A Galaxy-based bioinformatics pipeline for optimised, streamlined microsatellite development from Illumina next-generation sequencing data

Abstract

Microsatellites are useful tools for ecologists and conservationist biologists, but are taxa-specific and traditionally expensive and time-consuming to develop. New methods using next-generation sequencing (NGS) have reduced these problems, but the plethora of software available for processing NGS data may cause confusion and difficulty for researchers new to the field of bioinformatics. We developed a bioinformatics pipeline for microsatellite development from Illumina paired-end sequences, which is packaged in the open-source bioinformatics tool Galaxy. This optimises and streamlines the design of a microsatellite panel and provides a userfriendly graphical user interface. The pipeline utilises existing programs along with our own novel program and wrappers to: quality-filter and trim reads (Trimmomatic); generate sequence quality reports (FastQC); identify potentially-amplifiable microsatellite loci (Pal_finder); design primers (Primer3); assemble pairs of reads to enhance marker amplification success rates (PANDAseq); and filter optimal loci (Pal_filter). The complete pipeline is freely available for use via a pre-configured Galaxy instance, accessible at https://palfinder.ls.manchester.ac.uk.

Multi‐individual microsatellite identification: A multiple genome approach to microsatellite design (MiMi)

“…These frequencies are dependent upon the genome size, and the microsatellite richness of the genome, of the species of interest. Where estimates of genome coverage are approximately 1X or below, removal of duplicate primers/loci from the data set of each individual is recommended (implemented automatically in the Griffiths et al () workflow) as coverage of >1X of a locus in a single individual does not contribute any additional information to the MiMi process. However, where estimated coverage is significantly >1X, their removal may result in the dismissal of an increased frequency of otherwise useful loci that appear multiple times in the sequence data as a result of the random nature of shotgun sequencing (Bouck, Miller, Gorrell, Muzny, & Gibbs, ).…”

“…However, where estimated coverage is significantly >1X, their removal may result in the dismissal of an increased frequency of otherwise useful loci that appear multiple times in the sequence data as a result of the random nature of shotgun sequencing (Bouck, Miller, Gorrell, Muzny, & Gibbs, ). In the event of a low number of markers ultimately being returned, the filter that removes loci appearing more than once in the data can easily be disabled at the web interface of the Griffiths et al () tool. In this case, multiple reads containing the primer sequence from the same biological sample will appear alongside each other in the output MSA, allowing the user to assess the reads as “shotgun duplicates” (i.e., multiple sequence reads covering the same genomic region of an individual, by chance).…”

“…Microsatellite markers were initially designed in data from each sample using the pal_finder (Castoe et al, ) workflow of Griffiths et al (); a traditional design method using the data of a single individual. A novel quality control procedure was developed for those data sets in which multiple individuals of the same species were sequenced (two species) with the aim of identifying polymorphic loci, filtering out primer pairs containing point mutations within the priming regions, and avoiding other potential issues with a locus including nonspecific primer binding and insertion/deletion mutations in the flanking regions.…”

“…Primer pairs developed under either design method were tested in 5 µl reactions using the Type‐it Microsatellite PCR Kit (Qiagen) using the standard protocol and thermal cycling parameters (5 min at 95°C, 25–28*[30 s at 95°C, 90 s at 60°C, 30 s at 72°C], 30 min at 60°C). Only a single annealing temperature (60°C) was tested, as Primer3 (Koressaar & Remm, ; Untergasser et al, ) which is used during the traditional marker design process (Castoe et al, ; Griffiths et al, ), had been configured specifically for these PCR reagents and a primary goal of this method was to avoid time consuming annealing temperature optimisation. A marker was given successful amplification status if clean PCR products were clearly visible on a 2% agarose gel in the 100–1,000 bp range for six or more individuals out of eight tested.…”

“…Here, we develop microsatellite markers using MiMi in two species: the green sea urchin ( Psammechinus miliaris ) and the Eurasian blue tit ( Cyanistes caeruleus ). For comparison, we also present the success rates of microsatellite development in P. miliaris and C. caeruleus , and in two other species ( Tragelaphus eurycerus isaaci and Nycticebus pygmaeus) , which were designed using a traditional microsatellite design method (Castoe et al, ; Griffiths et al, ). The results from the successful development of each panel of markers, combined with our refined bioinformatics method, provide a strong case for the utility of the MiMi concept and the value to microsatellite marker development.…”