Transcriptional and translational mechanisms diversifying the proteome

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EDUKACJA BIOLOGICZNA I ŚRODOWISKOWA | ebis.ibe.edu.pl | ebis@ibe.edu.pl | © for the article by the Authors 2016 © for the edition by Instytut Badań Edukacyjnych 2016

Transcriptional and

translational mechanisms

diversifying the proteome

Anna Dawid

Summary:

Results of genome sequencing show a surprising lack of a clear dependence between the number of genes and the organisms’ level of complexity. Moreover, along with pro-teomic data they indicate substantial disparity between the number of proteins and genes in Eukaryota. The reso-lution of this conundrum, along with post-translational modifications, may lie in mechanisms diversifying the proteome. Here, along with the most often cited examples such as alternative splicing, transcription initiation and termination, less common phenomena are described: RNA recoding, RNA editing, alternative translation ini-tiation, and STOP codon readthrough.

Key words: alternative splicing, alternative promoters,

read-through

Introduction

The more a particular scientific field is explored by an enthusiast, the more simplifications and concealments given by teachers in elementary, middle, and high schools can be noticed. One of such reductions is an extremely popular “one gene – one protein” scheme. A gene is rep-resented there as a DNA segment flanked by a promoter from 5’ end and a terminator from 3’ end, that can be transcribed into linear single messenger RNA molecule (mRNA), which in turn poses a matrix in the

transla-tion process that is in synthesising a protein coded by an original gene. In Eukaryota, whose genes are not con-tinuous as prokaryotic ones but consist of both coding (exons) and non-coding (introns) regions, there is also a splicing process where introns from immature mRNA molecule (pre-mRNA) are removed and exons are put together forming final, mature mRNA. This molecule will be equipped with the 5’ cap and 3’ poly(A) tail and transported from the cell nucleus to the cytoplasm.

This picture is definitely incomplete what is quite visible when taking following facts into account. First,

received: 16.01.2016; accepted: 4.03.2016; published: 1.04.2016

Anna Dawid: Bachelor’s degrees in Biotechnology and

Chemistry (obtained accordingly in the Faculty of Bio-logy and Faculty of Chemistry at University of Warsaw), currently a student of the second cycle of chemistry and physics in the College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences UW. Affiliation: MISMaP College UW and Faculty of Biology UW

Fig. 1. C-values for chosen groups of organisms (pg of DNA contained in haploid cell nucleus)

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there is no perfect correlation between the number of genes and the organisms’ complexity level. Secondly, in Eukaryota there is a huge disparity between the number of genes and the number of proteins. It indicates an ex-istence of mechanisms vastly diversifying the proteome in relation to the genome. They act on different levels of the transcription and translation, and the aim of this paper is to present them along with examples of gene-protein pathways where they occur, with limitation to Eukaryota. Moreover, this article will not describe post-translational modifications (such as phosphorylation and glycosylation) that also diversify the proteome.

Historical outline

From the middle of 19th and till the middle of the 20th century proteins were considered the most impor-tant components of the cell. Even the name itself indi-cates it, as it comes from a Greek word “proteios” mean-ing “primary”, “major”. In 1869 Friedrich Miescher, 25-year-old Swiss physician, when doing research on leukocytes obtained from the pus from used bandages collected in the clinique located nearby, isolated from cell nuclei a substance containing significant amounts of nitrogen and phosphor, precipitating in an acid en-vironment, insoluble in water and sodium chloride, but soluble in sodium hydroxide and disodium phosphate. He correctly deduced that it could not be any known compound and called it “nuclein” – a term still pre-served in today’s name deoxyribonucleic acid (Dahm, 2005). This discovery was followed by numerous others and as a result, DNA stopped being treated as an ordi-nary molecule functioning probably as a nucleus phos-phor reservoir (as was hypothesised by Miescher till his death) and became a symbol of modern life sciences.

DNA amount (in contrary to proteins) in cells of all tissues is similar except for germ cells that have half as

much DNA as others. That is one of arguments support-ing the thesis of DNA as a hereditary material. Therefore, for every species so-called C-value can be determined that is DNA amount contained in haploid cell nucleus (usually expressed in pg or bp). Letter “C” (accord-ingly to the term’s author Hewson Swift) comes from “constant” (Gregory, 2005). It is logical to conclude that DNA amount is proportional to the number of genes that in turn should be proportional to the organism’s stage of evolutionary progress. This conclusion, how-ever, was demolished immediately when the compari-son of number of genes between more species became possible (Mirsky, 1951). It turned out there are plenty of cases of less complex organisms having significantly more DNA than more complex ones e.g. salamander’s C-value is over 70 times higher than chicken’s (Figure 1). In the 1970s term “C-value paradox” was formulated that embraced three curious facts:

• Some simple organisms have significantly more

DNA than more complicated ones.

• Genomes, understood as all DNA contained in

a single cell of the organism, accommodate more DNA than it would seem fit from the number of the organism’s genes.

• Some groups of morphogically similar organisms

have a huge dispersion of C-value.

The conclusion can be derived that DNA amount is not linearly correlated with the number of genes, what is paradoxical in a sense that a constant amount of DNA in cells was indeed an argument for DNA as a material containing genes. It is not paradoxical for us today, as we know that DNA does not contain only genes, even more, significant majority of the eukaryotic genome is non-coding. There were many mechanisms that led to accumulation of non-coding DNA such as spread-ing of transposons (“selfish” DNA), accumulation of pseudogenes (“junk” DNA), occurance of introns and

phenomena on the chromosomal level e.g. duplications (Gregory, 2001).

Although the C-value paradox has been partially explained (except for questions concerning the func-tion and origin of non-coding DNA), the comparison of the number of genes between species also gives supris-ing results. First of all, evolutionary advanced as well as morphologically and physiologically complicated eukaryotes, especially humans, have relatively small number of genes (Cooper, 2000). Earliest estimations of the human genome in the late 1960s indicated that it may consist of over 2 milions protein-coding genes (Kauffman, 1969). Over the years this number had been decreasing. In the early 1990s geneticists’ estimations favoured 100 000 genes (Pennisi, 2003) to determine in 21st century that Homo sapiens has only around 22 000 of them (Figure 2).

Proteomic research results were astonishing as well. In 2014 the paper was published that contained a sum-mary of up-to-date results of the analysis of the

hu-Fig. 2. The number of genes of chosen species

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man proteome. Investigation of 17 294 genes allowed to identify 30 057 proteins in total, built from 293 700 unique peptides (Kim et al., 2014), what gives almost 17 times more peptides than sequences that code them. To help with understanding these striking data, sci-entists turned to many studies conducted in lat 20-25 years that testify the existence of extraordinary mecha-nisms that allow to produce many proteins from one gene.

Mechanisms diversifying the genetic information

on the transcription level in Eukaryota

Alternative transcripts are a result of mechanisms such as alternative splicing, use of alternative promot-ers, alternative polyadenylation and RNA editing.

Alternative promoters

From 40 to 50% of genes is estimated to have alter-native promoters (APs), whose expression causes a pro-duction of transcripts with different 5’ ends originated from one gene (Landry, 2003). Research indicates that APs are used most abundantly in brain, heart and liver in embryonic and fetal stages and there is a strong cor-relation between use of APs and the organism’s develop-ment (Baek, 2007).

It is important to note that translation of mRNA transcribed with use of different APs still may result in the same protein if in spite of different 5’ ends, they have a common exon with translation initiation site (de-termined usually by the first codon ATG on the sense DNA strand), so the reading frame remains the same (Figure 3a). Such transcripts, however, can differ in tis-sue specificity, expression level or secondary structure of untranslated regions (UTR), what also can influence the transcript stability or translation initiation efficien-cy e.g. gene CYP19, which encodes aromatase P450

(es-In other cases, transcripts coming from different APs encode different proteins. It is possible when APs contain separate transcription initiation sites. Resulting proteins may differ in N-termini sequence (Figure 3b,i) trogen sythetase), contains tissue specific APs that are

used differently accordingly to the stage of development what allows of a regulation of CYP19 expression (Ka-mat, 2002).

Figure 1. Types and consequences of alternative transcription initiation. Own elaboration based on Landry et al. (2003)

(a) APs expression (black arrows) does not result in a new protein isoform because of the second

exon that is common for all translational options and that contains translation initiation site marked as ATG. Splicing (black lines) is marked in (a) and (b) only for two first exons (b) APs expression results in isoforms differing in (i) N-termini sequence (ii) N-termini length (c) Completely different proteins originate as a result of a reading frame change

Figure 1. APs of the dystrophin gene. From Brown (2009)

Fig. 3. Types and consequences of alternative transcription initiation

Source: own elaboration based on Landry et al., 2003. (a) APs expression (black arrows) does not result in a new protein isoform because of the second exon that is common for all translational options and that contains translation initiation site marked as ATG. Splicing (black lines) is marked in (a) and (b) only for two first exons. (b) APs expression results in isoforms differing in (i) N-termini sequence (ii) N-termini length. (c) Completely different proteins originate as a result of a reading frame change.

Fig 4. APs of the dystrophin gene

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exons from pre-mRNA are joined in different order (what may result e.g. in a change of product function) and when some introns get included to mRNA or some exons – excluded (what may have impact on translation intensity or mRNA stability). Around 95% of mamma-lian genes encode transcripts that are a subject of AS (Shabalina, 2014).

Five main events of AS can be distinguished: exon skipping (Figure 5a), use of alternative 5’ end and 3’ end exons (Figure 5b,c), introns retention (Figure 5d) and mutual exclusion of exons (Figure 5e). Also trans-AS was observed i.e. joining exons from different genes (not shown in the Figure 5). When analysing AS, exons get classified into two types: constitutive that almost always are included to mature mRNA and alternative that usu-ally are skipped.

Exon skipping accounts for almost 40% of AS cas-es in higher eukaryotcas-es and is very rare in lower oncas-es

(Keren et al., 2010). There are also a few interesting fea-tures of conserved alternative exons: shorter than con-stitutive ones, they have divisible by three number of base pairs what allows of maintaining the reading frame when the exon is skipped as well as when is included. Non-conserved alternative exons do not have these at-tributes (de Klerk and ‘t Hoen, 2015). Moreover, in hu-mans, exons flanked by longer introns are skipped more often (Keren et al., 2010). Alternative ends of the tran-script may occur when ending exons have more than one splice site. Such cases account for around 15% of AS. Intron retention takes place mainly in plants, fungi and protozoa, in H. sapiens only 2-5% of AS is retaining an intron, but with 252 243 introns in the human genome it can significantly influence the proteomic variety (Hubé and Francastel, 2015). It is still not completely clear how a spliceosome recognises alternative exons and choose between them.

or length (so-called ΔN isoform) (Figure 3b,ii) or be completely different as a result of a change of a reading frame (Figure 3c). APs expression in the gene of PPARγ protein leads to two protein isoforms differing in tissue specificity (Fajas et al., 1997). Transcription of one gene with use of different APs results in two proteins INK4A and ARF having distinct functions (Quelle et al., 1995). There is also an interesting example of ΔN isoform that comes from the AP expression, namely ΔNp73 isoform. p73 protein has a similar function to p53 i.e. takes part in stopping the cell cycle, apoptosis induction and acti-vation of genes encoding proteins that cooperate with it. ΔNp73 isoform, however, is a negative regulator of both p73 and p53. Evolutionary conservation of this AP between species suggest there is an advantage in expression of potentially oncogenic protein. Research indicates its presence is necessary to correct induction of the apoptosis by p53 and p75 (Pozniak et al., 2000).

Research conducted on single genes indicates that the choice of APs plays an important role during cell development and differentiation and mutations in these promoters lead to diseases including cancer, neuropsy-chiatrist and development disorders. The AP can be chosen in two ways: by changes in the chromatin and by cell regulation through tissue specific factors (de Klerk and ‘t Hoen, 2015). The typical example of the second mechanism is the dystrophin gene (Figure 4), distinc-tive also for being the longest known human gene (2.5 Mb, 1.5% of chromosome X length, 0.1% of the human genome). It consists of 79 exons and has many APs that are expressed depending on the tissue what results in different proteins with distinct functions.

Alternative splicing

Canonical splicing is removing introns (non-coding sequences) from pre-mRNA and joining exons (cod-ing sequences). Alternative splic(cod-ing (AS) occurs when

Figure 1. Alternative splicing. From Keren et al. (2010)

Exons are represented by rectangles (constitutive – blue, alternative – violet), introns by solid lines, dotted lines indicate splicing options

Fig. 5. Alternative splicing

Source: Keren et al., 2010.

Exons are represented by rectangles (constitutive – blue, alternative – violet), introns by solid lines, dotted lines indicate splicing options

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AS, among others, plays an important role in sex de-termination in Drosophila (Venables et al., 2012) and is the source of diversification of auditory predisposition between humans by generating a huge number of gene SLO transcripts in cochlear hair cells (Graveley, 2001). While AS is thought to be rather a rule that an excep-tion for human genes, it is not suprising that particular genes’ splicing disorders may cause genetic diseases. Best-characterised examples are spinal muscular atro-phy, myotonic dystroatro-phy, retinitis pigmentosa, Frasier syndrome, and hemophilia A (Ghigna et al., 2008).

Alternative polyadenylation

Use of alternative polyadenylation sites results in transcripts differing in 3’ end. If these sites lie in the exon (or in the intron included to mRNA in the pro-cess of AS), then transcripts differ in the coding region length. However, usually alternative polyadenylation accounts for different lengths of 3’-UTR what influences mRNA localization, stability, and translation efficiency but also makes alternative polyadenylation a process that does not significantly diversify the proteome (de Klerk and ‘t Hoen, 2015).

The example of generating the proteome variety by alternative polyadenylation is the using of alternative polyadenylation site in the intron 9 of the luc7l2 gene transcript in mice resulting in a shorter protein with different C-termini domain that occurs among others in brain, kidneys and stomach (Howell et al., 2o07).

RNA editing

RNA editing is the process of modifying the nucleo-tide sequence of RNA right after its synthesis. Despite the fact that it is relatively rare, it has been observed in many eukaryotic groups i.e. humans as well as protists (e.g. Trypanosoma) and plants (Brennicke et al., 1999). Phenomena described above as splicing, 5’ cap adding

and polyadenylation do not count as RNA editing, in-stead the definition covers such mechanisms as inser-tion, deletion and nitrogenous base change within edit-ed RNA. All types of RNA may be edit-editedit-ed, but obviously only modifications in mRNA can have impact on the amino acid sequence of the final protein.

The most popular example of this phenomenon is ed-iting of human apolipoprotein B mRNA (Figure 6). In liver this mRNA is a matrix for translation of 4563-amino acid protein called “apolipoprotein B100” (100 states for number of kDa) which is secreted into the bloodstream and takes part in the lipid transport. In the small intestine cells, however, this mRNA is edited by deamination of cytosine into uracil, what changes CAA codon (encod-ing a glutamine) into UAA i.e. STOP codon. It results in a shorter protein – apolipoprotein B48 (having only 48 kDa out of original 100) responsible for binding and resorbing fatty acids in the lining of the small intestine. The best known type of RNA editing is deamina-tion of adenosine into inosine catalysed by adenosine deaminases acting on RNA (ADAR) (Sacharczuk et al., 2004). The ADAR substrate is a double stranded RNA that can result from pairing intron and exon sequences before intron removal during splicing or from pairing mRNA with antisense RNA. Adenosine conversion into inosine was observed for the first time in the yeast’s tRNA. Inosine is interpreted by translation machinery as guanosine what is an effect of their chemical simi-larity. This conversion causes among others decrease of calcium flow in glutamate-gated channels because of an exchange of glutamine codon into arginine codon in mRNA encoding a subunit of glutamate receptor and drastic changes in efficiency of G protein binding by serotonine receptor.

RNA editing also plays a role in achieving immuno-globulin variety by modification of antibodies’ mRNA in B lymphocytes.

Translational mechanisms diversifying the

proteome

Human transcriptome contains over 80 000 pro-tein-coding transcripts, and estimated proteome size amounts between 250 000 and 1 000 000 polypeptides, excluding posttranslational modifications (de Klerk and ‘t Hoen, 2015). Therefore, in average, one transcript is a matrix for 3 – 13 proteins what suggests the signifi-cant scale of translational mechanisms that diversify the proteome i.e. alternative translation initiation and RNA recoding. The following processes count as RNA recoding: frameshifting, ribosome hopping, change of codon – amino acid recognition and readthrough.

Alternative translation initianion

In 1987 scientists had already known that mammalian translation may begin from the codon different than AUG e.g. ACG (Peabody, 1987) or CUG (Starck et al., 2012). The mechanism of choosing alternative translation initiation sites (alternative TISs) is still unclear, nevertheless it is thought to occur in two ways: dependent on the 5’ cap and independent of it (Wan and Qian, 2013). In the cap-dependent mechanism, the small ribosomal subunit along with many translation initiation factors is assembled on the 5’ cap structure, creating so-called “43 S pre-initiation complex”. Then, in an ATP-dependent process, it scans 5’ UTR to find a TIS, usually AUG codon and starts the translation. This mechanism is the most common in eu-karyots. In the second type of translation initiation, the more alternative one, the translation machinery starts in the site indicated by a specific mRNA secondary struc-ture (usually, but not always, in 5’ UTR) called “internal ribosome entry site” (IRES).

There are two possible consequences of choosing an alternative TIS in 5’ UTR in the context of creating the proteome diversification:

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Use of alternative TISs is common among animals (de Klerk and ‘t Hoen, 2015) and occurs both under stress and physiological conditions. 50%-65% of mRNA is estimated to have more than one TIS, and TISs in mammalian mRNA is being catalogued in TISdb (Translation Initiation Sites database) (Wan and Qian, 2013).

RNA recoding

More than 40 years ago scientists noted first indica-tions that the genetic code is not fully universal (Wein-er and Web(Wein-er, 1973 and Gesteland and Atkins, 1996). Different variants of the genetic code were observed in many organisms and it this case it means codon reas-signment in the entire genome of a species (or an or-ganellum) irrespective of a codon’s mRNA context (At-kins and Baranov, 2010).

Subsequent discoveries were even more mysterious. In 1980s, a shift of the reading frame during translation in E. coli was observed, and then a use of two non-ca-nonical amino acids, selenocysteine and pyrrolysine, in

the translation was noted. These phenomena are count-ed as RNA recoding i.e. the mechanism in which par-ticular nucleotide sequences influence the translational machinery what results in translational changes such as shift of the reading frame (“frameshifting”), redefini-tion of the codon, ribosome hopping (also: bypassing) and readthrough i.e. recognition of the STOP codon as a protein-coding one. The consequence of RNA recod-ing is change of amino acid sequence of a final protein. It is important to note that RNA recoding is a dynamic process regulated by many cell’s signals and in constant competition with the standard mRNA meaning (Atkins and Baranov, 2010).

Frameshifting

When the ribosome meets a frameshifting site, sig-nals coming usually from distant RNA regions can make it efficiently “skip” one or two nucleotides (+1 and +2) or “jump back” by one or two nucleotides (-1 and -2), what causes the reading frame change and synthesis of a new protein with amino acid sequence completely different

• If the translation starting from the alternative TIS

ends with the same STOP codon as the canonical one, the outcome is a protein that differs in N-terminal end from a protein being a result of the canonical translation.

• If an alternative TIS is in the different reading

fra-me than a primary open reading frafra-me (ORF), or if the alternative translation ends with the STOP co-don that is upstream in terms of the primary ORF, the outcome is a completely new protein.

What is more, ORFs that are entirely upstream in terms of the primary ORF (uORFs, Upstream Open Reading Frames) take part in regulating the gene ex-pression. Recognition of a TIS in the beginning of the uORF by the 43 S pre-initiation complex may result in stopping the ribosome in the elongation or termitaion stage on the uORF, blocking the access to the primary ORF for next ribosomes or even inducing mRNA de-cay, influencing directly the translation efficiency of the primary ORF (Medenbach et al., 2011 and Barbosa et al., 2013).

Fig. 6. Human

apolipoprotein B mRNA editing

Source: own elaboration based on Brown, 2009.

Fig. 7. Frameshifting in translation of ODC antizyme

Source: Ivanov et al., 2000.

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from the canonical one starting from the frameshifting site. +1 and -1 frameshifting occur in many species, but +2 and -2 have been described so far only in artificial test systems (Gesteland and Atkins, 1996).

A well-known example of this process is a frameshift-ing in translation of ornithine decarboxylase (ODC) an-tizyme (Manteuffel-Cymborowska, 1996). For the first time it was described as an ODC inhibitor whose activ-ity was increased by polyamines – compounds that are highly important in the organism (e.g. influence trans-lation rate and efficiency), but have toxic properties in bigger concentrations. ODC takes part in their biosyn-thesis. Cloning of a gene that encodes the antizyme in-dicated that its ORF did not contain the START codon. Instead, the translation is initiated in an uORF, which partially overlaps the primary ORF, in such a way that +1 frameshifting gives a functional antizyme (Ivanov et al., 2000). Further analysis allowed to state that frameshifting indeed took place and was stimulated by high concentration of polyamines in a cell (Figure 7). It means that antizyme synthesis is under a negative feed-back control – its synthesis leads to ODC inhibition and therefore to polyamine concetration decrease and lack of frameshifting stimulation which in turn causes an inhibition of antizyme synthesis. Frameshifting occurs widely in many species, from fungi to mammals, and is strongly evolutionarily conserved.

Incorporation of selenocysteine into polypeptyde chain

An unusual example of RNA recoding is incorpo-ration of selenocysteine (Sec) (Figure 8). Sec is called “the 21st amino acid” and is incorporated into poly-peptide chain during translation in archaea, bacte-ria and eukaryotes (Ivanov et al., 2000). To translate the STOP codon UGA (named opal) as a selecysteine, the following elements must be present (Copeland, 2003):

• cis elements in 3’ UTR mRNA with a stem-loop structure, called “selenocysteine insertion sequen-ce” (SECIS), assembled with SECIS-binding prote-in 2 (SBP2) prote-into a complex,

• tRNA with UCA anticodon and loaded with

sele-nocysteine (tRNASec

UCA), created as a result of

seri-ne modification in tRNASer

UCA catalysed by

seleno-cysteine synthase and consisting in selene transfer from selenophosphate to serine hydroxyl group,

• elongation factor eEFSec specific for this tRNA,

which determines the ability of translational

bin-ding of tRNASec_{to opal codon.}

Most selenoproteins play roles in redox reactions and in defense mechanisms against reactive oxygen species. Sec is in the active centre of such enzymes as glutathione peroxidase, iodothyronine deiodinases and thioredoxin reductase (Kryczyk and Zagrodzki, 2013).

Rybosome hopping (also: bypassing)

In a translational hopping, a ribosome “bypasses” some part of mRNA without insertion of any amino acid. It is sort of a translational splicing. A bypassed region always has a number of nucleotides divisible by three, so the ribosome hopping does not cause any shift of the reading frame. If a bypassed sequence is entire-ly coding, then a product is just shorter than one that would result from a canonical translation. If a bypassed region contains a STOP codon, a ribosome hopping causes translation of a sequence that so far was non-coding (Ivanov et al., 2000).

For many years the expression of the bacteriophage T4 gene 60 had been the only experimentally confirmed example of the ribosome hopping. Lately, however, common occurance of this phenomenon was confirmed in mitochondrial genes expression of the yeast Magnu-siomyces capitatus (Lang et al., 2014).

Readthrough

For the first time, a term “readthrough” was used probably in 1970s (Forget et al., 1975), and it is used to a phenomenon in which a termination signal coming from a STOP codon is ignored, and translation con-tinues in the same reading frame. It is still argued if readthrough is a translational error or a “programmed” process (Rospert et al., 2005; von der Haar and Tuite, 2007). Recognition of the opal codon as selenocysteine-coding is not counted as a readthrough because of com-pletely different mechanism of this phenomenon.

Most of what is known about the translation termi-nation and eukaryotic readthrough mechanism comes from research on yeasts, especially on Saccharomyces cerevisiae (von der Haar and Tuite, 2007).

Readthrough is an interaction between a STOP co-don and tRNA loaded with an amino acid that results in continuing the translation. The tRNA that inserts

Fig. 8. Complex that recognizes UGA codon as selenocysteine-coding

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the amino acid can be a cognate of the stop codon if this tRNA is a suppressor one, which arises by a point

mutation in the anticodon (e.g. tRNALys

UUC may mutate

to tRNALys

AUC and therefore recognise the amber codon

instead of a codon that codes lysine) and which, despite the mutation, is aminoacylated (what suggests that ami-noacylation specificity is determined by elements out-side the anticodon). Suppressor tRNAs occur naturally in eukaryots (Beier and Grimm, 2001). Alternatively, for certain ‘‘leaky’’ stop codon contexts (more frequent-ly subject to readthrough), a near-cognate tRNA can insert its cognate amino acid instead (Jungreis et al., 2011). Such a recognition results in an amino acid in-sertion instead of termination with level from 1 to 30% depending on promoting sequences’ occurance (Namy et al., 2001). During readthrough, usually glutamine, ty-rosine and lysine are inserted at UAA and UAG codons, whereas tryptophan, cysteine and arginine are inserted at UGA codon (Blanchet et al., 2014).

The readthrough effect is a synthesis of a poly-peptide with longer C-terminus. Consequences for the translational machinery depend on 3’ region of mRNA. If there is next STOP codon downstream the suppressed one, translation ends as usual. However, if the suppressed STOP codon is the only one in this par-ticular reading frame, a ribosome gets stuck in 3’ end of mRNA creating so-called “ribosome-nascent chain-mRNA complex” (RNC). Such chain-mRNA, which is trapped in RNC, can be recognised by Ski proteins in nonstop mRNA decay process leading to its degradation (Wu and Brewer, 2012).

For many years the readthrough was thought to play an unsignificant role in eukaryots, as it was experi-mentally observed only for six wild-type genes in three species: syn (Klagges et al., 1996), kelch (Robinson and Cooley, 1997) and hdc (Steneberg and Samakovlis, 2001) genes in Drosophila melanogaster, PDE2 and IMP3 genes

in S. cerevisiae (Namy et al., 2001, 2003) and β – globin gene in a rabbit. Last research indicates, however, that readthrough is relatively frequent in Drosophila and probably other arthropods (Jungreis et al., 2011). What is more, lately, scientists discovered that programmed readthrough in human cells was used to generate per-oxisomal isoforms of cytosolic enzymes (Stiebler et al., 2014) and that readthrough occurred in OPRK1, OPRL1, MAPK10 and AQP4 genes in a human (Loughran et al., 2014).

Conclusion

All described mechanisms increase coding potential of genomes, and with posttranslational modifications pose an answer to the question how it is possible that the proteome contains dozens of times more types of pro-teins than the genome has protein-coding genes. Their occurance also indicates that the number of genes and the evolutionary progress level along with physiological complexity do not have to be proportional. Discussed mechanisms could have arisen as a result of strong evolutionary pressure exerted on organisms with com-pact genomes such as viruses, and indeed, they occur in these organisms most commonly. In Eukaryota, ex-cept for increasing the coding potential of the genome, which seems to be mostly non-coding, these mecha-nisms give an opportunity to regulate a ratio between different proteins coded by the same gene on different levels of its expression.

Not so long ago the molecular biology seemed to be governed by a simple scheme “one gene – one protein”. It is obvious now, however, that the gene expression is far more complicated and richer in events than it was thought. Amazing complexity of the genetic informa-tion reading process may be suprising – why did the evolution favour decrease of the number of coding

se-quences and mechanisms diversifying the proteome, instead of using bigger part of the genome to code pro-teins? Too little is known about these mechanisms’ evo-lution and the role of non-coding DNA to determine the answer, but there are some clues suggesting that mechanisms increasing coding potential have at least one advantage, namely, greater possibility of their con-trol. They are sensitive to many regulation factors, often are tissue specific and change along with the organism’s development.

We live in a splendid era when the genomes’ and transcriptomes’ sequencing allows large-scale research on various biological mechanisms and comparing them between branches of the evolutionary tree. Publications of the genomes of human, S. cerevisiae, and many others vertebrates, invertebrates, yeasts, plants and protozoa as well as their transcriptomes give great opportunities to comparative genomics and transcriptome analyt-ics. Since the genetic code was broken in 1960s, huge progress has been made in understanding the genetic information decoding mechanisms and despite many questions left without answers, next discoveries hope-fully should explain at least part of them.

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