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How is RNA of retrovirus converted into cDNA?

How is RNA of retrovirus converted into cDNA?


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The retrovirus (oncovirus) contains RNA. It also has a molecule called reverse transcriptase. This molecule transcribes RNA into cDNA. This cDNA is the DNA copy of viral RNA genome

RNA has Uracil instead of thymine and DNA has thymine instead of uracil. So, how can RNA be converted into DNA? Where does Uracil go and where does thymine come from?


RNA has Uracil instead of thymine and DNA has thymine instead of uracil. So, how can RNA be converted into DNA?

I think you may want to ask a more basic question. DNA and RNA are extremely similar, with only an oxygen being the difference. This has vast consequences for organisms, and life as we know it uses DNA and RNA for very separate purposes. DNA stores the genome providing the instructions for life, and RNA in a nutshell is how that message gets converted into protein for a useful action. RNA is generally less stable than DNA, so this arrangement works out well.

DNA is regularly and constantly transcribed to RNA, so Thymine is regularly used in favor of Uracil. There is a fantastic answer here on Biology.SE already dealing with why so I suggest reading that. The how is pretty straightforward, there are different molecules used! DNA polymerases incorporate Thymine whereas RNA polymerases incorporate Uracil. The reverse transcriptase that is encoded by the retrovirus does just this: it transcribes RNA to DNA, using Thymine instead of Uracil. Both Uracil and Thymine are present in the cell and are thus available for use.


I think it might be of use to show you the difference between uracil and thymine

They are very similar structures. The part that is involved in base pairing is actually the Nitrogen and the oxygen furthest from the sugar. See below:

So having an extra methyl group on the other side of the molecule does not interrupt basepairing. And remember, with DNA/RNA synthesis you have a template, and the new strand is based on the template. So, when the RT enzyme Medhat mentions encounters an adenine in the template RNA, it will pair it with a thymidine. And when it encounters a uracil, it is able to pair it with an adenine. The enzyme is structured specifically to only allow in thymine and not uracil, which is how it makes the distinction.


CDNA Synthesis

Whatever your requirements, there is a Bio-Rad cDNA synthesis kit that meets your needs.

Reliance Select cDNA Synthesis
Kit

Select the Reliance Select cDNA Synthesis Kit to capture GC-rich targets and secondary structure in FFPE and difficult samples with degraded RNA or inhibitors.

Reverse Transcription Supermix
for RT-qPCR

Choose iScript reverse transcription supermix for fast, efficient, and sensitive cDNA synthesis for RT-qPCR &ndash a single tube and a 40-minute protocol.

Advanced cDNA Synthesis Kit
for RT-qPCR

Choose the iScript Advanced cDNA Synthesis Kit which has an extended dynamic range with a capacity for up to 7.5 µg input RNA.


How is RNA of retrovirus converted into cDNA? - Biology

This enzyme reverse transcriptase allows us to use an RNA template to produce a double-stranded cDNA copy. Reverse transcriptase was discovered by H. Temin and D. Baltimore while studying retroviruses. Retroviruses contain an RNA genome which is converted to a DNA copy and integrated into the host genome during its replicative cycle. This is an interesting set of viruses including many tumor viruses and the AIDS virus HIV.

Reverse transcriptase is an RNA-dependant DNA polymerase. It utilizes RNA as a template, requires dNTPs and a primer (free 3' OH) to initiate DNA polymerization.

Two types of primer are commonly used.

Oligo-dT initiates priming from the 3' end of the mRNAs.
cDNAs primed with oligo-dT are enriched for mRNA 3' ends.

Random oligonucleotides can hybridize anywhere along the mRNA sequence and prime cDNA synthesis. Randomly primed cDNAs are distributed along the length of the template and are therefore more representitive of the mRNA population.

mRNAs are typically short (as compared to the genome) - most mRNAs are under 6 kb in length and only rare mRNA exceed 10 kb in length.
This small size means that both plasmid and phage insertion vectors are appropriate for the construction of cDNA libraries
(in contrast to genomic libraries where phage substitution vectors are preferred).

In our discussion of genomic libraries, we focused on complete coverage of genome.
Random genomic fragments were generated by partial digestion with a frequent cutting enzyme.
The resulting random shotgun library contains multiple overlapping clones that cover the complete genome sequence.

cDNA libraries are a little different.
Here each bacterial transformant or packaged phage represents a unique mRNA molecule.
Recombinants containing the same DNA sequence represent different template molecules present in the e original mRNA population.

For example, there are 100,000 mRNA molecules in the cell at a given time
10% of them are some highly expressed mRNA (lets say actin mRNAs)
then in a primary cDNA library consisting of 100,000 clones,
10% of them (10,000) will be actin cDNAs.
Or you could just screen a couple of hundered cDNAs and still find actin cDNAs.

Well, thats very nice if you want to study actin.

What if you want to study some rare transcription factor that is only expressed at low levels.
In your 100,000 mRNAs, there may be only 10 mRNAs encoding your transcription factor.
Now you would have to screen your entire library of 100,000 clones.

If your transcript was only expressed for a short time at low levels, it might be present at even lower levels.

The majority of recombinant phage in a standard cDNA library carry highly expressed sequences.
Rare mRNAs are hard to find unless your library is very large (number of recombinants - should contain more than 10 6 independant recombinants to cover a mRNA population of 100,000 transcripts with 99% probability).

The alternative to screening increasing numbers of independant recombinants is to 'normalize' the library utilizing hybidization kinetics as we discussed previously.
Normalized libraries contain fewer copies of highly expressed mRNAs (removed on hybridization) and more copies of rare transcripts (in a relative sense).


Retrovirus

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Retrovirus, any of a group of viruses that belong to the family Retroviridae and that characteristically carry their genetic blueprint in the form of ribonucleic acid ( RNA). Retroviruses are named for an enzyme known as reverse transcriptase, which was discovered independently in 1971 by American virologists Howard Temin and David Baltimore. Reverse transcriptase transcribes RNA into deoxyribonucleic acid ( DNA), a process that constitutes a reversal of the usual direction of cellular transcription (DNA into RNA). The action of reverse transcriptase makes it possible for genetic material from a retrovirus to become permanently incorporated into the DNA genome of an infected cell the enzyme is widely used in the biological sciences to synthesize genes.

Retroviruses cause tumour growth and certain cancers in animals and are associated with slow infections of animals, such as equine infectious anemia. In humans, a retrovirus known as human T-cell lymphotropic virus type 1 (HTLV-1) causes a form of cancer called adult T-cell leukemia (ATL). It can also cause a neurodegenerative condition known as HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). A closely related virus named HTLV-2 is associated with relatively mild neurological disorders but has not been identified as a causative agent of human disease. As many as 20 million people worldwide are thought to be infected with HTLVs, but only a small percentage of infected individuals actually develop ATL or HAM/TSP. The retrovirus known as human immunodeficiency virus ( HIV) causes acquired immunodeficiency syndrome ( AIDS) in humans. HIV is closely related to simian immunodeficiency virus (SIV), a retrovirus found in chimpanzees and gorillas.

So-called endogenous retroviruses (ERVs) are persistent features of the genomes of many animals. ERVs consist of the genetic material of extinct, or “fossil,” viruses, the genomic constitution of which is similar to that of extant retroviruses. Human ERVs (HERVs) have become distributed within human DNA over the course of evolution. They are passed from one generation to the next and make up an estimated 1 to nearly 5 percent of the human genome. HERVs are suspected of having influenced the evolution of certain elements of the human genome. They also have been implicated in certain human diseases, including multiple sclerosis.

HTLV-1 was the first human retrovirus to be discovered, having been detected and isolated in 1979 by American virologist Robert C. Gallo and colleagues. HIV was first isolated in 1983.


The Widespread Occurrence and Potential Biological Roles of Endogenous Viral Elements in Insect Genomes

Modern genomic sequencing and bioinformatics approaches have detected numerous examples of DNA sequences derived from DNA and RNA virus genomes integrated into both vertebrate and insect genomes. Retroviruses encode RNA-dependent DNA polymerases (reverse transcriptases) and integrases that convert their RNA viral genomes into DNA proviruses and facilitate proviral DNA integration into the host genome. Surprisingly, DNA sequences derived from RNA viruses that do not encode these enzymes also occur in host genomes. Non-retroviral integrated RNA virus sequences (NIRVS) occur at relatively high frequency in the genomes of the arboviral vectors Aedes aegypti and Aedes albopictus, are not distributed randomly and possibly contribute to mosquito antiviral immunity, suggesting these mosquitoes could serve as a model system for unravelling the function of NIRVS. Here we address the following questions: What drives DNA synthesis from the genomes of non-retroviral RNA viruses? How does integration of virus cDNA into host DNA occur, and what is its biological function (if any)? We review current knowledge of viral integrations in insect genomes, hypothesize mechanisms of NIRVS formation and their potential impact on insect biology, particularly antiviral immunity, and suggest directions for future research.


Retroviruses 'almost half a billion years old'

A retrovirus has a membrane containing glycoproteins, which are able to bind to a receptor protein on a host cell. There are two strands of RNA within the cell that have three enzymes: protease, reverse transcriptase, and integrase (1). The first step of replication is the binding of the glycoprotein to the receptor protein (2). Once these have been bound, the cell membrane degrades, becoming part of the host cell, and the RNA strands and enzymes enter the cell (3). Within the cell, reverse transcriptase creates a complementary strand of DNA from the retrovirus RNA and the RNA is degraded this strand of DNA is known as cDNA (4). The cDNA is then replicated, and the two strands form a weak bond and enter the nucleus (5). Once in the nucleus, the DNA is integrated into the host cell's DNA with the help of integrase (6). This cell can either stay dormant, or RNA may be synthesized from the DNA and used to create the proteins for a new retrovirus (7). Ribosome units are used to transcribe the mRNA of the virus into the amino acid sequences which can be made into proteins in the rough endoplasmic reticulum. This step will also make viral enzymes and capsid proteins (8). Viral RNA will be made in the nucleus. These pieces are then gathered together and are pinched off of the cell membrane as a new retrovirus (9). Credit: Wikipedia/CC BY-SA 3.0

Retroviruses - the family of viruses that includes HIV - are almost half a billion years old, according to new research by scientists at Oxford University. That's several hundred million years older than previously thought and suggests retroviruses have ancient marine origins, having been with their animal hosts through the evolutionary transition from sea to land.

The findings, reported in the journal Nature Communications, will help us understand more about the continuing 'arms race' between viruses and their hosts.

Study author Dr Aris Katzourakis, from Oxford University's Department of Zoology, said: "Very little has been known about the ancient origin of retroviruses, partly because of the absence of geological fossil records. Retroviruses are broadly distributed among vertebrates and can also transmit between hosts, leading to novel diseases such as HIV, and they have been shown to be capable of leaping between distantly related hosts such as birds and mammals. But until now, it was thought that retroviruses were relative newcomers - possibly as recent as 100 million years in age.

"Our new research shows that retroviruses are at least 450 million years old, if not older, and that they must have originated together with, if not before, their vertebrate hosts in the early Paleozoic era. Furthermore, they would have been present in our vertebrate ancestors prior to the colonisation of land and have accompanied their hosts throughout this transition from sea to land, all the way up until the present day."

Retroviruses are a family of viruses that includes the HIV virus responsible for the AIDS pandemic. They can also cause cancers and immunodeficiencies in a range of animals. The 'retro' part of their name comes from the fact they are made of RNA, which they can convert into DNA and insert into their host genome - the opposite direction to the normal flow of information in a cell. This property means that they can occasionally be inherited as endogenous retroviruses (retroviruses with an internal origin), forming a virtual genomic fossil record that can be used to look back into their evolutionary history.

This research used genome sequences from endogenous retroviruses that resemble the 'foamy' viruses - a group of viruses that tend to diverge alongside their hosts. Foamy viruses are widespread in mammals, and in this study the researchers unearthed genomic fossils for foamy-like retroviruses in highly diverse hosts, including ray-finned fish and amphibians in which they had not previously been found.

During this study, the researchers overcame one of the key limitations in studying the deep evolutionary history of viruses: their rapid evolution. This trait facilitates the reconstruction of viruses' recent history but obscures their more distant past. However, a new model used in this research - in combination with the genomic fossil records of the foamy-like viruses - allowed the scientists to account for an apparent slowdown in the rate of evolution the further back they went.

Dr Katzourakis added: "These findings show that this medically important group of viruses is at least up to half a billion years in age - far older than previously thought. They date back to the origins of vertebrates, and this gives us the context in which we should consider their present-day activity and interactions with their hosts. For example, we need to consider the adaptations that vertebrates have developed to combat viruses, and the corresponding viral countermeasures, as the product of a continuous arms race that stretches back hundreds of millions of years.

"Our inferred date of the origins of retroviruses coincides with the origins of adaptive immunity, and thus it is likely that retroviruses have played an important role in the emergence of this key tool in vertebrate antiviral defence. As we understand the nature of the interaction between viruses and host immunity, we will be better placed to intervene in this delicately balanced arms race in order to develop novel treatments and interventions.

"And as we build a clearer picture of the origins of the diverse groups of viruses that infect us today, we should come closer to unravelling the mystery of their ultimate origins."


Components used in the RT-qPCR:

The selection of components for the reverse transcription PCR is as crucial as selecting temperature conditions but don’t worry about it, the ready to use reverse transcription PCR kit contains all the ingredients into the reaction buffer and reaction mixture.

Selecting every PCR ingredient and its quantity is as important as selecting temperature conditions for PCR. Nowadays, ready to use reverse transcription PCR kits make your work efficient as it has every ingredient in it. Let us see some components of RT-PCR,

  • Reverse transcriptase enzyme with RNase activity
  • RNase H (if the reverse transcriptase does not have it)
  • DNA polymerase

Abstract

Many viruses carry more than one segment of nucleic acid into the virion particle, but retroviruses are the only known group of viruses that contain two identical (or nearly identical) copies of the RNA genome within the virion. These RNA genomes are non-covalently joined together through a process known as genomic RNA dimerization. Uniquely, the RNA dimerization of the retroviral genome is of crucial importance for efficient retroviral replication. In this article, our current understanding of the relationship between retroviral genome conformation, dimerization and replication is reviewed.


Step 7: Data analysis

A. Data normalisation𠅌omparative Cq method

The importance of normalisation of qPCR data has been emphasised repeatedly [1, 26]. Data normalisation is a critical step in the qPCR workflow, as it corrects for variations in multiple steps, including RNA purification, RNA concentration assessment, as well as reverse transcription and amplification efficiency. Normalisation with stably expressed reference genes as internal controls, known as the comparative Cq or the Δ㥌q method, is the most common method for the normalisation of mRNA data. However, this technique requires appropriate validation to make sure it is performed correctly [27]. For the comparative Cq method to be valid, it is important to make sure the reference genes and target genes have a similar amplification efficiency, as a valid comparative Cq method is based on an additional assumption of similar amplification efficiency [28]. A standard curve can be plotted for the 㥌q (the difference between reference and target gene against the log of cDNA input), and the absolute value of the slope should be π.1 [29]. See an example of 㥌q between Cyclophilin and PGC-1α in Fig 6 . If it is not possible to obtain reference genes with similar amplification efficiency as the target, it is suggested to use the Pfaffl method for calculation, in which the calculation is adjusted by the differences in the amplification efficiency of the target and reference genes [30, 31].

The comparative Cq method normalises the Cq value of a target gene to internal reference genes before comparisons are made between samples. First, the difference between Cq values (㥌q) of the target gene and the geometric mean of multiple reference genes is calculated for each sample, and then the difference in the 㥌q (Δ㥌q) is calculated between two samples (e.g., control and treatment, or pre and post treatment). The fold-change in expression of the two samples is calculated as 2 -Δ㥌q , where 2 derives from 1 + efficiency and efficiency is assumed to be 1 (i.e., 100% efficiency) [28]. Our recommendation for using comparative Cq method is listed in Box 9.

Box 9

It is important to ensure that the reference genes and target genes have a similar amplification efficiency when using the comparative Cq method otherwise the Pfaffl method should be considered.

B. Choice of reference genes

Several traditional reference genes have been widely used in the qPCR analysis. A review article has reported that 33% and 32% of the expression analysis from 6 high-impact journals used glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and actin beta (ACTB) as reference genes respectively for papers published in 1999 [32]. However, the same review pointed out that the expression of both GAPDH and ACTB varies considerably under different experimental settings in a range of tissues [32]. GAPDH was originally identified as an intermediate in glycolysis pathway and expected to be stably present in all cells thus it was selected as a reference gene. However, other activities of GAPDH, including functions in endocytosis, translational control, and DNA replication [33], were not recognised until later [32].

Various reference genes have been used in different exercise studies. Mahoney et al. -[34] reported that β-2-microglobulin (B2M) and ACTB were the most stable reference genes following 300 eccentric contractions, whereas B2M and GAPDH were the most stable following 75 min of high-intensity intermittent cycling. In another study, muscle biopsies were taken before, immediately after, and 4 h following 30 min of treadmill running at 70% of VO2max, and RNA was extracted from 40 single fibres. GAPDH was found to be stably expressed in all samples [35]. Thus, when using reference genes as internal controls for an exercise study, the stability of each reference gene needs to be evaluated carefully, and there is no ‘one-size-fits-all’ gene that can be used in all studies and with all exercise protocols.

In order to reduce the variability of internal control, it is recommended to use multiple genes for normalisation [36, 37]. Using samples obtained from neuroblastoma cell lines, Vandesompele and his colleagues showed that normalisation using a single reference gene led to differences of 3.0-fold in 25%, and 6.4-fold in 10%, of the cases analysed [36]. The evaluation of reference genes can be achieved by running a statistical analysis on the Cq value or using available software. Several software programs are available for reference gene evaluation using different analytical approaches, such as BestKeeper [38], NormFinder [39], and GeNorm [36].

In our laboratory, we have six commonly-used reference genes, ACTB, TATA-box binding protein (TBP), Cyclophilin, GAPDH, B2M, and 18S rRNA ( Table 4 ). There are a few reasons why these candidate reference genes were chosen. First of all, these six genes are potentially stably-expressed reference genes, and are widely used in the qPCR analysis of skeletal muscle samples obtained in human exercise studies [34, 35, 40]. Second, they belong to different functional classes thus it is unlikely they are co-regulated. However, using comparative Cq method, it is difficult to qualify small differences in gene expression (i.e., less than 2-fold) unless multiple stably-expressed reference genes are used for normalisation [36, 41].

Table 4

GeneAccession no.Function (NCBI Reference sequence database [42])
ACTB (actin beta) <"type":"entrez-nucleotide","attrs":<"text":"NM_001101.3","term_id":"168480144","term_text":"NM_001101.3">> NM_001101.3This gene encodes one of six different actin proteins, which is a major constituent of the contractile apparatus and one of the two nonmuscle cytoskeletal actins.
TBP (TATA-box binding protein) <"type":"entrez-nucleotide","attrs":<"text":"NM_003194.4","term_id":"285026518","term_text":"NM_003194.4">> NM_003194.4This gene encodes a general transcription factor that binds specifically to a DNA sequence called the TATA box, and helps position RNA polymerase II over the transcription start site of the gene.
Cyclophilin (PPIA, peptidyl-prolyl cis-trans isomerase A) <"type":"entrez-nucleotide","attrs":<"text":"NM_021130.4","term_id":"665821272","term_text":"NM_021130.4">> NM_021130.4This gene encodes a protein that catalyses the cis-trans isomerization of proline imidic peptide bonds in oligopeptides and accelerates the folding of proteins.
GAPDH (glyceraldehyde-3-phosphate dehydrogenase) <"type":"entrez-nucleotide","attrs":<"text":"NM_001289746.1","term_id":"576583523","term_text":"NM_001289746.1">> NM_001289746.1This gene encodes a key enzyme in the glycolytic pathway, which catalyses the reversible oxidative phosphorylation of glyceraldehyde-3-phosphate in the presence of inorganic phosphate and nicotinamide adenine dinucleotide (NAD).
B2M (β-2-microglobulin) <"type":"entrez-nucleotide","attrs":<"text":"NM_004048.2","term_id":"37704380","term_text":"NM_004048.2">> NM_004048.2This gene encodes a serum protein in association with the major histocompatibility complex (MHC) class I heavy chain on the surface of nearly all nucleated cells.
18S rRNA (RNA, 18S ribosomal) <"type":"entrez-nucleotide","attrs":<"text":"NR_003286.2","term_id":"225637497","term_text":"NR_003286.2">> NR_003286.2This gene represents the portion of one rDNA repeat which encodes a 18S rRNA.

Experiment 4

In our human exercise study (see Materials and methods), muscle samples were taken from 9 participants at rest (Baseline), and then immediately post (0 h) and 3 h post (3 h) the final training session of a 4-week training intervention. All muscle samples were snap-frozen immediately after the muscle biopsy, and the RNA for all samples (n = 27) was extracted using RNeasy Plus Universal Mini Kit with a modified protocol (using 2-propanol) for all samples we obtained an A260/A280 ratio greater than 1.9 and an RQI score greater than 7 (using an Experion automated electrophoresis system). We then performed the reverse transcription to convert RNA into cDNA in a single run, before conducting qPCR analysis. To find stably expressed reference genes across all samples at all time points, we tested six reference genes (ACTB, TBP, Cyclophilin, GAPDH, B2M, and 18S rRNA Table 5 and Fig 7 ). We then used RefFinder to evaluate the stability of these genes. RefFinder is a web-based tool, which is able to run four well-established algorithms simultaneously (GeNorm [36], BestKeeper [38], NormFinder [39] and comparative delta-CT [43]), assign an appropriate weight to each individual gene, and calculate the geometric mean of their weights for the overall final ranking [44]. Based on the recommended comprehensive ranking from RefFlinder, our candidate genes were ranked from most to least stable as B2M, TBP, 18S rRNA, ACTB, GAPDH and Cyclophilin ( Table 5 ).

Cq values of individual reactions using ACTB, TBP, Cyclophilin, GAPDH, B2M, and 18S rRNA primers are presented. All samples are from an exercise study (n = 9 participants × 3 time points = 27 samples).

Table 5

Ranking Order (Most to least stable)
Method123456
Delta CTTBPB2M18S rRNAACTBGAPDHCyclophilin
BestKeeperB2MTBP18S rRNAACTBGAPDHCyclophilin
NormFinderTBPB2M18S rRNAACTBGAPDHCyclophilin
GenormB2M / 18S rRNATBPACTBGAPDHCyclophilin
Recommended comprehensive rankingB2MTBP18S rRNAACTBGAPDHCyclophilin

To illustrate how one might go about choosing reference genes, we choose PPARG coactivator 1 alpha (PGC-1α) as an example for gene expression analysis. PGC-1α is a transcriptional coactivator that is enriched in skeletal muscle. It has been shown that exercise is able to increase PGC-1α mRNA content in humans [45]. The amplification efficiency of all six candidate reference genes was similar to our target gene, PGC-1α ( Table 6 ). We used the geometric mean of top three ranked genes by RefFinder (TBP, B2M, and 18S rRNA) for subsequent data normalisation. Our recommendations for choosing reference genes are listed in Box 10.

Table 6

GeneAccession no.Primers (Forward and Reverse)Amplicon size (bp)Start position (bp)Efficiency (%)Source
TBP (TATA-box binding protein) <"type":"entrez-nucleotide","attrs":<"text":"NM_003194.4","term_id":"285026518","term_text":"NM_003194.4">> NM_003194.4 F: CAGTGACCCAGCAGCATCACT
R: AGGCCAAGCCCTGAGCGTAA
20512199[46]
Cyclophilin (PPIA, peptidyl-prolyl cis-trans isomerase A) <"type":"entrez-nucleotide","attrs":<"text":"NM_021130.4","term_id":"665821272","term_text":"NM_021130.4">> NM_021130.4 F: GTCAACCCCACCGTGTTCTTC
R: TTTCTGCTGTCTTTGGGACCTTG
10093100[47]
B2M (β-2-microglobulin) <"type":"entrez-nucleotide","attrs":<"text":"NM_004048.2","term_id":"37704380","term_text":"NM_004048.2">> NM_004048.2 F: TGCTGTCTCCATGTTTGATGTATCT
R: TCTCTGCTCCCCACCTCTAAGT
8658998[36]
ACTB (actin beta) <"type":"entrez-nucleotide","attrs":<"text":"NM_001101.3","term_id":"168480144","term_text":"NM_001101.3">> NM_001101.3 F: GAGCACAGAGCCTCGCCTTT
R: TCATCATCCATGGTGAGCTGGC
7026107Designed by authors
18S rRNA (RNA, 18S ribosomal 5) <"type":"entrez-nucleotide","attrs":<"text":"NR_003286.2","term_id":"225637497","term_text":"NR_003286.2">> NR_003286.2 F: CTTAGAGGGACAAGTGGCG
R: GGACATCTAAGGGCATCACA
71144399[48]
GAPDH (glyceraldehyde-3-phosphate dehydrogenase) <"type":"entrez-nucleotide","attrs":<"text":"NM_001289746.1","term_id":"576583523","term_text":"NM_001289746.1">> NM_001289746.1 F: AATCCCATCACCATCTTCCA
R: TGGACTCCACGACGTACTCA
82388106[49]
PGC-1α (PPARG coactivator 1 alpha) <"type":"entrez-nucleotide","attrs":<"text":"NM_013261.3","term_id":"116284374","term_text":"NM_013261.3">> NM_013261.3 F: CAGCCTCTTTGCCCAGATCTT
R: TCACTGCACCACTTGAGTCCAC
101199104[50]

Box 10

It is recommended to test multiple reference genes [36, 37], and the stability of each gene should be assessed before choosing appropriate reference genes for a particular study. We recommend using RefFinder to assess the stability of reference genes, as it runs four well-established algorithms simultaneously. Other than the stability of the reference gene, the amplification efficiency of the reference genes should be similar to the target genes.

C. Normalising gene expression via cDNA quantification

Finding stable reference genes is a challenge when performing qPCR, and researchers have been seeking alternative methods such as quantifying cDNA. Quant-iT ™ OliGreen ssDNA reagent is a fluorescent nucleic acid dye for quantifying cDNA, and it has been used in many published papers including studies investigating gene expression in human skeletal muscle in response to exercise [51�]. A potential problem with using OliGreen dye to quantify cDNA content is that the dye is also sensitive to RNA, as stated in the user manual “the OliGreen reagent does exhibit fluorescence enhancement when bound to RNA” [54].

Experiment 5

To test the specificity and validity of using OliGreen dye to qualify cDNA content, we synthesised cDNA from four different amounts (0, 0.25, 0.5, and 1 μg) of RNA obtained from Experiment 1 (‘Good Practice”, n = 4 for each RNA input). We also loaded 1 μg RNA in the–RT control reaction, which contained no cDNA (n = 4). We used iScript ™ Reverse Transcription Supermix (Bio-Rad) for cDNA synthesis. The enzyme reverse transcriptase in this kit has RNase H + activity that degrades the RNA strand in RNA-DNA hybrids after cDNA synthesis. The cDNA content in each sample was then measured using OliGreen dye ( Fig 8A ). Consistent with previous research [51], cDNA samples synthesised from different amounts of RNA showed a strong positive correlation for the measured cDNA concentration versus RNA input (r = 0.9947, P< 0.0001) ( Fig 8B ). However, the -RT control reaction, which contained only 1 μg RNA but no cDNA, showed a higher reading than cDNA synthesised from 0.5 μg RNA. This result confirmed that the OliGreen dye is not specifically measuring ssDNA, but measures RNA as well. This could cause a false high cDNA content in the assay if RNA is not degraded properly. Our recommendations for normalising gene expression via cDNA quantification are listed in Box 11.

A: Determination of cDNA amount in reactions with different RNA input. Different amounts of RNA were used to synthesise cDNA (n = 4 for each RNA input), and the relative amount of cDNA in each reaction was measured using OliGreen dye. Values are presented as mean ± SD. B: Correlation between RNA input and average relative amount of cDNA measured.

Box 11

In order to obtain an accurate and specific measurement of cDNA from the Oligreen dye, RNA in the RNA-DNA hybrids needs to be degraded before measurement. This can be achieved by using a reverse transcriptase enzyme with RNase H + activity ( Fig 8 ), or including an RNase degradation step after cDNA synthesis [51].

D. Effect of normalisation methods on the results

Experiment 6

To investigate how normalisation might alter the outcome, we measured the exercise-induced expression of PGC-1α mRNA in the samples from a human exercise study (as described in Experiment 4) and analysed the same set of data in three ways. We performed normalisation using three of the most stable reference genes (TBP, B2M, and 18S rRNA), based on the reference gene evaluation ( Table 5 ). In comparison, we also used a single reference gene, Cyclophilin, which was the lowest ranked reference gene. Lastly, we analysed the data using the cDNA content measured by Quant-iT ™ OliGreen ssDNA Reagent. We saw a significant difference in gene expression at 3 hours after exercise using all three normalisation options (P < 0.01, Fig 9 ). These exercise-induced fold changes in PGC-1α expression are consistent with the existing literature [40, 45].

Muscle samples were taken at rest (Baseline, Week 0) and immediately post-exercise (0 h), and 3 h post-exercise. Data were analysed using 3 different normalisation methods. Values are fold change ± SD.

There were no significant differences between the fold changes in PGC-1α mRNA content when using different methods of normalisation however, the fold changes were more similar when using three reference genes and cDNA content for normalisation, rather than using one reference gene. The increase of PGC-1α was 3.4 ± 2.0 fold when three reference genes were used for normalisation. When a single reference gene (Cyclophilin) was used for normalisation, the increase in gene expression was 5.1 ± 2.4 fold (P = 0.08 compared to 3 reference genes). When cDNA content was used for normalisation, the increase of gene expression was 3.2 ± 1.9 fold (P = 0.51 compared to 3 reference genes, P = 0.09 compared to 1 reference gene). In certain experimental settings, especially when examining small changes in mRNA level, these different results could lead to different conclusions. This may also help to explain the inter-study variability for exercise-induced changes in mRNA content. As previously suggested, use of a single reference gene is considered ‘not acceptable’ unless its stability has been clearly demonstrated in the same study [1]. Our recommendations for normalising gene expression via reference genes are listed in Box 12.

Box 12

We recommend testing four or more candidate reference genes for each study, and selecting the ones that are stably expressed for data normalisation. In our research laboratory, we chose to use two to three most stable reference genes based on evaluation software for an individual study [45, 55].


DNA provirus hypothesis

In the mid-20th century there were many advances in molecular biology, including the description of DNA in 1953 by American geneticist and biophysicist James D. Watson and British biophysicists Francis Crick and Maurice Wilkins. By the 1960s it was understood that sarcomas are caused by a mutation that results in uncontrolled cell division. It was also evident that RSV was inherited during the division of cancerous cells. This inheritance occurred in a manner agreeing with the Mendelian laws of genetic inheritance—laws that heretofore had been understood to apply only to DNA molecules (see the articles genetics and heredity).

Scientists hypothesized that, in order for such viral inheritance to occur, a virus would need to transcribe its RNA genome into DNA and then insert this DNA into the host cell genome. Once incorporated into the host genome, the virus would be transcribed as though it were another gene and could produce more RNA virus from its DNA. This hypothesis, called the “DNA provirus hypothesis,” was developed in the late 1950s by American virologist Howard Martin Temin, when he was a postdoctoral fellow in the laboratory of Italian virologist Renato Dulbecco at the California Institute of Technology. Temin’s hypothesis was formally proposed in 1964. The provirus hypothesis came about when experiments demonstrated that an antibiotic called actinomycin D, which is capable of inhibiting DNA and RNA synthesis, inhibited the reproduction of RSV. However, the concept of an RNA molecule’s turning itself into DNA drew very few supporters.


Watch the video: RNA extraction and cDNA synthesis (December 2022).