Phylogenetic Analysis

Gupta, Manoj Kumar; Gouda, Gayatri; Sabarinathan, S.; Donde, Ravindra; Rajesh, N.; Pati, Pallabi; Rathore, Sushil Kumar; Behera, Lambodar; Vadde, Ramakrishna

doi:10.1007/978-981-16-3993-7_9

Cited by 3 publications

(3 citation statements)

References 125 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Internal nodes are hypothetical taxonomic units (HTUs), with the topmost internal node called the root node, symbolizing the most recent common ancestor of all leaf nodes, marking the starting point of evolution. External nodes represent operational taxonomic units (OTUs), typically indicating species but also capable of representing extinct lineages or fossil endpoints [6,7]. The evolutionary clade within the phylogenetic tree encompasses a node and all lineages stemming from it.…”

Section: Introductionmentioning

confidence: 99%

Common Methods for Phylogenetic Tree Construction and Their Implementation in R

Zou,

Zhang,

Zeng

et al. 2024

Bioengineering

View full text Add to dashboard Cite

A phylogenetic tree can reflect the evolutionary relationships between species or gene families, and they play a critical role in modern biological research. In this review, we summarize common methods for constructing phylogenetic trees, including distance methods, maximum parsimony, maximum likelihood, Bayesian inference, and tree-integration methods (supermatrix and supertree). Here we discuss the advantages, shortcomings, and applications of each method and offer relevant codes to construct phylogenetic trees from molecular data using packages and algorithms in R. This review aims to provide comprehensive guidance and reference for researchers seeking to construct phylogenetic trees while also promoting further development and innovation in this field. By offering a clear and concise overview of the different methods available, we hope to enable researchers to select the most appropriate approach for their specific research questions and datasets.

show abstract

Section: Introductionmentioning

confidence: 99%

Common Methods for Phylogenetic Tree Construction and Their Implementation in R

Zou,

Zhang,

Zeng

et al. 2024

Bioengineering

View full text Add to dashboard Cite

show abstract

“…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). Population genetics and phylogenetics are two of the most important subfields for inferring the evolutionary history of any sequences/organisms (Haubold, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Phylogenies relation are inferred by comparing homologous characteristics that differ (Haubold, 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). 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).…”

Section: Introductionmentioning

confidence: 99%

Next-generation development and application of codon model in evolution

Gupta

Vadde²

2023

Front. Genet.

View full text Add to dashboard Cite

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. Out of these three, the codon substitution model is the most powerful. These models have been utilized extensively to detect selective pressure on a protein, codon usage bias, ancestral reconstruction and phylogenetic reconstruction. 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. Hence, there is always a question of how to develop more robust but less computationally demanding codon substitution models to get more accurate results. 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. 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. Thus, in the near future, these codon models can be utilized in the field of conservation, breeding and medicine.

show abstract

Molecular Functional and Transcriptome Analysis of Arabidopsis thaliana Overexpression BrBBX21 from Zicaitai (Brassica rapa var. purpuraria)

Fu,

Lu,

Guo

et al. 2024

Plants

View full text Add to dashboard Cite

B-box transcription factors (TFs) in plants are essential for circadian rhythm regulation, abiotic stress responses, hormonal signaling pathways, secondary metabolism, photomorphogenesis, and anthocyanin formation. Here, by blasting the AtBBX21 gene sequence, we identified a total of 18 BBX21 genes from five distinct Brassica species (Arabidopsis thaliana, Brassica rapa, Brassica oleracea, Brassica napus, and Brassica juncea). The BrBBX21-1 gene is most closely linked to the AtBBX21 gene based on phylogeny and protein sequence similarities. The BrBBX21-1 gene, which encodes a polypeptide of 319 amino acids, was identified from Zicaitai (Brassica rapa ssp. purpuraria) and functionally characterized. BrBBX21-1 was localized within the nucleus, and its overexpression in Arabidopsis augmented anthocyanin accumulation in both leaves and seeds. We further performed an RNA-seq analysis between the BrBBX21-OE and WT A. thaliana to identify the key regulators involved in anthocyanin accumulation. In detail, a total of 7583 genes demonstrated differential expression, comprising 4351 that were upregulated and 3232 that were downregulated. Out of 7583 DEGs, 81 F-box protein genes and 9 B-box protein genes were either up- or downregulated. Additionally, 7583 differentially expressed genes (DEGs) were associated with 109 KEGG pathways, notably including plant hormone signal transduction, the biosynthesis of secondary metabolites, metabolic pathways, glutathione metabolism, and starch and sucrose metabolism, which were considerably enriched. A transcriptome analysis led us to identify several structural genes, including DFRA, GSTF12, UGT75C1, FLS1, CHI1, 4CL3, and PAL1, and transcription factors, MYB90, TT8, and HY5, that are regulated by the overexpression of the BrBBX21-1 gene and involved in anthocyanin biosynthesis. Altogether, these findings demonstrate the beneficial regulatory function of BrBBX21-1 in anthocyanin accumulation and offer valuable information about the basis for breeding superior Brassica crops.

show abstract

Phylogenetic Analysis

Cited by 3 publications

References 125 publications

Common Methods for Phylogenetic Tree Construction and Their Implementation in R

Common Methods for Phylogenetic Tree Construction and Their Implementation in R

Next-generation development and application of codon model in evolution

Molecular Functional and Transcriptome Analysis of Arabidopsis thaliana Overexpression BrBBX21 from Zicaitai (Brassica rapa var. purpuraria)

Contact Info

Product

Resources

About