A novel approach for mining polymorphic microsatellite markers in silico

Hoffman J, Nichols HJ (2011)
PLoS ONE 6(8): e23283.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
Volltext vorhanden für diesen Nachweis
Abstract / Bemerkung
Abstract: An important emerging application of high-throughput 454 sequencing is the isolation of molecular markers such as microsatellites from genomic DNA. However, few studies have developed microsatellites from cDNA despite the added potential for targeting candidate genes. Moreover, to develop microsatellites usually requires the evaluation of numerous primer pairs for polymorphism in the focal species. This can be time-consuming and wasteful, particularly for taxa with low genetic diversity where the majority of primers often yield monomorphic polymerase chain reaction (PCR) products. Transcriptome assemblies provide a convenient solution, functional annotation of transcripts allowing markers to be targeted towards candidate genes, while high sequence coverage in principle permits the assessment of variability in silico. Consequently, we evaluated fifty primer pairs designed to amplify microsatellites, primarily residing within transcripts related to immunity and growth, identified from an Antarctic fur seal (Arctocephalus gazella) transcriptome assembly. In silico visualization was used to classify each microsatellite as being either polymorphic or monomorphic and to quantify the number of distinct length variants, each taken to represent a different allele. The majority of loci (n = 36, 76.0%) yielded interpretable PCR products, 23 of which were polymorphic in a sample of 24 fur seal individuals. Loci that appeared variable in silico were significantly more likely to yield polymorphic PCR products, even after controlling for microsatellite length measured in silico. We also found a significant positive relationship between inferred and observed allele number. This study not only demonstrates the feasibility of generating modest panels of microsatellites targeted towards specific classes of gene, but also suggests that in silico microsatellite variability may provide a useful proxy for PCR product polymorphism.
Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.


Hoffman J, Nichols HJ. A novel approach for mining polymorphic microsatellite markers in silico. PLoS ONE. 2011;6(8):e23283.
Hoffman, J., & Nichols, H. J. (2011). A novel approach for mining polymorphic microsatellite markers in silico. PLoS ONE, 6(8), e23283. doi:10.1371/journal.pone.0023283
Hoffman, J., and Nichols, H. J. (2011). A novel approach for mining polymorphic microsatellite markers in silico. PLoS ONE 6, e23283.
Hoffman, J., & Nichols, H.J., 2011. A novel approach for mining polymorphic microsatellite markers in silico. PLoS ONE, 6(8), p e23283.
J. Hoffman and H.J. Nichols, “A novel approach for mining polymorphic microsatellite markers in silico”, PLoS ONE, vol. 6, 2011, pp. e23283.
Hoffman, J., Nichols, H.J.: A novel approach for mining polymorphic microsatellite markers in silico. PLoS ONE. 6, e23283 (2011).
Hoffman, Joseph, and Nichols, H. J. “A novel approach for mining polymorphic microsatellite markers in silico”. PLoS ONE 6.8 (2011): e23283.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Access Level
OA Open Access
Zuletzt Hochgeladen

19 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

High-throughput sequencing and graph-based cluster analysis facilitate microsatellite development from a highly complex genome.
Shah AB, Schielzeth H, Albersmeier A, Kalinowski J, Hoffman JI., Ecol Evol 6(16), 2016
PMID: 27547349
Genomic Methods Take the Plunge: Recent Advances in High-Throughput Sequencing of Marine Mammals.
Cammen KM, Andrews KR, Carroll EL, Foote AD, Humble E, Khudyakov JI, Louis M, McGowen MR, Olsen MT, Van Cise AM., J Hered 107(6), 2016
PMID: 27511190
Efficient development of highly polymorphic microsatellite markers based on polymorphic repeats in transcriptome sequences of multiple individuals.
Vukosavljev M, Esselink GD, van 't Westende WP, Cox P, Visser RG, Arens P, Smulders MJ., Mol Ecol Resour 15(1), 2015
PMID: 24893879
Microsatellites in Pursuit of Microbial Genome Evolution.
Saeed AF, Wang R, Wang S., Front Microbiol 6(), 2015
PMID: 26779133
Efficient development of highly polymorphic microsatellite markers based on polymorphic repeats in transcriptome sequences of multiple individuals
Vukosavljev M, Esselink GD, ’t Westende WPC, Cox P, Visser RGF, Arens P, Smulders MJM., Mol Ecol Resour 15(1), 2015
PMID: IND601379373
An empirical review: Characteristics of plant microsatellite markers that confer higher levels of genetic variation.
Merritt BJ, Culley TM, Avanesyan A, Stokes R, Brzyski J., Appl Plant Sci 3(8), 2015
PMID: 26312192
PSR: polymorphic SSR retrieval.
Cantarella C, D'Agostino N., BMC Res Notes 8(), 2015
PMID: 26428628
Identification of conserved and polymorphic STRs for personal genomes.
Chen CM, Sio CP, Lu YL, Chang HT, Hu CH, Pai TW., BMC Genomics 15 Suppl 10(), 2014
PMID: 25560225
A combined strategy involving Sanger and 454 pyrosequencing increases genomic resources to aid in the management of reproduction, disease control and genetic selection in the turbot (Scophthalmus maximus).
Ribas L, Pardo BG, Fernández C, Alvarez-Diós JA, Gómez-Tato A, Quiroga MI, Planas JV, Sitjà-Bobadilla A, Martínez P, Piferrer F., BMC Genomics 14(), 2013
PMID: 23497389
Efficient isolation of polymorphic microsatellites from high-throughput sequence data based on number of repeats.
Cardoso SD, Gonçalves D, Robalo JI, Almada VC, Canário AV, Oliveira RF., Mar Genomics 11(), 2013
PMID: 23665344
Microsatellite markers for the yam bean Pachyrhizus (Fabaceae).
Delêtre M, Soengas B, Utge J, Lambourdière J, Sørensen M., Appl Plant Sci 1(7), 2013
PMID: 25202568
Characterization of the heart transcriptome of the white shark (Carcharodon carcharias).
Richards VP, Suzuki H, Stanhope MJ, Shivji MS., BMC Genomics 14(), 2013
PMID: 24112713

64 References

Daten bereitgestellt von Europe PubMed Central.

The genome-wide determinants of human and chimpanzee microsatellite evolution.
Kelkar YD, Tyekucheva S, Chiaromonte F, Makova KD., Genome Res. 18(1), 2008
PMID: 18032720
Biased distribution of microsatellite motifs in the rice genome.
Grover A, Aishwarya V, Sharma PC., Mol. Genet. Genomics 277(5), 2007
PMID: 17237941
Genome sequencing in microfabricated high-density picolitre reactors.
Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, Dewell SB, Du L, Fierro JM, Gomes XV, Godwin BC, He W, Helgesen S, Ho CH, Ho CH, Irzyk GP, Jando SC, Alenquer ML, Jarvie TP, Jirage KB, Kim JB, Knight JR, Lanza JR, Leamon JH, Lefkowitz SM, Lei M, Li J, Lohman KL, Lu H, Makhijani VB, McDade KE, McKenna MP, Myers EW, Nickerson E, Nobile JR, Plant R, Puc BP, Ronan MT, Roth GT, Sarkis GJ, Simons JF, Simpson JW, Srinivasan M, Tartaro KR, Tomasz A, Vogt KA, Volkmer GA, Wang SH, Wang Y, Weiner MP, Yu P, Begley RF, Rothberg JM., Nature 437(7057), 2005
PMID: 16056220
Selection on MHC-linked microsatellite loci in sheep populations.
Santucci F, Ibrahim KM, Bruzzone A, Hewit GM., Heredity (Edinb) 99(3), 2007
PMID: 17519962
Signatures of natural selection in the human genome.
Bamshad M, Wooding SP., 2003
Mining microsatellites in eukaryotic genomes.
Sharma PC, Grover A, Kahl G., Trends Biotechnol. 25(11), 2007
PMID: 17945369
Detecting short tandem repeats from genome data: opening the software black box.
Merkel A, Gemmell N., Brief. Bioinformatics 9(5), 2008
PMID: 18621747
Microsatellite discovery by deep sequencing of enriched genomic libraries.
Santana Q, Coetzee M, Steenkamp E, Mlonyeni O, Hammond G, Wingfield M, Wingfield B., BioTechniques 46(3), 2009
PMID: 19317665
A panel of new microsatellite loci for genetic studies of Antarctic fur seals and other otariids.
Hoffman JI., 2009
Microsatellite null alleles and estimation of population differentiation.
Chapuis MP, Estoup A., Mol. Biol. Evol. 24(3), 2007
PMID: 17150975


Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®


PMID: 21853104
PubMed | Europe PMC

Suchen in

Google Scholar