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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

Bias of dinucleotide frequencies observed in species of different complexity. Mutational biases CA/AC (a), AT/TA (b), AG/GA (c), GC/CG (d). Examples of sequences and their frequencies in human cDNA comprising a random collection of low-frequency (e) or high-frequency dinucleotides are shown (f). Horizontal lines represent ratio 1:1, i.e., no bias. Error bars are contained in data points and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus), Hs (Homo sapiens)
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Fig1: Bias of dinucleotide frequencies observed in species of different complexity. Mutational biases CA/AC (a), AT/TA (b), AG/GA (c), GC/CG (d). Examples of sequences and their frequencies in human cDNA comprising a random collection of low-frequency (e) or high-frequency dinucleotides are shown (f). Horizontal lines represent ratio 1:1, i.e., no bias. Error bars are contained in data points and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus), Hs (Homo sapiens)

Mentions: Many interactions between genes involve sequence-specific regulation of promoters, transcripts or proteins [21, 22]. The nucleotide distribution in the sequences of organisms of different complexity is important for understanding how the different layers of regulation are recruited. In Fig. 1, we can observe changes in the dinucleotide frequencies observed in species of different complexity: Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus) and Hs (Homo sapiens). Some of these changes could reflect mutational biases that were revealed after the release of the pressure to bias codon composition to optimize translation proficiency. Others could correspond to new mutational biases. One such bias is the well-known high mutability and scarcity of CpGs in vertebrates [23]. Interestingly, also note the decrease in the TA/AT ratio from the lowest values, found in E. coli, to those in eukaryotes (TA, not AT, is present in two of three stop codons).Fig. 1


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)

Bias of dinucleotide frequencies observed in species of different complexity. Mutational biases CA/AC (a), AT/TA (b), AG/GA (c), GC/CG (d). Examples of sequences and their frequencies in human cDNA comprising a random collection of low-frequency (e) or high-frequency dinucleotides are shown (f). Horizontal lines represent ratio 1:1, i.e., no bias. Error bars are contained in data points and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. 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

Fig1: Bias of dinucleotide frequencies observed in species of different complexity. Mutational biases CA/AC (a), AT/TA (b), AG/GA (c), GC/CG (d). Examples of sequences and their frequencies in human cDNA comprising a random collection of low-frequency (e) or high-frequency dinucleotides are shown (f). Horizontal lines represent ratio 1:1, i.e., no bias. Error bars are contained in data points and represent 95 % confidence intervals (binomial distributions) in comparison with random expectations. Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus), Hs (Homo sapiens)
Mentions: Many interactions between genes involve sequence-specific regulation of promoters, transcripts or proteins [21, 22]. The nucleotide distribution in the sequences of organisms of different complexity is important for understanding how the different layers of regulation are recruited. In Fig. 1, we can observe changes in the dinucleotide frequencies observed in species of different complexity: Ec (Escherichia coli CFT073), At (Arabidopsis thaliana), Ce (Caenorhabditis elegans), Dm (Drosophila melanogaster), Mm (Mus musculus) and Hs (Homo sapiens). Some of these changes could reflect mutational biases that were revealed after the release of the pressure to bias codon composition to optimize translation proficiency. Others could correspond to new mutational biases. One such bias is the well-known high mutability and scarcity of CpGs in vertebrates [23]. Interestingly, also note the decrease in the TA/AT ratio from the lowest values, found in E. coli, to those in eukaryotes (TA, not AT, is present in two of three stop codons).Fig. 1

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