Influence of Parameters and Differences in Results of Microsatellite Detection Software: A Bioinformatics Study

Author Name(s): *Sujan Patnana, Ramasree Sripada
Author Email: sujan.patnana@gmail.com

Abstract

Microsatellites are small nucleotide repeats which are formed by tandem repetition of motifs of size 1-6 bp. These repeats play an important role in Genome evolution, Associated with various diseases, Used as molecular markers in DNA Fingerprinting, Population Genetics, Paternity Studies, Forensics, etc. Various bioinformatics tools are being used for extraction of STRs during the computational studies. However, computational studies of STRs can suffer from a significant bias depending on the software tool used in the study. We did a comparative study of various popular microsatellite extraction tools while detecting perfect and imperfect microsatellites separately. We found that the tools show similar efficiencies while detecting perfect repeats whereas differ a lot in efficiencies while detecting imperfect microsatellites.

 

Keywords

Microsatellites; Perfect Repeats; Software Tools; Comparison; Short Tandem Repeats; Simple Sequence Repeats.

Introduction

Microsatellites or Short Tandem Repeats (STRs) or Simple Sequence Repeats (SSRs) are tandem repeats of nucleotide motifs of the size 1-6bp [1]. Because of their polymorphic nature, abundance and distribution through out coding and non-coding regions, these repeats have been a major area of interest for the researchers. They have been used as genetic markers in DNA Fingerprinting and in paternity studies [2]. They are also associated with various diseases [3] and play an important role in various regulatory mechanisms and evolution [4] [5]. Recently, they are also found to be associated with the plasticity and evolution of bacterial genomes [6] Microsatellites can be categorized into perfect, imperfect (with few mismatches) and compound microsatellites. A perfect microsatellite tract is one with 100% identical copies of motifs. For example, ATGATGATGATG is a perfect microsatellite tract with the motif ‘ATG’ repeating 4 times (represented as (ATG)4). The ‘Perfect’ microsatellite tracts also suffer from point mutations such as indels and substitutions there by making it an ‘Imperfect’ microsatellite tract. For example, ATGATCATGATG is the imperfect tract with a substitution at 6th position. The other type of microsatellites called ‘Compound’ microsatellite includes multiple motifs in the same tract separated by certain distance among the individual repeats. For example, (ATG)ngcctc(GC)m is a compound microsatellite tract with two microsatellite tracts of ATG and GC motifs separated by 5 nucleotides. Out of the three, imperfect microsatellites are of much interest for the researchers and are more stable when compared to perfect tracts [7] Increasing availability of genome data has led to the development of various software tools for in-silico study of these microsatellites in various genomes in place of cost and time intensive laboratory methods. Till date, many software programs are available for extraction of tandem repeats from genome sequences. These tools have been used extensively by biologists who might not have the necessary knowledge about the inner implementation (algorithm) and functionality of the software. Even though many software tools are available for microsatellite extraction, they vary largely in-terms of their algorithm, efficiency and functionality. Recent studies [8, 9, 10] showed that there is a significant bias in the number of repeats detected by various microsatellite detection algorithms. This is a serious problem as the microsatellite studies involving these repeats suffer from inconsistent and incomplete results and the credibility of the studies may be questioned. This paper attempts a similar study to compare the efficiency of a set of microsatellite detecting tools in detecting perfect and imperfect repeats.

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