Scaling properties of protein family phylogenies

Herrada, E. Alejandro; Eguı́luz, Vı́ctor M.; Hernández-Garcı́a, Emilio; Duarte, Carlos M.

doi:10.1186/1471-2148-11-155

Cited by 14 publications

(22 citation statements)

References 66 publications

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“…Ultimately, this process is shaping the diversity of life on Earth. Our findings on evolutionary relatedness and the diversification of B1-subfamily members support the universal branching rule (Herrada et al 2011(Herrada et al , 2008, and we assume that this rule applies everywhere from gene families to protein families, and finally, within the continuous process of speciation. Our analysis impressively suggests that evolutionary relatedness occurs during the branching process.…”

Section: Resultssupporting

confidence: 76%

Insight into Evolution and Conservation Patterns of B1-Subfamily Members of GPCR

Chakraborty

Sharma

et al. 2020

Int J Pept Res Ther

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The diverse, evolutionary architectures of proteins can be regarded as molecular fossils, tracing a historical path that marks important milestones across life. The B1-subfamily of GPCRs (G-protein-coupled receptors) are medically significant proteins that comprise 15 transmembrane receptor proteins in Homo sapiens. These proteins control the intracellular concentration of cyclic AMP as well as various vital processes in the body. However, little is known about the evolutionary correlation and conservational blueprint of this GPCR subfamily. We performed a comprehensive analysis to understand the evolutionary architecture among 13 members of the B1-subfamily. Multiple sequence alignment analysis exhibited six multiple sequence aligned blocks and five highly aligned blocks. Molecular phylogenetics indicated that CRHR1 and CRHR2 share a typical ancestral relationship and are siblings in 100% bootstrap replications with a total of 24 nodes observed in the cladogram. CRHR2 has the maximum number of extremely conserved amino acids followed by ADCYAP1R1. The longest continuous number sequence logos (74) were found between sequence location 349 and 423, and consequently, the maximum and minimum logo height recorded was 3.6 bits and 0.18 bits, respectively. Finally, to understand the model and pattern of evolutionary relatedness, the conservation blueprint, and the diversification among the members of a protein family, GPCR distribution from several species throughout the animal kingdom was analysed. Together, the study provides an evolutionary insight and offers a rapid method to explore the potential of depicting the evolutionary relationship, conservation blueprint, and diversification among the B1-subfamily of GPCRs using bioinformatics, algorithm analysis, and mathematical models.

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Section: Resultssupporting

confidence: 76%

Insight into Evolution and Conservation Patterns of B1-Subfamily Members of GPCR

Chakraborty

Sharma

et al. 2020

Int J Pept Res Ther

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“…An asymptotic behavior as is found to correspond to a well defined value of the parameter in the beta-splitting model and it is associated to a great variety of real phylogenetic tree [5]. Moreover, in some recent analysis [13], [8], authors found the same asymptotic behavior (respectively and ) for the mean topological distance and the mean depth when looking at the scaling laws of all the trees in the PANDIT [46] and TreeBASE [47] databases. It should be noted that logarithmic exponent can greatly vary in these cases and the authors of [8] mention that a power law with fits TreeBASE data equally well [48] while for larger tree sizes as those contained in PANDIT, the seems more accurate.…”

Section: Methodsmentioning

confidence: 99%

Phylogenetic Properties of RNA Viruses

2012

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A new word, phylodynamics, was coined to emphasize the interconnection between phylogenetic properties, as observed for instance in a phylogenetic tree, and the epidemic dynamics of viruses, where selection, mediated by the host immune response, and transmission play a crucial role. The challenges faced when investigating the evolution of RNA viruses call for a virtuous loop of data collection, data analysis and modeling. This already resulted both in the collection of massive sequences databases and in the formulation of hypotheses on the main mechanisms driving qualitative differences observed in the (reconstructed) evolutionary patterns of different RNA viruses. Qualitatively, it has been observed that selection driven by the host immune response induces an uneven survival ability among co-existing strains. As a consequence, the imbalance level of the phylogenetic tree is manifestly more pronounced if compared to the case when the interaction with the host immune system does not play a central role in the evolutive dynamics. While many imbalance metrics have been introduced, reliable methods to discriminate in a quantitative way different level of imbalance are still lacking. In our work, we reconstruct and analyze the phylogenetic trees of six RNA viruses, with a special emphasis on the human Influenza A virus, due to its relevance for vaccine preparation as well as for the theoretical challenges it poses due to its peculiar evolutionary dynamics. We focus in particular on topological properties. We point out the limitation featured by standard imbalance metrics, and we introduce a new methodology with which we assign the correct imbalance level of the phylogenetic trees, in agreement with the phylodynamics of the viruses. Our thorough quantitative analysis allows for a deeper understanding of the evolutionary dynamics of the considered RNA viruses, which is crucial in order to provide a valuable framework for a quantitative assessment of theoretical predictions.

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“…We have calculated [11,12] the depth d for all trees (and subtrees) in the phylogenetic databases TreeBASE (containing species phylogenies [16]) and PANDIT (protein phylogenies [17]). The result in Figure 1(a) suggests that the average depth grows with the number of tips as…”

Section: Tree Shape and Depthmentioning

confidence: 99%

“…Evolutionary histories and genealogies are naturally represented as trees. Each branching point represents an ancestral relationship in a population or an event of diversification on sets of languages [8], species [9][10][11][12][13] or socio-cultural innovations [14]. Based on genetic information, modern computational biology has inferred thousands of trees, socalled phylogenies [15], depicting the evolutionary relationships between sets of species, from bacteria to mammals [16].…”

Section: Introductionmentioning

confidence: 99%

Anomalous scaling in an age-dependent branching model

et al. 2015

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We introduce a one-parametric family of tree growth models, in which branching probabilities decrease with branch age τ as τ −α . Depending on the exponent α, the scaling of tree depth with tree size n displays a transition between the logarithmic scaling of random trees and an algebraic growth. At the transition (α = 1) tree depth grows as (log n)2 . This anomalous scaling is in good agreement with the trend observed in evolution of biological species, thus providing a theoretical support for age-dependent speciation and associating it to the occurrence of a critical point.

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Scaling properties of protein family phylogenies

Cited by 14 publications

References 66 publications

Insight into Evolution and Conservation Patterns of B1-Subfamily Members of GPCR

Insight into Evolution and Conservation Patterns of B1-Subfamily Members of GPCR

Phylogenetic Properties of RNA Viruses

Anomalous scaling in an age-dependent branching model

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