Eliminating fossil fuel subsidies would reduce the health risks of air pollution, and would greatly reduce global carbon emissions thus helping to limit climate change. As of 2021, policy researchers estimate that substantially more money is spent on fossil fuel subsidies than on environmentally harmful agricultural subsidies or environmentally harmful water subsidies. The International Energy Agency
says: "High fossil fuel prices hit the poor hardest, but subsidies are
rarely well-targeted to protect vulnerable groups and tend to benefit
better-off segments of the population."
Despite the G20 countries having pledged to phase-out inefficient fossil fuel subsidies, as of 2023 they continue because of voter demand,or for energy security.
Definition
Fossil fuel subsidies have been described as "any government action
that lowers the cost of fossil fuel energy production, raises the price
received by energy producers, or lowers the price paid by energy
consumers." Including negative externalities such as health costs results in a much larger total. Thus by the IMF definition they are far larger than by the OECD and International Energy Agency (IEA) definitions.
Subsidies for electricity and heat may be taken into account, depending on the share produced by fossil fuels. Sometimes there are disputes about what definition to use: for example
the UK government said in 2021 that it uses the IEA definition and does
not subsidize fossil fuels, but others said the same year that under the OECD definition it does.
Measurement
Subsidies may be estimated by adding up direct subsidies from government, comparing prices in a country to world market prices, and sometimes attempting to include the cost of damage to human health and the climate. Setting fossil fuel prices that reflect their true cost would cut global CO2 emissions by 10% by 2030, according to the IPCC in 2023. The International Institute for Sustainable Development say that G7 countries should reveal their subsidies every year under Sustainable Development Goal (SDG) indicator 12.c.1 (fossil fuel subsidies).
The fiscal cost of government support for fossil fuels was 1.1
trillion USD in 2023. Most (90%) of which is related to the consumption
of fossil fuels. The fiscal cost of support for residential users was
189 billion USD in 2023, while for manufacturing and other industries it
was 103.8 billion USD. The OECD
said that "Most of this support lacked systematic targeting towards
those in greatest need, raising both equity and efficiency concerns."
Economic incentives to decarbonise from fuel taxes, carbon taxes, emissions trading systems
(ETSs) and price-reducing support mechanisms - summarised in the net
Effective Carbon Rate (Net ECR) - averaged EUR 14.0/tCO2e in 2023. The
share of GHG emissions covered by a positive Net ECR was 42%; 27% of GHG
emissions are covered by explicit carbon prices (carbon taxes or ETSs).
The OECD
said that "The high fiscal cost of government support for fossil fuels
and low Net ECR highlight the challenges of staying on track with net
zero commitments in the face of economic and geopolitical pressures.
Reforms should focus on better targeting those most in need and phasing
out inefficient support for fossil fuels as soon as possible to enable
the release of much-needed resources for the net zero transition and
help accelerate innovation for energy efficiency. Given the high costs
of inaction, governments should reaffirm and implement their SDG
commitment to phase out and reform inefficient support to fossil fuels
to align fiscal policy with climate goals."
Effects
Subsidies on consumption reduce the price of energy for end
consumers, for example the cost of gasoline for car drivers in Iran.
This may win votes at elections and some people in government say it
helps poorer citizens.
The consensus among economists is that the rich get most absolute benefit from fossil fuel subsidies, for example the poorest people do not usually own cars. But removing
the subsidies may hit poor people via indirect price increases such as
food prices, so they get a lot of benefit relative to their total
income. Producers, such as oil companies, say that increasing taxes on them would cause unemployment and reduce national energy security.
Health effects
Subsidies are estimated to cause hundreds of thousands of deaths from air pollution each year.
Fossil fuel subsidies are a negative carbon price and use government money that could be spent on other things. The International Monetary Fund says that by encouraging excess energy use they can make countries more vulnerable to variation in international energy prices. However some governments say that the subsidies are necessary to shield citizens from such variation. According to the International Energy Agency (IEA) phasing out fossil fuel subsidies would benefit energy markets, climate change mitigation and government budgets.
Many economists recommend replacing consumption subsidies with direct payments targeted at poor people or households. The best way to use the money saved will likely require country specific studies. However phase-out is politically difficult.
The International Energy Agency estimates that governments subsidised consumption of fossil fuels by US $1 trillion in 2022. At their meeting in September 2009 the G-20
countries committed to "rationalize and phase out over the medium term
inefficient fossil fuel subsidies that encourage wasteful consumption". Many say that all fossil fuel subsidies are inefficient.
The 2010s saw many other countries reducing energy subsidies, for
instance in July 2014 Ghana abolished all diesel and gasoline
subsidies, whilst in the same month Egypt raised diesel prices 63% as
part of a raft of reforms intended to remove subsidies within 5 years.
In Sept, 2021, the IMF
produced a working paper with estimates for the subsidies caused by the
gap between the efficient price of fossil fuels and user prices. "Underpricing for local air pollution costs is the largest contributor
to global fossil fuel subsidies, accounting for 42 percent, followed by
global warming costs (29 percent), other local externalities such as
congestion and road accidents (15 percent), explicit subsidies (8
percent) and foregone consumption tax revenue (6 percent)." Globally, fossil fuel subsidies were $5.9 trillion which amounts to
6.8% of GDP in 2020 and are expected to rise to 7.4% in 2025.
The table below shows excerpts from a 2021 IMF study for 20
countries with biggest subsidies. It also shows the biggest component of
explicit subsidies, electricity costs, and of implicit subsidies, coal.
See these references for complete data:(Units are billions of 2021 US dollars.)
Fossil fuel subsidies - top 20 countries US$ billions
2020
Explicit Subsidies
Implicit Subsidies
Total
Electricity
Total
Coal
Total
China
13.69
15.73
1,391.78
2,187.50
2,203.23
United States
0.00
16.06
121.45
646.00
662.05
Russia
25.14
77.36
195.26
445.26
522.62
India
8.71
16.18
162.72
230.89
247.07
Japan
2.74
4.75
57.69
164.80
169.55
Saudi Arabia
8.72
53.75
0.00
104.36
158.11
Iran
26.51
41.72
4.59
111.05
152.77
Indonesia
5.49
11.96
32.85
115.13
127.09
Turkey
0.24
4.11
52.59
112.61
116.72
Egypt
7.32
9.69
1.89
95.38
105.07
Germany
0.00
3.43
25.50
68.32
71.75
Korea, South
0.00
0.58
28.93
68.39
68.98
Canada
2.43
10.34
3.04
53.69
64.03
South Africa
5.62
5.72
30.41
44.84
50.56
Kazakhstan
4.57
9.93
19.11
37.05
46.98
Taiwan
1.67
2.58
25.42
43.55
46.13
Australia
2.14
5.57
14.85
38.92
44.49
Ukraine
4.57
7.76
28.76
35.87
43.63
Malaysia
0.90
3.52
5.52
39.50
43.02
Brazil
0.00
5.80
4.60
37.17
42.97
World total
189.53
454.79
2,362.26
5,402.57
5,857.36
Canada
The Canadian federal government offers subsidies for fossil fuel
exploration and production and Export Development Canada regularly
provides financing to oil and gas companies. A 2018 report from the
Overseas Development Institute, a UK-based think tank, found that Canada
spent a greater proportion of its GDP on fiscal support to oil and gas
production in 2015 and 2016 than any other G7 country.
In 2018, in response to low Canadian oil prices, the federal
government announced $1.6 billion in financial support for the oil and
gas sector: $1 billion in loans to oil and gas exporters from Export
Development Canada, $500 million in financing for "higher risk" oil and
gas companies from the Business Development Bank of Canada, $50 million
through Natural Resources Canada's Clean Growth Program, and $100
million through Innovation, Science and Economic Development Canada's
Strategic Innovation Fund. Minister of Natural Resources Amarjeet Sohi
said that this financing is "not a subsidy for fossil fuels", adding
that "These are commercial loans, made available on commercial terms. We
have committed to phasing out inefficient fossil fuel subsidies by
2025, and we stand by that commitment". Canada has committed to phase out fossil fuel subsidies by 2023.
Canadian provincial governments also offer subsidies for the
consumption of fossil fuels. For example, Saskatchewan offers a fuel tax
exemption for farmers and a sales tax exemption for natural gas used
for heating.
A 2018 report from the Overseas Development Institute was
critical of Canada's reporting and transparency practices around its
fossil fuel subsidies. Canada does not publish specific reports on its
fiscal support for fossil fuels, and when Canada's Office of the
Auditor-General attempted an audit of Canadian fossil fuel subsidies in
2017, they found much of the data they needed was not provided by
Finance Canada. Export Development Canada reports on their transactions
related to fossil fuel projects, but do not provide data on exact
amounts or the stage of project development.
China
The energy policy of China says that energy security requires subsidy of production and consumption of fossil fuels including coal, oil and natural gas.
India
In financial year 2021 fossil fuel subsidies have been estimated at 9
times renewable energy subsidies: with INR 55,250 crore for oil and gas
and INR 12,976 crore for coal.
Russia holds the world's largest natural gas reserves (27% of total),
the second-largest coal reserves, and the eighth-largest oil reserves. Russia is the world's third-largest energy subsidizer as of 2015. The country subsidizes electricity and natural gas as well as oil
extraction. Approximately 60% of the subsidies go to natural gas, with
the remainder spent on electricity (including under-pricing of gas
delivered to power stations). For oil extraction the government gives tax exemptions and duty
reductions amounting to about 22 billion dollars a year. Some of the tax
exemptions and duty reductions also apply to natural gas extraction,
though the majority is allocated for oil. The large subsidies of Russia are costly and it is recommended in
order to help the economy that Russia lowers its domestic subsidies. However, the potential elimination of energy subsidies in Russia
carries the risk of social unrest that makes Russian authorities
reluctant to remove them.
Saudi Arabia
Most energy subsidies in Saudi Arabia are implicit in nature. This is
due to the fact domestic oil prices are generally below global market
prices but above domestic production costs, leading to forgone revenue
but not direct subsidy costs. Contrary to the estimates above, a recent
paper posits that the incremental electricity subsidy in Saudi Arabia
has been eliminated as a result of the 2018 domestic energy price
reforms.
Turkey
In the 21st century, Turkey's fossil fuel subsidies are around 0.2% of GDP, including at least US$14 billion (US$169 per person) between January 2020 and September 2021. If unpaid damages (such as health damage from air pollution) are
included road fuel subsidy is estimated at over 400 dollars per person
per year and for all fossil fuels over one thousand dollars. Data on finance for fossil fuels by state-owned banks and export credit agencies is not public. The energy minister Fatih Dönmez supports coal and most energy subsidies are for coal, which the OECD has strongly criticised. Capacity mechanism payments to coal-fired power stations in Turkey in 2019 totalled ₺720 million (US$130 million) compared to ₺542 million (US$96 million) to gas-fired power stations in Turkey. In 2022 these payments totalled over US$200 million. As of 2020, the tax per unit energy on gasoline was higher than diesel, despite diesel cars on average emitting more lung damaging NOx (nitrogen oxide).
Venezuela
2020 subsidy has been estimated at 7% of GDP. In 2021 the subsidized and rationed gasoline price was around 25 US cents a litre, half of the unsubsidized price.
In philosophy, the brain in a vat (BIV) is a scenario used in a variety of thought experiments intended to draw out certain features of human conceptions of knowledge, reality, truth, mind, consciousness, and meaning. Gilbert Harman conceived the scenario, which Hilary Putnam turned into a modernized version of René Descartes's evil demon thought experiment. Following many science fiction stories, the scenario involves a mad scientist who might remove a person's brain from the body, suspend it in a vat of life-sustaining liquid, and connect its neurons by wires to a supercomputer that would provide it with electrical impulses identical to those a brain normally receives. According to such stories, the computer would then be simulating reality
(including appropriate responses to the brain's own output) and the
"disembodied" brain would continue to have perfectly normal conscious
experiences, like those of a person with an embodied brain, without
these being related to objects or events in the real world. According to
Putnam, the thought of "being a brain-in-a-vat" is either false or
meaningless.
Considered a cornerstone of semantic externalism, the argument produced significant literature. The Matrix franchise and other fictional works (below) are considered inspired by Putnam's argument.
Intuitive version
Putnam's argument is based on the causal theory of reference, where a word
describing a spatio-temporal object is meaningful if and only if it
possesses an information-carrying causal relation to whatever it
denotes. Next, an "envatted" brain is one whose entire world is composed
of (say) electric manipulations performed by a computer simulation
to which it is connected. With this much in place, consider the
sentence "I am a brain in a vat" (BIV). In case you are not a brain in a
vat, the sentence is false by definition. In case you are a brain in a
vat, the terms "brain" and "vat" fail to denote
actual brains and actual vats with whom you had an information-carrying
causal interaction since, again by definition, the only interaction
available is with the computer simulation, which is not information carrying. By the causal theory of reference, such references do not carry referential meaning. Thus, the sentence "I am a brain in a vat" is either false or meaningless.
Uses
The simplest use of brain-in-a-vat scenarios is as an argument for philosophical skepticism and solipsism.
A simple version of this runs as follows: since the brain in a vat
gives and receives exactly the same impulses as it would if it were in a
skull, and since these are its only way of interacting with its
environment, then it is not possible to tell, from the perspective of that brain,
whether it is in a skull or a vat. Yet in the first case, most of the
person's beliefs may be true (if they believe, say, that they are
walking down the street, or eating ice-cream); in the latter case, their
beliefs are false. Since the argument says if one cannot know whether
one is a brain in a vat, then one cannot know whether most of one's
beliefs might be completely false. Since, in principle, it is impossible
to rule out oneself being a brain in a vat, there cannot be good
grounds for believing any of the things one believes; a skeptical
argument would contend that one certainly cannot know them, raising issues with the definition of knowledge.
Other philosophers have drawn upon sensation and its relationship to
meaning in order to question whether brains in vats are really deceived
at all, thus raising wider questions concerning perception, metaphysics, and the philosophy of language.
Recently, many contemporary philosophers believe that virtual
reality will seriously affect human autonomy as a form of brain in a
vat. But another view is that VR will not destroy our cognitive
structure or take away our connection with reality. On the contrary, VR
will allow us to have more new propositions, new insights and new
perspectives to see the world.
Philosophical debates
While the disembodied brain (the brain in a vat) can be seen as a
helpful thought experiment, there are several philosophical debates
surrounding the plausibility of the thought experiment. If these debates
conclude that the thought experiment is implausible, a possible
consequence would be that we are no closer to knowledge, truth,
consciousness, representation, etc. than we were prior to the
experiment.
Argument from biology
A human brain in jar
One argument against the BIV thought experiment derives from the idea
that the BIV is not – and cannot be – biologically similar to that of
an embodied brain (that is, a brain found in a person). Since the BIV is
disembodied, it follows that it does not have similar biology to that of an embodied brain. That is, the BIV lacks the connections from the body to the brain, which renders the BIV neither neuroanatomically nor neurophysiologically similar to that of an embodied brain. If this is the case, we cannot say that it is even possible for the BIV
to have similar experiences to the embodied brain, since the brains are
not equal. However, it could be counter-argued that the hypothetical
machine could be made to also replicate those types of inputs.
Argument from externalism
A second argument deals directly with the stimuli coming into the brain. This is often referred to as the account from externalism or ultra-externalism. In the BIV, the brain receives stimuli from a machine. In an embodied
brain, however, the brain receives the stimuli from the sensors found in
the body (via touching, tasting, smelling, etc.) which receive their
input from the external environment. This argument oftentimes leads to
the conclusion that there is a difference between what the BIV is
representing and what the embodied brain is representing. This debate
has been hashed out, but remains unresolved, by several philosophers
including Uriah Kriegel, Colin McGinn, and Robert D. Rupert, and has ramifications for philosophy of mind discussions on (but not limited to) representation, consciousness, content, cognition, and embodied cognition.
Argument from incoherence
A third argument against BIV comes from a direction of incoherence, which was presented by the philosopher Hilary Putnam.
He attempts to demonstrate this through the usage of a transcendental
argument, in which he tries to illustrate that the thought experiment's
incoherence lies on the basis that it is self-refuting. This relationship is further defined, through a theory of reference that
suggested reference can not be assumed, and words are not automatically
intrinsically connected with what it represents. This theory of
reference would later become known as semantic externalism. This concept
is further illustrated when Putnam establishes a scenario in which a monkey types out Hamlet by chance; however, this does not mean that the monkey is referring to the play, because the monkey has no knowledge of Hamlet and therefore can not refer back to it. He then offers the "Twin Earth"
example to demonstrate that two identical individuals, one on the Earth
and another on a "twin Earth", may possess the exact same mental state
and thoughts, yet refer to two different things. For instance, when people think of cats, the referent of their thoughts
would be the cats that are found on Earth. However, people's twins on
twin Earth, though possessing the same thoughts, would instead be
referring not to Earth's cats, but to twin Earth's cats. Bearing this in
mind, he writes that a "pure" brain in a vat, i.e., one that has never
existed outside of the simulation, could not even truthfully say that it
was a brain in a vat. This is because the BIV, when it says "brain" and
"vat", can only refer to objects within the simulation, not to things
outside the simulation it does not have a relationship with. Putnam
refers to this relationship as a "causal connection" which is sometimes
referred to as "a causal constraint". Therefore, what it says is demonstrably false. Alternatively, if the
speaker is not actually a BIV, then the statement is also false. He
concludes, then, that the statement "I'm a BIV" is necessarily false and
self-refuting. This argument has been explored at length in philosophical literature
since its publication. A potential loophole in Putnam's reference theory
is that a brain on Earth that is "kidnapped", placed into a vat, and
subjected to a simulation could still refer to brains and vats which are
real in the sense of Putnam, and thus correctly say it is a brain in a
vat according to Putnamian reference theory. However, the notion that the "pure" BIV is incorrect and the reference theory underpinning it remains influential in the philosophy of mind, language and metaphysics. Anthony L. Brueckner has formulated an extension of Putnam's argument which rules out this loophole by employing a disquotational principle. It will be discussed in the following two sections.
Reconstructions of Putnam's argument
An issue that has arisen with Putnam's argument is that his premises only imply the metalinguistic
statement "my utterances of 'I am a BIV' are false", but a skeptic may
demand the object-language statement "I am a BIV" to be proven. To combat this issue, various philosophers have reconstructed Putnam's argument. Some, like Anthony L. Brueckner and Crispin Wright, have taken approaches that utilize disquotational principles. Others, like Ted A. Warfield, have taken approaches that focus on the concepts of self-knowledge and priori.
The disjunctive argument
One of the earliest but influential reconstructions of Putnam's transcendental argument
was suggested by Anthony L. Brueckner. Brueckner's reconstruction is as
follows: "(1) Either I am a BIV (speaking vat-English) or I am a
non-BIV (speaking English). (2) If I am a BIV (speaking vat-English),
then my utterances of 'I am a BIV' are true if I have sense impressions
as of being a BIV. (3) If I am a BIV (speaking vat-English), then I do
not have sense impressions as of being a BIV. (4) If I am a BIV
(speaking vat-English), then my utterances of 'I am a BIV' are false.
[(2), (3)] (5) If I am a non-BIV (speaking English), then my utterances
of 'I am a BIV' are true if I am a BIV. (6) If I am a non-BIV (speaking
English), then my utterances of 'I am a BIV' are false. [(5)] (7) My
utterances of 'I am a BIV' are false. [(1), (4), (6)]" Though these premises further define Putnam's argument, they do not so
far prove "I am not a BIV", because, although the premises imply the
metalinguistic statement "my utterances 'I am a BIV' are false", they do
not yet imply the object-language statement "I am not a BIV". To
achieve the Putnamian conclusion, Brueckner strengthens his argument by
employing the disquotational principle "My utterances of 'I am not a
BIV' are true if I am not a BIV." This statement is justified since the
metalanguage that contains the tokens for the disquotational principle
also contains the object language tokens to which the utterances 'I am
not a BIV' belong.
Gene expression is the process by which the information contained within a gene is used to produce a functional gene product, such as a protein or a functional RNA molecule. This process involves multiple steps, including the transcription of the gene's sequence into RNA. For protein-coding genes, this RNA is further translated
into a chain of amino acids that folds into a protein, while for
non-coding genes, the resulting RNA itself serves a functional role in
the cell. Gene expression enables cells to utilize the genetic
information in genes to carry out a wide range of biological functions.
While expression levels can be regulated in response to cellular needs
and environmental changes, some genes are expressed continuously with
little variation.
Mechanism
Transcription
The
process of transcription is carried out by RNA polymerase (RNAP), which
uses DNA (black) as a template and produces RNA (blue).
The production of a RNA copy from a DNA strand is called transcription, and is performed by RNA polymerases, which add one ribonucleotide at a time to a growing RNA strand as per the complementarity law of the nucleotide bases. This RNA is complementary to the template 3′ → 5′ DNA strand, with the exception that thymines (T) are replaced with uracils (U) in the RNA and possible errors.
In bacteriatranscription is carried out by a single type of RNA polymerase, which needs to bind a DNA sequence called a Pribnow box with the help of the sigma factor
protein (σ factor) to start transcription. In eukaryotes, transcription
is performed in the nucleus by three types of RNA polymerases, each of
which needs a special DNA sequence called the promoter and a set of DNA-binding proteins—transcription factors—to initiate the process (see regulation of transcription below). RNA polymerase I is responsible for transcription of ribosomal RNA (rRNA) genes. RNA polymerase II (Pol II) transcribes all protein-coding genes but also some non-coding RNAs (e.g., snRNAs, snoRNAs or long non-coding RNAs). RNA polymerase III transcribes 5S rRNA, transfer RNA (tRNA) genes, and some small non-coding RNAs (e.g., 7SK). Transcription ends when the polymerase encounters a sequence called the terminator.
While transcription of prokaryotic protein-coding genes creates messenger RNA (mRNA) that is ready for translation into protein, transcription of eukaryotic genes leaves a primary transcript
of RNA (pre-RNA), which first has to undergo a series of modifications
to become a mature RNA. Types and steps involved in the maturation
processes vary between coding and non-coding preRNAs; i.e. even though preRNA molecules for both mRNA and tRNA undergo splicing, the steps and machinery involved are different. The processing of non-coding RNA is described below (non-coding RNA maturation).
The processing of pre-mRNA include 5′ capping, which is set of enzymatic reactions that add 7-methylguanosine (m7G) to the 5′ end of pre-mRNA and thus protect the RNA from degradation by exonucleases. The m7G cap is then bound by cap binding complex heterodimer (CBP20/CBP80), which aids in mRNA export to cytoplasm and also protect the RNA from decapping.
Another modification is 3′ cleavage and polyadenylation. They occur if polyadenylation signal sequence (5′- AAUAAA-3′) is
present in pre-mRNA, which is usually between protein-coding sequence
and terminator. The pre-mRNA is first cleaved and then a series of ~200 adenines (A)
are added to form poly(A) tail, which protects the RNA from degradation. The poly(A) tail is bound by multiple poly(A)-binding proteins (PABPs) necessary for mRNA export and translation re-initiation. In the inverse process of deadenylation, poly(A) tails are shortened by the CCR4-Not 3′-5′ exonuclease, which often leads to full transcript decay.
Illustration
of exons and introns in pre-mRNA and the formation of mature mRNA by
splicing. The UTRs (in green) are non-coding parts of exons at the ends
of the mRNA.
A very important modification of eukaryotic pre-mRNA is RNA splicing. The majority of eukaryotic pre-mRNAs consist of alternating segments called exons and introns. During the process of splicing, an RNA-protein catalytical complex known as spliceosome catalyzes two transesterification reactions, which remove an intron and release it in form of lariat structure, and then splice neighbouring exons together. In certain cases, some introns or exons can be either removed or retained in mature mRNA. This so-called alternative splicing
creates series of different transcripts originating from a single gene.
Because these transcripts can be potentially translated into different
proteins, splicing extends the complexity of eukaryotic gene expression
and the size of a species proteome.
Extensive RNA processing may be an evolutionary advantage
made possible by the nucleus of eukaryotes. In prokaryotes,
transcription and translation happen together, whilst in eukaryotes, the
nuclear membrane separates the two processes, giving time for RNA processing to occur.
In most organisms non-coding genes (ncRNA)
are transcribed as precursors that undergo further processing. In the
case of ribosomal RNAs (rRNA), they are often transcribed as a pre-rRNA
that contains one or more rRNAs. The pre-rRNA is cleaved and modified (2′-O-methylation and pseudouridine
formation) at specific sites by approximately 150 different small
nucleolus-restricted RNA species, called snoRNAs. SnoRNAs associate with
proteins, forming snoRNPs. While snoRNA part basepair with the target
RNA and thus position the modification at a precise site, the protein
part performs the catalytical reaction. In eukaryotes, in particular a
snoRNP called RNase, MRP cleaves the 45S pre-rRNA into the 28S, 5.8S, and 18S rRNAs. The rRNA and RNA processing factors form large aggregates called the nucleolus.
In the case of transfer RNA (tRNA), for example, the 5′ sequence is removed by RNase P, whereas the 3′ end is removed by the tRNase Z enzyme and the non-templated 3′ CCA tail is added by a nucleotidyl transferase. In the case of micro RNA (miRNA),
miRNAs are first transcribed as primary transcripts or pri-miRNA with a
cap and poly-A tail and processed to short, 70-nucleotide stem-loop
structures known as pre-miRNA in the cell nucleus by the enzymes Drosha and Pasha. After being exported, it is then processed to mature miRNAs in the cytoplasm by interaction with the endonuclease Dicer, which also initiates the formation of the RNA-induced silencing complex (RISC), composed of the Argonaute protein.
Even snRNAs and snoRNAs themselves undergo series of modification before they become part of functional RNP complex. This is done either in the nucleoplasm or in the specialized compartments called Cajal bodies. Their bases are methylated or pseudouridinilated by a group of small Cajal body-specific RNAs (scaRNAs), which are structurally similar to snoRNAs.
For some non-coding RNA, the mature RNA is the final gene product. In the case of messenger RNA (mRNA) the RNA is an information carrier
coding for the synthesis of one or more proteins. mRNA carrying a single
protein sequence (common in eukaryotes) is monocistronic whilst mRNA carrying multiple protein sequences (common in prokaryotes) is known as polycistronic.
During
the translation, tRNA charged with amino acid enters the ribosome and
aligns with the correct mRNA triplet. Ribosome then adds amino acid to
growing protein chain.
Every mRNA consists of three parts: a 5′ untranslated region (5′UTR), a protein-coding region or open reading frame (ORF), and a 3′ untranslated region (3′UTR). The coding region carries information for protein synthesis encoded by the genetic code to form triplets. Each triplet of nucleotides of the coding region is called a codon
and corresponds to a binding site complementary to an anticodon triplet
in transfer RNA. Transfer RNAs with the same anticodon sequence always
carry an identical type of amino acid. Amino acids are then chained together by the ribosome
according to the order of triplets in the coding region. The ribosome
helps transfer RNA to bind to messenger RNA and takes the amino acid
from each transfer RNA and makes a structure-less protein out of it. Each mRNA molecule is translated into many protein molecules, on average ~2800 in mammals.
In prokaryotes translation generally occurs at the point of
transcription (co-transcriptionally), often using a messenger RNA that
is still in the process of being created. In eukaryotes translation can
occur in a variety of regions of the cell depending on where the protein
being written is supposed to be. Major locations are the cytoplasm for soluble cytoplasmic proteins and the membrane of the endoplasmic reticulum for proteins that are for export from the cell or insertion into a cell membrane.
Proteins that are supposed to be produced at the endoplasmic reticulum
are recognised part-way through the translation process. This is
governed by the signal recognition particle—a protein that binds to the ribosome and directs it to the endoplasmic reticulum when it finds a signal peptide on the growing (nascent) amino acid chain.
The patchy colours of a tortoiseshell cat are the result of different levels of expression of pigmentation genes in different areas of the skin.
Regulation of gene expression is the control of the amount and timing
of appearance of the functional product of a gene. Control of
expression is vital to allow a cell to produce the gene products it
needs when it needs them; in turn, this gives cells the flexibility to
adapt to a variable environment, external signals, damage to the cell,
and other stimuli. More generally, gene regulation gives the cell
control over all structure and function, and is the basis for cellular differentiation, morphogenesis and the versatility and adaptability of any organism.
Numerous terms are used to describe types of genes depending on how they are regulated; these include:
A constitutive gene is a gene that is transcribed continually as opposed to a facultative gene, which is only transcribed when needed.
A housekeeping gene
is a gene that is required to maintain basic cellular function and so
is typically expressed in all cell types of an organism. Examples
include actin, GAPDH and ubiquitin.
Some housekeeping genes are transcribed at a relatively constant rate
and these genes can be used as a reference point in experiments to
measure the expression rates of other genes.
A facultative gene is a gene only transcribed when needed as opposed to a constitutive gene.
An inducible gene is a gene whose expression is either responsive to environmental change or dependent on the position in the cell cycle.
Any step of gene expression may be modulated, from the DNA-RNA transcription step to post-translational modification
of a protein. The stability of the final gene product, whether it is
RNA or protein, also contributes to the expression level of the gene—an
unstable product results in a low expression level. In general gene
expression is regulated through changes in the number and type of interactions between molecules that collectively influence transcription of DNA and translation of RNA.
Some simple examples of where gene expression is important are:
When
lactose is present in a prokaryote, it acts as an inducer and
inactivates the repressor so that the genes for lactose metabolism can
be transcribed.
Regulation of transcription
can be broken down into three main routes of influence; genetic (direct
interaction of a control factor with the gene), modulation interaction
of a control factor with the transcription machinery and epigenetic
(non-sequence changes in DNA structure that influence transcription).
The lambda repressor transcription factor (green) binds as a dimer to major groove of DNA target (red and blue) and disables initiation of transcription. From PDB: 1LMB.
Direct interaction with DNA is the simplest and the most direct method by which a protein changes transcription levels. Genes often have several protein binding sites around the coding region with the specific function of regulating transcription. There are many classes of regulatory DNA binding sites known as enhancers, insulators and silencers. The mechanisms for regulating transcription are varied, from blocking key binding sites on the DNA for RNA polymerase to acting as an activator and promoting transcription by assisting RNA polymerase binding.
The activity of transcription factors is further modulated by
intracellular signals causing protein post-translational modification
including phosphorylation, acetylation, or glycosylation. These changes influence a transcription factor's ability to bind,
directly or indirectly, to promoter DNA, to recruit RNA polymerase, or
to favor elongation of a newly synthesized RNA molecule.
The nuclear membrane in eukaryotes allows further regulation of
transcription factors by the duration of their presence in the nucleus,
which is regulated by reversible changes in their structure and by
binding of other proteins. Environmental stimuli or endocrine signals may cause modification of regulatory proteins eliciting cascades of intracellular signals, which result in regulation of gene expression.
It has become apparent that there is a significant influence of non-DNA-sequence specific effects on transcription. These effects are referred to as epigenetic and involve the higher order structure of DNA, non-sequence specific DNA binding proteins and chemical modification of DNA. In general epigenetic effects alter the accessibility of DNA to proteins and so modulate transcription.
In eukaryotes, DNA is organized in form of nucleosomes. Note how the DNA (blue and green) is tightly wrapped around the protein core made of histoneoctamer (ribbon coils), restricting access to the DNA. From PDB: 1KX5.
In eukaryotes the structure of chromatin, controlled by the histone code, regulates access to DNA with significant impacts on the expression of genes in euchromatin and heterochromatin areas.
Enhancers, transcription factors, mediator complex and DNA loops
Regulation of transcription in mammals. An active enhancer regulatory region is enabled to interact with the promoter region of its target gene by formation of a chromosome loop. This can initiate messenger RNA (mRNA) synthesis by RNA polymerase II (RNAP II) bound to the promoter at the transcription start site
of the gene. The loop is stabilized by one architectural protein
anchored to the enhancer and one anchored to the promoter and these
proteins are joined to form a dimer (red zigzags). Specific regulatory transcription factors
bind to DNA sequence motifs on the enhancer. General transcription
factors bind to the promoter. When a transcription factor is activated
by a signal (here indicated as phosphorylation
shown by a small red star on a transcription factor on the enhancer)
the enhancer is activated and can now activate its target promoter. The
active enhancer is transcribed on each strand of DNA in opposite
directions by bound RNAP IIs. Mediator proteins (a complex consisting of
about 26 proteins in an interacting structure) communicate regulatory
signals from the enhancer DNA-bound transcription factors to the
promoter.
Enhancers
are genome regions that regulate genes. Enhancers control
cell-type-specific gene expression programs, most often by looping
through long distances to come in physical proximity with the promoters
of their target genes. Multiple enhancers, each often tens or hundred of thousands of
nucleotides distant from their target genes, loop to their target gene
promoters and coordinate with each other to control gene expression.
The illustration shows an enhancer looping around to come into
proximity with the promoter of a target gene. The loop is stabilized by a
dimer of a connector protein (e.g. dimer of CTCF or YY1).
One member of the dimer is anchored to its binding motif on the
enhancer and the other member is anchored to its binding motif on the
promoter (represented by the red zigzags in the illustration). Several cell function-specific transcription factors (among the about 1,600 transcription factors in a human cell) generally bind to specific motifs on an enhancer. A small combination of these enhancer-bound transcription factors, when
brought close to a promoter by a DNA loop, govern transcription level
of the target gene. Mediator (a complex usually consisting of about 26
proteins in an interacting structure) communicates regulatory signals
from enhancer DNA-bound transcription factors directly to the RNA
polymerase II (pol II) enzyme bound to the promoter.
Enhancers, when active, are generally transcribed from both
strands of DNA with RNA polymerases acting in two different directions,
producing two eRNAs as illustrated in the figure. An inactive enhancer may be bound by an inactive transcription factor.
Phosphorylation of the transcription factor may activate it and that
activated transcription factor may then activate the enhancer to which
it is bound (see small red star representing phosphorylation of
transcription factor bound to enhancer in the illustration). An activated enhancer begins transcription of its RNA before activating transcription of messenger RNA from its target gene.
DNA methylation and demethylation
DNA methylation is the addition of a methyl group to the DNA that happens at cytosine.
The image shows a cytosine single ring base and a methyl group added on
to the 5 carbon. In mammals, DNA methylation occurs almost exclusively
at a cytosine that is followed by a guanine.
DNA methylation is a widespread mechanism for epigenetic influence on gene expression and is seen in bacteria and eukaryotes
and has roles in heritable transcription silencing and transcription
regulation. Methylation most often occurs on a cytosine (see Figure).
Methylation of cytosine primarily occurs in dinucleotide sequences where
a cytosine is followed by a guanine, a CpG site. The number of CpG sites in the human genome is about 28 million. Depending on the type of cell, about 70% of the CpG sites have a methylated cytosine.
Methylation of cytosine in DNA has a major role in regulating
gene expression. Methylation of CpGs in a promoter region of a gene
usually represses gene transcription while methylation of CpGs in the body of a gene increases expression. TET enzymes play a central role in demethylation of methylated cytosines. Demethylation of CpGs in a gene promoter by TET enzyme activity increases transcription of the gene.
In eukaryotes, where export of RNA is required before translation is
possible, nuclear export is thought to provide additional control over
gene expression. All transport in and out of the nucleus is via the nuclear pore and transport is controlled by a wide range of importin and exportin proteins.
Expression of a gene coding for a protein is only possible if the
messenger RNA carrying the code survives long enough to be translated. In a typical cell, an RNA molecule is only stable if specifically protected from degradation. RNA degradation has particular importance in regulation of expression
in eukaryotic cells where mRNA has to travel significant distances
before being translated. In eukaryotes, RNA is stabilised by certain post-transcriptional modifications, particularly the 5′ cap and poly-adenylated tail.
Intentional degradation of mRNA is used not just as a defence
mechanism from foreign RNA (normally from viruses) but also as a route
of mRNA destabilisation. If an mRNA molecule has a complementary sequence to a small interfering RNA then it is targeted for destruction via the RNA interference pathway.
Three prime untranslated regions (3′UTRs) of messenger RNAs
(mRNAs) often contain regulatory sequences that post-transcriptionally
influence gene expression. Such 3′-UTRs often contain both binding sites
for microRNAs (miRNAs) as well as for regulatory proteins. By binding to specific sites within the 3′-UTR, miRNAs can decrease
gene expression of various mRNAs by either inhibiting translation or
directly causing degradation of the transcript. The 3′-UTR also may have silencer regions that bind repressor proteins that inhibit the expression of a mRNA.
The 3′-UTR often contains microRNA response elements (MREs).
MREs are sequences to which miRNAs bind. These are prevalent motifs
within 3′-UTRs. Among all regulatory motifs within the 3′-UTRs (e.g.
including silencer regions), MREs make up about half of the motifs.
As of 2014, the miRBase web site, an archive of miRNAsequences
and annotations, listed 28,645 entries in 233 biologic species. Of
these, 1,881 miRNAs were in annotated human miRNA loci. miRNAs were
predicted to have an average of about four hundred target mRNAs (affecting expression of several hundred genes). Friedman et al. estimate that >45,000 miRNA target sites within human mRNA 3′UTRs
are conserved above background levels, and >60% of human
protein-coding genes have been under selective pressure to maintain
pairing to miRNAs.
Direct experiments show that a single miRNA can reduce the stability of hundreds of unique mRNAs. Other experiments show that a single miRNA may repress the production
of hundreds of proteins, but that this repression often is relatively
mild (less than 2-fold).
The effects of miRNA dysregulation of gene expression seem to be important in cancer. For instance, in gastrointestinal cancers, nine miRNAs have been identified as epigenetically altered and effective in down regulating DNA repair enzymes.
The effects of miRNA dysregulation of gene expression also seem
to be important in neuropsychiatric disorders, such as schizophrenia,
bipolar disorder, major depression, Parkinson's disease, Alzheimer's
disease and autism spectrum disorders.
Translational
Neomycin
is an example of a small molecule that reduces expression of all
protein genes inevitably leading to cell death; it thus acts as an antibiotic.
Direct regulation of translation is less prevalent than control of transcription or mRNA stability but is occasionally used. Inhibition of protein translation is a major target for toxins and antibiotics, so they can kill a cell by overriding its normal gene expression control. Protein synthesis inhibitors include the antibiotic neomycin and the toxin ricin.
Post-translational modifications (PTMs) are covalent
modifications to proteins. Like RNA splicing, they help to
significantly diversify the proteome. These modifications are usually
catalyzed by enzymes. Additionally, processes like covalent additions to
amino acid side chain residues can often be reversed by other enzymes.
However, some, like the proteolytic cleavage of the protein backbone, are irreversible.
PTMs play many important roles in the cell. For example, phosphorylation is primarily involved in activating and deactivating proteins and in signaling pathways. PTMs are involved in transcriptional regulation: an important function
of acetylation and methylation is histone tail modification, which
alters how accessible DNA is for transcription. They can also be seen in the immune system, where glycosylation plays a key role. One type of PTM can initiate another type of PTM, as can be seen in how ubiquitination tags proteins for degradation through proteolysis. Proteolysis, other than being involved in breaking down proteins, is
also important in activating and deactivating them, and in regulating
biological processes such as DNA transcription and cell death.
Measurement
Schematic karyogram of a human, showing an overview of the expression of the human genome using G banding, which is a method that includes Giemsa staining, wherein the lighter staining regions are generally more transcriptionally active, whereas darker regions are more inactive.
Measuring gene expression is an important part of many life sciences,
as the ability to quantify the level at which a particular gene is
expressed within a cell, tissue or organism can provide a lot of
valuable information. For example, measuring gene expression can:
Identify viral infection of a cell (viral protein expression).
Determine an individual's susceptibility to cancer (oncogene expression).
Similarly, the analysis of the location of protein expression is a
powerful tool, and this can be done on an organismal or cellular scale.
Investigation of localization is particularly important for the study of
development
in multicellular organisms and as an indicator of protein function in
single cells. Ideally, measurement of expression is done by detecting
the final gene product (for many genes, this is the protein); however,
it is often easier to detect one of the precursors, typically mRNA and to infer gene-expression levels from these measurements.
mRNA quantification
Levels of mRNA can be quantitatively measured by northern blotting, which provides size and sequence information about the mRNA molecules. A sample of RNA is separated on an agarose gel and hybridized to a radioactively labeled RNA probe that is complementary to the target sequence. The radiolabeled RNA is then detected by an autoradiograph. Because the use of radioactive reagents makes the procedure
time-consuming and potentially dangerous, alternative labeling and
detection methods, such as digoxigenin and biotin chemistries, have been
developed. Perceived disadvantages of Northern blotting are that large quantities
of RNA are required and that quantification may not be completely
accurate, as it involves measuring band strength in an image of a gel. On the other hand, the additional mRNA size information from the
Northern blot allows the discrimination of alternately spliced
transcripts.
Another approach for measuring mRNA abundance is RT-qPCR. In this technique, reverse transcription is followed by quantitative PCR. Reverse transcription first generates a DNA template from the mRNA; this single-stranded template is called cDNA. The cDNA template is then amplified in the quantitative step, during which the fluorescence emitted by labeled hybridization probes or intercalating dyes changes as the DNA amplification process progresses. With a carefully constructed standard curve, qPCR can produce an
absolute measurement of the number of copies of original mRNA, typically
in units of copies per nanolitre of homogenized tissue or copies per
cell. qPCR is very sensitive (detection of a single mRNA molecule is
theoretically possible), but can be expensive depending on the type of
reporter used; fluorescently labeled oligonucleotide probes are more
expensive than non-specific intercalating fluorescent dyes.
For expression profiling, or high-throughput analysis of many genes within a sample, quantitative PCR may be performed for hundreds of genes simultaneously in the case of low-density arrays. A second approach is the hybridization microarray.
A single array or "chip" may contain probes to determine transcript
levels for every known gene in the genome of one or more organisms. Alternatively, "tag based" technologies like Serial analysis of gene expression (SAGE) and RNA-Seq, which can provide a relative measure of the cellular concentration of different mRNAs, can be used. An advantage of tag-based methods is the "open architecture", allowing
for the exact measurement of any transcript, with a known or unknown
sequence. Next-generation sequencing (NGS) such as RNA-Seq
is another approach, producing vast quantities of sequence data that
can be matched to a reference genome. Although NGS is comparatively
time-consuming, expensive, and resource-intensive, it can identify single-nucleotide polymorphisms,
splice-variants, and novel genes, and can also be used to profile
expression in organisms for which little or no sequence information is
available.
Protein quantification
For genes encoding proteins, the expression level can be directly
assessed by a number of methods with some clear analogies to the
techniques for mRNA quantification.
One of the most commonly used methods is to perform a Western blot against the protein of interest. This gives information on the size of the protein in addition to its identity. A sample (often cellular lysate) is separated on a polyacrylamide gel, transferred to a membrane and then probed with an antibody to the protein of interest. The antibody can either be conjugated to a fluorophore or to horseradish peroxidase
for imaging and/or quantification. The gel-based nature of this assay
makes quantification less accurate, but it has the advantage of being
able to identify later modifications to the protein, for example
proteolysis or ubiquitination, from changes in size.
mRNA-protein correlation
While transcription directly reflects gene expression, the copy
number of mRNA molecules does not directly correlate with the number of
protein molecules translated from mRNA. Quantification of both protein
and mRNA permits a correlation of the two levels. Regulation on each
step of gene expression can impact the correlation, as shown for
regulation of translation or protein stability. Post-translational factors, such as protein transport in highly polar cells, can influence the measured mRNA-protein correlation as well.
In situ-hybridization of Drosophilaembryos at different developmental stages for the mRNA responsible for the expression of hunchback. High intensity of blue color marks places with high hunchback mRNA quantity.
Analysis of expression is not limited to quantification; localization
can also be determined. mRNA can be detected with a suitably labelled
complementary mRNA strand and protein can be detected via labelled
antibodies. The probed sample is then observed by microscopy to identify
where the mRNA or protein is.
The three-dimensional structure of green fluorescent protein.
The residues in the centre of the "barrel" are responsible for
production of green light after exposing to higher energetic blue light.
From PDB: 1EMA.
By replacing the gene with a new version fused to a green fluorescent protein marker or similar, expression may be directly quantified in live cells. This is done by imaging using a fluorescence microscope.
It is very difficult to clone a GFP-fused protein into its native
location in the genome without affecting expression levels, so this
method often cannot be used to measure endogenous gene expression. It
is, however, widely used to measure the expression of a gene
artificially introduced into the cell, for example via an expression vector.
By fusing a target protein to a fluorescent reporter, the protein's
behavior, including its cellular localization and expression level, can
be significantly changed.
The enzyme-linked immunosorbent assay works by using antibodies immobilised on a microtiter plate
to capture proteins of interest from samples added to the well. Using a
detection antibody conjugated to an enzyme or fluorophore the quantity
of bound protein can be accurately measured by fluorometric or colourimetric
detection. The detection process is very similar to that of a Western
blot, but by avoiding the gel steps more accurate quantification can be
achieved.
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