Characterization of multiple sequence alignment errors using complete-likelihood score and position-shift map

Abstract The classic methodology of inferring a phylogenetic tree from sequence data is composed of two steps. First, a multiple sequence alignment (MSA) is computed. Then, a tree is reconstructed assuming the MSA is correct. Yet, inferred MSAs were shown to be inaccurate and alignment errors reduce tree inference accuracy. It was previously proposed that filtering unreliable alignment regions can increase the accuracy of tree inference. However, it was also demonstrated that the benefit of this filtering is often obscured by the resulting loss of phylogenetic signal. In this work we explore an approach, in which instead of relying on a single MSA, we generate a large set of alternative MSAs and concatenate them into a single SuperMSA. By doing so, we account for phylogenetic signals contained in columns that are not present in the single MSA computed by alignment algorithms. Using simulations, we demonstrate that this approach results, on average, in more accurate trees compared to 1) using an unfiltered MSA and 2) using a single MSA with weights assigned to columns according to their reliability. Next, we explore in which regions of the MSA space our approach is expected to be beneficial. Finally, we provide a simple criterion for deciding whether or not the extra effort of computing a SuperMSA and inferring a tree from it is beneficial. Based on these assessments, we expect our methodology to be useful for many cases in which diverged sequences are analyzed. The option to generate such a SuperMSA is available at http://guidance.tau.ac.il.

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Accuracy of multiple sequence alignment methods in the reconstruction of transposable element families

10.1101/2021.08.17.456740 ◽

2021 ◽

Author(s):

Robert M. Hubley ◽

Travis J. Wheeler ◽

Arian F.A. Smit

Keyword(s):

Transposable Element ◽

Sequence Alignment ◽

Dna Sequences ◽

Multiple Sequence Alignment ◽

Structural Features ◽

Sequence Evolution ◽

Sequence Alignments ◽

Multiple Sequence ◽

Consensus Sequences

The construction of a high-quality multiple sequence alignment (MSA) from copies of a transposable element (TE) is a critical step in the characterization of a new TE family. Most studies of MSA accuracy have been conducted on protein or RNA sequence families where structural features and strong signals of selection may assist with alignment. Less attention has been given to the quality of sequence alignments involving neutrally evolving DNA sequences such as those resulting from TE replication. Such alignments play an important role in understanding and representing TE family history. Transposable element sequences are challenging to align due to their wide divergence ranges, fragmentation, and predominantly-neutral mutation patterns. To gain insight into the effects of these properties on MSA accuracy, we developed a simulator of TE sequence evolution, and used it to generate a benchmark with which we evaluated the MSA predictions produced by several popular aligners, along with Refiner, a method we developed in the context of our RepeatModeler software. We find that MAFFT and Refiner generally outperform other aligners for low to medium divergence simulated sequences, while Refiner is uniquely effective when tasked with aligning high-divergent and fragmented instances of a family. As a result, consensus sequences derived from Refiner-based MSAs are more similar to the true consensus.

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Multiple Sequence Alignment and Profile Analysis of Protein Family Utsing Hidden Markov Model

International Journal of Scientific Research ◽

10.15373/22778179/june2013/66 ◽

2012 ◽

Vol 2 (6) ◽

pp. 208-211

Author(s):

Navjot Kaur ◽

◽

Rajbir Singh Cheema ◽

Harmandeep Singh Harmandeep Singh

Keyword(s):

Markov Model ◽

Hidden Markov Model ◽

Sequence Alignment ◽

Multiple Sequence Alignment ◽

Profile Analysis ◽

Hidden Markov ◽

Protein Family ◽

Multiple Sequence

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Faculty Opinions recommendation of MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.731078852.793536612 ◽

2017 ◽

Author(s):

Feng Gao

Keyword(s):

Sequence Alignment ◽

Multiple Sequence Alignment ◽

Online Service ◽

Multiple Sequence

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Computational Analysis of Therapeutic Enzyme Uricase from Different Source Organisms

Current Proteomics ◽

10.2174/1570164616666190617165107 ◽

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

Current Nutrition & Food Science ◽

10.2174/1573401314666180223143523 ◽

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

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