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Identification of sequences common to more than one therapeutic target to treat complex diseases: simulating the high variance in sequence interactivity evolved to modulate robust phenotypes.

Varela MA - BMC Genomics (2015)

Bottom Line: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect.The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes.The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

View Article: PubMed Central - PubMed

Affiliation: Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road, Oxford, OX1 3QX, UK. miguel.varela@wikisequences.org.

ABSTRACT

Background: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect. In contrast, most therapies based on macromolecules like antibodies, antisense oligonucleotides or peptides focus on a single gene product. On the other hand, complex organisms seem to have a plethora of functional molecules able to bind specifically to multiple genes or genes products based on their sequences but the mechanisms that lead organisms to recruit these multispecific regulators remain unclear.

Results: The mutational biases inferred from the genomic sequences of six organisms show an increase in the variance of sequence interactivity in complex organisms. The high variance in the interactivity of sequences presents an ideal evolutionary substrate to recruit sequence-specific regulators able to target multiple gene products. For example, here it is shown how the 3'UTR can fluctuate between sequences likely to be complementary to other sites in the genome in the search for advantageous interactions. A library of nucleotide- and peptide-based tools was built using a script to search for candidates (e.g. peptides, antigens to raise antibodies or antisense oligonucleotides) to target sequences shared by key pathways in human disorders, such as cancer and immune diseases. This resource will be accessible to the community at www.wikisequences.org .

Conclusions: This study describes and encourages the adoption of the same multitarget strategy (e.g., miRNAs, Hsp90) that has evolved in organisms to modify complex traits to treat diseases with robust pathological phenotypes. The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes. The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

No MeSH data available.


Related in: MedlinePlus

High variance in the interactivity of sequences facilitates the recruitment of multispecific regulators. (a) Average ratio of dinucleotide frequencies with the same base composition observed in species of different complexities. (b) Human sequences in the 3’UTR have a very similar nucleotide composition to the rest of the genome in comparison with the 5’UTR, increasing the likelihood of interactions with other sequences by complementarity. (c) Relative proportion per nucleotide of the common nucleotide sequences targeting genes of therapeutic interest identified in this work (considering the average nucleotide size of the 5’UTR, coding sequence and 3’UTR as 200, 1340 and 800 bp, respectively). Error bars are contained in data points in (A) and (B) and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. Horizontal lines represent ratio 1:1, i.e., no bias. Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus), Hs (Homo sapiens)
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Fig3: High variance in the interactivity of sequences facilitates the recruitment of multispecific regulators. (a) Average ratio of dinucleotide frequencies with the same base composition observed in species of different complexities. (b) Human sequences in the 3’UTR have a very similar nucleotide composition to the rest of the genome in comparison with the 5’UTR, increasing the likelihood of interactions with other sequences by complementarity. (c) Relative proportion per nucleotide of the common nucleotide sequences targeting genes of therapeutic interest identified in this work (considering the average nucleotide size of the 5’UTR, coding sequence and 3’UTR as 200, 1340 and 800 bp, respectively). Error bars are contained in data points in (A) and (B) and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. Horizontal lines represent ratio 1:1, i.e., no bias. Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus), Hs (Homo sapiens)

Mentions: During the evolution of complexity, organisms have allowed or recruited mutational biases that have shaped the frequency of some of these sequences to the point of having combinations of nucleotides or amino acids that are rarely formed, whereas others act as attractors regardless of any direct selective pressure. For example, the frequencies of sequences in human cDNA comprising a random collection of low-frequency or high-frequency dinucleotides in human cDNA are shown in Fig. 1 (E and F, respectively). In Fig. 3a, it is shown how these asymmetries in the ratios of dinucleotide frequencies are especially evident in mouse and in human when compared with less complex species. In human genes the strength of the asymmetries increases gradually from 5’ to 3’ and is of similar strength in the 3’UTR as in the rest of the genome (Fig. 3b). Human sequences in the 3’UTR have a very similar dinucleotide composition to the rest of the genome in comparison with the 5’UTR, increasing the likelihood of interactions with other sequences by complementarity. The high variance in the interactivity of sequences could facilitate the adoption of sequence-specific regulators able to target multiple gene products. 3’UTR is also the main target of miRNAs and, interestingly, the distribution of the nucleotide sequences described in this study as having therapeutic potential for multitargeting also show a significant trend toward being more commonly located in the 3’UTR, with decreasing frequency approaching the 5’UTR (Fig. 3c).Fig. 3


Identification of sequences common to more than one therapeutic target to treat complex diseases: simulating the high variance in sequence interactivity evolved to modulate robust phenotypes.

Varela MA - BMC Genomics (2015)

High variance in the interactivity of sequences facilitates the recruitment of multispecific regulators. (a) Average ratio of dinucleotide frequencies with the same base composition observed in species of different complexities. (b) Human sequences in the 3’UTR have a very similar nucleotide composition to the rest of the genome in comparison with the 5’UTR, increasing the likelihood of interactions with other sequences by complementarity. (c) Relative proportion per nucleotide of the common nucleotide sequences targeting genes of therapeutic interest identified in this work (considering the average nucleotide size of the 5’UTR, coding sequence and 3’UTR as 200, 1340 and 800 bp, respectively). Error bars are contained in data points in (A) and (B) and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. Horizontal lines represent ratio 1:1, i.e., no bias. Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus), Hs (Homo sapiens)
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4506634&req=5

Fig3: High variance in the interactivity of sequences facilitates the recruitment of multispecific regulators. (a) Average ratio of dinucleotide frequencies with the same base composition observed in species of different complexities. (b) Human sequences in the 3’UTR have a very similar nucleotide composition to the rest of the genome in comparison with the 5’UTR, increasing the likelihood of interactions with other sequences by complementarity. (c) Relative proportion per nucleotide of the common nucleotide sequences targeting genes of therapeutic interest identified in this work (considering the average nucleotide size of the 5’UTR, coding sequence and 3’UTR as 200, 1340 and 800 bp, respectively). Error bars are contained in data points in (A) and (B) and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. Horizontal lines represent ratio 1:1, i.e., no bias. Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus), Hs (Homo sapiens)
Mentions: During the evolution of complexity, organisms have allowed or recruited mutational biases that have shaped the frequency of some of these sequences to the point of having combinations of nucleotides or amino acids that are rarely formed, whereas others act as attractors regardless of any direct selective pressure. For example, the frequencies of sequences in human cDNA comprising a random collection of low-frequency or high-frequency dinucleotides in human cDNA are shown in Fig. 1 (E and F, respectively). In Fig. 3a, it is shown how these asymmetries in the ratios of dinucleotide frequencies are especially evident in mouse and in human when compared with less complex species. In human genes the strength of the asymmetries increases gradually from 5’ to 3’ and is of similar strength in the 3’UTR as in the rest of the genome (Fig. 3b). Human sequences in the 3’UTR have a very similar dinucleotide composition to the rest of the genome in comparison with the 5’UTR, increasing the likelihood of interactions with other sequences by complementarity. The high variance in the interactivity of sequences could facilitate the adoption of sequence-specific regulators able to target multiple gene products. 3’UTR is also the main target of miRNAs and, interestingly, the distribution of the nucleotide sequences described in this study as having therapeutic potential for multitargeting also show a significant trend toward being more commonly located in the 3’UTR, with decreasing frequency approaching the 5’UTR (Fig. 3c).Fig. 3

Bottom Line: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect.The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes.The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

View Article: PubMed Central - PubMed

Affiliation: Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road, Oxford, OX1 3QX, UK. miguel.varela@wikisequences.org.

ABSTRACT

Background: Genome-wide association studies show that most human traits and diseases are caused by a combination of environmental and genetic causes, with each one of these having a relatively small effect. In contrast, most therapies based on macromolecules like antibodies, antisense oligonucleotides or peptides focus on a single gene product. On the other hand, complex organisms seem to have a plethora of functional molecules able to bind specifically to multiple genes or genes products based on their sequences but the mechanisms that lead organisms to recruit these multispecific regulators remain unclear.

Results: The mutational biases inferred from the genomic sequences of six organisms show an increase in the variance of sequence interactivity in complex organisms. The high variance in the interactivity of sequences presents an ideal evolutionary substrate to recruit sequence-specific regulators able to target multiple gene products. For example, here it is shown how the 3'UTR can fluctuate between sequences likely to be complementary to other sites in the genome in the search for advantageous interactions. A library of nucleotide- and peptide-based tools was built using a script to search for candidates (e.g. peptides, antigens to raise antibodies or antisense oligonucleotides) to target sequences shared by key pathways in human disorders, such as cancer and immune diseases. This resource will be accessible to the community at www.wikisequences.org .

Conclusions: This study describes and encourages the adoption of the same multitarget strategy (e.g., miRNAs, Hsp90) that has evolved in organisms to modify complex traits to treat diseases with robust pathological phenotypes. The increase in the variance of sequence interactivity detected in the human and mouse genomes when compared with less complex organisms could have expedited the evolution of regulators able to interact to multiple gene products and modulate robust phenotypes. The identification of sequences common to more than one therapeutic target carried out in this study could facilitate the design of new multispecific methods able to modify simultaneously key pathways to treat complex diseases.

No MeSH data available.


Related in: MedlinePlus