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Genome-Wide Detection and Analysis of Multifunctional Genes.

Pritykin Y, Ghersi D, Singh M - PLoS Comput. Biol. (2015)

Bottom Line: We also find that multifunctional genes are significantly more likely to be involved in human disorders.These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes.Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.

ABSTRACT
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms--H. sapiens, D. melanogaster, and S. cerevisiae--and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality.

No MeSH data available.


Related in: MedlinePlus

Multifunctional genes are more central in protein physical interaction networks.Boxplots of degree (number of interactions), betweenness centrality and participation coefficient of multifunctional and other annotated genes in the BioGRID protein physical interaction network are shown for (A) fly, (B) human, and (C) yeast. Colored dots show the means, notches show bootstrap-generated 95% confidence intervals around the medians, boxes show quartile ranges, and whiskers extend to the most extreme data points within 1.5 times the size of the inner quartile range. According to all three measures of centrality, multifunctional genes are significantly more central than other genes (Mann–Whitney U test).
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pcbi.1004467.g008: Multifunctional genes are more central in protein physical interaction networks.Boxplots of degree (number of interactions), betweenness centrality and participation coefficient of multifunctional and other annotated genes in the BioGRID protein physical interaction network are shown for (A) fly, (B) human, and (C) yeast. Colored dots show the means, notches show bootstrap-generated 95% confidence intervals around the medians, boxes show quartile ranges, and whiskers extend to the most extreme data points within 1.5 times the size of the inner quartile range. According to all three measures of centrality, multifunctional genes are significantly more central than other genes (Mann–Whitney U test).

Mentions: We observe that with respect to all three considered measures, multifunctional genes are significantly more central than other genes (p-values from 2e-13 to 3e-50, Mann–Whitney U; Fig 8). However, not surprisingly, degree is correlated with betweenness and participation (S6 Fig), and thus the correlation between multifunctionality and degree could potentially explain the correlation with the other two more complex measures. In order to test for this, we compare multifunctional and other annotated genes with respect to their betweenness and participation when controlling for degree distribution, and still observe that multifunctional genes have significantly larger betweenness and participation (S6 Fig and S2 Table).


Genome-Wide Detection and Analysis of Multifunctional Genes.

Pritykin Y, Ghersi D, Singh M - PLoS Comput. Biol. (2015)

Multifunctional genes are more central in protein physical interaction networks.Boxplots of degree (number of interactions), betweenness centrality and participation coefficient of multifunctional and other annotated genes in the BioGRID protein physical interaction network are shown for (A) fly, (B) human, and (C) yeast. Colored dots show the means, notches show bootstrap-generated 95% confidence intervals around the medians, boxes show quartile ranges, and whiskers extend to the most extreme data points within 1.5 times the size of the inner quartile range. According to all three measures of centrality, multifunctional genes are significantly more central than other genes (Mann–Whitney U test).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4593560&req=5

pcbi.1004467.g008: Multifunctional genes are more central in protein physical interaction networks.Boxplots of degree (number of interactions), betweenness centrality and participation coefficient of multifunctional and other annotated genes in the BioGRID protein physical interaction network are shown for (A) fly, (B) human, and (C) yeast. Colored dots show the means, notches show bootstrap-generated 95% confidence intervals around the medians, boxes show quartile ranges, and whiskers extend to the most extreme data points within 1.5 times the size of the inner quartile range. According to all three measures of centrality, multifunctional genes are significantly more central than other genes (Mann–Whitney U test).
Mentions: We observe that with respect to all three considered measures, multifunctional genes are significantly more central than other genes (p-values from 2e-13 to 3e-50, Mann–Whitney U; Fig 8). However, not surprisingly, degree is correlated with betweenness and participation (S6 Fig), and thus the correlation between multifunctionality and degree could potentially explain the correlation with the other two more complex measures. In order to test for this, we compare multifunctional and other annotated genes with respect to their betweenness and participation when controlling for degree distribution, and still observe that multifunctional genes have significantly larger betweenness and participation (S6 Fig and S2 Table).

Bottom Line: We also find that multifunctional genes are significantly more likely to be involved in human disorders.These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes.Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.

ABSTRACT
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms--H. sapiens, D. melanogaster, and S. cerevisiae--and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality.

No MeSH data available.


Related in: MedlinePlus