Final published version
Licence: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Multi-individual microsatellite identification
T2 - A multiple genome approach to microsatellite design (MiMi)
AU - Fox, G.
AU - Preziosi, R.F.
AU - Antwis, R.E.
AU - Benavides-Serrato, M.
AU - Combe, F.J.
AU - Harris, W.E.
AU - Hartley, I.R.
AU - Kitchener, A.C.
AU - de Kort, S.R.
AU - Nekaris, A.-I.
AU - Rowntree, J.K.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - 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).
AB - 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).
KW - cost‐effective marker development
KW - high‐throughput sequencing
KW - in silico quality control
KW - microsatellite design
KW - polymorphic loci detection
KW - short tandem repeat (STR)
U2 - 10.1111/1755-0998.13065
DO - 10.1111/1755-0998.13065
M3 - Journal article
VL - 19
SP - 1672
EP - 1680
JO - Molecular Ecology Resources
JF - Molecular Ecology Resources
SN - 1755-098X
IS - 6
ER -