LegumeDB: Development of Legume Medicinal Plant Database and Comparative Molecular Evolutionary Analysis of matK Proteins of Legumes and Mangroves

2019 ◽  
Vol 15 (4) ◽  
pp. 353-362
Author(s):  
Sambhaji B. Thakar ◽  
Maruti J. Dhanavade ◽  
Kailas D. Sonawane
Keyword(s):  
Phylogenetic Analysis ◽  
Medicinal Plants ◽  
Homology Modeling ◽  
Sequence Alignment ◽  
Vigna Unguiculata ◽  
Multiple Sequence Alignment ◽  
Legume Species ◽  
Mangrove Species ◽  
Multiple Sequence ◽  
Thespesia Populnea

Background: Legume plants are known for their rich medicinal and nutritional values. Large amount of medicinal information of various legume plants have been dispersed in the form of text. Objective: It is essential to design and construct a legume medicinal plants database, which integrate respective classes of legumes and include knowledge regarding medicinal applications along with their protein/enzyme sequences. Methods: The design and development of Legume Medicinal Plants Database (LegumeDB) has been done by using Microsoft Structure Query Language Server 2017. DBMS was used as back end and ASP.Net was used to lay out front end operations. VB.Net was used as arranged program for coding. Multiple sequence alignment, phylogenetic analysis and homology modeling techniques were also used. Results: This database includes information of 50 Legume medicinal species, which might be helpful to explore the information for researchers. Further, maturase K (matK) protein sequences of legumes and mangroves were retrieved from NCBI for multiple sequence alignment and phylogenetic analysis to understand evolutionary lineage between legumes and mangroves. Homology modeling technique was used to determine three-dimensional structure of matK from Legume species i.e. Vigna unguiculata using matK of mangrove species, Thespesia populnea as a template. The matK sequence analysis results indicate the conserved residues among legume and mangrove species. Conclusion: Phylogenetic analysis revealed closeness between legume species Vigna unguiculata and mangrove species Thespesia populnea to each other, indicating their similarity and origin from common ancestor. Thus, these studies might be helpful to understand evolutionary relationship between legumes and mangroves. : LegumeDB availability: http://legumedatabase.co.in

scholarly journals SHOOT: phylogenetic gene search and ortholog inference

2021 ◽  
Author(s):  
David Emms ◽  
Steven Kelly
Keyword(s):  
Phylogenetic Analysis ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Phylogenetic Trees ◽  
Query Sequence ◽  
Gene Tree ◽  
Biological Research ◽  
Gene Sequences ◽  
Multiple Sequence ◽  
Gene Search

Determining the evolutionary relationships between gene sequences is fundamental to comparative biological research. However, conducting such analyses requires a high degree of technical proficiency in several computational tools including gene family construction, multiple sequence alignment, and phylogenetic inference. Here we present SHOOT, an easy to use phylogenetic search engine for fast and accurate phylogenetic analysis of biological sequences. SHOOT searches a user-provided query sequence against a database of phylogenetic trees of gene sequences (gene trees) and returns a gene tree with the given query sequence correctly grafted within it. We show that SHOOT can perform this search and placement with comparable speed to a conventional BLAST search. We demonstrate that SHOOT phylogenetic placements are as accurate as conventional multiple sequence alignment and maximum likelihood tree inference approaches. We further show that SHOOT can be used to identify orthologs with equivalent accuracy to conventional orthology inference methods. In summary, SHOOT is an accurate and fast tool for complete phylogenetic analysis of novel query sequences. An easy to use webserver is available online at www.shoot.bio.

scholarly journals Gotree/Goalign : Toolkit and Go API to facilitate the development of phylogenetic workflows

2021 ◽  
Author(s):  
Frederic Lemoine ◽  
Olivier Gascuel
Keyword(s):  
Phylogenetic Analysis ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Phylogenetic Analyses ◽  
Bootstrap Support ◽  
Complex Task ◽  
Important Data ◽  
Multiple Sequence ◽  
Tree Comparison ◽  
User Friendly

Besides computer intensive steps, phylogenetic analysis workflows are usually composed of many small, reccuring, but important data manipulations steps. Among these, we can find file reformatting, sequence renaming, tree re-rooting, tree comparison, bootstrap support computation, etc. These are often performed by custom scripts or by several heterogeneous tools, which may be error prone, uneasy to maintain and produce results that are challenging to reproduce. For all these reasons, the development and reuse of phylogenetic workflows is often a complex task. We identified many operations that are part of most phylogenetic analyses, and implemented them in a toolkit called Gotree/Goalign. The Gotree/Goalign toolkit implements more than 120 user-friendly commands and an API dedicated to multiple sequence alignment and phylogenetic tree manipulations. It is developed in Go, which makes executables efficient, easily installable, integrable in workflow environments, and parallelizable when possible. This toolkit is freely available on most platforms (Linux, MacOS and Windows) and most architectures (amd64, i386). Sources and binaries are available on GitHub at https://github.com/evolbioinfo/{gotree|goalign} , Bioconda, and DockerHub.

scholarly journals VP2 Gene-Based Molecular Evolutionary Patterns of Major Circulating Bluetongue Virus Serotypes Isolated during 2014–2018 from Telangana and Andhra Pradesh States of India

Intervirology ◽  
2020 ◽  
pp. 1-8
Author(s):  
Ravali Thota ◽  
Vishweshwar Kumar Ganji ◽  
Sharanya Machanagari ◽  
Narasimha Reddy Yella ◽  
Bhagyalakshmi Buddala ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Bluetongue Virus ◽  
Andhra Pradesh ◽  
Geographical Location ◽  
Effective Control ◽  
Effective Vaccine ◽  
Multiple Sequence ◽  
Vp2 Gene

<b><i>Introduction:</i></b> Bluetongue disease is an economically important viral disease of livestock caused by bluetongue virus (BTV) having multiple serotypes. It belongs to the genus <i>Orbivirus</i> of family Reoviridae and subfamily Sedoreovirinae. The genome of BTV is 10 segmented dsRNA that codes for 7 structural and 4 nonstructural proteins, of which VP2 was reported to be serotype-specific and a major antigenic determinant. <b><i>Objective:</i></b> It is important to know the circulating serotypes in a particular geographical location for effective control of the disease. The present study unravels the molecular evolution of the circulating BTV serotypes during 2014–2018 in Telangana and Andhra Pradesh states of India. <b><i>Methods:</i></b> Multiple sequence alignment with available BTV serotypes in GenBank and phylogenetic analysis were performed for the partial VP2 sequences of major circulating BTV serotypes during the study period. <b><i>Results:</i></b> The multiple sequence alignment of circulating serotypes with respective reference isolates revealed variations in antigenic VP2. The phylogenetic analysis revealed that the major circulating serotypes were grouped into eastern topotypes (BTV-1, BTV-2, BTV-4, and BTV-16) and Western topotypes (BTV-5, BTV-12, and BTV-24). <b><i>Conclusion:</i></b> Our study strengthens the need for development of an effective vaccine, which can induce the immune response for a range of serotypes within and in between topotypes.

scholarly journals An Alignment-free Method for Phylogeny Estimation using Maximum Likelihood

2019 ◽  
Author(s):  
Tasfia Zahin ◽  
Md. Hasin Abrar ◽  
Mizanur Rahman ◽  
Tahrina Tasnim ◽  
Md. Shamsuzzoha Bayzid ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Computational Complexity ◽  
Maximum Likelihood ◽  
Phylogenetic Tree ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Multiple Sequence ◽  
Alignment Free ◽  
Phylogeny Estimation ◽  
Statistical Approaches

AbstractPhylogenetic analysis i.e. construction of an accurate phylogenetic tree from genomic sequences of a set of species is one of the main challenges in bioinformatics. The popular approaches to this require aligning each pair of sequences to calculate pairwise distances or aligning all the sequences to construct a multiple sequence alignment. The computational complexity and difficulties in getting accurate alignments have led to development of alignment-free methods to estimate phylogenies. However, the alignment free approaches focus on computing distances between species and do not utilize statistical approaches for phylogeny estimation. Herein, we present a simple alignment free method for phylogeny construction based on contiguous sub-sequences of length k termed k-mers. The presence or absence of these k-mers are used to construct a phylogeny using a maximum likelihood approach. The results suggest our method is competitive with other alignment-free approaches, while outperforming them in some cases.

Multiple Sequence Alignment in Phylogenetic Analysis

2000 ◽  
Vol 16 (3) ◽  
pp. 317-330 ◽  
Author(s):  
Aloysius Phillips ◽  
Daniel Janies ◽  
Ward Wheeler
Keyword(s):  
Phylogenetic Analysis ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Multiple Sequence

scholarly journals Multiple sequence alignment for phylogenetic purposes

2006 ◽  
Vol 19 (6) ◽  
pp. 479 ◽  
Author(s):  
David A. Morrison
Keyword(s):  
Phylogenetic Analysis ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Multiple Alignment ◽  
Evolutionary Processes ◽  
Multiple Sequence ◽  
Molecular Sequence ◽  
The Many ◽  
Tree Building ◽  
Automated Procedures

I have addressed the biological rather than bioinformatics aspects of molecular sequence alignment by covering a series of topics that have been under-valued, particularly within the context of phylogenetic analysis. First, phylogenetic analysis is only one of the many objectives of sequence alignment, and the most appropriate multiple alignment may not be the same for all of these purposes. Phylogenetic alignment thus occupies a specific place within a broader context. Second, homology assessment plays an intricate role in phylogenetic analysis, with sequence alignment consisting of primary homology assessment and tree building being secondary homology assessment. The objective of phylogenetic alignment thus distinguishes it from other sorts of alignment. Third, I summarise what is known about the serious limitations of using phenetic similarity as a criterion for automated multiple alignment, and provide an overview of what is currently being done to improve these computerised procedures. This synthesises information that is apparently not widely known among phylogeneticists. Fourth, I then consider the recent development of automated procedures for combining alignment and tree building, thus integrating primary and secondary homology assessment. Finally, I outline various strategies for increasing the biological content of sequence alignment procedures, which consists of taking into account known evolutionary processes when making alignment decisions. These procedures can be objective and repeatable, and can involve computerised algorithms to automate much of the work. Perhaps the most important suggestion is that alignment should be seen as a process where new sequences are added to a pre-existing alignment that has been manually curated by the biologist.

Computational Analysis of Therapeutic Enzyme Uricase from Different Source Organisms

2020 ◽  
Vol 17 (1) ◽  
pp. 59-77
Author(s):  
Anand Kumar Nelapati ◽  
JagadeeshBabu PonnanEttiyappan
Keyword(s):  
Uric Acid ◽  
Amino Acid ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Protein Sequences ◽  
Amino Acid Sequences ◽  
Amino Acid Residues ◽  
Multiple Sequence ◽  
Physiochemical Properties ◽  
Pharmaceutical Industries

Background:Hyperuricemia and gout are the conditions, which is a response of accumulation of uric acid in the blood and urine. Uric acid is the product of purine metabolic pathway in humans. Uricase is a therapeutic enzyme that can enzymatically reduces the concentration of uric acid in serum and urine into more a soluble allantoin. Uricases are widely available in several sources like bacteria, fungi, yeast, plants and animals.Objective:The present study is aimed at elucidating the structure and physiochemical properties of uricase by insilico analysis.Methods:A total number of sixty amino acid sequences of uricase belongs to different sources were obtained from NCBI and different analysis like Multiple Sequence Alignment (MSA), homology search, phylogenetic relation, motif search, domain architecture and physiochemical properties including pI, EC, Ai, Ii, and were performed.Results:Multiple sequence alignment of all the selected protein sequences has exhibited distinct difference between bacterial, fungal, plant and animal sources based on the position-specific existence of conserved amino acid residues. The maximum homology of all the selected protein sequences is between 51-388. In singular category, homology is between 16-337 for bacterial uricase, 14-339 for fungal uricase, 12-317 for plants uricase, and 37-361 for animals uricase. The phylogenetic tree constructed based on the amino acid sequences disclosed clusters indicating that uricase is from different source. The physiochemical features revealed that the uricase amino acid residues are in between 300- 338 with a molecular weight as 33-39kDa and theoretical pI ranging from 4.95-8.88. The amino acid composition results showed that valine amino acid has a high average frequency of 8.79 percentage compared to different amino acids in all analyzed species.Conclusion:In the area of bioinformatics field, this work might be informative and a stepping-stone to other researchers to get an idea about the physicochemical features, evolutionary history and structural motifs of uricase that can be widely used in biotechnological and pharmaceutical industries. Therefore, the proposed in silico analysis can be considered for protein engineering work, as well as for gout therapy.

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