Gtr model of evolution3/31/2024 In probability theory, any stochastic process has the Markov property if the probability distribution of future states of the process is dependent only on the present state ( Gudivada et al., 2015). Nevertheless, all models share a common assumption, i.e., the Markov property ( Liò and Goldman, 1998). However, in reality, there are numerous mutations, and some mutations are less tolerated in comparison to others ( Liò and Goldman, 1998 Choudhuri, 2014). For instance, the JC69 model hypothesizes that the rate of nucleotide substitution is the same for all pairs of the four nucleotides, namely, guanine (G), cytosine (C), adenine (A), and thymine (T) ( Jukes and Cantor, 1969). However, the validity of certain models could be plausibly challenged while analyzing real data. All phylogenetic tree analysis is based on certain implicit/explicit hypothetical models that make the complex biological process into simpler form ( Gatto et al., 2007 Zaheri et al., 2014). A phylogenetic tree, often known as an evolutionary tree, is a diagrammatic depiction of the evolutionary relationship between different species ( Gupta et al., 2021c). Phylogenies relation are inferred by comparing homologous characteristics that differ ( Haubold, 2014). It is pertinent to note that there is only one diagram, a phylogeny, that appears in Darwin’s seminal work, “The Origin of Species.” This, in turn, indicates that phylogenies are the core metaphor of evolutionary biology, and efforts to create them is as old as the evolutionary science field itself. ![]() While phylogeny approaches infer the evolution of species and higher taxonomic orders, population genetics approaches are generally used for understanding the evolution of the groups below the species level ( Haubold, 2014). Population genetics and phylogenetics are two of the most important subfields for inferring the evolutionary history of any sequences/organisms ( Haubold, 2014). The continuous growth of DNA and protein data has provided an opportunity to infer their function and their evolutionary history of any sequence/organisms in a more comprehensive way ( Anisimova and Liberles, 2007 Miyazawa, 2011a Dufresne and Jeffery, 2011 Gupta and Vadde, 2019a Gupta et al., 2019 Gouda et al., 2020 Gupta et al., 2021a Gupta et al., 2021b Gupta et al., 2021c Gupta et al., 2021d Gupta et al., 2021e Chu et al., 2021). Thus, in the near future, these codon models can be utilized in the field of conservation, breeding and medicine. The codon substitution model enables to detect selection regime under which any gene or gene region is evolving, codon usage bias in any organism or tissue-specific region and phylogenetic relationship between different lineages more accurately than nucleotide and amino acid substitution models. In this review article, the authors attempted to understand the basis of the development of different types of codon-substitution models and how this information can be utilized to develop more robust but less computationally demanding codon substitution models. Hence, there is always a question of how to develop more robust but less computationally demanding codon substitution models to get more accurate results. ![]() However, due to more computational demanding, in comparison to nucleotide and amino acid substitution models, only a few studies have employed the codon substitution model to understand the heterogeneity of the evolutionary process in a genome-scale analysis. These models have been utilized extensively to detect selective pressure on a protein, codon usage bias, ancestral reconstruction and phylogenetic reconstruction. Out of these three, the codon substitution model is the most powerful. To date, numerous nucleotide, amino acid, and codon substitution models have been developed to estimate the evolutionary history of any sequence/organism in a more comprehensive way. Department of Biotechnology & Bioinformatics, Yogi Vemana University, Kadapa, Andhra Pradesh, India.
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