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Translational Research in Veterinary Science

Benchmark of algorithms for multiple DNA sequence alignment across livestock species
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Benchmark of algorithms for multiple DNA sequence alignment across livestock species

Authors

  • Artur Bąk Department of Cattle Breeding and Genetics, National Research Institute of Animal Production, Balice https://orcid.org/0000-0001-6623-0587
  • Grzegorz Migdałek Institute of Biology, Pedagogical University of Cracow https://orcid.org/0000-0003-1458-2673
  • Chandra Shekhar Pareek Department of Fundamental and Preclinical Sciences, Faculty of Biology and Veterinary Sciences, Nicolaus Copernicus University in Toruń https://orcid.org/0000-0002-0329-787X
  • Kacper Żukowski Department of Fundamental and Preclinical Sciences, Faculty of Biology and Veterinary Sciences, Nicolaus Copernicus University, Toruń https://orcid.org/0000-0002-5690-3634

DOI:

https://doi.org/10.12775/TRVS.2020.009

Keywords

multiple sequence alignment, ClustalO, ClustalW, Kalign, MAFFT, MUSCLE, Probcons and T-Coffee, bioinformatics pipeline, livestock

Abstract

Background: Due to the growing amount of biological data, it is often necessary to select the most optimal estimation method for DNA sequence alignment across livestock species. One of the most important benches of genomics is to modelling homology between considered DNA sequences. A multiple sequence alignment is a potent tool for molecular and evolutionary biology, and there are several programs and algorithms applicable for this purpose. The purpose of this paper was to study the most commonly used DNA alignment algorithms to select the optimal tool dedicated for short sequences.

Methods: Four steps of bioinformatics pipelines were considered to benchmark the algorithms for multiple DNA sequence alignment across livestock species: 1) selection of reference genome sequences of ARS1.2 for cattle, EquCab3.0 for horse and vicPac2 for alpaca with a low E-value using TBLASTn 2) removing gaps for these sequences 3) alignment of obtained sequences using examined algorithms 4) matching the quality of aligned sequences with sequences of reference genomes by more software. The time of computation was archived for the whole analysis. The seven programs were utilized, each based on different alignment algorithms, namely: ClustalO, ClustalW, Kalign, MAFFT, MUSCLE, Probcons and T-Coffee.

Results: The result obtained in this study showed that the fastest is progressive algorithms such as Kalign or MUSCLE-FAST. Moreover, the iterative algorithms like MAFFT and MUSCLE revealed a higher quality of the alignment. The T-Coffee and Probcons programs were computational cost-effective; simultaneously, they were generating a medium-quality calculation in a relatively long time. The best quality of alignment was shown by iterative variants of the MAFFT program; however, the speed of the calculations was relatively low. The fastest algorithm was Kalign, making alignment much faster than the competitors, but achieving average results in the quality of the alignment. The average speed ratio concerning the quality of the analyzed algorithms was obtained by the progressive version of MAFFT, NS1.

Conclusions: We conclude that the results of this study can be used to re-alignment of variant primers in new livestock genome releases.

References

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Translational Research in Veterinary Science

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Published

2021-01-24

How to Cite

1.
BĄK, Artur, MIGDAŁEK, Grzegorz, PAREEK, Chandra Shekhar and ŻUKOWSKI, Kacper. Benchmark of algorithms for multiple DNA sequence alignment across livestock species. Translational Research in Veterinary Science. Online. 24 January 2021. Vol. 3, no. 2, pp. 41-47. [Accessed 6 July 2025]. DOI 10.12775/TRVS.2020.009.
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Vol. 3 No. 2 (2020)

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Research Articles

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multiple sequence alignment, ClustalO, ClustalW, Kalign, MAFFT, MUSCLE, Probcons and T-Coffee, bioinformatics pipeline, livestock
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