Click
here to close Hello! We notice that
you are using Internet Explorer, which is not supported by Echinobase
and may cause the site to display incorrectly. We suggest using a
current version of Chrome,
FireFox,
or Safari.
Mol Ecol Resour
2019 Nov 01;196:1672-1680. doi: 10.1111/1755-0998.13065.
Show Gene links
Show Anatomy links
Multi-individual microsatellite identification: A multiple genome approach to microsatellite design (MiMi).
Fox G
,
Preziosi RF
,
Antwis RE
,
Benavides-Serrato M
,
Combe FJ
,
Harris WE
,
Hartley IR
,
Kitchener AC
,
de Kort SR
,
Nekaris AI
,
Rowntree JK
.
Abstract
Bespoke microsatellite marker panels are increasingly affordable and tractable to researchers and conservationists. The rate of microsatellite discovery is very high within a shotgun genomic data set, but extensive laboratory testing of markers is required for confirmation of amplification and polymorphism. By incorporating shotgun next-generation sequencing data sets from multiple individuals of the same species, we have developed a new method for the optimal design of microsatellite markers. This new tool allows us to increase the rate at which suitable candidate markers are selected by 58% in direct comparisons and facilitate an estimated 16% reduction in costs associated with producing a novel microsatellite panel. Our method enables the visualisation of each microsatellite locus in a multiple sequence alignment allowing several important quality checks to be made. Polymorphic loci can be identified and prioritised. Loci containing fragment-length-altering mutations in the flanking regions, which may invalidate assumptions regarding the model of evolution underlying variation at the microsatellite, can be avoided. Priming regions containing point mutations can be detected and avoided, helping to reduce sample-site-marker specificity arising from genetic isolation, and the likelihood of null alleles occurring. We demonstrate the utility of this new approach in two species: an echinoderm and a bird. Our method makes a valuable contribution towards minimising genotyping errors and reducing costs associated with developing a novel marker panel. The Python script to perform our method of multi-individual microsatellite identification (MiMi) is freely available from GitHub (https://github.com/graemefox/mimi).
Figure 1. Summary statistics showing the rate at which potential microsatellite markers were successfully amplified in the laboratory, and the rate at which they were discovered to be informative. Markers were designed using both methodologies in P. miliaris and C. caeruleus. Stated values are the average for each design method, in each measure of success (amplification rate and informative loci rate). Error bars show the standard deviations. The use of MiMi results in both an increase in the rate at which markers amplify and are informative, and also a reduction in the variability at each of these measures compared to the traditional workflow [Colour figure can be viewed at http://wileyonlinelibrary.com]
Figure 2. The MiMi tool was used to analyse 5,657 potential microsatellite loci discovered in P. miliaris sequence data and 4,513 discovered in C. caeruleus. Loci were filtered to just those which appeared in the sequence data of three or more individuals. The total number of loci which were successfully detected in multiple individuals, and in how many individuals they were detected is shown below. The bar labels are the absolute number of loci that were detected in each category (number of individuals)
Abdelkrim,
Fast, cost-effective development of species-specific microsatellite markers by genomic sequencing.
2009, Pubmed
Abdelkrim,
Fast, cost-effective development of species-specific microsatellite markers by genomic sequencing.
2009,
Pubmed
Abdul-Muneer,
Application of microsatellite markers in conservation genetics and fisheries management: recent advances in population structure analysis and conservation strategies.
2014,
Pubmed
Angers,
Complex evolution of a salmonid microsatellite locus and its consequences in inferring allelic divergence from size information.
1997,
Pubmed
Bashalkhanov,
A simple method for estimating genetic diversity in large populations from finite sample sizes.
2009,
Pubmed
Bhargava,
Mutational dynamics of microsatellites.
2010,
Pubmed
Blacket,
Universal primers for fluorescent labelling of PCR fragments--an efficient and cost-effective approach to genotyping by fluorescence.
2012,
Pubmed
Bouck,
Analysis of the quality and utility of random shotgun sequencing at low redundancies.
1998,
Pubmed
Castoe,
Correction: Rapid Microsatellite Identification from Illumina Paired-End Genomic Sequencing in Two Birds and a Snake.
2015,
Pubmed
Combe,
Rapid isolation and characterization of microsatellites in the critically endangered mountain bongo (Tragelaphus eurycerus isaaci).
2018,
Pubmed
Davey,
Genome-wide genetic marker discovery and genotyping using next-generation sequencing.
2011,
Pubmed
De Barba,
High-throughput microsatellite genotyping in ecology: improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA.
2017,
Pubmed
Dieringer,
Two distinct modes of microsatellite mutation processes: evidence from the complete genomic sequences of nine species.
2003,
Pubmed
Edgar,
MUSCLE: multiple sequence alignment with high accuracy and high throughput.
2004,
Pubmed
Ekblom,
A field guide to whole-genome sequencing, assembly and annotation.
2014,
Pubmed
Goldstein,
An evaluation of genetic distances for use with microsatellite loci.
1995,
Pubmed
Goldstein,
Launching microsatellites: a review of mutation processes and methods of phylogenetic interference.
1997,
Pubmed
Griffiths,
A Galaxy-based bioinformatics pipeline for optimised, streamlined microsatellite development from Illumina next-generation sequencing data.
2016,
Pubmed
Grimaldi,
Microsatellite allelic homoplasy due to variable flanking sequences.
1997,
Pubmed
Hale,
Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies.
2012,
Pubmed
Hosseinzadeh-Colagar,
Microsatellite (SSR) amplification by PCR usually led to polymorphic bands: Evidence which shows replication slippage occurs in extend or nascent DNA strands.
2016,
Pubmed
Koboldt,
The next-generation sequencing revolution and its impact on genomics.
2013,
Pubmed
Koressaar,
Enhancements and modifications of primer design program Primer3.
2007,
Pubmed
McPherson,
A defining decade in DNA sequencing.
2014,
Pubmed
Nichols,
In silico detection of polymorphic microsatellites in the endangered Isis tamarind, Alectryon ramiflorus (Sapindaceae).
2018,
Pubmed
Price,
Population genetics and the effects of a severe bottleneck in an ex situ population of critically endangered Hawaiian tree snails.
2014,
Pubmed
Ribout,
Fine-scale genetic structure in a high dispersal capacity raptor, the Montagu's harrier (Circus pygargus), revealed by a set of novel microsatellite loci.
2019,
Pubmed
Rico,
Null alleles are ubiquitous at microsatellite loci in the Wedge Clam (Donax trunculus).
2017,
Pubmed
Rose,
A threshold size for microsatellite expansion.
1998,
Pubmed
Shikano,
Utility of sequenced genomes for microsatellite marker development in non-model organisms: a case study of functionally important genes in nine-spined sticklebacks (Pungitius pungitius).
2010,
Pubmed
Shin,
CRISPR-Cas9-targeted fragmentation and selective sequencing enable massively parallel microsatellite analysis.
2017,
Pubmed
Silva,
Pitfalls in genetic testing: a case of a SNP in primer-annealing region leading to allele dropout in BRCA1.
2017,
Pubmed
Untergasser,
Primer3--new capabilities and interfaces.
2012,
Pubmed
Vieira,
Microsatellite markers: what they mean and why they are so useful.
2016,
Pubmed
Wang,
A maximum-likelihood method to correct for allelic dropout in microsatellite data with no replicate genotypes.
2012,
Pubmed
Zhan,
megasat: automated inference of microsatellite genotypes from sequence data.
2017,
Pubmed
