

the 7300), according to the manufacturer ThermoFisher. In the new method with QS and Solis,

Mustang Purple (MP) was used as passive reference. In each duplex reaction, regardless

method, either FAM, VIC or NED dyes were used to detect the two target sequences in each

assay.

Table 4: Passive reference dye and reporter dye in use for each method and PCR instrument. Emission maxima for each

dye is specified.

Instrument Passive reference

dye

Reporter dye type 1 Reporter dye type 2 Reporter dye type 3

Applied Biosystems

7300

ROX (~610 nm) FAM (~520 nm) NED (~575 nm) VIC (~554 nm)

QuantStudio 6 or 7 MP (~654 nm) FAM NED VIC

13

3. Methodology

3.1. DNA Samples

The samples used in the experiments was already extracted and purified DNA obtained from

Dynamic Code’s costumers and samples were picked randomly for the experiments where they

all throughout remained anonymous (i.e. could never be linked to a person).

Purification of DNA was done with Quick-DNA™ 96 Kit from the brand Zymo Research

which is a technique based on a series of lysis buffer wash steps on a silica-based plate and

where the finished product finally is eluted through the silica into an elution plate. After eluted,

the product is ready to be directly placed into a PCR-mix in a PCR-plate.

3.2. Negative and Positive Controls

Controls are used to supervise the method of analysis to make sure it works properly and to

warn against possible errors as well as for follow up of the method over a longer period of time.

To better understand where in the process contamination took place, or where possible

inhibitors were introduced in the sample, negative and positive controls can be specified into

extraction negative and positive and amplification negative and positive. This makes it possible

to more or less pinpoint where in the process contamination was introduced and what steps

needs to be redone. For example, if the extraction negative control was contaminated, the entire

extraction process and the following amplification process has to be redone, but if only the

amplification negative control failed, solely the amplification has to be redone.

For this project, only amplification negatives and positives were of relevance since no

extraction was done.

With all analyses involved in this project, a negative control along with a positive control

unique for each mix (four of them), were amplified together with the rest of the samples.

Amplification negative and positive were placed directly to the PCR-plate along with the other

samples right before amplification.

3.2.1. Negative Controls

Negative controls verify sample-to-sample contamination, PCR contamination and reagent

contamination. The negative control should only contain those reagents necessary for the

polymerase chain reaction, but no template. It should be ‘blank’ and should not be showing any

kind of amplification in the amplification plot. If there is considerable noise from the negative

control sample, the control was at some point in the process contaminated and chances are all

or some of the other samples on that plate also were, meaning none of the results can be trusted.

In the negative control wells, 3 µl ddH2O was placed instead of the 3 µl template DNA.

Accepted Ct-values for the negative controls are everything >35 or “undetermined” (not enough

amplification to cross the given threshold).

3.2.2. Positive Controls

Positive controls verify that the DNA yield is good enough to draw any conclusions from. If

the positive control, which should be of known concentration, is ‘as positive’ as expected, it

14

affirms that DNA was not degraded by inhibitors thereby risking false-negative or faulty results,

and that in all the reaction was carried through completely and correctly.

In the positive control wells, 3 µl purified DNA, extracted with Quick-DNA™ 96 Kit, from

specific individuals of Dynamic Code’s staff positive for the given genotypes being analysed,

was placed instead of the 3 µl template DNA. At some point in the project, amplification

positive related to two of the mixes ran out and a new positive control was created and used.

The new positive control was created through DNA pooling of equal amounts of samples

previously analysed that showed strong amplification (corresponding to the Ct-values in table

of the target genes).

Accepted Ct-values for the positive controls are the same as what is considered a positive

result for costumer samples (Table 5).

Table 5: Accepted Ct-values for the positive controls.

Gene Ct-value

DQA1*02 <29

DQA1*05 <27

DQB1*02 <28

DQA1*03 <30

DQB1*0302 <27

DQB1*0302B# <27

IPC <32

3.3. Reaction Components

The total reaction volume was always 15 µl per well. 12 µl of these were the PCR-mix (Master

Mix) and 3 µl were the DNA sample (or 3 µl ddH2O if negative control/3 µl positive control

DNA template if positive control).

PCR-mixes consists of double-distilled water (from here on labelled only as ‘water’), HLA-

mix (1-4 depending on reaction) and Master Mix, either TaqMan™ Gene Expression Master

Mix (original method) or SolisFast® Probe qPCR Mix (Purple) (new method). Volumes vary

depending on the Master Mixes stock concentration where one of them (specified further down)

is more concentrated and needs to be diluted with more water.

The double distilled water, ddH2O, is deionized water with a resistance better or equal to

18MΩcm and it is obtained from a dispenser called ELGA PureLab Flex and aliquoted into

sterile Eppendorf tubes before use.

3.3.1. HLA-mix

What is labelled as “HLA-mix” is the oligonucleotide-mix containing the primers and probes.

The oligo-mix was for this optimisation project the most central part of the method optimisation

where volumes of the different components (Table 9) were varied and tested.

Each one of the four oligo-mixes contains primers and probes for two target sequences (so

called duplex). A total of six unique targets are amplified in pairs in this analysis:

15

Table 6: Target genes amplified in each of the four HLA-mixes.

HLA-mix 1 DQA1_05 IPC

HLA-mix 2 DQA1_02 DQB1_02

HLA-mix 3 DQA1_03 DQB1_0302

HLA-mix 4 DQB1*0302 B IPC

Mix 4 is a confirmative analysis performed on any samples positive for only HLA-DQ8

(DQA1_03 & DQB1_0302) that have been analysed with mixes 1-3 prior.

3.3.2. PCR-mix: TaqMan™ Gene Expression Master Mix

In the original method used for HLA gene amplification via qPCR within Dynamic Code,

TaqMan Master Mix is used and samples are placed in the ABI 7300 instrument.

Standard protocol for the TaqMan PCR mixes is as followed (12 µl per sample, 15 µl in

total when template is added):

Table 7: Protocols for PCR-mixes based on the TaqMan Master Mix, original method.

Mix 1 (DQA1_05 & IPC)

Stock concentration End concentration Volume

TaqMan™ Gene

Expression Master Mix

2X 1X 7,5 µl

HLA-mix 1 25X 1X 0,6 µl

ddH2O 3,9 µl

Mix 2 (DQA1_02 &DQB1_02)


TaqMan™ Gene


2X 1X 7,5 µl


ddH2O 3,9 µl

Mix 3 (DQA1_03 & DQB1_0302)


TaqMan™ Gene


2X 1X 7,5 µl


ddH2O 3,9 µl

Mix 4 (DQB1*0302 B & IPC)


TaqMan™ Gene


2X 1X 7,5 µl


ddH2O 3,9 µl

The polymerase included in TaqMan is called AmpliTaq Gold DNA Polymerase, UP (Ultra

Pure). Passive internal reference is ROX dye.

16

3.3.3. PCR-mix: SolisFast® Probe qPCR Mix (Purple)

When running the reaction with Solis Master Mix, composition of PCR-mix components is

slightly changed because of the 5X-concentration (compared to TaqMan’s 2X-concentration),

therefore more water is added.

Standard protocol for the Solis PCR mixes is as followed (12 µl per sample, 15 µl in total

when template is added):

Table 8: Protocols for PCR-mixes based on the Solis Master Mix, new method.



SolisFast® Probe qPCR

Mix (Purple)

5X 1X 3,0 µl


ddH2O 8,4 µl

Mix 2 (DQA1_02 &DQB1_02)



Mix (Purple)

5X 1X 3,0 µl


ddH2O 8,4 µl

Mix 3 (DQA1_03 & DQB1_0302)



Mix (Purple)

5X 1X 3,0 µl


ddH2O 8,4 µl




Mix (Purple)

5X 1X 3,0 µl


ddH2O 8,4 µl

The polymerase included in Solis is called SolisFAST® DNA Polymerase. Passive internal

reference is MP (Mustang Purple).

17

3.4. Oligonucleotide Mixes

Six different sequences were, together with an internal positive control targeting the human

RNA polymerase II gene in reaction 1 and 4, amplified to express and detect HLA-DQ2 and

HLA-DQ8 in samples analysed for celiac disease.

Each mix is duplexed and each target has one forward primer (FP1 and FP2), one reversed

primer (RP1 and RP2) and one probe (P1 and P2), as listed below. In tables below are

concentrations and volumes optimised for the original method, with TaqMan Master Mix run

on ABI 7300.

Table 9: Protocols for oligonucleotide mixes (HLA-mixes), original method.


Oligo Tag Stock

concentration

End

concentration

Volume

HLAmix1_FP1 100 µM 300 nM 45 µl

HLAmix1_RP1 100 µM 300 nM 45 µl

HLAmix1_P1 FAM 100 µM 200 nM 30 µl

HLAmix1_mix4_FP2 100 µM 50 nM 7,5 µl

HLAmix1_mix4_RP2 100 µM 50 nM 7,5 µl

HLAmix1_mix4_P2 NED 100 µM 200 nM 30 µl

ddH2O 435 µl

Mix 2 (DQA1_02 & DQB1_02)

Oligo Tag Stock

concentration

End

concentration

Volume



HLAmix2_P1 VIC 100 µM 200 nM 30 µl


HLAmix2_mix3_RP2 100 µM 300 nM 45 µl


ddH2O 360 µl

Mix 3 (DQA1_03 & DQB1_0302)

Oligo Tag Stock

concentration

End

concentration

Volume



HLAmix3_P1 VIC 100 µM 200 nM 30 µl


HLAmix2_mix3_RP2 100 µM 300 nM 45 µl


ddH2O 360 µl

18


Oligo Tag Stock

concentration

End

concentration

Volume




HLAmix1_mix4_FP2 100 µM 50 nM 7,5 µl

HLAmix1_mix4_RP2 100 µM 50 nM 7,5 µl

HLAmix1_mix4_P2 NED 100 µM 200 nM 30 µl

ddH2O 435 µl

The concentrations above are what have been optimised in order to make the HLA analysis run

properly with the Solis Master Mix and QS instruments.

3.5. PCR Optimisation and Validation

Although most manufacturers provide solid and robust assays designed to meet all necessary

criteria, ThermoFisher included, assays need to be adjusted depending on the selection of

instrument, reagents, thermal PCR conditions and primer and probe concentrations.

Although optimisation can be done through adjustment of many different components, it is

favourable to maintain standard buffer conditions and instead solely focus on modifying primer

and/or probe concentrations, which will affect primer binding kinetics.

Primer design optimisation is sometimes a valid way of approach, for example if primer

dimers are a problem, however, in this project, focus was solely on optimisation through

modifications in primer/probe concentrations. Primers were already design and working

properly.

The approach was a one-factor-at-a-time approach where only one of the components

(forward and reverse primer for target one, forward and reverse primer for target two, probe for

target one or probe for target two) concentration was varied while remaining components had

a fixed concentration. For DQ-targets, the original primer concentration, 300 nM, was tested

together with 100 nM and 900 nM. For IPC, 100 nM and 300 nM were tested for primers, and

for each probe, 200 nM, 100 nM and 400 nM were tested.

Figure 7: Overview of experiments on primer (blue squares) and probe (grey squares) optimisation during the project. The

so called one-factor-at-a-time approach. Probe 1 is connected to target 1 and probe 2 is connected to target 2.

19

When all mixes were completely optimised, each mix was placed on a full PCR-plate and

compared to the original method by placing those same samples on yet another PCR-plate

which was analysed according to the original, already optimised method. If results added up

with the already validated method, the optimisation was successful.

Figure 8: Overview of validation experiments of the four optimised mixes.

20

4. Method

4.1. Optimisation of Primers and Probes

An oligonucleotide mix (oligo-mix) was prepared with the concentrations being evaluated in

the particular experiment. When doing this, the original protocol for preparing oligo-mixes

(Table 9) was used as a guideline and volumes of the components were adjusted to create the

desired concentrations.

The PCR-mixes were prepared, one for each concentration being examined in the particular

experiment. For experiments on ABI 7300 according to the original method, the protocols in

Table 7 were followed, and for experiments on QS 6 or 7, the protocols in Table 8 were

followed. The previously prepared oligo-mix was combined with the Master Mix and water, 12

µl for each sample in total.

12 µl of the PCR-mix was pipetted into each well of a PCR-plate. 3 µl template DNA was then

pipetted in each well, adding up to a total of 15 µl reaction solution per well. One amplification

positive control and one amplification negative control was added for each different

concentration. See appendix A for PCR-plate setup.

Initially, one full PCR-plate containing all four HLA-mixes (24 wells of each mix) was pipetted

and analysed according to the original method, and one with the new Solis Master Mix on the

QS, i.e. two identical plates but with different Master Mixes and placed in different instruments.

The samples and their positions on the plates matched up between the two plates, so as to make

a direct comparison of the results possible. This experiment was conducted to get an overview

of the differences right away from just running the experience non modified, with a different

Master Mix and on a different instrument.

The experiments following this initial experiment was conducted based on the one-factor-at-

a-time approach described in chapter 3.6.

4.2. Validation of Modified PCR Method

After optimisation of each primer and each probe in all the mixes was completed, validation

experiments were performed, one for each of the four HLA-mixes, where the final

concentration for each of the components (primers and probes) was tested on a full PCR-plate.

The same samples were placed on two PCR-plates, one according to the original method and

one according to the optimised method. This was done for each of the four mixes.

The data obtained from the validation experiments were compared, and the Ct-values obtained

from each method were inserted into an algorithm that determines final HLA diagnosis. The

algorithm compared the values from each method, and determined final diagnosis (positive or

negative for the DQ-genes, or not proven) so as to see if final results were the same regarding

method. If so, the goal of the project was reached – final results were the same disregarding of

method.

21

5. Results

From the initial experiment, where the original method was compared to the new method, but

with no modifications to any of the primer or probe concentrations, the differences in Ct-values

between the methods were calculated (Solis QS – TaqMan 7300). The values varied from a

median of -1,8 (for DQB1_0203 in mix 3) up to 6,6 (for DQB1_02 in mix 2).

Table 10: Mean and median of the difference between Ct-values from each sample on QS versus 7300 before optimisation.

Mix 1 Mix 2 Mix 3 Mix 4

DQA1_05 IPC DQA1_02 DQB1_02 DQB1_0203 DQA_03 DQB1*0203 B IPC

Mean 4,207 2,866 -0,239 6,603 -1,812 2,563 3,913 3,286

Median 4,119 3,018 0,794 6,563 -1,897 2,631 5,744 3,635

Also found from this experiment was the fact that 12 of the 88 costumer samples on the plate

that was valued as “undetermined” (was not assigned a Ct-value due to too little amplification)

on ABI 7300, was in fact detected on QS, although with high Ct-values. An indication on a

greater sensitivity on the QS compared to ABI 7300.

5.1. Mix 1: DQA1_05

Figure 9: Amplification plot for mix 1 DQA_05 300 nM (red), 100 nM (pink) and 900 nM (purple), and IPC 50 nM

(purple). Probe 1 200 nM and probe 2 200 nM.

In general, the shape of the curves is similar with some shifting along the x and y axis between

the different concentrations. The 900 nM concentration of DQA1_05 did result in the highest

amplitude amongst the three different concentrations, especially higher than 100 nM, but also

slightly higher than 300 nM. Although, when studying the different concentrations individually,

it seems like DQA1_05 samples with 900 nM concentration did somewhat suppress the IPC

signals (purple) the most. Regarding Ct-values, samples appear in pretty much the same range

when it comes to concentrations 300 nM and 900 nM. Ct-values for the 100 nM samples was

much higher than both higher concentrations, indicating on a less effective amplification.

22

The IPC amplification was, in general, far too low when using the original concentration from

Table 9 of 50 nM. IPC should be in the Ct-range 23-32 while Ct-values from this experiment

were 33 and above. Not only was the amplification delayed, also the efficiency was poor. No

clear exponential phase or even linear phase was achieved. IPC primer concentration had to be

increased drastically in order to get more sensible amplification.

For DQA1_05 in Mix 1, 900 nM concentration was at this point considered to be the most

optimal and following optimisation experiments on Mix 1 was based on this concentration for

DQA1_05.

5.1.1. Mix 1: IPC

Figure 10: Amplification plot for mix 1 IPC 100 nM (green) and 300 nM (blue), and DQA1_05 900 nM. Probe 1 200 nM

and probe 2 200 nM.

When IPC primer concentration was increased to 100 nM (green) and 300 nM (blue), signals

were stronger and appearance of the curves made more sense. There was a significant difference

between the stronger and the weaker concentration, both in amplitude and in amplification

efficacy, where samples analysed with the higher concentration were detected with higher

signals as well as after fewer cycles.

However, the goal is not to obtain the most efficient amplification of the IPC, since the purpose

of the internal control is to indicate whether any inhibitors might be present in the sample. If

the IPC concentration is made too high, results of a quantitative amplification might be faulty

as the signals could be exaggerated due to the excessive concentration.

Although, at this point, 300 nM IPC was considered giving the best results but would later be

reconsidered due to the fact just stated.

23

5.1.2. Mix 1: Probe 1

Figure 11: Amplification plot for mix 1 probe 1 in 100 nM (yellow), 200 nM (red) and 400 nM (grey), DQA1_05 900 nM,

IPC 300 nM, signals are hidden. Probe 2 200 nM.

For probe 1, connected to DQA1_05 in mix 1, signals were stronger the higher the concentration

of the probe. Also, Ct-values decreased when concentration increased, i.e. samples were

amplified earlier in the PCR when probe concentration was higher.

400 nM gave objectively speaking slightly better results, but 200 nM was not far off. Therefore,

due economic reasons, 200 nM was chosen.

5.1.3. Mix 1: Probe 2

Figure 12: Amplification plot for mix 1 probe 2 in 100 nM (orange), 200 nM (lilac) and 400 nM (blue), DQA1_05 900

nM, IPC 300 nM, probe 1 200 nM.

In this case, regarding probe 2 connected to IPC in mix 1, the higher the concentration the better

the result was not the case.

The lowest probe concentration, 100 nM, clearly gave the worst results – amplification

started many cycles into the reaction, fluorescence signals were weak and there was a large

scattering between samples regarding Ct-values.

24

Figure 13: Amplification plot for mix 1 probe 2 in 100 nM (orange), 200 nM (lilac) and 400 nM (blue), DQA1_05 900 n,

IPC 300 nM, probe 1 200 nM. Only samples 1-8 are previewed for concentrations 200 nM and 400 nM.

If comparing a smaller selection of samples of 200 nM and 400 nM (Figure 13), it becomes

clearer as to which one of these concentrations was more successful.

200 nM was considered the optimal concentration for probe 2.

5.2. Mix 2: DQA1_02

Comparing the three variations of concentrations of the forward and reversed primers for

DQA1_02 target in mix 2 (see appendix B for amplification plots), 100 nM had by far the worst

amplification. While six samples from the 300 nM concentration and five samples from the 900

nM concentration was clearly positive, none of the samples from the 100 nM was successfully

amplified; they appear very late into the reaction and amplification curves do not adapt desirable

shape.

When comparing 300 nM to 900 nM, there is a better distinction between the two clusters of

curves in the lower concentration, 300 nM. When comparing samples individually, one can see

that DQB1_02 signals have been supressed by raising the concentration on DQA1_02 primers.

In some samples, the DQB1_02 is barely detected at all.

Considering all this, 300 nM was chosen as the most optimal primer concentration for

DQA1_02.

5.2.1. Mix 2: DQB1_02

When comparing the three concentrations for the second target in mix 2, DQB1_02, what is

most obvious is the spread amongst the signals in the lowest concentration, 100 nM. The non-

concurrent signals along with poor fluorescence signal rules out this concentration to be the

best.

25

Figure 14: Amplification plot for mix 2 DQB1_02 in 300 nM (green) and DQB1_02 900 nM (blue), probe 1 and probe 2

both 200 nM.

When looking at 300 nM and 900 nM, displayed together in the figure above, there are no

apparent differences. Therefore, due to economic reasons, 300 nM was considered the optimal

primer concentration of DQB1_02.

5.2.2. Mix 2: Probe 1

The most apparent difference between the different concentrations on probe 1 connected to

DQA1_02 is the spread in Ct-values amongst the samples. Raising the concentration up to 400

nM seems to have resulted in non-current signals amongst the samples. In addition, the non-

specific amplification visible in the far right of the plot (see appendix B) was a bigger issuer

with this concentration where many of those non-specific curves crossed the threshold quite

early in the reaction.

For 100 nM, the non-specific amplicons did barely cross the threshold, and if they did, it was

at a high Ct-value. Results were not much better for 300 nM; therefore 100 nM was chosen for

probe 1.

5.2.3. Mix 2: Probe 2

100 nM concentration was not successful for probe 2. Amplification was just not efficient

enough.

400 nM clearly resulted in stronger signals of DQB1_02, but at the same time DQA1_02 signals

were supressed. Over all, curves in the plot showing probe 2 concentration 200 nM showed

great results and thus, this concentration was chosen as the optimal.

26

5.3. Mix 3: DQA1_03

Figure 15: Amplification plot for mix 3 DQA1_03 in 100 nM (red), 300 nM (yellow) and 900 nM (blue), and DQB1_0302

300 nM (grey), probe 1 and probe 2 both 200 nM.

Moving on to mix 3, even displaying all three concentrations in the same plot, one can clearly

notice the differences between them.

100 nM primer concentration resulted in very poor amplification of DQA1_03 where all

samples positive for DQA1_03 was detected late and with weak fluorescence.

300 nM and 900 nM curves adapt the same appearance and amplification seems to be efficient.

However, there is a significant difference in at what point samples start amplifying as well as

when they intercept with the threshold. Considering these aspects, 900 nM amplification did

perform better and decision was at this point made to move forward with this concentration.

5.3.1. Mix 3: DQB1_0302

Figure 16: Amplification plot for mix 3 DQB1_0302 in 100 nM (red), 300 nM (green) and 900 nM (blue), and DQA1_03

900 nM (yellow), probe 1 and probe 2 both 200 nM.

27

Generally, between all three concentrations, amplification of non-specific sequences was a

bigger problem than with previously targets, especially when using 300 nM and 900 nM primer

concentration.

Regarding the signals that are obviously DQB1_0302, the target sequence, there is a correlation

in primer concentration, amplitude and cycle number. The higher the concentration, the higher

the amplitude and the lower the cycle number.

However, there was no greater difference between 300 nM and 900 nM, as both primer

concentration performed well and due to economic reasons, 300 nM was therefore considered

the optimal concentration for DQB1_0302.

5.3.2. Mix 3: Probe 1

Figure 17: Amplification plot for mix 3 probe 1 in 100 nM (green), 200 nM (yellow) and 400 nM (lilac), DQA1_03 900

nM and DQB1_0302 300 nM, probe 2 200 nM.

The lowest concentration of probe 1 connected to DQA1_03, 100 nM, in mix 3 clearly gave the

weakest fluorescence signals and also the highest cycle numbers. In addition, when looking at

the targets individually, 100 nM made non-specific amplification signals more wide spread than

the higher concentrations. Non-specific amplification was reduced with the higher probe

concentrations.

28

Figure 18: Amplification plot for mix 3 probe 1 in 200 nM (yellow) and 400 nM (lilac), DQA1_03 900 nM and

DQB1_0302 300 nM, probe 2 200 nM.

DQA1_03 signals from the two higher concentrations were similar, in fact pretty much

overlapping each other, see Figure 18. Due to economic reasons, the lower concentration, 200

nM was chosen.

5.3.3. Mix 3: Probe 2

Results from amplification with all three probe concentrations are similar and all yield strong

signals implying an efficient amplification. 100 nM was considered the optimal concentration

for probe 2 in mix 3.

5.4. Mix 4: DQB1*0302 B

IPC signals from all three mixes were similar and was therefore not considered when evaluation

the results from the primer concentrations of DQB1*0302 B in mix 4.

As in most other previous cases, the lowest primer concentration did perform unsatisfactory in

regards to efficiency.

29

Figure 19: Amplification plot for mix 4 DQB1*0302 B in 300 nM (lilac) and 900 nM (blue), IPC has been hidden in the

plot, probe 1 and probe 2 both 200 nM.

300 nM and 900 nM are displayed together in the amplification plot above to show the

accordance with each other. With both concentrations, there is a clear distinction between what

are non-specific amplification signals and what are DQB1*0302 B signals. The target signals

are clustered nicely together and amplification efficiency was good. Even though the sample

size is small, at least within these samples 300 nM signals appear at a lower Ct and with even

more narrow spread.

300 nM was chosen as the most optimal concentration for primers connected to this target.

5.4.1. Mix 4: IPC

IPC in mix 4 was initially only tested in 300 nM. This concentration was considered too high

for the IPC as curves appeared with Ct-values as low as the Ct-values, and explained in chapter

5.1.1., the goal is not to have IPC signals as high as possible, at as low Ct-values as possible.

In a later experiment, 100 nM was confirmed as the optimal IPC primer concentration, but in

the following experiments regarding mix 4, 300 nM IPC is what is being used.

5.4.2. Mix 4: Probe 1

Generally, in this assay signals were strong and amplification efficient. The lowest

concentration clearly gave the weakest signals and highest Ct-values. Results obtained from

200 nM and 400 nM were similar in regards to signal strength and especially in regards to Ct-

values where all samples of these concentrations fall within the same range.

Due to economic reasons 200 nM was chosen to move forward with.

5.4.3. Mix 4: Probe 2

For the probe connected to the IPC in mix 4, 400 nM showed the worst performance out of the

three concentrations. IPC signals were discordant and a real plateau phase was not reached

30

before the 40 cycles in the reaction, if compared to both 100 nM and 200 nM, where samples

gather and plateau around Ct 36.

Considering the two lower concentrations, results are more satisfying in 200 nM samples

where amplitude is higher and spacing along the threshold is slightly smaller. Results are not

bad with 100 nM probe either, but since 200 nM was chosen for this probe in mix 1, choosing

the same concentration in this mix will ease laboratory work and reduce complications when

preparing the mixes.

5.5. Validation

5.5.1. Mix 1

When comparing the two targets within mix 1 run with the new optimised method on QS with

the old method on 7300, Ct-values from each method align well.

Ct-values of DQA1_05 range from 21,3 to 26,7 on 7300, and between 22,9 and 28,4 on QS.

For IPC the interval is 23,2 to 33,4 on 7300, and 24,8 to 35,6 on QS.

5.5.2. Mix 2

Samples positive for DQA1_02 range from 22,2 to 27,7 on 7300 and from 22,9 to 27,4 on QS.

For DQB1_02 the interval is 21,4 to 26,8 on 7300 and 22,6 to 27,7 on QS. Hence, there is a

great accordance between the Ct-values obtained from the different methods, for both targets

included in mix 2.

5.5.3. Mix 3

Besides the deviating sample at around Ct 36 in the DQA1_03 plots, samples range from 22,8

to 34,7 on 7300 and from 23,5 to 28,6 on QS. If the deviating sample at 30,0 on 7300 is

disregarded, the sample range is 22,8 to 28,5. This particular sample is “undetermined” on QS.

For DQB1_0302, Ct-values for positive samples fall within the interval 21,0 to 25,3 on 7300

and 21,2 to 26,5 on QS.

5.5.4. Mix 4

Samples positive for DQB1*0302 B in mix 4 fall within the Ct range 19,3 to 25,5 on 7300 and

21,0 to 26,4 on QS. For the IPC, values are 25,2 to 36,2 on 7300 and 22,3 to 32,7 on QS.

After optimisation of the primer and probe concentrations along with lowering of some of the

thresholds, the differences between Ct-values from each sample obtained from both methods

was calculated (Solis QS – TaqMan 7300). The medians of the differences are presented in

Table 11, together with corresponding medians calculated from data before optimisation.

31

Table 11: Medians of the difference between Ct-values from each sample on QS versus 7300 after optimisation and

adjustments to the thresholds compared to before optimisation and with old thresholds.

Mix 1 Mix 2 Mix 3 Mix 4

DQ

A1_05 IPC

DQ

A1_02

DQ

B1_02

DQ

B1_0203

DQ

A1_03

DQB1

*0203 B IPC

Median

before: 4,119 3,018 0,794 6,563 -1,897 2,631 5,744 3,635

Median

after:

0,504

0,404

0,368

-0,453

0,374

0,794

0,566

-3,678

Table 12: Mean values of medians from Table 11, before and after optimisation for all targets and for only DQ-targets.

Before optimisation After optimisation

Mean difference DQ-targets 2,992 0,359

Mean difference all targets 3,076 -0,140

5.6. Final Primer and Probe Concentrations


Oligo End

concentration,

original method

End

concentration,

new method

HLAmix1_FP1 300 nM 300 nM*

HLAmix1_RP1 300 nM 300 nM*

HLAmix1_P1 200 nM 200 nM

HLAmix1_mix4_FP2 50 nM 100 nM*

HLAmix1_mix4_RP2 50 nM 100 nM*

HLAmix1_mix4_P2 200 nM 200 nM

Mix 2 (DQA1_02 & DQB1_02)

Oligo End

concentration

End

concentration,

new method

HLAmix2_FP1 300 nM 300 nM

HLAmix2_RP1 300 nM 300 nM



HLAmix2_mix3_RP2 300 nM 300 nM


32

Mix 3 (DQA1_03 & DQB1_0302)

Oligo End

concentration

End

concentration,

new method

HLAmix3_FP1 300 nM 300 nM*

HLAmix3_RP1 300 nM 300 nM*






Oligo End

concentration

End

concentration,

new method


HLAmix1_RP1 300 nM 300 nM


HLAmix1_mix4_FP2 50 nM 100 nM*


HLAmix1_mix4_P2 200 nM 200 nM

Concentrations marked with an asterisk (*) were changed following further evaluation of the

results, after the experiments were already carried through. For example, primer concentration

for DQA1_05 in mix 1, named HLAmix1_FP1 and HLAmix1_RP1 in the table above, was first

set to 900 nM and further optimisation of the mix was based on this concentration. It was later

on changed to 300 nM. However, all validation experiments, chapter 5.5., were conducted with

the re-evaluated concentrations as shown in the tables above.

5.7. Final Affirmation of Genotypes

After evaluation of the results obtained from the validation experiments, decision was made to

lower some of the thresholds to better match the Ct-values obtained with the new method with

those obtained with the old one. Thresholds were adjusted according to Table 13.

Table 13: Thresholds according to the original method and the adjusted thresholds after optimisation.

Target Old threshold New threshold

DQA1_02 0,1 0,1

DQA1_03 0,1 0,1

DQA1_05 0,2 0,1

DQB1_02 0,2 0,1

DQB1_0302 0,2 0,1

IPC 0,05 0,02

After thresholds were adjusted, each Ct-value, from all mixes on both instruments, was inserted

into an Excel sheet programmed to calculate the final genotyping result (positive, negative or

not proven) for each DQ-target, also taking IPC value into account. The algorithm presents the

conclusive HLA-diagnosis (positive/negative for HLA-DQ2 and HLA-DQ8).

The final genotype results for HLA-DQ2 and HLA-DQ8 is presented in the list below.

33

QS QS 7300 7300

Sample

Name

HLA-

DQ2

HLA-

DQ8

HLA-

DQ2

HLA-DQ8

1 + - + -

2 - - - -

3 - - - -

4 - - - -

5 - - - -

6 - - - -

7 + - + -

8 - - - -

9 - - - -

10 - - - -

11 - - - -

12 - - - -

13 - - - -

14 - - - -

15 - - - -

16 - - - -

17 - - - -

18 - - - -

19 - - - -

20 - - - -

21 - - - -

22 - - - -

23 + - + -

24 + - + -

25 + - + -

26 - - - -

27 - - - -

28 - - - -

29 - - - -

30 - - - -

31 - - - -

32 + - + -

33 - - - -

34 - - - -

35 - - - -

36 - - - -

37 - - - -

38 - - - -

39 - - - -

40 - - - -

41 + - + -

42 - - - -

43 - - - -

44 - - - -

34

45 + - + -

46 - - - -

47 - - - -

48 - - - -

49 - - - -

50 + - + -

51 - - - -

52 + - + -

53 + - + -

54 - - - -

55 + - + -

56 + - + -

57 - - - -

58 - - - -

59 - - - -

60 + - + -

61 Invalid

result

Invalid

result

- -

62 - - - -

63 - - - -

64 - - - -

65 - - - -

66 + - + -

67 - - - -

68 + - + -

69 - - - -

70 + - + -

71 - - - -

72 - - - -

73 - - - -

74 - - - -

75 + - + -

76 - - - -

77 + - + -

78 - - - -

79 - - - -

80 - - - -

81 + - + -

82 + - + -

83 - - - -

84 - - - -

85 - - - -

86 - - - -

87 - - - -

88 + - + -

89 - - - -

90 - - - -

35

91 + - + -

92 - - - -

93 + - + -

94 - - - -

All but one of the 94 samples were genotyped the same regardless method. The deviant sample,

sample 61, was classified as invalid on the QS but was classified as negative on the 7300 for

both targets, DQ2 and DQ8.

The reason for the invalid result lies in the evaluation method in use by Dynamic Code.

Sample 61 obtained a Ct-value of 33,715 for the IPC on QS, and 31,868 on 7300. The sample

was otherwise negative for all targets. A negative result for all targets in combination with an

IPC <32 makes the result invalid and a new sample has to be taken and analysed.

36

6. Discussion

Out of 16 primer and probe concentrations up for optimisation in this project, four were

ultimately changed: the IPC probe in mix 1 and mix 4, and two probe concentrations, connected

to mix 2 and mix 3, whereby one of them was cut in half and one was doubled. Over all,

changing the Master Mix together with the PCR instrument was possible without any major

complications, through primer and probe concentration optimisation and through adjustments

of the PCR thresholds. If thresholds were not adjusted, the existing evaluation protocol for

diagnosis of HLA would not be appliable and would have to be remodelled.

Generally, when calculating the median of the difference in Ct-values between QS and 7300,

values obtained from QS were higher for each target but the IPC in mix 4, yielding a positive

median. The mean of the medians was for all targets combined -0,140, meaning QS Ct-values

were higher. Lowering the threshold will automatically make curves intercept with it earlier,

resulting in lower Ct-values, thus solving the problem with the overall higher values of the QS.

When studying Table 11 and Table 12, containing the median differences between Ct-values,

QS – 7300, for each mix before and after optimisation, the differences are generally lower after

optimisation. The Ct-difference between the methods started off being 3,076 and were after

optimisation -0,140, meaning the project was successful in changing PCR instrument and

Master Mix without having the Ct-values change too much so as to still be able to use the

already elaborated patient diagnosis evaluation system.

The one sample that achieved different final HLA diagnosis, Sample 61, was classified as

invalid on the QS but got a negative test result on the 7300. The reason for it being invalidated

when analysed on the QS is because it was negative for all HLA-targets in combination with

having a Ct-value higher than 32 for the IPC (33,72). This combination will, according to the

evaluation premises, result in an invalid test result after which a new test has to be sampled and

analysed. This is because a test with a too low IPC signal is not consider reliable as it might be

an indication of PCR inhibitors or a faulty sampling and lack of DNA in the sample. Giving

false negative results is a risk when analysing such tests.

Sample 61 received a Ct-value of 31,87 on the 7300, which is right under the limit for what

is accepted for the IPC. Hence, the possibility for the sample to be invalidated on the 7300 was

not far off.

Although this sample generated different end results on the two instruments, in this

particular case, that would not result in a faulty diagnosis. This patient is clearly negative for

all DQ-targets, regarding method, but if analysed on the QS, the patient would have to redo the

test for confirmation reasons. Hence, no critical consequences would follow this error.

One limitation of the study is the fact that only one validation experiment per mix was

conducted. Even though sample quantity was quite large, 94 samples, the experiment would

have to be executed again to account for possible measurement aberrations due to stochastic

variations and changes in conditions. For example, reaction conditions might vary between runs

in where heating of the block holding the samples inside the instrument not always carries out

identically. Besides temperature variations between runs, variations in detection is possible,

depending on the strength of the excitation lamp in the instrument.

In addition, there are practical aspects in the laboratory work pre analysation to take into

consideration, where volume variations when pipetting might be the biggest source of error.

37

When handling such small volumes as 3 µl, a minor divergence in the volume might have a

massive effect on outcome.

Reagent quality is another factor not to be neglected that will compromise the results.

Inequality in reagent freshness depending on how the reagent was stored and for long it has

been stored will influence the outcome.

Repeating the experiments but with different conditions and circumstances is necessary in

the future as that will give a better overall view of how the method actually performs.

Conducting only one experiment will only tell you how the method performed in those specific

conditions under those exact circumstances.

38

7. Conclusion

Optimisation of the new method to enable PCR instrument transfer and Mater Mix change

through primer and probe concentration manipulation was considered successful. The goal of

not having existing patient diagnosis validation algorithms changed after the method change

was also reached.

Based on the validation experiments, HLA diagnosis results were the same regardless of method

in 98,9% of the cases. Only one out of 94 samples had conflicting results. It did not obtain

different diagnosis, as it was negative in both methods, but was invalidated in the new method

because of a too high IPC value.

Compared to the old method, the new method allows for 83% more samples to be analysed in

the same amount of time thanks to the instrument transfer. The change in Master Mix means a

decrease in reagent costs by 21% (comparing the current market price for a 5x1 ml batch

SolisFast® Probe qPCR Mix and TaqMan™ Gene Expression Master Mix, according to each

manufacturers’ websites at current date).

39

8. Acknowledgments

First, I want to thank Dynamic Code for giving me this opportunity, and especially every single

one of my co-workers in the laboratory, who made my time spent there memorable and who

were always open for discussion or support with whatever I encountered during this project.

I want to thank Josephine Overmyr, my supervisor, for taking me on during this project.

Thanks to Malin Farnebäck, who were involved in designing the project and who helped me to

come on stream with it from the beginning. Malin also provided much valuable input and

guidance throughout the project.

A special thanks to Maria Lundström, who taught me everything I needed to know regarding

both practical work in the laboratory, as well as theoretically, and who were always there for

me to answer any of my questions or concerns.

Thank you, Robin Östman, my opponent, for noteworthy comments and questions regarding

my work.

Thank you, Lars-Göran Mårtensson, my examiner, for valuable input and feedback on my

report.

Finally, thank you mother, for your never-ending support.

40

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42

Appendix A

1. PCR-plate Setups

Figure 20: PCR-plate setup for experiments when varying concentrations of one component. Concentration 1 in yellow,

concentration 2 in teal and concentration 3 in orange. Template DNA is identical between the different concentrations.

Figure 21: PCR-plate setup for the initial experiment when all four mixes were analysed. Mix 1 in pink, mix 2 in blue,

mix 3 in purple and mix 4 in green. The same samples and setup were analysed according to the original method as well

as with the new Master Mix on the new instrument.

43

Figure 22: PCR-plate setup for the validation experiments. One full plate of each mix was pipetted, above shows mix 1,

and analysed according to the original method as well as the new, optimised method.

44

Appendix B

1. PCR Amplification Plots – Optimisation experiments

Figure 23: Amplification plot for mix 2 DQA1_02 in 100 nM (red) and DQB1_02 300 nM (green), probe 1 and probe 2

both 200 nM.

Figure 24: Amplification plot for mix 2 DQA1_02 in 300 nM (blue) and DQB1_02 300 nM (green), probe 1 and probe 2

both 200 nM.

45

Figure 25: Amplification plot for mix 2 DQA1_02 in 900 nM (light green) and DQB1_02 300 nM (dark green), probe 1

and probe 2 both 200 nM.

Figure 26: Amplification plot for mix 2 DQB1_02 in 100 nM (red) and DQA1_02 300 nM (orange), probe 1 and probe 2

both 200 nM.

Figure 27: Amplification plot for mix 2 DQB1_02 in 300 nM (green) and DQA1_02 300 nM (orange), probe 1 and probe

2 both 200 nM.

46

Figure 28: Amplification plot for mix 2 DQB1_02 in 900 nM (blue) and DQA1_02 300 nM (orange), probe 1 and probe 2

both 200 nM.

Figure 29: Amplification plot for mix 2 probe 1 100 nM (red), DQA1_02 300 nM, DB1_02 300 nM (green), probe 2 200

nM.

Figure 30: Amplification plot for mix 2 probe 1 200 nM (lilac), DQA1_02 300 nM, DB1_02 300 nM (green), probe 2 200

nM.

47

Figure 31: Amplification plot for mix 2 probe 1 400 nM (blue), DQA1_02 300 nM, DB1_02 300 nM (green), probe 2 200

nM.

Figure 32: Amplification plot for mix 2 probe 2 in 100 nM (brown), DQB1_02 300 nM and DQA1_02 300 nM (blue),

probe 1 100 nM.

Figure 33: Amplification plot for mix 2 probe 2 in 200 nM (green), DQB1_02 300 nM and DQA1_02 300 nM (blue),

probe 1 100 nM.

48

Figure 34: Amplification plot for mix 4 probe 1 in 100 nM (yellow), 200 nM (orange) and 400 nM (grey), DQB1_0302 in

300 nM, IPC in 300 nM (hidden in the plot), probe 2 200 nM.

Figure 35: Amplification plot for mix 4 DQB1*0302 B in 100 nM (orange), IPC has been hidden in the plot, probe 1 and

probe 2 both 200 nM.

Figure 36: Amplification plot for mix 2 probe 2 in 400 nM (teal) and DQA1_02 300 nM (blue), probe 1 100 nM.

49

Figure 37: Amplification plot for mix 3 probe 2 in 100 nM (blue), 200 nM (grey) and 400 nM (orange), DQB1_0302 300

nM and DQA1_03 900 nM, probe 1 200 nM.

Figure 38: Amplification plot for mix 4 IPC 300 nM (purple), DQB1*0302 B 100 nM (orange), 300 nM (lilac) and 900

nM (blue), probe 1 and 2 200 nM.

Figure 39: Amplification plot for mix 4 probe 2 in 100 nM (yellow), IPC 300 nM and DQB1*0302 B 300 nM (orange),

probe 1 200 nM.

50

Figure 40: Amplification plot for mix 4 probe 2 in 200 nM (purple), IPC 300 nM and DQB1*0302 B 300 nM (orange),

probe 1 200 nM.

Figure 41: Amplification plot for mix 4 probe 2 in 400 nM (grey), IPC 300 nM and DQB1*0302 B 300 nM (orange),

probe 1 200 nM.

2. PCR Amplification Plots – Validation experiments

Figure 42: Amplification plot for DQA1_05 on ABI 7300.

51

Figure 43: Amplification plot for DQA1_05 on QS.

Figure 44: Amplification plot for IPC on ABI 7300.

Figure 45: Amplification plot for IPC on QS.

52

Figure 46: Amplification plot for DQA1_02 on 7300.


Figure 48: Amplification plot for DQB1_02 on 7300.

53

Figure 49: Amplification plot for DQB1_02 on QS.

Figure 50: Amplification plot for DQA1_03 on 7300.


54

Figure 52: Amplification plot for DQB1_0302 on 7300.

Figure 53: Amplification plot for DQB1_0302 on QS.

Figure 54: Amplification plot for DQB1*0302 B on 7300.

55

Figure 55: Amplification plot for DQB1*0302 B on QS.

Figure 56: Amplification plot for IPC on 7300.

Figure 57: Amplification plot for IPC on QS.

optimisation and validation of pcr method for hla gene

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