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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

Increase in the variance of sequence interactivity in the human and mouse genomes. 3D plots of sequence frequency in cDNA relative to the length and relative interactivity (r. interactivity) measured as the percentage of high-frequency (CA, AT, GC, AG) vs low-frequency dinucleotides (AC, TA, CG, GA) show an increase in the variance of sequence interactivity in Mus musculus and Homo sapiens (e and f) in comparison with Escherichia coli (a), Arabidopsis thaliana(b), Caenorhabditis elegans(c) and Drosophyla melanogaster(d)
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Fig2: Increase in the variance of sequence interactivity in the human and mouse genomes. 3D plots of sequence frequency in cDNA relative to the length and relative interactivity (r. interactivity) measured as the percentage of high-frequency (CA, AT, GC, AG) vs low-frequency dinucleotides (AC, TA, CG, GA) show an increase in the variance of sequence interactivity in Mus musculus and Homo sapiens (e and f) in comparison with Escherichia coli (a), Arabidopsis thaliana(b), Caenorhabditis elegans(c) and Drosophyla melanogaster(d)

Mentions: Although Fig. 1 provides a good summary of how the nucleotide distribution varies with organism complexity, it provides substantially less information about how these asymmetries can affect the frequency distribution of longer sequences. Consequently, plots for the frequency of 10–16 nt sequences were constructed for each species by blasting sequences with different proportions of the most common dinucleotides against the cDNA of each species (Fig. 2). We can observe that these dinucleotide asymmetries can add up to striking increases in the frequency of longer sequences. Figure 2 also reveals how Mus musculus and Homo sapiens show an increased slope in sequence frequency depending on the nucleotide composition when compared with other organisms. Considering complementarity as the basis for interaction with regulatory elements, we could also describe this observation as an increase in the variance of sequence interactivity.Fig. 2


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)

Increase in the variance of sequence interactivity in the human and mouse genomes. 3D plots of sequence frequency in cDNA relative to the length and relative interactivity (r. interactivity) measured as the percentage of high-frequency (CA, AT, GC, AG) vs low-frequency dinucleotides (AC, TA, CG, GA) show an increase in the variance of sequence interactivity in Mus musculus and Homo sapiens (e and f) in comparison with Escherichia coli (a), Arabidopsis thaliana(b), Caenorhabditis elegans(c) and Drosophyla melanogaster(d)
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig2: Increase in the variance of sequence interactivity in the human and mouse genomes. 3D plots of sequence frequency in cDNA relative to the length and relative interactivity (r. interactivity) measured as the percentage of high-frequency (CA, AT, GC, AG) vs low-frequency dinucleotides (AC, TA, CG, GA) show an increase in the variance of sequence interactivity in Mus musculus and Homo sapiens (e and f) in comparison with Escherichia coli (a), Arabidopsis thaliana(b), Caenorhabditis elegans(c) and Drosophyla melanogaster(d)
Mentions: Although Fig. 1 provides a good summary of how the nucleotide distribution varies with organism complexity, it provides substantially less information about how these asymmetries can affect the frequency distribution of longer sequences. Consequently, plots for the frequency of 10–16 nt sequences were constructed for each species by blasting sequences with different proportions of the most common dinucleotides against the cDNA of each species (Fig. 2). We can observe that these dinucleotide asymmetries can add up to striking increases in the frequency of longer sequences. Figure 2 also reveals how Mus musculus and Homo sapiens show an increased slope in sequence frequency depending on the nucleotide composition when compared with other organisms. Considering complementarity as the basis for interaction with regulatory elements, we could also describe this observation as an increase in the variance of sequence interactivity.Fig. 2

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