Literature DB >> 27333119

megasat: automated inference of microsatellite genotypes from sequence data.

Luyao Zhan1, Ian G Paterson2, Bonnie A Fraser3, Beth Watson2, Ian R Bradbury4, Praveen Nadukkalam Ravindran1, David Reznick5, Robert G Beiko1, Paul Bentzen2.   

Abstract

megasat is software that enables genotyping of microsatellite loci using next-generation sequencing data. Microsatellites are amplified in large multiplexes, and then sequenced in pooled amplicons. megasat reads sequence files and automatically scores microsatellite genotypes. It uses fuzzy matches to allow for sequencing errors and applies decision rules to account for amplification artefacts, including nontarget amplification products, replication slippage during PCR (amplification stutter) and differential amplification of alleles. An important feature of megasat is the generation of histograms of the length-frequency distributions of amplification products for each locus and each individual. These histograms, analogous to electropherograms traditionally used to score microsatellite genotypes, enable rapid evaluation and editing of automatically scored genotypes. megasat is written in Perl, runs on Windows, Mac OS X and Linux systems, and includes a simple graphical user interface. We demonstrate megasat using data from guppy, Poecilia reticulata. We genotype 1024 guppies at 43 microsatellites per run on an Illumina MiSeq sequencer. We evaluated the accuracy of automatically called genotypes using two methods, based on pedigree and repeat genotyping data, and obtained estimates of mean genotyping error rates of 0.021 and 0.012. In both estimates, three loci accounted for a disproportionate fraction of genotyping errors; conversely, 26 loci were scored with 0-1 detected error (error rate ≤0.007). Our results show that with appropriate selection of loci, automated genotyping of microsatellite loci can be achieved with very high throughput, low genotyping error and very low genotyping costs.
© 2016 John Wiley & Sons Ltd.

Entities:  

Keywords:  animal mating/breeding systems; bioinformatics/phyloinformatics; captive populations; conservation genetics; landscape genetics; population genetics - empirical

Mesh:

Year:  2016        PMID: 27333119     DOI: 10.1111/1755-0998.12561

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  23 in total

1.  Development and characterization of polymorphic microsatellite markers in northern fulmar, Fulmarus glacialis (Procellariiformes), and cross-species amplification in eight other seabirds.

Authors:  Meg C Gravley; George K Sage; Andrew M Ramey; Scott A Hatch; Verena A Gill; Jolene R Rearick-Whitney; Aevar Petersen; Sandra L Talbot
Journal:  Genes Genomics       Date:  2019-05-27       Impact factor: 1.839

2.  New microsatellite markers for Ellipse, Venustaconcha ellipsiformis (Bivalvia: Unionidae), with notes on optimal sample size and cross-species amplification.

Authors:  Kentaro Inoue; Bernard E Sietman; Stephen E McMurray; J Scott Faiman; David T Zanatta
Journal:  Mol Biol Rep       Date:  2021-03-26       Impact factor: 2.316

3.  Next Gen Pop Gen: implementing a high-throughput approach to population genetics in boarfish (Capros aper).

Authors:  Edward D Farrell; Jeanette E L Carlsson; Jens Carlsson
Journal:  R Soc Open Sci       Date:  2016-12-14       Impact factor: 2.963

4.  Identifying the minimum number of microsatellite loci needed to assess population genetic structure: A case study in fly culturing.

Authors:  Wolfgang Arthofer; Carina Heussler; Patrick Krapf; Birgit C Schlick-Steiner; Florian M Steiner
Journal:  Fly (Austin)       Date:  2017-12-01       Impact factor: 2.160

5.  Genotyping-by-sequencing of genome-wide microsatellite loci reveals fine-scale harvest composition in a coastal Atlantic salmon fishery.

Authors:  Ian R Bradbury; Brendan F Wringe; Beth Watson; Ian Paterson; John Horne; Robert Beiko; Sarah J Lehnert; Marie Clément; Eric C Anderson; Nicholas W Jeffery; Steven Duffy; Emma Sylvester; Martha Robertson; Paul Bentzen
Journal:  Evol Appl       Date:  2018-03-11       Impact factor: 5.183

6.  SSR-seq: Genotyping of microsatellites using next-generation sequencing reveals higher level of polymorphism as compared to traditional fragment size scoring.

Authors:  Petra Šarhanová; Simon Pfanzelt; Ronny Brandt; Axel Himmelbach; Frank R Blattner
Journal:  Ecol Evol       Date:  2018-10-25       Impact factor: 2.912

7.  Genetic and genomic monitoring with minimally invasive sampling methods.

Authors:  Emma L Carroll; Mike W Bruford; J Andrew DeWoody; Gregoire Leroy; Alan Strand; Lisette Waits; Jinliang Wang
Journal:  Evol Appl       Date:  2018-03-24       Impact factor: 5.183

8.  De novo assembly and characterization of the Hucho taimen transcriptome.

Authors:  Guang-Xiang Tong; Wei Xu; Yong-Quan Zhang; Qing-Yu Zhang; Jia-Sheng Yin; You-Yi Kuang
Journal:  Ecol Evol       Date:  2017-12-21       Impact factor: 2.912

9.  Fast sequence-based microsatellite genotyping development workflow.

Authors:  Olivier Lepais; Emilie Chancerel; Christophe Boury; Franck Salin; Aurélie Manicki; Laura Taillebois; Cyril Dutech; Abdeldjalil Aissi; Cecile F E Bacles; Françoise Daverat; Sophie Launey; Erwan Guichoux
Journal:  PeerJ       Date:  2020-05-04       Impact factor: 2.984

10.  CHIIMP: An automated high-throughput microsatellite genotyping platform reveals greater allelic diversity in wild chimpanzees.

Authors:  Hannah J Barbian; Andrew Jesse Connell; Alexa N Avitto; Ronnie M Russell; Andrew G Smith; Madhurima S Gundlapally; Alexander L Shazad; Yingying Li; Frederic Bibollet-Ruche; Emily E Wroblewski; Deus Mjungu; Elizabeth V Lonsdorf; Fiona A Stewart; Alexander K Piel; Anne E Pusey; Paul M Sharp; Beatrice H Hahn
Journal:  Ecol Evol       Date:  2018-07-16       Impact factor: 2.912

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