PolyMorphPredict: A Universal Web-Tool for Rapid Polymorphic Microsatellite Marker Discovery From Whole Genome and Transcriptome Data

Abstract

Microsatellites are ubiquitously distributed, polymorphic repeat sequence valuable for association, selection, population structure and identification. They can be mined by genomic library, probe hybridization and sequencing of selected clones. Such approach has many limitations like biased hybridization and selection of larger repeats. In silico mining of polymorphic markers using data of various genotypes can be rapid and economical. Available tools lack in some or other aspects like: targeted user defined primer generation, polymorphism discovery using multiple sequence, size and number limits of input sequence, no option for primer generation and e-PCR evaluation, transferability, lack of complete automation and user-friendliness. They also lack the provision to evaluate published primers in e-PCR mode to generate additional allelic data using re-sequenced data of various genotypes for judicious utilization of previously generated data. We developed the tool (PolyMorphPredict) using Perl, R, Java and launched at Apache which is available at http://webtom.cabgrid.res.in/polypred/. It mines microsatellite loci and computes primers from genome/transcriptome data of any species. It can perform e-PCR using published primers for polymorphism discovery and across species transferability of microsatellite loci. Present tool has been evaluated using five species of different genome size having 21 genotypes. Though server is equipped with genomic data of three species for test run with gel simulation, but can be used for any species. Further, polymorphism predictability has been validated using in silico and in vitro PCR of four rice genotypes. This tool can accelerate the in silico microsatellite polymorphism discovery in re-sequencing projects of any species of plant and animal for their diversity estimation along with variety/breed identification, population structure, MAS, QTL and gene discovery, traceability, parentage testing, fungal diagnostics and genome finishing.

Detection of Microsatellite Instability: State of the Art and Future Applications in Circulating Tumour DNA (ctDNA)

“…The MSI status could also be inferred using NGS data from whole-genome, whole-exome, gene targeted, or RNA sequencing that were not originally developed for MSI diagnosis [ 62 ]. During the process of sequencing, numerous MS loci are incidentally captured along with regions of interest and can be easily identified using web-based tools such as MISA (MicroSAtellite identification tool), GMATo (Genome-wide Microsatellite Analyzing Tool), or PolyMorphPredict [ 26 , 87 , 88 , 89 ]. Different MSI computational tools have been developed for MSI diagnosis by exploiting existing NGS data ( Table 3 ).…”

Fungal Genomic Resources for Strain Identification and Diversity Analysis of 1900 Fungal Species

“…A total of 66 genome assemblies ( (accessed on 15 October 2020)) of different isolates of this species from four different continents (Asia, Australia/Oceania, Europe, North America) were selected for strain differentiation by SSR polymorphism using e-PCR. In silico genotyping of 75 SSR loci was carried out using ePCR of online tool [ 29 ]. Five simple and di- nucleotide repeat loci were selected from each of the 15 chromosomes which are expected to have a high degree of polymorphism and thus better representation of variability of both genome as well as population.…”

MultiplexSSR: A pipeline for developing multiplex SSR‐PCR assays from resequencing data

“…However, the available tools are all lacking in some regards. PolyMorphPredict (Das et al, ) and PSR (Cantarella & D'Agostino, ) lack the masking of mutations in primer design. PolySSR (Tang et al, ) and CandiSSR (Xia et al, ) depend on assembled sequences.…”

“…However, the available tools are all lacking in some regards. PolyMorphPredict (Das et al, 2019) and PSR (Cantarella & D'Agostino, 2015) lack the masking of mutations in primer design.…”