Vartia Salla, Villanueva-Cañas José L, Finarelli John, Farrell Edward D, Collins Patrick C, Hughes Graham M, Carlsson Jeanette E L, Gauthier David T, McGinnity Philip, Cross Thomas F, FitzGerald Richard D, Mirimin Luca, Crispie Fiona, Cotter Paul D, Carlsson Jens
Area 52 Research Group, University College Dublin, Belfield, Dublin, Republic of Ireland; Earth Institute, University College Dublin, Belfield, Dublin, Republic of Ireland; Carna Research Station, Ryan Institute, National University of Ireland, Galway, Carna, Connemara, Republic of Ireland.
Evolutionary Genomics Group , Research Programme on Biomedical Informatics (GRIB) , Hospital del Mar Research Institute (IMIM), Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.
R Soc Open Sci. 2016 Jan 20;3(1):150565. doi: 10.1098/rsos.150565. eCollection 2016 Jan.
This study examines the potential of next-generation sequencing based 'genotyping-by-sequencing' (GBS) of microsatellite loci for rapid and cost-effective genotyping in large-scale population genetic studies. The recovery of individual genotypes from large sequence pools was achieved by PCR-incorporated combinatorial barcoding using universal primers. Three experimental conditions were employed to explore the possibility of using this approach with existing and novel multiplex marker panels and weighted amplicon mixture. The GBS approach was validated against microsatellite data generated by capillary electrophoresis. GBS allows access to the underlying nucleotide sequences that can reveal homoplasy, even in large datasets and facilitates cross laboratory transfer. GBS of microsatellites, using individual combinatorial barcoding, is potentially faster and cheaper than current microsatellite approaches and offers better and more data.
本研究探讨了基于下一代测序的微卫星位点“测序基因分型”（GBS）在大规模群体遗传学研究中进行快速且经济高效基因分型的潜力。通过使用通用引物的PCR结合组合条形码技术，从大型序列库中获得个体基因型。采用三种实验条件来探索将该方法与现有及新型多重标记面板和加权扩增子混合物结合使用的可能性。GBS方法针对毛细管电泳产生的微卫星数据进行了验证。GBS能够获取潜在的核苷酸序列，即使在大型数据集中也能揭示同塑性，并有助于跨实验室转移。使用个体组合条形码的微卫星GBS可能比当前的微卫星方法更快、更便宜，且能提供更好、更多的数据。
